ldb convergenze parallele_colelli_01

Giancarlo Colelli Università di Foggia

COME MI

PIACE LA FRUTTA !/?

COME MI

PIACE LA

FRUTTA?

SENSORIAL ATTRIBUTES

(overall appearance, firmness & texture, aroma &

flavour)

NUTRITIONAL ATTRIBUTES (nutritional value,

functionality, nutraceutical properties)

SAFETY (chemical contamination, microbial aspects,

foreign bodies)

R&D IN POSTRACCOLTA

ESTENSIONE VITA

COMMERCIALE (TRATTAMENTI

FISICI/CHIMICI)

SISTEMI NON DISTRUTTIVI

MODELLI PREDITTIVI (ATTRIBUTI

QUALITATIVI, SHELF LIFE, ETC.)

SICUREZZA ALIMENTARE

SOSTENIBILITÀ DELLE

OPERAZIONI POSTRACCOLTA

(MATERIALI, PROCESSI,

IMPIANTI)

MECCANISMI DI BASE

(GENOMICA, PROTEONOMICA,

METABOLONOMICA, ETC.)

Continuous microwave treatment to control postharvest brown rot in stone fruit (Sisquella et al.)

Antioxidant changes during postharvest processing and storage of leek (Allium ampeloprasum var. porrum) (Bernahert et al.)

Segregation of apricots for storage potential using non-destructive technologies (Feng et al.)

Automatic image analysis and spot classification for detection of fruit fly infestation in hyperspectral images of mangoes (Haff et al.)

Pulsed light effects on surface decontamination, physical qualities and nutritional composition of tomato fruit (Aguilò-Aguayo et al.)

Tomato shelf-life extension at room temperature by hyperbaric pressure treatment (Liplap et al.)

The metabolism of soluble carbohydrates related to chilling injury in peach fruit exposed to cold stress (Liplap et al.)

Effect of atmospheres combining high oxygen and carbon dioxide levels on microbial spoilage and sensory quality of fresh-cut pineapple (Zhang et al.)

A new descriptive method for fruit firmness changes with various softening patterns of kiwifruit (Terasaki et al.)

Aloe vera gel coating maintains quality and safety of ready-to-eat pomegranate arils (Martinez-Romero et al.)

from

R&D

to

BUSINNESS

DALLA RICERCA DI BASE AL SUCCESSO COMMERCIALE: 2 ESEMPI DEGLI ULTIMI ANNI

STRATEGIE:

- CHIMICA (DIFENILAMMINA, ETOSSICHINA)

- ATMOSFERE (ULO, ILOS, DCA)

MOST SERIOUS PROBLEM: FEAR OF

UNDESIRABLE ANAEROBIC EFFECTS, E.G.

OFF-FLAVOURS, SKIN PURPLING, IF THE O2 IS

TOO LOW FOR TOO LONG

= NEED TO KNOW ANAEROBIC

COMPENSATION POINT (ACP)

DPA ED ETOSSICHINA SONO STATI BANDITI (IN

EU E IN DIVERSE PARTI DEL MONDO)

CANDIDATES FOR BIOLOGICAL RESPONSE

TO STORAGE CONDITIONS: (SALTVEIT, 2003)

• RESPIRATORY QUOTIENT

• ANAEROBIC COMPENSATION POINT

• METABOLITES OF ANAEROBIC

RESPIRATION

(ETHANOL, ACETALDEHYDE)

• ETHYLENE PRODUCTION

• EXTERNAL COLOR CHANGES

• NIRS DETERMINED COMPOSITION

• CHLOROPHYLL FLUORESCENCE

Oxygen (kPa)

0

50

100

5 10 15

Rela

tive R

esp

irati

on

Aerobic Respiration

Overall Respiration

Anaerobic Compensation Point (ACP)

Anaerobic Respiration

FT

Re

lative

Re

sp

ira

tio

n (

CO

2) Respiratory Quotient (RQ)

RQB

IDENTIFICATION OF LOL: ACP THE O2 CONCENTRATION AT WHICH THE CO2

EVOLUTION IS MINIMUM

The LOL represents the O2 level where respiration changes:

from predominantely aerobic to fermentative.

IDENTIFICATION OF LOL: CF

CHLOROPHYLL FLUORESCENCE

A CHLOROPHYLL

FLUORESCENCE (CF)

SENSOR* RESPONDS

TO LOW O2 LEVELS

WITH FLUORESCENCE

SPIKE SIGNALS *Robert Prange et al. 2002, (2001 at CA-Conference,

Rotterdam), FIRM sensor in “HarvestWatch“ System

by Satlantic

16.11.01 16.03.02

OXYGEN

FLUORESCENCE

FLUORESCENCE RESPONSE TO LOW O2-LEVEL

FROM ZANELLA, 2013

The HarvestWatch™ system, developed by AAFC and Satlantic Inc,

Halifax, NS), and distributed via Isolcell Italia S.p.A., uses fluorescence

(Fα) to let storage operators know when their fruit are stressed –

Introduced at the ISHS CA Conference, Rotterdam, 2001.

computer

hub

kennel sensor

FROM PRANGE, 2013

Detection of LOL (Fα „spike‟) in a commercial packinghouse

FROM PRANGE, 2013

Number of commercial DCA-CF rooms is increasing

every year (1,134 DCA-CF rooms between 2007-2013)

ETHYLENE EFFECTS IN POSTHARVEST HORTICULTURE

Desirable Undesirable

Promotes faster, more uniform fruit ripening

Promotes softening of fruits

Used for degreening of citrus Hastens senescence of plant tissues

Loosens fruits & nuts for mechanical harvest

Promotes abscission of leaves and flowers

Promotes phenolic metabolism related to lignification and oxidative browning

Causes/promotes some physiological disorders

STRATEGIE PER LA RIDUZIONE

DEGLI EFFETTI DELL‟ETILENE

RIMOZIONE DEI FRUTTI

MATURI

INIBIZIONE DELLA SINTESI

INIBIZIONE DELL‟ATTIVITÀ

DEPURAZIONE CHIMICA E/O

FISICA

1-metilciclopropene (1-MCP)

• Formula molecolare: C4H6

• Peso molecolare: 54

• Stato fisico: aeriforme

• Formulazione: α - ciclodestrina in polvere

(zucchero) solubile in acqua (libera il

principio attivo in forma gassosa)

• Marchio commerciale:

EthylBloc™ per specie ornamentali

SmartFresh™ per prodotti commestibili

I recettori dell’etilene sono

presenti sulla cellula

Le molecole di etilene presenti

nell’atmosfera si legano ai recettori

Ma, non essendo la chiave giusta, non attivano il

recettore

Anche le molecole dell’1-MCP si

legano ai recettori dell’etilene

0

10

20

30

40

50

60

0 2 4 6 8

Settimane a 0 °C

Du

rezza (

kg

) CONTROLLO IN ARIA

1ppm 1-MCP PER 24h IN ARIA

CONTROLLO IN ARIA + 1ppm C2H4

1ppm 1-MCP PER 24h IN ARIA + 1ppm C2H4

0 50 100 150 200

DURATA RELATIVA (%)

1ppm 1-MCP PER

24h IN ARIA + 1ppm

C2H4

CONTROLLO IN

ARIA + 1ppm C2H4

1ppm 1-MCP PER

24h IN ARIA

CONTROLLO IN

ARIA

NEL NOSTRO

PICCOLO LAB

http://www.facebook.com/postharvestunifg

SEVENTH FRAMEWORK PROGRAMME

THEME 2: Food, Agriculture and Fisheries, and Biotechnology

Collaborative Projects KBBE.2011.2.4-01

COMPREHENSIVE APPROACH TO ENHANCE QUALITY & SAFETY OF READY-TO-EAT FRESH PRODUCTS

L‟Obiettivo generale di QUAFETY è migliorare la QUALITÀ e SICUREZZA dei prodotti di IV GAMMA attraverso la messa a punto di:

• nuovi modelli predittivi e probabilistici, e strumenti di supporto alle decisioni;

• metodi rapidi e non distruttivi per la predizione della qualità;

• tecnologie innovative per prevenire, quantificare e gestire lo sviluppo di microrganismo patogeni, minimizzando il rischio per i consumatori e preservando la qualità.

WP1Kit

Diagnostici

WP2Controllo di

Processi

WP3Supporto alle

decisioni

WP4Processi

Innovativi

WP6Valutazione Economica

WP7Sistema di Gestione

di Qualità e

Sicurezza

WP8Disseminazione

WP5Implementazione e Dimostrazione

WP9Gestione e

Coordinamento

Strumenti rapidi ed

affidabili per la

rilevazione di L.

monocytogenes e di

E. coli O157:H7

Sviluppo di modelli previsionali delle

proprietà barriera di film polimerici per

l’imballaggio

Inibizione della

formazione di

biofilm da L.

monocytogenes

Determinazione

della durata della

fase lag di cellule

singole per batteri

patogeni in relazione

alle condizioni

ambientali

Effetto di trattamenti termici sugli

attributi organolettici e nutrizionali di prodotti di IV

gamma

Sviluppo di modelli

fisiologici per la

valutazione dei

benefici

dell’atmosfera

modificata su

ortofrutta di IV

gamma

Previsione della

qualità organolettica

e nutrizionale basata

sulle cinetiche di

degradazione di

attributi qualitativi

esterni

Linea robotizzata per la lavorazione del melone di IV gamma basati su

tecniche di analisi di immagine

Metodi innovativi sostenibili per la decontaminazione

superficiale di meloni

Metodi innovativi di

disinfezione

dell‟acqua

alternativi all‟uso

del cloro

Sistemi a refrigerazione

passiva per assicurare la

catena del freddo dal campo alla

tavola

Identificazione

marker molecolari

per la valutazione

della qualità

Rilevazione e misura

di metaboliti

secondari volatili per

la valutazione non

distruttiva della

qualità

Messa a punto di un

modello ad-hoc per la

stima ex-ante degli

investimenti in

innovazione

tecnologica nel settore

degli alimenti a

contenuto in servizio

Identificazione di

marker molecolari

per l‟identificazione

di contaminanti

microbici

Uso di modelli

previsionali per il

controllo dello

sviluppo di

marciumi e di

sapori anomali su

frutta di IV gamma

Audit nutrizionale e funzionale per la

produzione di ortofrutta di IV

gamma

Melone ideale per

la IV gamma:

modello e

applicazione

Identificazione di

marker per la

qualità nutrizionale

e funzionale

Miglioramento della qualità e della sicurezza dei

prodotti attraverso lo sviluppo di

tecniche di coltivazione fuorisuolo

Sviluppo di sistemi di

imballaggio attivi e

intelligenti

“Prevalence” di L.

monocytogenes e

di E. coli O157:H7 Trattamenti UV per

migliorare la

qualità e a

sicurezza di

prodotti di IV

gamma

IS THERE ANY RELATIONSHIP BETWEEN APPEARANCE ATTRIBUTES AND THE FATE OF

COMPOUNDS RELATED TO ORGANOLEPTIC AND NUTRITIONAL QUALITY?

CAN WE THINK OF A TOOL WHICH WOULD ALLOW TO PREDICT THE FATE OF INTERNAL QUALITY

ATTRIBUTES BY SIMPLY GETTING INFORMATION ON THE DEGRADATION KINETICS

OF EXTERNAL PARAMETERS?

1

2

3

4

5

0 2 4 6 8 10

Giorni a 5 °C

Sco

re

50

60

70

80

90

100

0 2 4 6 8 10

Giorni a 5 °C

An

go

lo d

i T

inta

( ° )

0

10

20

30

40

50

60

0 2 4 6 8 10

Giorni a 5 °C

Du

rezza (

N)

0 2 4 6 8 10

Days at 5 °C

RE

LA

TIV

E V

AR

IAT

ION

Hue angle

Total phenols Firmness

FRUITS WERE CUT & STORED AT 5 °C AND 95% RH FOR 9 DAYS

QUALITY PARAMETERS WERE MONITORED: EXTERNAL (COLOR,

APPEARANCE SCORE) AND INTERNAL (FIRMNESS, TA, ACIDS, TSS, SUGARS,

PHENOLS, ANTIOXIDANT ACTIVITY, AND VITAMIN C)

FOR EACH PARAMETER A DEGRADATION OVER TIME CURVE

WAS OBTAINED, WHICH WAS FITTED IN KINETICS OF ZERO AND FIRST

ORDER

nQkdt

Qd

Red delicious Pink Lady Gala

Zero First Zero First Zero First

External quality parameters

Appearance Score 0.7 0.81* 0.65** 0.67** 0.40* 0.34*

L* 0.06 0.06 0.25 0.25 0.07 0.07

a* 0.59**** 0.59**** 0.72*** 0.72** 0.36 0.36

b* 0.12 0.11 0.36 0.35 0.07 0.08

Hue angle 0.58*** 0.59*** 0.70** 0.71** 0.34 0.34

Chroma 0.1 0.11 0.36 0.35 0.36 0.35

Internal quality parameters

Firmness 0.09 0.09 0.14 0.14 0.86*** 0.90****

Fructose 0.71*** 0.72*** 0.26 0.25 0.26 0.25

Glucose 0.64*** 0.66*** 0.51* 0.49* 0.51* 0.49*

Sucrose 0.61*** 0.64*** 0.46* 0.45* 0.46* 0.45*

Soluble solids 0.03 0.03 0.14 0.14 0.17 0.08

Acidity 0.5 0.59* 0.71*** 0.70*** 0.08 0.09

Malic acid 0.52*** 0.49 0.02 0.02

Vitamin C 0.12 0.03 0.04 0.03 0.65** 0.44*

Phenols 0.55** 0.64** 0.03 0.02 0.06 0.07

Antioxidant activity 0.11 0.13 0.65** 0.58* 0.03 0.02

y = 108.29e-0.0946x

0

30

60

90

120

150

0 2 4 6 8Days

Ph

en

ols

(m

g/1

00

g)

y = 0.233e-0.0727x

0

0.1

0.2

0.3

0 2 4 6 8Days

Ac

idit

y (

%)

y = 0.2199x - 1.5463-2.3

-1.8

-1.3

-0.8

-0.3

0.2

0 2 4 6 8

Days

a*

y = 2.9763e-0.0638x

0

0.5

1

1.5

2

2.5

3

0 2 4 6 8Days

Fru

cto

se

(g

/10

0g

)

y = 1.1899e-0.0735x

0

0.5

1

1.5

2

2.5

3

0 2 4 6 8

Days

Glu

co

se

(g

/10

0g

)

y = 1.1936e-0.0561x

0

0.5

1

1.5

2

0 2 4 6 8Days

Ac

ids

(g

/10

0g

)

y = 4.2179e-0.0708x

1

2

3

4

5

0 2 4 6 8Days

Sc

ore

y = 2.0685e-0.0493x

0

0.5

1

1.5

2

2.5

3

0 2 4 6 8Days

Su

cro

se

(g

/10

0g

)

- 5 10 25 40 55 70

a*

Acidity

Fructose

Acids

'RED DELICIOUS'

Edibility

Marketability Sucrose

Glucose

Firmness

RELATIVE VARIATION (%)

80 60 40 20 0 -20 -40 -60 -80

L*

a*

b*

Acidity

Phenols

Vit C

Fructose

% Variation

marketability

edibility

Amodio et al., 2012

The general objective of predicting internal quality, based on degradation rate of external attributes, will be reached in 3 steps:

OBJECTIVES

The First step is to obtain degradation patterns of quality parameters of fresh-cut products during time.

The second step is aimed to calculate the mathematical relationships between external and internal parameters showing significant kinetics.

The Third step will be aimed to validate the prediction models

Melons and rocket leaves have been used as model

Experimental conditions includes:

isothermal storage in air;

isothermal storage in different controlled atmospheres:

Storage in MA packaging with different gas evolution according

to the temperature.

Non-isothermal condition in air and MAP

OBJECTIVES

Sensorial attributes

Appearance Score

Aroma score

Texture score

Translucency score

Sweetness score

Overall quality score

Physical attributes

Firmness (N)

L* value

a* value

b* value

Chroma

Hue angle

Compositional attributes

Vitamin C (mg/100g)

Phenol content

Antioxidant capacity (mg

TE/100 g w.b.)

Titrable acidity

Fructose (g/100 w.b.)

Glucose (g/100 g w.b.)

Sucrose (g/100 w.b.)

Soluble solids (°Bx)

At cutting and during storage different quality attributes were monitored

MATERIALS

SS df MS F p-level

Sensorial attributes

Appearance score 111.48 5 22.29 141.64 <0.001

Aroma score 21.33 5 4.26 5.31 <0.001

Texture score 1.017 3 0.33 0.90 0.446

Translucency score 33.03 5 6.60 18.7 <0.001

Firmness 2429.66 5 485.93 4.94 <0.001

L* value 155.30 5 31.10 5.18 <0.001

a* value 36.75 5 7.35 1.57 0.183

b* value 208.30 5 41.70 7.11 <0.001

Chroma(c) 196.40 5 39.30 6.22 <0.001

Hue angle (h) 207.4 5 41.5 7.06 <0.001

Compositional attributes

Vitamin C 442.40 5 88.48 4.90 <0.001

Phenol contents 85.69 5 17.14 1.16 0.339

Antioxidant activity 58.59 5 11.72 0.57 0.718

Titrable acidity 22.59 5 4.51 6.12 <0.001

Fructose content 0.66 5 0.13 4.33 <0.001

Glucose content 0.20 5 0.04 1.70 0.146

Sucrose content 3.09 5 0.61 1.88 0.112

Soluble solids (°Bx) 8.49 5 1.70 0.97 0.443

RESULTS

Rating Scale Fresh-cut Melon (Cantaloupe)

Score 5 - Excellent

Fresh appearance,

bright color,

firm texture.

Score 4 - Good

Fresh appearance

with minor

symptoms of

translucency on

tissue edges, firm

texture.

Score 3 - Fair

Slightly pale flesh,

noticeable water soaked

areas,

start of softening.

Limit of marketability

Score 2 - Poor

Evident water

soaked tissues,

slimy surfaces.

Limit of edibility

Score 1 - Very Poor

Mushy appearance,

severe tissue damages,

possible bacterial and/or

fungal spoilage.

Deliverable n. 2.6

Mathematical Models

Quality Changes were modeled by using Weibull model :

C0 is the initial value of each quality attributes

is the scale factor (days)

is the shape factor (dimensionless)

t is the time (days)

Also, the fraction of not-marketable and not-edible samples

expressed as F=N/Ntot were modeled by the following logistic

model: X (dimensionless) is the average appearance score

C, A, and B are fitting parameters (dimensionless)

MATERIALS

Quality attribute Model Correlation

coefficient (r)

SSE RMSE

Appearance score Zero order kinetic 0.972 0.6051 0.3088

First order kinetic 0.946 1.17 0.5408

Weibull 0.974 0.518 0.4280

Aroma score Zero order kinetic 0.933 0.335 0.2896

First order kinetic 0.947 0.2694 0.2594

Weibull 0.956 0.2254 0.2674

Translucency score Zero order kinetic 0.980 0.0812 0.1426

First order kinetic 0.981 0.1366 0.1848

Weibull 0.990 0.0717 0.1546

Firmness Zero order kinetic 0.994 2.804 0.8373

First order kinetic 0.988 5.563 1.1790

Weibull 0.992 3.43 0.9260

Vitamin C Zero order kinetic 0.926 7.374 1.3580

First order kinetic 0.946 5.416 1.1640

Weibull 0.973 2.718 0.9518 Amodio et al., JAE,

accepted

RESULTS

1

1.5

2

2.5

3

3.5

4

4.5

5

0 1 2 3 4 5 6 7 8 9

Ap

pe

ara

nc

e

sc

ore

Time (days)

RESULTS

Temperature 1/ Confidence intervals R

5 0.1175 0.0029 –0.026 2.083 0.99

15 0.1265 0.0030 –0.27 1.386 0.98

20 0.2783 0.471 – 0.5095 1.26 0.99

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10 11 Time (days)

fit

0 ° C

15 ° C

5°C

Ap

peara

nc

e s

co

re

A fraction of 35.8 % of the

samples were no-marketable

A fraction of 4.8% of the

samples were no-edible

A fraction of

20.5% was still

edible

A fraction of

13.5% was still

marketable

RESULTS

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5

F

Appearance score

Experimental data

marketability

Edibility

RESULTS

0

5

10

15

20

25

0 1 2 3 4 5 6 7 8 9

Vit

am

in C

(m

g/1

00

g f

.w.)

Time (days)

30

40

50

60

70

80

90

100

0 2 4 6 8 10

Ci

/ C

0 (

qu

ality

in

dex f

racti

on

,%)

Time (days)

Translucency score

Appearance Score

vitamin c

Aroma score

Firmness

AT THE LIMIT OF MARKETABILITY MELONS PROVIDED 28% OF THE

RECOMMENDED DAILY INTAKE (RDI) FOR VITAMIN C, WHILE FRESH MELON

SAMPLES PROVIDED 44% OF RDI.

Starting from this and other obtained results first conclusion may be drawn:

accurate modeling in different ambient conditions is possible both on external and internal quality attribute

degradation rate dependence from time of storage differs among different attributes

indication of internal quality based on appearence is possible and will allow to give more information to

consumer and producers on the best timing of consumption

Melons and rocket leaves have been used as model

For melon only a preliminary trial in air at 5 °C was conducted

For rocket

Isothermal storage in MA packaging with different gas evolution according

to the temperature;

Validation in non-isothermal condition in MAP

isothermal storage in air at 3 temperatures;

Isothermal storage at 5 °C texting the individual effect of lowering O2 and increasing CO2

EXPERIMENTAL

Storage in MAP with different gas evolution according

to the temperature

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10 11

Time (days)

Fit

0°C

5°C

15°C

CO

2 co

nce

ntr

atio

n (C

(0)/

C(i

))

RESULTS MAP

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10 11

Asco

rbic

Acid

(C

(0)/

C(i

))

Time (days)

fit

0°C

15°C

5C

RESULTS MAP

Storage in CA: effect of CO2 and temperature RESULTS CA

0

10

20

30

40

50

60

0 2 4 6 8 10

Asc

orb

ic a

c (m

g/1

00

g )

Days

5°C

15°C

20 °C

0

10

20

30

40

0 2 4 6 8 10

Asco

rbic

acid

(m

g/1

00

g)

Days

ARIA

5%CO2

10%CO2

20%CO2

Effect of temperature seems higher than the

effect of CO2

RESULTS CA

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7 8 9 10 11

off

od

ors

(C

(0)/

C(i

))

Time (days)

0C

5°C

15°C

1

2

3

4

5

0 2 4 6 8

Off

od

ou

r

Days

20% CO2

10% CO2

5% CO2

Air

CO2 accumulation in MAP at 15 °C may be

the cause of the off-odor during the bags

MAP

FURTHER ACTIVITIES

We are testing the effect of 0.5%, 3 and 6 % O2 which will allow to determine wether temperature, gas

composition or both, are affecting major quality changes in rocket

Isothermal storage in MAP for melons and validation in non isothermal conditions

Further validation would be needed

CONCLUSIONS

Do these fresh-cut fruits taste as

good as they look?

THERE‟S A LONG WAY AHEAD…

…AND WE WANT TO GET THERE!!!

Grazie per l’attenzione! giancarlo.colelli@unifg.it

http://www.facebook.com/postharvestunifg