international scientific journal · morphological traits of amaranth ‘cv. koniz’ as influenced...

International ScientificJournal

VOL. 69_2016ISSN 2545-4315

INTERNATIONAL SCIENTIFIC JOURNALJOURNAL OF AGRICULTURAL, FOOD AND ENVIRONMENTAL SCIENCES

http://www.fznh.ukim.edu.mk/jafes/

The JAFES is an International scientific peerreviewed Open Access Journal published twice а yearlyJAFES On line (e-ISSN 2545-4315) offers free access to all articles at http://www.fznh.ukim.edu.mk/jafes/

Published by: “Ss. Cyril and Methodius" University in Skopje,

Faculty of Agricultural sciences and food-Skopje

Advisory board

EDITORIAL BOARD

Еditor in Chief

Vjekoslav Tanaskovikj, Skopje, MacedoniaKocho Porchu, Skopje, Macedonia

Associate Editor

Snezana Jovanovic, Belgrade, SerbiaJovica Vasin, Novi Sad, SerbiaRadmila Stikić, Belgrade, SerbiaBiljana Škrbić, Novi Sad, SerbiaAna Marjanovic Jeromel¸ Novi Sad, SerbiaBojan Srdljević, Novi Sad, SerbiaZoran Rajić, Belgrade, SerbiaJasmina Havranek, Zagreb, CroatiaMirjana Herak Ćustić, Zagreb, CroatiaVlasta Piližota, Osijek, CroatiaIvo Tursich, Zagreb, CroatiaDarko Vončina, Zagreb, CroatiaZlatan Sarić, Sarajevo, B&HJosip Ćolo, Sarajevo, B&HMuhamed Brka, Sarajevo, B&HVelibor Spalević, Podgorica, MontenegroBozidarka Marković, Podgorica, MontenegroNazim Gruda, Bonn, GermanyVenelin Roychev, Plovdiv, BulgariaNasya Tomlekova, Plovdiv, BulgariaIrena Rogelj, Ljubljana, SloveniaDrago Kompan, Ljubljana, SloveniaMichael Murković, Graz, AustriaHristaq Kume, Tirana, AlbaniaSonja Srbinovska, Skopje, MacedoniaMarjan Kiprijanovski, Skopje, MacedoniaMarina Stojanova, Skopje, MacedoniaBiljana Kuzmanovska, Skopje, MacedoniaMirjana Jankulovska, Skopje, MacedoniaDragi Dimitrievski, Skopje, Macedonia

JOURNAL OF AGRICULTURAL, FOOD AND ENVIRONMENTAL SCIENCESAddress

(Editorial Board)“Ss. Cyril and Methodius" University in Skopje

Faculty of Agricultural sciences and food-SkopjeP.O. Box 297, MK-1000 Skopje,

Republic of MacedoniaE-mail: [email protected]

Издава:Универзитет „Св. Кирил и Методиј“ во Скопје,Факултет за земјоделски науки и храна Скопје

Издавачки совет

УРЕДУВАЧКИ ОДБОР

Главен уредник

Вјекослав Танасковиќ, Скопје, МакедонијаКочо Порчу, Скопје, Македонија

Уредници

Снежана Јованович, Белград, СрбијаЈовица Васин, Нови Сад, СрбијаРадмила Стикич, Белград, СрбијаБилјана Шкрбич, Нови Сад, СрбијаАна Марјанович Јеромел, Нови Сад, СрбијаБојан Срдљевич, Нови Сад, СрбијаЗоран Рајич, Белград, СрбијаЈасмина Хавранек, Загреб, ХрватскаМирјана ХеракЧустич, Загреб, ХрватскаИво Туршич, Осијек, ХрватскаВласта Пилижота, Загреб, ХрватскаДарко Вончина, Загреб, ХрватскаЗлатан Сарич, Сарајево, БиХЈосип Чоло, Сарајево, БиХМухамед Брка, Сарајево, БиХВелибор Спалевич, Подгорица, Црна ГораБожидарка Маркович, Подгорица, Црна ГораНазим Груда, Бон, ГерманијаВенелин Ројчев, Пловдив, БугаријаНасиа Томлекова, Пловдив, БугаријаИрена Рогељ, Љубљана, СловенијаДраго Компан, Љубљана, СловенијаМихаел Муркович, Грац, АвстријаХристаќ Куме, Тирана, АлбаниаСоња Србиновска, Скопје, МакедонијаМарјан Кипријановски, Скопје, МакедонијаМарина Стојанова, Скопје, МакедонијаБилјана Кузмановска, Скопје, МакедонијаМирјана Јанкуловска, Скопје, МакедонијаДраги Димитриевски, Скопје, Македонија

Адреса(Редакција)Универзитет „Св. Кирил и Методиј“ во СкопјеФакултет за земјоделски науки и храна Скопјеп. фах. 297, МК1000 Скопје,Република Македонија

*THE AUTHORS ARE RESPONSIBLE FOR THE CONTENT AND FOR THE LANGUAGE OF THEIR CONTRIBUTION

Journal of Agricultural, Food and Environmental Sciences

____________________________________________________________________________________________________

JAFES, Vol 69 (2016)

TABLE OF CONTENTS

B. Popovski, M. Popovska CHEMICAL CONTENT OF FRUITS OF SOME PERSPECTIVE STRAWBERRY VARIETIES CULTIVATED ON OPEN FIELD 1-7 L. Lepaja, E. Kullaj, K. Lepaja, N. Krasniqi INFLUENCE OF RDI, MULCHING AND THEIR COMBINATIONS ON NUTRIENT CONTENT OF YOUNG "WILLIAM" PEAR STORED IN BASEMENT 8-13 M. Popovska, B. Popovski MORPHOMETRIC CHARACTERISTICS ON SELECTED CHERRY PLANTS, A PRIMARY EFFECT PRODUCT OF GAMMA RADIATION (Cz137) 14-20 V. Avdiu, F. Thomaj, S. Sylanaj, E. Kullaj, K. Lepaja EFFECT OF GROW REGULATORS ON THE STOMATA CONDUCTANCE IN THE APPLE TREE 21-25 A. Markovski, T. Arsov, V. Gjamovski ROOTING OF HAZELNUT (CORYLUS AVELLANA L.) VARIETIES HARDWOOD CUTTINGS 26-31 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj SOIL EROSION EVALUATION IN THE RASTOCKI POTOK WATERSHED OF MONTENEGRO USING THE EROSION POTENTIAL METHOD 32-40 G. Patamanska WATER RESOURCES PLANNING MODELING FOR EFFICIENT MANAGEMENT OF IRRIGATION CANAL 41-45 C. Berar, M. Silivasan, E. Pet, A. Groszler, C. Tota, D. Camen THE MANAGEMENT AND CAPITALIZATION OF THE LANDSCAPING POTENTIAL OF THE CRUCII SQUARE FROM TIMISOARA CITY 46-52 H. Knüpffer PLANT GENETIC RESOURCES FROM THE BALKAN PENINSULA IN THE WORLD’S GENEBANKS 53-68


____________________________________________________________________________________________________

JAFES, Vol 69 (2016)

H. Kirchev, N. Semkova INVESTIGATION ON SOME MORPHOLOGICAL AND BIOLOGICAL CHARACTERISTICS OF EINKORN WHEAT (T. MONOCOCCUM L.) DEPENDING ON NITROGEN FERTILIZATION 69-74 Doneva S., Yordanova D., Daskalova N., Spetsov P. POLYMORPHISM OF ENDOSPERM PROTEINS IN AMPHIDIPLOIDS WITH THE G GENOME OF Triticum timopheevii (Zhuk.) 75-80 M. T. Stojanova, L. Karakashova, H. Poposka, I. Ivanovski, B. Knezevic THE INFLUENCE OF FOLIAR FERTILIZATION WITH ORGANIC FERTILIZERS ON THE YIELD AND THE CHEMICAL CONTENT OF POTATOES GROWN IN STRUMICA REGION 81-86 M. Yarnia, M. B. K.Benam, E. Farajzadeh, V. Ahmadzadeh, N. Nobari THE EVALUATION OF GRAIN AND OIL PRODUCTION, SOME PHYSIOLOGICAL AND MORPHOLOGICAL TRAITS OF AMARANTH ‘CV. KONIZ’ AS INFLUENCED BY THE SALT STRESS IN HYDROPONIC CONDITIONS 87-93 N. Mrkovački, D. Bjelić, D. Jošić, I. Đalović YIELD RESPONSE OF FIVE MAIZE HYBRIDS TO INOCULATION WITH RHIZOBACTERIA 94-97 D. Cvetkovic, D. Boshev, Z. Dimov, S. Ivanovska, M. Jankulovska YIELD AND YIELD COMPONENTS ON SOME WHEAT VARIETIES GROWN IN ALEKSINAC REGION 98-105


UDC 634.75:581.19(497.7)

Original scientific paper

____________________________________________________________________________________________________

CHEMICAL CONTENT OF FRUITS OF SOME PERSPECTIVE STRAWBERRY

VARIETIES CULTIVATED ON OPEN FIELD

B. Popovski1*, M. Popovska2

1Faculty of Agricultural Sciences and Food, Ss. Cyril and Methodius University,

Skopje, Republic of Macedonia 2Institute of Agriculturae, Ss. Cyril and Methodius University, Skopje, Republic of Macedonia

*corresponding author: [email protected]

Abstract

This research contains results concerning the chemical composition of 15 introduced varieties of

strawberries in Macedonia: Idea, Camarosa, Belrubi, Evita, Honeoye, Tethis, Chandler, Onda,

Miranda, Paros, Elsanta, Eris, Madalene, Favette and Marmolada and two controll varieties:

Pocahontas and Sengasengana. The analysis has been conducted on the following substances: soluble

dry matter, sugars (total and reductive), acids, pulp’s pH, sugar/acid ratio, vitamin C, anthocyanins

and mineral matters. The percentage of soluble dry matter is between 8.5% with the Eris variety and

11% with Idea. Idea has the highest concentration of sugars with 8.80% of total and 6.16% of

reductive sugars. Eris has the lowest concentration of 6.80% total and 4.76% reductive sugars. Lowest

amount of acids is 0.79% (Onda and Madalene) and highest is 0.94% (Evita). The range of pH value

goes from 3.5 (Tethis) to 4.2 (Chandler and Pocahontas). The Marmolada variety has the highest

sugar/acid ratio with 10.4 and Evita has the lowest of 8.1. The concentration of vitamin C goes

between the range of 72.49mg% (Pocahontas) and 113.73mg% (Camarosa). The anthocyanins

concentration with the Favette is to be the lowest with 37.06mg/kg, whereas the Elsanta reaches the

highest content with 48.88mg/kg. The content of mineral matter within the fruit is between 0.52%

(Chandler and Onda) and 0.94% (Tethis).

Key words: Fragariaananassa Duch., strawberry, variety, chemical content, open field.

Introduction

The strawberry plant fruit poses an attractive

fruit which is rich in important and essential

nutricious matter (Wozniak et al., 1997). The

fruit is composed of a wide variety of organic

and mineral substances responsible for its high

nutritional, medicinal, and dietary value

(Stančević, Stanisavljević 1986;Gavrilović,

1986;Благојевиќ, 1998). The chemical

composition points towards a real employable,

alimentary, and technological value of the

strawberries (Поповски, 2008).

The main nutritional substances within the

fruit are soluble dry matters, sugars (glucose,

fructose, and sucrose) as well as organic acids

which account for the refreshing flavour

strawberries are known for. The increased

number of sugary components results in a less

notable citrusy flavor. Strawberries are a

known source of various numbers of other

chemical substances with protective anti-

oxydant characteristics, such as vitamins and

couloured matter, vitamin C and antocyanins

in particular. (Mratinić-Nenadović, 1989,2003,

2006; Milivojević, 2003).

The chemical composition of the strawberry

fruit varies greatly within the mass of varieties.

Afore all, its composition depends on the

variety, degree of ripeness of the fruit, the

fecundity, the growth system, applied agro-

technical and protective measures for during

the produce period, climate factors and the

like.(Kiprijanovski, 2001; Milivojević, 2003;

Popovski, 2008).

The aim of this study is a firm analysis of the

chemical composition of the fruit of 17

different varieties of strawberries laid with a

modern technology under a polyethylenefoil in

an open field. The growing of strawberries out

on an open field has been a dominant trend

within the Skopje region and has been widely

adopted within the entire region of the

Republic of Macedonia.

2 B. Popovski, M. Popovska

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Materials and methods

The analysis was performed in an

experimental orchard of the Agricultural

Institute in Skopje during 2002–2004. The

experiment was established in the second half

of September 2001, with a frigo virus-free

planting material, in three repetitions in a line,

consisting of 30 plants of each repetition. The

cultivation system was an open field, in two-

row lines (long plots method), on black

polyethylene foil at distance of 40x30 cm. The

plants were irrigated with controlled quantities

of water, through the drop-by-drop system.

The soil was homogeneous, alluvial,

possessing a good water-air regime, suitable

for strawberry growing. The agrochemical

composition of the soil consisted of 0.93-

2.05% hummus, 9.32-10.38mg/100g N, 14.3-

21.1mg/100g P2O5, 10.06-22.2 mg/100g K2O,

6.49-7.25% CaCO3, pH 7.93-8.19 in H2O and

7.4-7.63 in KCl. Based on the analyses, the

soil has been ameliorative fertilized with

mineral fertilizer and organic fertilizer from

California worms. According to data for

meteorological parameters from the

Hydrometeorological Office Petrovec, the

climate of the Skopje Region featured warm

dry muggy summer and foggy cold winters.

Тhe chemical content was observed on

15introduction strawberry varieties: Idea,

Camarosa, Belrubi, Evita, Honeoye, Tethis,

Onda, Chandler, Miranda, Paros, Elsanta, Eris,

Madlen, Favette and Marmolada, and two

standard varieties: Senga Sengana and

Pocahontas. The analysis has been conducted

on the following substances: soluble dry

matter, sugars (total and reductive), acids,

pulp’s pH, sugar/acid ratio, vitamin C,

anthocyanins and mineral matters.

The composition of soluble dry matters is

determined with a Carl Zeiss™ binocular

refractometer, the sugars (total and reductive)

are determined by liquid chromatography,

whereas the total acids are differentiated by

means odd titration with 0.1 N/10 NaOH and

indicated as malic acid. The Tilman’s method

was employed to extract the values of Vitamin

C by means of titration with 2,6

dichlorophenol–indophenol, while the

antocyanins (mg/kg) have been determined

spectrophotometrically, where the pH has been

established by a PHmeter, and the content of

mineral matters through a 550 0C heat

exposure. The elication index was reached

through a relation between the total sugars

content and the total number of acids.

Analyses of variance were performed for

statistical analysis of the results. The results

were processed using LSD-test to prove the

statistical significance of the differences

between the varieties, with significance levels

of 0.05 and 0.01.Coefficient of variation

(CV%)of investigated characteristics is also

analysed.

Results and discussion

The percentage of solvable dry matters within

the tested varieties circles round a broad frame

of 8.5%with Eris and 11.0% with Idea with the

average content amounting to 10.0% (Table

1).In comparison to Pocahontas;Idea,

Marmolada, S. Sengana, Favetteand Paros

show a greater number of soluble dry matters,

while only Idea and Marmolada are richer in

content that S. Sengana. Some statistically

highly significant differences between dry

matters content within the varieties have been

established between the Ideaand Belrubi,

Tethis, Honeoye, Evita, Chandler, Onda,

Camarosaand the Eris variety. Another set of

differences have also been established between

Marmolada, S. Sengana, Favette, Paros,

Pocahontas, Miranda, Elsanta, Madlen,

Belrubiand Tethiswith Honeoye, Evita,

Chandler, Onda, Camarosaand Eris.

The great variation between the varieties exists

in terms of composition of sugars. The greatest

content in total and reductive sugars has been

established with Idea (7.17 and 5.02%

respectively), whereas the lowest with Eris

(6.80and 4.76). The average for all the

varieties amounts to 7.97% in total and 5.58%

in reductive sugars.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Table 1. Chemical content of strawberry fruits

The S. Senganaand Pocahontasstandards are

high in almost the equal amount of sugars with

only the Idea variety showing higher values

than them.The greatest and statistically most

significant differences are there in the relation

between Ideaand Belrubi, Tethis, Honeoye,

Evita, Chandler, Onda, Camarosaand Erisas

well as Marmolada, S. Sengana, Favette,

Parosand Pocahontasand Evita, Chandler,

Onda, Camarosaand Eris, between Mirandaand

Elsantawith Onda, Camarosaand Eris, between

Elsanta, Madlenand Belrubiwith Camarosaand

Eris.

The total content of acids is 0.85% on average

and moves from 0.79% with Ondaand Madlen

to 0.94% withEvita. Belrubi, Idea, Miranda,

Tethis, Chandler, Favette и Evita show greater

values in total acids than S. Sengana, while

Pocahontas is characterized by lower values

than all of the aforementioned with the

Honeoye variety added to the list.The Evita

variety has statistically highly significant

content of total acids from all of the 15 tested

varieties. A significant difference does not

show only with the Favette variety. The

differences between Favette and Chandler are

similar, showing a highly significant higher

values of total acids with 13 tested varieties.

The difference with S. Senganais significant in

relation to theEris variety and highly

significant with Paros, Marmolada, Camarosa,

Ondaand Madlen. The differences between

Pocahontasand Camarosa, Ondaand Madlen

are highly significant.

The pulp acidity revolves around the figures of

3.5 (Tethis), and 4.2 (Chandler, Onda and

Pocahontas). The average for all of the

varieties is 3.9. Eris, Evita, Onda,

Pocahontasand Chandler show greater рН

values than S. Sengana.The ChandlerandP

ocahontas varieties show statistically higher

pH than S. Sengana, Parosand Elsantaand a

significantly higher value than the 9 varieties.

No differences have been established only

with Eris, Evitaand Onda. Statistically

significant differences of the S.

Senganavariety have been noted with the

Camarosa, Honeoyeand Favette varieties and

highly significant with Madlenand Tethis.

TheTethis variety, which is characterized by

the lowest pH value, shows statistically highly

significant differences of its values in relation

to 11 varieties. This varietis shows no relations

only with the Camarosa, Honeoye, Favette,

Madlenand Tethis varieties.

No. Variety

Soluble

dry

matters, %

Sugars Total

acids, %

Pu-lp’s

pH

Sugar/ acid

ratio

Vitamin

C, mg%

Antho-cyanins,

mg/kg Mineral

matters, %

Total Redu-ctive

1 Idea 11,0 8,80 6,16 0,87 3,9 10,2 100,46 40,94 0,88

2 Camarosa 9,0 7,17 5,02 0,80 3,7 9,0 113,73 38,94 0,84

3 Belrubi 9,9 7,89 5,53 0,86 3,8 9,2 82,01 45,20 0,77

4 Evita 9,4 7,55 5,28 0,94 4,1 8,1 87,58 43,11 0,87

5 Honeoye 9,6 7,68 5,38 0,85 3,7 9,0 101,88 40,06 0,90

6 Tethis 9,8 7,84 5,49 0,89 3,5 8,8 103,64 47,28 0,94

7 Chandler 9,3 7,41 5,19 0,91 4,2 8,2 86,60 38,06 0,52

8 Onda 9,2 7,33 5,13 0,79 4,2 9,3 77,20 39,07 0,52

9 Pocahontas 10,4 8,35 5,84 0,84 4,2 9,9 72,49 47,21 0,61

10 S.Sengana 10,6 8,51 5,95 0,86 4,0 9,9 75,03 47,96 0,72

11 Miranda 10,3 8,27 5,79 0,89 3,8 9,4 75,67 47,90 0,80

12 Paros 10,6 8,48 5,94 0,82 4,0 10,4 86,79 43,11 0,90

13 Elsanta 10,3 8,24 5,77 0,84 3,9 9,9 98,81 48,88 0,69

14 Eris 8,5 6,80 4,76 0,83 4,1 8,2 75,51 47,90 0,61

15 Madlen 10,3 8,21 5,75 0,79 3,6 10,4 89,32 41,06 0,69

16 Favette 10,6 8,51 5,95 0,92 3,7 9,3 82,91 37,06 0,66

17 Marmolada 10,7 8,53 5,97 0,82 3,9 10,4 89,72 47,21 0,70

Average 10,0 7,97 5,58 0,85 3,9 9,4 87,90 43,58 0,74

CV% 5,01 5,01 5,01 1,87 3,59 5,52 4,12 2,56 7,31

LSD0,05 0,83 0,66 0,47 0,03 0,23 0,86 6,03 1,86 0,09

LSD0,01 1,12 0,89 0,63 0,04 0,31 1,16 8,11 2,49 0,12


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Paros, Madlen и Marmolada show for the

greatest elication index(10.4), whereas Evita

the lowest(8.1). The average for all of the

varieties amounts to 9.4. The controls’ values

prove to be within the range of the average and

higher with a higher index established with the

Marmolada, Madlen, Parosand Idea varieties.

The Marmolada, Madlenand Parosvarieties

show statistically significant differences in

terms of mid values odd the elication index

with Miranda, Favetteand Ondaand highly

significant differences with Belrubi, Honeoye,

Camarosa, Tethis, Eris, Chandler and Evita.

The Pocahontas, S. Sengana and Elsanta

standards, are varietie showing statistically

significant differences within the mid values of

the elication index withHoneoye,

CamarosaandTethisand highly significant

differences with Eris, Chandlerand Evita.

Evitashows the lowest elication index and no

significant differences have been establish

apart from with Chandler, Erisand theTethis

variety.

During the process of establishing the

chemical composition of a fruit’s flesh, the

values of Vitamin C are of the utmost

significance as fruits rich in Vitamin C are of a

greater interest to anyone. The lowest in

Vitamin C values are theS. Sengana (87.90

mg%) and Pocahontas(72.49 mg%) varieties

whereas the highest figures are appointed to

Camarosa(113.73mg%). The Camarosa variety

shows a statistically highly significant

difference in relation to all the other 16

varieties under analysis. Other highly

significant differences are there between

Tethis, Honeoye, Ideaand Elsantawith 12

varieties (Marmolada, Madlen, Evita, Paros,

Chandler, Favette, Belrubi, Onda, Miranda,

Eris, S. Senganaand Pocahontas). S. Sengana и

Pocahontas show significant and highly

significant lower values for Vitamin C to all

the varieties with the exception of Onda,

MirandaandEris.

The alluring red color of the fruit is owed to

the antocyanins. The antocyanins and Vitamin

C are a vital source of anti-oxidants. The

Favette variety is the lowest in anthocyanin’s

(37.06mg/kg), and Elsantashows the highest

concentration of anthocyanin’s (48.88mg/kg).

The average amounts to43.58mg/kg.S.

Senganais characterized with a rather large

concentration of antocyanins

(47.96mg/kg)with only Elsantashowing a

greater content of antocyanins.

Pocahontastakes up as the sixth richest in

antocyanins. With Elsanta, S. Sengana,

Miranda, ErisandTethis filling in the spots

from first to fifth place, respectively.The

greatest statistically significant differences are

there between Elsanta, S. Sengana, Miranda,

Eris, Tethis, Pocahontasand Marmolada with

Belrubi, Evita, Paros, Madlen, Idea, Honeoye,

Onda, Camarosa, Chandler and Favette.

Favette shows for the lowest values of

antocyanins and has no established differences

apart from those with the Chandler and

Camarosa varieties. .

The mineral matters within a fruit if the

strawberry varies from 0.52% (Onda) to 0.94%

(Tethis) with the average being 0.74%. S.

Senganawith 0.72%, takes the ninth place

whereas Pocahontaswith 0.61% is at the

fifteeth place.Higher values thanS. Senganaare

noticed with Tethis, Paros, Honeoye, Idea,

Evita, Camarosa, MirandaandBelrubi, and

lower values than Pocahontashave been

establish only with Chandler и

Onda.Tethisshows no statistically significant

differences whereas Paros, Honeoye, Idea и

Evita. Paros, Honeoye, Ideaand Evitaare

notices to have a higher concentration of

mineral matters than Belrubi, S. Sengana,

Marmolada, Elsanta, Madlen, Favette, Eris,

Pocahontas, Chandlerand Onda.TheS.

Senganastandard is noted to have significant

differences with Erisand Pocahontas, and

highly significant differences with

Chandlerand Onda. Statistically,

Pocahontasshows significantly higher values

than Chandler and Onda.

According to the data on coefficients of

variation, the characteristics under analysis

vary only in the slightest percentage (Table 1).

The lowest variation coefficient has been

established with the total acid content

(CV%=1.87), whereas the highest with the

content of mineral matters (CV=7.31%).

The acquired results on the soluble dry matters

are similar to those of the analyses conducted

by Mratinić- Nenadović (1989) where the

author claims that the content between

varieties varies from од 8.5to 14.2%.

Stanisavljević et al. (1997), noted a

composition of soluble dry matters from

6.15to 9.50 %, Wozniak et al., (1997), from

9.46 to 9.57%, while Stančević, Stanisavljević

(1986) and Stanisavljevićet al.(1996) from

9.,5%, i.e.from6.3% дo 10.1%. According to

Nenadović - Mratinićet al.(2003, 2006)the


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

soluble dry matters content varies from 7.92 to

9.41%. Mratinić (1989) has established

content of soluble dry matters with the S.

Senganaraised in outdoor conditions with

figure varying from 8.50 to 14.25 %. For

Milivojević (2003), this variety showed

numbers of 9.70%, while Blagojević (1999)a

nalysed at 10.01%. In order to provide a

proper choice of industrial strawberries with a

high percentage of soluble dry matters fit to

dry, Vittenet al. (2008), have established

contents with 97 genotypes which ranged

between 7.5%and 18.5%.

Кипријановски (2001) in the Skopje region

analyses 8.1% dry matters with the

Pocahontas variety. Gavrilović (1986)with

theBelrubivariety notes 9.50% in dry matters.

The content of soluble dry matters withElsanta

(10.3%) and Marmolada (10.7%) are higher

than those reached by Milivojević (2003)in the

Belgrade region, of 8.30% i.e. 8.56%.

Wozniak et al. (1997), note a reductive sugars

content of 5.5 to 5.8% and an amount of total

sugars of 6.35% to 6.70 %. The values of

Vitamin C range between 59% and

99.4%mg/kg. Growing strawberries in

conditions of a drier and warmer climate is

always accompanied by a larger content in

sugars.

The average content of total acids, mineral

matters and antocyanins are a match with the

date acquired by Благојевиќ (1998) while the

content of total sugars (7.97%) and

antocyanins (43.58 mg/kg) is higher in

contract to his research. The author notes an

average content of total acids from 0.38% to

0,84 %, a total sugars contents within the

limits of 3.87%and 7.10% and antocyaninsof

31,79 mg/kg. The also notes an antocyanins

content with the Belrubi (34.63 mg/kg) and S.

Sengana (36.11mg/kg) varieties.

Stanisavljevićet al.(1996), state the average

values of total acids to be ranging from од

0.64%to 1.00%, while th рН values moves

from3.30 to 3.72.

Our results on the chemical composition of the

Marmolada variety are significantly higher

than those reached by Milivojević (2003). The

author has established a content of 5,.68% in

total and 4.48% in reductive sugars, 0.66%

total acids, 51.08mg% Vitamin С and 0.26%

of mineral matters.

According toWozniak et al. (1997), Elsantahas

6.70%in sugars and an elication index of

7.32.Voća et al. (2006), note a Vitamin С

content оf 58.32 mg% in anon-soiled

supstratum to 68.58 mg%in high tunnels,

within the Zagreb region. The fruit’s рН

values amounted to 3.70 onto an open fieldto

3.91 in a non-soiled substratum. Milivojević

(2003), on the other hand, shows figures for

this variety starting from5.52in totaland 4.

43% in reductive sugars, 0.71%in total acids,

13.,18 mg%of Vitamin Cand 0.24% of mineral

matters. Our results concerning the Elsanta

variety, show higher values in terms of the

chemical composition covering all the

parameters in contrast to the analysis by

Milivojević (2003), an equal content of

Vitamin С and рНvalues of the pulp which

concerns a non-soiled substratum Voća et al.

(2006) and elocation index higher than the one

reached byWozniak et al. (1997).

The acquired data on the chemical

composition the S. Senganavariety are higher

in contrast to all the parameters established by

Milivojević (2003)– 7.35in total and 6.11%in

reductive sugars, 0.84% in total acids, 11.61

mg%of Vitamin С and 0.34 % in mineral

matters, and those byБлагојевиќ (1998)– 6.61

in total and 4.41% in reductive sugars, 0.80%

in total acids, 2.87 pulp pHand 8.26 elication

index.

Mratinić-Nenadović (1989), had been

analyzing the chemical composition of the

fruit with the S. Senganavariety both out and

indoors and figures of 8.50% to 14.25% in

soluble dry matter, 6.35%to 4.56% in total

sugars, and 0.37%to 0.87% in total acids were

established with the plants raised outdoors.

The chemical composition of the plants raised

indoors shows for higher values over the same

parameters (soluble dry matters from 7.80to

15.60%, total sugars from 4.25 to 8.46%

andtotal acids from 0.62 to 0.97%).

During the analysis of the chemical

composition of Honeoye, Wozniak et al.

(1997) presented slightly lower values that

those we have in terms of total sugars (6.78%)

and total acids (0.71%).

Results on the total acids content (0.84%) and

Vitamin С (72,49mg%) with the Pocahontas

variety are higher in contrast to those reached

by Kiprijanovski (2001) who established

0.67% in toatal acids and 47,5 mg%in Vitamin

C.

Nenadović - Mratinićet al. (2003)conducted an

analysis over 7 varieties of strawberries with a

different planting distance among which were

the Favette, Evita, Erisand Madlen varieties.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

The total sugars ranges between 6.31% and

8.00 %, inverterted sugars from 5.53% to 6.34

%, total mineral matters of 0.21%to 0.28 %

and Vitamin Cfrom 14.0 to 18.5 mg%. From

these figures a conclusion has been drawn that

a greater distance planting (30х30and

40х40cm) has a positive effect in raising the

values of the tested chemical characteristics.

The data acquired on the chemical

composition in soluble dry matters, total

sugars, Vitamin C and mineral matters with

the FavetteandMadlen varieties, are higher

than those reached byNenadović - Mratinićet

al.(2006) concerning the same varieties and

are insignificantly lower in the values of total

acids and reductive sugars. WithNenadović -

Mratinićet al.(2006), Favette contains 7.92%

soluble dry matter, 6.30% total sugars,

6.0%reductive sugars, 0.90% total acids, 18.8

mg%Vitamin С and 0.21% mineral matters.

Madlen contains 9.90% soluble dry matters,

7.81% total sugars, 5.86% reductive sugars,

0.96% total acids, 15.2mg%Vitamin С and

0.27% mineral matters.

The results reached in terms of soluble dry

matters, total and reductive sugars, and total

acids with the Evita and Eris varieties are

lower that thoe reached in the research of

Nenadović - Mratinićet al.(2006), over the

same varieties, however are significantly

higher in terms of Vitamin C and mineral

matters. According to Nenadović - Mratinićet

al.(2006), Evita contains 10.05% soluble dry

matters, 8.80% total sugars, 6.60% reductive

sugars, 0.98% total acids, 16.2 mg% Vitamin

С and 0.30% mineral matters. Eriscontains

9.30 % soluble dry matters, 8.14% total

sugars, 6.96% reductive sugars, 0.68% total

acids, 14.70 mg% Vitamin С and 0.28%

mineral matters.

Conclusions

With all the analyzed varieties a high content

of the tested values within the chemical

composition has been established.

The average content of soluble dry matters

amounts to 10.0%, and varies from 8.5 (Eris)

to 11.0% (Idea). The total and reductive sugars

within the fruit of the plant range between 6.8

and 4.76% (Eris) and 8.80% and 6,16% (Idea),

while the average amount to 7.97% and 5.58%

respectivelly.The total acid concentration

varies from0.79% (OndaandMadlen)to 0.94%

Evitaor 0.85%. A pulp рН has been

established between 3.5 (Tethis) to 4.2

(Chandler, Onda и Pocahontas) or a 3.9 pH on

average. The average elication index for all the

varieties amounts to 9.4.with Evita(8.1) with

the lower,and the Paros, Madlen and

Marmolada varieties with the highest

index(10.4).The tested varieties of strawberries

are characterized by a high content of Vitamin

C which ranges somewhere between 72.49

(Pocahontas) and 113.73 mg% (Camarosa)

with an average of 87.90mg%.The strawberry

poses a high source of antocyanins with the

average being 43.58mg/kgand a variation of

the figures between37.06 (Favette) and

48.88mg/kg (Elsanta).The mineral matters

within the fruit show for numbers between

0.52(Chandler и Onda)and 0.94 % (Tethis)

with an average value amounting to 0.74% for

all the analysedvarieties .

Out of all the tested caharcteristics the lowest

variation coefficient has been noted with the

content of total acids (CV%=1.87) whereas the

highest variation coefficient has been noted

with the content of mineral matters

(CV=7.31%).All of the analysed

characteristics show only a slight variation.

References

1. Благојевиќ Р. (1998). Проучување на

биолошките и технолошки особини кај

поважните сорти јагоди. Докторска

дисертација, Универзитет “Св. Кирил и

Методиј”-Скопје, Земјоделски факултет,

Скопје.

2. Blagojević R. (1999).

Biološkekarakteristikenekihsortijagoda u

uslovimaNiša.Jugoslovenskovoćarstvo, 33,

125-126:17-25.

3. Vitten M. D., Tiedke F., Olbricht K.

(2008). Dry Matter In Fragaria Fruit: A

New Breeding Goal. VI International

Strawberry Symposium, Spain.Spisanie,

Vol, pp

4. Voća Sandra, Duralija B., DružićJasmina,

SkendrovićBabojelić Martina,

DobrevićNadica, Čmelik Z. (2006).

Influence of Cultivation System on

Physical and Chemical Composition of

Strawberry Fruits cv. Elsanta.Agriculturae

Conspectus Scientificus, Vol. 71, No.4,

171-174.

5. GavrilovićJelica. 1986.

Uticajlokalitetanakvalitetploda u

nekihsortijagoda. Jugoslovenskovoćarstvo

20, 75-76, 689-692, Čačak.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

6. Кипријановски М. (2001) Влијание на

начинот на одгледување на јагодите врз

вегетативниот прираст и приносот.

Докторска дисертација, Универзитет

“Св. Кирил и Методиј”-Скопје,

Земјоделски факултет, Скопје.

7. MilivojevićJasminka. (2003).

Uticajvelićinehranidbenogprostoranabiološ

keosobinesortijagode

(FragariaananassaDuch.).

Magistarskateza.Univerzitet u Beogradu,

Pojloprivrednifakultet, Beograd.

8. Mratinić-NenadovićEvica.(1989).

Uticajsredinegajenjanavodnirežim,

prinosikvalitetplodovajagode.

Jugoslovenskivoćarstvo, 23, 87-88: 565-

570, Čačak.

9. Nenadović – MratinićEvica,

MilivojevićJasminka, Đurović D. (2003).

Pomološke osobine novointrodukovanih

sorti jagode.Zborniknaučnihradovasa XVII

savetovanja agronoma, veterinara I

tehnologa, Vol. 9. br.1, Beograd.

10. Nenadović – Mratinić Evica, Milivojević

Jasminka, Đurović D. (2006).Uticaj

rastojanja sadnjena kvalitet ploda

novointrodukovanih sorti jagode.

Voćarstvo.Vol. 40.br.154, 2, 123-132,

Čačak.

11. Поповски, Б. (2008). Биолошки и

производни карактеристики на некои

перспективни сорти јагоди. Докторска

дисертација, Универзитет “Св. Кирил и

Методиј”-Скопје, Факултет за

земјоделски науки и храна, Скопје.

12. Stanisavljević M., Gavrilović-Damjanović

J., Mitrović O. (1996). Važnijebiološko-

privredneosobinenovijihsortijagode.Jugoslo

venskovoćarstvo, Vol. 30, Br. 115-116:

385-390, Čačak.

13. Stanisavljević M., Srečković M., Mitrović

M. (1997). Field performance of some

foreign strawberry cultivars grown in

Yugoslavia.Proc.Third international

Strawberry Symposium, Acta

Horticulturae, 439, vol 1, ISHS.

14. Stančević A., Stanisavljević M. (1986).

Biološko-tehnološke karakteristike elitnih

hibridajagode. Jugoslovenski voćarstvo, 20,

77-78: 65-69, Čačak.

15. Wozniak W., Radajewska B., Ciszewski I.

(1997). Influence of different cultivation

factors under protection on physico-

chemical features of strawberry fruits of

“Elsanta” and “Kent”. Proc.ThirdIct.

Strawberry Symp.,Acta Hort. 439 Vol. 2:

549-552.

16. Wozniak W., Radajewska B., Reszelska-

Sieciechowicz A., Dejwor I. (1997). Sugar

and acid content influence organoleptic

evaluation of fruit of six strawberry

cultivars from controlled cultivation.

Proc.ThirdIct. Strawberry Symp.,Acta Hort.

439 Vol. 1: 333-336.


UDC 634.13-167(497.115)


____________________________________________________________________________________________________

INFLUENCE OF RDI, MULCHING AND THEIR COMBINATIONS ON NUTRIENT

CONTENT OF YOUNG "WILLIAM" PEAR STORED IN BASEMENT

L. Lepaja1, E. Kullaj1, K. Lepaja1, N. Krasniqi2

1Agriculture University of Tirana, Koder-Kamez, Tirana, Albania

2University of Prishtina, Faculty of Agriculture and Veterinary, Kosovo


Abstract

The aim of this research was to determine the content of macro- and micro-elements in pear fruits

stored in basement after the application of regulated deficit irrigation (RDI) combined with mulching.

Using a water budged methodology, four levels of irrigation, specifically 100% of ET (control) and

deficits of 80%, 60% and 40%, were applied to 10 trees, 5 of which were mulched by a 10 cm layer.

The experiment was conducted in Kosovo (Dukagjini Plain) during 2013 on a pear orchard of 10 ha

on third year using a nested experimental design. Using ANOVA two-way with post hoc testing we

found significant changes in a series of nutrient elements. Irrigation levels significantly influenced

pH, acids, brix, carbohydrates, dry matter, organic matter, ash, Ca and Na, while mulch has influenced

brix, dry matter, pH, Cu, P, Fe, Mg and Na. The combination of irrigation and mulching have

influenced pH, acids, brix, carbohydrates, dry matter, organic matter, proteins and Na while changes

were not significant for fat, K, Pb and Zn. Young age of trees especially first year of production and

long-term plant responses to RDI are more accurate than short-term responses so experiment is

continuing.

Key words: water stress, Pyruscommunis, wood chips, nutrient elements, basement

Introduction

Production of pear considered

(Pyruscommunis) that is of particular

importance for the economy of Kosovo. Until

now about 600 ha are planted with pear.

Regulated deficit irrigation (RDI) was

developed to improve control of vegetative

vigour in high-density orchards in order to

optimize fruit size, fruitfulness and fruit

quality. RDI is usually applied during the

period of slow fruit growth when shoot growth

is rapid. However, it can also be applied after

harvest in early-maturing varieties.

Furthermore, RDI can generate considerable

water savings. Thus, it is useful for reducing

excessive vegetative vigour, and also for

minimizing irrigation and nutrient loss through

leaching RDI is an ideal water saving

technique. Its application and adaptation in

various environments have led to improved

understanding of the process, the benefits, and

the requirements for adoption (Goodwin and

Boland, 2002).

RDI consists of applying water in quantities

below those necessary to satisfy ETc during

certain periods of the crop cycle when

production and crop quality are hardly

affected, and in the application of all the water

needed during the rest of the cycle, especially

at critical periods of the cycle when the yield

and/or quality would be most affected by a

lack of water. RDI is normally applied during

stages of the cycle when reproductive growth

is relatively slow and when vegetative growth

and other plant processes may be affected,

9 L. Lepaja, E. Kullaj, K. Lepaja, N. Krasniqi

__________________________________________________________________________________

JAFES, Vol 69, (2016)

such effects frequently being translated into

improved fruit quality (Sanchez et al., 2010).

Fruit quantity and quality is directly connected

with optimum soil moisture. In other words,

irrigation plays a crucial role in achieving high

yields and quality besides other measures like

agricultural and pomological techniques.

Through their root system plants receive

nutrients dissolved in water thus reduction of

water absorbed by the roots reduces mineral

uptake. Drip irrigation, used also in our

experiment is the most effective irrigation

system and its application in fruit tree

production is spreading around the world after

its first discovery in Israel. The uniform

distribution of water for each tree cannot be

achieved with other types of irrigation. In

addition, other advantages of this way of

irrigation are: application in different terrains,

uniform soil wetting, prevention of crust

formation, free access for people and

machinery after every irrigation event,

avoidance of soil compression, prevention of

erosion, possibility for the use of fertigation,

etc. (Lepajaet al., 2015).

Today, irrigation is the largest single consumer

on the planet. Competition for water from

other sectors will force irrigation to operate

under water scarcity. Deficit irrigation, by

reducing irrigation water use, can aid in

coping with situations where supply is

restricted (Fereres and Soriano, 2007).

Responses of Asian pear (PyrusserotinaRehd.

'Nijisseiki') to water stress were studied by

(Behboudian and Lawes, 1994) and they gave

information that fruit concentration of N, P, K,

Ca and Mg decreased during the early stress

period. Water stress did not affect the

concentration of N, P, K, and Mg in fruit, but

tended to reduce Ca in early stressed fruit. The

latter had a higher concentration of sucrose,

glucose, fructose, and sorbitol than

nonstressed fruit after 35 days treatment.

Pliakoni and Nano, 2010 studied the effects of

deficit water and mulch in quality and storage

of peach fruit have found that peaches from

reflective mulched trees had the most

advanced maturity fruit at harvest compared to

the other treatments, and higher quality fruit

but also lower storage ability than control

fruit. In short, fruit quality of both cultivars

studied was improved due to deficit irrigation

or reflective mulching but their storage ability

was reduced from these treatments.

The objective of this study was to determine

the impact of RDI in combination with

mulching on quality parameters after fruits

stored in basement where water resources are

limited, and pear tress are in water stress.


To determine the content of macro- and micro-

elements in pear fruits after the application of

regulated deficit irrigation (RDI) combined

with mulching, stored in basement were used

in a commercial pear orchard. Ten ha orchard

of pears was planted on April 2011 in Kosovo

(Dukagjini Plain). The experimental set up

was a nested or hierarchical design whereby

the categories of nested factor within each

level of the main factor are different, i.e.

different trees give rise to the leaf/fruit

samples within each of the main irrigation

treatment. Trees were belonging to cv.

‘Williams’ on BA29 rootstock, on third year

respectively on first year of production. Pear

orchard was in under antihail system. Four

levels of irrigation were applied during the

season, 100% of evapotranspiration (ET) as

control (1.6 liters of water/h per drip) and

water deficit in 80% of full ET (1.28 liters of

water/h per drip) 60% of full ET (0.96 liters of

water/h per drip) and 40% (0.64 liters of

water/h per drip). Drip distance in the lateral

pipe was 0.60 m. First irrigation was applied

on May 22, 2013, while the last irrigation was

applied on September 20, 2013. A total of 19

irrigations (one irrigation per two hours) were

applied. Each treatment (each level of

irrigation) has been in a row. For each

treatment we used 10 trees, 5 of which were

mulched with a 10 cm thick layer of wood

chips totalling 40 trees for the entire

experiment. Mulching material was placed in a

row of a width of 0.60 m on May 21, 2013.

Planting distances were 3.5 m between the


__________________________________________________________________________________

JAFES, Vol 69, (2016)

rows and 1.3 m in the row. After harvesting on

September 6, 2013 for each trees two fruits

were stored in basement in temperature 12 °C,

for 21 days, then the same fruits were sent to

the laboratory where the following quality

indicators were analysed: pH, Brix, dry matter,

organic matter, acids, proteins, fats,

carbohydrates, Ca, K, Cu, Pb, Fe, Na, Mg, Zn,

P and ash.

Our state has a moderate continental climate

with a coastal impact which penetrates through

the valley of the Driniibardhë moderating

markedly continental climate elements (Lepaja

et al., 2014; 2015). In Kosovo average

temperature multiyear (1951-1980) is 10.3 °C,

that of vegetation 16.5 °C, the coldest month is

January (-0.9 °C) while the hottest month is

July with 20.1 °C. Regarding the annual

rainfall is 744.8 mm, and during vegetation is

346.7 mm which shows the need to intervene

with supplementary irrigation (Zajmi, 1996).

Water shortages in the territory of Kosovo,

especially during the vegetation period, need

supplemental irrigation.

The amount of rainfalls for Peja region for a

30 - year period are 907.4 mm and 352.5 mm

during the growing season. Rainfalls during

the period of the study were much lower

compared to the average 30 - year period with

a total of 571.7 mm and 309.8 mm during the

growing period. The first irrigation was

applied at the end of May when temperatures

started to raise and there were no rainfalls. The

average temperature and the temperature

during the growing period was 1°C higher

compared to the 30 - year average. Data from

the measurements were analysed using

ANOVA two–way with post hoc testing.

Result and discussion

Early cultivars need less water than late

cultivars. In Kosovo, at the beginning of the

vegetative period trees have enough moisture

supplied by the heavy spring rainfalls, as well

as water reserves accumulated in the soil

during winter from snow. This has happened

for centuries, but with global warming it also

can change, as it is increasingly witnessed in

many countries with dry winters in one side, or

spring floods on the other.

At the end of the treatment period (100%

irrigation as control, deficit of 80%, 60 and

40%),normal irrigation, two laterals, side

laterals, without irrigation), of RDI

application, we found changes in a series of

macro- and micro elements, after fruit stored

in basement and then were sent to the

laboratory.

Table 1, 2, 3 summarises the results of the

application of RDI in combination with

mulching on quality parameters of William

pears, after fruits stored in basement, with

differences between treatments according LSD

testing. Using ANOVA we found significant

changes in a series of nutrient elements.

Irrigation levels significantly influenced pH,

acids, brix, carbohydrates, dry matter, organic

matter, ash, Ca and Na, while mulch has

influenced brix, dry matter, pH, Cu, P, Fe, Mg

and Na. The combination of irrigation and

mulching have influenced pH, acids, brix,

carbohydrates, dry matter, organic matter,

proteins and Na while changes were not

significant for fat, K, Pb and Zn (table 3).

As seen in Table 1, to 7 elements (pH, brix,

dry matter, organic matter, acids, proteins and

carbohydrates) the highest values were

reaching in 100% irrigation, followed by 80%,

60% and lastly 40%. Higher values are

reached without mulch treatments, but the

same elements that have been made at the time

of harvest after applying the RDI, treatments

with mulch had higher value.

Unlike the elements of table 1 those in table 2.

(ash, Ca, Fe, Cu, Na, Mg and P) higher values

are reached with mulch treatments. The

highest values were found in 80% irrigation,

followed by 100%, while 60% and 40%

irrigation have had approximate value.


__________________________________________________________________________________

JAFES, Vol 69, (2016)

Table.1. Average values of the parameters tested in fruits at harvest with differences between treatments

according LSD testing

Elements pH Brix Dry

matter

Org.

matter Acids Proteins

Carbohy

drates

Irrigation

100 %

Mulch + a 3.88 a 15.44 a 17.65 a 17.27 a 0.28 a 0.24 a 16.48

Mulch - 4.02 a 16.00a 18.06 a 17.52 a 0.24 a 0.32 a 16.61 a

Irrigation

80 %

Mulch + b 3.64 b 14.66 b 16.24 b 16.10 b 0.40 b 0.42 b 15.15

Mulch - 3.76 b 15.03b 16.77 b 16.35 b 0.38 b 0.24 b 15.62 b

Irrigation

60 %

Mulch + c 3.77 b 14.29 b 15.99 c 15.57 c 0.22 c 0.33 c 14.78

Mulch - 3.69 c 13.77c 15.66 c 15.19 c 0.33 c 0.27 b 14.28 c

Irrigation

40 %

Mulch + c 3.52 c 12.50 c 14.28 d 13.74 c 0.23 a 0.22 d 13.09

Mulch - 3.75 c 13.88c 15.44 c 14.92 d 0.26 a 0.37 c 14.08 c

Table.2. Average values of the parameters tested in fruits at harvest with differences between treatments

according LSD testing

Elements Ash Calcium

(Ca)

Cooper

(Cu)

Sodium

(Na)

Magnesium

(Mg)

Phosphorus

(P)

Irrigation

100 %

Mulch + a 0.33 a 10.00 a 0.42 a 3.60 a 9.97 a 5.83

Mulch - 0.32 a 13.33 a 0.09 a 3.10 a 8.57 a 4.67 a

Irrigation

80 %

Mulch + a 0.32 b 16.33 b 0.23 a 3.77 a 9.73 a 7.80

Mulch - 0.28 b 13.66 a 0.14 a 3.20 a 8.63 a 3.20 a

Irrigation

60 %

Mulch + b 0.23 a 10.00 c 0.08 a 3.57 a 9.63 a 8.50

Mulch - 0.27 b 12.33 a 0.08 a 4.30 b 8.00 a 4.80 a

Irrigation

40 %

Mulch + b 0.25 c 12.67 d 0.20 a 3.93 b 8.40 b 3.53

Mulch - 0.27 b 15.33 b 0.11 a 3.03 a 7.90 a 5.10 a

*In table 1 and 2. letters on the left in each column represent differences for mulch +, while on the right

represent differences for mulch- (without mulch).

In Table 3 are presented the elements, which

in based ANOVA variance analysis are not

found significant differences (K, Zn, Pb and

fat), but even here the highest values are

reached in without mulch treatments.

Table.3. Average values of the parameters tested in fruits at harvest in which there were no differences between

treatments

Elements Fat Iron

(Fe)

Potassium

(K)

Zinc

(Zn)

Lead

(Pb)

Irrigation

100 %

Mulch + 0.21 0.56 101.66 0.28 0.008

Mulch - 0.25 0.45 111.66 0.32 0.010

Irrigation

80 %

Mulch + 0.20 0.56 102.00 0.32 0.010

Mulch - 0.20 0.48 106.00 0.36 0.008

Irrigation

60 %

Mulch + 0.22 0.55 98.66 0.31 0.004

Mulch - 0.24 0.49 93.66 0.30 0.011

Irrigation

40 %

Mulch + 0.18 0.55 94.00 0.33 0.006

Mulch - 0.19 0.47 97.00 0.25 0.011

These results can be obtained primarily as a

result of weather conditions: temperature and

rainfall during the time the experiment,

furthermore long-term effects of deficit

irrigation, together with climatic conditions,

crop techniques variations, type of soil, age of

plants etc. must be considered, because the

long-term plant responses to RDI or PRD are

more accurate than short-term responses

(Lepajaet al., 2015).


__________________________________________________________________________________

JAFES, Vol 69, (2016)

Conclusions

High nutritional values of pear fruit make this

crop highly demanded all around the world.

Different cultivars have different nutrient

values. However, changes in these values

depend also on a number of factors such as

climate, cultural practices, rootstocks,

irrigation etc.

In experiments in open field where irrigation is

applied, respectively deficit irrigation, RDI or

PRD, crucial factors in the results of the

research are the climatic conditions of that

region but on the other side the results of the

first year of the experiment, are only

preliminary results and for sustainable results

the experiment it must continue for many

years. Pear culture is very demanding on the

market throughout the year, as long

preservation of fruit without losing their

quality is an advantage.

The use of the four different levels of

irrigation (100%, 80%, 60% and 40%)

combination with mulch on Williams pear is a

new thinks (innovation), so each result

increases our understanding of the effects of

regulated water deficit practices, respectively

RDI practices. Based on our investigations on

the optimal deficit irrigation regime under the

agro ecological conditions of Kosovo and

Dukagjini Plain in particular, under an

intensive pear growing technology we can

deduct that harvesting of fruits for storage cv.

‘Williams’ is to be done earlier to the

beginning of August so that the fruits can be

stored longer although preserving fruits can be

affected by temperature. We found significant

changes in a series of nutrient elements.

Irrigation levels significantly influenced pH,

acids, brix, carbohydrates, dry matter, organic

matter, ash, Ca and Na, while mulch has

influenced brix, dry matter, pH, Cu, P, Fe, Mg

and Na. The combination of irrigation and

mulching have influenced pH, acids, brix,

carbohydrates, dry matter, organic matter,

proteins and Na while changes were not

significant for fat, K, Pb and Zn.

As the experiment is continuing, in the next

years we expect an attenuation of the RDI

effects in combination with mulching.

References

1. Behboudian, M. and Lawes S. 1994. Fruit

quality in ‘Nijisseiki’ Asian pear under

deficit irrigation: Physical attributes, sugar

and mineral content, and development of

flesh spot decay. New Zeland Journal of

crop and horticultural science. 22:4, 393-

400.

2. Caspari, H. 1993. The effects of water

deficits on the water balance and water

relations of Asian pear trees

(PyrusserotinaRend., cv. Hosui) growing in

lysimeters. Unpublished PhD thesis,

University of Bonn.

3. Caspari, H., Behboudian, M., Chalmers, D.,

Clotheir, B. and Lenz, Fritz. 1996. Fruit

Characteristics of ‘Hosui’ Asian Pears after

Deficit Irrigation. HortScience 31(1):162.

4. Fereres, E. and Soriano Maria Auxiliadora.

2007. Deficit irrigation for reducing

agricultural water use. Journal of

Experimental Botany. Vol. 58, No. 2, pp.

147-159.

5. Goodwin, I. and Boland AM. 2002.

Scheduling deficit irrigation of fruit trees

for optimizing water use efficiency. Deficit

Irrigation Practices. Water Reports

Publication n. 22, FAO, Rome., 67-79.

6. Griffiths, K.M., M.H. Behboudian, and M.

Dingle. 1992. Irrigation management and

fruit quality in Asian pear. HortScience

27:627. (Abstr.).

7. Lepaja, L., Kullaj, E., Lepaja, K., Shehaj,

M. and Zajmi, A. 2014.Fruit quality

parameters of five pear cultivars in western

Kosovo.J. International Scientific. Vol.

2:245-250.

8. Lepaja, K., Lepaja, L., Kullaj, E., Krasniqi,

N. and Shehaj, M. 2015. Effect of partial

rootzone drying (PRD) on fruit quality and

nutrient contents of ‘Albion’

strawberry.50th Croatian and 10th

International Symposium on

Agriculture.600-604.


__________________________________________________________________________________

JAFES, Vol 69, (2016)

9. Lepaja, L., Kullaj, E., Lepaja, K. and

Zajmi, A.2015.Effect of regulated deficit

irrigation, mulching and their combination

on fruit diameter growth of young

‘William’ pears.50th Croatian and 10th

International Symposium on

Agriculture.580-584.

10. Pliakoni, E.D. and Nanos, G.D. 2010.

Deficit irrigation and reflective mulch

effects on peach and nectarine fruit quality

and storage ability. Acta Hort. (ISHS)

877:215-222.

11. Sanchez, M.C., Domingo, R. and Castel

J.R. 2010.Deficit irrigation in fruit trees

and vines in Spain.Instituto Nacional de

Investigacion y TecnologiaAgraria y

Alimentaria (INIA).Spanish Journal of

Agriculture Research. 8(S2), S5-S20.

12. Zajmi, A. 1996.The opportunities of

utilizing the natural and biological

potentials, in the agriculture productivity in

Kosovo. Pp. 201-220. In: A scientific

conference: A MultidisiplinaryAproach of

Developing Possibilities of Kosova.

ASHAK.Prishtinë.


UDC 634.23:539.166


____________________________________________________________________________________________________

MORPHOMETRIC CHARACTERISTICS ON SELECTED CHERRY PLANTS, A

PRIMARY EFFECT PRODUCT OF GAMMA RADIATION (Cz137)

M. Popovska1*, B. Popovski2

1University ,,Ss. Cyril and Methodius“Institute of Agriculture – Skopje, Macedonia

2University ,,Ss. Cyril and Methodius“Faculty of Agricultural Sciences and Food – Skopje,

Macedonia


Abstract

A study has been conducted on the rootstock cross area, trunk cross area and total growth with 195

selected plants, a primary effect product from Bigareau Burlat, Pobeda Krimska and Kozerska cherry

varieties, during the first MV1 generation after the gamma radiation with Cz137. Graft branches were

exposed to dosages of 25Gy, 35Gy and 45Gy at the Institute of Radiobiology and Radiopreservation

in Sofia. The graft was taken during dormant buds onto a Prunus mahaleb rootstock. The average

values of all study parameters with the selected plants are 10 to 50% smaller in comparison with the

controls (plants not treated with radiation). The highest reduction of total plant growth is noticed at

Kozerska variety. The average value is 40% smaller in contrast to the control. The average values for

this characteristic provide statistical significant differences for all radiation dosages with the selected

plants in contrast to the control. The highest difference was noticed with the dosage of 25 Gy, where

the total growth is 50% smaller than the control. A very high positive correlation is determent

between the rootstock and trunk cross area, as well as between the rootstock and trunk cross area and

with the total growth in all of the tested varieties. Negative correlation between the radiation dosage

and the total growth is detected for Pobeda Krimska and Kozerska. This kind of correlation is not

present in Bigareau Burlat.

Key words: Prunus avium L., gamma radiation, dosage, rootstock and trunk cross area, total growth.

Introduction

The radiation treatment with gamma rays is

applied with the sole purpose of enhancing the

frequency of the natural variability, shortening

the process of selection, and enriching the

gene-fund with new initial material for

creating new gene- types (Popovska and

Popovski, 2012). The efficiency of the

ionization with the fruit species depends on the

type and intensity of the radiation, radio-

sensitivity of the variety, the part of the plant

that is exposed to the radiation, the units

stadium of development, the cells’

physiological condition and their dynamism at

the moment of treatment, the climate, the

temperatures during the winter period above

all, etc. (Kolesnikova, 1970; Ravkin, 1973;

Milenkov, 1974; Lapins, 1983; Donini et al.,

1991).

Appearance of the modification changes at

fruit plants after radiation treatment with

gamma rays, can be used as a diagnostic

measure for somatic mutations (Nybom, 1961;

Bishop,1967; Равкин, 1973; Миленков,1974;

Donini, 1975, Lapins,1983). All of the

changes are primary effect result of serious

damage of the apical meristem of the leaf

buds, as well as the secondary effect of the

physiological disbalance which emerges in the

affected cells (Guncle and Sparrow, 1961).

The authors mention that the regeneration area

of the affected cells emerges in the primary

brunches with an atypical position of the buds,

significantly fattened nodal regions, and an

atypical brunch color, presence of furcations

and fasciations and atypical leaves.

The changes which the radiation exposure

causes over the DNA molecule, directly slows

down its synthesis, as well as that of the RNA,

proteins, ATR and the cell’s mitosis (Gunchel

and Sparrow, 1961; Borojević, 1976; Pearson

mailto:[email protected]

15 M. Popovska, B. Popovski

__________________________________________________________________________________

JAFES, Vol 69, (2016

et al., 1975; Mišić, 1999).The occurrence of

shortened internodes leads to a decreased

growth in the plants and poses one of the most

substantial modification changes which are a

result to the radiation treatment (Ravkin 1973,

Milenkov, 1974).

The aim of this paper is to analyze some

morphometric characteristics of selected

prospective cherry plants, as a primary effect

product from radioactive treatment of three

cherry varieties with three different dosages of

Cz137, and to compare them with the controls

(plants not treated with radiation). The

selected plants present a promising starting

material for further selection and creation of

new varieties or cherry rootstocks.


Dormant buds from Bigareau Burlat, Pobeda

Krimska and Kozerska cherry varieties were

treatedwith radioactive Cz137 in doses of 25Gy,

35Gy and 45Gy. Graft branches were exposed

to radiation at the Institute of Radiobiology

and Radiopreservation in Sofia. Prunus

mahaleb L. was used as a rootstock for

grafting the buds, right after the treatment (30th

of August 2000 and 2001). Untreated buds

from each variety were used as a control

variant. Each variant was grafted onto two

hundred rootstocks.

An early diagnosis of the primary effects of

the radiation was made in the first MV1

generation following the treatment. Basic

criteria for first choice was made according to

the appearance of plants with the following

four characteristics: decreased vigorousness

and irregularly positioned leaf buds, presence

of furcations (bi-, three- and polyfurcations),

atypical leaves (shape, size, color, edginess,

deficiency of chlorophyll etc.) and expressive

outspread of the plants (Popovska et al.,2011).

A study has been conducted on the rootstock

cross area, trunk cross area and total growth

with 195 selected plants, a primary effect

product from radiation in the first year after

the treatment of dormant buds. The measures

were made in autumn, after falling of the

leaves. The obtained experimental results were

processed using t-test to prove the statistical

significance of the differences between the

controls and variants at levels of significance

0.05, 0.01 and 0.001 (Најчевска, 2002). The

correlation between the different traits is

established with a correlation analysis,

determining the strength of the connection

through a correlation coefficient, according to

Snedecor (1959) (Најчевска, 2002).

The research was performed at the

experimental field in the Institute of

Agriculture in Skopje. The soil type is silt -

clay loam, suitable for cherry production, with

moderate alkaline pH according to its reaction

in water and neutral according to its reaction

in KCl, very carbonate, with a low amount of

humus, with a good amount of hydrolyzing

nitrogen and optimal amount of easily

obtainable phosphorous and potassium. The

trial was watered with a drop irrigation

system.


According to the basic criteria for early

diagnostic of the effects of treatment with

radioactive Cz137, 195 or 46,9% of the total

number of plants received after the treatment,

have been selected in MV1 generation

(Popovska et al.,2011). The decreased

vigorousness of the selected plants has the

most participation of 29,3% from all present

primary effects, followed by furcations (23%),

then plants with atypical leaves (6,1) and then

with expressive outspread (4,3%) (Popovska et

al., 2011).Respective to the variety,88 plants

are selected from Bigareau Burlat, 54plants

from Pobeda Krimska and 53 are from

Kozerska . Related to the dosage, 83 are

selected from radiation of 25Gy, 58 from

35Gy and 54 from 45Gy (Popovska еt al.

,2011).

The data about the tested morphometric

parameters are presented in Tables 1-3 and

Figures 1-3. The control Bigareau Burlat has

the lowest values for the three tested traits,

compared to the controls of the other varieties,

while Pobeda Krimska has the highest values

for rootstock cross area. Kozerska has the

highest values for trunk cross area and total

growth.

Almost all of the average values for the three

tested traits among the selected material are

lower than the control values, from 10 to 50%,

depending on the variety and the dosage. This

is expected, because the trait lower growth is

the most determined among the selected

material. Exception is established for the

variety Bigareau Burlat for the dosage of 35

Gy, where the values for rootstock cross area

and total growth are higher for 10-20%


__________________________________________________________________________________


compared to the control. The reason for this

result is found to be in the highest number of

plants with expressive outspread selected from

this variety.

The average rootstock cross area is 339.9 mm2

(Table 1). The smallest deviation from the

control value is determined at Bigareau Burlat,

which represents 10%. The differences

between the tested variants and the control are

statistically insignificant. Higher

dissimilarities are established for the varieties

Pobeda Krimska and Kozerska. For the both

varieties the total average is 40% smaller than

the control value and the difference is

statistically important at the level of

significance of 0.01. Statistically significant

differences are established among all of the

variants, but the highest differences and very

statistically significant are for the average

values of the 45 Gy dosages. Analyzing the

tested dosages, significantly smaller rootstock

cross area is determined for the dosages of 25

and 45 Gy. Overall, the rootstock cross area

from the whole selected material is lower for

30% and the difference is statistically

significant at the level of significance of 0.01.

The average trunk cross area of the selected

plants is 214.9 mm2, which is 30% smaller

than the control values (Table 2). Because the

rootstock and the graft branches are directly

connected, they influence each other’s growth.

A very strong positive correlation is

determined between the rootstock cross area

and the trunk cross area. The correlation

coefficient for Bigareau Burlat is 0.896 and is

statistically significant at the level of

significance of 0.05, according to Snedecor

(1959). For the varieties Pobeda Krimska and

Kozarskaa complete positive correlation is

established between the two traits. The

correlation coefficients are 0.969 and 0.961

accordingly and are statistically significant at

the level of significance of 0.01.

Table.1. Rootstock cross area of selected plants

Again, the smallest deviation from the control

value is determined for Bigareau Burlat, which

represents 10% and the differences between

the tested variants and the control are

statistically insignificant. The highest

difference is observed for the variety Pobeda

Krimska. The average value is 40% smaller

than the control value, which represents

statistically significant difference. The value is

the smallest for the 45 Gy dosages and the

plants have 50% smaller trunk cross area than

the control and the differences are statistically

highly significant. The smallest trunk crosses

area for the variety Kozerska is established for

the plants treated with 45 Gy dosages. The

trunks have 40% smaller cross area and the

Variety Dose Rootstock cross

area (mm2) Index T

CV

%

Bigareau

Burlat

Control 441.0 ± 35.4 1.0 31,5

25Gy 350.0 ± 49.5 0.8 1.495 60,2

35Gy 440.8 ± 72.9 1.0 0.002 57,9

45Gy 383.9 ± 78.1 0.9 0.666 68,0

25-45 391.6 ± 66.8 0.9 0.654 62,0

Pobeda

Krimska

Control 575.4 ± 51.3 1.0 32,6

25Gy 372.8 ± 42.6** 0.6 3.040 44,4

35Gy 364.1 ± 72.7* 0.6 2.684 65,9

45Gy 261.3 ± 52.8*** 0.5 5.491 67,0

25-45 332.7 ± 46.8** 0.6 3.493 59,1

Kozerska

Control 534.1 ± 48.9 1.0 34,8

25Gy 326.8 ± 55.2* 0.6 2.813 41,1

35Gy 326.2 ± 71.4 * 0.6 2.403 54,3

45Gy 232.9 ± 26.3*** 0.6 5.425 37,8

25-45 295.3 ±` 50.9** 0.6 3.382 44,4

Average of controls 516.8 ± 45.2 1.0 32,9

Average 25 Gy 349.9 ± 49.1* 0.7 2.503 48,6

Average 35 Gy 377.0 ± 63.0 0.7 1.796 59,3

Average 45 Gy 292.7 ± 43.2*** 0.6 3.584 57,6

Average 25- 45 Gy 339.9 ± 55.2** 0.7 2.490 55,2


__________________________________________________________________________________


difference from the control value is

statistically highly significant. The average

value is 220 mm2, which is 30% smaller than

the control. Analyzing the tested dosages,

statistically significant smaller trunk cross area

is determined for the 45 Gy dosage.

Table.2. Trunk cross area of selected plants

Variety Dose Trunk cross area

(mm2) Index t

CV %

Bigareau

Burlat

Control 285.4 ± 22.8 1.0 36,0

25Gy 216.8 ± 41.0 0.8 1.462 80,3

35Gy 324.1 ± 49.5 1.1 0.712 73,5

45Gy 211.2 ± 62.7 0.7 1.112 88,8

25-45 250.7 ± 51.1 0.9 0.620 80,8

Pobeda

Krimska

Control 286.5 ± 36.6 1.0 47,5

25Gy 172,0 ± 28.7* 0.6 2.465 52,8

35Gy 203.7 ± 57.7 0.7 1.212 89,6

45Gy 146,4 ± 25.3** 0.5 3.152 67,0

25-45 174,0 ± 37.2* 0.6 2.156 69,8

Kozerska

Control 314.5 ± 35.0 1.0 40,3

25Gy 240.3 ± 72.6 0.8 0.922 98,6

35Gy 248.3 ± 70.4 0.8 0.842 62,9

45Gy 171,3 ± 26.3** 0.6 3.272 37,8

25-45 220.0 ± 56.4 0.7 1.424 66,4


Average 25 Gy 209.7 ± 47.4 0.7 1.508 77,2

Average 35 Gy 258.7 ± 59.2 0.9 0.548 75,3

Average 45 Gy 176,3 ± 38.1* 0.6 2.413 64,5

Average 25- 45 Gy 214.9 ± 48.2 0.7 1.399 72,4

The average total growth of the selected plants

is 224.5 cm and is 20% smaller compared to

the control average value (276.8 cm) (Table

3). For the Bigareau Burlat, the highest

number of plants with expressive outspreadis

determined, which resulted with the highest

average total growth from all of the tested

varieties. The average is 10% higher than the

control. Most of these plants are established

among the 35 Gy dosage. Accordingly, for this

dosage the highest total growth is measured,

which is 20% higher compared to the control.

Deviations were established, but the t-test did

not show statistically significant differences in

any of the variants for this variety. For the

variety Pobeda Krimska, a statistically very

high significant difference for the total plant

growth is established for the 45Gy dosage.

The tested plants have 40% smaller total

growth than the control. The biggest

deviations are determined for Kozerska. That

is a variety with the most branched crown. The

control has the highest total growth from all of

the tested varieties (334.8 cm). The radiation

effect gave a high number of plants with

decreased vigorousness, which also resulted in

high deviations in the total growth from the

control. The differences are statistically

significant for all of the dosages. In the other

variants, the plants have 40 to 50% smaller

total growth. The highest difference,

statistically significant at the level of

significance of 0.01 is established for the 45

Gy dosages.


__________________________________________________________________________________


Table.3. Total growth of selected plants

Variety Dose Total growth

(cm) Index t

CV

%

Bigareau

Burlat

Control 243.9 ± 24.2 1.0 37,1

25Gy 240.1 ± 45.4 1.0 0.074 86,9

35Gy 303.8 ± 65.7 1.2 0.857 72,9

45Gy 232.9 ± 50.0 1.0 0.198 70,3

25-45 258.9 ± 53.7 1.1 0.256 76,7

Pobeda

Krimska

Control 251.8 ± 22.9 1.0 33,2

25Gy 198.9 ± 39.3 0.8 1.163 57,4

35Gy 195.9 ± 42.4 0.8 1.162 70,2

45Gy 139.6 ± 25.3** 0.6 3.291 67,0

25-45 178.1 ± 35.7 0.8 1.739 64,8

Kozerska

Control 334.8 ± 39.7 1.0 43,7

25Gy 183.6 ± 41.1* 0.5 2.645 73,4

35Gy 211.0 ± 50.7* 0.6 1.921 55,7

45Gy 188.5 ± 26.3** 0.6 3.070 37,8

25-45 194.4 ± 39.4* 0.6 2.510 55,6


Average 25 Gy 207.5 ± 41.9 0.7 1.361 72,6

Average 35 Gy 236.9 ± 52.9 0.9 0.662 66,2

Average 45 Gy 229.0 ± 33.9 0.8 1.074 58,4

Average 25- 45 Gy 224.5 ± 42.9 0.8 1.012 65,7

A statistically significant positive correlation

between the rootstock and trunk cross area,

and the total plant growth is established. The

correlation coefficients between the rootstock

cross area and total growth, as well as the

trunk cross area and total growth, for Bigareau

Burlat are 0.597 and 0.849, accordingly. These

coefficients show strong correlation between

the traits, statistically significant at the level of

0.05. Stronger and complete correlation is

determined for the other two varieties. For

Pobeda Krimska, the correlation coefficients

are accordingly 0.971 and 0.927 and for the

variety Kozerska are 0.945 and 0.839. The

correlation coefficients are statistically


Also, complete and very strong negative

correlations between the height of the dosages

used and the total growth for the varieties

Pobeda Krimska and Kozerskaare determined.

The correlation coefficients are accordingly -

0.952 and -0.882 and are statistically


This kind of correlation is not established for

the variety Bigareau Burlat. The correlation

coefficient r is 0.170. The reason for this is

that most of the plants with furcations are

determined in the variant with 35 Gydosage,

which led to higher total growth for this

variety.

The degree of variation for these three traits is

measured through the values of the coefficient

of variation (CV), given in Tables 1-3.

Overall, the tested traits in the selected plants

vary in much higher ranges, than in the control

variants. The highest variation is observed in

all of the varieties for the trait trunk cross area

(CV=72.4%), while the smallest variation is

monitored for the trait rootstock ross area

(CV=55.2%). Analyzing the varieties

separately, the three traits vary the most in the

variety Bigareau Burlat, in average from 62%

for rootstock cross area to 80.8% for trunk

cross area. The traits vary the least in the

variety Kozerska, from 44.4% for rootstock

cross area, to 66.4% for trunk cross area.


__________________________________________________________________________________


Figure1. Rootstock cross area of selected plants

Figure 2.Trunk cross area of selected plants

Figure 3. Total growth of selected plants

Analyzing overall, according to the height of

the dosages used, the rootstock cross area

varies the most for the dosage of 35 Gy, while

the trunk cross area and total growth for 25

Gy. The rootstock cross area varies the least

for the dosage of 25 Gy, while the trunk cross

area and total growth for 45 Gy.

Conclusions

The morphometric characteristics of the

selected cherry plants, as a primary effect from

the treatment with gamma rays, depend from

the traits and the number of plants who

according to the basic criteria were chosen in

the first MV1 generation following the

radiation treatment.

Most of the selected plants have decreased

vigorousnes, which leads to that, that the

selected material has in average 10-50% lower

values for all of the tested traits in comparison

with the control, depending on the variety and

the rootstock. Exception represents Bigareau

Burlat for the dosage of 35 Gy, where the

values for the rootstock cross area and total

growth are higher for 10-20% than the control,

because of the highest number of plants with

expressive outspread, selected from this

variety.

A very high positive correlation is determent

between the rootstock and trunk cross area, as

well as between the rootstock and trunk cross

area and with the total growth in all of the

tested varieties. Negative correlation between

the radiation dosage and the total growth is

detected for Pobeda Krimska and Kozerska.

This kind of correlation is not present in

Bigareau Burlat.

All of the tested traits vary in much higher

degree in the selected plants than in the control

variants. The trunk cross area is the trait with

highest variation, while the rootstock cross

area with least variation.

The three tested morphometric characteristics

vary the most in the variety Bigareau Burlat,

while they vary the least in the variety

Kozerska. The rootstock cross area varies the

most for the dosage of 35 Gy and the least for

25 Gy, while the trunk cross area and total

growth vary the most for 25 Gy and the least

for 45 Gy.

The selected 195 plants present a promising

starting material for further selection and

creation of new varieties or cherry rootstocks.

References

1. Bishop C.J. (1967). Radiation induced

mutations in vegetative propagated fruit


__________________________________________________________________________________


trees. Proceedings of the XVII International

Horticultural Congress, Vol 1,pp. 83-95.

2. Borojević S., Borojević K. (1976).

Genetika. Poljoprivredni fakultet. Novi

Sad.

3. Donini B. (1975). Improvement of

vegetative propagated plants through

induced mutations. Proceedings of

Research Coordination Meeting, Tokai,

Vienna. IAEA, Vol1, pp. 35-51.

4. Donini et.al. (1991). Mutation breeding

programmes for the genetic improvement

of vegetative propagated plants in Italy.

Proceedings of an International Symposium

on the Contribution of Plant Mutation

Breeding to Crop Improvement. Vienna.

IAEA., Vol.1, pp. 237-254.

5. Gunchel, J.E. Sparrow A.H. (1961).

Ionizing radiations:biochemical,

physiological and morphological aspects of

their effects on plants. Encyclopedia of

Plant Physiology, 16, pp. 555-611.

6. Колесникова А.Ф. (1970).

Индуцированный мутации вишни.

Селъскохозяйственная биология., No 4.

Москва.

7. Lapins K.O. (1983). Mutation breeding.

Methods in fruit breeding. Edited by James

N. Moore and Jules Janick. Purdue

University Press West Lafayette. Indiana.

8. Миленков М.М. (1974).

Индуцированный мутагенез у черешни.

Диссертация на соискание ученой

степени кандидата биологических наук.

Академия наук СССР, Сибирское

отделение. Обединенный ученый совет

по биологическим наукам. Новосибирск.

9. Mišić P. (1999). Genetika. Partenon. PKB

INI Agroekonomik. Beograd.

10. Nybom, N. (1961).Theuse of induced

mutations for the improvement of

vegetative propagated plants. Symposium

on mutation and plant breeding.

Washington, pp. 252-294.

11. Најчевска Ц.(2002).Експериментална

статистика применета во земјоделските

и биолошките истражувања.

Бона.Скопје.

12. Pearson O.W., Sander C., NilanR.A.

(1975). The effect of sodium aside on cell

processes in the embryonic barley shoot.

Radiation Botany, 15, pp. 315-322.

13. Поповска М.(2007).Ефекти од гама

зрачењето кај некои сорти цреши.

Докторска дисертација. УКИМ,

Факултет за земјоделски науки и храна -

Скопје.

14. Popovska M., Popovski B., Gjamovski V.

(2011). Criteria for early diagnostics of

primary effects of the treatment with

gamma rays (Cz137) at some cherry

varieties. Plant Science No 48, pp. 47-52.

15. Popovska M., Popovski B. (2012). The

influence of the treatment with different

gamma rays (Cz137) doses on bud

sprouting at some sweet cherry varieties.

Journal of Mountain Agriculture on the

Balkans, Vol. 15, 3, pp. 634-642.

16. Равкин А.С.(1973). Исполъзование

ионизирующей радиации и химических

мутагенов в селекции плодовых и

ягодных култур. Москва.


UDC 634.11-181.198


____________________________________________________________________________________________________

EFFECT OF GROW REGULATORS ON THE STOMATA CONDUCTANCE IN

THE APPLE TREE

V. Avdiu1*, F. Thomaj2, S. Sylanaj1, E. Kullaj2, K. Lepaja2

1Faculty of Agriculture & Veterinary, University of Pristina, Pristina, Kosovo

2Faculty of Agriculture and Environment, Agriculture University of Tirana, Tirana, Albania


Abstract

This research paper presents the results of a field trial with managed yang orchard including apple

cultivar Gala Galaxy, on the rootstocks M9. In November 2012, nursery tree “knip” were planted in

the distance 3 m x 1 m. In the first vegetation season (2013) the experimental plot was separated in a

randomized block system of four treatments. For research are taken 12 apple trees, which were treated

with growth regulators in the stage of nursery trees production with Gerba 2.5% (benzyl adenine),

Progebalin2.5%, (gibberellins A4+7 + benzyl adenine) Pinching (i.e. removal of terminal leaves)and

Control (untreated). The stomata conductance was examined. During the period from July to

September are realized 15 measurements. In each plant measurements made in 10 leaves (5 inside and

5 on the periphery of the crown of the tree). Also in same time made measurement temperature of

leaf, soil temperature and moisture, to analyze the dependence between these ecological factors and

stomata conductance. By the results obtained the treatment with GerBA 2.5%, has given higher values

of leaf stomata conductivity (200.89 mmol m-² s-¹) in relation to treatments, Progerbalinin, Pinching

and Control, respectively; (174.76, and 141.94 162. 57 mmol m-² s-¹). It is also remark that exist

strong correlation between stomata conductance with soil moisture, soil and leaf temperature.

Key words: stomata conductance, grow regulators, ecological factors

Introduction

The process of plant function is quite complex

and the impacted of many factors internal or

external. It is quite important to recognition as

more as possible of these factors were their

role in the plants could be different. This could

help us in some processes interfering with the

aim of establishing an optimum balance in the

development of plants. Apical dominance is

the control exerted by the shoot apex over the

outgrowth of the lateral buds (Cline, 2000).

Also according Ibro (2008) the auxin have

essential role in apical dominance respectively

dominance top of the buds in relation with

lateral. The development of lateral shoots is in

direct correlation with the phenomenon of

apical domination (Avdiuet al., 2014; Martin,

1987; Cline, 1997; Wilson, 1994). Hormone

production and assimilate retention by the

branch are the most likely candidates for the

primary causes of apical control (Wilson,

2000). Apical dominance is exerted by the

shoot apex over the outgrowth of lateral buds

in apple (Wang, 1994). The environmental

impact on the organs of plants and their related

functions is conditioned very much by the

power and duration of certain factors, even by

the interaction of the factor with genetic

features of plants (Zlatevet al., 2012).

Defining and recognizing by vapour pressure

deficit (VPD) as an environmental factor is

necessary for the evaluation of evaporation -

transpiration (since it is the part of equations

that compute potential evapotranspiration -

PET), but along with global radiation (GR)

have the key impact on the stomata activity

and transpiration (Tonelloet al., 2012; Mugani,

2004). Stomata of leaves are a mechanism

through which is controlled the process of

transpiration and absorption of CO2 and

according to Tonelloet al., (2012) when we

want to determine the stoma response to

various climatic factors, potential impacts may

appear including all main elements that

participate in leaf’s function.

22 V. Avdiu, F. Thomaj, S. Sylanaj, E. Kullaj, K. Lepaja

__________________________________________________________________________________

JAFES, Vol 69, (2016)


To establish of experimental orchards selected

the standardized apple nursery “knip” tree

with cultivar‘Gala Galaxy’, on the rootstock

M9 at the distance 3 m x 1 m. For research 12

apple trees were taken (3 for each variant),

which were treated with growth regulators in

the stage of nursery trees production

GerBA2.5% (benzyl adenine), and Progebalin

2.5%, (gibberellins A4+7 + benzyl adenine).

Besides, two other treatment were included:

pinching (i.e. removal of terminal leaves) and

control (untreated).

The soil in which saplings were planted was of

good quality, up to 60 cm deep and in average

contained: humus 2.36 %, (moderate) N 0.13

% (moderate), P2O5 10.69 mg/100g (low), soil,

K2O 43 mg/100g soil (high), Ca101.73

mg/100g soil (moderate), Mg 47.14 mg/100g

soil (moderate). pH value in water was 6.8

whereas in KCl 5.8 (slightly acid)

Ploughing was made at 50 cm depth, organic

and mineral fertilizer was distributed in

advance: organic 5kg/m2 and mineral NPK

15:15:15 100g/m2.The plot was tilled 5 times;

plants were drip irrigated and have received 3

treatments with fungicides and insecticides.

The model and experiment design

For research is taken stomata conductance and

impact of ecological several factors which

connected with this process inside of the 10.07

- 06.09.2013 period.

In 12 plans taken for research, 12

measurements were carried, where in each

plant are selected 10 leaves for measurements

(5 inside and 5 outside the apple tree shape).

In same time to the all cases, exanimate

temperature of leaves. The Porometer

measures stomata conductance using a sensor

head with a fixed diffusion path to the leaf. It

measures the vapor concentration at two

different locations in the diffusion path. It

computes vapor flux from the vapor

concentration measurements and the known

conductance of the diffusion path using the

following equation:

Where CvL is the vapour concentration at the

leaf, Cv1 and Cv2 are the concentrations at the

two sensor locations, Rvs is the stomata

resistance, and R1 and R2 are the resistances

at the two sensors. If the temperatures of the

two sensors are the same, conductance can be

replaced with relative humidity, giving:

Conductance is the reciprocal of resistance, so

gvs = 1/Rvs.

The soil temperature depth 15 cm measured

with Sensor type ”WET 2” whereas the soil

moisture in two levels 20 and 40 cm depth,

measured with “DELMHORS” Sensor.


Stomata conductance is an important indicator

that shows that the behaviour of the stomata is

a necessary reaction of the plant to climate

factors. Through them, it controls two

important physiological processes;

transpiration and absorption of CO2 that is the

basis for photosynthesis. Tonelloet al., (2012)

point out that when we want to determine the

reaction of stomata to different climatic

factors, potential impacts may pluck including

all the main elements that take part in the

functions of the leaf.

3

2 1

Figure 1. The process of measures: 1.Porometer

(stomata conductance), 2. Delmhorst (soil moisture

20-40 cm depth), 3. WET 2 (soil temperature 15 cm

depth)


__________________________________________________________________________________

JAFES, Vol 69, (2016)

Table 1. Obtained means for some ecological and physiological factors during the period 10.07-06.09.2013 to

the apple cultivar “Gala Galaxy” on the rootstock M9

Date

Soil

moisture

(20-40cm)

KS-D1

Soil temp. oC

(0-15cm)

Leaf

temp. oC

Stomata conductance mmol m⁻² s⁻¹

Progerbalin

2.5%

Gerba

2.5% Pinching Control

10.07. 13 96.00 23.80 21.93 123.9 144 117.5 102.7

13.07. 13 96.20 26.87 28.52 195 229 207.6 173.5

16.07. 13 96.30 21.67 19.83 124.2 122.3 123.2 147.1

19.07.13 96.80 32.47 31.83 179.9 225.4 186.3 171.4

22.07. 13 96.35 31.07 29.68 198.1 212.5 174.2 139.4

25.07. 13 92.30 31.00 33.85 163.5 176.6 165 115.8

29.07. 13 74.90 33.63 36.15 159.1 165.5 131.6 95.38

31.07. 13 69.60 30.67 28.87 180.9 190.4 189.8 157.4

03.08. 13 63.85 35.40 34.54 122.6 176.7 95.54 77.26

06.08. 13 80.40 31.80 35.67 138.4 141.8 113.6 84.32

09.08. 13 60.62 37.93 37.34 132.3 141.2 88.68 63.42

28.08. 13 95.9 27.93 29.18 220.1 242.8 207.1 212.5

31.08. 13 95.75 27.93 26.75 230.6 310 226.6 223.4

03.09. 13 94.95 25.30 27.33 260.9 299.4 250.5 218.3

06.09. 13 94.95 29.30 29.05 191.7 232.6 161.3 176.4

The data presented in Figure 2 shows that

existed a strong connection between stomata

conductance and soil moisture, temperature

soil and leaf. Another interesting phenomenon

that finds compliance with studies of Cechinet

al., (2010), is that the fall of stomata

conductance of leaf aging, which stands very

well in the last part of the above figure that

coincides with the decade first of September.

In this case, although temperature and

humidity indicators remain almost constant

values, whereas have a noticeable decrease of

stomata conductance for all variants.

Figure 2. Comparison of stomata conductance between Soil moisture (Sm), Soil temperature (St) and Leaf

temperature (Lt) according the variants

According to the results obtained on the

stomata conductance presented in the Table 2

and Figure 3, distinguish the difference

between the average values achieved in each

of the analyzed variant. The variant treated

with Gerba 2.5%, has given higher values


__________________________________________________________________________________

JAFES, Vol 69, (2016)

leaf’s stomata conductance (200.89 mmol m-²

s-¹) in relation to options, Progerbalin,

Pinching and Control respectively; (174.76,

162. 57 and 141.94 mmol m-² s-¹).

Table 2. Comparison of several statistical descriptive parameters of stomata conductance (mmol m⁻² s⁻¹) means, control and three (Progerbaline, Gerbadhe Pinching) during the comparison period

Level Mean Significantly different

Gerba 2.5% 209.58* A

Progerbalin 2.5% 182.79 AB

Pinching 170.09 AB

Control 150.55 B

Means Comparisons q* Alpha

Tukey-Kramer HSD

2.64794 0.05

3.25848 0.01

Levels not connected by same letter are significantly different, * significantly in level 0.05,

Figure 3. Stomata conductance [mmol m-² s-¹] by Variants Gerba2.5%, Progerbalin 2.5%, Pinching and Control

Conclusions

Reduction of moisture in soil stimulates ABA

synthesis of the root that further is transported

through xylem up to the leaves and causes a

slight closure of stoma, whereas, cytokinin

stimulate the opening of the stoma and

transpiration growth rates (Kullajet al., 2014;

Mameli, 2007). This cytokinin effect to the

stoma opening is associated with water

potential in the other parts of the plant. There

occur several interactions between cytokinins,

ABA and CO2 concentration (Blackman and

Davies, 1984; Das and Raghavendra, 1976).

Decagon, (2006) emphasizes that the

conductance is reciprocal with the stomata

resistance. This means that trees derived from

seedlings treated with grow regulator of

cytokinins content (Gerba 2.5%) have higher

stomata conductance but lower resistance,

while the opposite is true for trees untreated

(control) which have lower stomata

conductance and higher resistance of stoma.

This brought the stoma, match quite well with

ecological factors as soil moisture,

temperature soil and leaf, but to take into

consideration the development phase of the

plant within the vegetation.


__________________________________________________________________________________

JAFES, Vol 69, (2016)

References

1. Avdiu V, Thomaj F, Sylanaj S, Kullaj E,

(2014) Effect of “knip” Method in Apple

Nursery Tree Production on the Apical

Dominance cv Gala Galaxy. J. Int.

Environmental Application & Science,

No.9(2), pp. 323-327.

2. Avdiu V, Thomaj F, Sylanaj S, Kullaj E,

(2014) Effect of “Knip” method in apple

nursery tree production on the apical

dominance Cv Golden Reinders.

Procedings of the 4th Interational

conference of ecosystems ICE, No. 4, pp.

704-709.

3. Blackman PG, WJ Davies, (1983) The

effects of cytokinins and ABA on stomatal

behaviour of maize and Commelina.

Journal of Experimental Botany, No.34,

pp.1619-1626.

4. Cline MG, (2000) Execution of the auxin

replacement apical dominance experiment

in temperate woody species. Am. J.

Bot., No. 87 (2), pp. 182-190

5. Cline MG, (1997) Concepts and

terminology of apical dominance. Amer. J.

Bot., No 4(9), pp.1064- 1069

6. Cechin I, Corniani N, Terezinha FFT,

Cataneo CA, (1980) Differential responses

between mature and young leaves of

sunflower plants to oxidative stress caused

by water deficit. CienciaRural.,No. 40 (6 ),

pp. 1290-1294

7. Das VSR, Raghavendra AS, (1976)

Reversal of abscisic and induced stomatal

closure bybenzyladenine. New Phytologist,

No. 76, pp. 449-452.

8. Decagon (2006)

http://www.decagon.com/instruments/short

course.html Ibro V, (2008) Fiziologjia e

bimëve (parimetëpërgjithshme).Universiteti

Bujqësori Tiranës.

9. Kullaj E, Avdiu V, Thomaj F, (2014)

Model Unveils Changes in Stomatal

Conductance in Apple Saplings after Use

of Bioregulators. Physiological Principles

and Their Application to Fruit Production

(ISHS)

10. Kullaj E, Avdiu V, Lepaja L, Kucera J,

Thomaj F, (2014) Modelling Canopy

Transpiration and Stomata Conductance of

Young Apples Using a Parameterized

Penman-Monteith Equation. Physiological

Principles and Their Application to Fruit

Production (ISHS).

11. Mameli GM, (2007) Dendrometri e stress

idrico (CRAS) Mugani S, (2004) Elementi

di ecofisiologiavegjetale. QuadernoArsia,

No.5, pp. 35-47.

12. Tonello CK, Filho TJ, (2012) Ecofisiologi

de tresespeciesarboreasnativas da mata

atlantica do Brasilemdiferentes regimes de

agua. Irriga, No.17(1), pp. 85-101

13. Wilson SJ, Jarassamrit N, (1994) Nursery

factors influencing lateral shoot

development in a spur type apple cultivar.

ScientiaHorticulturae, No.56, pp. 207-

215.

14. Wilson BF, (2000) Apical control of branch

growth and angle in woody plants.

American Journal of Botany, No.87, pp.

601-607.

15. Wang ShY, (1994) Apical Dominance in

Apple (MalusdomesticaBorkh): The

Possible Role of Indole-3-Acetic Acid

(IAA). J. Aamer. Soc. Hort. Sci.,

No.119(6), pp.1215–1221.

16. Zlatev Z, Lidon C.F, (2012) An overview

on drought induced changes in plant

growth, water relations. J. Food Agric.,

No.24 (1), pp.57-72

http://www.decagon.com/instruments/shortcourse.html

http://www.decagon.com/instruments/shortcourse.html


UDC 634.54(497.7)


____________________________________________________________________________________________________

ROOTING OF HAZELNUT (CORYLUS AVELLANA L.) VARIETIES HARDWOOD

CUTTINGS

A. Markovski1*, T. Arsov2, V. Gjamovski1

1Institute of Agriculture-Skopje, Ss. Cyril and Methodius University in Skopje, Skopje, R.

Macedonia. 2Faculty of Agricultural Sciences and Food-Skopje, Ss. Cyril and Methodius University in Skopje,

Skopje, R. Macedonia


Abstract

Intensity of rooting on hardwood hazelnut cuttings is evaluated during two consecutive years. The

evaluation is conducted on 6 hazelnut varieties (Istarski, Tonda Romana, Extra Yagli, Ludolf, Hall’s

Giant, Devianna) in greenhouse conditions at experimental greenhouse of Institute of Agriculture,

Skopje. The cuttings are collected during dormancy of the plants, before start of vegetation. Two

types of auxins IBA (indole-3-butyric acid) 2%, and NAA (α-naphthalene acetic acid) 0.2% are used.

From evaluated varieties, Tonda Romana has the highest percentage of rooting (85.5%) and it is

characterized with the highest value of rooted cuttings of first class. At all evaluated varieties,

treatment with higher concentration of IBA gives higher percentage of rooted cuttings and higher

value of rooted cuttings of first class.

Key words: Hazelnut, variety, hardwood cuttings, rooting, biohormone

Introduction

The European hazelnut (Corylus avellana L.)

is the fruit kind which increasingly spread in

the world due to high income and profitability

in the orchards. This culture attract increasing

attention especially when and where the

difficult and expensive manual harvest of the

kernels is replaced with harvest

mechanization. The biggest production of

hazelnut kernels in the world has the Turkye

with about 75% of the total world production

from which 80% go for export (Faostat, 2012).

In the hazelnut cultivation has the inention for

decreasing of plant distances in orchards, with

aim to achieve the higher yields per ha, which

is in maximum utilized in USA, where the

yields is reached up to 3 t/ha kernels and with

200% increasing of the Hazelnut plantations

area (Faostat, 2012). In this country is going

with the interspecies crossing (Corylus

avellana x Corylus americana) with aim to

create hybrids for expansion of the cultivation

zone to the drier and colder areas (Demchik et

al., 2011). Hazelnut is a feedstock that is

widely used in food industry especially in

chocolate. Eighty percent of the world

hazelnut production is used in chocolate

sector, 15% in cake, biscuit and sweet sector

and 5% in marketing as appetizers

(Fiskobirlik, 2003). The increased appetites of

the world market for the hazelnut kernels can

be satisfied with the increased and more

efficient production of the plant material from

this culture. The most common techniques of

hazelnut propagation are by stool layering and

root suckers. Micropropagation is the safest

and most productive form of propagation, but

in hazelnut it still shows low yield due to

contamination during culture establishment

and the limited adaptability of the explants to

in vitro conditions (Bacchetta et al., 2008).

The propagation by cuttings can be considered

as rapid and relatively economic method but,

in spite of the numerous studies conducted for

the hazelnut, the technique has not yet been

transferred to an industrial scale due to poor

rooting ability and cutting survival of most

cultivars (Contessa et al, 2012). Without usage

of the chemical agents for root initiation

(auxins), the plant material production in this

way becomes impossible. Except that, the bud

abscission is a limiting factor to propagation of

hazelnut stem cuttings, even though the

27 A. Markovski, T. Arsov, V. Gjamovski

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

rooting percentage may be acceptable (Bassil

et al., 1991). Actually, the auxins are using for

the annulation of the ethylene inhibitory effect

on rooting, which is releasing from the cutted

plant parts used for rooting. The ethylene

disable the rooting process (Serek et al., 2006).

Therefore, as the ethylene inhibitors in rooting

process can be used some other compounds

except the auxins, like silver nitrate (AgNO3)

or silver tiosulphate (AgS2O3) (Contessa et al,

2012). The hazelnut can be propagated with

softwood cuttings or with hardwood cuttings.

The softwood cuttings have good rooting with

bottom heating and influence of biohormons,

except that in the period of 6th to 10th week of

rooting, the development of the bud stops

(Lagerstedt 1983). At the hardwood cuttings,

cold survival and acclimatization problems

have been observed. The best rooting has been

obtained from semi-hardwood cuttings taken

from mid-June to mid-July (Contessa et al,

2011). The using of IBA gives excellent

results in rooting of the cuttings from some

fruit kinds (Ercisli, Read, 2001). But, other

studies show that some modified combinations

can provide the better results. According to

Agele (2013), coconut water and NAA were

found better than IBA and IAA in terms of bud

retention and rooting, leaf development and

survival of plantlets. In most of the tested

species (pepper fruit, guava, bush mango and

cashew), wilting of leaves commenced 6

weeks after planting (WAP) and attained

100% mortality thereafter except for pepper

fruit cuttings dipped in coconut water. With

aim to determine the rooting ability of the

different hazelnut varieties (Corylus avellana

L.) we have used the concentration of different

auxins.


In the period 2004-2005 are collected the

hardwood cuttings from six hazelnut varieties

(Istarski, Tonda Romana, Extra Yagli, Ludolf,

Hall’s Giant, Devianna) in the beginning of

tree dormancy (November), then stored in

sand. At the end of February and in the

beginning of March, the cuttings are prepared

for the rooting with the mitter cut from the

bottom, 5-6 mm below the bud, and flat cut

from the top, 8-10 mm above the last top bud,

by limiting the cutting length of 30-35 cm. The

environmental, and the treatments influence

over variety Tonda Romana is also studied.

For that purpose, the cutting basal part is

treated with biohormons: 2% IBA (C12H13NO2

(Indole-3-butyric acid)) in talc carrier, 0.2%

NAA (C10H7CH2CO2H (1-Naphthaleneacetic

acid)) and the control variant, without treating.

The cuttings are set in inert substrate (sand), 4-

5 cm in depth. Thirty cuttings in three

replications are used. During the vegetation is

performed mist with automized system, and

shading, depending on the conditions. The

rooting is performed in green house

conditions. Through the rooting process, two

times are performed the protection with

Previcur and foliar feeding. All rooted cuttings

which have certain superior vegetative

characteristics (over 30 roots, over 10 cm root

length, and over 5 cm high of the growth) we

classify them in the first class, and other that

do not met provided characteristics are

separated in the second class.

At the end of the vegetation, in November,

after the leaves fall, the hardwood cuttings are

extracted from the sand and then are study the

following parameters:

- Number of set cuttings;

- Number of rooted cuttings;

- Number of I class cuttings;

- Number of II class cuttings;

- Number of roots;

- Length of roots;

- Height of vegetative growth.

The data are statistically analysed by

ANOVA and Fisher’s multiple comparision

test at level of 0.05 using the Minitab software.


There are many methods for vegetative

propagation of the hazelnut: with grafting,

basal shoots, root suckers, layerings, and with

cuttings. For most of this methods a large

number of mother trees, and the large

propagating area is needed, which is mean

prolonged period for the mass plant material

production and meeting the increased needs

for that. The only possible way to starts in the

short period the large production of plant

material, is to obtain them from rooting of

cuttings.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Figure 1. Percent of hazelnut variety Tonda Romana rooting cuttings in different years and its participation in

different class.

Figure 2. Quality characteristics of the rooted cuttings in different years.

The mother plants from which are taken the

branches, needed as material for cuttings, were

in excellent condition, without presence of

pests and diseases. Our investigations show

that the hazelnut (Corilus avellana L.), as a

species, has affinity to rhizogenesis from the

vegetative plant parts, in our case, from one

year branches. The rooting intensity vary due

to the influence of the different factors.

Successively investigations in different years

show statistically insignificant influence of the

environmental conditions, over total rooting.

So, the percent of the rooting at hazelnut

variety Tonda Romana in the first year was

smaller (61.4%), unlike the next year when the

percent reach 68.5% (Fig.1.). The cuttings

classification by quality shows that the

environmental factors which affect the rooting

of the cuttings, not affect the quality of the

cuttings. At the same hazelnut variety in the

first year, although there was weaker rooting,

it was obtained the higher percent of first class

0

10

20

30

40

50

60

70

80

2004 2005

perc

en

t (%

)

rooting

I-class

II-class

0

10

20

30

40

50

60

I-class 2004 I-class 2005 II-class 2004 II-class 2005

nu

mb

er

of

roo

ts

0

10

20

30

cm

root number growth length of roots


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

material (55.8%) in equal greenhouse

conditions (Fig.1.). The quality characteristics

of the rooted cuttings indicate that in the

second investigation year is obtained slightly

better quality of the rooted cuttings (53.5

roots, 13 cm length of the roots and 10 cm

over ground growth) in the first class and in

second class (15 roots, 5 cm length of the roots

and 3 cm over ground growth). It can be

noticed the high difference in the quality

between the classes in the first and also in the

second year (Fig.2.)

The influence of the treatments with different

biohormons (IBA 2% and NAA 0.2%) over

the cuttings from the variety Tonda Romana is

significantly higher. The highest positive

influence over the rooting of cuttings is

determined at the treatment with 2% IBA,

when is obtained almost ninety percent (89,

5%) rooted cuttings, which is 55% more than

in the control (Fig.3.).

Is also determined statistically significant

difference in the treatment with 0.2% NAA

(71.1%), compared with control. The

treatments with different concentrations (500

mgL-1 and 1000 mgL-1) of IBA show almost

equal influence of the rooting percent of the

cuttings (70% and 72.5%) at the variety Tonda

Gentile delle Langhe, even, at the lower

concentration of the IBA is obtained more

rooted cuttings with live buds (56%) (Contessa

et al., 2012).

In our case, the differences are more

noticeable when are analysed the participation

of the different classes in the total amount of

the rooted cuttings. So, is noted statistically

significant difference in terms of the first class

rooted cuttings percent (92.6%) in the

treatment with 2% IBA compared with

treatment with 0.2% NAA (48.1%) and also

with control (15.4%) (Fig.3.). The influence of

the different auxins over the rooting can be

different. At some fruit kinds (Guava) NAA

gives the better results than the IBA (Agele et

al., 2013).

Figure 3. Influence of different auxins on percent of rooting cuttings of the hazelnut variety Tonda di Romana

* Footnote: The means followed by the same letter in similar column are not significantly different at P ≤ 0.05

by Fisher’s multiple comparisons test.

The investigation of the different hazelnut

varieties shows partial influence of the

genotype (Tonda Romana) over the ability for

rooting of the hardwood cuttings. With

statistically significant higher percent of

hardwood cuttings rooting is characterized the

variety Tonda Romana (85.4%) (Fig.4.).

Among the other five varieties is not noticed

statistically significant difference. The variety

Tonda Romana also is characterized with

significantly higher percent of first class

cuttings (92.9%), than the other hazelnut

varieties. In some variety investigations with

the rooting of semi-hardwood cuttings, the

a

b

c

c

b

a

c

b

a

0

10

20

30

40

50

60

70

80

90

100

control 0.2% NAA 2% IBA

cuttings basal treatment

perc

en

t (%

)

rooting I-class II-class


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

variety Tonda Romana shown the lowest

percent of rooting, which alluded that the time

of taking the branches for the cuttings has

different influence over the ability for rooting

at the same varieties (Contessa et al, 2011).

The variety Devianna is characterized with the

lowest percent of rooting and with the lowest

percent of first class rooted cuttings (37.7%

and 38.8%) (Fig.4.).

Figure 4. Influence of the genotype on rooting capability of the cuttings.

* The means followed by the same letter in similar column are not significantly different at P ≤ 0.05 by Fisher’s

multiple comparisons test.

Figure 5. Different Hazelnut varieties rooting cuttings

Conclusions

The investigations show that the rooting of the

hazelnut hardwood cuttings gives numerous

and quality planting material with much better

developed root system than in the usually most

used propagating method-with suckers. The

using of the auxin IBA (2%) contribute for the

much higher rooting percent and for the better

quality of the rooted cuttings. The variety

Tonda Romana is especially suitable for

propagation with hardwood cuttings due to the

high rooting percent.

References

1. Agele, S.O., Aiyelari, O.P., Obi, E.A.

(2013). Pattern of rooting and growth of

cuttings of some species of insecticidal and

medicinal importance as affected by growth

promoting substances. Oct. Jour. Env. Res.

Vol. 1(2): 151-160

bb

bbb

aa

b bbc

cdd

d

c cbc

aba

0

10

20

30

40

50

60

70

80

90

100

Tonda

Romana

Istarski Extra jagli Ludolf Hall’s

Giant

Devianna

Hazelnut variety

perc

en

t (%

)

rooting I-class II-class


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

2. Bacchetta, L., Aramini, M., Bernardini, C.,

Rugini. E. (2008). In vitro propagation of

traditional Italian hazelnut cultivars as a

tool for the valorization and conservation of

local genetic resources. HortScience 43,

562-566.

3. Bassil, N.V., Proebsting, W.M., Moore,

L.W., Lightfoot, D.A. (1991). Propagation

of hazelnut stem cuttings using

Agrobacterium zhizogenes. HortScience

26(8), 1058-1060.

4. Contessa C., Valentini N., Botta R. (2012).

Decreasing the concentration of IBA or

combination with ethylene inhibitors

improve bud retention in semi-hardwood

cuttings of hazelnut cultivar ‘Tonda Gentile

delle Langhe’. Scientia Horticulturae,

Volume 131, 22 November 2011, Pages

103–106.

5. Contessa C., Valentini N., Caviglione M.,

Botta R. (2011). Propagation of Corylus

avellana L. by Means of Semi-hardwood

Cutting: Rooting and Bud Retention in

Four Italian Cultivars. Europ.J.Hort.Sci., 76

(5/6). S. 170–175, 2011, ISSN 1611-4426.

6. Demchik M., McCown B., Fischbach J.,

Kern A., Zeldin E. (2011). A new Hazelnut

development Program in the lake states.

Agroforestry: A profitable land use.

7. Ercisli S. Read P.E. (2001): Propagation of

hazelnut by softwood and semi-hardwood

cuttings under Nebraska condition. Acta

Hort. 556, 275–279.

8. Fiskobirlik, (2003). Records of Union of

Agriculture Cooperatives for the Sale of

Hazelnut. Giresun, Turkye.

http://www.fiskobirlik.org.tr/

9. Lagerstedt H.B. (1983). The American nut

industry-filberts (Corylus avellana L.),

cultivars, culture production. North. Nut

Grow. Assoc. Annu. Rep. 74: 179-185.

10. Serek, M., Woltering, E.J., Sisler, E.C.,

Frello, S., Sriskandarejah, S. (2006).

Controlling ethylene at the receptor level.

Biotechnol. Adv. 24, 368-381.

http://www.fiskobirlik.org.tr/


UDC 631.459

Original Scientific Paper

____________________________________________________________________________________________________

SOIL EROSION EVALUATION IN THE RASTOCKI POTOK WATERSHED OF

MONTENEGRO USING THE EROSION POTENTIAL METHOD

V. Spalevic1*, D. Vujacic1, G. Barovic1, I. Simunic2, M. Moteva3, V. Tanaskovikj4

1*Department of Geography, Faculty of Philosophy Niksic, University of Montenegro

2Faculty of Agriculture, University of Zagreb, Croatia 3University of Architecture, Civil Engineering and Geodesy, Dpt. of Land Management, Sofia,

Bulgaria 4Agricultural Sciences and Food, Ss. Cyril and Methodius University, Macedonia


Abstract

Soil erosion is the most important factor of land degradation worldwide, causing significant

environmental problems in the region of South East Europe also. We studied soil erosion processes in

the RastockiPotok Watershed of Montenegro using the Erosion Potential Method (EPM) of

Gavrilovic, which is created in Yugoslavia and is the most suitable on catchment level for the

watershed management needs in this Region. The peak discharge (Qmax) is calculated on 150 m3s-1

and there is a possibility for large flood waves to appear in the studied basin. According to our

analysis, the coefficient fs, (portion under forest) is 0.45; ft (grass) is 0.41 and fg (bare land) is 0.14

and the coefficient of the river basin planning, Xa, is 0.52. Real soil losses, Gyr, were calculated on

1472m3yr-1, specific 250m3km-2yr-1. The value of the Z coefficient of 0.488indicates that the studied

watershed belongs in the Destruction Category III: the erosion process is medium. This study

confirmed the findings of the other Balkan researchers that the EPM method of Professor Gavrilovic

is a useful tool for calculating sediment yield in the South East Europe.

Keywords: Montenegro, watershed, soil erosion, runoff, Erosion Potential Method (EPM)

Introduction

Soil is an essential resource for the food chain

and our society. Soil formation is a slow

process, while soil destruction can be rapid.

Hence, soil is considered a non-renewable

resource, and its sustainability is important.

Among the threats to soil is erosion, which is a

natural phenomenon that can be impacted by

global change (Paroissien, 2015).

The issue of sediment yield and runoff and

their factors is one of the hot spots in

hydrological science. Various studies show

that sediment yield and runoff in a river basin

are mainly affected by local natural conditions,

such as precipitation, vegetation coverage,

terrain, lithology, and soil structure, as well as

human activities (Xu 2006). Quantitative

information on sediment yield and runoff is

needed for erosion risk assessment. Besides

field and laboratory investigation, erosion risk

models have proved to be good tools to

understand these processes (Boardman, 2006).

This study aims to estimate the annual

sediment yield, due to rainfall and runoff, at

theoutlet of RastockiPotok River basin, which

is located in north Montenegro. The main

processes quantified in the study are runoff

resultingfrom rainfall, soil erosion due to

rainfall and runoff, inflow of soil erosion

products intostreams, and sediment transport

in streams. The quantification leads to the

computation of sediment yield at the basin

outlet.

Erosion Potential Method (EPM) of Gavrilovic

(1972) was chosen for this study as it is widely

used in different studies in the Region (Bosnia

and Herzegovina, Macedonia, and Serbia).

Blinkov and Kostadinov (2010) evaluated

applicability of erosion risk assessment

methods for the Balkan region, considering

dependence on scale and different needs. The

EPM was, according to them, the most suitable

for the watershed management needs in this

Region. The EPM model was earlier validated

for simulating the processes of soil erosion and

33 V. Spalevic, D. Vujacic, G. Barovic, I. Simunic, M. Moteva, V. Tanaskovikj

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

sediment transport over the Polimlje River

Basin in North of Montenegro (Spalevic,

2011).

The new detailed report about the state of the

runoff and sediment yield in this format may

be used further in watershed management

sector of Montenegro, illustrating the

possibility of modelling of sediment yield with

such approach.


We studied the area of the Rastocki Potok

drainage basin (6 km2), a right-hand tributary

of the river Lim.In terms of geomorphology

and climate, it is a part of the natural entity of

the Bijelo Polje Valley of the Polimlje region,

North of Montenegro (Figure 1).

Figure 1. Study area of the Rastocki drainage basin

The river basin of Rastocki Potok stretches

from its inflow to the River Lim (Hmin, 540 m)

to the tops of the hills over the villages

Cerovar and Krusev Do where the Hmax is

1278m. There is a flat area on the lower

alluvial terrace close to the inflow of the


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

RastockiPotok to the River Lim. The average

river basin decline, Isr, is calculated at 25.5%

and indicates that steep slopes prevail in the

studied river basin. The average river basin

altitude, Hsr, is calculated at 840 m; the

average elevation difference of the river basin,

D, is 300 m.

The detailed information on the soil erosion

processes were collected during the field visit.

This includes also the analysis of the status of

plant cover, the type of land use, and the

measures to reduce the erosion processes, as

well as determination of the slopes, specific

lengths, the exposition, the depth of the

erosion base and the density of erosion rills.

We used the data of Soils of Montenegro

(Djuretic and Fustic, 2000) for the studied area

of the RastockiPotok. Furthermore, some

pedological profiles had been reopened, and

soil samples were taken for physical and

chemical analysis. The granulometric

composition of the soil was determined by the

pipette method; the soil samples were air-dried

at 105°C and dispersed using sodium

pyrophosphate. The soil reaction (pH in H2O

and nKCl) was determined with a

potentiometer. The total carbonates were

determined by the volumetric Scheibler

method; the content of the total organic matter

was determined by the Kotzman method;

easily accessible phosphorous and potassium

were determined by the Al-method, and the

adsorptive complex (y1, S, T, V) was

determined by the Kappen method (Spalevicet

al., 2013).

Understanding of soil erosion processes is

essential in appreciating the extent and causes

of soil erosion and in planning soil

conservation. According to the previous

experience in the Region, the most reliable

method for determining the sediment yields

and the intensity of the erosion processes for

the studied area is the Erosion Potential

Method (EPM). This method was created,

developed, and calibrated in Yugoslavia

(Gavrilovic, 1972).

With the increased computing powers of the

last 20to 30 years, there has been a rapid

increase in the explorationof catchment

erosion and sediment transportthrough the use

of computer models (Merritt et al., 2003) and

have also been demonstrated in Montenegro,

specifically in the Region of Polimlje (Barovic

and Spalevic, 2015; Fustic and Spalevic, 2000;

Gazdic et al, 2015; Spalevic et al., 2015a;

Spalevic et al., 2015b; Spalevicet al., 2015c;

Spalevic et al., 2015d; Spalevic et al., 2015e;

Spalevic et al., 2014a; Spalevic et al., 2014b;

Spalevic et al., 2014c; Spalevic et al., 2014d;

Spalevic et al., 2013a; Spalevic et al., 2013b;

Spalevic et al., 2013c; Spalevic et al., 2013d;

Vujacic&Spalevic, 2015). That approach was

used in the research on the RastockiPotok river

basin.

These methods involve several steps: data

acquisition, model specification and estimation

(Madureiraa et al., 2011). We used the

program package Intensity of Erosion and

Outflow - IntErO (Spalevic, 2011) in this

research. This program is an integrated, more

modern second-generation version of the

program „Surface and Distance Measuring”

(Spalevic, 1999) and the program “River

basins” (Spalevic, 2000). We used this

program to obtain data on forecasts of

maximum runoff from the basin and the

intensity of the soil erosion. The EPM is

embedded in the algorithm of IntErO

computer-graphic method.


Climatic characteristics.The climate and

human pressure on the land in the Rastocki

Potok river basin is very variable. The area is

characterised by short, fresh, dry summers;

rainy autumns and springs, and cold winters.

The absolute maximum air temperature is

39.2OC. Winters are severe, so much so that

negative temperatures can fall to a minimum

of -27.6 OC.

The temperatures are highest on average in

July, at 20.8 °C. January is the coldest month,

with temperatures averaging -5.6 °C.

It is well well-known fact that the

precipitations and runoff are direct driving

forces of soil erosion and sediment transport.

The least amount of rainfall occurs in July

(and August). Most of the precipitation here

falls in November (Figure 2).


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Figure 2. Climate graph

The average annual air temperature, t0, is

8.9°C. The average annual precipitation, Hyr, is

873.7 mm. Temperature coefficients for the

region, T, is calculated at 0.99. The torrential

rain, hb, is calculated at 157.6 mm.

The geological structure of the area consists

mainly of Paleozoic clastic, carbonate and

silicate volcanic rocks and sediments of the

Triassic, Jurassic, Cretaceous-Paleogene and

Neogene sediments and Quaternary. In the

structural-tectonic sense, the area belongs to

the Durmitor geotectonic unit of the inner

Dinarides of Northern and North-eastern

Montenegro (Zivaljevic, 1989).

In order to define the permeability of the rocks

of the studied area we used both: the

Geological Atlas of Serbia (Dimitrijevic,

1992) and Geological Map of Montenegro

(Zivaljevic, 1989) and extracted a map of

permeability for the study area.

Figure 3: The structure of the river basin, according to bedrock permeability (fpp: medium; fo: low

permeability)

The coefficient of the region's permeability,

S1, is calculated to be 0.98. Within the studied

basin, the area with medium permeable rocks

(class fp) is 7% and the rest has poor

permeability (class fo) is 93%.

Soil characteristics of the area. According to

the results of the filed visits and

supplementary laboratory analysis, but also

using the previous research data of the project

Soils of Montenegro (1964-1988) of the team

of the Biotechnical faculty (Fustic & Djuretic,

2000), the most common soil types in the

studied river basin are: Dystric Cambisols and

Eutric Cambisols.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Figure 4: The structure of the river basin, according to the soil types

Land use. The structure of the Rastocki Potok

watershed, according to the land use is

presented in the Figure 5.

Figure 5: The structure of the river basin, according to the land use

According to our analysis, the coefficient fs,

(part of the river basin under forests) is 0.39, ft

(grass, meadows, pastures and orchards) is

0.45 and fg (bare land, plough-land and ground

without grass vegetation) is 0.16.

The coefficient of the river basin planning, Xa,

is 0.54. Of the total river basin area, related to

the river basin structure, degraded forests are

the most widespread form (25.41%). The

proportion is further as follows: Meadows,

24.72%; Plough-lands, 15.56%; Orchards and

vineyards, 13.72%; Well-constituted forests,

13.68%; Mountain pastures, 6.91%.

Soil erosion. The dominant erosion form in

the study area is sheet erosion with the

uniform detachment and removal of soil and

sediment particles from the soil surface by

overland flow and raindrop impact distributed

across slopes of the watershed. It has taken

place in all soils on slopes, being the most

pronounced on steep slopes with scarce or

denuded vegetation cover.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

We used the software IntErO to process the

input data required for calculation of the soil

erosion intensity and the peak discharge.

A complete report for the Rastocki Potok river

basin is presented in Table 1.

Table 1. Part of the IntErO report for the RastockiPotok Watershed

Input data

River basin area F 5.88 km²

The length of the watershed O 10.55 km

Natural length of the main watercourse Lv 3.24 km

The shortest distance between the fountainhead and

mouth Lm 2.97 km

River basin length measured by a series of parallel

lines Lb 4.44 km

The area of the bigger river basin part Fv 3.46 km²

The area of the smaller river basin part Fm 2.42 km²

The area between the two neighboring contour lines fiz 0.76 km²

Altitude of the first contour line h0 600 m

Equidistance Δh 100 m

The lowest river basin elevation Hmin 540 m

The highest river basin elevation Hmax 1278 m

Very permeable products from rocks fp 0

Medium permeable rocks fpp 0.07

Poor water permeability rocks fo 0.93

A part of the river basin under forests fš 0.39

Grass, meadows, pastures and orchards ft 0.45

Bare land, plough-land and ground without grass

vegetation fg 0.16

The volume of the torrent rain hb 157.6 mm

Incidence Up 100 years

Average annual air temperature t0 8.9 °C

Average annual precipitation Hyr 873.7 mm

Types of soil products and related types Y 1.2

River basin planning, coefficient of the river basin

planning Xa 0.54

Numeral equivalents of visible erosion process φ 0.28 Results:

Coefficient of the river basin form A 0.64

Coefficient of the watershed development m 0.38

Average river basin width B 1.32 km

(A)symmetry of the river basin a 0.35

Density of the river network of the basin G 0.55

Coefficient of the river basin tortuousness K 1.09

Average river basin altitude Hsr 840.01 m

Average elevation difference of the river basin D 300.01 m

Average river basin decline Isr 25.49 %

The height of the local erosion base of the river basin Hleb 738 m

Coefficient of the erosion energy of the river basin's relief Er 150.86

Coefficient of the region's permeability S1 0.98

Coefficient of the vegetation cover S2 0.75

Analytical presentation of the water retention in inflow W 1.7325 m

Energetic potential of water flow during torrent rains 2gDF^½ 186.03 m km s

Maximal outflow from the river basin Qmax 150.81 m³ s-1

Temperature coefficient of the region T 0.99

Coefficient of the river basin erosion Z 0.488

Production of erosion material in the river basin W yr 5476.8969 m³ yr-1

Coefficient of the deposit retention Ru 0.269

Real soil losses G yr 1472.09 m³ yr-1

Real soil losses per km2 G yr km² 250.39 m³ km-² yr-1


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

(A) symmetry coefficient indicates that there

is a possibility for large flood waves to appear

in the river basin. The value of G coefficient of

0.55, indicates there is medium density of the

hydrographic network.

The value of 25.49% indicates that in the river

basin prevail steep slopes. The value of Z

coefficient of 0.488 indicates that the river

basin belongs to III destruction category. The

strength of the erosion process is medium, and

according to the erosion type, it is surface

erosion.

The value of 250.39 m³ km² yr-1indicates,

according to Gavrilovic, that the river basin is

a region of very weak erosion.

Conclusion

Several factors influenced the erosion

processes in the territory of the RastockiPotok

river basin. The most significant factors are

the area’s climate, relief, geological substrate

and pedological composition, as well as the

condition of the vegetation cover and the land

use. The peak discharge (incidence of 100

years) from the river basin, Qmax, is 150.81 m³

s-1and is suggesting the possibility of a large

flood. The strength of the erosion process is

medium, and the erosion type is surface

erosion. The predicted soil losses were 1472

m³ yr-1, specific, 250m³ km-² yr-1. According to

Babic et al (2003) from the “Jaroslav Cerni”

Institute for the Development of Water

Resources (JCI), the leading research

organization in Serbia’s water sector, real soil

losses are 350 m³ km-² yr-1for the Lim river

basin. By using the IntErO software to

estimate the soil losses per km2 in 57 river

basins of Polimlje, the average value

was331.78 m³ km-² yr-1(Spalevic, 2011). This

study confirmed the findings of the other

Balkan researchers that the EPM method of

Professor Gavrilovic is a useful tool for

calculating sediment yield in the South East

Europe. EPM is embedded in the algorithm of

IntErO computer-graphic method.

Acknowledgement

This research was funded by the Ministry of

Science of Montenegro, Project: Soil erosion

processes in the Polimlje Region, Montenegro.

References

1. Barovic, G., Spalevic, V. (2015):

Calculation of runoff and soil erosion

intensity in the Rakljanska Rijeka

watershed, Polimlje, Montenegro.

Agriculture and Forestry 61(4): 109-115.

2. Blinkov I. and Kostadinov S. 2010.

Applicability of various erosion risk

assessment methods for engineering

purposes, BALWOIS 2010 Conference -

Ohrid, Republic of Macedonia. 25 - 29

May 2010.

3. Boardman, J., 2006. Soil erosion science:

reflections on the limitations of current

approaches. Catena 68, 73–86.

4. Dimitrijevic MD. 1992. Coloured map of

the Geology of Serbia, with overlay and

legend. In: Geological Atlas of Serbia, 1:

2,000,000. Belgrade: Grafimex.

5. Fustic, B. and Djuretic, G., (2000): Soils of

Montenegro. Biotechnical institute,

University of Montenegro.

6. Fustic, B. and Spalevic. V.,(2000):

Characteristics of erosion processes in the

river basinof Daspic river. Agriculture and

Forestry. 46(1-2): 5-17.

7. Gazdic, M., Pejovic, S., Vila, D., Vujacic,

D., Barovic, G., Djurovic, N., Tanaskovikj,

V., Spalevic, V. (2015): Soil erosion in the

Orahovacka Rijeka Watershed,

Montenegro. Book of Proceedings.Sixth

International Scientific Agricultural

Symposium “Agrosym 2015”.p: 1425-

1432. DOI: 10.7251/AGSY15051425G

8. Madureiraa, L., Nunesb, L., Borgesc, J.,

Falcãod, A. (2011): Assessing forest

management strategies using a contingent

valuation approach and advanced

visualisation techniques: A Portuguese case

study. Journal of Forest Economics.

Volume 17, Issue 4, December 2011, Pages

399–414.

9. Merritt, W.S., Letcher, R.A., Jakeman, A.J.

(2003): A review of erosion and sediment

transport models. Environmental Modelling

& Software 18: 761–799.

10. Paroissien, J.B., Darboux, F., Couturier, A.,

Devillers, B., Mouillot, F., Raclot, D., Le

Bissonnais, Y. 2015: A method for

modeling the effects of climate and land

use changes on erosion and sustainability

of soil in a Mediterranean watershed

(Languedoc, France). Journal of

Environmental Management 150 (2015)

57-68.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

11. Spalevic, V., Curovic, M., Barovic, G.,

Florijancic, T., Boskovic, I., Kisic, I.

(2015a): Assessment of Sediment Yield in

the Tronosa River Basin of Montenegro.

The 9th International Symposium on Plant-

Soil Interactions at Low pH.October 18-23,

2015, Dubrovnik, Croatia.


Vujacic, D., Djurovic, N. (2015b): Soil

erosion in the River Basin of KisjeleVode,

Montenegro. International conference:

Land Quality and Landscape Processes,

Keszthely, Hungary; 06/2015

13. Spalevic, V., Barovic, G., Vujacic, D.,

Bozovic, P., Kalac, I., Nyssen, J. (2015c):

Assessment of soil erosion in the Susica

River Basin, Berane Valley, Montenegro.

International Conference on Soil, Tirana,

Albania; 4-7 May, 2015.

14. Spalevic, V., Barovic, G., Mitrovic, M.,

Hodzic, R., Mihajlovic, G., Frankl, A.

(2015d): Assessment of sediment yield

using the Erosion Potential Method (EPM)

in the Karlicica Watershed of Montenegro.

International Conference on Soil, Tirana,

Albania; 4-7 May, 2015.


Vujacic, D., Tunguz, V., Djurovic, N.

(2015e): Soil erosion in the River Basin of

Provala, Montenegro. Agriculture and

Forestry 61(4): 133-143.

16. Spalevic, V., Curovic, M., Andjelkovic, A.,

Djekovic, V., Ilic, S. (2014a): Calculation

of soil erosion intensity in the Nedakusi

Watershed of the Polimlje Region,

Montenegro. International Scientific

conference: Challenges in modern

agricultural production, December 11,

2014, Skopje, Macedonia.

17. Spalevic, V., Tazioli, A. Djekovic, V.,

Andjelkovic, A., and Djurovic, N. (2014b):

Assessment of soil erosion in the Lipnica

Watershed, Polimlje, Montenegro. The 5th

International Symposium “Agrosym 2014”,

Jahorina, 23-26 October 2014, Bosnia and

Herzegovina, p 723-729.

18. Spalevic, V., Hübl, J. Hasenauer, H. and

Curovic, M. (2014c): Calculation of soil

erosion intensity in the Bosnjak Watershed,

Polimlje River Basin, Montenegro. The 5th




19. Spalevic, V., Curovic, M., Billi, P., Fazzini,

M. Frankl, A., and Nyssen, J. (2014d): Soil

erosion in the ZimPotok Watershed,

Polimlje River Basin, Montenegro. The 5th




20. Spalevic, V., Djurovic, N., Mijovic, S.,

Vukelic-Sutoska, M., Curovic, M. (2013a):

Soil Erosion Intensity and Runoff on the

Djuricka River Basin (North of

Montenegro). Malaysian Journal of Soil

Science, Vol. 17: p.49-68.

21. Spalevic, V., Curovic, M. Tanaskovik, V.,

Oljaca, M., Djurovic, N. (2013b): The

impact of land use on soil erosion and run-

off in the Krivaja river basin in

Montenegro. The First International

Symposium on Agricultural Engineering,

4th - 6th October 2013, Belgrade–Zemun,

Serbia, VI: 1-14.

22. Spalevic, V., Nyssen, J., Curovic, M.,

Lenaerts, T., Kerckhof, A., Annys, K. Van

Den Branden, J., Frankl, A. (2013c): Тhe

impact of land use on soil erosion in the

river basin Boljanska Rijeka in

Мontenegro. In proceeding of the 4th

International Symposium “Agrosym 2013”.

p. 54-63.

23. Spalevic, V., Curovic, M., Uzen, N.,

Simunic, I., Vukelic-Shutoska, M. (2013d):

Calculation of soil erosion intensity and

runoff in the river basin of Ljesnica,

Northeast of Montenegro. In proceeding of

the 24th International Scientific-Expert

Conference on Agriculture and Food

Industry, Sarajevo, Bosnia and

Herzegovina.

24. Spalevic, V. (2011): Impact of land use on

runoff and soil erosion in Polimlje.

Doctoral thesis, Faculty of Agriculture of

the University of Belgrade, Serbia, p 1-260.

25. Spalevic V., Dlabac A., Spalevic B., Fustic

B., Popovic V. (2000): Application of

computer - graphic methods in the research

of runoff and intensity of ground erosion - I

program "River basins". Agriculture and

Forestry.46(1-2): 19-36.

26. Spalevic, V. (1999): Application of

computer-graphic methods in the studies of

draining out and intensities of ground

erosion in the Berane valley. Master

thesis.Faculty of Agriculture of the

University of Belgrade, Serbia, p.1-131.

27. Xu, J. X. 2006. Effect of the changing rural

socio-economic factors on sediment yield


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

of the Jialinjiang River Basin. Journal of

Mountain Science, 24(4), 385-394..

28. Vujacic, D., Spalevic, V. (2015):

Assessment of runoff and soil erosion in

the Radulicka Rijeka Watershed, Polimlje,

Montenegro. The 6th International

Symposium Agrosym 2015, Jahorina, 15-

18 October 2015, Bosnia and Herzegovina.

29. Zivaljevic M. (1989): TumacGeoloskekarte

SR Crne Gore, 1:200 000;

PosebnaizdanjaGeoloskogglasnika, Knjiga

VIII, Titograd.


UDC 626.82


____________________________________________________________________________________________________

WATER RESOURCES PLANNING MODELING FOR EFFICIENT MANAGEMENT

OF IRRIGATION CANAL

G. Patamanska1*

Institute of Soil science, Agrotechnologies and Plant Protection, Sofia, Bulgaria

*coresponding author: [email protected]

Abstract

In the last years the spreadsheet-based models are widely applied for water resources planning and

management. In this report, a model for planning water allocation from irrigation canal is presented.

Algorithm based on the water balance which allows for allocation of available water resources of the

source according to water requirements of crops in irrigated area, considering current technological

constraints was developed and implemented in Excel environment. An existing canal was as a case

study. The spreadsheet-based model provides support for efficient management of the irrigation canal.

Keywords: irrigation canal, water allocation, planning, spreadsheet-based model

Introduction

Planning of water allocation in irrigation

canals is an important managerial activity

aimed efficient use of water for irrigation,

minimizing yield losses of the irrigated crops

due to water deficit and water stress, also

preventing over supply and the negative

outcomes such as water logging and

salinization agricultural land.

Using the optimization methods and

computers, the operation of irrigation canals

can be planned effectively. Last decades many

models based of the integer linear

programming and mixed integer linear

programming techniques have been developed

for solving the problem of optimal water

allocation in irrigation canal (Anwar et al.,

2001; Ramesh et al., 2009; Santhi et al., 2000).

By reason of certain limitations in their

formulation few of the developed models were

used for water resources planning and

management. For practical use, computer

implementation of the planning algorithms is

good to be done in an accessible manner for

use of the engineering staff in charge of

operational management of irrigation system

(Steele et al., 2010). An alternative is the

software application EXCEL, which as part of

Microsoft Office is widespread and required

basic computer knowledge.

In this paper a model for planning water

allocation from run-of-the river irrigation

canal is presented. Algorithm based on the

water balance which allows for allocation of

available water resources of the source

according to water requirements of crops in

irrigated area, considering current

technological constraints was developed and

implemented in Excel environment. The

model was validated for an existing irrigation

canal.

Material and methods

Water delivery network of the most of the

existing irrigation systems consists of main

canal, which is flowing all irrigation season

and distributaries canals, which are controlled

periodically for need of delivery of irrigation

water to its command area. As water

requirements of the agricultural crops are

varied in the different growth stages, total of

the days of the irrigation season is divided to

the equal time intervals, a length of a week or

a decade (10 days). Water distribution

schedule is prepared on any day during the

time interval that enables allocation of

available water in terms of actual irrigation

water requirements considering the

technological constraints.

Mathematical formulation of the model

The planning model works on daily basis and

10-days irrigation period. As the main canal is

feeding variable river discharge, the river flow

is measured on any day of the time period.

Available net water discharge (daily supply at


42 G. Patamanska

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

the head of main canal minus losses in main

canal) is allocated to the distributary canals to

fulfill their demands in terms of water for

irrigation of the crops.

For proper execution of the plan of water

supply of manually operated distributary

canals, it is essential that the canal operation is

to be simple. In the present operation scenario,

distributary canals will be running at full, half

or nil capacity on every day during the

irrigation period. To keep daily water balance

in the main canal one of the canals will be

running in variable supply (Ramesh et al.,

2009).

Objective function

The objective function is defined as

maximization of the total supply to the

distributary for the entire irrigation period.

Mathematical representation of the objective

is:

Max

10

1 1k

lk

N

lii

ik QQ (1)

where k = day number, N= distributary canals

number, i = the distributary canal number, l =

distributary canal with varied supply number,

Qlk= daily supply in the lth distributary canal

on kth day (m3/s), Qik= daily supply in the ith

distributary canal on kth day(m3/s).

.day kon open fully isry distributa iwhen

day kon open half isry distributa iwhen 5.0

day kon closed isry distributa i when0

thth

thth

thth

i

iik

q

qQ

where qi= capacity of ith distributary canal

(m3/s).

In daily allocation of the net available

irrigation water at the head of the main canal

to the distributaries should be kept the

following technological constraints.

Main Canal Supply Constraint

To ensure the balance of water amounts in the

main canal the sum of supplies to distributary

on any day should be less than or equal to net

daily supply in the main canal:

kvlk

N

lii

ik QQQ 1

k=1,2…….10 (2)

where Qvk=net supply in the main canal on kth

day.

Distributary canal demand constraint

The sum of daily supply of the distributaries

for the irrigation period should be less than or

equal to demand for 10– day period.

Mathematical representation of this constraint

is:

i

k

ik DQ

10

1

i =1,2,…….N

And ≠l (3.1)

and for the distributary canal with

variable supply:

10

1k

llk DQ (3.2)

where Di= demand for ith distributary canal for

10–day period (m3/s), Dl = demand for ith

distributary canal with varied supply for 10–

day period (m3/s).

Canal capacity constraint

The water supplies to canals should not exceed

the capacity of the canals on any day during

the time period.

ii

vkv

qq

QQ

max

max

(4)

where Qvmax= design capacity of the main

canal(m3/s), qmaxi=design capacity of the ith

distributary canal (m3/s).

In addition the distributary canal with variable

supply should be supplied discharge at least

equal to half design capacity to maintain

sufficient flow depth in the canal. This

limitation is expressed as follows:

llk

l qQq

max

max

2 k=1,2,……..10 (5)

These equations and constraints constitute a

mathematical model of plan of supply and

distribution of water in irrigation canal. Since

an optimization problem is formulated the

solution is an optimal water allocation plan

which enables water supply of distributaries

canals in accordance with the water

requirements of the irrigated crops.

In this study an approach to be found in Excel

environment an approximate solution for the

optimization problem (1)-(5) is adopted.

43 G. Patamanska

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Figure 1. Layoutof the main canal of "Stryama-Chirpan” Irrigation system


The spreadsheet model for operational

planning of supply and distribution of water

was developed and validated with data main

canal "Stryama-Chirpan" irrigation system

(Figure 1). The water source for this irrigation

system is the Stryama River. The main canal

works during the irrigation season from May

to October and irrigates 1,843 ha agricultural

area planted with rice, corn and vegetables.

The canal has five distributaries. Water for

rice fields is supplied by two open canals.

Three conduits are located on the canal course.

Details of the distributaries have been given in

Figure 1.

The proposed algorithm based on the water

balance was built in this table using Excel

capabilities for consecutive estimates and

available logic functions. No Visual Basic

macros were used for the model development

in Excel environment. The only macro was

designed to reset the table before any new

estimate thus provides an opportunity for

repeated use of the table. The spreadsheet

layout is shown on Figure 2.

0 кm

Р-1 2 m3

/s

Р-2 4,2 m3

/s

Р-2-1

ГВ-2 1,5 m3

/s

ГВ-4 1 m3

/s

ГВ-5 2,2 m3

/s

Legend: Р - Irrigation canal

ГВ - Conduit

44 G. Patamanska

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Figure 2.Spreadsheet layout for planning of water allocation from main canal of "Stryama-Chirpan” Irrigation

system.

The input data needed to start the calculations

are daily river discharge, minimum river flow

rate, canal losses, demands of the distributaries

canals for 10–day period (m3/s), defined on the

basis of net irrigated norms of irrigated crops.

Input data are entered in the boxes from the

table, colored in purple.

The net supply values at the head of the main

canal for any days of the irrigation period are

located in the third column of the table. In the

next columns each of the distribution canals

has a box in which the values of supply for

each day of the interval are entered. The head

cell of this box contains maximum capacity of

the distributary.

Preparation of the water allocation plan

For each day of the period initially the daily

measured value of river discharge is entered

and on its basis the net daily supply at the head

of the main canal is calculated as the

difference of measured river discharge minus

the sum of the amount of canal losses and the

minimum river flow rate. Then selection of the

operational discharges of distributary canals is

made.

When entering a value of operational

discharge of a distributary canal, the water

balance in the main channel is monitored from

the result in the cell in the last column of the

table "Canal Outflow ". In obtaining a

negative result, the supply to the canal should

be reduced or stopped.

Based on the entries of distributary canals on

any day of the period, water discharge value of

the distributary canal P-1, which is assumed to

operate at variable supply is automatically

calculated from the water balance equation

and in accordance with the restrictions (2) -

(5). Implementation of the target (1) is

monitored by calculating the deviation of

water delivery to each distributary from the

requested.

The model was tested with data for flow of the

Stryama River for the lastten days of June. At

the beginning of the period the flow rate of the

river is high 8-10 m3/s, but in the last days the

main canal can be supplied less water

discharge 5.3 m3/s The model shows how to manage

distributaries in the 10-day period to fulfill the

requests. Request of the canal P-2 is satisfied,

when it runs at maximum capacity during the

irrigation period. Request of conduits ГВ-2,

ГВ-4 и ГВ-5 are met for 3consecutive days at

work at half capacity. The obtained delivery

schedule for the canal with a variable supply is

shown on Figure 3. Its implementation does

not require frequent changes of the regulating

structure at its head. Total, the accuracy of

45 G. Patamanska

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

meeting the requests of canals is relatively

high - 4.9%. For the conduits the deviations

are greater. This is due to the fact that the

canals are oversized relative to the actual

needs of the water for irrigation. Also,

assuming that the distributaries work

completely open or half capacity brings

approach in determining the solution of the

problem for optimal operational planning.

Figure 3. Delivery schedule for the canal with a variable supply

It is appropriate to choose the days that water

will be delivered in the canals that do not work

continuously close to the dates for watering

the crops cultivated in the command area of

the distributary. In order to minimize

operational losses of the water is also

appropriate to adopt operational sequence of

distributaries canals "down-up" as the water

supply to the canal up stream can immediately

begin after stopping the supply of canal

downstream.

Conclusions

The main objective of the modeling in this

study is daily allocation of the net available

irrigation water at the head of the main canal

to the distributaries in accordance with water

requirements and technological constraints.

The model developed was validated for

existing irrigation canal. Its use for preparation

a schedule for distribution and supply of water

in the irrigation canal does not create

particular difficulties and satisfactory results

were obtained. The spreadsheet-based model

can provide support for efficient management

of the irrigation canal.

References

Anwar A., Clarke D., (2001). Irrigation

Scheduling Using Mixed-Integer Linear

Programming, Journal of Irrigation and

Drainage Engineering, 127(2), pp. 63-69.

Ramesh R., Venugopal K., Karunakaran K.

(2009).Zero One-programming model for

Daily Operation Scheduling of Irrigation

Canal, Journal of Agricultural Science, 1(1).

Santhi C., Pundarikanthan V.N. (2000). A

New Planning Model for Canal Scheduling of

Rotational Irrigation. Agricultural Water

Management, Vol. 43, pp. 327-343.

Steele, D.D., Scherer T.F., Hopkins D.G.,

Tuscherer S.R., Wright J. (2010).Spread shee

timplementation of irrigation scheduling by

the checkbook method for North Dakota and

Minnesota. Appl. Engr. Agric.26(6) pp. 983-

995.


UDC 712.25(498)


____________________________________________________________________________________________________

THE MANAGEMENT AND CAPITALIZATION OF THE LANDSCAPING

POTENTIAL OF THE CRUCII SQUARE FROM TIMISOARA CITY

C. Berar 1*, M. Silivasan1, E. Pet1, A. Groszler1, C. Tota1, D. Camen1 1Banat’s University of Agricultural Sciences and Veterinay Medicine

“King Michael I of Romania” from Timisoara


Abstract

The Crucii Square is situated in the Elisabetin district in the city of Timisoara, in a residential area.

According to a map from 1849, the current Crucii Square is situated on the very line of the building

injunction circle around the fortress of Timisoara. The square name originates from an old cross

which was preserved until today. Taking into the age of the oldest trees, the square was set as a green

space after 1920. The current landscaping consists in tracing and slabbing the allies and building a

new hero monument, also dates from after 1920. The square’s surface is of 6255mp. In the present

paper we carried out an estimate of the green space and determined the current vegetation state, since

green cadastre is the only way to determine the real state of green spaces belonging to a city’s

patrimony, including parks and squares as well as the entire street vegetation (Ciupa et al., 2005). The

paper‘s character is thus that of a vegetation fund inventory, as well as organisational design based on

ecologic and landscaping criteria. The paper also comprises a square landscaping proposal,

highlighting the site’s historic character and the high vegetation value.

Key words: Crucii Square, green cadastre, identification, capitalization, management

Introduction

The existence of a green cadastre in a big city

is indispensable for a modern approach of the

optimal relation issue, of ecologic and social

nature, between a city’s manager and its

inhabitants. It is the only way to get to know

the reality of green spaces which enter a city’s

patrimony, including parks as well as the

entire street vegetation. It is also the only way

to properly manage, from a technical as well

as economic point of view, this important city

component.


For each woody vegetation element identified

in the field according to its position in the

plan, after the topographic determinations, the

following characteristics have been collected

and registered in code as follows (Primaria

Municipiului Timisoara, 2001):

1. Identification number corresponding to the

one in the plan –NRI.

2. Scientific name – SPE.

3. Age – VIR: 1– 10 years – code 11; 11– 20

years – code 12; 21– 40 years – code 20; 41–

60 years – code 30; 61– 80 years – code 40;

81–100 years – code 50; over 100 years – code

60.

4. Height classes – INA: 1 - 1 – 5 m; 2 - 6 –

10 m; 3 - 11 – 15 m; 4 - 16 – 20 m; 5 - 21 - 25

m; 6 - 26 – 30 m; 7- 31 – 35 m.

5. Crown diameter – DCO.

6. Crown structured (standard) volume – VRE.

7. Ecologic value – VAE.

Tree and shrub ecologic value is determined

by their influence on the surrounding areas’

physical-climatic factors. This influence

depends directly especially on the tree and

shrub crown, respectively on its volume and

branch and leaf density. The effects of the tree

and shrub crown reflect on the following

climatic elements: solar energy absorption;

atmospheric turbulence – wind intensity

reduction; CO2 absorption; oxygen emission;

filter effect on the solid particles from the

atmosphere; negative ion emission; phytoncide

emission; phonic isolation.

In order to determine this relative structured

volume, we can use the following formula:

Ecologic value = crown volume x crown

density indices


47 C. Berar , M. Silivasan, E. Pet, A. Groszler, C. Tota, D. Camen

______________________________________________________________________________________________________________________________________________________

JAFES, Vol 69, (2016)

As a maximum crown density index, with the

value 1, one may take the de sycamore, linden,

spruce, fir crown one. For all other species,

this index is established by estimation, its

minimum possible value being 0.5.

For the efficiency in the ecologic value

expression, absolute values are grouped as

follows: standard crown value 2 mc - cod

1; 2,1 - 10 mc - cod 2; 10,1 - 20 mc - cod 3;

20,1 - 40 mc - cod 4; 40,1 - 80 mc - cod 5;

over 80,1 mc - cod 6.

8. Landscaping value –VPE.

The landscaping value is an element of high

importance in characterizing the park’s woody

vegetation. The park’s recreational and

educational function is fully correlated with

this value.

This value generally depends on three

characteristics: general species physiognomy

in singular port; the specimen’s height, crown

and trunk, which depend especially on the age;

trunk anomalies such as: tree forks, twisting

etc. Regarding the general species

physiognomy, the following are basic

elements: general crown shape, leafage and

structure, leaf colour, including its variation in

time, blooming, remnant fructification.

Another basic characteristic is the specimen’s

size which impresses through its grandeur and,

implicitly, through the specimen’s age

estimation. Anomalies impress because of

their rarity and singularity. From these

characteristics, the last two have a permanent

character, while the first presents a

conjunctural, dynamic character and thus of a

variable impressive value. Resineferous trees

are the exception, for whom this characteristic

is permanent, thus increasing their value.

The landscaping estimation stages used in the

project are: Very low – code 1; Low – code 2;

Medium – code 3; High – code 4; Very high –

code 5; Exceptional – code 6 .

9. Global value – VGL. It is established by the

computer using the formula: VGL = VAE x

VIT x VPE

This value may vary between 0 when the

vitality is 0 – dried tree and 108, at maximum

values (VAE = 6; VIT = 3; VPE = 6). The

maximum value is encountered very rarely, as

in the example of a monumental sycamore

forest. This global value bears a special

significance for the establishment of a park’s

importance, or for the establishment of

penalties in the case of some element

destruction.

10. Proposed works.

Several works are foreseen: intact maintenance

— code 1; toileting, pruning — code 2; dry

extraction — code 3; biologically inadequate

extraction — code 4; landscaping inadequate

extraction — code 5.


31 species have been identified, which

represent a quite high variety for the square

surface. The resineferous proportion is of 20%,

and the shrub’s also of 20%. From this aspect,

the structure is relatively close to that of a

park. The high young specimen number, under

20 years, representing 83%, determine a rather

high density: 193 specimens / ha. There are

also some older specimens, even above 80

years, proving just how old the landscape is.

. Picture 1. Crucii Square – Google Earth view


______________________________________________________________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Picture 2. Crucii Square – current situation plan

The cover index is reduced, 24%, and the

ecologic layer thickness carries a medium

value of 0.80 m. The square is designed in a

mixed style. As elements of a regular style,

one can mention: the regular and somewhat

symmetrical style of the alley network, the

execution of a central focal point,

“monumental – cross”, towards which the

perspective of most alleys tends, bench

alignment, facing towards the central focal

point, the central high vegetation placement,

thus achieving a premises effect. All in all, the

square displays a balanced design and achieves

a valuable impressive effect. Due to lack of

space, in Table 1 is presented trees and shrubs

description inventory only for 40 specimens

out of a total of 191.

Table 1. Trees and shrubs description inventory

No Species denomination Age

class Height

Crown

diam.

Struct.

volume

Ecol.

value

Landsc.

value

Proposed

works

1 AESCULUS HIPPOCASTANUM 40 3 6.0 135.68 6 4 1

2 ABIES ALBA 12 1 1.0 0.56 1 3 1

3 SPIRAEA VANHOUTTEI 12 1 3.0 11.28 3 2 1


5 SPIRAEA VANHOUTTEI 12 1 2.0 5.04 2 2 1

6 ROBINIA PSEUDOACCACIA 11 1 2.0 2.17 2 1 1




10 FRAXINUS AMERICANA 20 2 7.0 107.73 6 3 1

11 ABIES ALBA 12 1 1.0 0.64 1 3 1


13 ACER NEGUNDO 40 3 9.0 228.90 6 4 1

14 PICEA ABIES 30 3 3.0 21.18 4 4 1



17 ABIES ALBA 12 1 1.0 0.64 1 3 1

18 THUJA ORIENTALIS 20 1 0.8 0.80 1 4 1

20 PRUNUS CERASIFERA 11 1 1.0 0.35 1 1 1

21 BETULA VERRUCOSA 11 1 0.6 0.18 1 1 1

22 THUJA ORIENTALIS 20 1 1.0 1.28 1 3 1

23 ACER PLATANOIDES 12 2 4.0 17.57 3 2 1


______________________________________________________________________________________________________________________________________________________

JAFES, Vol 69, (2016)

24 PINUS STROBUS 12 2 2.0 7.52 2 4 1


26 JUGLANS REGIA 12 2 5.0 47.10 5 2 1


28 ACER NEGUNDO 40 2 7.0 103.86 6 4 1

29 JUGLANS REGIA 20 2 5.0 78.48 5 3 1










39 ABIES ALBA 12 1 1.0 0.56 1 3 1


Table 2. Centralizing species situation – specimen no. and crown surface

Centralizing species situation – specimen no. and crown surface

No. Species denomination Crown surface

Specimen no.

1 ABIES ALBA 3.140 4

2 ACER NEGUNDO 228.435 5

3 ACER PLATANOIDES 43.175 7

4 AESCULUS HIPPOCASTANUM 364.240 11

5 BETULA VERRUCOSA 12.843 2

6 CATALPA BIGNONIOIDES 22.765 3

7 DEUTZIA SCABRA 31.400 13

8 FORSYTHIA INTERMEDIA 5.495 4

9 FRAXINUS AMERICANA 164.065 7

10 FRAXINUS EXCELSIOR 445.095 13

11 JUGLANS REGIA 39.250 2

12 JUNIPERUS SQUAMATA MEYERI 0.785 1

13 LONICERA FRAGRANTISSIMA 10.990 3

14 PHILADELPHUS CORONARIUS 8.831 6

15 PICEA ABIES 28.260 4

16 PINUS NIGRA 43.960 6

17 PINUS STROBUS 20.410 8

18 PINUS SYLVESTRIS 25.120 2

19 PLATANUS ACERIFOLIA 63.585 1

20 PRUNUS CERASIFERA 87.920 5

21 PRUNUS PISSARDI 45.530 4

22 ROBINIA PSEUDOACCACIA 230.005 41

23 SALIX MATSUDANA 69.865 2

24 SAMBUCCUS NIGRA 12.560 1

25 SPIRAEA VANHOUTTEI 13.345 3

26 TAXUS BACCATA 25.120 6

27 THUJA OCCIDENTALIS 0.785 1

28 THUJA OCCIDENTALIS

AUREO-VARIEGATA 0.785 1

29 THUJA ORIENTALIS 4.427 3


______________________________________________________________________________________________________________________________________________________

JAFES, Vol 69, (2016)

30 TILIA CORDATA 127.170 5

31 TILIA PLATYPHYLLOS 58.090 2

TOTAL 2237.446 176.000

Proposal for the re-landscaping of the

Crucii Square

The landscaping way aims to fulfil the

following functions: social, decorative, and

recreational. The decorative or aesthetic

function will be achieved through material

alternation, succession, chromaticity as well as

various textures, in vertical as well as

horizontal plain turning the park into a living

mechanism in continual transformation.

Picture 3. Top view proposal

The decorative function is supported by the

usage of dendrologic material already existent

which forms a „curtain", conferring the space

an intimacy nuance. The vegetation influence

is directly or indirectly reflected in the

people’s health. Air purity, lower day or

season temperature amplitudes or the tree

shadow exercise a direct physical-sanitary

action on the organism, while the line, shape

and colour harmony, the aesthetic tree, shrub

and flower grouping enchant the eye, creating

a positive state of mind which, in its turn,

positively influences the general state of mind.

Through oxygen production and carbon

dioxide consumption, the vegetation,

especially the woody one, contributes to the

obvious air composition improvement,

insuring life maintenance. Today, we

acknowledge the fact that negative ions have a

positive influence on the psyche. Their

presence is insured by natural ionizing factors,

by ion generators, alongside which the woody

vegetation, through the photosynthesis

process, contributes to a large extend to air

ionization. Also, the sharp points of the leaf

needles facilitate, under certain atmospheric

conditions, electricity discharge in the soil.

Picture 4. 3D perspective

Through subtle means like colour and shape

harmony, suave perfumes, leaf murmuring,

fragile grace or impressive firmness, life pulse

in every leaf, flower, branch, the vegetation

touches people’s sensitivity, positively

influencing their psychological tonus (Iliescu,

2003). It is known that people’s health is

influenced not only by environmental balance,

but also by compensating the physical and

intellectual effort and nervous strain through

recreational activities (Florincescu, 1999). For

city inhabitants, the open air recreation option

is conditioned by the necessary moving time,

the movement facilitation, the landscape

organization and design, their natural

ambiance etc. The benches introduced in the


______________________________________________________________________________________________________________________________________________________

JAFES, Vol 69, (2016)

landscape will be placed in the centre focal

area but also on the entire alley length. There

will be an adequate garbage bin number and

the lighting will also be optimal. There shall

be easy access, all alleys being traced in a

hierarchical order (secondary alleys flowing

into main alleys). The composition is unitary,

coherent and simple.

Picture 5. 3D perspective

The harmony is achieved by identity, as well

as resemblance, and the succession of certain

elements is accomplished by logical order,

harmonizing the various spaces complex.

Within this landscape the harmonious

combination of simplicity and variety was

achieved. The visitor perceives the space as a

unitary whole. The proportionality principle is

especially highlighted by the use the individual

scale so as to offer visitors heightened comfort

impression and to eliminate the overwhelming

element sensation. The space must offer a

welcoming place that is why where elements

were designed on an individual scale. The

rhythm is differentiated by means of various

dimension circle usage, even though it may

create monotony. Due to the fact that the

elimination of the existing vegetation was

avoided as much as possible, as well as the

fact that local, rustic plants were integrated in

the landscape, from the start conditions were

created for the plant biologic potential

achievement as well as the harmonious

development of all existing species. From a

technical point of view, we adopted solutions

to satisfy movement safety and comfort

requirements, but which are simultaneously

aesthetic and harmonizing with other

landscape elements. For the landscaping, we

used natural elements instead of manufactured

ones, as well as the maximum capitalization of

the terrain possibilities, function adaptation

and the establishment of the equipment in

relation with the previous elements,

interweaved with the compositional and

aesthetic organization. The landscape can be

accessed through four entrances. The alleys

follow itineraries linking the main interest

focal point (compositional centres, entrances,

objectives). They are of various widths. Their

functional role is organically intertwined with

their compositional importance. The

landscaping needs to encompass circulation

itineraries which firstly answer some

functional requirements such as insuring

visitor access to well-chosen points, leading

visitors to several areas fulfilling various

functions, connecting objectives included in

every part of the landscape, insuring

movement comfort and influencing traffic on

drive areas. Species proposed for the

landscaping: trees (Tilia tomentosa, Acer

palmatum, Populus tremula, Quercus rubra,

Acer saccharineum, Citrus bergamia, Fagus

grandifolia), shrubs (Sambucus cerulea,

Lonicera caerulea, Hibiscus rosa-sinensis,

Chaenomeles superba Texas Scarlet), flower

plants (Coreopsis gigantea, Anagallis

arvensis, Aster alpinus, Centaurea cyanus, Iris

croatica, Petunia hybrida, Impatiens new

guinea, Aster amelus).

Conclusions

The following works are foreseen: toileting

and pruning, dried branch cutting, extraction

of the dried specimens, as well as of the

inadequate ones, from a biological and

landscaping point of view, the execution of a

minimum of 4-5 mowing in summer, with

immediate grass collecting. On surfaces where

the carpet density is reduced, we propose

either the rehabilitation of the entire vegetal

carpet, or the execution of Lolium perene over-

seeding. The following maintenance works are

deemed necessary: alley repairing, repairing or

replacing deteriorated benches, garbage bin

supplementing.


______________________________________________________________________________________________________________________________________________________

JAFES, Vol 69, (2016)

References

Ciupa V., Radoslav R., Oarcea C., Oarcea Z.

(2005). Timisoara verde – sistemul de spatii

verzi al Timisoarei. Editura Marineasa.

Timisoara. pp. 116-117.

Florincescu Adriana (1999). Arhitectura

peisajului. Editura Divya. Cluj-Napoca. pp.

69-80.

Iliescu, Ana-Felicia (2003). Arhitectura

peisagera. Editura Ceres. Bucuresti pp. 189-

247.

Primaria Municipiului Timisoara (2001).

Cadastrul Verde al Primariei Municipiului

Timisoara. Editura Brumar. Timisoara pp. 37-

52.


UDC 631.526.4(497)


__________________________________________________________________________________________

PLANT GENETIC RESOURCES FROM THE BALKAN PENINSULA IN THE

WORLD’S GENEBANKS

H. Knüpffer*

Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr. 3, D-

06466 Stadt Seeland, Germany


Abstract

An overview is given of plant genetic resources that originate from countries of the Balkan Peninsula

and are preserved in genebanks worldwide. For each country, the number of genebanks holding ma-

terial from this country, and the number of accessions are presented. A summary is also provided by

crops (scientific names). The survey is based on databases such as FAO WIEWS (World Information

and Early Warning System), EURISCO (European search catalogue for plant genetic resources), and

Genesys (worldwide database on plant genetic resources).

Key words: genebanks, Balkan Peninsula.

Introduction

The Balkan Peninsula, also called the Balkans,

is considered to include Albania, Bosnia and

Herzegovina, Bulgaria, Croatia, Greece,

Kosovo, the Republic of Macedonia,

Montenegro, Serbia, Slovenia, Romania, and

the European part of Turkey. For the present

study, we exclude the European part of Turkey

(which is difficult to distinguish from Turkey

as a whole by the data accessible through the

sources used), and additionally include the

Republic of Moldova.

According to the FAO World Information and

Early Warning System (WIEWS), the total

number of genetic resources accessions

preserved in genebanks worldwide is

7,199,179 (WIEWS 2015). Of these, 126,230

accessions (or 1.8 percent) are originating

from countries of the Balkan Peninsula. Based

on data from three international information

systems on plant genetic resources, namely,

WIEWS, EURISCO and Genesys (details see

below), we present information on the number

of accessions originating from each of the

Balkan countries, their distribution across

genebanks worldwide, and their taxonomic

composition (major species and genera).

For individual countries of the Balkan region,

similar overviews have been carried out (e.g.

Knüpffer 2010a, b for Greece), and for

Albania, the composition of the genetic

resources collections was studied (Gixhari et

al. 2013), but for the complete Balkan region,

this is the first study of its kind.


There are three international online databases

available that contain data relevant for this

study.The following databases were searched

in September 2015: WIEWS (WIEWS 2015),

Genesys (a worldwide database on plant

genetic resources; Genesys 2015), and

EURISCO (European search catalogue for

plant genetic resources; EURISCO 2015).

WIEWS gives summary information on

germplasm preserved in genebanks worldwide;

the data were last updated between 1984 and

2014 (the majority in 2008 and 2009). Genesys

includes accessions from EURISCO

(transferred on request), the genebanks of the

CGIAR centres, and the USDA genebank. The

majority of records related to Balkan-origin

accessions were last updated in April, and

some in September 2015. Data in EURISCO

are being updated whenever a National Focal

Point (person authorizedto collect data within

the country and to upload them to EURISCO)

updates the respective National Inventory.

For the same holding institution (genebank),

data in Genesys are generally more up-to-date

than in WIEWS, and even more so in

EURISCO, since Genesys is receiving

EURISCO data from time to timeon request.


54 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

A selection was made for accessions

originating from any of the Balkan countries,

and relevant data fields were extracted or

calculated, i.e. number of accessions, holding

genebank, genus, species, country of origin,

status of sample, source of information, and

date of last update of the information. These

data were transformed into the same format

and combined into a single table. For

genebanks appearing in more than one of the

databases, only the most recent data were

used.

Holding institutions are coded by FAO

institution codes downloadable from the FAO

WIEWS website (FAO 2015). An institution

may receive a new code if its name or

affiliation changes; thus the same institution

may occur under different codes. By taking

this into account, the number of different hold-

ing genebanks of Balkan material was reduced

from 359 to 345, and the total number of

accessions reported from 135,359 to 126,230.

There may be institutions that do not exist any

longer, but are still documented in WIEWS.

This is known to be the case in Albania (all

genetic resources collections have been

transferred recently to the centralized Albanian

genebank).

Scientific namesare a problematic issue in

databases, especially when the information is

compiled from a large number of different

sources (Hintum and Knüpffer 2010).

Therefore, they were checked for major

problems (format, contents of the field, and

spelling). The resulting list of names was sub-

mitted for analysis to the “List matching

service” of the Catalogue of Life (CoL 2015),

which returns for each scientific name its

status (e.g. accepted or synonym), and lists

unidentifiable names. Synonyms and

unidentifiable names were checked against the

taxonomic system of GRIN (USDA Genetic

Resources Information Network) (GRIN

2015). Thus, the number of different genus

names could be reduced from 752 to 697, and

the number of different species names

(combinations of genus and species) from

2,748 to 2,415. Names not found in GRIN

taxonomy were generally left unaltered.

Therefore, the number of different genera and

species reported is likely to be slightly biased

(too large).

Countries of origin. “Yugoslavia” is still

reported in many records as country of origin;

this could not be resolved into the single

follower-countries. In addition, the FAO

WIEWS database often combines material

from different countries into a single record,

without indicating the number of accessions

for each of the countries. The records

containing Balkan countries (together with

others) refer to a total of more than 13,000

accessions in 15 genebanks. Such records were

excluded from the statistics.


Overview by holding genebanks and countries

Germplasm from the Balkans is reported tobe

held in a total of 345 genebanks in 61

countries. The genebanks holding the largest

collections of this material are located in

Bulgaria, Romania and Germany. Genebanks

with more than 200 Balkan-origin accessions

are shown in Table 1. Some countries have

more than one genebank; countries holding the

largest numbers of accessions of Balkan origin

are Romania, Bulgaria, USA, Australia and

Germany. Countries holding more than 200

such accessions are listed in Table 2.

Table 3 shows the countries of the Balkan

region, and the numbers of accessions

conserved in genebanks worldwide from each

of these countries. There are approximately

30,000 accessions each from Romania,

Bulgaria and Greece, followed by ca. 9,700

accessions from former Yugoslavia (present

country not specified). Material from Kosovo

(79 accessions) is reported by a single

genebank in the U.S.

In Table 4, the total numbers of germplasm

accessions held by genebanks in the Balkan

countries are compared with the numbers of

accessions originating from the holding

countries. In Albania, Croatia, Greece,

Montenegro, and Slovenia, more than 75

percent of the accessions originate from the

holding country.

Overview by status of the samples

According to the sample status, the germplasm

from the Balkans can be divided into various

categories, including wild, weedy forms,

landraces, advanced cultivars, and other

categories (cf. Table 5). The largest proportion

of the Balkan material belongs to traditional

cultivars and landraces, followed by breeding

or research material (with several

subcategories).

55 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

For more than 17,000 accessions, the status is

unknown or not stated.

Taxonomic composition of plant genetic

resources from the Balkans

With respect to the taxonomic composition,

the germplasm from the Balkan Peninsula

belongs to 697 genera (Table 6) and 2,415

species (Table 7). These are likely to be slight

overestimates, since some of the synonyms

may not have been resolved. In fruit trees, for

example, the genus Prunusas well as a number

of smaller genera such as Amygdalus,

Armeniaca, Cerasus, Persica and others be-

longing to the same taxonomic group, were

reported as separate genera in the databases –

they were brought together under Prunus. In

addition, scientific names given at the level of

genus (e.g. Triticum sp.) are counted as

separate species. For 57 accessions, even the

genus name is not known (reported as

“unidentified” or “unknown”).

The most highly represented genera are

Triticum, Zea, Phaseolus, Hordeum, and

Trifolium (Table 6). At the species level, Zea

mays, Triticum aestivum, Phaseolus vulgaris,

and Hordeum vulgarehave the largest numbers

of accessions (Table 7).

Conclusions

Overviews of genetic resources material

originating from a particular country or region

provide a first indication of the wealth of crop

plant species and their wild relatives, and they

may assist in identifying gaps (need for further

collecting). They may also be a good starting

point for compiling checklists of cultivated

plant species (and possibly their wild relatives)

for certain areas, as has been shown by us for a

number of countries such as Italy (Hammer et

al. 1992, 1999).

The study was based solely on the three

databases, which have different geographical

scopes (from worldwide to European), and

which differ in their up-to-dateness. Therefore,

some recent changes may not have been

reflected. It is known that in some countries of

the Balkans, not all genetic resources

collections are completely included in

EURISCO, for example, in Bulgaria (N.

Velcheva, pers. comm., June 2015) or Mace-

donia (S. Ivanovska, pers. comm., October

2015). Thus, contacting the curators of the

individual genebanks of the Balkan countries,

and those of other genebanks known to have

Balkan material, may have resulted in more

precise figures.

Acknowledgements

I am grateful to the organisers of the

2ndInternational Symposium for Agriculture

and Food in Ohrid, Republic of Macedonia, 7-

9 October 2015, for providing the possibility

to present this topic. I want to thank my

colleagues Stephan Weise and Markus

Oppermann for critical reading of the manu-

script, and for valuable comments.

References

1. CoL (2015) Catalogue of Life. List

matching service.

http://www.catalogueoflife.org/listmatching

/ – accessed October 2015

2. EURISCO (2015) European search

catalogue for plant genetic resources.

http://eurisco.ecpgr.org– accessed

September 2015

3. FAO (2015) FAO Institution Codes.

Downloaded from

http://www.fao.org/wiews-

archive/wiewspage.jsp?i_l=@@&show=D

ownloadinstEN.jsp – accessed October

2015

4. FAO/Bioversity (2012) FAO/Bioversity

Multi-Crop Passport Descriptors.Version 2.

June 2012.

5. http://www.bioversityinternational.org/filea

dmin/user_upload/online_library/publicatio

ns/pdfs/FAO

6. Bioversity_multi_crop_passport_descriptor

s_V_2_Final_rev_1526.pdf – accessed

October 2015

7. Genesys (2015) Genesys – the Global

Gateway to Genetic Resources.

https://www.genesys-pgr.org– accessed

September 2015

8. Gixhari B, Ismaili H, Lashi F, Ibraliu A,

Dias S (2013) Diversity of Albanian plant

genetic resources inventory assessed by

EURISCO passport descriptors. Alban J

Agric Sci 12:741-746

9. GRIN (2015) GRIN [Genetic Resources

Information Network] Taxonomy for

Plants. http://www.ars-grin.gov/cgi-

bin/npgs/html/queries.pl – accessed

October 2015

10. Hammer K, Knüpffer H, Laghetti G,

Perrino P (1992) Seeds from the past. A

catalogue of crop germplasm in South Italy

http://www.ars-grin.gov/cgi-bin/npgs/html/queries.pl%20–%20accessed%20October%202015



56 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

and Sicily. Institut für Pflanzengenetik und

Kultur pflanzenforschung, Gatersleben,

Germany; Istituto del Germoplasma, Bari,

Italy. ii+173 pp.

11. Hammer K, Knüpffer H, Laghetti G,

Perrino P (1999) Seeds from the past. A

catalogue of crop germplasm in Central and

North Italy. IPK Gatersleben, Germany;

Germplasm Institute of C.N.R., Bari,

Italy.iv+255 pp.

12. Hintum T van, Knüpffer H (2010) Current

taxonomic composition of European

genebank material documented in

EURISCO. Plant Genet Resour 8:182-188

13. Knüpffer H (2010a) Plant genetic resources

from Greece preserved in the German

Genebank in Gatersleben, with emphasis on

Hans Stubbe’s Balkan collections in 1941-

1942. In: Proc 12th Panehellenic Congr,

Hellenic Sci Soc Plant Breed & Genet, 8-10

Oct2008, Naoussa, Greece, pp16-29 (on

CD-ROM)

14. Knüpffer H (2010b) The Balkan collections

1941-1942 of Hans Stubbe in the

Gatersleben Genebank. Czech J Genet

Plant Breed 46 (Special Issue): S27–S33

15. WIEWS (2015) FAO World Information

and Early Warning System for Plant

Genetic Resources.

http://www.fao.org/wiews-

archive/germplasm_query.htm?i_l=EN –

accessed September 2015

57 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Tables

Table 1. Genebanks (FAO institution codes, explained below) holding more than 200 germplasm accessions of Balkan origin, and number of accessions per country

of origin. ALB — Albania, BIH — Bosnia and Herzegovina, BGR — Bulgaria, HRV — Croatia, GRC — Greece, XKX — Kosovo (not an official FAO country

code), MKD — Macedonia, MNE — Montenegro, MVA — Moldova, ROU — Romania, SRB — Serbia, SVN — Slovenia, YUG — (former) Yugoslavia

Accs Holding institution Country of origin

ALB BIH BGR HRV GRC XKX MKD MNE MVA ROU SRB SVN YUG

13602 Institute for Plant Genetic Resources “K. Malkov”,

Sadovo, Bulgaria

9 — 12408 — 149 — 10 — 9 559 — 24 434

11050 Suceava Genebank, Romania — — 78 — 18 — — — 39 10859 — — 56

8227 Leibniz Institute of Plant Genetics and Crop Plant

Research (IPK), Gatersleben, Germany

1051 — 1723 522 2835 — 10 — 21 1453 2 8 602

5641 N. I. Vavilov Institute of Plant Production, St. Pe-

tersburg, Russian Federation

42 49 1919 68 271 — 25 8 1589 742 — 32 896

5638 International Centre for Agricultural Research in the

Dry Areas (ICARDA), Aleppo, Syria

67 46 952 59 3385 — 338 42 85 463 93 — 108

4823 National Small Grains Germplasm Research Facility,

USDA-ARS, Aberdeen, Idaho, USA

36 292 375 135 919 — 1407 259 9 — 1391 — —

4774 Greek Genebank, Thessaloniki, Greece 2 — 13 — 4701 — — — — — — — 58

3910 Australian Medicago Genetic Resources Centre,

Adelaide, Australia

— — 241 — 3400 — — — — 113 — 2 154

3553 Plant Genetic Resources Center, Tirana, Albania 3443 — 53 — 42 — 5 — — 10 — — —

2823 Plant Gene Resources of Canada, Saskatoon, Canada 32 82 304 79 1462 — 458 — 22 336 — 48 —

2597 Institute for Agrobotany, Tápiószele, Hungary 12 — 534 3 93 — — — 2 1491 1 1 460

2377 Gene Bank, Prague-Ruzyne, Czech Republic 19 1 742 109 232 — 7 1 35 475 43 146 567

2330 Western Regional Plant Introduction Station, USDA-

ARS, Pullman, Washington, USA

87 78 965 42 1017 — 63 29 13 — 36 — —

2328 Maize Research Institute “ZemunPolje”, Belgrade,

Serbia

— 324 61 285 29 — 221 — — 25 — 103 1280

2228 Millennium Seed Bank Project, Royal Botanic Gar-

dens, Kew, Wakehurst Place, UK

— 48 761 37 1111 — 53 11 — 31 12 164 —

2225 Faculty of Agriculture, University of Zagreb, Croatia — 96 — 2124 — — 4 — — 1 — — —

2214 Research Institute for Cereals and Technical Plants

Fundulea, Romania

— — 167 — 25 — — — 33 1911 — — 78

2030 Australian Temperate Field Crops Collection,

Horsham, Victoria, Australia

21 5 605 10 1160 — 6 — 25 44 — 1 153

58 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)



1976 Australian Trifolium Genetic Resource Centre, South

Perth, Australia

— — 65 — 1835 — — — — 7 — — 69

1832 Dobrudja Agricultural Institute, General Toshevo,

Bulgaria

— — 1829 — — — — — — 3 — — —

1828 Institute of Plant Production “V. Y. Yurjev”,

Kharkiv, Ukraine

6 — 573 80 36 — — — 417 389 19 4 304

1775 Plant Breeding and Acclimatization Institute,

Radzików, Poland

128 — 567 12 251 — 34 — 161 388 3 2 229

1560 Agricultural Institute of Slovenia, Ljubljana, Slove-

nia

— — — — — — — — — — — 1560 —

1545 Faculty of Agriculture, University Ss. Cyril and

Methodius, Skopje, Macedonia

19 — 120 8 11 — 1086 — 1 1 — 6 293

1217 Agricultural Research Station Simnic-Dolj, Romania — — 3 — — — — — 5 1208 — — 1

1141 Plant Production Research CenterPiešťany, Slovakia 1 — 467 32 65 — — — 50 255 6 35 230

1092 Fruit Growing Research Institute Mărăcineni-Argeş,

Romania

— — 56 — 4 — — — 7 982 — — 43

1016 Centro Internacional de Agricultura Tropical (CIAT),

Cali, Colombia

— 10 514 4 41 — 420 — 4 15 — — 8

949 Satellite Collections North of IPK, Oil and Fodder

Crops, Malchow, Germany

27 — 262 169 52 — — — 3 399 — — 37

851 Asian Vegetable Research Development Center,

Taiwan

— — 177 — 19 — — — 3 — — — 652

805 Australian Winter Cereals Collection, Tamworth,

Australia

29 — 121 15 209 — — — — 96 — — 335

780 Agricultural Research Station PoduIloaiei-Iași, Romania

— — 3 — — — — — 5 770 — — 2

739 Agricultural Research Station Suceava, Romania — — 1 — 3 — — — 12 721 — — 2

663 University of Agricultural Sciences and Veterinary

Medicine,Timișoara, Romania

— — — — — — — — — 663 — — —

652 North Central Regional Plant Introduction Station,

USDA-ARS, Ames, Iowa, USA

37 22 114 17 164 — 269 4 17 — 8 — —

633 Ustymivka Experimental Station of Plant Production,

Ukraine

4 — 229 1 56 — 1 — 159 49 10 2 122

617 Agricultural Research Station Turda-Cluj, Romania — — 12 — 1 — — — 7 595 — — 2

59 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)



608 Department of Applied Genetics, John Innes Centre,

Norwich, U.K.

— — 54 12 100 — — — — 63 — — 379

596 Department of Genetic Resources I, National Insti-

tute of Agrobiological Sciences, Tsukuba, Japan

— — 132 1 45 — — — — 90 — — 328

583 Western Australia Department of Agriculture, South

Perth, Australia

— — 4 — 575 — — — — — — — 4

567 Vine Institute, National Agricultural Research

Foundation, Lykovrissi, Athens, Greece

— — — — 567 — — — — — — — —

527 Medicinal and Aromatic Plants Research Station

Fundulea, Romania

1 — 13 — — — — — 27 482 — — 4

503 Centre for Genetic Resources The Netherlands, Wa-

geningen, Netherlands

4 1 138 7 99 — 25 — 17 59 42 15 96

492 Centro Internacional de Mejoramiento de Maíz y

Trigo (CIMMYT), México, Mexico

4 3 41 — 324 — 6 1 1 35 6 — 71

474 Genetic Resources Unit, Aberystwyth University,

U.K.

— 10 127 8 121 — 1 — — 101 — 10 96

439 Institute of Vegetable and Melon Growing, S. Sel-

ektsiine, Kharkivs’ka obl., Ukraine

1 — 50 — 4 — — — 336 19 — — 29

437 Fruit Growing Research Station Băneasa-Bucureşti,

Romania

— — 2 — 1 — 46 — 8 377 — — 3

435 Fruit Growing Research Station Constanța, Romania — — 12 — 10 — 5 — 22 383 — — 3

429 Plant Genetic Resources Conservation Unit, Southern

Regional Plant Introduction Station, University of

Georgia, USDA-ARS, Griffin, Georgia, USA

11 6 179 13 176 — 37 1 3 — 3 — —

428 Northeast Regional Plant Introduction Station, Plant

Genetic Resources Unit, USDA-ARS, New York

State Agricultural Experiment Station, Cornell

University, Geneva, New York, USA

12 2 66 1 23 — 310 — 8 — 6 — —

384 Grassland Research Institute Braşov. Romania — — — — 1 — — — — 383 — — —

368 Central Research Station for Crops on Sandy Soils

Dăbuleni-Dolj, Romania

— — 2 — — — — — — 366 — — —

367 Nikitskyi Botanical Gardens, Yalta, Crimea, Ukraine 18 — 29 — — — — — 292 19 — — 9

367 Station INRA, Saint Martin de Hinx, France — — 212 — 22 — — — — 133 — — —

332 Institute of Agriculture, Podgorica, Montenegro — 2 1 — — — 1 248 — — 3 77 —

60 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)



310 Institute of Grape and Wine ‘Maharach’, Yalta,

Crimea, Ukraine

— — 86 — 33 — — — 108 31 — — 52

302 Fruit Growing Research Station Valcea, Romania — — 5 — — — — — — 282 — — 15

298 Fruit Growing Research Station Bistrița, Romania — — 1 — — — — — 3 294 — — —

275 Fruit Growing Research Station Iaşi, Romania — — 5 — — — — — — 268 — — 2

274 Nordic Genetic Resource Center, Alnarp, Sweden 6 — 117 7 113 — — — — 28 — — 3

272 Wine Growing Research Station Odobești-Vrancea,

Romania

8 — 47 — 21 — — — 20 174 — — 2

264 Centro Nacional de RecursosFitogenéticos, Alcalá de

Henares,Madrid, Spain

12 — 37 — 194 — — — 1 9 — — 11

256 Wheat Genetics Resource Center, Manhatta, Kansas,

USA

11 13 13 16 90 79 3 5 — 18 6 — 2

249 AGRITEC, Research, Breeding and Services Ltd.,

Šumperk, Czech Republic

1 — 109 — 37 — — — — 69 — 1 32

241 International Crop Research Institute for the Semi-

Arid Tropics (ICRISAT), Hyderabad, India

2 — 170 — 39 — — — 4 — — — 26

233 Banco de Germoplasma, EscuelaTécnica Superior de

IngenierosAgrónomos, Madrid, Spain

— — — — 223 — — — — — — — 10

232 National Germplasm Repository USDA, ARS, Uni-

versity of California, Davis, California, USA

68 1 11 — 151 — — — 1 — — — —

228 Institute of Genetics Academy of Sciences of Mol-

dova, Chișinău, Moldova

— — 9 — — — — — 184 29 — — 6

225 Soybean Germplasm Collection, USDA-ARS, Ur-

bana, Illinois, USA

— 2 34 4 — — — — 161 — 24 — —

213 Genetics and Plant Breeding Station, ESRA-INRA

SGAP, Mauguio, France

— — 98 — 3 — — — — 74 — — 38

212 Botany Department, University of California, Davis,

California, USA

9 2 21 2 160 — — — 8 — 10 — —

207 National Genebank of Kenya, Crop Plant Genetic

Resources Centre,Muguga, Kenya

— — 10 — 73 — — — — 20 — — 104

61 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Table 2. Countries holding the largest numbers of germplasm accessions (over 200) from the Balkans, and number of accessions per country of origin. For explana-

tion of country codes, see Table 1.

Accessions Holding country Genebanks Country of origin


23094 Romania 45 9 — 440 — 86 — 52 — 208 22079 — 1 219

15454 Bulgaria 4 9 — 14257 — 149 — 10 — 9 562 — 24 434

10103 USA 27 378 484 1855 295 2753 79 2128 321 228 32 1498 16 36

9449 Australia 8 50 5 1065 25 7201 — 9 — 25 311 — 3 755

9420 Germany 15 1078 — 2039 702 2921 — 11 — 37 1911 4 17 700

5878 Greece 7 2 — 13 — 5805 — — — — — — — 58

5641 RussianFederation 1 42 49 1919 68 271 — 25 8 1589 742 — 32 896

5638 Syria 1 67 46 952 59 3385 — 338 42 85 463 93 — 108

4380 Ukraine 39 29 — 1278 81 164 — 2 — 1501 641 33 17 634

3578 U.K. 7 — 58 1004 74 1384 — 56 11 1 230 32 178 550

3553 Albania 1 3443 — 53 — 42 — 5 — — 10 — — —

3300 Czech Republic 15 23 3 1043 131 307 — 9 1 40 735 44 182 782

2823 CAN –Canada 1 32 82 304 79 1462 — 458 — 22 336 — 48 —

2653 Croatia 8 — 96 — 2547 — — 5 — — 1 4 — —

2597 Hungary 1 12 — 534 3 93 — — — 2 1491 1 1 460

2328 Serbia 1 — 324 61 285 29 — 221 — — 25 — 103 1280

2287 Poland 10 139 — 754 13 326 — 34 — 161 564 6 14 276

1669 Slovenia 2 — — — — — — — — — — — 1669 —

1545 Macedonia 1 19 — 120 8 11 — 1086 — 1 1 — 6 293

1456 Slovakia 9 2 — 573 34 74 — — — 61 354 6 40 312

1018 Colombia 2 — 10 514 4 43 — 420 — 4 15 — — 8

949 Italy 36 190 2 143 36 314 — — 2 30 16 37 3 176

916 Spain 20 58 — 76 11 658 — 2 — 3 22 3 — 83

851 Taiwan 1 — — 177 — 19 — — — 3 — — — 652

691 France 7 — — 347 2 80 — — — — 217 — — 45

602 Japan 2 — — 132 1 51 — — — — 90 — — 328

507 Netherlands 2 4 1 138 7 102 — 25 — 17 60 42 15 96

492 Mexico 1 4 3 41 — 324 — 6 1 1 35 6 — 71

403 Moldova 3 — — 16 — — — — — 311 67 — — 9

354 Montenegro 2 — 2 1 — — — 1 270 — — 3 77 —

332 India 2 2 3 220 — 54 — — — 4 13 — 3 33

274 Sweden 1 6 — 117 7 113 — — — — 28 — — 3

62 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Accessions Holding country Genebanks Country of origin


235 Austria 7 3 1 20 45 21 — — — 1 38 8 69 29

207 Kenya 1 — — 10 — 73 — — — — 20 — — 104

Table 3. Countries of originin decreasing order of number of Balkan germplasm accessions held in genebanks worldwide. The percentage is given in relation to the

total number of Balkan accessions, i.e. 126,230

Accessions Percentage Country of origin Number of

holding countries holding genebanks genera species

31382 24.9 Romania 45 187 296 675

30659 24.3 Bulgaria 52 211 468 1280

28735 22.8 Greece 45 181 318 941

9743 7.7 former) Yugoslavia 42 165 125 286

5616 4.4 Albania 29 70 148 247

4905 3.9 Macedonia 22 40 80 148

4529 3.6 Croatia 27 71 291 457

4399 3.5 Moldova 32 111 91 147

2524 2.0 Slovenia 23 45 178 276

1822 1.4 Serbia 17 42 47 82

1181 0.9 Bosnia and Herzegovina 18 33 101 146

656 0.5 Montenegro 8 18 38 57

79 0.1 Kosovo 1 1 4 15

Table 4.Total numbers of accessions in genebanks of Balkan countries (according to EURISCO data), and numbers of “own” accessions for each country. The gene-

banks of Macedonia and Serbia also report accessions from former Yugoslavia.

Country Genebanks Total accessions Ownaccessions AccessionsfromYugoslavia

Albania 1 4105 3443

Bulgaria 3 63608 14241

BosniaandHerzegovina 2 434 10

Greece 4 6265 5492

Croatia 8 3264 2547

Moldova 3 1211 311

Macedonia 1 2158 1086 293

Montenegro 2 356 270

Romania 37 42837 21979

Serbia 1 5475 0 1280

63 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Country Genebanks Total accessions Ownaccessions AccessionsfromYugoslavia

Slovenia 2 1776 1669

Table 5. Accessions from the Balkans grouped by sample status according to the FAO/Bioversity Multi-Crop Passport Descriptors, Version 2 (FAO/Bioversity

2012). In FAO WIEWS, the sample status is coded by two-letter abbreviations, which have been transformed into the three-digit codes, which are hierarchical, i.e.

100 also includes 110, 120 etc.

Accessions Sampstat — Status of sample FAO WIEWS codes included

17431 Unknown or not stated

18044 100 — Wild WS: Wild

3942 110 — Natural

444 120 — Semi-natural/wild

643 130 — Semi-natural/sown [onlyusedforforagecrops]

1078 200 — Weedy WE: Weedy

42453 300 — Traditional cultivar/landrace CU: Cultivated; LR: Traditional cultivar/Landrace; OL: Old cultivar

12641 400 — Breeding/research material

7574 410 — Breeder’sline BL: Breeder's line

225 411 — Syntheticpopulation

792 412 — Hybrid

446 413 — Founder stock/basepopulation

3725 414 — Inbredline (parent of hybrid cultivar)

21 415 — Segregatingpopulation

401 420 — Mutant/genetic stock GS: Genetic stock; MT: Mutant

13510 500 — Advanced/improved cultivar AC: Advanced cultivar

2860 999 — Other (to be elaborated in the REMARKS field)

Table 6. Genera of germplasm from the Balkans with more than 100 accessions, and number of accessions per country of origin. For explanation of country codes,

see Table 1.

Accessions Genus Country of origin


18831 Triticum 945 222 6425 284 2773 58 935 209 358 3018 1057 19 2528

15629 Zea 856 338 2919 609 284 — 408 71 890 7093 2 116 2043

10232 Phaseolus 445 10 2728 193 676 — 483 — 472 3835 8 1049 333

6897 Hordeum 122 115 1317 176 2306 1 916 61 70 1018 240 39 516

5143 Trifolium 24 104 571 155 3461 — 91 24 2 344 24 122 221

4283 Medicago 18 8 472 55 3202 — 7 6 21 292 16 37 149

4134 Vicia 118 8 1335 21 1520 — 21 — 53 733 15 59 251

64 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)



3422 Vitis 291 1 499 163 1011 — 94 27 254 559 26 77 420

3348 Prunus 275 4 216 43 225 — 75 4 183 2149 12 — 162

3092 Aegilops 49 13 610 28 2124 19 84 14 — 47 35 — 69

2672 Avena 105 83 448 90 746 — 163 27 21 447 185 12 345

2427 Pisum 92 — 1100 19 551 — 13 1 34 497 10 — 110

2399 Capsicum 112 1 1028 28 80 — 125 — 66 327 1 4 627

2036 Lycopersicon 165 1 658 32 68 — 202 — 365 345 2 5 193

1851 Linum 3 — 337 3 130 — — 1 3 1341 — 10 23

1834 Secale 54 8 886 6 36 — 346 14 — 407 53 7 17

1472 Lens 21 12 533 41 685 — 24 22 2 39 16 1 76

1435 Nicotiana 146 1 329 8 783 — 5 3 2 71 4 2 81

1372 Glycine 6 2 123 25 — — 1 — 597 329 25 2 262

1341 ×Triticosecale — — 776 1 21 — — — 64 463 — 1 15

1280 Lupinus — — 22 4 1190 — 1 — — 31 — — 32

1249 Allium 69 — 488 39 297 — 72 — 20 219 3 6 36

1208 Cucurbita 33 — 376 29 59 — 177 — 18 429 1 3 83

1175 Beta 8 — 66 9 758 — 27 — 8 267 1 2 29

1093 Malus 106 — 21 47 4 — 13 19 256 550 3 9 65

1026 Festuca 2 3 226 69 98 — 57 — 2 478 — 49 42

993 Dactylis 3 8 289 35 229 — 4 2 3 317 — 62 41

991 Cicer 18 — 451 5 336 — 2 12 110 21 2 — 34

988 Lactuca 13 — 244 47 160 — 6 — 1 251 1 187 78

986 Lolium 11 — 293 57 168 — — — 3 425 — 13 16

948 Lathyrus 55 3 172 5 651 — — 1 13 15 1 10 22

907 Brassica 28 — 142 90 336 — 74 1 15 148 2 20 51

900 Cucumis 102 — 338 19 75 — 16 — 58 209 2 3 78

808 Helianthus 9 — 126 3 4 — — — 6 562 — 2 96

729 Oryza — — 270 — 67 — 124 — — 243 — — 25

702 Pyrus 150 — 53 21 5 — 37 3 120 267 4 — 42

594 Solanum 9 1 92 2 24 — 27 52 23 282 — 19 63

555 Arachis — — 408 1 16 — 15 — — 106 — 2 7

456 Salvia 163 37 19 133 57 — 3 11 4 13 — 10 6

399 Daucus 10 1 58 28 155 — 2 — 19 95 — 2 29

388 Lotus 3 5 46 13 222 — 2 — 1 45 2 15 34

65 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)



378 Gossypium 11 — 156 — 177 — — — — 9 — — 25

360 Papaver 1 1 81 22 3 — 1 — 1 234 — 3 13

324 Citrullus 14 — 154 5 12 — 3 — 52 62 2 — 20

299 Vigna 8 — 36 1 42 — 2 — 1 206 — — 3

286 Sesamum — — 200 — 74 — 10 — — 1 — — 1

284 Dasypyrum 7 2 23 10 237 1 2 1 — — — — 1

277 Juglans 19 — 28 — 3 — — — 9 210 4 — 4

273 Panicum 1 1 60 5 3 — — — 27 115 — 2 59

261 Satureja 115 1 31 27 3 — 2 — 1 73 — 7 1

246 Sorghum 18 — 149 8 15 — — — 4 45 — 3 4

241 Origanum 139 — 4 46 21 — — — — 27 — 3 1

238 Ornithopus — — 7 — 231 — — — — — — — —

228 Bromus 1 — 61 8 66 — 13 — 5 58 4 6 6

216 Phleum 3 — 53 8 30 — 1 — 1 66 — 35 19

207 Petroselinum 7 — 48 11 18 — 43 — 8 67 3 — 2

205 Cannabis 1 — 10 1 — — — — 1 155 — 4 33

199 Poa 2 — 88 27 12 — — — — 58 — 8 4

197 Olea 92 — — 37 45 — — 15 — — — — 8

193 Silene — 8 66 11 64 — 18 3 — 13 — 10 —

182 Fagopyrum 2 2 3 10 — — — 7 2 19 2 118 17

181 Mentha 6 1 32 37 2 — — — 12 87 — — 4

179 Astragalus — — 47 2 84 — — — 7 35 — 3 1

172 Trigonella 2 — 18 1 145 — — — — 6 — — —

166 Anethum 4 1 45 17 14 — 1 — 21 62 — 1 —

164 Hypericum 13 3 25 109 2 — — — — 8 — 4 —

147 Onobrychis — — 42 — 48 — 1 — 3 33 2 7 11

137 Cydonia 27 — 20 — — — — — 19 62 3 — 6

136 Raphanus 4 — 40 1 28 — 4 — 6 48 — 1 4

127 Hymenocarpos — — 2 — 123 — — — — — — — 2

116 Ficus 72 — 14 16 13 — — — — — — — 1

112 Melilotus 1 — 31 3 43 — — — 7 14 3 8 2

109 Datura 1 — 8 3 3 — — — — 91 — — 3

108 Brachypodium 2 — 20 3 78 — — — — 3 — 2 —

108 Tanacetum — — 7 80 1 — — — 3 16 — 1 —

66 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)



107 Thymus 51 — 12 24 4 — — — — 16 — — —

102 Agrostis — — 34 1 2 — — — 1 56 — 5 3

Table 7. Species of germplasm from the Balkans with more than 200 accessions, and number of accessions per country of origin.For explanation of country codes,

see Table 1.

Accessions Species Country of origin


15612 Zea maysL. 856 338 2917 594 284 — 408 71 890 7093 2 116 2043

13772 Triticum aestivumL. 422 181 4738 247 1136 4 695 121 305 2620 977 18 2308

8771 Phaseolus vulgarisL. 434 10 2552 173 647 — 465 — 464 3644 8 43 331

6357 Hordeum vulgareL. 120 115 1260 175 1884 — 914 61 70 995 239 38 486

3023 Vitis viniferaL. 291 1 377 163 1008 — 94 27 154 425 25 77 381

2397 Pisum sativumL. 91 — 1089 19 538 — 13 1 34 497 10 — 105

2384 Capsicum annuumL. 112 1 1021 28 80 — 125 — 66 320 1 4 626

2380 Triticum durumDesf. 294 — 1297 4 518 — 68 — 48 122 — — 29

2058 Avena sativaL. 48 83 431 81 306 — 159 23 21 413 174 12 307

1809 Secale cerealeL. 52 8 877 6 27 — 346 14 — 403 53 6 17

1771 Lycopersicon esculentumMill. 164 1 547 32 65 — 202 — 299 306 2 5 148

1706 Linum usitatissimumL. 3 — 327 3 117 — — — 2 1226 — 5 23

1534 Triticum turgidumL. 28 36 183 27 815 28 169 84 5 45 58 — 56

1531 Vicia sativaL. 50 1 703 5 607 — 6 — 22 29 7 — 101

1529 Vicia fabaL. 23 — 204 10 456 — 14 — 17 646 — 48 111

1419 Nicotiana tabacumL. 145 1 324 8 780 — 5 3 2 68 4 — 79

1417 Phaseolus coccineusL. 10 — 156 20 25 — 17 — 8 182 — 997 2

1385 Lens culinarisMedik. 21 1 532 3 684 — 24 6 2 39 16 — 57

1341 ×Triticosecale sp. — — 776 1 21 — — — 64 463 — 1 15

1326 Glycinemax(L.) Merr. 6 2 123 25 — — 1 — 597 313 25 2 232

983 Cicer arietinumL. 18 — 444 5 335 — 2 12 110 21 2 — 34

974 Dactylis glomerataL. 3 8 270 35 229 — 4 2 3 317 — 62 41

913 Beta vulgarisL. 6 — 39 9 527 — 27 — 8 267 1 2 27

873 Cucurbita pepoL. 25 — 241 22 26 — 125 — 14 360 — 3 57

836 Trifolium subterraneumL. — — 12 — 785 — — — — — — — 39

830 Lactuca sativaL. 12 — 199 39 72 — 6 — 1 242 1 181 77

821 Lolium perenneL. 5 — 252 47 115 — — — 3 384 — 9 6

67 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)



785 Prunus sp. — 2 76 — 6 — — — 23 623 — — 55

769 Helianthus annuusL. 9 — 106 3 4 — — — 4 553 — 2 88

748 Malus domesticaBorkh. 1 — 14 47 3 — 13 19 215 367 3 9 57

747 Medicago sativaL. 14 6 218 51 94 — 5 4 21 218 15 26 75

737 Trifolium pratenseL. 10 39 95 105 104 — 53 21 1 219 5 57 28

729 Oryza sativaL. — — 270 — 67 — 124 — — 243 — — 25

724 Lupinus angustifoliusL. — — 2 — 719 — — — — 1 — — 2

722 Prunus armeniacaL. 17 — 37 — 34 — 55 1 72 486 6 — 14

700 Aegilops triuncialisL. 4 — 168 6 474 1 30 1 — 5 7 — 4

656 Triticum monococcumL. 177 5 71 4 127 24 3 4 — 149 19 1 72

550 Medicago polymorphaL. — — 28 — 498 — — — — 3 — — 21

549 Arachis hypogaeaL. — — 407 — 13 — 15 — — 106 — 1 7

546 Allium cepaL. 39 — 232 17 48 — 56 — 8 139 1 1 5

545 Brassica oleraceaL. 23 — 100 65 155 — 74 1 14 62 2 18 31

518 Prunus avium(L.) L. 67 — 40 4 57 — 2 — 9 324 — — 15

499 Prunus persica(L.) Stokes 20 — 23 2 35 — — — 42 367 — — 10

479 Medicago orbicularis (L.) Bartal. — — 23 — 438 — 1 — — 6 — — 11

455 Cucumis sativusL. 37 — 118 10 16 — 5 — 41 178 2 — 48

450 Festuca pratensisHuds. — — 125 17 2 — 52 — 1 217 — 18 18

431 Medicago truncatulaGaertn. — — 2 — 426 — — — — 1 — — 2

404 Trifolium repensL. 1 15 105 17 186 — 7 — — 38 1 22 12

400 Aegilops biuncialisVis. 1 6 98 — 261 1 18 — — 1 12 — 2

371 Gossypium hirsutumL. 11 — 150 — 176 — — — — 9 — — 25

370 Solanum tuberosumL. — — 54 — — — — 52 9 207 — 19 29

369 Aegilops geniculataRoth 34 1 83 11 206 2 7 4 — 11 1 — 9

358 Cucumis meloL. 65 — 154 9 58 — 11 — 11 28 — 3 19

358 Pyrus communisL. 123 — 28 21 — — 19 1 110 21 1 — 34

352 Lupinus albusL. — — 14 2 302 — 1 — — 16 — — 17

348 Aegilops neglectaReq. ex Bertol. 7 6 85 11 200 1 21 8 — — 1 — 8

329 Papaver somniferumL. — — 72 18 1 — — — 1 225 — — 12

322 Daucus carotaL. 8 1 57 27 83 — 2 — 19 94 — 2 29

316 Citrullus lanatus(Thunb.) Matsumuraet Nakai 14 — 149 5 10 — 3 — 51 62 2 — 20

315 Lathyrus sativusL. 48 — 101 4 143 — — 1 9 5 — — 4

315 Vitis sp. — — 103 — 3 — — — 39 132 — — 38

68 H. Knüpffer

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)



311 Triticum sp. 23 — 73 2 115 — — — — 57 — — 41

306 Aegilops comosaSm. — — 5 — 301 — — — — — — — —

302 Salvia officinalisL. 162 37 1 73 2 — 3 11 — 11 — — 2

300 Prunus domesticaL. 90 1 16 21 40 — 12 3 35 34 2 — 46

291 Festuca arundinaceaSchreb. — — 29 10 70 — 2 — 1 157 — 5 17

289 Pyrus sp. 3 — 21 — 2 — — 1 8 246 2 — 6

288 Aegilops lorentiiHochst. 1 — 9 — 277 — — — — — — — 1

285 Vigna unguiculata(L.) Walp. 7 — 32 1 37 — — — 1 205 — — 2

284 Dasypyrumvillosum(L.) Borbás 7 2 23 10 237 1 2 1 — — — — 1

275 Vicia ervilia(L.) Willd. 37 — 49 — 186 — 1 — — 1 — — 1

271 Sesamum indicumL. — — 200 — 60 — 10 — — — — — 1

270 Panicum miliaceumL. 1 1 60 4 2 — — — 27 115 — 1 59

253 Lathyrus ciceraL. — — 2 — 248 — — — 3 — — — —

251 Allium sativumL. 8 — 127 5 17 — 1 — 10 61 1 1 20

235 Medicago rigidula(L.) All. — — 31 — 186 — — 1 — 4 — — 13

234 Cucurbita maximaDuchesne 4 — 53 6 27 — 51 — 4 63 1 — 25

230 Medicago minima(L.) L. 1 1 50 3 156 — — — — 17 — — 2

229 Lycopersicon sp. 1 — 75 — 3 — — — 66 39 — — 45

218 Origanum vulgareL. 139 — 3 46 1 — — — — 25 — 3 1

214 OrnithopuscompressusL. — — 5 — 209 — — — — — — — —

213 Solanum melongenaL. 9 — 37 — 24 — 27 — 14 72 — — 30

206 Petroselinum crispum(Mill.) Fuss 7 — 47 11 18 — 43 — 8 67 3 — 2

205 Prunus cerasusL. 2 — 12 13 7 — 5 — 2 142 4 — 18

204 Cannabis sativaL. 1 — 10 — — — — — 1 155 — 4 33

202 Medicago arabica(L.) Huds. — — 20 — 172 — — — — 1 — — 9

202 Sorghum bicolor(L.) Moench 18 — 114 8 13 — — — 1 41 — 3 4


UDC 633.11-184(497.2)


____________________________________________________________________________________________________

INVESTIGATION ON SOME MORPHOLOGICAL AND BIOLOGICAL

CHARACTERISTICS OF EINKORN WHEAT (T. MONOCOCCUM L.) DEPENDING

ON NITROGEN FERTILIZATION

H. Kirchev*, N. Semkova

Faculty of Agronomy, Agricultural University, Plovdiv, Bulgaria


Abstract

The aim of this study is to investigate some quantitative and qualitative indicators of einkorn wheat

(T. monococcum L.). A three-year field experiment has been carried out at the experimental field of

Department of Crop Science in Agricultural University - Plovdiv. To compare the performance,

Sadovo1 common wheat (T. aestivum L.) is used as a standard. Both wheat species have been grown

on two nitrogen fertilization levels – 80 and 160 kg.ha-1 nitrogen. Phenological development of the

plants was recorded at the onset of the main phenophase. Inter-phase period has been calculated

(number of days). Grain yield (t ha-1) is accounted indirectly by ¼ m2 plot. The main structural

elements of plants have been established. It has been found that phenological development stage of

tillering occurs at the same time for both wheat species. Following the start of spring vegetation,

common wheat enters a phase earlier than the einkorn. Common wheat is a high-yielding einkorn, that

puts both proven wheat varieties in different groups. Einkorn has high tiller appearance but it has a

low productive tillering than common wheat. Einkorn form lower grain in the spike and lighter grain

per spike. Nitrogen fertilization significantly increased harvested grain in common wheat. In einkorn

it has no significant impact on yield.

Key words: einkorn, wheat, yield, nitrogen fertilization.

Introduction

The first cultivated wheat, einkorn (Triticum

monococcum L.) was domesticated during the

Pre-Pottery Neolithic period. It then spread to

the Balkans, and finally to Western and

Northern Europe (Desheva et al., 2014);

(Laghetti et al., 2009); (Mielke & Rodemann,

2007).

Growing of the einkorn has no significance in

modern agriculture due to its late ripeness and

low yields. At present, there is interest for

einkorn because of the nutritional qualities, its

adaptation to low-input agriculture and

resistance to diseases that it gives an

opportunity for organic farming (Konvalina et

al., 2009); (Konvalina et al., 2010); (Ruiz et

al., 2008). Compared to the common wheat,

often only 20% of the soft wheat yield are

achieved when cropping einkorn (without

husks). The einkorn flour distinguishes itself

by very high contents of proteins and glue.

The yellow pigmentation gives the bread and

cakes a pleasant looking color. Einkorn bread

and cakes have a taste of nut (Guzmán et al.,

2009; Hidalgo et al., 2009; Hidalgo et al.,

2014; Zaharieva & Monneveux, 2014).

Einkorn contains the highest levels of lutein

among wheat species. It is a specialty wheat

with high levels of carotenoids and other

phytonutrients, with emphasis on its potential

as a high-carotenoid wheat ingredient for use

in developing high-lutein whole grain baked

food products (Abdel-Aal & Hucl, 2014).


The aim of this study is to establish some

morphological and biological characteristics of

einkorn, compared with common wheat,

depending on the level of nitrogen

fertilization. For this purpose, a three-year

field experiment has been carried out at the

experimental field of Department of Crop

Science in Agricultural University – Plovdiv.

To compare the performance, Sadovo1

common wheat (T. aestivum L.) is used as a

standard. Both wheat species have been grown

on two nitrogen fertilization levels – 80 and

160 kg.ha-1 nitrogen. Phenological


70 H. Kirchev, N. Semkova

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

development of the plants was recorded at the

onset of the main phenophase. Inter-phase

period has been calculated (number of days).

Grain yield (t ha-1) is accounted indirectly by

¼ m2 plot. In einkorn, yield is assimilated to a

naked grain by correlating grain glumes by

medium samples of 20 g of harvested spikes.

The main structural elements of plants have

been established: Plant heigh, cm ;

Number of tillers per plant; Number of spikes

per plant; Productive tillers, %; Spike

length, cm; Numbers of spikelets per spike;

Numbers of grains per spike; Mass of grains

per spike, g and Mass of glumes per spike, g.

To establish a statistically significant influence

of the examined factors and differences

between the tested variants was used analysis

of variance.


Phenological development of wheat species in

this study during the three years of the study

indicated as dates for the main phenological

phases (Table 1). The different dates of sowing

during the three years of the study are due to

rainfall conditions and the ability to perform

quality tillage and timely sowing. The sowing

during of three years has been done later than

the optimal period for the region (20 October).

This is the reason crops to spring up at

different times in each of the years, but both

types of wheat germinate at the same time

each year. Obviously germination depends on

the meteorological conditions, but not on the

genotype.

Late germination is the reason of entering the

crops the tillering phase in December. Even

though this phase of the development of winter

cereal crops is influenced mainly by

temperature conditions, einkorn enters the

tillering stage between 4 and 6 days later than

common wheat. The earliest tillering occurs

during the first harvest year - between

December 10 to 15, and later - during the third

year of the study - between 26 to 30

December.

Table 1. Phenological development.

Species Sowing Germination Tillering Stem

elongation

Spike

emergence

Maturity

2010

Wheat 28.10.2009 12.11.2009

10.12.2009 09.04.2010 28.04.2010 28.06.2010

Einkorn 15.12.2009 30.04.2010 15.05.2010 06.07.2010

2011

Wheat 04.11.2010 15.11.2010

14.12.2010 11.04.2011 02.05.2011 30.06.2011

Einkorn 20.12.2010 02.05.2011 17.05.2011 07.07.2011

2012

Wheat 01.11.2011 15.11.2011

26.12.2011 16.04.2012 05.05.2012 27.06.2012

Einkorn 30.12.2011 05.05.2012 20.05.2012 05.07.2012

The beginning of the durable spring vegetation

and the entering of the plants the phase of stem

elongation occurs at different times in each of

the species. In common wheat difference

between the year with the early and later

occurrence of the phase of stem elongation is 7

days (between 9 and 16 April), while einkorn

– five days (April 30 and May 5). Similar to

phase of stem elongation, the spike emergence

in the common wheat occurs earlier (between

April 28 and May 5) compared to einkorn,

wherein the spike emergence was recorded

between 15 to 20 May. The maturity occurs at

different times for both types of wheat. The

phase of full maturity in common wheat was

registered one week earlier compared to

einkorn.

In both species during the three years of study

differences in the dates of entering the main

phases of development of the crop are not

registered, depending on the level of nitrogen

fertilization, which gives grounds to consider

that nitrogen fertilization does not affect

phenological development of the wheat.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

29

34

30

36

42

46

121

137

119

134

112

127

20

16

22

16

20

16

62

53

60

52

54

47

232

240

231

238

228

236

0 50 100 150 200 250 300 350 400 450 500

T. aestivum

T. monococcum

2010

T. aestivum

T. monococcum

2011

T. aestivum

T. monococcum

2012

sprung-tillering tillering-stem elongation

stem elongation-spike emergence spike emergence-maturity

total vegetation period

Number of days

Figure 1. Inter-phase periods, number of days.

Different dates of entering the main

phenophases of development are the reason of

different lengths of inter-phase periods in both

types of wheat (Fig. 1). Inter-phase period

germination – tillering in einkorn lasts

between 34-46 days and in common wheat is

shorter – between 29-42 days depending on

the year. During the three years of study the

period between tillering and stem elongation is

longer by 15 days average at einkorn to

common wheat. The period between phase of

stem elongation and spike emergence is

shorter in einkorn – 16 days during the three

harvest years, while in common wheat –

between 20-22 days. Even though maturity

occurs first in common wheat, interphase

period spike emergence – maturity is shorter in

einkorn – 47 days in year 2012 and 53 days in

the first year of study. Differences in the

duration of inter-phase periods in wheat

species are the reason of the different lengths

of vegetation from germination to maturity.

The vegetation period of common wheat is

between 228-232 days, while for the einkorn is

longer an average of 8 days – between 236-

240 days.

Table 2. Grain yield, t ha-1.

Species N rate,

kg ha-1

Years Average

2010 2011 2012

Triticum aestivum

L.

80 4.532** 4.128** 3.265** 3.975**

160 6.657*** 6.053*** 4.867*** 5.859***

Triticum

monococcum L.

80 1.532* 1.831* 1.062* 1.475*

160 1.862* 2.106* 1.302* 1.757*

LSD 5% 0.332 0.277 0.246 0.285

*Values with the different symbols are statistically proven.

Grain yield of the tested species of wheat

varies during three years of study, as in the

three harvest years common wheat variety

Sadovo1 significantly exceed the yields

obtained from einkorn (Table 2). Due to the

very large differences in yields between the


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

two species, the differences in the three years

are statistically proven. In common wheat

highest yields were obtained in the first

harvesting year – an average of 5.595 t ha-1 for

both fertilization rates, while einkorn yields

are highest in the second year of study – 1.969

t ha-1. The lowest yields in both species were

obtained during the third harvest year.

Nitrogen fertilization increases the yield in

both species, but during the three years of

study and average for the period at einkorn the

difference between the two levels of

fertilization are smaller than the least

significant difference (LSD). In common

wheat during the three studied years and

average for the three years higher fertilizer rate

of 160 kg ha-1 nitrogen proved increases grain

yield by an average of 1.884 t ha-1.

Table 3. Structural elements of the crop.

Species N rate,

kg ha-1

Plant

heigh, cm

Number of

tillers per plant

Number of

spikes per plant

Productive

tillers, %

T. aestivum L. 80 70.5* 2.8* 2.5* 89.3***

160 88.6** 3.2* 2.6* 81.2**

T.

monococcum

L.

80 103.4*** 3.8* 2.3* 60.5*

160 106.2*** 4.2* 2.5* 59.5*

LSD 5% 14.2 1.3 0.5 3.3


The structural elements of the crop for the two

species of wheat enable them to be compared,

both in height and density (Table 3). Plant

height in both species is drastically different.

In einkorn the average height of the crop is

104.8 cm – proved higher by 25.2 cm the

formation of sowing Sadovo1 – 79.6 cm.

Similar to the results for yield, nitrogen

fertilization has no proven change in the height

of the plants in einkorn, while wheat variety

Sadovo1the higher fertilizer rate leads to

proven raising of the height of the crop to 18.1

cm. Overall species Triticum monococcum

formed higher stem than common wheat.

Crop density, determined by the number of

tillers per plant allows einkorn to be defined as

more strongly tillering species compared to

common wheat. For both species nitrogen

fertilization has no proven change in the

number of tillers per plant. Number of spikes

per plant is a factor determining how many of

formed tillers are productive. Even though

einkorn differs as dramatically strong tiller

species, spikes formed on one plant are almost

as many as on the common wheat. This puts

both species close to each other by this

indicator, since the difference does not exceed

the necessary least significant difference

(LSD), which indicates that it is not

statistically significant. This is the main reason

for the big difference, for productive tillering,

which is in favor of common wheat. Einkorn

has a low productive tillering for only about

60% of the generated tillers become

productive, while Sadovo1 variety, despite the

relatively small number of tillers per plant,

over 80% of them form spikes. Nitrogen

fertilization has no proven effect on productive

tillers on einkorn, while on common wheat it

increases productive tillers by 8.1%.

In addition to the structure of the crop, the

structural elements of the spike are essential

for the productive potential of wheat (Table

4). The length of the spike is higher in

common wheat in comparison with einkorn by

about 2 cm, so the difference of the spike in

common wheat in comparison with einkorn

may be considered to be statistically proven.

Nitrogen fertilization did not significantly

affect this feature in einkorn, while common

wheat higher nitrogen rates lead to the

formation of a longer spike. Although

common wheat formed a longer spike, the

number of spikelets per spike are on average 2

more in einkorn. In both wheat species

nitrogen fertilization had no proven effect. In

common wheat the number of grains per spike

varies proven under the influence of nitrogen

fertilization from 37.4 in fertilization with N80

to 39.6 in higher fertilization rates N160. As

einkorn forms only one grain in spikelet, the

number of grains per spike is equal to the

number of spikelets. The mass of grain per

spike in common wheat has been proven

heavier about 1 g than in einkorn. In einkorn

nitrogen fertilization had no proven effect on


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

this feature, while on common wheat

difference in the weight of the grain between

the two fertilization rates has been proven

statistically.

Table 4. Structural elements of the spike.

Species N rate,

kg ha-1

Spike

length, cm

Numbers of

spikelets per

spike

Numbers of

grains per

spike

Mass of grains

per spike, g

Mass of

glumes per

spike, g

T. aestivum L. 80 9.4** 20.7* 37.4** 1.45** 0.04*

160 10.5** 21.3* 39.6*** 1.87*** 0.05*

T. monococcum

L.

80 7.3* 23.3** 23.3* 0.79* 0.40**

160 7.6* 23.5** 23.5* 0.86* 0.42**

LSD 5% 1.2 1.8 2.0 0,19 0.08


Typical of einkorn hulled wheat, with tough

glumes that tightly enclose the grains, causing

to form heavier glumes (0.41 g). In common

wheat weight of glumes is low, compared with

einkorn. Nitrogen fertilization did not

significantly affect this feature in both species

of wheat.

Conclusions

In einkorn, vegetation period is longer by an

average of 8 days, compared to the common

wheat. The reason for this is the late entry in

the main phenophases of development in

einkorn and different lengths of inter-phase

periods in both wheat species. Nitrogen

fertilization does not affect phenological

development of both types of wheat.

In common wheat grain yields are significantly

higher than einkorn. The main reasons for this

are that einkorn has higher tiller appearance

but it has a lower productive tillering than

common wheat. Einkorn forms lower grain in

the spike and lighter grain per spike.

Nitrogen fertilization significantly increased

harvested grain in common wheat. In einkorn

it has no significant impact on yield.

References

1. Abdel-Aal, E. M., Hucl, P. (2014).

Einkorn: a functional wheat for developing

high-lutein whole grain baked products. Cereal

Foods World, 59(1), 5-10.

2. Desheva, G., Valchinova, E., Kyosev,

B., Stoyanova, S. (2014). Grain physical

characteristics and bread-making quality of

alternative cereals towards common and

durum wheat. Emirates Journal Of Food And

Agriculture, 26(5), 418-424.

3. Guzmán, C., Caballero, L., Alvarez, J.

B. (2009). Variation in Spanish cultivated

einkorn wheat (Triticum monococcum L. ssp.

monococcum) as determined by morphological

traits and waxy proteins. Genetic Resources

And Crop Evolution, 56(5), 601-604.

4. Hidalgo, A., Brandolini, A., Ratti, S.

(2009). Influence of genetic and environmental

factors on selected nutritional traits of Triticum

monococcum. Journal Of Agricultural And

Food Chemistry, 57(14), 6342-6348.

5. Hidalgo, A., Brandolini, A. (2014).

Nutritional properties of einkorn wheat

(Triticum monococcum L.). Journal Of The

Science Of Food And Agriculture, 94(4), 601-

612.

6. Konvalina, P., Šrámek, J., Stehno, Z.,

Moudrý, J. J. (2009). Efficiency of alternative

wheat growing in organic farming. Lucrari

Stiintifice, Universitatea De Stiinte Agricole Si

Medicina Veterinara A Banatului, Timisoara,

Seria I, Management Agricol, 11(1), 111-116.

7. Konvalina, P., Capouchová, I., Stehno,

Z., Moudrý, J. (2010). Morphological and

biological characteristics of the land races of

the spring soft wheat grown in the organic

farming system. Journal Of Central European

Agriculture, 11(2), 235-244.

8. Laghetti, G., Fiorentino, G., Hammer,

K., Pignone, D. (2009). On the trail of the last

autochthonous Italian einkorn (Triticum

monococcum L.) and emmer (Triticum

dicoccon Schrank) populations: a mission

impossible?. Genetic Resources And Crop

Evolution, 56(8), 1163-1170.

9. Mielke, H., Rodemann, B. (2007).

Zum Anbau und Pflanzenschutz bei der

seltenen Weizenart Einkorn (Triticum

monococcum). Nachrichtenblatt Des


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Deutschen Pflanzenschutzdienstes, 59(7), 162-

165.

10. Ruiz, M., Aguiriano, E., Carrillo, J. M.

(2008). Effects of N fertilization on yield for

low-input production in Spanish wheat

landraces (Triticum turgidum L. and Triticum

monococcum L.). Plant Breeding, 127(1), 20-

23.

11. Zaharieva, M., Monneveux, P. (2014).

Cultivated einkorn wheat (Triticum

monococcum L. subsp. monococcum): the

long life of a founder crop of agriculture.

Genetic Resources And Crop Evolution, 61(3),

677-706.


UDC 633.11-152.75(497.2)


____________________________________________________________________________________________________

POLYMORPHISM OF ENDOSPERM PROTEINS IN AMPHIDIPLOIDS

WITH THE G GENOME OF Triticum timopheevii (Zhuk.)

Doneva S.1*, Yordanova D.1, Daskalova N.2, Spetsov P.3

1Dobroudja Agricultural Institute – General Toshevo, Bulgaria

2Technical University, Department of Plant Growing - Varna, Bulgaria 3 Konstantin Preslavsky University of Shumen, College–Dobrich, Bulgaria

*e-mail: [email protected]

Abstract

During evolution in Triticum the diversity of genes in T. aestivum L. was greatly reduced compared to

its ancestors. This tendency restricted further improvement of productivity and quality in common

wheat and narrowed the plant resistance to biotic and abiotic stresses. Wide hybridization resulted in

synthetic genotypes that offered opportunities for introduction of new genes for useful traits in

breeding. The objects of this study were two amphidiploids with G-genome inherited from tetraploid

wheat relative T. timopheevii (2n=28, GGAuAu). Glutenin and gliadin allelic composition of the

synthetic wheats H-68/44 and H-69/36 were analysed by SDS-PAGE and A-PAGE electrophoretic

methods. New allelic variants in Glu-G1 loci, which are not characteristics for the spectrum of T.

aestivum, were identified. In contrast to the high polymorphism of amphidiploids for high-molecular

weight proteins, variation in the low-molecular glutenins was much less. More gliadin alleles in

synthetic lines were found than in hexaploid wheat, due to the parent polymorphism. The results of

this survey showed that synthetics with T. timopheevii genome might serve as an important sources of

increased genetic variation for endosperm proteins in common wheat.

Keywords: synthetic wheats, T. timopheevii, glutenins, SDS-PAGE, gliadins, A-PAGE.

Introduction

Many cultivated and wild species from

Aegilops – Triticum group possessed various

and useful genes for wheat improvement

(Monneveux et al., 2000; Zaharieva et al.,

2003; Mujeeb-Kazi, 2005; Spetsov et al.

2006). Various synthetic and translocated

genotypes were developed from Triticum x

Aegilops crosses and used as bridges to

transfer different breeding traits to common

wheat (Jauhar and Peterson, 2006; Plamenov

and Spetsov, 2011).

Wheat grain quality depends on gluten, which

is the complex endosperm protein. It consists

of two prolamin groups–glutenins and

gliadins. Glutenins include high molecular and

low molecular proteins, shortly named as

HMW-GS and LMW-GS, respectively. HMW-

GS are coded by two genes (х- and у-), which

are localized in three loci (Glu-A1, Glu-B1,

Glu-D1) on the long arms of the

homoeologous group 1. LMW-GS are

classified in three groups (В, С и D) due to

their molecular weight and isoelectrical points

(Jackson et al., 1983). Genes, responsible for

them, are localized in the short arms of the

homoeologous group 1 (Glu-A3, Glu-B3 and

Glu-D3 loci). Gliadins are monomeric proteins

and electrophoretically separated in α-, β-, γ-,

ω- gliadins. Two of them (α- and β-) are coded

by Gli-2 loci in the short arms of

chromosomes 6А, 6В и 6D, and others (γ- and

ω-) by Gli-1 loci in the short arms of

chromosomes 1А, 1В and 1D (Masci et al.,

2002). There is a strong connection between

Glu-3 loci, responsible for LMW-GS and Gli-

1 loci, conducting the output of gliadins (Singh

and Shepherd, 1988).

Some investigations showed that the variation

of Glu-1, Glu-3 и Gli-1 loci in bread wheat

was limited (Gianibelli et al., 2001; Li et al.,

2007). Related species to wheat as Ae. tauschii

(Yan et al., 2003), T. turgidum (Li et al., 2006)

and T. monococcum (Ciaffi et al., 1998)

expressed a large diversity of glutenin and

76 Doneva S., Yordanova D., Daskalova N., Spetsov P

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

gliadin alleles. New HMW-GS have been

detected in the A genome of diploid T. urartu

and some tetraploid species, which are

potential sources for genes in wheat

improvement.

T. timopheevi (GGAuAu) is a hulled tetraploid

wheat relative (Goncharov et al., 2009) and

still in seed production to some extent in the

Caucasus (Wan et al., 2002). Its genomes are

considered as homoeologous to wheat А- and

В- genomes (Brown-Guedira et al., 1997).

High protein content (19-22%), diversity in

HMW-GS and resistance to biotic stresses are

remarkable breeding traits for this tetraploid

species (Obukhova et al. 2009). Genes from

the G genome, responsible for endosperm

proteins, are probably similar to those,

governing the protein synthesis in hexaploid

wheat. Through SDS-PAGE и PCR methods

Li et al. (2002) found 8 allelic variants in Glu-

G1, suggesting T. timopheevi as a valuable

source for new glutenin genes in bread wheat

(Li et al., 2007). Two genes, belonging to А-

and G-genome, coding for х- and у- subunits,

were isolated (Wan et al., 2002). It is proved

that wheat lines with both types (х- and у-

subunits) in Glu-A1 are better in quality than

plants having only x-type subunit (Johansson

et al., 1993).

Despite that numerous researches has been

focused on seed proteins, T. timopheevi is

deeply involved in wheat improvement as a

resource of genes not only for grain quality,

but also for fungi resistance – leaf rust, stem

rust, powdery mildew and fusarium (McIntosh

et al., 2008; Lеonova et al., 2011).

Characterization of storage proteins (glutenins

and gliadins) in two amphidiploids possessing

the G-genome from Triticum timopheevii, is

the main purpose of this study. The two

synthetics differ with the second parent used in

the cross. Analysis of synthetic lines may

increase their role as important source of novel

protein genes for wheat breeding.


Synthetic hexaploid wheat Н-68/44 was

obtained from the cross between Т.

timopheevii (GGAuAu) and Aegilops tauschii

(DD), and the second one, Н-69/36 - between

T. turanicum (BBAuAu) and T. timopheevii

(GGAuAu) (Table 1). Two bread wheat

varieties, Bezostaya 1 and Chinese Spring,

were used as standards in biochemiсаl

analyses.

Table 1. Breeding number and genome formulae of synthetic wheats

Breeding No C r o s s Genome formula1 (2n)

Н-69/36 T. turanicum x T. timopheevii BBАuАuGGАuАu

Н-68/44 T. timopheevii x Ae. tauschii GGАuАuDD 1, Genome formulae are according Goncharov et al. (2009).

Glutenins (HMW- and LMW-GS) were

extracted according to Singh et al. (1991).

Gliadins were first extracted in 70% ethanol

and protein fractions were separated by A-

PAGE using 8% polyacrylamide gel under

constant 10°С (Кhan et al., 1983). The

electrophoresis run on vertical apparatus in

two ways: а) classical one-dimensional 12%

polyacrylamide gel (Laemmli, 1970); б) one-

dimensional 10% polyacrylamide gel SDS –

PAGE with addition of 4М urea (Lafiandra et

al., 1993).

Arrangement and numbering of HMW-GS in

wheat was carried out according Payne and

Lawrence (1983). LMW-GS nomenclature in

wheat (Gupta and Shepherd, 1990) and

combined method for LMW-GS and gliadin

identification were adopted (Jackson et al.,

1996). Аlleles in Glu-D1 locus were described

according to William et al. (1993), while

subunits in Glu-G1 and Glu-А1 loci were

marked and compared to those expressed in

genomes of common wheat (Hu et al., 2012).


Amphidiploid (AD) Н-68/44 expressed the

following HMW-GS subunits: 1Ах null in

Glu-A1, 1Gx and 1Gу in Glu-G1, and the

subunit pair 1Dx2 + 1Dy12.4 in Glu-D1 locus

(Fig. 1-2). Glutenins displayed in Glu-A1 and

Glu-G1 loci were inherited from the tetraploid

T. timopheevii, and those found in Glu-D1 –

from the diploid Ae. tauschii. These findings

were supported by studies of Wan et al.

(2002), Li et al. (2007) and Obukhova et al.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

(2009) showing two HMW glutenin subunits

in the G-genome, х- and у- subunit. They have

lower electrophoretic mobility, but higher

molecular weight than 1Вх7 in Glu-В1 of

wheat varieties Bezostaya 1 and Chinese

spring. The classical Laemmli system (12%

SDS-PAGE) could not differentiate the

subunits, expressed in T. timopheevii, because

of their overlap. With the help of 10% SDS-

PAGE with 4М urea, they were divided and

identified (Тоdorov, 2006).

Synthetic H-69/36 exerted the following

HMW-GS: 1Ах 2* and 1Ау in Glu-A1, 1Вх7

in Glu-В1, and 1Gx in Glu-G1 (Fig. 3-4).

Аllele b, coding 1Ах 2* in Glu-A1, was

inherited from Т. turaniсum. Results of 12%

SDS-PAGE and 10% SDS-PAGE with 4М

urea showed the presence of only subunit x in

Glu-G1. The second fraction, differing in

molecular weight and electrophoretical

mobility among those of 1Ву9 and 1Dy10 in

Glu-1 of wheat checks Bezostaya 1 and

Chinese Spring, was identified as subunit 1Ay,

transferred to H-69/36 from the locus Glu-A1

of T. timopheevii. Our data are in conformity

with Hu et al. (2012) for similarity of 1Ay

with 1Вх7, 1Ву8, 1Dy10 and 1Dy12 in many

Triticum species, and its exhibition even

stronger than 1Dy12 in common wheat.

Fig. 1. 12% SDS-PAGE of HMW-GS: 1. Ае. tauschii,

2. Bezostaya 1; 3. AD Н-68/44; 4. Chinese Spring; 5.

Т. timopheevii.

Fig. 2. 10% SDS-PAGE of HMW-GS wth urea:

1. Ae. tauschii; 2. Bezostaya 1; 3. AD Н-68/44; 4.

Chinese Spring; 5. Т. timopheevii.

Fig. 3. 12% SDS-PAGE of HMW-GS: 1. T.

turanicum; 2. Bezostaya 1; 3. AD Н-69/36; 4.

Chinese Spring; 5. Т. timopheevii.

Fig. 4. 10% SDS-PAGE of HMW-GS wth urea: 1. T.

turanicum; 2. Bezostaya 1; 3. AD Н-69/36; 4. Chinese

Spring; 5. Т. timopheevii.

Synthetic H-68/44 expressed 12 fractions in

LMW-GS (5 major and 7 minor), against 11

glutenin subunits for AD H-69/36 (Fig. 5-6).

LMW-GS were identified in the В-zone,

probably inherited from T. timopheevii.

According to the nomenclature of Gupta and

Sheppherd (1990) for the low molecular

weight of glutenins in common wheat, the two

synthetics displayed a subunit in Glu-A3,

probably coded by c allele. Two subunits in

Glu-D3 of H-68/44, similar to the expression

of a allele in common wheat cv. Chinese

Spring, were also found. They might originate

from the diploid Ae. tauschii. The protein

composition of Glu-B3 in AD H-69/36 was

not identified.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Fig. 5. 12% SDS-PAGE of

LMW–GS in Glu-D3: 1.

Bezostaya 1; 2. AD H-68/44; 3.

Chinese Spring; 4. AD H-69/36;

arrows indicate Glu-D3 subunits

in H-68/44 on the a allele in

Chinese Spring; Bezostaya

1 has c allele in Glu-D3.

Fig. 6. 10% SDS-PAGE with

4М урея in Glu-A3: 1.


Chinese Spring; 4. AD H-69/36;

arrows indicate Glu-A3 subunits

on the level of c allele in

Bezostaya 1; Chinese Spring has

a allele in Glu-A3.

Fig. 7. А-PAGE in gliadins: 1.


AD H-69/36; arrows indicate Gli

subunits corresponded to w1 and

w2 from Bezostaya 1; γ 43.5 is

marked in H-69/36 and

Bezostaya1.

Each synthetic line was characterized by a

distinct spectrum of gliadins (Fig. 7). AD Н-

68/44 exerted 22 bands (eight are ω-, five-γ-,

six-β- and three-α-gliadins). Slow moving pair

of ω-fractions, characteristic for Gli-D1 of

wheat check Bezostaya 1 and for any

hexaploid wheat variety, was also identified.

Six ω-, six γ-, five β- and two α-gliadins were

visualized in synthetic H-69/36. The typical

ω1- and ω2- subunits for wheat cultivars were

not expressed in this synthetic. One γ-gliadin

43.5, coded by a gene in Gli-B1 locus, was

indicated. This subunit is characteristic for

common wheat, corresponding to good gluten

quality (Тоdorov, 2006).

Conclusions

1. Expression of subunit 1Gx at Glu-G1 in two

synthetic wheat lines involving the G genome

of Triticum timopheevii, was recorded.

2. Synthetic H-69/36 exerted 1Ау subunit,

coded by a gene in Glu-A1 locus. A gliadin for

good gluten quality (γ- 43.5) was only

registered in this amphidiploid. 3. Synthetic line Н-68/44 displayed HMW-GS

1Dx2 and 1Dy12.4 subunits and different

LMW-GS in B- and D-zones, which were

absent in check wheat cultivars Bezostaya 1

and Chinese Spring. Additionally, both

synthetics showed a lot of gliadin alleles and

could be of great interest as sources of genes

for improved grain quality in wheat.

References

1. Brown-Guedira, G., Gill, B., Cox, T.,

Leath S. (1997). Transfer of disease genes

from Triticum araraticum to common wheat.

Plant Breeding No. 116, pp. 105-112.

2. Ciaffi, M., Dominici, L., Lafiandra D.

(1998). High molecular wight glutenin subunit

variation in wild and cultivated einkorn wheats

(Triticum ssp. Poaceae). Plant Syst. Evol. No.

209, pp. 123-137.

3. Gianibelli, M.C., Gupta, R.B.,

Lafiandra, D., Margiotta, B., MacRitchie F.

(2001). Polymorphism of High Mr Glutenin

Subunits in Triticum tauschii :

Characterisation by chromatography and

electrophoretic methods. Journal of Cereal

Science No. 33, pp. 39-52.

4. Goncharov, N.P., Golovina, K.A.,

Kondratenko E.Y. (2009). Taxonomy and

molecular phylogeny of natural and artificial

wheat species. Breeding Science No. 59, pp.

492-498.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

5. Gupta, R.B., Shepherd K.W. (1990).

Two-step one-dimensional SDS-PAGE

analysis of LMW subunits of glutenin.1.

Varation and genetic control of the subunits in

hexaploi wheats. Theor. Appl. Genet. No. 80,

pp. 65–74.

6. Hu, X.G., Wu, B.H., Bi, Z., Liu,

D.C., Zhang, L.Q., Yan, Z.H., Wei, Y.M.,

Zheng Y.L. (2012). Allelic variation and

distribution of HMW glutenin subunit 1Ay

in Triticum species. Genet. Resour Crop

Evol. No. 59, pp. 491-497.

7. Jackson, E.A., Holt, L.M., Payne P.I.

(1983). Characterization of high–molecular-

weight gliadin and low-molecular-weight

glutenin subunits of wheat endosperm by two-

dimensional electrophoresis and chromosomal

localisation of their controlling genes.

Theoretical and Applied Genetics No. 66, pp.

29-37.

8. Jackson, E.A., Morel, M.H., Sontag-

Strohm, T., Branlard, G., Metakovsky, E.V.,

Redaelli R. (1996). Proposal for combining the

classification systems of alleles of Gli-1 and

Glu-3 loci in bread wheat. Journal of Genetics

and Breeding No. 50, pp. 321–336.

9. Jauhar, P.P., Peterson, T.S. (2006).

Cytological analyses of hybrids and

derivatives of hybrids between durum wheat

and Thinopyrum bessarabicum, using

multicolour fluorescent GISH. Plant Breeding

No. 125, pp. 19 – 26.

10. Johansson, E., Henriksson, P.,

Svensson, G., Heneen W.K. (1993). Detection

chromosome location and evalution of the

functional value of a novel high Mr glutenin

subunit found in Swedish wheats. J. Cereal

Sci. No. 17, pp. 237-245.

11. Khan, K., McDonald, E., Banasik, O.J.

(1983). Polyacrylamide gel electrophoresis of

gliadin proteins for wheat variety.

Identification-procedural modifications and

observations. Cereal Chem. No. 60, pp. 178-

181.

12. Laemmli, U.K. (1970). Clavage of

structural proteins during the assembly of the

head of bacteriofage T4. Nature No. 227, pp.

680 – 685.

13. Lafiandra, D., D’Ovidio, R., Porceddu,

E., Margiotta, B., Colaprico G. (1993). New

data supporting high Mr glutenin subunits as

the determinant of quality differences among

the pairs 5 + 10 vs. 2 + 12. Journal of Cereal

Science No. 18, pp. 197-205.

14. Leonova, I., Budashkina, E., Kalinina,

N., Röder, M., Börner, A., Salina E. (2011).

Triticum aestivum-Triticum timopheevii

introgression lines as a source of pathogen

resistance genes. Czech. J. Genet. Plant.

Breed. No. 47 (Special Issue), pp. S49-S55.

15. Li, B., You, M., Liang, R., Zhang, Y.,

Liu G. (2002). Polymorphism of high

molecular weight glutenin subunits coded by

G-genome. J. China Agric. Univ. No. 7, pp.

33-37.

16. Li, Q.Y., Yan, Y.M., Wang, A.L., An,

X.L., Zhang, Y.Z., Hsam, S.L.K., Zeller, F.J.

(2006). Detection of HMW glutenin subunit

variation among 205 cultivated emmer

accessions (Triticum turgidum ssp. dicoccum).

Plant Breeding No. 125, pp. 120-124.

17. Li, X., Zhang, Y., Gao, L., Wang, A.,

Ji, K., He, Z., Appels, R., Ma, W., Yan Y.

(2007). Molecular cloning, heterologous

expression, and phylogenetic analysis of a

novel y-type HMW glutenin subunit gene

from the G genome of Triticum timopheevi.

Genome No. 50, pp. 1130-1140.

18. Masci, S., Rovelli, L., Kasarda, D.D.,

Vensel, W.H., Lafiandra D. (2002).

Characterisation and chromosomal

localization of C-type low-molecular-weight

glutenin subunits in the bread wheat cultivar

Chinese Spring. Theoretical and Applied

Genetics No. 104, pp. 422–428.

19. McIntosh, R., Yamazaki, Y.,

Dubcovsky, J., Rogers, J., Morris, C., Somers,

D., Appels, R., Devos K. (2008). Catalogue of

gene symbols for wheat. Available at

http://www.shigen.nig.ac.jp/Wheat/komugi/ge

nes

20. Monneveux, P., Zacharieva, M.,

Rekika (2000). The utilisation of Triticum and

Aegilops species for the improvement of

durum wheat. Options Mediterraneennes, Serie

A: Seminares Mediterraneennes, № 40, pp.

71–81.

21. Mujeeb-Kazi, A. (2005). Wide crosses

for durum wheat improvement. In: Durum

wheat breeding – Current approaches and

future strategies. C. Royo, M. Nachit, N. Di

Fonzo, J.L. Araus, W. Pfeiffer, G. Slafer –

Eds. Food Products Press, New York*

London*Oxford, Vol. 2, pp.703- 745.

22. Obukhova, L., Budashkina, E.,

Shumni V. (2009). A study of the storage

proteins in the introgression lines of common

wheat (Triticum aestivum L. x Triticum

timopheevii Zhuk.) resistant to brown leaf

http://www.shigen.nig.ac.jp/Wheat/komugi/genes

http://www.shigen.nig.ac.jp/Wheat/komugi/genes


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

rust. Russian Journal of Genetics Vol.45, № 3,

pp. 313-321.

23. Payne, P.I., Lawrence, G.J. (1983).

Catalogue of alleles for the complex gene loci,

Glu – A1, Glu – B1 and Glu – D1 which code

for high-molecular-weight subunit in

hexaploid wheat. Cereal Rresearch

Communications No. 11(1), pp. 29-35.

24. Plamenov, D., Spetsov, P. (2011).

Synthetic hexaploid lines are valuable

resources for biotic stress resistance in wheat

improvement. J. Plant Pathol. No. 93 (2), pp.

251-262.

25. Singh, N.K., Shepherd, K.W. (1988).

Linkage mapping of genes controlling

endosperm storage proteins in wheat

endosperm. Theor. Appl. Genet. No. 71, pp.

79-92.

26. Singh, N.K., Shepherd, K.W, Cornish

G.B. (1991). A simplified SDS-PAGE

procedure for separating LMW subunits of

glutenin. Journal of Cereal Science No. 14, pp.

203-208.

27. Spetsov, P., Plamenov, D., Kiryakova

V. (2006). Distribution and characterization of

Aegilops and Triticum species from the

Bulgarian Black Sea coast. Central European

Journal of Biology No. 1(3), pp. 399-411.

28. Тоdorov, I. (2006). Study on seed

proteins and their application as genetic

markers in wheat breeding. D. Sci.

dissertation, NCАN, Sofia.

29. Wan, Y., Wang, D., Shewry, P.,

Halford N. (2002). Isolation and

characterization of the five novel high

molecular weight subunit of glutenin genes

from Triticum timopheevi and Ae. cylindrica.

Theor. Appl. Genet. No. 104, pp. 828-839.

30. William, M.D.H.M., Peña, R.J.,

Mujeeb-Kazi A. (1993). Seed protein and

isozyme variations in Triticum tauschii (

Aegilops squarrosa). Theor. Appl. Genet. No.

87, pp. 257-263.

31. Yan, Y.M., Hsam, S.L.K., Yu, J.Z.,

Jiang, Y., Zeller F.J. (2003). Genetic

polymorphisms at Gli-Dt gliadin loci in

Aegilops tauschii as revealed by acid

polyacrylamide gel and capillyary

electrophoresis. Plant Breeding No. 122, pp.

120-124.

32. Zaharieva, M., Dimov, A., Stankova,

P., David, J., Monneveux P. (2003).

Morphological diversity and potential interest

for wheat improvement of three Aegilops L.

species from Bulgaria. Genetic Resources and

Crop Evolution, Vol. 50, № 5, pp. 56-61.


UDC 635.21-186(497.742)


____________________________________________________________________________________________________

THE INFLUENCE OF FOLIAR FERTILIZATION WITH ORGANIC FERTILIZERS

ON THE YIELD AND THE CHEMICAL CONTENT OF POTATOES GROWN IN

STRUMICA REGION

M. T. Stojanova1*, L. Karakashova1, H. Poposka2,

I. Ivanovski1, B. Knezevic3

1Faculty of agricultural sciences and food, University of Ss. Cyril and Methodius, Skopje,

Republic of Macedonia 2Institute of agriculture, University of Ss. Cyril and Methodius, Skopje, Republic of

Macedonia 3Faculty of agriculture, University of Prishtina, Prishtina, Republic of Kosovo


Abstract

The effect of foliar fertilization with organic fertilizers on the yield and the chemical content of

potatoes grown in Strumica region were studied, in the period from the year of 2011-2012. The

experiment was set in four variants and three repetitions. The variants in the experiment were: Control

(no-fertilizing variant); Humusil (organic matter 1.86%; organic carbon 1.08%; humin acids 0.14%; N

224 mg/L; P2O5 71 mg/L; K2O 1024 mg/L; CaO 180 mg/L); Humustim (organic matter 58.63 %; dry

matter 12.38 %; humin acids 20.40 %; fulvo acids 2.15%; N 3%; P2O5 1.02%; K2O 7.92%; Ca 3.70

%; Mg 1.03%); Ingrasamant foliar (N 0 %; P2O5 130 g/L; K2O 130 g/L; ME in helate form and plant

extracts 0.005 g/L). The experiment was arranged in 12 rows and in each variant and repetition was

involved 100 plants, total in all experiment were involved 1200 plants. The planting was made in

rows at a distance of 60 cm row by row and 20 cm in the rows. The row’s length was 20 m. Three

foliar treatments were applied with given above fertilizers at a concentration of 0.4%. The soil where

the experiment was carried had a good fertility with nitrogen, phosphorus and potassium. The foliar

fertilization had a positive influence on potatoes yield in all of the variants treated with different

organic fertilizers. The highest potatoes yield of 54.62 t ha-1 was established in variant 4. The foliar

fertilization had a positive influence on the chemical content of tubers potato, too. In three variants

treated with different fertilizers, higher content of all tested parameters was found, compared to the

control untreated variant. The highest average content of vitamin C (2.60 mg/100g), phosphorus (0.90

%), and potassium (1.30 %) was determined in the tubers potato in variant 3.

Key words: potatoes, foliar fertilization, yield.

Introduction

The main goal in the modern agriculture is to

obtained higher yields that are characterized

with good quality.

One of the most important agricultural

measures, which together with the others

should allow continuous, high and cost

effective production, is plant nutrition

(Vukadinović and Lonćarić, 1997).

For normal growing, bigger yield and getting

quality fruits is necessary normal regime of

plant nutrition. Regular nutrition means

availability of all macro and micro biogenic

elements in the right phenophases of the plant

development (Jekić, 1983, Horvat et al.,

2008). Each biogenic element has its specific

influence on the different plant parts. Plant

nutrition has an influence on numerous

physiological – biochemical processes, of

which depends growing, developing and

potato yield. Plants that are timely and regular

nourished, gets fruits with characteristic form,

color and size, with typically organoleptic

properties (Sarić et al., 1989; Šaćiragić and

Jekić, 1988). Because of different reasons,

often happens limiting of biogenic elements in

the root area. Intensive agriculture and use of

high productivity cultivars led to a continuous

decrease in soil micronutrient content (Ebert

2009, Kalinova et al., 2014). Using of foliar


82 M. T. Stojanova, L. Karakashova, H. Poposka, I. Ivanovski, B. Knezevic

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

fertilizers in the crop cultures nutrition, has a

big influence for getting higher yields and

productions that are characterized with better

quality, too. Using of foliar fertilizers allows

directly supply of leafs, flowers and fruits with

biogenic elements in the most needed period.

Foliar fertilization is a widely used practice to

correct nutritional deficiencies in plants caused

by improper supply of nutrients to roots

(Poljak, et al 2005, Tomov et al., 2009). Foliar

spray with fertilizers is necessary to further

activity in the whole system of optimal

mineral nutrition of plants. Foliar spray

provides more economical water regime of

plants and allows overcoming the

physiological disturbances caused by adverse

soil conditions that hamper mobility and

absorption of nutrients (Kostadinov and

Kostadinova, 2014). Potato, as one-year

culture, has a big economic importance. The

most importance has in the human nutrition, as

raw material in the industry and in the

livestock nutrition. In the human nutrition has

a principle place because of its using for

preparing lot of foods.

Potato is irreplaceable for preparing diet food.

By industrial processing, potato can

dehydrates and in this form it is easier for

keeping and transporting. In the food industry

it is using for preparing flour, mashed, fries

etc. It is also used by many other industries for

getting alcohol, starch, glucose, doctrines, and

maltose. Potato is widely used in the

conservatory and pharmacy industry (Lazić,

1990).

In the livestock nutrition it has great

importance for dairy and fattening livestock.

Potato is an excellent pre-culture for all the

cultures, especially for the cereals. After

potato harvesting, soil stay clean and loose

(Maksimoviћ and Jain, 1996). This makes it

suitable for preparation and sowing of autumn

crops. Potato is root vegetable that is

characterized with big nutrition value. Potato

is one of the richest sources of starch, minerals

and fiber. It contains vitamins A, C and B6,

minerals such as: iron, manganese, copper and

potassium (Ðinović, 1989).

The aim of this exploration is to determine the

influence of foliar fertilization with liquid

organic fertilizers on the yield and the

chemical content of potatoes grown in

Strumica region.


In the Strumica region, in the vicinity of the

village Kuklis during the years of 2011 and

2012 was appointed field experiment in the

protected space of 96 m2.

Material of work was potato cultivar carrera.

This is early cultivar and its vegetation period

is 95-100 days. The tubers have right globular

oval form. The experiment was set in 12 rows.

The tests included 4 variants and 3 repetitions.

Seeding was obtained in raw spacing of other

60 cm and between plants 20 cm. The rows

had 20 m length. In each variant and repetition

were included in 100 plants and total for the

whole experiment had 1200 plants. The

experiment was set in terms of watering.

During the potato vegetation period were

applied all basic agricultural measures.

Variants in the experiment were:

1. Control (no-fertilizing);

2. Humusil;

3. Humustim;

4. Ingrasa mant.

Each variant was treated foliar with 0.4%

solution of the tasted fertilizers. The

application of fertilizers was done with hand

spray, by spraying the played leaves. The

treatments were made in the evening hours.

During the vegetation were conducted seven

foliar treatments.

Three types of fertilizers were used:

Humusil (organic matter 1.86%, organic

carbon 1.08%, humic acid 0.14%, N 224

mg /L, P2O5 71 mg /L, K2O 1024 mg /L,

CaO 180 mg /L);

Humustim (organic matter 58.63%, dry

matter 12.38%, humic acids 20.40%, fulvo

acids 2.15%, N 3%, P2O5 1.02%, K2O

7.92%, Ca 3.70%, Mg 1.03 %);

Ingrasa mant (N 0%, P2O5 130 g/L, K2O

130 g/L, ME in helate form, plant extracts

0.005 g/L).

The harvesting was carried out in the full

maturity of the potatoes separately by

variations and repetitions.

Before setting up the experiment soil samples

were taken for agrochemical and analyses

were performed on the following parameters:

pH value determined potentiometric with

pH meter (Bogdanović, et al., 1966);

Content of easy available nitrogen –

determined

by method of Tjurin and Kononova;

Content of easy available phosphorus –

determined by AL method and reading of


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

spectrophotometer (Bogdanović et al.,

1966);

Content easy available potassium –

determined by AL method and reading of

spectrophotometer (Bogdanović et al.,

1966);

Content of carbonates –

determined with Schaiblerov Calcimeter

(Bogdanović et al., 1966).

In the tubers potato separately by variants the

following parameters were performed:

- Moisture content - determined by

calculation when from 100%, the

percentage of total dry matters is

deducted;

- Content of total dry matters - determined

by drying the material in dryer on

temperature of 105 °C;

- Content of organic matter - determined by

calculation when from 100% the

percentage of total ash will be deducted.

- Content of total ash - determined by

removing moisture from the prepared

material, drier on temperature of 105°C.

Then the rest was burned in electric oven

by gradually increasing the temperature to

550°C. The burning was done until ashes

became grey or white;

- Content of vitamin C - determined by

method of Thilmans, which is based on the

redox reaction between L-ascorbic acid

and organic color 2.6-

dichlorophenolindophenol;

- Content of nitrogen (N) - determined by

Kjeldhal method (Saric et al., 1989);

- Content of phosphorus (P2O5) -

determined using atomic emission

spectrometry with inductively coupled

plasma (ICP - AEC) (Saric et al., 1989);

- Content of potassium (K2O) - determined

by incineration of the material with

concentrated H2SO4 and plamenfotometar

(Saric et al., 1989);

- Content of proteins - determined with

calculation when the % N is multiplying

with coefficient 6.25.

- Content of iron (Fe) - determined using

atomic emission spectrometry with

inductively coupled plasma (ICP - AEC)

(Saric et al., 1989);


For getting high and quality potato yields it is

necessary favorable soil and climatic

conditions. The best potato yields are getting

in deep sand and loose soil rich in readily

available nutrients.

The optimal soil pH value for potato is weakly

acidic from 6.0 till 6.5. Potato requires high

soil permeability because tubers are deformed

by compact soils. Potato requires good soil

drainage. Waterlogged soil leads to numerous

physiological changes in tuber that become

watery and difficult to store. For successful

cultivation of potatoes of great importance is

the presence of organic matter improves soil

structure and water capacity (Lazić et al.,

2001, Baniuniene and Zekaite, 2008).

In Table 1 are shown the results of the soil

agrochemical analysis before setting up the

experiment.

Table 1. Agrochemical soil analysis

No. Tag Deep

(cm)

pH Available forms (mg/100 g soil) CaCO3

(%) H2O KCl N P2O5 K2O

1 Potato I

part

0-20 7.35 6.75 8.30 20.70 25.20 /

2 20-40 7.40 6.70 8.10 21.30 24.80 /

Average 0-40 7.37 6.72 8.20 21.00 25.00 /

3 Potato II

part

0-20 7.43 6.80 8.15 22.00 22.80 /

4 20-40 7.40 6.85 8,10 20.30 25.70 /

Average 0-40 7.41 6.82 8.12 21.15 24.25 /

From the data in the table can be concluded

that soil in which the experiment was carried

out has neutral pH, and good fertility with the

available nitrogen, phosphorus and potassium.

There is no presence of carbonates.

In Table 2 are shown the results for obtained

yield in different varieties.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Table 2. Average potato yield 2011/2012

Variant Total yield per

variant (kg)

Average per

plant (kg)

Yield (t ha-1)

1 114.90 0.383 47.87

2 121.50 0.405 50.62

3 126.90 0.423 52.87

4 131.10 0.437 54.62

LSD (0.05) = 2.403

LSD (0.01) = 3.497

Table 3. Average chemical content of tubers 2011/2012 (% of dry matter)

Parameter Variant

1 2 3 4

Hygroscopic water 75.20 76.35 76.50 75.10

Dry matter 24.80 23.65 23.50 24.90

Organic matter 96.30 96.25 96.00 95.90

Ash 3.70 3.75 4.00 4.10

Vitamin C mg/100g 2.40 2.52 2.60 2.48

N 0.97 0.99 1.10 1.15

P2O5 0.75 0.87 0.90 0.87

K2O 1.18 1.23 1.30 1.25

Fe 0.35 0.30 0.36 0.37

Proteins 6.09 6.22 6.90 9.42

From the obtained data can be concluded that

foliar fertilization with liquid organic

fertilizers had a positive influence on potato

yield achieved. In all of the variants with

different organic fertilizers was obtained

higher yield compared to control (no-

fertilizing) variant. Higher yield (54.62t ha-1)

was obtained in variant 4 where the treatments

were made with organic fertilizer Ingrasa mant

(N 0%, P2O5 130 g/L, K2O 130 g/L, ME in

helate form, plant extracts 0.005 g/L).

The lowest yield (47.87 t ha-1) was determined

in control (no-fertilizing) variant. The

differences in achieved potato yield between

separated variants were small. The positive

foliar influence of used organic fertilizers on

potato yield is due to their chemical

composition. The presence of micro elements

in the analyzed fertilizers has a great influence

on the regular growing, development and

potato yield (Gramatikov, 2005 Bansal and

Trehan 2011). This elements has an influence

on numerous physiological – biochemical

processes that has a vital importance on

culture vegetation cycle. Balanced nutrition

plays a significant role for increasing of crop

production and its quality and presents an

essential component of nutrient management

(Panayotova et al., 2014).

Obtained results in all of the variants with

different organic fertilizers are statistically

significant at LSD (0.05) level, but in the

variants 3 and 4 the statistically significance is

at LSD (0.01) level.

Foliar fertilization has a positive influence on

the content of all determined parameters in the

tubers (Table 3). In all of the variants treated

with different kinds of fertilizers, the analyzed

parameters have higher content compared to

the control one.

The highest average content of dry matters

(24.90%) and ash content (4.10%) was

determined in the tubers from variant 4. The

content of hygroscopic water is correlated with

the content of dry matters, and its value is the

highest in the variant 3 (76.50%). The content

of organic matter (96.30%) is the highest in

the control variant. The highest average

content of vitamin C (2.60 mg/100g),

phosphorus (0.90%) and potassium (1.30%)

was determined in the tubers from variant 3.

The highest average content of nitrogen

(1.15%), proteins (9.42%) and iron (0.37%)

was determined in the tubers from variant 4.

Conclusions

Based on the obtained results for the influence

of foliar fertilization with different liquid

organic fertilizers on potato yield, the

following conclusions can be made:

The soil where the experiment was carried

out had a good fertility with nitrogen,

phosphorus and potassium;


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Foliar fertilizing had achieved positive

effects in all variants treated with different

organic fertilizers compared to control

one;

The highest yield, 54.62 t ha-1 of potato

was determined in variant 4 (Ingrasa mant

(N 0%, P2O5 130 g/L, K2O 130 g/L, ME in

helate form, plant extracts 0.005 g/L));

The results in all variant are statistically

significant at the level LSD (0.05), and the

results in variants 3 and 4 has statistical

significance on the level LSD (0.01);

The highest average content of vitamin C

(2.60 mg/100g), phosphorus (0.90%) and

potassium (1.30%) was determined in the

tubers from variant 3 (Humustim (organic

matter 58.63%, dry matter 12.38%, humic

acids 20.40%, fulvo acids 2.15%, N 3%,

P2O5 1.02%, K2O 7.92%, Ca 3.70%, Mg

1.03 %));

The highest average content of nitrogen

(1.15%), proteins (9.42%) and iron

(0.37%) was determined in the tubers from

variant 4 (Ingrasa mant (N 0%, P2O5 130

g/L, K2O 130 g/L, ME in helate form,

plant extracts 0.005 g/L)).

References

Baniuniene A., Zekaite V. (2008). The effect

of mineral and organic fertilizers on potato

tuber yield and quality. Latvian Journal of

Agronomy, Vol. 11, pp. 127-132.

Bansal S., Trehan S. (2011). Effect of

potassium on yield and processing quality

attributes of potato. Karnataka Journal of

Agricultural Sciences, Vol. 24, No. 1, pp. 48-

54.

Bogdanović, M., Velikonja, N., Racz, Z.

(1966). Chemical methods for soil exploration.

Manual for Soil Exploration, Book I,

Belgrade, pp. 44, 162, 184, 189.

Ebert G. (2009). Potassium nutrition and its

effect on quality and post harvest properties of

potato. Proceedings of the International

Symposium on Potassium Role and Benefits in

Improving Nutrient Management for Food

Production, Quality and Reduced

Environmental Damages 1, pp. 637- 638.

Gramatikov, B. (2005). Effect of

microfertilizer “Humustim” on the

productivity of some field crops. 2nd Barley

response, Balkan Science Conference, Book of

proceedings, Karnobat, Vol. 2, pp. 476-479.

Horvat, T., Poljak, M., Majić, A., Svečnjak,

Z., Jurkić, V. (2008). Effects of foliar

fertilization and water stress on yield and

physiological characteristics of potato. Cereal

Research Communications, Vol. 36, No. 3, pp.

1659-1662.

Jekić, M. (1983). Agro-chemistry I, University

of “Ss. Cyril and Methodius”, Skopje, pp. 160-

180.

Kalinova, St., Kostadinova, S., Hristoskov, A.

(2014). Nitrogen use efficiency and maize

yield response to nitrogen rate and foliar

fertilizing. Bulgarian Journal of Agricultural

Science, No. 20, pp. 194-197.

Kostadinov, K., Kostadinova, S. (2014).

Nitrogen efficiency in eggplants (Solanum

Melongena L.) depending on fertilizing.

Bulgarian Journal of Agricultural Science, No.

20, pp. 287-292.

Lazić, B. (1990). Health from garden all year,

Nolit, Belgrade, pp. 146-147.

Lazić, B., Marković, V., Ðurovka, M., Ilin, Z.

(2001). Vegetable from protected spaces,

Nolit, Belgrade, pp. 75-82.

Maksimoviћ, P., Jain, N. (1996). Vegetable

production, Nolit, Belgrade, pp. 32-37.

Panayotova, G., Bozhanova, V., Kostadinova,

S., Valkova, M., Almaliev, A. (2014).

Response of durum wheat (Triticum durum

Desf.) cultivar progress to foliar feeding,

Journal of International Scientific

Publications: Agriculture and Food, Vol. 2, pp.

288-297.

Poljak, M., Ćosić, T., Herak Ćustić, M.,

Horvat, T., Buturac, I. (2005). Potato nitrogen

fertilization efficiency. Proceedings of the XL

Croatian Symposium on Agriculture with

International Participation. Faculty of

Agriculture, University of J. J. Strossmayer,

Osijek, pp. 369-370.

Sarić, M., Stanković, Z., Krstić, B. (1989).

Plant Physiology, Agricultural Faculty, Novi

Sad, pp.250-270.

Takacs Hajos, M., Szabo, L., Racz, I., Mathe,

A., Szőke, E. (2007). The effect of Mg-leaf

fertilization on quality parameters of some

horticultural species. Cereal Research

Communications, Vol. 35, No. 2, pp. 1181-

1184.

Tomov T., Rachovski G., Kostadinova S.,

Manolov I. (2009). Handbook of

Agrochemistry. Academic publisher of

Agricultural University Plovdiv, pp. 109.

Vukadinović, V., Lonćarić, Z. (1997). Plant

nutrition, Agricultural Faculty, Osijek, pp. 98-

110.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Šaćiragić, B., Jekić, M. (1988).

Agrochemistry, Agricultural Faculty, Sarajevo,

pp. 140-158.

Ðinović, I. (1989). Your vegetable production,

Publishing and Journalism Center, Belgrade,

pp.105-107.


UDC 633.1582.661.21]:631.589.2


____________________________________________________________________________________________________

THE EVALUATION OF GRAIN AND OIL PRODUCTION, SOME PHYSIOLOGICAL AND

MORPHOLOGICAL TRAITS OF AMARANTH ‘CV. KONIZ’ AS INFLUENCED BY THE

SALT STRESS IN HYDROPONIC CONDITIONS

M. Yarnia1*, M. B. K.Benam2, E. Farajzadeh3, V. Ahmadzadeh4 N. Nobari4

1Department of Agronomy and Plant Breeding, Tabriz Branch, Islamic Azad University, Tabriz, Iran 2East Azarbaıjan Agrıcultural and Natural Resources Research Center, Tabriz, Iran

3Malekan Branch, Islamic Azad University, Malekan, Iran 4Tabriz Branch, Islamic Azad University, Tabriz, Iran


Abstract

The purpose of this study was investigation of salinity effect on some traits of Amaranth. A split plot

designed with three replications with two factors: 5 salinity levels (control, 75, 150, 225, 300 mM

NaCl) and applied time at 4 levels (plant establishment, branching, flowering, grain filling) in a

greenhouse under hydroponic system. Application of 300 mM salinity after plant establishment led to

death of amaranth. Salinity application after establishment decreased significantly plant height and

number of branches as 44.9 and 31.8, respectively. Production of grain weight was not affected by 75

mM salinity, but at higher salinity showed significantly decrease. The highest decrease in grain

weight obtained by applying 225 mM salt after the plant establishment and salinity at 300 mM after

branching as 86.6 and 71.3 percent respectively, resulting in a decrease in both 1000 kernel weight

and grain number, respectively. Salinity application increased H2O2, MDA and total phenolics

contents, severely. Most of characteristics hadnot affect by 75 mM NaCl, but other concentrations had

a negative effect on the growth and production of Amaranth and increasing salinity had more negative

impact. In this study, the most sensitive to salinity was after plant establishment and grain filling stage

was the most tolerant.

Key words: Amaranth, growth stage, salinity, yield.

Introduction

Amaranth belongs to genus Amaranthus. The

genus includes about 60 species of amaranth

that the majority of them are wild. Some of

them as edible crops and some of them are

used as ornamental crop (Borneo & Aguirre,

2008; Pospisil et al., 2006). Based on the soil

map published in recent years, the area of soils

with low to moderate salinity is 25.5 million

hectares and 8.5 million hectares of soils

tolerate high salinity (Almodares et al., 2008).

Salinity leads to serious changes in the

photosynthesis and photorespiration of plants

(Vega et al., 2006). High levels of sodium

reduce potassium adsorption and its

accumulation in the cytoplasm stopped the

activity of many enzymes (Jaleel et al., 2008),

because, potassium had import role in various

processes such as metabolism, growth and

adaptation to stresses. The salinity prevents

enzyme activity, cell division and

development, and causes disorganization of

the membrane and ion balance and eventually

led to the growth stop (Mahajan et al., 2008).

Salinity had a significant reduction in growth

and yield of Amaranthus family. Omami

(2005) and Omami et al., (2006) studied

salinity impact on Amaranth cultivars ( A.

tricolor ،Accession ’83 ،A. hypochondriacus

and A. cruentus showed that increasing salinity

in the soil leads to a significant reduction in

crop height, leaf area, specific leaf area, and

stomatal conductance rates. Dave and Patel

(2011) examined effect of salinity 2.7, 5.5, 8.5,

11.1 and 13.8 ds/m in A. lividus. The root and

shoot length, number of leaves, fresh and dry

weight of leaves, roots and stems showed a

significant decreased with increasing salinity

levels. In this study proline showed a

significant increase with increasing salinity,

while chlorophyll content reduced by salinity.

Salinity reduced number of hairy roots and


88 M. Yarnia, M. B. K.Benam, E. Farajzadeh, V. Ahmadzadeh.N. Nobari

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

distal root growth and root cells were more

resistant to water penetration (Wang & Li,

2008). Malondialdehyde (MDA) a product of

lipild peroxidation, showed greater

accumulation in plants under stress condition.

Cell membrane stability has been widely used

to differentiate stress tolerant and susceptible

cultivars of some crops, and in some cases,

lower MDA content could be correlated with

stress tolerance (Wang et al., 2009). As salt

stress occur frequently and can affect most

habitats, plants have developed several

strategies to cope with these challenges. One

of the stress defense mechanisms is the

antioxidant defense system, which includes

antioxidant enzymes. antioxidant enzymes

converts H2O2 into water and oxygen (Gaber,

2010). Soil salinity is one of the most

important environmental and ecological

tensions in many parts of the world, nowadays

is one of the main reasons in reduction of

agricultural products. Grain amaranth is new

crop with high yield potential and good

nutrition can be a good substitute for salt-

sensitive crops in such areas. Growth study

reactions and seed production in saline

conditions and determining plant tolerance to

salinity and the sensitivity of the different

growth stages were important also.


The experiment was conducted in greenhouse

of Tabriz Branch, Islamic Azad University,

located at 15 km East of Tabriz in 2013. This

place located at 46, 17 E and 38, 5 N degrees

with 1360 meters altitude. Salinity factor

levels in 5 different levels (control, salinity

stress, 75, 150, 225 and 300 mM NaCl) and

applied stress time at 4 levels (plant

establishment, branching, flowering and grain

filling) under hydroponic system with

Hoagland solution arranged as split plot with

three replications in grain amaranth CV. Koniz

(Amaranthus hypochindriacus L.×

Amaranthus hybridus L.) as a new crop. 1100

g. perlite medium grain size was filled into

pots. Seeds randomly distributed on the

surface of the perlite. Nutrition of crops was

supplied by using nutrient solution after

emergence. Hoagland's A-Z solution is used to

provide macro and micro nutrients (Nenova,

2008). 2 weeks after emergence, seedlings

have been thinned to 5 plants per pot and in

third week after emergence were kept only 3

plants per pot. Every 4 days nutrient solution

(1/2 fold in the early period of growth) was

supplied to plants (Nenova, 2008). The amount

of used solution for treatment was determined

based on available water in each pot. For this

purpose, the weight of irrigated perlite

determined after 24 hours and the initial

weight of pearlite before irrigation was

fractioned. Then the amount of water turned to

volume. The resulted number is between 550

to 600 mL of water for each pot. Accordingly,

550 mL of each solution was used for the

treatments. No water leaching was permitted

from pots. After 30 days excess water used to

leaching pots. Hydrogen peroxide content in

amaranth leaves at grain filling stage were

determined according to Velikova et al.,

(2000). The level of lipid peroxidation

(Malondialdehyde: MDA) was determined in

terms of thiobarbituric acid-reactive

substances (TBARS) concentration as

described by Noreen and Ashraf (2009). After

harvest, characteristics such as plant height,

number of branches, seed weight and seed

weight per plant was measured. Grain oil

percentage were measured by micro-

souqksole. Before statistical analysis, the

normality test of data was performed. Data

analyzed using MSTATC software. Mean

comparisons done by Duncan's multiple range

test at the 5 percent level.


Applying different levels of salinity different

growth stages and their interaction was

significant for all traits (Table 1).

Plant height: Salinity applying in the

beginning stages of branching, flowering and

grain filling had no significant effect on plant

height, but salinity levels affected plant height.

Salinity up to 150 mM did not affect on plant

height at establishment stage but increasing

significantly decreased plant height. Salinity

level at 225 mM, decreased plant height to 38

cm which was 44.9 percent lower than the

control treatments mean (Fig. 1). Omami

(2005) studied effect of salinity on some

varieties of grain amaranth (A. tricolor,

Accession '83, A. hypochondriacus and A.

cruentus) and announced that 200 mM salt

decreased A. hypochondriacus height at a rate

of 62% and A. cruentus by 59%. Apply 300

mM NaCl after establish stage led to plant

death. Simple linear regression equation

showed that for every unit increase in salinity

in the growth stage, plant height reduced 14.9


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

units. While the reduction in the branching and

grain filling was 4.6 and 2.6 units,

respectively, which may not provide a

significant effect (Fig. 1).

Branch number: Salinity at beginning of

branching, early flowering and grain filling

stages had not significant effect on number of

branches per Amaranth plant. In this study,

300 mM salt after plant establish had a

significant effect on number of branches (Fig.

2). The beginning and end of branching in

amarath depends on the type of crop and

environmental factors. In most crops

branching ends by beginning of flowering

(Beveridge et al., 2003).

1000 Kernel Weight: Salinity applying at 75,

150 and 225 mM in the establishment stage of

Amaranth reduced 10, 13.3 and 23.3 percent of

the 1000 kernel weight respectively (Fig. 3).

Stress at different growth stage had different

results. In this study, salinity applying 75 mM

in the beginning stages of branching and

flowering decreased 16.6 and 13.3 percent of

1000 kernel weight, respectively. Salinity

application at 150 mM at the beginning of

branching was not affected 1000 kernel weight

and 150 mM salt in the flowering stages,

increased 1000 kernel weight significantly.

This increase was due to a decrease in the

number of grain per plant (Fig. 4) which leads

to more assimilate for grain filling. In the

higher salinity of 150 mM was observed

significantly reduction in 1000 kernel weight.

Simple linear regression equations showed that

for every unit increase in salinity after the

establishment, 1000 kernel weight was

reduced 0.65 units. The reduction in the

branching and flowering stages was 0.22 and

0.08 unit respectively. Changes rate in salinity

levels after grain filling hadn't significant

differences. Thus, the delay in applying

salinity reduced the negative effects of salt

stress on 1000 kernel weight (Fig. 3).

Applying salinity stress in crop growth stage

reduced growth. Similar results have been

observed in other grain crops also (Omami,

2005). Research has shown that reproductive

organs of plants are more sensitive to

environmental stresses than grain filling period

(Gelalcha & Hanchinal, 2013). This

experiment showed a significant reduction in

seed weight also. Application 225 and 300

mM salinity at the branching reduced 20% and

36%, respectively and application 300 mM salt

in flowering stage decreased 1000 kernel

weight as 16.6%.

Seed number per plant: The maximum

number of grain per plant was 5524 in control.

Salinity of 75 mM had not effect on seed per

plant, however, higher salinity levels showed

significantly negative effect on seed per plant.

The decrease in seed per plant at salinity of

225 and 300 mM, was 38.5 and 56%,

respectively. Application of 150, 225 and 300

mM, in the beginning stages of branching

reduced 35.4, 38.5 and 35.5%, respectively,

the number of seed per plant. Application of

225 mM salinity after crop establishment

reduced 81.2% of seed number per plant.

Application of 150 mM salinity at crop

establishment reduced 50.2% seed number per

plant. So in three concentrations of 150, 225

and 300 mM, the maximum reduction in the

number of seed per plant was affected by

salinity imposed in the early stages of crop

growth (Figure 4). Salinity reduced number of

branches per plant and growth and

development such as reducing number of

florets and earliness flowering of plant

affected by salinity (Muuns & Tester, 2008).

Seed weight per plant: Maximum seed

weight was 15 g in control treatment. 75 mM

salinity had not effect on Amaranth seed

production, but on the other salinity levels

depending on the stage that salt stress was

applied, the weight of the produced seed

reduced. In all three levels of salinity, 150, 225

and 300 mM, the maximum reduction in yield

was in the stage of crop establishment. Seed

yield in both the 150 and 225 mM stress after

crop establishment stage was 6 and 2 g per

plant, respectively, which was 60 and 86.6%,

respectively, less than control. Stress at the

onset of branching in salinity levels of 150,

225 and 300 mM, a significant reduction in

seed weight was obtained. In the three

treatments, seed weight was 8.3, 7.3 and 4.7 g,

which 38, 46.6 and 71.3 % respectively, less

than control. With increasing salinity levels

seed yield of amaranth decreased (Fig. 5).

With increasing solute concentrations yield

decreased and even plant dies at high

concentrations. According to study, the low-

salt (75 mM) concentration had not affected

Amaranth seed yield, but higher salinity

concentration showed significant decreasing

yield. Application of 225 and 300 mM salt at

the beginning of flowering decreased 40 and

66.6% of the seed weight. Simple linear


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

regression equations showed that for every

unit increase in salinity after crop

establishment, seed production reduced 47.3

units. The reduction in branching and

flowering stages were 1.9 and 1.7 units,

respectively. Changes observed in

morphological traits and yield components of

produced seed after seed filling stages were

not significant (Fig. 5).

Oil Production: As the stress is increased, oil

percentage decreases. In addition, the stress

application in the early stages of growth had a

greater impact on oil percentage. The highest

reduction in oil percentage was observed with

applying salinity stress in the establishment

stages. Applying salinity stress in the

establishment, branching, early flowering and

grain filling stages respectively led to 80, 62,

51 and 30% decrease in amaranth’s oil

percentage compared to control condition. The

study of linear regression equation showed that

for every unit increase in salinity after the

establishment ,branching, flowering and grain

filling stages, 3.76, 2.89, 2.12 and 1.41 unit of

oil percent were reduced. Thus, amaranth’s oil

production is more sensitive to salinity stress

compared to its other characteristics (Fig. 6).

H2O2, MDA and total phenolics contents: Salinity was increased MDA, the H2O2 and

total phenolics contents in amaranth leaves

(Table 2). The salinity levels of 75 mM had no

significant effect on H2O2 and MDA content in

amaranth leaves. However, enhancment of

salinity to 150, 225 and 300 mM significantly

increased H2O2 content as 35.9, 50.3 and

74.7%, respectively compared to non saline

conditions; these increase for MDA amount

were 62.9, 77.3 and 86.9 % respectively.

Result showed that total phenolics contents in

amaranth leaves significantly increased with

enhancment of salinity from non salinity

condition to 75, 150, 225 and 300 mM NaCl as

15.7, 24.2, 33.7 and 46.8% respectively (Table

2). The high increase content of H2O2 showed

that amarant in high salinity levels was

sensitive; on the other hand the high increase

content of MDA is Amaranth appropriate

response to salinity. MDA is the

decomposition product of polyunsaturated

fatty acids of membranes under stress. The rate

of lipid peroxidation level in terms of MDA

can therefore be used as an indication to

evaluate the tolerance of plants to oxidative

stress as well as sensitivity of plants to salt

stress. It is also known that the formation of

ROS enhances peroxidation at the cellular

level and that the rate of such enhancement

relates to plant species and the severity of

stress (Wang et al., 2009). Variation in MDA

contents were found in rice (Tijen & Ismail,

2005) and cotton (Meloni et al., 2003)

cultivars differing in salt tolerance. In

Amaranth leaves H2O2 remained changed due

to salt stress. While, in contrast, it is generally

known that salt stress enhances the production

of singlet oxygen, superoxide anion, H2O2 and

hydroxyl radical in plants. However,

regulation of these ROS depends on their rates

of generation, their rate of reaction with other

metabolites such as proteins, lipids and nucleic

acids, their rate of degradation and rate of their

neutralizing by enzymatic or non-enzymatic

antioxidants. Generally, the dismutation of two

superoxide anions, either enzymatically or

non-enzymatically, give rise to H2O2. H2O2 is

also produced from the β oxidation of fatty

acids and peroxisomal photorespiration

reactions (Noreen & Ashraf, 2009).

Conclusions

Seed yield reduction and its components

within components of Amaranth growth

indices affected by salinity were similar to

most crops. Based on these results, the grain

amaranth cultivar (cv. Koniz) growth factors

such as crop height, productive branches and

yield components such as number and grain

weight decreased with increasing salinity.

Highest and lowest significant reduction in

seed yield production was 86 % and 1000

kernel weight was 13 %. Salinity up to 75 mM

had not significant effect on most

morphological and physiological attributes.

According to not significant changes of

imposing salinity on different characteristics at

different stages of crop growth, it can be

concluded that grain Amaranth has a good

tolerance to the environmental stresses ranging

up to 75 mM NaCl extrusion. But with the

increasing salinity, significant negative effects

on the crop increased and in 300 mM salt plant

died in end of growth. Earlier salinity

imposing increased salinity effect on plant, but

extremely high salinity occurs at grain filling

stage had no effect on seed production. The

occurrence of moderate salinities (150 and 225

mM) in the later stages of the plant life in the

post-blooming stage did not cause a significant

loss, but, rising tension in early period was not

suitable for Amaranth. Grain Amaranth can


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

produce suitable seed production in areas with

low salinity and the most important limitation

was high salinity of the soil in these areas in

the entire developmental period.

Acknowledgements

We wish to thank the Tabriz Branch, Islamic

Azad University for financial support of this

project.

References

Almodares, A., M.R. Hadi and B. Dosti .2008.

The effect of salt stress on growth parameters

and carbohydrate contents in sweet sorghum.

Research Journal of Environmental Science.

2(4): 298-304.

Beveridge, C.A., J.L. Weller, S.R. Singer, and

J.M.I. Hofer. 2003. Auxillary meristem

development. Budding relationships between

networks controlling flowering, branching, and

photoperiod responsiveness. Plant Physiology.

131: 927-934.

Borneo, R., and A. Aguirre. 2008. Chemical

composition, cooking quality cereals, and

consumer acceptance of pasta made with dried

Amaranth leaves flour. LWT - Food Science

and Technology. 41: 1748–1751.

Dave, D.S., and N.K. Patel. 2011. Salinity

effect on Amaranthus lividus Linn.

(Amaranthaceae) in relation of physiological

and biochemical aspects. Life Sciences

Leaflets 21: 1018-1042.

Gaber, M.A. 2010. Antioxidative defense

under salt stress. Plant Signal Behav. 5(4):

369-374.

Gelalcha, S., and R.R. Hanchinal. 2013.

Correlation and path analysis in yield and

yield components in spring bread wheat

(Triticum aestivum L.) genotypes under

irrigated condition in Southern India. African

Journal of Agricultural Research. 8(24): 3186-

3192.

Jaleel, C.A., B. Sankar, R. Sridharan, and R.

Panneerselvam. 2008. Soil salinity alters

growth, chlorophyll content, and secondary

metabolite accumulation in Catharanthus

roseus. Turkish Journal of Biology. 32: 79-83.

Mahajan, S., G.K. Pandey, and N. Tuteja.

2008. Calcium and salt-stress signaling in

plants: Shedding light on SOS pathway.

Archives of Biochemistry and Biophysics.

471(2): 146–158.

Meloni, D.A., M.A. Oliva, C.A. Martinez, and

J. Cambraria. 2003. Photosynthesis and

activity of superoxide dismutase peroxidase

and glutathione reductase in cotton under salt

stress. Environ. Exp. Bot. 49: 69-76.

Munns, R., and M. Tester. 2008. Mechanisms

of salinity tolerance. Annual Review Plant

Biology. 59: 651–681.

Nenova, V. 2008. Growth and mineral

concentrations of pea plants under different

salinity levels and iron supply. Genetic Apply

Plant Physiol. 34 (3-4): 189-202.

Noreen, Z., and M. Ashraf. 2009. Assessment

of variation in antioxidative defense system in

salt-treated pea (Pisum sativum) cultivars and

its putative use as salinity tolerance markers. J.

Plant Physiol. 166(16): 1764-1774.

Omami, E.N. 2005. Response of amaranth to

salinity stress. Department of Plant Production

and Soil Science. Faculty of Natural and

Agricultural Sciences. University of Pretoria.

Omami, E.N., P.S. Hammes, and P.J.

Robbertse. 2006. Differences in salinity

tolerance for growth and water use efficiency

in some amaranth (Amaranthus spp.)

genotypes. New Zealand Journal of Crop and

Horticultural Science. 34(1): 11-22.

Pospisil, A., M. Pospisil, B. Varga, Z.

Svecnjak. 2006. Grain yield and protein

concentration of two amaranth species

(Amaranthus spp.) as influenced by the

nitrogen fertilization. European Journal of

Agronomy. 25: 250–253.

Tijen, D., and T. Ismail. 2005. Comparative

lipid peroxidation, antioxidant defense systems

and proline content in roots of two rice cultivar

differing in salt tolerance. Env. Exp. Bot.

53(3): 247-257.

Vega, J.M., I. Garbayo, M.J. Domınguez, and

J. Vigara. 2006. Effect of abiotic stress on

photosynthesis and respiration in

Chlamydomonas reinhardtii: induction of

oxidative stress. Enzyme and Microbial

Technology. 40(1): 163–167.

Velikova, V., I. Yordanov, and A. Edreva.

2000. Oxidative stress and some antioxidant

systems in acid rain treated bean plants,

protective role of exogenous polyamines. Plant

Sci. 151: 59–66.

Wang, X., G. Zhao, H. Gu. 2009.

Physiological and antioxidant responses of

three leguminous species to saline

environment during seed germination stage.

African Journal of Biotechnology. 8(21):

5773-5779.

Wang, Y., and X. Li. 2008. Salt stress-induced

cell reprogramming, cell fate switch and

adaptive plasticity during root hair


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

development in Arabidopsis. Plant Signaling

and Behavior. 3(7): 436-438.

Table 1. Analysis of variance of traits in Amaranth

SOV df Plantا

height

Branch

No MDA H2O2 Total phenol

salinity

levels 4 877.79** 4.23** 53.89** 21. 43 * 4.54 *

salinity

applying

time

3 3141.02** 8.84** 6.23 4.41 0. 65

salinity

level×time 12 492.09** 2.29** 0.87 2.34 0.22

error 40 70.35 0.45 18.57 3.84 0.88

CV (%) 13.17 16.23 13.68 13.83 7.04

and ** significant at 5% and 1% levels, respectivly

Table 1. Continue

SOV df 1000 kernel

weight

Seed No

per plant

Seed W

per plant Oil percentage

salinity levels 4 3.063** 15953857.1** 152.77** 163.88**

salinity applying time 3 2.475** 8674358.6** 99.66** 52.79**

salinity level×time 12 0.933** 3010661.5** 26.58** 4.35**

error 40 0.017 357547.5 3.5 0.516

CV (%) 4.76 17.01 18.37 5.43

and ** significant at 5% and 1% levels, respectivly

Table 2. Mean of H2O2, Total phenolics and MDA content as affected by NaCl levels

NaCl

(mmol)

H2O2

(µmol/g fw)

Total phenolics

( mg/g fw)

MDA

(nmol/g fw)

0 9.23 d 4.21 d 2.91 cd

75 10.33 dc 4.87 c 3.37 c

150 12.54 c 5.23 bc 4.74 b

225 13.87 b 5.63 b 5.16 ab

300 16.12 a 6.18 a 5.44 a

Treatments with the same letter(s) don’t have significant difference

d

c

bc

abcabcabcabc

abab

abc

ababab

abab

ab

ab

ab

aa

Stablishment: y = -14.901x + 87.237

R2 = 0.8395

Grain filling: y = -4.599x + 88.931

R2 = 0.8248

Flowering: y = 2.501x + 62.299

R2 = 0.6413

Branching: y = -2.599x + 74.999

R2 = 0.4822

0

10

20

30

40

50

60

70

80

90

Control(0) 75 150 225 300

NaCl (mMol)

Pla

nt

Heig

ht

(cm

)

Stablishment Branching Flowering Grain filling

Fig. 1. Comparison means of plant height affected

by salinity and applying time

aa

a a

b

aa

aa

a

a

a

a aa

aa a a a

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Control(0) 75 150 225 300

NaCl (mMol)

Bra

nc

h N

o.

Stablishment Branching Flowering Grain fi l l ing

Fig. 2. Comparison of number of branches

affected by salinity and apply time


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

g

e

dcd

b

f

d

b

d

b

de

bc

a

d

bbc

b

bcbc

b

Flow ering: y = -0.0833x + 3.2363

R2 = 0.0901

Branching: y = -0.2201x + 3.3405

R2 = 0.4804

Grain f illing: y = -0.0233x + 3.0965

R2 = 0.3325


R2 = 0.702

0

0.5

1

1.5

2

2.5

3

3.5

4

Control(0) 75 150 225 300

NaCl (mMol)

1000 k

ern

el w

eig

ht

(g)

Stablishment Branching Flow ering Grain f illing

Fig. 3. Comparison of 1000 kernel weight under

influence of salinity and application times

g

fg

ef

aba-e

ef

dede

a-d

a-d

ef

decde

ab

ef

a-da-d

b-e

a-e

a


R2 = 0.0543

Flowering: y = -577.2x + 5161.4

R2 = 0.6731

Branching: y = -720.9x + 5718.5

R2 = 0.8909Stablishment: y = -1359.4x + 6686.4

R2 = 0.9131

-1000

0

1000

2000

3000

4000

5000

6000

Control(0) 75 150 225 300

NaCl (mMol)

Grain

per p

lan

t


Fig. 4. Comparison of number of seed per plant

under influence of salinity and application times

f

ef

c-f

abab

def

b-e

bcd

abc

ab

def

b-e

bcd

abab

ab

ab

bcda-d

a


R2 = 0.0723

Flowering: y = -1.7003x + 13.902

R2 = 0.887

Branching: y = -1.9003x + 14.368

R2 = 0.9845


R2 = 0.9042

-2

0

2

4

6

8

10

12

14

16

Control(0) 75 150 225 300

NaCl (mMol)

Gra

in w

eig

ht

(g/p

lant)


Fig. 5. Comparison of grain yield production in

crop affected by salinity and time application

p

n

lm

hij

cde

o

m

ijk

abcab

n

jk

ghiefg

ab

kl

fghdef

bcd

a


R2 = 0.909

Branching: y = -2.8954x + 21.737

R2 = 0.9617 Flowering: y = -2.121x + 19.997

R2 = 0.9468


R2 = 0.9668

0

2

4

6

8

10

12

14

16

18

20

Control=0 75 150 225 300

NaCl (mmol)

Oil

percen

tag

e (

%)


Fig. 6. Comparison of oil percentage under

influence of salinity and application times


UDC 633.15-152.75:631.461(497.11)"2010"


____________________________________________________________________________________________________

YIELD RESPONSE OF FIVE MAIZE HYBRIDS TO INOCULATION WITH

RHIZOBACTERIA

N. Mrkovački 1*, D. Bjelić 1, D. Jošić 2, I. Đalović 1

1Institute of Field and Vegetable Crops, Novi Sad, Serbia

2Institute of Soil Science, Belgrade, Serbia


Abstract

The biofertilizers are found positive contribution to soil fertility, resulting in an increase in crop yield

without causing any environmental, water or soil pollution hazards. Nitrogen fixing and phosphorus

solubilizing bacteria play an important role in nitrogen mobilization and phosphorus solubilization for

the benefit of plant growth. A field experiment to study yield response of maize to inoculation with

rhizobacteria, was conducted during 2013 at experimental field of Institute of Field and Vegetable

Crops in Novi Sad. The maize hybrids (NS 3014, NS 4015, NS 5043, NS 6010 and NS 6030) were

used in the study. The field experiment was laid out in randomized complete block design with four

treatments (control and 3 inoculations) and four replications. Inoculation was done with Pseudomonas

PS2, Bacillus Q7 and their mixture with Azotobacter chroococcum (Q7 + PS2 + AC). Application

method was incorporation immidiately before planting with liquid culture of strains (1 l + 300 l H2O

ha-1). The results showed significant increase in maize yield with inoculation treatments. The best

effect on maize yield was achieved with mixture of strains (19.7%). Significantly higher yield was

obtained for hybrids NS6010 and NS 6030. The highest increase in yield of maize was achieved with

hybrid NS 6030 (32.2%). Statistically significant differences in comparison to the control were

obtained on treatments with Q7 and PS2 + Q7 + AC.

Key words: Azotobacter, Bacillus, Pseudomonas, yield.

Introduction

Maize is one of the most important cereal

crops in the world. In 2010, this crop was

grown in an area of nearly 162 million ha and

occupied second place in overall production

(http://faostat.fao.org). In Serbia, maize is

grown on about 1 200 000 ha and the total

grain production is between 4 and 7 million

tons per year. The grain yield of maize

dependson the genetic potential of a hybrid,

soil characteristics, agrotechnical measures

and climatic factors (Jocković et al., 2010;

Đalović, 2014).

Microbial inoculants are highly ranked among

promising alternatives for reducing global

fertilizer inputs into agroecosystems. Their use

has been steadily growing through the last

decade. some microbial inoculants are able to

improve nutrient availability and plant uptake

capability, thereby reducing nutrient inputs

and increasing the use efficiency of applied

chemical fertilizers. Single or mixed inoculant

formulations containing plant growth

promoting bacteria (PGPB) stimulate plant

growth by diverse mechanisms, which include

biological nitrogen fixation, synthesis of

hormones and a variety of other molecules,

phosphate solubilization and biological control

of pathogens.

Maize (Zea mays L.) is widely used for human

and animal food and is a staple in many


http://faostat.fao.org/

95 N. Mrkovački, D. Bjelić, D. Jošić, I. Đalović

____________________________________________________________________________________________________

JAFES, Vol 70, (2016)

developing world communities where small

increases in productivity without increasing

production costs represent significant gains in

food security. Thus, new technologies

promoting the effectiveness of bioinoculants

based on endophythyc diazotrophic microbes

(such as plant growth promoting bacteria

(PGPB) are of compelling social

environmental reelvance).

Significant increases in growth and yield of

agronomical important crops in response to

inoculation with PGPR have been reported by

Asghar et al. (2002), Bashan et al. (2004) and

Biswas et al. (2000). Azospirillum,

Pseudomonas and Azotobacter strains could

affect seed germination and seedling growth

(Shaukat et al. 2006). Kloepper et al. (1992)

has been shown that wheat yield increased up

to 30% with Azotobacter inoculation and up to

43% with Bacillus inoculation. Strains of

Pseudomonas putida and Pseudomonas

fluorescens could increase root and shoot

elongation in canola (Glick et al. 1997) as well

as wheat and potato (De Freitas and Germida,

1992; Frommel et al., 1993). Thus it has been

shown that Azospirillum and Pseudomonas had

the potential for agricultural exploatation and

could use as natural fertilizers (Bashan et al.,

1989; Cakmakci et al., 2006).

The main objestive of this research was to

determine the effect og PGPR strains on yield

of five maize hybrids.


The trial was conducted at Rimski Sancevi

experimental field of Institute of Field and

Vegetable Crops in Novi Sad. The

experimental objects were five hybrids of

maize (NS 3014, NS 4015, NS 5043, NS 6010

and NS 6030) developed at Institute and three

treatments with microorganisms. Non

inoculated treatment was control. Inoculation

was done with Pseudomonas PS2, Bacillus Q7

and their mixture with Azotobacter

chroococcum (Q7 + PS2 + AC). Application

method was incorporation immediately before

planting with liquid culture of strains (1 l +

300 l H2O ha-1). The experimental design was

a randomized, complete block with four

replications. Data were analyzed by the

analysis of variance; LSD test were used to

separate treatment means when there was a

significant difference at the P<0.05 level. All

analyses were conducted using the statistical

software package STATISTICA 10.0 (StatSoft

Inc. USA) (Mead et al., 1996).


The results showed significant increase in

maize yield with inoculation treatments (Table

1). The best effect of inoculation was achived

with mixture of strains (PS2 + Q7 + AC). The

highest yield was obtained with hybrids NS

6010 and NS 6030 on all examined treatments

in comparison with control. The highest

increase in yield of maize was achieved with

hybrid NS 6030 (32.2%). Statistically

significant differences in comparison to the

control were obtained on treatments with Q7

and PS2 + Q7 + AC.


____________________________________________________________________________________________________

JAFES, Vol 70, (2016)

Table 1. Effect of inoculation with PGPR on maize yield

Treatment Hybrid Yield (t ha-1)

Control

NS 3014 6.23f

NS 4015 6.77ef

NS 5043 6.82ef

NS 6010 7.38cde

NS 6030 6.89def

Treatment 1: Pseudomonas PS2

NS 3014 6.32f

NS 4015 6.83ef

NS 5043 6.95def

NS 6010 7.56bcde

NS 6030 7.64bcde

Treatment 2: Bacillus Q7

NS 3014 6.98def

NS 4015 7.48cde

NS 5043 7.85bcd

NS 6010 8.19abc

NS 6030 8.29abc

Treatment 3: PS2 + Q7 + AC

Pseudomonas + Bacillus + Azotobacter

NS 3014 7.42cde

NS 4015 7.65bcde

NS 5043 8.13abc

NS 6010 8.49ab

NS 6030 9.11a Means with the same letter are not significantly different at the P = 0.05 level of significance

Co–inoculation (Azotobacter, Bacillus,

Pseudomonas) had an advantage compared to

single inoculation, which is similar in our

results, while in case of single strains, better

effects were achieved in Pseudomonas and

Azotobacter treatments (Jarak et al., 2012).

Hajnal-Jafari (2010) investigated the effect of

co–inoculation of NS 640 maize hybrid on the

grain yield and microbiological activity in the

rhizosphere. The results obtained over the

period of three years showed that the average

grain yield amounted to when microbial

inoculants were used, and that microbiological

variants had a significant effect on the total

number of microorganisms, number of

aminoheterotrophs, free nitrogen–fixing

bacteria and phosphorus–mobilizing bacteria.

Mixture of biofertilizers, biostimulants and

biopesticides (A. chroococcum, A. vinelandi,

A. lipoferum, B. megaterium and B. subtilis)

caused an increase in the yield of all three

investigated maize hybrids (Govedarica et al.,

2002). Results of Hamidi et al. (2009)

revealed that co–inoculation with PGPR (A.

chroococcum, A. lipoferum, A. brasilense and

P. fluorescens) had the highest promoting

effect on phenology and grain yield of maize

hybrids. The best results on dry matter

accumulation and yield of maize hybrids were

obtained by the plots which seeds were

inoculated with Azotobacter bacteria compared

with Azosprillium and Azotobacter +

Azosprillium priming (Sharifi et al., 2011).

Findings of Umesha et al. (2014) have clearly

showed that combined application of

Azotobacter chroococcum, Bacillus

megaterium and Pseudomonas fluorescens

along with recommended dose of NPK and

enriched compost has resulted in obtaining

highest plant growth, crop yield and dry matter

production of maize.

References

Asghar, H.N., Zahir, Z.A., Arshad, M., Khaliq,

A. (2002). Releationship between in vitro

production of auxins by rhizobacteria and their

growth promoting activities in Brassica juncea

L. Biol. Fert. Soils No. 35, pp. 231-237.

Bashan, Y., Holguin, G., de-Bashan, L.E.

(2004). Azospirillum-plant relationships:

physiological, molecular, agricultural, and


____________________________________________________________________________________________________

JAFES, Vol 70, (2016)

environmental advances (1997-2003). Can. J.

Microbiol. No. 50, pp. 521-577.

Bashan, Y., Ream, Y., Levanony, H.L., Sade,

A. (1989). Non-specific response in plant

growth yields and root colonization of non-

cereal crop plants to inoculation

with Azospirillum brasilense cd. Can. J. Bot.

No. 67, pp. 1317-1324.

Biswas, J.C., Ladha J.K., Dazzo F.B. (2000).

Rhizobia inoculation improves nutrient uptake

and growth of lowland rice. Soil Sci. Soc. Am.

J. No. 64, pp.1644–1650.

Cakmakci, R., Donmez, F., Aydin, A., Sahin

F. (2006). Growth promotion of plants by

plant growth-promoting rhizobacteria under

greenhouse and two different field soil

conditions. Soil Biol. Biochem. No. 38, pp.

1482-1487.

De Freitas, J.R., Germida, J.J. (1992). Growth

promotion of winter wheat by fluorescent

pseudomonads under growth chamber

conditions. Soil Biol. Biochem. No. 24, pp.

1127-1135.

Đalović, I. (2014). More important

morphological traits and the content of mineral

elements in maize at the different levels of

fertilization. Ph.D. Thesis. Faculty of

Agriculture, University of Novi Sad.

Frommel, M.I., Nowak J., Lazarovits, G.

(1993). Treatment of potato tubers with a

growth promoting Pseudomonas sp.: Plant

growth responses and bacterium distribution in

the rhizosphere. Plant Soil No. 150, pp. 51-60.

Glick, B.R., Changping, L., Sibdas, G.,

Dumbroff, E.B. (1997). Early development of

canola seedlings in the presence of the plant

growth-promoting

rhizobacterium Pseudomonas putida GR12-2.

Soil Biol. Biochem. No. 29, pp.1233-1239.

Govedarica, M., Milosević, N., Jarak, M.,

Đuric, S., Jeličić, Z., Kuzevski, J., Đorđević,

S. 2002. Use of biofertilizers, biostimulators

and biopesticides in agriculture production.

Field Veg. Crop Res. No. 37, pp. 85-95.

Hajnal-Jafari, T. (2010). Effect of inoculation

on the yield and microbial activity in soil

under maize. PhD thesis. Faculty of

Agriculture, University of Novi Sad.

Hamidi, A., Chaokan, R., Asgharzadeh, A.,

Dehghaoshoar, M., Ghalavand A., Malakouti,

M.J. (2009). Effect of plant growth promoting

rhizobacteria (PGPR) on phenology of late

maturity maize (Zea mays L.) hybrids. Iranian

J. Crop Sci. No. 11, pp. 249–270.

Jarak, M., Mrkovački, N., Bjelić, D., Jošić, D.,

Hajnal-Jafari, T., Stamenov, D. (2012). Effects

of plant growth promoting rhizobacteria on

maize in greenhouse and field trial. Afr. J.

Microbiol. Res. No.6, pp. 5683–5690.

Jocković, Đ., Stojaković, M., Ivanović, M.,

Bekavac, G., Popov, R., Đalović, I. (2010).

NS maize hybrids – today and tomorrow. Field

Veg. Crop Res. No. 47, pp. 325–333.

Kloepper, J.W., Beauchamp, C.J. (1992). A

review of issues related to measuring

colonization of plant roots by bacteria. Can. J.

Microbiol. No. 38, pp. 1219-1232.

Mead, R., Curnow, N.R., Hasted, M.A. (1996).

Statistical methods in agriculturae and

experimental biology, Chapman and Hall,

London, pp. 415.

Sharifi, R.S., Khavazi, K., Gholipouri, A.

(2011). Effect of seed priming with plant

growth promoting Rhizobacteria (PGPR) on

dry matter accumulation and yield of

maize (Zea mays L.) hybrids. J. Food Agr.

Environ. No. 9, pp. 393–397.

Shaukat, K., Affrasayab, S., Hasnain, S.

(2006). Growth responses of Triticum

aestivum to plant growth promoting

rhizobacteria used as a biofertilizer. Res. J.

Microbiol. No. 1, pp. 330-338.

Umesha, S., Srikantaiah, M., Prasanna, K.S.,

Sreeramulu, K.R., Divya, M., Lakshmipathi,

R.N. (2014). Comparative effect of organics

and biofertilizers on growth and yield of maize

(Zea mays L.). Curr. Agr. Res. J. No. 2, pp.

55-62.

http://faostat.fao.org

http://www.cabdirect.org/search.html?q=do%3A%22Iranian+Journal+of+Crop+Sciences%22

http://www.cabdirect.org/search.html?q=do%3A%22Iranian+Journal+of+Crop+Sciences%22

http://faostat.fao.org/


UDC 633.11-116.424(497.11)


__________________________________________________________________________________________

YIELD AND YIELD COMPONENTS ON SOME WHEAT VARIETIES GROWN IN

ALEKSINAC REGION

D. Cvetkovic1, D. Boshev2*, Z. Dimov2,

S. Ivanovska2, M. Jankulovska2

1Agricultural Pharmacy “Pchela Prom”, Aleksinac, R. of Serbia

2Faculty of Agricultural Sciences and Food, UKIM, Skopje, R. of Macedonia


Abstract

Yield and yield components of 5 wheat varieties (Kruna, Toplica, Zvezdana, Etida, Angelina) in

Aleksinac region (Serbia) were analysed. The experiment was performed in randomized block design

in 3 replications on the experimental field in area of Aleksinac city. The results showed relatively high

yields in all varieties. The general average yield was 6140 kg ha-1. The highest average yield varied

from 6858 kg ha-1 in cultivar Zvezdana to 5050 kg ha-1 in Toplica. The cultivar Kruna showed lowest

number of productive stems per square meter – 572, and largest number in Zvezdana and Angelina,

with an average of 658 and 641, respectively. Average longest spike was found in variety Angelina

12.4 cm, and shortest in Toplica (9.8 cm). The average number of spikelets per spike for all cultivars

was 19.4. Cultivar Angelina showed biggest number (21.1), and Kruna smallest number (17.9). The

biggest number of grains per spike was obtained in cultivar Etida(54.8), and lowest in Zvezdana

(51.4). During the examination, the highest average value for hectoliter weight is obtained in variety

Zvezdana (78.3 kg hl-1), and lowest in Toplica (75.4 kg hl-1). From the data on yield and yield

components, it can be concluded that all tested varieties can be grown in the region of Aleksinac, with

preference to varieties Zvezdana and Etida.

Key words: wheat, yield, yield components.

Introduction

Wheat is grown on about 600000 ha in Serbia

(http://webrzs.stat.gov.rs/WebSite/repository/d

ocuments/). About 52 % of this area is on the

territory of Vojvodina, and 48 % in the other

regions of Serbia. Average yield at the State

level is around 3.4 t ha-1 (Malesevic et al.,

2011). In terms of assortment, most national

varieties are developedin the Institute of Field

and Vegetable Crops in Novi Sad and Institute

for cereals in Kragujevac, and the rest are

imported varieties.However, although there

are many varieties, in Serbia is noticeable

appearance of greater variation of the area

under wheat, tending to their slight decline last

years

(http://webrzs.stat.gov.rs/WebSite/repository/d

ocuments/). Introduction of new varieties in

production for all different microclimatic areas

is one of the measures that can achieve a stop

to this trend, because, achieving the genetic

potential for yield and quality largely depends

on environment conditions in micro areas

(Hristov et al., 2010). Proper classification of

level of microclimate conditions may be the

key factor, which will used maximum genetic

potential of variety in a separate area, and will

get stable yields and good quality.

Based on these findings, the aim of this study

was to investigate the potential of some new

national wheat varieties in the region of

Aleksinac. The goal was to investigate the

possibilities for breeding through field trials

and to obtain data on yield and quality. The

research is aimed at studying the productive

components for each genotype individually, as

well as the mutual comparison of the

genotypes tested in order to make

recommendations for growing varieties in

similar microclimate conditions.


Field trials were conducted during two years

(2009/10 and 2010/11), on the fields of JSC

"Selekcija" in Aleksinac - Serbia. Five

national soft wheat varieties such: Kruna and

Toplica developed in the Institute of cereals in

Kragujevac, and Zvezdana, Etida and


http://webrzs.stat.gov.rs/WebSite/repository/documents/




99 D. Cvetkovic, D. Boshev, Z. Dimov, S. Ivanovska, M. Jankulovska

____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Angelina from the Institute of Field and

Vegetable Crops in Novi Sad were used as

plant material.

Experiments were setup in a randomized block

system, in three replications of 5 m2, and the

planting is carried out with 550 seeds per m2.

The basic soil preparation was made with the

autumn plowing at a depth of 25 cm.Complex

fertilizer of 300 kg ha-1 of 15N2-15P2O5-

15K2O was applied before seeding and 150 kg

ha-1 of KAN (27 % N2) was used as top-

dressing fertilizer in both years. Inspring at the

end of the tillering stage, plants were treated

against weeds with herbicide Monosan Herba,

at a doseof 2 l ha-1. The plant-based

measurement of the number of productive

stems per m2, were made during the vegetation

season. During the research, also were

measured: length of spike, number of spikelets

per spike, number of grains per spike, grain

yield per hectare and hectoliter weight of

grain. The results of the test were statistically

processed by ANOVA method of analysis of

variance and compared with LSD test.


Climatic and soil conditions

It is extremely important to know the climatic

conditions in a certain area as a essential factor

for successful production of certain wheat

varieties in a region (Vasilevski et al., 1992).

Each region is characterized by specific

conditions, which directly affect the yield and

quality of wheat (Hristov et al., 2011; Yanchev

et al., 2014).

Moderate continental climate dominates in the

area of Aleksinac. The springs are usually cold

and humid, summers are hot and dry, and

winters are often cold, with insufficient

quantities of snow.

According to the data on average monthly air

temperatures in the investigated years (Table

1), it may be noted that the warmest months

are July and August, with average

temperatures of 21.1 or 21.2 °C. The lowest

average monthly temperatures are registered in

January and February, with amount of 0.7 - 0.9

for the first, as well 1.1 °C for the second year.

The average annual temperature in the first

testing year was 10.6 °C and 11.7 °C in the

second year. Annual fluctuations in the

average monthly temperatures, suggest

existence of temperate continental climate in

the region.

Table 1. Average monthly and annual air temperatures (оС)

VIII IX X XI XII I II III IV V VI VII Av.

2009/10 21 16.8 11.2 6.9 1.5 0.7 0.9 4.7 10.4 14.8 18 20.8 10.6

2010/11 21.4 18 12.6 7.5 2.1 1.1 1.1 6.1 12 16 20.4 21.5 11.7

Average 21.2 17.4 11.9 7.2 1.8 0.9 1 5.4 11.2 15.4 19.2 21.1 11.1

Table 2. Monthly and annual amount of precipitation (mm)

VIII IX X XI XII I II III IV V VI VII Sum

2009/10 48 45 51 60 43 18 27 28 38 27 30 53 468

2010/11 36 39 57 54 58 41 52 49 56 61 55 47 605

Table 2 shows the values of precipitation per

month as well annual amount of rainfall.

According to the results of the first year,

highest amount of precipitation was recorded

in November (60 mm), and the lowest in

February and May (27 mm). In the second

year, the largest amount of rainfall was

registered in May (61 mm), and lowest in

August (36 mm). The total rainfall amount in

the second year is 605 mm which is higher

than the precipitation amount in the first year

(468 mm) for 137 mm. Also, it is noticeable

that, during the spring months (III, IV, V, and

VI) in the second year, there is more

precipitation in contrast to the first. Generally,

2010/11 has higher amounts of precipitation,

the schedule is good in both years of the

research, and there is a sufficient amount of

rainfalls in both years.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Table 3. Mechanical compositionofthesoil (%)

Horizon Depth

(cm)

Skeleton

(<2)

Sand

(0,2 – 0,02)

Dust

(0,02 – 0,002)

Cley

(> 0,002)

I 0 – 30 9.5 31.6 35 23.9

Although wheat can be grown on different soil

types, she has positive reaction of rich soil

with good physical properties and pH of 6.8 to

7.2. The best soil types for wheat are humus,

alluvial and diluvia deposits (Filipovski,

1993). The soil where were placed

experimental plots, were alluvial sediments,

with first-class creditworthiness. The layout of

the mechanical structure to a depth of 30 cm is

equal, but below this depth, sharply growing

share of the soil skeleton (Table 3).

Grain yield

Wheat yield is quite variable and depends of

the capacity of the yield elements (Yanchev et

al., 2013). According to the analysis of

Jestorovic (1998), 97.9% of the total impact on

the yield belongs to external factors, while

only 2.1% of the genotype. Confirmation of

strong dependence of this property from

external influences, also attached Jevtic

(1992), which concluded that, the lack of

sufficient water in the period after the

fertilization of grains, results in reduced yield,

absolute and hectoliter mass of grain. Tsenov

et al., (2001) concluded that the yield and

quality of wheat depends on both the variety

and the agro-technique, which should be

correlated with climatic conditions. Hristov et

al,. (2012) examined 8 NS wheat varieties in

different agro-ecological conditions of

Vojvodina, in the period from 2005 to 2011.

They found that varieties Zvezdana and Etida

are characterized by high genetic potential for

yield than standard variety Pobeda, but yield

of these varieties is strongly influenced by

external conditions. On the other hand, the

variety Angelina showed slightly lower yield,

but higher yield stability.

Table 4. Grain yield (kgha-1)

Cultivar Year Average of cultivar

2009/10 2010/11

Kruna 5610 6100 5855

Toplica 4860 5240 5050

Zvezdana 6810 6907 6858

Etida 6650 6740 6695

Angelina 6187 6306 6246

Average of year 6023 6258 6140

Cultivar

LSD0,05 = 206

LSD0,01 = 282

Year

LSD0,05 = 130

LSD0,01 = 178

Interaction cultivar x year

LSD0,05 = 291

LSD0,01 = 399

All varieties exhibited relatively high yields

per hectare, regardless of the year (Table 4).

The general average yield was 6140 kg and the

average highest yield for both years had

variety Zvezdana (6858 kg) and lowest

Toplica (5050 kg). Variety Toplica had the

lowest yield in both years, in the first year it

was 4860 kg, and in the second 5240 kg. On

the other hand, the variety Zvezdana showed

the highest values in both years, which in 2010

stood at 6810 kg and in 2011, 6907 kg. Higher

amount of rain in the second year has

noticeably greater impact on some varieties.

Thus, varieties Zvezdana, Etida and Angelina,

exhibit no statistically significant differences.

Regarding this, it can be concluded that these

varieties are easily adaptable and have greater

tolerance to periods of less rainfall, unlike

varieties Kruna and Toplica. The data shows

strong and significant impact of the rainier

year on high statistical significant level at 99

%.

Analyzing the differences between varieties,

which includes the impact of the year, the

variety Zvezdana showed statistically

significant differences in yield on level of 99

% compared to Angelina, Toplica and Kruna,

while there are not significantly differences

from the variety Etida. Second positioned

variety in terms of yield, the variety Etida, also

shows statistically significant difference in the

yield level of 99 % significance compared to


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Angelina, Toplica and Kruna. The yield of

Angelina showed differences at the level of 99

% significance compared to the yield of

Toplica, at level of 95 % compared to Kruna.

Kruna proved reliable statistical significant

difference at the level of 99 %, compared with

Toplica.

Number of productive stems

The number of productive stems is one of the

indicators of yield, because it is the number of

all stems with formed spike (Bokan and

Malesevic, 2004). In determination of the

optimal crop density, it is necessary to know

the potential of the variety for tillering and

accordingly to plant optimal agrotechnics

(Nedic, 1989). For high potential of wheat

varieties,t he number of productive stems

should be between 600 and 700 per m2, which

is accomplished by sowing 500-550 seeds per

m2 (Mastilovic, 1998).

Table 5. Number of productive stems (spikes per m2)


2009/10 2010/11

Kruna 571 573 572

Toplica 612 600 606

Zvezdana 680 637 658

Etida 598 566 582

Angelina 609 674 641

Average of year 614 610 612

Cultivar

LSD0,05 = 23

LSD0,01 = 31

Year

LSD0,05 = 14

LSD0,01 = 20


LSD0,05 = 32

LSD0,01 = 44

According to thedata, variety Kruna has

smallest amount of productive stems – 572,

and Angelina and Zvezdana higher, with an

average of 658 and 641, respectively. Yearly

average of all varieties showed that there were

not major differences, in both years

considering productive stems per m2 (Table 5).

Statistical analysis of interaction variety x

year,showed thegreatest coefficient of

differences, followed the differences between

the varieties and the impact of the year.

Spike length

The spike length varies depending of the

agrotechnique, rainfall in the region and

amounts of fertilizers, especially during the

formation of the spikes (tillering stage).

Roncevic (1998) studied the morphological

and productive characteristics of several

foreign varieties of wheat and received major

differences between varieties for this property.

Vasilevski (1980), in experiments with

different doses of fertilization, observed

differences in the length of the spikes for

certain varieties of winter wheat, regardless of

the method of fertilization, indicating that this

trait is inherited strictly under the same

growing conditions.

Table 6. Spike length (cm)


2009/10 2010/11

Kruna 10.3 11 10.6

Toplica 10.1 9.5 9.8

Zvezdana 10.5 11.5 11

Etida 11.1 11.2 11.1

Angelina 11.9 12.9 12.4

Average of year 10.8 11.2 11

Cultivar

LSD0,05 = 0.5

LSD0,01 = 0.7

Year

LSD0,05 = 0.3

LSD0,01 = 0.4


LSD0,05 = 0.7

LSD0,01 = 0.9

Average value of this feature was 11 cm

regardless of year and cultivar (Table 6). The

average of the first year was 10.8 cm, and the

second was higher by 0.4 cm, respectively


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

accounted for 11.2 cm. Statistical significance

compared to the year has been observed in all

cultivars, except for Etida, indicating that this

variety has good stability in terms of

cultivation. In individual analysis of the

varieties, the longest average length was

recorded for the variety Angelina (12.4 cm),

and the shortest in Toplica (9.8 cm). Angelina

showed statistically reliable differences at the

level of 99 % compared with other varieties in

both years. In the Etida variety, in the first

year is certainly received statistical deviation

level of 95 % compared with all other

varieties, while in the second year, only at

variety Toplica.

Number of spikelets per spike

The number of spikelets per spike is a direct

indicator of fertility of a particular variety, in

certain growing conditions. This component

depends on both the characteristics of the

variety and conditions of cultivation (Jevtic,

1986). According to Jestorovic (1998), the

number of spikelet in 83.5 % depends on the

influence of external factors, and in 16.5 % of

genotype variability. Vasilevski (1980)

concluded that the impact on the schedule of

precipitation is an important determinant of

the total amount of rainfall for the number of

spikelet per spike.

According to the results of our research, the

values correspond to previous studies (Table

7). The average number of spikelets per spike

for all varieties for both years was 19.4.

Angelina showed the highest (21.1) and Kruna

the lowest (17.9) value. Analyze of the impact

of interaction variety x year there are evident

statistical differences among all varieties

except between Zvezdana and Toplica. Among

the variety Kruna, the number was the lowest

in both years of the survey, while Angelina

and Etida had the highest number in the first

year (20.4) and Etida (21.8) in the second.

Differences due to the impact of the year as

well as the differences between varieties were

highly statistically significant at the level of 99

%.

Table 7. Number of spikelets per spike


2009/10 2010/11

Kruna 17.3 18.4 17.9

Toplica 18.2 19.1 18.6

Zvezdana 18 19.6 18.8

Etida 20.4 20.9 20.6

Angelina 20.4 21.8 21.1

Average of year 18.9 20 19.4

Cultivar

LSD0,05 = 0.4

LSD0,01 = 0.5

Year

LSD0,05 = 0.2

LSD0,01 = 0.3


LSD0,05 = 0.5

LSD0,01 = 0.7

Number of grains per spike

The number of wheat grains in the spike

largely depends on the genetic characteristics

of the variety, but also, extremely important

are climatic conditions during the formation of

spikelet.

Jestorovic (1998) finds that external factors

have affected 66.1 % of this capacity, and 33.9

% was due to the impact of genotype. In other

research, Vasilevski (1980) concluded that the

impact of the year on the average number of

grains is great. Nedic (1989) concluded no

influence of sowing density, to average

number of grains per spike varies in different

years of investigation.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Table 8. Number of grains per spike


2009/10 2010/11

Kruna 50.6 56.1 53.3

Toplica 51.4 58.1 54.7

Zvezdana 48.5 54.4 51.4

Etida 59 50.7 54.8

Angelina 53.6 50 51.8

Average of year 52.6 53.9 53.2

Cultivar

LSD0,05 = 1.3

LSD0,01 = 1.7

Year

LSD0,05 = 0.8

LSD0,01 = 1.1


LSD0,05 = 1.8

LSD0,01 = 2.4

The results in our research (Table 8), shows

that all varieties have well-developed spikes

with big number of grains per spike. The

highest average value for this property from

two years of research was obtained in cultivar

Etida (54.8), and lowest among the Zvezdana

(51.4). Seen by year, the lowest number of

grains in the first year of studies had variety

Zvezdana (48.5) and second year Angelina

(50). The largest number of grains in the first

year was found in variety Etida (59) and

second year in cultivar Toplica (58.1). A

comparison of average values for all varieties

of two years showed that in the second year,

varieties had larger number of grains in spike

(53.9) than in the first year (52.6). Statistically

significant differences in the number of grains

in spike exist between varieties and between

conditions of the year, which coincides with

previous similar studies.

Hectolitre grain weight

Hectolitre grain weight is one of the most

important parameters in assessing of milled

quality of the wheat. It is an indicator of two

thirds of the required qualitative-quantitative

properties of the grain, and parameter for

necessary capacity and equipment of storage

(Miric et al., 2007). In addition, hectoliter

grain weight is an indicator of biological

plasticity and adaptability of the variety in

different climate conditions, especially in high

temperatures and air drought. Mladenov and

Milosevic (2011) concluded that the

environmental conditions greatly affect

hectolitregrain weight. Mastilovic (1998),

determining the quality of wheat in Serbia

from 1995 to 1998, found differences of

hectoliter grain weight in the same variety in

different years.

In our investigations, hectolitre weight of grain

varied depending of the year and variety

(Table 9). Highest value is obtained in variety

Zvezdana (78.3 kg hl-1), and lowest in Toplica

(75.4 kg hl-1). The highest average weight in

the two years of the examination was obtained

in Zvezdana, which in 2010 amounted to 77.3

kg hl-1, and in 2011 to 79.3 kg hl-1. The

average for all varieties in the first year was

76.3 kg hl-1, in the second year 77.4 kg hl-1,

and the general average was 76.8 kg hl-1.

Table 9. Hectolitre grain weight (kg hl-1)


2009/10 2010/11

Kruna 75.5 77.8 76.6

Toplica 76 74.9 75.4

Zvezdana 77.3 79.3 78.3

Etida 76.8 76.5 76.6

Angelina 76 78.4 77.2

Average of year 76.3 77.4 76.8

Cultivar

LSD0,05 = 1.5

LSD0,01 = 2

Year

LSD0,05 = 0.9

LSD0,01 = 1.3


LSD0,05 = 2.1

LSD0,01 = 2.9


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Conclusions

Based on the research results of five wheat

varieties in the region of Aleksinac we can

extract several conclusions.

Climate and soil conditions in the investigated

area are favorable for growing these varieties,

since without irrigation it was obtained

relatively high yields. Grain yield is the

highest among the variety Zvezdana, which

occurs as a result of the large number of grains

productive per unit area and number of grains

per spike. Variety Zvezdana has average yield

of 6858 kg ha-1. The variety Etida, also proved

very high yield, with an average of 6695 kg ha-

1. These results coincide with the results of

previous studies of these two varieties on the

territory of Vojvodina. The lowest average

yield was obtained in the variety Kruna, with

4902 kg ha-1. Number of productive stems is

confirmed as a cultivar trait. Highest number

was in the variety Zvezdana (658), and lowest

in Kruna (572). The longest spike is obtained

in Angelina (12.4 cm), and the shortest in

Toplica (9.8 cm). The highest number of

spikelet has Angelina (21.1) and lowest Kruna

(17.9), but the number of fertilized and shaped

grains showed the highest values among the

variety Etida (54.8), and lowest among

Zvezdana (51.4). Highest value for hectoliter

grain weight was obtained for varieties

Zvezdana (78.3 kg hl-1) and Angelina (77.2 kg

hl-1). As a final conclusion, it was found that,

although all tested varieties can be grown in

the region of Aleksinac, preference may be

given to varieties Zvezdana and Etida.

References

Bokan, N., Malesevic, M. (2004): Influence of

Crop Density on Wheat Yield Structure.

ActaAgriculturaeSerbica, 9(18), 65-79

FilipovskiGj. (1993): Pedology. University

Book. Skopje

Hristov N., Mladenov N., Djuric V., Kondic-

Spika A., Marjanovic- Jeromela A., Simic, D.

(2010): Genotype by environment interactions

in wheat quality breeding programs in

southeast Europe. Euphytica, 174 (3), 315-324

Hristov N., Mladenov N., Kondic-Spika A.,

Jockovic, B. (2012): NS Wheat Cultivars in

Agro-ecological Conditions of Vojvodina.

Institute of Agroeconomic PKB. Book of

Papers. 18 (1-2), 21-28

Hristov N., Mladenov N., Kondic-Spika A.,

Marjanovic-Jeromela A., Jockovic B.,

Jacimovic, G. (2011): Effect of Ecological and

Genetic Factors of Correlation and Stability on

Wheat. Genetika, 43 (1), 141-152

Jevtic S. (1986): Wheat. Scientific Book,

Belgrade

Jevtic, S. (1992): Field Crops Production –

Second Part. Science, Belgrade

Jestorovic, Z. (1998): The Effect of Genotype

and Environment to Phenotypic Variability of

Different Quantitative Characters in Wheat.

International Symposium ''Breeding of small

grains'' Kragujevac, Book of Proceedings,

153-156

Malesevic, M., Jacimovic, G., Jevtic, R., Acin,

V. (2011): The Exploitation of the Genetic

Potential of Wheat in Terms of Abiotic

Stresses. 45thMeeting of Agronomists of

Serbia. Institute of Crops and Vegetables Novi

Sad. Book of Papers, 3-14.

Mastilovic, J. (1998): Reflection of Growing

Conditions on the Quality of Commercial

Wheat in Yugoslavia. International

Symposium ''Breeding ofSmall Grains''

Kragujevac. 357-362

Miric, M., Jovin, P., Filipovic, M. (2007):

Hectoliter Weight of Cereals in Serbian Seed

Literature. Cereals-Bread, 34(1-2), 1-11

Mladenov, V, Milosevic M. (2011): Influence

of Cultivar and Location on Quality of Winter

Wheat Seed. Plant Breeding and Seedlings,

17(1), 83-95

Nedic M. (1989): Assesment of Optimal

Density of Seedlings in Production of Winter

Wheat in Area of Stiga. Scientific Meeting

“Proving Production of Wheat and Other

Small Cereals”.University

“SvetozarMarkovic” – Kragujevac. Book of

Papers, 311-322.

Roncevic, P. (1998): Variability of Important

Quantitative Characteristics in Spring Wheat

Genotypes. International Symposium

''Breeding of small grains'' Kragujevac. Book

of Papers, 179-185

Tsenov, N., Stoeva, I., Gubatov, Т.,Peeva, V.

(2011): Variability and Stability of Yield and

Quality of Grain of Several Bread Wheat

Cultivars. Agricultural Science and

Technology, 3 (2), 81 - 87

Vasilevski G. (1980): Influence of Fertilizers

on Development, Yield and Quality of Wheat

in Ovce Pole Region. Doctoral thesis. Faculty

of Agriculture, Skopje

Vasilevski G., Ivanovski M., Cvetkovic T.

(1992): Influence of Soil-Climatic Conditions

and Laser Treatment of Seed on Wheat Yield.


____________________________________________________________________________________________________

JAFES, Vol 69, (2016)

Yearly Book of Papers, Faculty of Agriculture,

XXXVII, 37-44

Yanchev I., Kolev T., Kirchev H. (2013):

Study on Productivity Formation and Yield

elements of Cereal Crops for Green Mass.

Journal of Mountain Agriculture on the

Balkans, 16 (6), 1441-1449

Yanchev, I., Ivanova D., Ivanov V. (2014):

Effect of the Meteorological Conditions in

Two Ecological Regions on Common Wheat

Development and Productivity. “BENA” -

Balkan Environmental Association. Journal of

Environmental Protection and Ecology, 15 (3),

965-972

http://webrzs.stat.gov.rs/WebSite/repository/d

ocuments/00/00/82/26/09_Poljoprivredа.pdf


“Ss. Cyril and Methodius" University in Skopje Faculty of Agricultural sciences and food-Skopje

P.O. Box 297, MK-1000 Skopje,Republic of Macedonia

[email protected]/jafes/

international scientific journal · morphological traits of amaranth ‘cv. koniz’ as influenced...

Documents