salinity tolerance of giant swamp taro (cyrtosperma...
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Salinity Tolerance of Giant Swamp Taro (Cyrtosperma merkusii); In vitro
and In vivo
By
Shiwangni RAO
A thesis submitted in fulfilment of the requirements of the Degree of Master of
Science
School of Biological and Chemical Sciences
Faculty of Science, Technology and Environment
The University Of the South Pacific
September, 2011
©Shiwangni Rao 2011
i
Author Declaration
I Shiwangni Rao, declare that this thesis is my own work and that, to the best of my
knowledge, it contains no material substantially overlapping with material submitted
for the award on any other degree at any institution, except where due
acknowledgement is made in the text.
ii
Supervisor Declaration This is to declare that this thesis titled “Salinity Tolerance of Giant Swamp Taro
Cyrtosperma merkusii” submitted in fulfilment for the Degree of Master of Science
in Environmental Science to the University of the South Pacific, is the original
research work of Miss Shiwangni Rao conducted under our supervision and
guidance. It contains no material that is overlapping with material submitted for the
award on any other degree at any institution, except where due acknowledgment is
made in the text.
Principle Chief Supervisor;
Dr. Anjeela Jokhan
Dean Faculty of Science Technology and Environment
University of the South Pacific
P.O. Box 1168
Suva
Principle Co-supervisors:
Dr. Mary Taylor
Genetic Resources Coordinator/Centre of Pacific Crops and Trees (CePaCT)
Secretariat of the Pacific Community
Private Mail Bag
Suva
Signature: Date: ____02/12/11_________
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Dr. Arthur Webb
Division of Science and Technology
Secretariat of the Pacific Community
Private Mail Bag
Suva
Signature:
iv
Acknowledgement
I would like to acknowledge the very important people that have helped me
throughout this research. First and foremost the Australian Government, who
provided the funding for this research through the International Climate Change
Adaptation Initiative (ICCAI).
Dr. Anjeela Jokhan the chief principle supervisor for introducing me to the sponsors
of this research. For being the academic guiding light throughout the research in
terms of building the research and write-up.
Dr. Mary Taylor the co-supervisor, for accepting me as a candidate for this research
and allowing me to conduct my research at the Centre for Pacific Crops and Tress
(CePaCT), Narere. For giving her full support despite her busy schedules and
encouraging my exposure in the field of scientific research. Also for introducing me
to the resource personnel’s and for her continuous academic and technical support.
Dr. Arthur Webb co-supervisor, for his scientific and technical input and advice
during the research, especial for the ground water salinity survey in Tuvalu. The
staff of CePaCT, for teaching me tissue culture and for their moral and technical
support during the experimental phase of the research.
University of the South Pacific Research committee for considering this research as
significant and the developments that can be achieved through it and giving their
approval. The technical staff in the chemistry and biology departments namely
Rosely Sharm, Shelvin Singh, Dinesh Sharma and Roselyn Lata.
The Tuvalu Agriculture Minister Mr. Itai Lausaveve for guiding my stay in Tuvalu
and for his technical support. The Kaupule members and agriculture officers of
Nanumaga, Nanumea, Niutao, Nui and Nukulaelae for providing me with
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information and technical support. The very enlightening farmers of the six surveyed
islands of Tuvalu for sharing their knowledge on the giant swamp taro.
The Federated States of Micronesia, Pohnpei State Department Chief Agriculture
officer Mr. Adelino Lorens, the office staff and the agriculture field technicians at
the pilot farm. For all their technical support in the two day workshop in Pohnpei,
helping in translation, collection of information in the farm. The farmers that
participated in the workshop for sharing their bulk of knowledge and contributing in
the development of the Giant swamp taro Cyrtosperma merkusii Descriptor List.
I would also like to acknowledge my husband Mr. James Chand, for his continuously
encouragement and pushing me to go the extra mile in my research. For being
understanding, for his prayers and advice during the research. My Parents Mr
Mahendra Prakash, Mrs. Shanti Mani and my sisters for their moral support and
prayers.
Finally, I would like to thank the many people that have not been listed above but
have in their very own little way contributed to the smooth running and the
successfully completion of this research project
Thank you all.
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Abstract Climate change related sea level rise together with adjustments to wind and wave
patterns may cause an increase in the incidence of salt water intrusion into fresh
ground water lenses, particularly in atoll islands. This saline intrusion may end up in
Giant swamp taro (Cyrtosperma merkusii) cultivation pits, a crop which is a major
food on these atoll islands and also a great part of their cultural identity. Hence, an
increase in the salinity levels of the fresh ground water not only threatens the food
security of these atoll island communities, but also their identity. In past literature,
Giant swamp taro has been referred to as slightly salt tolerant. It has been seen to
survive at a salinity level of around 2-3ppt (Dunn, 1976; Manner, 2006: Webb,
2007). However, these salinity levels are only claims and have not been tested in
controlled trials. Therefore, there is an urgent need to investigate the salt tolerance
potential of Giant swamp taro and utilize it as a buffer against increases in ground
water salinity. Furthermore, the documentation along with sustainable conservation
of giant swamp taro is also essential to prevent the loss of traditional knowledge and
diversity of this important crop. Given that climate change is expected to increase the
incidence of salt intrusion into giant swamp taro pits, the fundamental endeavours of
this project were threefold (a) to investigate the incidence of salt water intrusion in
Tuvalu (b) to develop the knowledge base of giant swamp taro through a descriptor
list (c) to develop a rapid in vitro screening methodology for salt tolerance screening
which could be used to assess the salinity tolerance of two groups of swamp taro
cultivars, Ikaraoi and Katutu from Kiribati. A preliminary in vivo method for
screening for salt tolerance was also developed. The ground water salinity survey in
Tuvalu was carried out over a period of five weeks and six islands were visited.
Measurements were taken using a salinity meter. The survey showed ground water
salinity levels between 2006 and 2010 increased on Funafuti but not on the other
islands.
An in vitro method was developed for rapid screening. Using this methodology, the
two cultivar groups from Kiribati were shown to survive salinity concentrations of
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0% (0ppt), 0.5% (5ppt), 1.0% (10ppt), 1.5% (15 ppt) and 2% (20ppt) salt. However,
the in vivo plants were only able to tolerate up to 0.5% (5pp) salt concentrations,
possibly due to stress imposed by other environmental factors. However, further
research is needed for both the ground water salinity survey and the salt tolerance
screening. Further investigations would give both a clearer idea of the incidence of
increase in ground water salinity levels and also the variation that might exist in
salinity tolerance with different cultivars. A more clear understanding of the extent to
which genetic diversity can affect salt tolerance would assist the selection of hardier
cultivars. There is much significant scientific value to be gained from this project, as
limited studies have been carried out generally on giant swamp taro and determining
the level of salinity tolerance is essential so that farmers and communities know
which cultivars they can use as they try to manage climate change.
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Contents Author Declaration ..................................................................................................... i
Supervisor Declaration .............................................................................................. ii
Acknowledgement ..................................................................................................... iv
Abstract .................................................................................................................... VI
1.0 INTRODUCTION ................................................................................................ 1
2.0 LITERATURE REVIEW .................................................................................... 5
2.1 ATOLL GROUND WATER LENS ................................................................... 5
2.1.1 Threats to fresh ground water lens ............................................................... 7
2.2 SALINITY TOLERANCE IN PLANTS ........................................................... 9
2.2.1 Effects of increased soil salinity ................................................................ 11
2.2.2 Plant Response ........................................................................................... 13
2.2.3 Approaches to salt tolerance ...................................................................... 17
2.2.4 Salinity Testing .......................................................................................... 21
2.3 GIANT SWAMP TARO (Cyrtosperma merkusii) ........................................... 24
2.3.1 Origin ......................................................................................................... 27
2.3.2 Current Distribution ................................................................................... 29
2.3.3 Physiology ................................................................................................. 30
2.3.4 Morphology ............................................................................................... 38
2.3.5 Cultivar Descriptor List ............................................................................. 41
2.3.7 Utilization .................................................................................................. 48
2.3.8 Nutrition ..................................................................................................... 50
2.3.9 Conclusion ................................................................................................. 52
3.0 TUVALU GROUND WATER FIELD STUDY .............................................. 54
3.1 INTRODUCTION ............................................................................................ 54
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3.2 PRE SURVEY .................................................................................................. 58
3.3 SURVEY .......................................................................................................... 61
3.4 RESULTS & DISCUSSION ............................................................................ 62
3.4.1 Nanumea .................................................................................................... 62
3.4.2 Nanumaga .................................................................................................. 68
3.4.3 Niutao......................................................................................................... 73
3.4.4 Nui ............................................................................................................. 77
3.4.5 Funafuti ...................................................................................................... 82
3.4.6 Nukulaelae ................................................................................................. 88
3.4.7 Rainfall- Ground Water Recharge ............................................................. 93
3.4.8 Tuvalu Ground Water Salinity ................................................................... 94
.3.5 CONCLUSION ............................................................................................... 98
4.0 DEVELOPMENT OF A RAPID IN VITRO SCREENING METHOD ...... 101
4.1 INTRODUCTION .......................................................................................... 101
4.2 METHOD ....................................................................................................... 101
4.2.1 Multiplication........................................................................................... 102
4.2.2 In Vitro ..................................................................................................... 103
4.2.3 In Vivo ...................................................................................................... 107
4.2.4 Evaluation Parameters ............................................................................. 109
4.2.5 Data Analysis ........................................................................................... 110
4.3 RESULTS ....................................................................................................... 111
4.3.1 In Vitro ..................................................................................................... 111
4.3.2 In Vivo ...................................................................................................... 119
5.0 DISCUSSION ................................................................................................ 125
6.0 CONCULSION .............................................................................................. 128
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Bibliography ........................................................................................................... 130
ANNEX ................................................................................................................... 140
XI
List of Figures
1.1 Atoll islands in the Pacific
1.2 Giant swamp Taro Cyrtosperma merkusii plantation
1.3 Man hidden by Giant swamp taro leaf that is more than 1m in length and width
2.1 Ground water lens as defined by the Ghybe-Herzberg Principle
2.2 Giant Swamp taro Cyrtosperma merkusii
2.3 Giant Swamp taro corm.
2.4 Giant Swamp taro farm in FSM.
2.5. Phylogenic classification of Giant Swamp taro. 2.6. Map of Malesia, including the possible origins of Giant swamp Taro
Cyrtosperma merkusii.
2.7. Map of the cultural spheres and the current distribution of giant swamp taro
expect for New Zealand
2.8. Sunken cultivation in Tuvalu, Nanumea.
2.9 ’Opened’/’ Bottomless’ Padanus Pandanus tectorious leaf woven baskets in
Kiribati
2.10 Coconut Cocus nucifera leaf woven bottomless basket in Funafuti, Tuvalu.
2.11 Giant swamp taro cultivation in Fiji.
2.12 Concrete cement pit Taro cultivation on Tuvalu in Funafuti
2.13 Giant swamp taro harvested corms
2.14 Giant swamp taro corms
2.15 Labelled giant swamp taro flower.
2.16 young spadix and flower.
2.17 Seeded berries on spadix.
2.18 Mature spadix.
2.19 young Pwh weitata flower.
2.20 Mature Pwh weitata flower.
2.21 leaves of giant swamp taro.
2.22 corm of giant swamp taro.
3.1. Giant Swamp Taro (Cyrtosperma merkusii) or Pulaka
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3.2. Pulaka pit on Nui Island, Tuvalu.
3.3. Causeway constructed in the Tepela Pit area, which had greatly divested the
crops due to highly saline water.
3.4. Abandoned Giant swamp taro pit on Nanumea.
3.5. A fully productive pit on Nanumea, depicting the Pulaka productivity level that
can be attained on the island
3.6. The Tepela area where pulaka is being once again cultivated in hope of reviving
the plantation.
3.7. Very healthy pulaka plants that grow in Funafuti.
3.8 Pulaka Kula, one of the cultivars of Giant swamp Taro found on Funafuti
claimed to be highly salt tolerant
4.1 In vitro Experiment treatment combination structure
4.2 Overall morphological response to salt applications, plants from the left; 0%,
0.5%, 1.0% and 1.5% salt.
List of Tables
2.1 Number of studies done for genetic modifications per species for salt tolerance
from 1998-2003 (Flowers, 2003)
2.2 Number of tests done for a particular gene to improve salinity tolerance in plants
and the number of studies carried out in each one since 1993-2003 (Flowers,
2003).
2.3 Kiribati description of giant swamp taro growth stages (Manner, 2009).
2.4 List of pests, diseases and their impacts on giant swamp taro (Bradburry, 1988;
Iese.V, 2005; Manner, 2009).
2.5 Revised descriptor list
2.6 Local recipes of giant swamp taro
2.7 Giant swamp taro nutritional value (SPC, 2006)
2.8 Giant swamp taro cultivar nutritional value (Englberger, 2005)
3.1 Nanumea ground water salinity
3.2 Ground water salinity on Nanumaga
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3.3 Pulaka pit salinity on Niutao
3.4 Pulaka pit salinity on Nui
3.5 Pulaka pit salinity on Funafuti
3.6 Pulaka pita salinity on Nukulaelae
3.7 Comparison of average rainfall for 2006 and 2010
3.8 Comparison of 2006 and 2010 ground water salinity levels
4.1 Salt solution mixtures
4.2 Salinity increment
4.3 In vitro experimental design
4.4 In vivo Experimental Design
4.5 Mean of cultivar group measured parameters when subjected to the five salinity
levels
4.6 Mean of plant response measured parameters when subjected to the five salinity
levels
4.7 Plant Response to ASW and NaCl
4.8 Contamination Rate according to application method
4.9 Pre and post experiment salinity levels
4.10Cultivar group response to the salinity levels
4.11 Percentage survival rate of the cultivar groups
4.12Plant response to the various salinity levels
4.13Percentage survival rate of the various salinity levels
List of Graphs
3.1. Pulaka pit salinity on Nanumea 2010
3.2. Ground water salinity on Nanumea
3.3. Pulaka pit salinity on Nanumaga 2010
3.4. Ground water salinity on Nanumaga
3.5. Pulaka pit salinity on Niutao 2010
3.6. Ground water salinity on Niutao
3.7. Pulaka pit salinity on Nui 2010
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3. 8. Ground water salinity on Nui
3.9. Pulaka pit salinity on Funafuti 2010
3.10. Ground water salinity on Funafuti
3.11. Pulaka pit salinity on Nukulaelae 2010
3.12 Ground water salinity on Nukulaelae
3.13. 2010 Ground water salinity levels in Tuvalu
3.14. Comparison of the 2006 and 2010 ground water salinity levels
4. 1 Regression analysis graph of Suckers
4.2 Regression analysis graph of corm
4.3 Regression analysis graph of number of dying leaves
List of Maps
3.1 Nanumea.
3.2 GPS located Pulaka pits on Nanumea
3.3 Nanumaga.
3.4 GPS located Pulaka pits on Nanumaga
3.5 Niutao.
3.6 GPS located Pulaka pits on Nanumaga
3.7 Nui
3.8 GPS located Pulaka pits on Nui.
3.9 Fongafale atoll.
3.10 GPS located Pulaka pits on Funafuti, Fongafale
3.11 Nukulaelae atoll.
3.12 GPS located Pulaka pits on Motutala Islet, Nukulaelae.
3.13 GPS located Pulaka pits on Nukulaelae main islet.
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1.0 INTRODUCTION A bit less than half a century (1961-2003) ago the rate of sea level rise was at 1.8+/-
0.5 mm per year (Bindoff, 2007). In the 21st century it is has been predicted by the
six scenarios presented in the 4th Assessment Report of the Intergovernmental Panel
on Climate Change (IPCC, 2007), to increase to 5 mm per year. At this rate of
increase low lying atolls such as in Kiribati, Tuvalu and the Federated States of
Micronesia (FSM) (Figure 1.1) are faced with the extreme effects of climate change,
which greatly threaten their food security and livelihoods.
Atolls are very fragile, in the sense that they are relatively small in size and have
limited geography and topography. They are also very vulnerable to extreme changes
in climate and natural disasters. Along with this, they have a low adaptive capacity to
environmental changes (Bindoff, 2007). Sea level rise and possible changes in
rainfall threaten these fragile ecosystems by the possible increased effects of salt
water intrusion. Salt water intrusion into the fresh ground water lens of the atolls
increases the ground water salinity, which can be lethal to atoll vegetation. Atoll
islands such as Tuvalu have seen a decline in crop production and salt water
intrusion is considered to be responsible. Webb (2007), in an attempt to investigate
the incidence of salt water intrusion in Tuvalu concluded that further, monitoring and
documentation is needed to fully understand the scenario of salt water intrusion.
The more obvious contributors to increases in ground water salinity on atolls are low
rainfall and sea water inundation, which is caused by storm surges, sea swells and
king tides. Sea level rise has increased the probability of occurrence of these
inundations, as it has given added height to the already high waves generated during
these occurrences (Liz, 2007; Aung and Prasad, 2009; White and Falkland, 2010).
This sea water penetrates through to the ground water lens and increases the ground
water salinity level contributing to the threat to food security (Woodroffe, 1989,
2008; White and Falkland, 2010).
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Figure 1.1 Atoll islands in the Pacific (from http:// www.infoplease. com)
To ensure food security and to buffer the impacts of climate change on these fragile
atolls there is a need for food crops that can withstand the challenging conditions
imposed by climate change. Among these needs are food crops that are tolerant to
increasing ground water salinity. Salinity tolerance is of key importance to the atolls
with any of their crops, hence the need for a rapid screening process for salinity
tolerance. Giant swamp taro (Cyrtosperma merkusii) (Figure 1.2 and 1.3) is one such
food crop where information regarding its salinity tolerance would be very useful,
but at present little research of any kind is carried out on this crop.
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Figure1.2 Giant swamp taro Cyrtosperma merkusii plantation
Figure1.3 Man hidden by Giant swamp taro leaf
that is more than 1m in length and width.
By Shiwangni Rao
By Shiwangni Rao
4
In past studies conducted in the Micronesian region and Tuvalu, giant swamp taro
has been consistently highlighted as a crop with potential salt tolerance
characteristics (Dunn, 1976; Lambert, 1982; Vickers, 1982; Brandburry and
Holloway, 1988; Onwueme, 1999; Kazutaka and Michia. 2003; Covich, 2006;
Deenik and Yost, 2006.; Iese, 2005). However, some atoll communities claim that
increasing soil salinity due to salt water intrusion is affecting their giant swamp taro
production (Lausaveve 2010, pers. comm.).
In some cases this has led to farmers abandoning their cultivation pits on the atolls of
Tuvalu. Since there has been no specific investigation on the crop in this regard, the
controversy still exists over the giant swamp taro’s actual salinity tolerance capacity.
Giant swamp taro is not only a local staple but has also been woven into the
traditions and cultures of Pacific atoll communities (Thaman, 2002; Iese, 2005;
Manner, 2009). This plant with a large diversity of cultivars is adapted to the
challenging natural environment of atoll islands unlike many other Pacific staple
crops. Therefore it is an ideal crop for looking for salinity tolerance and for building
on what tolerance that might exist.
This research aims to investigate the incidence of salt water intrusion by looking at
the ground water salinity in the ‘Pulaka Pits’ (Giant swamp taro pits in Tuvaluan) on
the atoll islands of Tuvalu. It further aims to test the possible salt tolerance level in
giant swamp taro (Cyrtosperma merkusii) by subjecting two Kiribati cultivar groups
the larger ‘Ikaraoi’ and the smaller ‘Katutu’ to various salinity levels and by doing
this an in vitro screening method will be developed. An in vivo screening method
will also be investigated to support the results from the in vitro methodology. It also
aims to development the initial cultivar character descriptor list done by Iese (2005).
Achieving all of the above will greatly add to the knowledge base on giant swamp
taro and provide a foundation on which to base further research regarding the very
important issues of salinity tolerance.
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2.0 LITERATURE REVIEW
2.1 ATOLL GROUND WATER LENS
Coral atolls such as the Federated States of Micronesia (FSM), Marshall Islands,
Tuvalu and Kiribati are built on the relics of volcanic craters consisting of two
layers. A Pleistocene karst of limestone deposit forms the first layer; this is covered
by a second layer from the Holocene period. The upper Holocene layer is composed
of unconsolidated calcareous matter such as sediments, coral sand, and coral
fragments (Metai, 2002; Metutera, 2002; Webb, 2007; White and Falkland, 2010).
Ground water lens which is the life source for the flora and fauna on these atolls
typically forms as a result of rainfall on these land masses, but it is difficult to define
the process in a simple formula. This is due to the many factors which affect the
ground water lens such as rainfall, composition of atoll soil ranging from Holocene
to present day, atoll underground structures, tidal pressure and vegetation
(Woodraffe, 1989; Mimura, 1999; Deenik and Yost, 2006; Rozell, 2007).
The classical model of ground water on atolls suggests ground water forms a lens
shape, with a transition boundary from sea water to fresh ground water. This
projection has been defined by the Ghyben-Herzberg principle (Woodraffe, 1989;
Mimura, 1999; Rozell, 2007) (Figure 2.1).
In light of further research and better understanding of the ground water lens White
and Falkland (2010), have proposed a steady state approximation. This takes into
account the majority of contributing factors, however this model has some
limitations as not all the atoll islands are the same. Another limitation to the classic
model provided by White and Falkland (2010) is that ground water probably does
not form an exact lens shape; rather it varies in shape according to the atoll
properties. In this steady state approximation, a ground water lens will not have a
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sharp boundary. It is actually a transition zone where salinity increases with depth
and distance from the centre of the land mass.
Ghyben-Herzberg principle- Ground water lens
Figure 2.1: Ground water lens as defined by the Ghyben-Herzberg principle
(Woodraffe, 1989).
According to this approximation and under conditions of similar rainfall and island
condition, higher and wider islands should have a larger ground water lens compared
to smaller and narrower islands. According to White and Falkland (2010), raised
limestone atolls will have more net ground water recharge than low coral atolls for
the same amount of rainfall since on low atolls large root trees such as coconut
(Cocus nucifera) transpire directly from the ground water lens (Dunn, 1976).
As stated earlier atolls are generally made up of karst limestone, coral fragments and
sediment deposits, however atoll deposits may differ in texture. Tuvalu has a coarse
texture, hence a more permeable atoll structure compared to the Maldives and
Kiribati. This coarse material is due to the deposition made by many storms that
resulted in boulders and rubble to be embedded on the atoll’s Holocene layer such
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occurred during cyclone Bebe in 1972 (White and Falkland, 1999). Since an increase
in permeability is expected to reduce the height of the ground water lens, Tuvalu’s
ground water lens is much thinner than the Maldives and Kiribati (White and
Falkland, 1999).
In addition, a ground water lens is also affected by daily tidal fluctuations, as the
movement of tides encourages mixing of the fresh ground water and sea water
(Metai, 2002; Deenik and Yost, 2006; White and Falkland, 2010). Tidal efficiency is
defined as the ratio of tidal amplitude of the ground water to that of the sea.
According to the common theory tidal influence decreases with distance from the
coast and the ground water lag of tidal force response should increase. However, this
does not hold true for low lying atoll islands, where wells and bores show a decrease
in tidal influence from shore. This is due to the permeable limestone karst, where
rapid transmission of tidal pressure takes place resulting in a vertical propagation in
the middle of the atoll and vertical along with horizontal tidal propagation towards to
the coast (Rozell, 2007; White and Falkland, 2010). All these factors combined make
the fresh ground water lens of atoll islands vulnerable, this in turn affects the flora
and fauna on the atolls.
2.1.1 Threats to fresh ground water lens The rate of sea level rise is increasing, with a projected 5mm per year in the 21st
century (Bindoff, 2007). This poses many threats to fragile low lying atoll ground
water lens and an atoll island’s food security.
According to some researchers, natural disasters as a result of climate change will
increase in frequency and/or intensity in the future (Bindoff, 2007; Rodgers, 2009;).
This means that frequency and probability of sea water inundation due to natural
disasters may increase; coupled with the high permeability of atolls this could result
in increased ground water salinity (White and Falkland, 2010). Such natural disasters
8
include storm surges, storm sea swelling, tsunamis generated from marine land slide,
earthquakes and volcanic eruptions.
Apart from inundation, some of these natural disasters such as earthquakes, marine
landslides and volcanic eruption may directly affect the ground water lens by causing
excessive disturbance and disrupting the delicate balance of the ground water lens.
However, at the moment there is no significant research on these scenarios. Drought
is another natural disaster that affects the ground water lens but in a different
manner. In the event of extended periods of drought, there is a decrease in ground
water recharge, hence a reduction in the ground water lens and a corresponding
increase in salinity. This is due to the main body of the ground water lens decreasing
in size and a widening of the transition zone where freshwater and sea water mixing
takes place (White and Falkland, 1999; Woodraffe, 1989).
One popular theory related to climate change and sea level rise is that sea level rise
increases coastal/land erosion (Eid and Huisbergen, 1992; Gerald, et al, 2007; Aung,
et al 2009; Lal, 2009; Talia, 2009). If erosion does occur then island land mass is
reduced pushing the ground water lens transition boundary inwards. This results in a
decrease in the ground water lens and an increase in the ground water salinity levels.
However, recent studies of erosion conducted by Webb and Kench (2010) show
otherwise. The research employed remote sensing images and historical aerial
photography of 27 atoll islands from Kiribati, Federated States of Micronesia and
Tuvalu. According to this study in spite of a rate of 2 mm per year sea level rise over
the last 19-61 years, 43% of the islands surveyed showed no change in size, 43%
increased in size and only 14% of the total islands assessed decreased in size. In
many cases it was observed that where an island was eroded on one side, the
opposite side accumulated sediments, equalizing the sediment movement giving a
net zero change in size. In line with this finding White and Falkland (2010) state that
it is more likely for coastal erosion to occur as a result of extreme events that
9
generate strong waves rather than just a gradual rise in sea level. They also state that
while sea level rise and coastal erosion could result in a decrease in size of the
ground water lens, it is more likely to be affected by a decrease in recharge (rainfall).
In a critique of the study carried out by Webb and Kench (2010), Schaeffer and Hare
(2010) state that Webb and Kench (2010) focused on a time period where the rate of
sea level raise was only 2mm/yr. They argue that with the projected increase in the
rate of sea level rise and an increase in ocean acidity, the conditions of island
stability may not persist. An increase in ocean acidity reduces calcification and
growth of coral reefs; hence reducing the protection these coral reefs provide atoll
islands in the face of increasing sea levels. Furthermore, the study by Webb and
Kench (2010) was only conducted in relation to island horizontal mass (width) and
has not taken the island elevation into account, which plays an important role in
determining island ground water lens.
While there are a number of threats faced by ground water lenses, the human factor
should not be ignored. According to Webb (2007) and White and Falkland (2010),
humans have contributed significantly to impacting the quality of ground water lens
on Pacific atolls. These contributions include pollution, over-extraction, population
and development pressures. However as stated earlier the incidence of salt water
intrusion and resultant increase in ground water salinity is a complex issue and needs
further investigation. The same goes for the claims by farmers of the atoll
communities that salt water intrusion is to blamed for the decrease in crop
production.
2.2 SALINITY TOLERANCE IN PLANTS
Soil salinity in terms of dryland and wetland salinity, is one of the primary abiotic
factors that hinders crop production not only in the Pacific but worldwide. It has
been present since the pre agricultural times but more recently has been aggravated
due to improper agricultural practices, deforestation, unsustainable living and
10
enhanced climate change (Zhao.M, et al., 2001; Yamaguchi and Blumwald, 2005).
More than 6% of the earth’s entire land mass, which is 800 million ha of land, is
currently affected by increased soil salinity (Munns and Tester, 2008). With the
global population projected to increase by 2.8 billion over the next fifty years
(United Nations 2004:4), increased soil salinity poses a threat to the food security
systems of the world. Investing in development of salt tolerant food crops may hold
some answers to these threats (Zhu, 2001; Arzani, 2008). This can be achieved by
screening the diverse gene pool of crop plants, with their cultivars that vary in their
response to environmental stress such as salinity (Arzani, 2008).
Salts are generally present in soil but at levels where they would be beneficial and
not detrimental to plants. However, where soil salinity exceeds an electrical
conductivity (EC) of 4000 dS/cm it is said to be saline (Munns and Tester, 2008). An
electrical conductivity of 4000 µS/cm is equal to 40 mM of NaCl or 2.34 ppt which
is the threshold of plant salinity tolerance. Only salt tolerant halophytes can survive
such salinity levels, while salt intolerant glycophytes which form the majority of the
earth’s mass flora cannot survive this level of salinity and the 0.2 MPa of osmotic
pressure imposed by it (Munns and Tester, 2008). The composition of soil salinity
includes sodium chloride along with other salts such as potassium chloride and
magnesium chloride and so on. Despite the many salts present in soil, sodium
chloride (NaCl) is the most researched salt. NaCl significantly affects plant health
compared to other salts (Chen, et al., 2007; Arzani, 2008). The Na+ and Cl- ions are
more detrimental to plants than other ions (Arzani, 2008); it causes ionic and osmotic
stress that leads to early senescence of leaves, deteriorated plant health and even
death. It is also the most soluble and wide spread salt (Munns and Tester, 2008).
11
2.2.1 Effects of increased soil salinity The effects of increased soil salinity on plant health are quite complex. Researchers
are still struggling to clearly identify the causes and effects of plant responses due to
salinity (Munns and Tester, 2008). For example, in the salt stress scenario, the cause-
effect relationship between photosynthesis and growth is difficult to classify.
Reduced photosynthesis can be a cause, or it can be the effect of reduced growth rate
(Munns and Tester, 2008). Many researchers have concluded that salinity affects
plants in two ways; osmotic and ionic stress (Yeo, 1998; Zhu, 2001; Flowers, 2003;
Arzani, 2008; Yamaguchi and Blumwald, 2005).
The first effect increased salinity has on plants is that it induces osmotic stress.
Similar to drought conditions, increased salt concentration in the soil causes a water
deficit resulting from osmotic stress. This is evident minutes after exposure to
increased salinity levels, above the 40 mM NaCl plant threshold limit. As a result of
osmotic stress, stomatal conductance and shoot growth are significantly reduced
(Zhu, 2001; Yamaguchi and Blumwald, 2005). Unlike roots which are in the
frontline of contact with salts, shoots are more sensitive. Hence while root growth
may be unaffected, shoot growth is significantly reduced. Followed by a decrease in
expansion of growing leaves, slow emergence of new leaves and lateral buds, lateral
buds may also remain dormant (Yamaguchi and Blumwald, 2005; Arzani, 2008).
Furthermore, osmotic stress reduces tillering and causes curling of leaf sides in
dicotyledons. The explanation given by Munns and Tester (2008) is that a reduction
in stomatal conductance, shoot growth and leaf area by curling of leaves, allows
plants to conserve water for longer. Reduction in stomatal conductance means that
the stomata remains closed more often which reduces the amount of water being lost,
while reduction in shoot growth and curling of leaf reduces the surface to volume
ratio hence reducing the amount of area available for transpiration to occur.
Conserving water is essential for plants in a salt stressed environment as this
prevents salt accumulation in the cells and therefore allows longer survival.
12
When osmotic stress is induced, cells and leaves lose water. This loss may be
quickly replaced within hours due to the plant’s internal osmotic adjustments but
biomass growth may still be reduced. Over time these reductions contribute to the
final smaller size of the plant and smaller and thicker dimension of leaves (Chen.Z,
et al., 2007; Munns and Tester, 2008; Kader, et al., 2011). Munns and Tester (2008)
explain that this response is due to some form of internal signalling which is initiated
at the first instance of reduction in cell water potential. In the past, abscisic acid
(ABA) had been seen as a potential initiator of the signal as it does play a role in
root-to-shoot signalling, stomatal conductance and cellular signalling. However,
ABA was ruled out when a study done in 2004 by Fricke found that while ABA
levels increased initially at the time of osmotic stress, the effects of reducing biomass
surface area and conductance still persisted long after. There is accruing evidence
that a negative growth regulator protein called DELL of integrates a range of
hormonal signals and gibberellins and is currently seen as the initiator of growth
regulation in stressful conditions (Munns and Tester, 2008).
Meanwhile, the second effect of ionic stress subsequently comes into play as Na+ and
Cl- ions accumulate to toxic levels over time, hence there is a delayed effect
(Yamaguchi and Blumwald, 2005). This toxicity is evident with the increased
senescence of old leaves. Salt ions “arrive” at the new and old leaves at the same
rate. However, since the new younger leaves are still growing and expanding they
are able to exceed the Na+ and Cl- ion accumulation and so avoid toxic effects. On
the other hand, the older leaves are no longer growing or expanding hence the ions
accumulate to toxic levels resulting in early leaf death and an increased rate of
senescence (Yamaguchi and Blumwald, 2005; Munns and Tester, 2008). If the net
pace at which old leaves expire exceeds the net pace at which new leaves emerge,
growth of the whole plant is hindered, due to the reduction in the amount of
photosynthesis occurring. Only in extremely high salt concentration does ion toxicity
hinder plant growth more than osmotic stress (Arzani, 2008; Munns and Tester,
2008).
13
Apart from the toxic effects of ions on leaves, ion accumulation in the plant also
hinders other physiological processes. Accumulation of Na+ in the cytosol causes an
imbalance in the plant’s homeostasis by altering the Na+/K+ ratio (Zhu, 2001;
Chen.Z, et al., 2007). This occurs due to the increased influx of Na+ ions through
low-affinity K+ channels, as well as through low and high-affinity K+ carriers. The
increase in concentration of the extracellular Na+ increases the -140mV potential
difference across the plasma membrane (Yamaguchi and Blumwald, 2005; Chen.Z,
et al., 2007). This results in an inward passive flow of Na+ ions through low-affinity
K+ channels such as K+ Outward Rectifying Channel (KORCs), K+ Inward
Rectifying Channels (KIRCs) and Non-Selective Cation Channels (NSCCs) (Zhu,
2001; Yamaguchi and Blumwald, 2005).
This ion accumulation also hinders enzyme reactions, and other processes such as
photosynthetic parameters. This includes pigment composition, leaf osmotic and
water potential, transpiration rate, temperature, leaf water content (Arzani, 2008;
Munns and Tester, 2008) and respiration and nutrition acquisition (Zhu, 2001;
Yamaguchi and Blumwald, 2005). Yet another indirect damage caused by increased
uptake of salts is the production of Reactive Oxygen Species better known as ROS,
produced mainly in the chloroplast. These substances can cause excessive cellar
damage (Zhu, 2001).
2.2.2 Plant Response Glycophytes and halophytes are both susceptible to high salinities. However
halophytes are better adapted to regulating uptake of salts than glycophytes
(Yamaguchi and Blumwald, 2005). Plants adjust to an increase in soil salinity
concentration in a number of ways. Glycophytes respond to the induced osmotic
stress resulting from increased soil salinity by restricting the inflow of salts and by
producing compatible solutes such as proline, glycinebetaine and sugars to adjust
osmotic pressure (Zhu, 2001; Flowers, 2003; Yamaguchi and Blumwald, 2005). In
14
contrast halophytes use their cellular vacuoles to accumulate and compartmentalise
the salts (Yamaguchi and Blumwald, 2005).
Responses to ionic stress are quite complex compared to osmotic stress. Plants do
this in two ways; firstly by removing Na+ ions from the cells and secondly by
compartmentalising of Na+ ions in vacuoles (Zhu, 2001; Flowers, 2003; Colmer, et
al., 2006). Plants employ H+-ATPase and Na+/H+ antiporters present in the cell
plasma membrane to actively ‘pump in’ H + and ‘pump out’ Na+. An electrochemical
H+ gradient is formed by the H+-ATPase which allows coupling of the passive flow
of H+ by the antiporters into cell and Na+ out of cell along the gradient (Yamaguchi
and Blumwald, 2005).
The compartmentalization of Na+ into the cell vacuoles is mediated by a similar
procedure whereby vacuole H+-trans locating enzyme such as the H+-PPiase and H+-
ATPase generate an electrochemical gradient that allows the Na+/H+ antiporters to
transport the Na+ into the vacuole (Yamaguchi and Blumwald, 2005). Furthermore,
to address the damaging effects of Reactive Oxygen Species (ROS), plants under
stress produce a number of proteins and osmolytes, many of which have unidentified
roles but are assumed to help the plant alleviate the ROS produced and reduce
damage (Zhu, 2001).
Twenty–five years ago Emanuel Epstein articulated aspects of the biological and
technical challenges related to solving soil salinity tolerance (Yamaguchi and
Blumwald, 2005). Since then many studies have been carried out but with little
success. This is because salinity tolerance is affected by more than one gene and the
identification of the key genetic codes is quite an intricate task (Yeo, 1998; Colmer,
et al., 2006; Cuarteo, et al., 2006; Soumaya, et al., 2010). However some studies on
the subject claim a small degree of improved salt tolerance, where genetic
engineering subjected to a single gene, enzyme, antiporter or osmolyte can bring
15
about significant tolerance (Fatokun, et al., 2002; Yesayan, et al., 2008; Kchaou, et
al., 2010).
On the other hand, Flowers (2003), in analysing 68 research papers on barley, citrus,
rice, and tomatoes from 1993 to 2003 (Table 2.1 and 2.2), concluded that while these
crop species were slightly improved by means of enhancements to a particular gene,
enzyme or osmolyte they should not be presumed to be total salinity tolerance at a
whole plant level. Improvements and enhancements may improve salinity tolerance
at a cellular level, however this may be detrimental at a whole plant level as at the
cellular level the complexities of a whole plant are not truly presented (Flowers,
2003; Cuarteo, et al., 2006). Munns and Tester (2008) are of a different opinion, in
that they believe that by engineering a gene, responsible for a single aspect of salt
tolerance such as intracellular compartmentation or osmolyte production, salt
tolerance may be enhanced. They acknowledge that this enhancement may be small
but can be improved by the development of more specific Quantitative Trait Loci
(QTL) Markers. QTLs can identify the multiple genes in association with the specific
trait and then using these traits to breed more tolerant cultivars (Colmer, et al., 2006;
Cuarteo, et al, 2006).
Table 2.1. Number of studies done for genetic modifications per species for salt
tolerance from 1998-2003 (Flowers, 2003)
Species studied No. of studies
Arabidopsis thaliana 14
Brassica napus and B. juncea 3
Citrus (Carrizo citrange) 1
Cucumis melo (melon) 2
Diospyros kaki (Japanese persimmon) 1
Lycopersicon esculentum (tomato) 5
Medicago sativa (alfalfa) 2
Nicotiana tabaccum (tobacco) 19
16
Oryza sativa (rice) 17
Solanum melongena (eggplant) 1
Solanum tuberosum (potato) 2
Triticum aestivum (wheat) 1
Table 2.2 Number of tests done for a particular gene to improve salinity
tolerance in plants and the number of studies carried out in each one since
1993-2003 (Flowers, 2003).
Tested Genes no. of Tests
Apoplastic invertase, Apo-Inv 1
Arginine decarboxylase, ADC 1
Betaine aldehyde dehydrogenase, BADH; betB, choline
dehydrogenase (CDH); 15 15
choline oxidase, codA (glycinebetaine)
Ca2+-dependent protein kinase, CDPK 1
Ca/H antiporter, CAX1 1
Calcium-binding protein, EhCaBP 1
Calicneurin; protein kinase, CaN 1
Ca protein kinase, OsCDPK7 1
Glutathione S-transferase, GST and glutathione peroxidase,
GPX 1
Glyceraldehyde-3-phosphate dehydrogenase, GPD 1
Glycogen-synthase kinase-3, AtGSK 1
Heat shock protein, DnaK/HSP70 1 1
High-af®nity potassium transporter, *HKT1a 3 3
Isopentenyl transferase, ipt (increased cytokinin) 1 1
Late embryo abundant protein, HVA1 (a LEA) 2 2
Mannitol 1-phosphate dehydrogenase, mt1D (mannitol) 6 6
Myo-inositol O-methyltransferase, IMT1 (ononitol) 1 1
17
Omega-3 fatty acid desaturase, fad7 (fatty acid processing) 1 1
Osmotin-like protein 1 1
Proline dehydrogenase; Delta (1)-pyrroline-5-carboxylate
synthetase (proline) 4 4
Proline transporter, AhProT1 1 1
Proton sodium exchanger, *HNX1a 4 4
Putative transcription factor, Al®n1 2 2
Rare Cold Inducible gene 3, RCI3 1 1
Glutamine synthetase, GS 2
Rice Hal2 like, RHL 1
S-adenosylmethionine decarboxylase, SAMDC (spermine,
spermidine) 1
Serine/threonine kinase, AT-DBF2 1
Sorbitol-6-phosphate dehydrogenase, SPD (sorbitol) 1
SR-like, putative splicing protein 1
Transcription factors, DREB1A; AhDREB1 2
Trehalose-6-phosphate synthase/phosphatase, TPSP
(trehalose) 1
Yeast halotolerance gene, Hal2 3
Yeast halotolerance gene, Hal1 2
Yeast mitochondrial superoxide dismutase, Mn-SOD 1
Vacuolar H+-pyrophosphatase, AVP1 1
2.2.3 Approaches to salt tolerance With the rise in global population and the demand for better climate adapted food
crops to meet the global food consumption needs, much effort and funding has gone
into researching crops of significance globally, rather than regional or national
importance.
18
One approach being used to address salinity tolerance employs Quantitative Trait
Loci (QTLs), marker-assisted selections, and direct selection in stressful conditions
to utilize the natural genetic variation in plants. The second approach includes
breeding of transgenic plants where existing gene expressions have been altered and
the introduction of novel genes (Yamaguchi and Blumwald, 2005; Arzani, 2008).
2.2.3.1 Approach 1
The first approach is basically selecting salt tolerant cultivars and lines using either
conventional selection techniques or modern day molecular biology techniques,
wherein DNA markers are used to identify QTLs. QTLs are able to identify several
genes controlling a specific trait. It requires less time and the factor of environmental
effects on a trait is eliminated, compared to conventional selection techniques
(Yamaguchi and Blumwald, 2005). However, the drawback of this particular
approach is that microsatellite markers using Restriction Fragment Length
Polymorphism (RFLP) and Amplified Fragment Length Polymorphism (AFLP) in
high density DNA maps are required, the development of this is costly and time
consuming.
Conventional selection or direct selection techniques are less expensive and
intensive. However they have their own limitations such as the time required and the
effect of the environment on the organism. A recent experiment using this technique
was conducted by Kchaou et al. (2010) on five Olive cultivars; Arbequira I18,
Arbosana I43, Chetoui, Chemlali and Koroneiki. The assessment of salinity tolerance
using direct selection found that overall ‘Chemali’ was the most tolerant and
‘Arbequina’ was the least tolerant (Kchaou, et al., 2010). It was observed that the
induced salinity levels (0, 0.5, 50, 100, 200 mM) affected plant growth parameters
differently. Kchaou et al. (2010) concluded this to be the result of the genetic
variation within the species (Kchaou, et al., 2010). Direct selection has been used by
many other researchers to select salt tolerant cultivars as in scented geranium
(Garnett, et al., 2002), tomato (Colmer, et al., 2006; Cuarteo,et al., 2006), wheat
19
(James and Munns.R, 2003), taro (Tyagi, et al., 2009) rice (Pajuabmon, et al., 2009),
potato (Aghaeri, et al., 2008), Barley (Fricke and Peters, 2002), pistachio (Banakar
and Ranjbar, 2010) and alfalfa (Peel, et al., 2004). This type of selection sometimes
forms the basis or foundation of salinity tolerance screening, which is then further,
developed using the second approach.
Wild relatives have also been used to improve salt tolerance in domestic cultivars.
The first approach is used to select the most salt tolerant wild cultivar of the crop
which is then hybridized with the domesticated one. This approach useful for those
crops where salt tolerant wild cultivars (Satoh, et al., 1998; Colmer, et al., 2006;
Cuarteo, et al., 2006) are available , for example tomato and wheat. However
progress has been slow despite the breakthroughs in genetic engineering and the
successful identification of salt tolerant wild cultivars. This is due to the involvement
of a large number of genes and the various environmental factors that affect the
production of a salt tolerant transgenic using a wild cultivar (Cuarteo, et al., 2006).
Furthermore, combining genes of distant relatives is quite difficult compared with
those for close relatives due to the greater divergence in gene pools (Colmer, et al.,
2006). It is also quite costly to recover the receptor cultivar’s genetic background
(Cuarteo, et al., 2006).
2.2.3.2 Approach 2
Advancements in genetics and molecular biology have provided a boost to the
second approach. Many researchers today focus on engineering a particular gene
(Wu, et al., 2008; Subramanyam, et al., 2010), enzyme, osmolyte (Sakhanokho and
Kelley, 2009) or antiporter (Rubio, et al., 2007; Hein'andez, et al., 2009; Wei, et al.,
2010), that can improve the tolerance and resistance of plants against increased
salinity (Fricke and Peters, 2002; Flowers, 2003; Yamaguchi and Blumwald, 2005).
There have been quite a number of studies carried out on mutagenesis and
enhancement of certain genes to produce tolerant cultivars of crop plants. One such
study shows that the gene coding for cation H+ AtNHX1 mutants in Arabidopsis
20
thaliana integrated in yeast can enhance salinity tolerance in yeast (Hein'andez, et
al., 2009). Similar studies have been conducted in other crops such as barley (Chen,
et al., 2007), tomato (Rubio, et al., 2004), arabidopsis (Zhao, et al, 2007) and
tobacco (Wu, et al., 2008) (Table 2.1 and 2. 2).
Research has also been carried out on halo-tolerant (salt tolerant) bacteria and algae
as they are believed to be true salt tolerants (Liska, et al., 2004; Kader, et al., 2011).
One such halo tolerant green algae is Dunaliella (Liska, et al., 2004) which has been
found to have 76 salt induced proteins that aid in tolerance to salinity levels of up to
3M NaCl. In salt stress conditions normal plants limit transpiration in order to retain
water, this restricts CO2 uptake and reduces plant photosynthetic productivity. Salt
induced proteins in Dunaliella induce CO2 assimilation, which means CO2 is
available for normal photosynthesis to take place and it also diversifies its energy
resources for glycerol production which acts as an osmotic regulator to buffer the
impact of osmotic stress.
More recent research has demonstrated an increase in the salinity tolerance of Maize
by means of inoculation with the bacteria Geobacillus caldoylisilyticus IRD (Kader,
et al., 2011). Maize plants inoculated with Geobacillus caldoylisilyticus showed
higher growth and weight at 350mM of NaCl compared to the non-treated plants.
Geobacillus caldoylisilyticus reduces the impact of salt stress in plants by regulating
plant physiology, reducing the accumulation of toxic levels of Na+ and Cl- ions. It
was also seen that plants inoculated with the bacteria had increased vascular bundles
in leaves and decreased in roots.
In the last two decades salicylic acid (SA) has received much attention from
scientists as not only does it provide possible solutions to salt tolerance but it also
induces resistance against low temperatures, heat stress, toxic metals , pathogens and
oxidative damage (Sakhanokho and Kelley, 2009; Zahra, et al., 2010). Salicylic acid
21
is phenolic in nature and acts as signalling proteins or hormone, it is also an
endogenous growth regulator of physiological processes in plants such as
photosynthesis, growth, ion transmission and absorption. Salicylic acid plays a
significant role in the redox reaction across membranes; hence it counteracts ROS
(produced due salt stress) negative effects by production of anti-oxidant enzymes
which induces oxidative stress, example superoxide dismutase. Salicylic acid has so
far been tested in a number of species such as tomato, maize and wheat.
Unfortunately, as for most species tested for salinity tolerance, there has been little
success in bringing these applications to crop production (Zhu, 2001).
However, some research does offer possible solutions to salinity problems.
Sakhanokho and Kelley (2009) have slightly improved salinity tolerance in Hibiscus
species by the in vitro application of salicylic acid to Hibiscus acetosella and
Hibiscus moscheutos. Both of the species had higher survival when exposed to a
salinity level of 0.5mM NaCl after application of salicylic acid. Tomato
(lycopersicum esculentum Mill.) plants were treated with 0, 0.5, 1.0 and 1.5 mM of
SA and tested against salinity concentrations of 0, 25, 50, 75 and 100 mM. The study
showed that plants treated with SA reduced ROS during photosynthesis, increasing
the chlorophyll a and b content (Zahra, et al., 2010).
2.2.4 Salinity Testing Various screening methodologies such as field, in vivo, in vitro tissue cultures and
hydroponics have been employed in the past by researchers to study the different
aspects of salinity tolerance. Of the three screening methodologies, field experiments
are advantageous for testing plant salinity tolerance in their natural habitat. However,
field testing means there are numerous variables that may affect the performance of
giant swamp taro besides salinity; e.g. micro climate, soil fertility, pH, temperature,
the amount of water in soil and the light intensity (Yamaguchi and Blumwald, 2005;
James and Munns, 2003; Arzani, 2008). To avoid some of the problem of external
22
factors affecting a field experiment, it has been suggested (James and Munns, 2003;
Arzani, 2008) that experiments should be done in a controlled environment. Green
house (referred to as In vivo in this research) experiments allow us to do whole-plant
experiments while controlling several environmental variables.
The majority of in vivo experiments employ the use of gardening pots with holes at
the base for drainage. Some researchers prefer additional procedures of rearranging
pots to ensure no one pot is excessively exposed or the contrary to sunlight (Nyman
et al, 1983). Pots are filled with either potting mix/ soil (Nyman, 1983; Zhao, et al.,
2007; Banakar and Ranjbar, 2010) or sand–perlite mixture of 1:1 (Kchaou, et al.,
2010; Shaddad, et al., 2010). Plants are watered with various concentrations of
Hoagland solution and additional fertilizers depending on plant requirement. When
testing the highest salinity levels salt solutions are usually applied in increasing
increments instead of one single application in order to acclimatise the plant and
avoid toxic shock. In vivo plants may also benefit from periodic additions of fresh
water that mimic flushing action of rain. For example Kchaou, (2010) applied 200 ml
of de-ionized water weekly to plants in a salinity tolerance study carried out on five
olive cultivars.
Peel (2004) employed Ray leach Cone-tainers, with a 70 mm layer of grit to hold
enough moisture and silica sand. Silica is an inert medium and prevents
accumulation of salts. A 10x10 cm2 square of capillary matting was used to confine
sand in the cones and to ensure proper flow of nutrients and treatments. These cones
were then arranged in flats of 98 cones each and submerged in nutrient solution and
salt treatments as and when required. Although when using in vivo techniques it is
possible to control light exposure, difference in soil microclimate and pH to some
extent, it is not so easy to control the level of moisture present in the soil, the
exposure to wind, cold and heat. These factors that are beyond control in an in vivo
experiment but can be controlled in an in vitro system.
23
Wilhem Roux first established the basic idea of tissue culture in 1885 as an in vitro
system when he maintained the medullary plate of an embryonic chicken for a
number of days using a warm saline solution (Steinhardt et.al., 1913). Since then
tissue culture as an in vitro system has been commonly used for salt tolerance
screening (Zhao, et al.,2007; Wu, et al., 2008; Tong, et al., 2010; Yifei, et al., 2009).
In an in vitro system, all the environmental and growth medium factors are strictly
controlled. Plants are cultured in a specific basal medium, in culture bottles and kept
in rooms with controlled duration and intensity of light, temperature and humidity.
Since the plants are in culture bottles they are not affected by the outside climate as
with green house and infield system.
In an in vitro screening, modified Murashige and Skoog medium (1962) has been
readily used as the basal medium, to which various NaCl concentrations are added
(Nyman, 1983; D’Antonio and Weber, 1999; Hady.A, 2006). The cultures are then
placed in a strictly controlled environment in labs. The use of in vitro techniques
allows for salinity screening of large numbers of genotypes. This is due to the
relatively short time taken for growth and multiplication in tissues culture compared
to conventional screening. It is also to some extent comparable with field
experiments and requires less area in which to conduct the experiment compared to
field experiments (Arzani, 2008).
Yet another form of screening methodology used is a hydroponic system. One such
study involving the use of hydroponics was carried out by Rush and Epstein in 1981
to study the relation of minerals such as potassium, sodium, and chloride to wild
halophytic and domestic salt-sensitive tomato species. Similarly, hydroponics has
been employed in present day, such as in the study of leaf growth in salt stress in
barley (Fricke and Peters, 2002) and many others. Both the experiments applied salt
treatments at incremental basis up to the highest salinity level of the experiment.
These increments were undertaken at periods of 2-7 days.
24
Therefore, with the complexities of the impacts of increased soil salinity on plants
and the need for development of salt tolerant cultivars, researchers have adopted and
modified these salt screening methodologies. Adjusting their choice of procedure to
the type of crop, level of growth assessment and extent of control over external
variables.
2.3 GIANT SWAMP TARO (Cyrtosperma merkusii)
The increase in the ground water salinity level poses a threat to the food security
system of the atoll island communities. Crop adaptation to increasing salinity levels
presents one way of curbing the problem. Due to the significant role Giant swamp
taro (Cyrtosperma merkusii) plays in food security and lives of the atoll island
communities, it has been selected for research and development as a climate ready
salt tolerant crop (Figure 2.2).
Figure 2. 2 Giant Swamp taro Cyrtosperma merkusii
By Shiwangni Rao
25
Figure 2.3 (left) Giant Swamp taro corm (from http://www.pbase.com/
jamato8/image/ 127855767). Figure 2.4 (right) Giant Swamp taro farm in FSM.
Giant swamp taro is a large herbaceous perennial plant that can reach up to 5 metres
in height and the corm can weigh up to 10 - 20 kg when harvested within a year or
two (Ivancic, 1992) (Figure 2.4). Some have been seen to weigh up to 100 - 120 kg
(Figure 2.3). However these values vary according to the genotype and with
maturity, especially in the larger cultivars (Dunn, 1976; Covich, 2006). Vickers
(1982) states giant swamp taro is the largest root crop with an edible corm. It has
large leaf blades reaching up to 1m in width and quite similar in shape to Alocasia
macrorrhizus that is it is saggitate to hastate with two long acute basal lobes
(Manner, 2009). Some giant swamp taros have pricks on the petioles and the colours
may vary according to the cultivar. While others have reduced leaves, ‘cataphylls’ on
the underside of the leaf blade (Ivancic, 1992.; Iese, 2005; Cyrtosperma merkusii,
2006). The inflorescence is a cylindrical spadix with a large spathe (Hather and
Weisler, 2000; Iese, 2005; Manner, 2009). The many cultivars of the giant swamp
taro are generally classified into two groups in Kiribati, which have been adopted for
the purpose of this study. Group one, the “Ikaraoi” is larger, takes much longer to
mature (2-3 years) and has five or less suckers (shoots emerging from corm). The
By Shiwangni Rao
26
“Katutu” is the smaller cultivar group; it matures much earlier than the Ikaraoi
(within 6 months) and has more than five suckers (Iese, 2005; Manner, 2009).
Figure 2.5. Phylogenic classification of Giant Swamp taro. (Cyrtosperma merkusii, 2006)
The genus name Cyrtosperma is derived from the Latin for “Curved Seed” (Mayo, et
al., 1997) (Figure2.5). The species name on the other hand is quite ambiguous, as the
giant swamp taro has been confused with other taro species in the past, which has led
to it being called by a number of species names. Consensus now favours
Cyrtosperma merkusii. From the limited documentation available there are 18
known cultivars in Tuvalu (Iese, 2005), about 11 in Kiribati and 60 in Federated
States of Micronesia (Englberger, et al., 2003.; Englberger, et al., 2005.; Englberger,
et al., 2007) plus many unknowns. Iese (2005) used 27 characterization descriptors
that were discussed and articulated with 21 farmers from Fiji, Pohnpei Federated
States of Micronesia and Tuvalu. He chose farmers from these three countries to
provide a better knowledge base of the diverse range of cultivars grown and known
on the three types of islands. Tuvalu represented atolls that are low lying, Pohnpei
for an intermediate between coralline and volcanic islands and the highlands of
Rewa province in Fiji for volcanic islands.
Giant swamp taro (Cyrtosperma merkusii) cultivation can be quite a strenuous task,
depending on soil fertility. In the highlands of Fiji, the soil is quite rich, hence little
Plantae Tracheophyta Subphylum: Euphyllophytina
Liliopisa Subclass: Aridae
Arales Superorder: Aranae
Araceae Subfamily: Lasioideae
Cyrtosperma
merkusii
27
work is required. However, on atolls such as Kiribati, Tuvalu and Federated States of
Micronesia (FSM) the plants require much nurturing. Cultivation on the other atoll
communities follows a similar pattern of cultivation with their own modifications.
Giant swamp taro is often referred to as being salt tolerant (Lambert, 1982;
Brandburry and Holloway, 1988; Kazutaka and Michia., 2003; Covich, 2006; Deenik
and Yost, 2006). However, the degree to which it is salt tolerant remains uncertain
(Nyman, 1983; Webb, 2007). Webb (2007) in his survey showed that giant swamp
taro grew well in soils with an electrical conductivity of 1000µScm-1 (0.67ppt) or
less. It could also tolerate 2000µScm-1 (1.34ppt) or less but electrical conductivity
between 2000µS cm-1 and 3000 µS cm-1 (2.01ppt) was fatal to the plant, meaning
that it grew well in fresh and mildly salty water but died in brackish water. Wiens
(1962) proposed that water in the giant swamp taro pits in Kiribati was particularly
fresh and sometimes fresher than well water. Dunn (1976) supports giant swamp taro
being salt tolerant. He found the tolerance to be within the range of 2-3ppt salinity as
did Brown (2000) who stated that giant swamp taro grew quite well in brackish
water. A 2004 Agroforestry in Micronesia report states that Cyrtosperma merkusii
grew well in salty pits. The results from these studies suggest that the extent to
which giant swamp taro is salt tolerant depends on the cultivar.
2.3.1 Origin Taro is a major staple of the Pacific islands. There are four types of taro which are
normally found in the Pacific. These include the common taro Colocasia esculenta,
Xanthosoma sagittifolium, Alocasia macrorrhizos and the giant swamp taro
Cyrtosperma merkusii. Of these four types of taro Cyrtosperma is the largest,
reaching up to 5 metres in height (Dunn, 1976; Hather, 2000; Iese, 2005) and takes
the longest to reach maturity. It is also known for its hardy qualities of surviving in
atoll environments; hence this spectacular crop has been found to be cultivated in
large numbers in the atoll islands.
28
Giant swamp taro is one of the root crops that have spread across the Pacific
reaching as far out as the Makatea Island on the northwest of Henderson island in the
Tuamotu Archipelago (Hather, 2000). Some researchers have concluded
Cyrtosperma to be of an Indonesian or Indo-Malayan origin. Lebot (1992) and Hay
(1990) argue that the high lands of Papua New Guinea could be a place of origin
(Figure 2.6). On the other hand, using archaeobotanical analysis Hather (2000) found
that “…Cyrtosperma was an aboriginal introduction across Polynesia except for New
Zealand and Easter Island where climate plus cultural preferences may have
discouraged its growth...” he also found that Cyrtosperma merkusii was present as
far back as 1451 A.D. While the uncertainty of origin may still exist, the Indo-
Malayan region is certainly the region that holds the greatest diversity of the root
crop (Bradburry, 1988; Iese, 2005).
Figure 2.6 .Map of Malesia, including the possible origins of Giant swamp Taro
Cyrtosperma merkusii. (wiki/File:Malesia.png).
29
2.3.2 Current Distribution
Figure 2.7 Map of the cultural spheres and the current distribution of giant swamp
taro expect for New Zealand (ANU Cartographic Services, 2008).
With the lapse of time from 1451 A.D to the twenty first century, modernization has
played a pivotal role in shaping the present trends in lifestyle preferences from
technology to traditions. Giant swamp taro has fallen victim to modernization. It
once flourished in the Indo-Pacific region and was seen as a major root crop and a
local food staple but it is now being replaced by western foods at an accelerating
pace. Currently the distribution of giant swamp taro may still be the same as it was in
the past but the intensity of cultivation / population has dropped drastically (Iese,
2005; Talia, 2009) (Figure 2.7). However, the full extent of this reduction is poorly
characterised, along with the many probable causes of it, highlighting a need for
further research and investigation.
30
According to Hather (2000) giant swamp taro is drought and salt tolerant in
comparison to other root crops such as the common taro and yams. Due to these
qualities modern cultivation is focused around areas where other crops do not do so
well such as on atolls. Atoll soils lack the minerals and texture of good soil, such as
those found on the volcanic islands. Atoll soils are dry and slightly saline and have a
thin organic top layer made from the decomposition of fallen vegetation. The
Micronesian and Western Pacific region are where most of these low lying atolls lay,
hence it is this area that has the highest giant swamp taro population (Manner, 2009).
The isolation of atoll islands from the main land and continents has resulted in
cultivar divergence such as in the atolls of Federated States of Micronesia where
approximately 60 cultivars exists. Giant swamp taro is also present on volcanic
islands where it grows wild or with limited cultivation such as in Fiji around the
Rewa province, where it is grown because the area is frequently flooded. The
common taro which is more preferred in Fiji cannot survive (Iese, 2005) this
frequent flooding.
2.3.3 Physiology
Giant swamp taro thrives in a tropical climate and tolerates occasional dry seasons
with variation in rainfall. Manner (2009) notes it easily tolerates temperatures of 35-
38°C down to 15°C monthly mean temperature. In Yap it is planted in Mesei type of
soil, it’s a soil with a pH of 4.5-5.5 which is high in organic matter and water logged,
resulting in a mucky dark loamy soil that is overlaid with soil alluvial in origin.
Dechel is another soil type similar to Mesei and Dechel is a type of soil that has a pH
of 5.1-7.3 and is used in Guam for giant swamp taro cultivation. Ngedebus is another
type of soil is used in Ulithi atoll, this is found in marshy land depressions with a
gravel, loam and sand mixture resulting in pH of 6.6-8.4.
31
Farmers on Funafuti in Tuvalu have found that a particular cultivar the ‘Pulaka
Kula’ is better adapted to saline conditions than other cultivars found on the island.
According to farmers during high tides sea water causes the pulaka (Tuvaluan name
for giant swamp taro) in the pits to wilt but the pulaka kula is unaffected. It also
needs less attention compared to the Tuvaluan cultivar ‘Ikaraoi’ which has the most
valuable corm.
2.3.3.1 Cultivation
Figure 2.8. (above, left)
Sunken cultivation in Tuvalu,
Nanumea.
Figure 2.9 (above left).Coconut Cocus nucifera leaf woven bottomless basket in
Funafuti, Tuvalu. Figure 2.10 (Right) Giant swamp taro cultivation in Fiji.
By Shiwangni Rao
By Shiwangni Rao By: Tevita Kete
32
Figure 2.11 Concrete cement pit Taro
cultivation on Tuvalu in Funafuti.
Cultivation of the crop varies from island to island and also among cultivars and
groups of Ikaraoi and Katutu. Very few cultivars of giant swamp taro produce viable
seeds; hence farmers prefer vegetative propagation. One method of vegetative
propagation is the planting of cuttings trimmed from harvested plants, with around a
30 cm petiole and a reasonable bit of corm attached (Manner, 2009). Another method
is to plant suckers that emerge from the corm. The petioles of the suckers are cut in a
downward diagonal direction for better growth of the plant (Iese, 2005) and it is
believed by some Tuvaluan farmers that if the plant is left unattended it will produce
suckers and if attended it does not.
Giant swamp taro is grown in natural or manmade swamp depressions. Many of the
manmade swamps present on the atolls today were excavated by the first settlers on
the island (Thaman, 2002; Iese, 2005) (Figure 2.8). The hard coralline soil was dug
with primitive tools (for instance a digging stick) and these swampy pits were dug
down until the ground water lens was reached. Then mulch and compost was applied
to create an organic soil. In Kiribati bottomless baskets are woven using pandanus
(Pandanus tectorious) or coconut (Cocus nucifera) leaves and the giant swamp taro
is planted in these with constant composting. In Tuvalu farmers dig holes in the
pulaka pits approximately 20-30 cm wide and 15-30 cm deep (Figure 2.8). This hole
is referred to as ‘Knowledge of the hole’ or in Tuvaluan ‘Logo o tepoko” by some
By Shiwangni Rao
33
Tuvaluan farmers (Iese, 2005). Young trimmed suckers are planted in this hole and
tied to a stick called the ‘tokai’ for support.
There are two methods of composting seen in Tuvalu in regards to what is being
used as compost and the timing of the compost application, both of which are
regarded essential by the farmers for a good, high quality. The first and most popular
cultivation method involves applying compost to the young plant when planting
using the fresh leaves of pukavai (Pisonia grandis). However, a limited amount of
compost is applied, as too much may cause overheating and eventual death of plant
(Iese, 2005). This is why some farmers prefer the second method where compost is
applied only after the first leaf appears. The leaves of the pukavai decay easily in
about two weeks and support rapid growth of the plant. When decaying it also
produces a pungent smell which deters insects and pests (Iese, 2005). After the
emergence of three to four leaves the next compost is applied; this may contain
cuttings of other plants including pukavai, gasu (Scaveola taccada), kanava (Cordia
subcordata), and puavao (Guettarada speciosa) (Thaman, 2002; Iese, 2005). This
compost along with some soil for air circulation is applied at a distance from the
young plants, as digging and applying at the base would damage the tender young
roots. After this, farmers check the decay of the compost by stamping around the
plant; if it feels cushioned it means that the compost has decayed (Iese, 2005). Also
when the base of the young plant starts to show it is taken as an indication that the
last compost has decayed and more needs to be applied. After seven months of
composting with the leaves of the above-stated plants, coconut husks and green
leaves are then employed, as it turns the soil dark and the giant swamp taro corm
becomes tasty with a good texture (Iese, 2005).
It was observed that similar to cultivation in Kiribati some farmers had woven
coconut leaves in a circle around the plant and then applied compost to it (Figure
2.9). This along with platted mud walls around the plant is done to hold the compost,
when the young plants have six to seven leaves. Using plaited coconut leaves also
34
supplied compost and a new one is plaited every time the old one decays. As stated
earlier the mulch of giant swamp taro consists of surrounding vegetation, cuttings of
leaves, soil, pumice and general compost. However, the contents of the mulch vary
between farmer families, that have their own secret recipes, times and chants that are
used during mulching; this knowledge is rarely revealed due to fear of competition
(Thaman, 2002). Many forms of compost timing are employed by farmers. This
includes taking into account moon phases, the number of leaves sprouting and when
the base of the plant starts to show the trimming at neap and spring tides, and when
the soil around the pit starts to feel soft (Iese, 2005).
In Guam farmers have the dechel cultivation system, where land is cleared and
planted with the setts (cuttings of the stem with a bit of corm) or suckers of previous
harvest (Manner, 2009). In Palau the Mesei system is employed where the soil is
mulched and overturned; the outer island of the Federated States of Micronesia have
cultivation methods similar to the Kiribati and Tuvalu. However on the main land
Pohnpei, cultivation is less intense similar to the highlands of Fiji. The most simple
and easiest cultivation of giant swamp taro can be found in the Rewa province in Fiji
where holes are dug and a bunch of suckers tied with giant swamp taro petiole strip
is planted ensuring that at least one sucker survives (Figure 2.10). This also gives
larger corms and gives protection to the plants during flooding (Iese, 2005). Apart
from this the most recent advancement seen in Tuvalu in giant swamp taro
cultivation is planting it in concrete cement pits as this ensures that salinity in the soil
does not affect the plant (Figure 2.11). The timing of planting giant swamp taro also
varies. Atoll island farmers such as on Tuvalu prefer to plant when the tide is very
low; usually during the cool and dry seasons when the pits are not flooded. Fijian
farmers prefer to plant during the rainy season when the soil is softer (months of
October to April).
35
2.3.3.2 Maturity and Harvest
Giant swamp taro in general matures in 2-4 yrs. However, the ‘Katutu’ cultivar of
Kiribati and the Chuukese cultivar ‘Onou maram’ (Manner, 2009), can mature in six
months. Plant height is directly related to its maturity age, in the sense that the longer
a plant cultivar takes to mature the taller it grows and vice versa. In Tuvalu, farmers
count the number of flowers as an indication of maturity; after seven flowers the
plant is said to be mature and ready for harvest (Iese, 2005). Similarly in Yap,
maturity depends on plant flowering, which begins in the second year of growth.
Also when emerging leaves are smaller than usual and when the corm starts to rise
above the ground (giant swamp taro corm grows both up and downwards) (Manner,
2009). In Kiribati, maturity is related to growth stage and time (Table 2.3). In Fiji
harvesting takes place when suckers begin to scatter, growth is reduced and when all
plant leaves turn yellowish. It is also believed by the Fijian farmers that the best time
to harvest giant swamp taro is between June to September. At the time of harvest
corm can weigh from 15-20 kg (Hather, 2000) to 100-120 kg when left for a long
time in ground (Dunn, 1976; Iese, 2005; Manner, 2009) (Figure 2.12 and 2.13).
Giant swamp taro also gives a good yield becasuae only a limited number of pests
and diseases is know to affect the plant. Except for the rarely found Dasheen Mosaic
Virus (DMV) which affects the whole plant, the rest of the pests are mostly
nematodes that burrow into the corm (Table 2.4)
Figure 2.12 Giant
swamp taro harvested
corms.(from
http://atinleparang.blo
gspot.com/2009
_11_01_archive.html)
36
Table 2.3 Kiribati description of giant swamp taro growth stages (Manner,
2009).
Growth stage Time Description
Te Kunei 9 months This is the harvest time for the Katutu cultivar
group. Corm is approximately half the size of
forearm in length; at this size the corm is
tender.
Te
namatanibura
3 years Corm is the size of a full forearm in length
and fully matured. However some are very
bitter at this stage.
Etan
tenamatanibura
5 years Corm three quarters of an arm in length.
Te anga 7 years Corm is a full arm's length in size and used in
certain rituals.
Te bonaua 10+ Corm is up to breastbone in length and the
corm becomes hard. This corm is mainly used
as presentation on special occasions such as
by the groom’s family to the brides during
weddings.
Figure 2.13 Giant swamp taro
corms (from http://bild-
art.de/kpress/)
37
Table 2.4 List of pests, diseases and their impacts on giant swamp taro
(Bradburry, 1988; Iese.V, 2005; Manner, 2009).
Pest/diseases Impact on plant
Papauana huebneri Beetle burrows and makes the corm
susceptible to other parasitic organism,
which can result in plant death.
Glover Ahis gossypii eat leaves of giant swamp taro
Mealy bugs Pseudococcus,
Nr.adoniumL.
eat leaves of giant swamp taro
Ferrisiana virgata Ck11 eat leaves of giant swamp taro
Bag worm (unidentified) eat leaves of giant swamp taro
Hippotion sp. Caterpillar, leaf eating
Spodotera Litura Caterpillar, leaf eating
Theretra pinastrina Caterpillar, leaf eating
Criconemella denoudeni Nematode that burrows into the corm
resulting in rot
C. onoesis Nematode that burrows into the corm
resulting in rot
Helicotylenchus dihystera Nematode that burrows into the corm
resulting in rot
Meloidogyne Sp Nematode that burrows into the corm
resulting in rot
Pratylenchus coffeae Nematode that burrows into the corm
resulting in rot
Radopholus similis Nematode that burrows into the corm
resulting in rot
Pythium rot affects corm
Dasheen mosaic virus affect whole plant
38
2.3.4 Morphology
Giant swamp taro produces bright and conspicuous flowers in many of its cultivars
(Figure 2.14). The inflorescences consist of a reproductive spadix, a colourful leaf
like spathe, seeds and flower stalk. The spadix is an elongated inflorescence and in
certain cultivars is fertile producing seeds upon maturity, while in others stays sterile
(Figure 2.15 and 2.16). The fertility rate of the inflorescences depends on the
cultivar. Usually fertility rate is quite low and many of the seeds produced are sterile;
hence many farmers use vegetative propagation (Figure 2.17). The spadix is
approximately 20-25cm in length, is hermaphroditic. It is unlike the common taro
Colocasia esculenta which has the female component at the top and the male
component at the bottom usually enclosed, giant swamp taro has both the male and
female component in each flower of the inflorescent and the spadix is usually
exposed. The pollen produced on these tiny anthers varies in colour from white
yellow to reddish orange (section 3.5).
Figure 2.14 (left) labelled giant swamp taro flower. Figure 2.15 (middle left) young spadix and flower.
Spathe
Spadix
By Shiwangni Rao By Shiwangni Rao
39
Figure 2.16 (middle right) Seeded berries on spadix. Figure 2.17 (right) Mature
spadix.
The spathe is a thick leaf like colourful covering that partially envelopes the spadix.
The colour of the spadix and spathe depends on the cultivar of giant swamp taro
ranging from green to yellowish green, pink to maroon at maturity. Pwh weitata a
Federated States of Micronesia cultivar has a unique spathe as it turns from yellow to
green at maturity which is rare (Figure 2.18 and 2.19). The flower stalk also has its
own colour usually intermediate between spathe and petiole colours.
Figure 2.18 (left)
young Pwh weitata
flower. Figure 2.19
Mature Pwh weitata
flower.
By Shiwangni Rao By Shiwangni Rao
By Shiwangni Rao By Shiwangni Rao
40
The leaf petioles have a diverse range of epidermis texture; they range from smooth
to varying degrees of spines. Petiole colours range from maroon, yellowish pink to
dark green. And have three types of petiole neck shape namely, straight, curved and
swan neck. Leaf height and size depends on cultivar and maturity of the plant (Figure
2.20).
Figure 2.20 (left)
leaves of giant
swamp taro.
Figure 2.21
(right) corm of
giant swamp taro.
As in all taro the stem of the giant swamp taro is absent (acaulescent), but it has a
very valuable corm (Figure 2.21). The swollen corm, can weigh from 10-150 kg
depending once again on cultivar and maturity. The corm flesh may be completely
white, pink to yellow in colour with brown to yellow corm fibres. The corm is
slightly harder than the other three taros and the degree of hardness depends on the
cultivars and length of stay the corm has been in ground. The Tuvaluan cultivars of
smooth and thorny suwetena and the Mwhng seri of FSM are three cultivars known
for the softness of their corms. The giant swamp taro corms have a small root
system, with root fibres that are 5mm in diameter, short and thick. These roots are
concentrated just below the leaf base area
By Shiwangni Rao
By Shiwangni Rao
41
2.3.5 Cultivar Descriptor List As stated earlier little research has been carried out on giant swamp taro, hence
limited knowledge is available for development of the crop. In an attempt to broaden
the knowledge on giant swamp taro a detailed cultivar descriptor list was developed
(Table 2.5) by improving on the list prepared by Iese (2005). Iese (2005) had a
number of traits and characteristics that were overly variable in response to
environmental conditions and hence had low utility in distinguishing between
cultivars. The revised descriptor list was developed during a two day workshop
conducted in Pohnpei, Federated States of Micronesia with the help of local experts.
The workshop consisted of 37 participants, 27 farmers and 10 agriculture field
technicians of Pohnpei Agriculture Department. There was an equal distribution of
ages ranging from young to old framers, while a 3:1 gender ration for men to women
was present in the workshop. Using a giant swamp taro descriptor list composed by
Iese (2005) consisting of 27 descriptors, along with IPGRI (2007) full descriptor list
for Taro Colocasia esculenta as a guide for characterisation a detailed draft
descriptor list was prepared. This was then presented on a PowerPoint presentation
and explained to the participants with translations in Pohnpeian from the Pohnpei
Chief Agriculture Officer Mr. Adelino Lorens. Through an open discussion the
participants at the workshop, worked through the various descriptors to select the
most pertinent descriptors for giant swamp taro. There was common agreement
among the participants for all the selected descriptors across both age range and
gender. Mr. Adelino Lorens on previous trips to the outer islands of Federated States
of Micronesia had collected approximately 50 proposed cultivars and had planted
these in the Pilot farm in Pohnpei. The Pilot farm presented a collection of all
Federated States of Micronesia cultivars; hence it was used for characterization of
the giant swamp taro cultivars using the developed descriptor list with the help of
four agriculture field technicians.
42
Table 2.5 Revised descriptor list
No. Trait Variability 1.1 Plant span/ spread 1.Narrow
(<50cm) 2. Medium
(50-100cm) 3. Large
(>100cm)
1.2 Plant height at maturity
1.short(3-4ft) 2.medium(5-
10ft) 3.long(>10ft)
1.3 Number of suckers (direct shoots)
1.many(<10) 2.few(5-10) 3.less (>5)
1.3 Number of suckers (direct shoots)
1.hastate (Having the shape of an arrowhead but with the basal lobes pointing outward at right angles)
2.peltate
(Having a flat circular structure attached to a stalk near the centre, rather than at or near the margin; shield-shaped
Direct suckers
Height
Hastate Peltated
Plant Span
43
2.2 Spread of leaf lobes 1.Overlapping
2. Acute
angles (<45º)
3.Right angles (90º)
2.3
Leaf blade margin 1.Entire (not wavy)
2.Undulate (wavy)
3. Sinuate (Very wavy)
2.4 Leaf blade colour 1.Whitis 2.Yellow/
Yellow green 3. Light green 4. Dark green 5. Pinkish
green 6. Reddish
green 7. Purplish 8. Blackish
2.5 Leaf lamina appendages/ cataphylls
1.Absent 2. Present
2.6 Leaf main vein colour 1.Whitis 2.Yellow/
Yellow green 3. Light green 4. Dark green 5. Pinkish
green 6. Reddish
green 7. Purplish 8. Blackish
Overlapping lobes Acute lobes
Entire Margin Wavy Margin
Leaf main vein
Cataphylls
44
2.7
Leaf arrangement(la) 1.Absent 2. Present
3.1 Colour of top third (P/c/t/third)
1.Whitis 2.Yellow/
Yellow green 3. Light green 4. Dark green 5. Pinkish
green 6. Reddish
green 7. Purplish 8. Blackish
2.8 Number of leaves(nol) 1.few(<5)
2.normal (5-10)
3.many (>10)
2.9 Leaf lamina length : width ratio
describe
2.1 Petiole junction pattern
describe
Clockwise
Counter-clockwise
Top
Middle
Bottom
Length
Width
45
3 Petiole(leaf stalk)
3.1 Colour of top third (P/c/t/third)
1.Whitis 2.Yellow/
Yellow green 3. Light green 4. Dark green 5. Pinkish
green 6. Reddish
green 7. Purplish 8. Blackish
3.2 Colour of middle third (P/c/m/third)
same as above
3.3 Colour of lower third (P/c/l/third)
same as above
3.4 Petiole stripes 1.Absent 2. Present
3.5 Petiole shape(top)(ps(top)
1.straight 2.curved 3.swan’s neck
3.6 Petiole throne/spine/(pthorns)
1.Absent 2. Present
Straight neck
Swan neck
Curved neck
Petiole with fine printed stripes
46
3.7 Petiole spine color(p/t/(col)
1.green 2.dark green 3.yellow 4.red 5.pink 6.purple
3.8 Spine size(p/t/size)
1.short(<2mm) 2.medium (2-
3mm) 3.long (3-
4mm) 4 Inflorescence/ Flower
4.1 Flower formation 1.Absent 2. Present
4.2 flower stalk color 1.Whitis 2.Yellow/
Yellow green 3. Light green 4. Dark green 5. Pinkish
green 6. Reddish
green 7. Purplish 8. Blackish
4.3 spathe (flower cover) color top/ bottom and young/old
Describe
4.4 Spadix/ pollen color Same as 4.2 options
4.5 Berries color Same as 4.2 options
4.6 Seeds Viability (sv) 1.viable
(grow) 2.non-viable
(don't grow
4.7 Male portion of flower
1.Enclosed 2. Exposed
Berries/ seeds
Indicator of fertility
Stalk
Spadix
Spathe
Thorns/ Spines
47
4.8 Fertility of the female part of the inflorescence
1.none 2. Low (<40%
fertile
flowers)
3.
Intermediate
(<80%)
4. High (almost 100%)
5 Corm
5.1 Corm Size 1.Small 2.Medium 3.Large
5.2 Corm Cortex Color 1.White 2. Yellow
3. Orange
4. Pink
5. Red
6. Purple
7. Other 5.4 Corm flesh color
central part same as above
5.5 Corm flesh Fiber color
same as above
6 Roots Describe
7 Taste 1.Very Hard 2. Itchy/
irritating 3. Good 4.Very good
8 Special characteristics eg. Drought or salinity tolerance
Describe
Cortex
Central part
Roots
48
2.3.7 Utilization
‘…for people of Tuvalu, pulaka appears to be the most important food crop next to
the coconut....’ (Dunn,1976). Iese (2005) citing Nakon (2001) states giant swamp
taro cultivation yearly was 8 million calories per hectare which is equal to the
production of true taro in Oceania.
Apart from being consumed for its nutritious corm the giant swamp taro has other
very essential uses as well. It has been woven into the island traditions and culture as
a precious gift to be presented as an offering to the chief or chiefly person’s on
special occasions such as family gatherings or marriage ceremonies. In Tuvalu the
Kaupule (Island Councils) call for Fuauli (medium sized giant swamp taro) for the
Fakaala (gathering such as weddings, funerals, village meeting) requiring every
family to provide Pulaka. Nafa competitions are one of the competitions the people
of Tuvalu look forward to. Partners for the competition are announced at the
beginning of the year and they work hard in the intervening period to produce the
best pulaka. The winner is announced according to the highest corm yield (Dunn ,
1976; Iese, 2005; Manner, 2009).
Giant swamp taro is a very prestigious plant for Micronesians and especially for
Tuvaluan and Kiribati people. It is a great contributor to the food security of the
atolls as well as to traditions and customs. Apart from this its valuable corm, giant
swamp taro has many other uses of its leaves. This is used to wrap food, cover
stored ripening fruits, used as an umbrella, drinking bowls, dancing shirts ‘Titi’ for
Tuvaluans, and garlands for Rotumans. Its petiole is used for fertilizer, mat weaving
and medicines (Dunn, 1976; Hather, 2000; Englberger, 2005; Iese, 2005; Manner,
2009; Talia, 2009)
49
Table 2.6 Local recipes of giant swamp taro
Tuvaluan traditional dishes:
Tao – peeled and earth oven baked pulaka
Kofuga pulaka- cleaned pulaka is cooked in coconut cream wrapped in banana
leaves.
Faalifu- cleaned and boiled pulaka in coconut cream
Taufagogo- pulaka is cleaned and cut into small pieces, this is then placed inside a
scraped green coconut shell with some coconut cream and Toddi and the baked in an
earth oven.
Lipilipi/ tokotokoi- small pieces of baked pulaka is mixed with boiled coconut cream
Fakapapulaka/ Tulolo – boiled pulaka is pounded until smooth then mixed with
Toddi
Fekei- grated pulaka is mixed with Toddi and cooked wrapped in pulaka leaves. This
is then mixed with boiled coconut cream
Nepo- scraped coconut and boiled pulaka is pound together until smooth and then
mix with water first followed by toddy
Solo/ Mafu- grated pulaka cooked covered with banana leaves
ValuValu pulaka- grated pulaka is mixed with water and Toddi placed inside a
scraped green coconut and baked.
__________________________________________________________(Iese, 2005)
Marshallese Traditional Dishes;
Wūden- giant swamp taro is mixed with nuts and grated coconut or cooked and
boiled banana, breadfruit and Colocasia taro.
Jebwater- mixed with coconut milk and grated Taro, baked in an oven wrapped in
taro leaves.
Totaimon – mixed with coconut oil and sap and grated Colocasia taro.
KōmāKij – with mashed potatoes or Colocasia taro.
Jukjuk- mixed with coconut and pounded Colocasia taro.
_____________________________________________________ (Manner, 2009)
50
2.3.8 Nutrition Giant swamp taro like other root crops has high starch and carbohydrate content and
low protein. It has the second lowest protein content (0.8% dry weight) in
comparison to the other three taro, of which the common taro has the highest protein
content of 4.5% of dry weight (Iese, 2005). Also in comparison to the other three
taro species giant swamp taro has a higher content of Vitamin B1, C, calcium and B-
carotene which is directly related to the uncooked corm colour; the darker the shade
of yellow for the corm the higher the carotene content (Englberger, 2003;
Englberger, 2005; Iese, 2005). Apart from this, giant swamp taro also has mineral
content as shown in table 2.7 and 2.8.
Giant swamp taro has a high content of oxalic acid crystals which causes irritation in
the mouth and throat; this is 10 times higher than common taro, sweet potatoes and
cassava. However, these crystals can be easily removed by proper cooking.
Federated States of Micronesia Dishes;
Women in FSM have learnt to make many exquisite dishes from giant swamp taro;
Lihili - taro is boiled and mashed with a special pounding stone, and coconut milk is
added to it.
Mwael/ Piaia - Taro boiled with coconut milk.
Rotama - Raw taro grated and mixed with cassava starch.
Taro chips - Taro is cut into thin slices then fried in oil, salt is added on top
according to taste.
Taro donuts - Taro is pounded and then sugar is added. This mixture is then shaped
into donuts and fried.
Taro flour - Finely grated taro is sundried till it turns floury. This can then be used as
normal flour for cooking and baking.
Taro cooked in earth oven is another popular way of having taro in FSM.
51
Tab
le 2
.7 G
iant
swam
p ta
ro n
utri
tiona
l val
ue (S
PC, 2
006)
Food
Item
K
cal
Fi
bre
(g)
Cal
cium
(mg)
Iron
(mg)
Zi
nc
(mg)
ß ca
rote
ne
equi
v. (µ
g)
Thi
mia
n
(mg)
Vita
min
C (m
g)
Cyr
tosp
erm
a co
rm
colo
ur u
nspe
cific
72
2
.5
165
0
.6
1.9
2
7
0.0
2
7.9
-whi
te/ c
ream
col
oure
d
(Com
mun
ity, 2
006)
3,4
na
n
a
na
n
a
na
5
5-30
0
na
n
a
-yel
low
-col
oure
d3-5
n
a
na
2
40-1
440
1
.4-3
.6
4.1
-63
4
60-4
486
n
a
na
Tab
le 2
.8 G
iant
swam
p ta
ro c
ultiv
ar n
utri
tiona
l val
ue (E
nglb
erge
r, 20
05)
Food
Sam
ple
a N
b Ir
on
Zn
Ca
M
g P
M
n C
u
Na
K
Gia
nt sw
amp
taro
,
fana
l
e3
0.1
7 10
3 24
.7
15.5
1.
6 0.
2 52
.8
130
Gia
nt sw
amp
taro
,
mw
ashe
i
e3
0.20
4.
8 13
7 23
.7
16.7
2.
2 0.
4 46
.4
141
52
2.3.9 Conclusion Increasing soil salinity is a pressing issue that needs to be addressed, especially with
small islands where the rise in sea level is expected to cause salt water intrusion in
the island’s fresh ground water lens. Crop failure due to increased soil salinity is
reported to be an increasing problem in the Pacific region in atolls such as in Tuvalu
and Kiribati as well as in other parts of the world, where prolonged drought and
improper agricultural practices have degraded ground water quality (Toshio et al.
2005).
Giant swamp taro does have variation in their genome despite being mostly
cultivated vegetatively by farmers (Iese, 2005). Current genetic diversity of the giant
swamp taro should be preserved. It is essential to conserve cultivars, along with
proper documentation and data collection so that invaluable information about these
cultivars and the cultivars themselves will not be lost. Currently a handful of
cultivars are threatened as many of these have evolved in isolation on the islands and
are endemic. In addition, not all the cultivars are cultivated; selection is more to do
with preference of taste, use and ease of cultivation (Iese, 2005). Apart from effects
of climate change and globalization the changing preference of farmers may cause
the disappearance of some of the cultivars.
Conserving crop biodiversity is one way of preserving the genetic diversity needed
for future breeding efforts to adapt to rising soil salinity. At present the gremplasam
centres around the world are working towards conserving genetic resources and
finding solutions to the current threats to agricultural sectors. The Centre for Pacific
Crops and Trees (CePaCT) established under SPC in Fiji is one such germplasm
centre and is currently responsible for the conservation, duplication and
documentation of Pacific crops and trees including giant swamp taro.
53
Lastly, apart from being a food crop giant swamp taro, as stated earlier, has been
incorporated into the island culture and traditions, which makes this particular crop
of major significance for Pacific island nations. If it is lost they will not only lose
genetic diversity but also a big portion of their culture, traditions and part of their
identity.
This research aims to establish a rapid salt tolerance screening methodology for giant
swamp taro and to broaden its knowledge base that will prove helpful to researches
and farmers in selecting salt tolerant cultivars. This is achieved by employing in vitro
and in vivo techniques on two groups of cultivars of giant swamp taro, the larger
cultivar group Ikraoi and the smaller cultivar group Katutu. In doing so this thesis
attempts to answer questions such as “What is the current salinity of the ground
water lens of atoll islands in Tuvalu?’, ‘Is Giant swamp taro truly salt tolerant?’,
“what amounts of salinity can it tolerate’.
54
3.0 TUVALU GROUND WATER FIELD STUDY
3.1 INTRODUCTION
Atolls have come about due to ages of deposition of unconsolidated carbonate
materials on the relics of karst limestone reef, atop volcanic craters (White, 2010).
Where rainfall is adequate these Holocene deposits give rise to a freshwater lens,
known as the ‘Ghyben-Herzberg lens’ (Dunn, 1976; Rozell, 2007; Woodraffe, 1989).
In contrast, according to White (2010) the lower boundary between the fresh water
and sea water is not the more or less classical lens shape given by the ‘Ghyben-
Herzberg model’. Rather a wide transition or mixing zone where the ground water
salinity increases with depth from freshwater to seawater. A well-developed Ghyben-
Herzberg lens will have salinity that is in standard acceptance with drinking water
guidelines of the World Health Organization, which is 250mg of chloride ion per
litre of water or its respective electrical conductivity (White, 2010).
This fresh water lens is very fragile, as stated in the International Panel on Climate
Change (IPCC) 2007 assessment report (Mimura, 2007).“…Owing to factors of
limited size, availability, geology and topography water resources in small islands
are extremely vulnerable to changes and variations in climate, especially in
rainfall…”.
Figure 3.1. Giant Swamp Taro
(Cyrtosperma merkusii) or Pulaka
By Shiwangni Rao
55
Since the freshwater lens consists of a transition zone, there is some degree of
mixing taking place of sea and fresh water. However, the question is will the effects
of climate change increase this mixing, causing salt water intrusion and a resulting
rise in salinity level. In the case of Tuvalu, the people fear the country’s food
security is being greatly threatened by the effects of climate change currently and
may worsen in the future. Tuvaluan farmers suspect that salt water intrusion due to
the increase in sea level is causing the decline in their crop production. Farmers
claim taro is not able to tolerate the high salinities and dies out. However, these are
mostly assumptions by the locals, and unfortunately there has been very little
research carried out on the issue except for the study done by Webb (2007), which
gives a brief account of the ground water salinity in taro pits for a number of islands
on the nine atolls of Tuvalu, namely Nanumaga 744µS/cm, Nanumea 608µS/cm,
Niutao 471µS/cm, Nui 209µS/cm, Funafuti 3774µS/cm and Nukulaelae 1236µS/cm.
One of the local food crops that are feared of being lost due to this expected increase
in ground water salinity by the locals is the Giant swamp taro (Cyrtosperma
merkusii) or ‘Pulaka’ in Tuvaluan (Figure 3.1). Pulaka not only plays a large role in
the atoll communities’ food security system, but is also significant in their cultural
and traditional systems. The plant depends heavily on the islands’ ground water
supply, as it is cultivated in swampy areas. Manmade swamps are created digging a
big pit until the ground water is reached (Dunn, 1976; Thaman, 2002; Iese, 2005;
Manner, 2009) (Figure 3.2). In other words, the giant swamp taro is cultivated in a
window dug into the ground water lens. Considering the concerns of the farmers, if
there is an increase in the ground water salinity these taro plants may be affected.
Apart from the suspected seawater intrusion as a result of sea level rise, seawater
inundation is another threat seen by the Tuvaluans in events of natural disasters, such
as cyclones, storm surges and King Tides (Liz, 2007; Talia, 2009). For instance in
1997 waves from cyclone Keli washed over the island of Tepuka Savilivili after
which much of the island vegetation was devastated (Liz, 2007; Talia, 2009).
56
Similarly the Northern Part of Nanumaga has a history of incursions that have
damaged Pulaka pits in the area (Dunn, 1976; Webb, 2007).
Coastal erosion is another impact of climate change that poses a threat to ground
water lens. The idea that increases in sea level will result in coastal erosion causing
loss of land and decrease in the size of groundwater lens is now in question, as a
recent report by Webb and Kench (2010) argue otherwise. The study was carried out
on the aerial photography of the 27 islands in the three atoll groups of Federated
States of Micronesia, Kiribati and Tuvalu. The study shows that with the total rise in
sea level of 120mm over the last 20 - 60 years at a rate of 2 mm per year a total of
86% of the islands remained stable. A portion of this 86% actually increased in size,
thus no land was lost as where shoreline erosion took place it was equalized by
sediment deposition on the opposite side. Only 14% of the islands showed scenarios
of erosion where land was lost. White (2011) in agreement with this states that
shoreline erosion is more likely to occur due to extreme events such as king tides and
cyclones, than just the gradual rise in sea level.
Figure 3.2. Pulaka pit on Nui
Island, Tuvalu.
By Shiwangni Rao
57
However, a limitation with the study is that it looked at the pattern of shoreline
movement only within the past 2mm/yr rate of increase. With the projected increase
in rate of sea level rise and increased acidity of the sea the question raised is will
these islands still be stable in the future (Schaeffer, 2010). Also with this argument
of Webb and Kench (2010) in place, the assumptions of the fresh ground water
transition boundary being pushed inland and decreasing in size with relative land
loss is in question and needs much detailed investigation.
Apart from the possible threats imposed by climate change and sea level rise, there
are other anthropogenic factors that may be affecting the decline in Pulaka
production, which have not yet been investigated. Some of these factors include
disturbance caused by construction, population pressure, and migration of pit owners
within the atolls and abroad. Also land disputes and the fast shifting preference
towards an easier lifestyle, imported food and white collar jobs. While climate
change is a prime suspect behind the decline in crop production by the farmers, these
anthropogenic factors also contribute.
This groundwater case study builds on the study carried out by Webb (2007), where
by the salinity of ground water in Pulaka pits was measured. These pits form a
window into the ground water lens of the island. Comparison with past data will
show if any change in salinity has occurred and if it has, to what degree. These are
only snapshot values that would aid in giving a brief idea of saltwater intrusion in
Tuvalu.
58
3.2 PRE SURVEY
Salinity is normally measured in electrical conductivity (EC) values µS/cm, as salt
water conducts electricity. Giant swamp taro has been considered a salt tolerant plant
by some (Vickers; Lambert, 1982; Brandburry, 1988; Wagih, 1997; Onwueme,
1999; Kazutaka, 2003; Covich, 2006; Deenik, 2006) and not so by others (Nyman,
1983; Wagih, 1997; Webb, 2007). In his report Webb (2007) found that giant swamp
taro grew well in electrical conductivity values of 1000µS/cm and less, which is
relatively fresh water. It tolerates EC of around 2000 - 3000µS/cm that is slightly
saline while EC values of more than 3000µS/cm may be lethal to the plant (Dunn,
1976; Webb, 2007). Webb (2007) states that the response of giant swamp taro to
high salinity is likely complex and the duration and intensity of exposure play a
significant role in this. Along with the duration, factors such as shade, soil
composition, weather and planting may also contribute significantly. To fully
analyse the situation these factors need to be taken into consideration.
Webb (2007) suggested that only the islands of Funafuti, Nukulaelae and Niutao had
salinity concentrations too high for swamp taro cultivation. Funafuti holds the
highest value at 5000µS/cm, Niutao at 4000µS/cm and Nukulaelae at 3000µS/cm. Of
these three atoll islands only Funafuti showed little variation between the salinity
concentrations of the different pits which suggested that high ground water salinity
was generally consistent throughout Funafuti. For the other two islands, apart from a
few pits, the majority had low salinity concentrations suggesting that high salinity
was not constant throughout the island. The high salinity found in the Tepela area
(Central region) on Niutao may have been due to causeway construction in the area.
The rest of the islands had salinity values average ranging from 1321+/- 363 µS/cm
to 161 +/- 90 µS/cm (Webb, 2007). Also Dunn (1976) in his report noted that a pit
on Motutala Islet in Nukulaelae had weak points in the bedrock which allowed
seawater to seep into the Pulaka pits.
59
Figure 3.3. Causeway constructed
in the Tepela Pit area, thought to
have changed hydrology and
caused greater salinity in some taro
pits.
Before the salinity survey was conducted, discussions were held with the Agriculture
Minister Mr. Lausaveve and farmers on the respective islands. These discussions
shed light on some of the causes and issues facing Pulaka cultivation in Tuvalu.
Niutao is an island that appears to be at high risk of increasing ground water salinity
(Webb, 2007). Niutao is renowned for its natural swamp called the Tepela, a large
pool of organic soils which produce Pulaka of the highest quality. However, after the
construction of a dyke/ causeway (Figure 3.3), farmers noticed a rapid decline in
Pulaka yield and many later abandoned their pits. There has also been a bridge
constructed across the large pool on the island, for ease of access and this may have
disturbed salinity in the Tepela. Some farmers today are trying to revive the pulaka
production of Niutao and have started to plant in the Tepela despite the risks of low
yield. Development is slow though there seems to be progress (Nuitao Kaupule
members 2010, pers. comm.).
On the islet of Motutala in Nukulaelae the ‘Kaupule’ island council have built a
small structure to stop the seawater from affecting the Pulaka pits. While most of the
planning information associated with this construction has been lost, the acting
secretary of Kaupule, Mr. Leki described it as a burrow that reaches deep into the
By Shiwangni Rao
60
ground water lens, similar to a well, essentially a square with concrete opening
measuring 30cm x 30cm. The council had hoped that this would gather all the sea
water entering the Pulaka pit during high tide, unfortunately this construction has
been of no benefit but may have aggravated the situation (discussed further in the
discussion section).
On the islands of Nanumaga and Nanumea (Lakena islet) the situation is worse with
many of the Pulaka pits abandoned. On Nanumaga a large northern pit has been
completely abandoned with only isolated Pulaka sprouting randomly. According to
the farmers the pit soil was too saline to grow Pulaka due to waves during King
Tides that washed over and inundated the pit with sea water. Nanumea has the same
situation, but other reasons such as landowners migrating to overseas or families
having no sons to cultivate pits were also identified as reasons for abandoning giant
swamp taro cropping.
In many of these islands there is a preference for imported food such as rice, noodles,
bread, biscuits as Pulaka requires more work to cultivate and to cook. The younger
generation is shifting towards the white collar jobs and has no interest in farming.
The preference of an easier and more relaxed lifestyle may be a threat to giant
swamp taro cultivation as great as the rise in ground water salinity in Tuvalu.
During discussions with farmers it was noted that there were two groups of farmers.
There were men who have been farming all their lives and men who were retired
government workers and seaman who have returned to work on the fields. Apart
from the issues of increase in soil salinity in regards to the giant swamp taro, the loss
of traditional knowledge is also a threat to the giant swamp taro. Tuvalu has around
18 cultivars of giant swamp taro (Iese, 2005) and there are only a handful of farmers
who are aware of all these cultivars and cultivate them. For new farmers such as the
retired workers, this knowledge is limited. The knowledge to differentiate/classify
between the cultivars is diminishing and only the common ones such as the
61
‘Paipialaliga’, ‘Ikalaoi’ and the ‘Ikaulalua’ are well known and grown. The others
are greatly endangered and at risk of local extinction.
3.3 SURVEY
Of the nine islands of Tuvalu, six were studied, Nanumea, Nanumaga, Niutao, Nui,
Funafuti, and Nukulaelae. Upon arrival on the island contact was established with
the island agriculture officer and a guide was provided. Pulaka Pits were located with
the help of Webb’s 2007 study, maps from Google Earth and the guide.
The following procedures were carried out to obtain data for GPS location, ground
water salinity and general observations:
Once the pits were located, the pit location was noted on a Garmin GPS 72H
Handheld unit.
General observations were made on the pit such as:
- Plants present
- Time of sampling
- Pit health status
- If it was still in use, or left fallow
- Vegetation apart from Giant swamp taro and soil status
At a single GPS location (refer to Google maps in the result section) six salinity
measures were taken around the area randomly using a DiST 4 EC and TDS tester
(salinity meter) with an accuracy of +/-1µS/cm. The 15 cm long salinity meter was
dipped in the swamp water. Special attention was paid to keep the swamp water as
undisturbed as much possible, as this would cause mixing of the swamp water and
the data would be compromised. Once the reading stabilized on the salinity meter the
conductivity value was noted.
During these survey sessions on the various islands discussions were carried out with
the farmers regarding the pulaka cultivation and so on. Also samples for the Centre
62
for Pacific Crops and Trees (CePacT) were collected for plant genetic resource
conservation and duplication.
Data analysis was done using Microsoft Excel, Garmin device software combined
with Google earth for maps. For data analysis surface salinity values collected in this
study were compared to surface salinity values in Webb (2007) using paired T-test in
Genstat software and an α =0.05.
3.4 RESULTS & DISCUSSION
Ground water salinity measurements were taken from a number of pulaka pits
present on the six atoll islands in late July and early August, 2010. The atoll islands
have been name tagged with a yellow square on the Google earth maps. These results
were then compared and analysed against the results from the study conducted by
Webb in January to April, 2006. The same pits were sampled as in Webb (2007)
study. Since these measurements were taken only four years after Webb (2007)
study, they do not reveal a long-term trend but they are useful to indicate how
constant overtime the ground water salinity is.
3.4.1 Nanumea Nanumea lies north of Funafuti, the main island of Tuvalu. It is a small elongated
northwest-southeast running closed lagoon atoll. 12.07km in length and 2.41km in
width with a total land area of 3.24km2 (Dunn, 1976). The low lying coral atoll
accommodates a small population of 918 (Resture, 2008). The atoll group also
consists of a smaller islet Lakena that was used as shelter for the people of Nanumea
during the World War II. At present locals have chosen Nanumea as the island of
residency and Lakena as the agricultural land where they plant their pulaka and other
vegetables. Like all the other low lying atolls of Tuvalu the small islet of Lakena
which rises barely 14.02m (Resture, 2008) above sea level is also facing the threat of
63
salt water intrusion and an increase in ground water salinity. Looking at the 2006
data the highest pulaka pit/ground water salinity was found to be 761.54 µS/cm +/-
186.79 and the lowest 386.67 µS/cm +/- 366.79. While for 2010 the highest salinity
was found to be 864.33 µS/cm +/- 763.40 and the lowest was 511.67 +/-44.91
µS/cm. The average ground water salinity of the island in 2006 was found to be
607.64 µS/cm +/-136.69 and in 2010, 597.37 µS/cm +/- 165.32 (Table 3.1).
Statistical analysis of the results showed that there is no significant difference in
between the 2006 and 2010 salinity levels in Nanumea.
Nanumea was found to have high variability in the pulaka pits, at a standard
deviation of 165.32, indicating that the pits experienced a range of salinity levels.
Plants generally had diminished growth and showed heavy chlorosis on leaves
compared to healthy plants on other islands. Many of the pits have been abandoned
(Figure 3.4) and others were covered in weed. Only a handful of the pits showed
cultivation of other crops such as common taro, banana, sugarcane but these were not
at their optimum health. The soil on the island is light and poor. The pits are very
exposed to sunlight; pulaka in pits that were shaded appeared healthier than the
others. In addition, the highest salinity values lay in the region close to the small
lagoon on the island, which had a salinity value of 8330 µS/cm+/-165.32. A similar
peak in salinity is also seen in Webb’s 2006 study.
Figure 3.4.(Left) Abandoned Giant
swamp taro pit on Nanumea.
By Shiwangni Rao
64
Figure 3.5. (Right) A fully
productive pit on Nanumea,
depicting the Pulaka productivity
level that can be attained on the
island
Hence for Nanumea it can be said that the ground water salinity is well below 1000
µS/cm which is more or less fresh water. If more effort is put in cultivating giant
swamp taro the plant could likely grow quite well on the island (Figure 3.5).
Location: Nanumea - Lakena
Date: 04/08/2010
Weather: Fine
65
Map 3.1 (Top) Nanumea. Map 3.2 GPS-located Pulaka pits on Nanumea
Vaipulaka ate Faifeau
Vaipulaka a Ranford
Vaipulaka a Haumaafe & Lolua
66
Tab
le 3
.1 N
anum
ea g
roun
d w
ater
salin
ity
Pit N
ame
G
PS
Con
duct
ivity
uS/
cm
Pit A
rea
Not
es/O
bser
vatio
ns
poin
t1
poin
t 2
poin t 3
poin
t 4
poin
t 5
poin
t 6
Mea
n SD
E V
Vai
pula
ka a
Hau
mae
fa
and
Lol
ua
05 3
9’06
.5”
S 17
6 04
’39.
8”E
340
310
290
330
310
290
429
95
heal
thy
pit
with
yo
ung
plan
ts
, bu
t di
min
ishe
d gr
owth
II
05 3
9’04
.8”
S 17
6 04
’33.
3”E
380
420
400
330
570
450
aver
age
heal
th o
f p
it, w
ell
culti
vate
d
III
05 3
9’03
.8”
S 17
6 04
’33.
2”E
560
500
450
580
450
530
IV
05 3
9’02
.7”
S 17
6 04
’32.
1”E
440
530
560
420
370
490
Vai
pula
ka
a
Ran
ford
05 3
9’02
.3”
S 17
6 04
’30.
8”E
350
410
460
300
520
560
864
763
pit
is r
egul
arly
vis
ited
but
plan
ts h
ave
poor
hea
lth
II
05 3
9’01
.5”S
17
6 04
’29.
1”E
630
620
570
510
520
420
wel
l cu
ltiva
ted
plan
ts
in
good
he
alth
, di
min
ishe
d gr
owth
II
I 05
39’
01.7
” S
440
360
480
610
510
520
pit
parti
ally
cul
tivat
ed w
ith
dalo
on
ra
ised
is
land
s
67
176
04’2
8.3”
E he
alth
y pi
t
IV
05 3
9’01
.7”
S 17
6 04
’28.
3”E
810
770
930
540
760
1200
av
erag
e he
alth
of p
it
V
05 3
9’01
.4”
S 17
6 04
’25.
8”E
3090
33
30
2540
11
20
1020
10
30
poor
pit
has
lots
of
wee
d an
d so
me
suga
rcan
e
Vai
pula
ka
ate
Faife
au
05 3
9’01
.2”S
17
6 04
’25.
2”E
610
590
650
660
620
710
aver
age
heal
th o
f pi
t, so
me
bana
na p
rese
nt
II
05 3
9’00
.7”S
17
6 04
’24.
9”E
600
660
1250
48
0 15
0 63
0 62
5 21
7 po
or p
it w
ith w
eak
plan
ts
and
wee
ds
III
05 3
8’58
.7”S
17
6 04
’25.
6”E
620
620
540
450
930
480
half
the
pit i
s lef
t fal
low
IV
05 3
9’59
.9”S
17
6 04
’27.
5”E
480
610
530
560
640
520
556
59
heal
thy
pit
with
som
e ta
ro
also
V
05 3
9’00
.6”S
17
6 04
’28.
8”E
540
470
540
440
540
540
511
44
heal
thy
pit
T
otal
59
7 16
5
The
abov
e ta
ble
show
s gro
und
wat
er s
alin
ity le
vel d
ata
reco
rded
in N
anum
ea a
nd th
e ob
serv
atio
n m
ade.
Vai
pula
ka a
Ran
ford
had
the
high
est
salin
ity a
t 864
.33
µS/c
m a
nd V
aipu
laka
ate
Fai
feau
V h
ad th
e le
ast a
t 511
.67
µS/c
m. T
he m
ean
salin
ity le
vel o
n th
e isl
and
was
597
.37
µS/c
m
with
a st
anda
rd d
evia
tion
of 1
65.3
2, th
e Pu
laka
pits
on
the
islan
d w
ere
fairl
y po
or w
ith m
ost l
eft p
artia
lly fa
llow
68
Graph 3.1. Showing the mean ground water salinity levels and standard deviation bars in
Nanumea Pulaka pits, with the Vaipulaka a Ranford with highest recording and Vaipulaka a
Haumaefa and Lolua with the lowest.
Graph 3.2. Comparisons of the mean ground water salinity levels and standard deviation
bars of 2006 data (Webb, 2007) for each of the respective pulaka pits.
3.4.2 Nanumaga Running North-South, Namugama is an oval shaped reef island approximately 3.62
Km long and 1.61 Km wide with a land area of about 3.24Km2 (Dunn, 1976). Dunn
(1976) in his report stated that the people of Nanumaga claimed the Northern pit on
the island was completely washed by sea water, rendering it unproductive and people
0
500
1000
1500
2000
Vaipulaka a Haumaefa
& Lolua
Vaipulaka a Ranford
Vaipulaka ate Faifeau
Unknown 1 Unknown 2
Elec
tric
al C
ondu
ctiv
ity (μ
S/cm
)
Pulaka Pits
Pulaka pit salinity on Nanumea 2010
-400 -200
0 200 400 600 800
1000 1200 1400 1600
Vaipulaka a Haumaefa
& Lolua
Vaipulaka a Ranford
Vaipulaka ate Faifeau
Unknown 1 Unknown 2
Elec
tric
al C
ondu
ctiv
ity (μ
S/cm
)
Pulaka Pit
Groundwater salinity on Nanumea
2010
2007
69
stopped planting. The pit recorded salinity values of 47000 and 30000 µS/cm (Dunn,
1976). Dunn concluded that the salts in the pit were highly mobile moving in and out
with the tide and as such he suggested that the pulaka plants were victims of ground
water salinity and not soil salinity.
Nanumaga is a single island with a large lagoon in the middle; this particular island
has been identified as one of the islands with serious salinity issues by Mr.
Levusevu. The northern pit ‘Vaipulaka I Tokelau’ was found deserted. At the time of
the survey the pit had a salinity measure of only 530 µS/cm which is quite fresh. The
pit had a few remnant pulaka growing and appeared quite healthy. In the rest of the
pits which are located at the southern end of the island the highest salinity recorded
was 550 µS/cm+/- 44.2. In 2006 the highest pulaka pit salinity was found to be
1665µS/cm+/-304.06 with the mean ground water salinity of the island 744.28
µS/cm+/-5.48 and 473.33 µS/cm+/- 115.9 in 2010 (Table 3.2). Overall there was no
statistical significant difference found between the 2006 and 2010 ground water
salinity level.
The soil on the island is dark and relatively rich in organic matter (this could be a
result of good mulching and composting in the past). There were lots of crop species
apart from giant swamp taro growing in the pits such as banana and breadfruit trees
which were all healthy and so were the pulaka plants in the pits. Vegetation such as
breadfruit trees is generally intolerant to saline conditions. The presence of these in
the pits is an indicator that the island has long profited from the good ground water.
Hence overall the island ground water status has improved since the washing over by
the king tides and the island at the time of this study can support a healthy flora. But
as stated by Dunn (1976) salinity moves with the rise and fall of tides hence at high
tides salinity may increase if high water ever occurs again. The southern pits which
are not as vulnerable to the tides as the northern pits had less variability compared to
2006 suggesting the salinity level at the time of the study was stable.
70
Location: Nanumaga
Date: 04/08/2010
Weather: Fine
Map 3.3 Nanumaga. Map 3.4 GPS located Pulaka pits on Nanumaga
Vaipulaka I Toga
Pit II Vaipulaka I Tokelau
N
71
Tab
le 3
.2 G
roun
d w
ater
salin
ity o
n N
anum
aga
Pit N
ame
G
PS
Con
duct
ivity
uS/
cm
Pit A
rea
Not
es/O
bser
vatio
ns
Poin
t 1
poin
t 2
poin
t 3
poin
t 4
poin
t 5
poin
t 6
Mea
n SD
E V
Vai
pula
ka
I T
okel
au
06 1
6’34
.3”S
17
6 19
’21.
7”E
490
510
550
540
520
570
530
28
Pit
has
been
ab
ando
ned
for
quite
so
me
time,
co
vere
d w
ith
wee
ds
and
som
e pu
laka
gr
owin
g w
ildly
an
d ar
e he
alth
y V
aipu
lak
a I T
oga
06 1
8’00
.5”S
17
6 19
’14.
7”E
300
370
350
310
350
360
340
28
heal
thy
Pit
with
so
me
Ban
ana
also
pre
sent
II
06
17’
59.8
”S
176
19’1
1.1”
E 59
0 50
0 56
0 51
0 53
0 61
0 55
0 44
he
alth
y Pi
t
T
otal
47
3 11
5
The
abo
ve ta
ble
depi
cts
the
mea
n gr
ound
wat
er s
alin
ity le
vels
of N
anum
aga
and
the
othe
r re
late
d ob
serv
atio
n. T
he h
ighe
st g
roun
d w
ater
salin
ity w
as r
ecor
ded
at 5
50 μ
S/cm
whi
le th
e lo
wes
t was
at 5
30 μ
S/cm
. The
Isla
nd’s
mea
n sa
linity
was
foun
d to
be
473.
33 μ
S/cm
with
a
stan
dard
dev
iatio
n 11
5.90
. Exc
ept f
or th
e Va
ipul
ak I
Toke
lau
pit t
he o
ther
two
pits
wer
e he
alth
y w
ith a
num
ber o
f oth
er fo
od c
rops
apa
rt fr
om
pula
ka.
72
Graph 3.3. Showing the mean ground water salinity levels and standard deviation bars of
Nanumaga Pulaka pits, with Pit 5 having the highest recording and Vaipulaka I Toga with
the lowest.
Graph 3.4. A comparison of the 2006 mean ground water salinity levels (standard deviation
bars) (Webb, 2007) and the 2010 salinity values of each pulaka pit on Nanumaga, pit II
showing the greatest decrease in the salinity values
0
100
200
300
400
500
600
700
Vaipulak I Tokelau Vaipulak I Toga II Elec
tric
al c
ondu
ctiv
ity μ
S/cm
Pulaka Pit
Pulaka Pit Salinity on Nanumaga 2010
0
500
1000
1500
2000
2500
Vaipulak I Tokelau Vaipulak I Toga II
Elec
tric
al c
ondu
ctiv
ity μ
S/cm
Groundwater Salinity in Nanumaga
2010
2007
73
3.4.3 Niutao The atoll has a rectangular shape running in the east-west direction approximately
2.41 Km in length and 1.21 Km in width with a total land mass of 2.43 Km2 (Dunn,
1976). Niutao has a large natural swamp ‘Tepela’ that was a favourable spot for
Pulaka farming in the past. However the dyke construction appears to have
aggravated ground water salinity problems. Many of the farmers and officials infer
this to be the result of the dyke construction that spiked increase in the pit salinity
level some years ago (Dunn, 1976; Webb, 2007).
Today many of the ‘Kaupule’ members and the farmers have started to plant in the
Tepela area again, hoping to revive the land and get it back to its old productivity
potential (Figure 3.6). Looking at the data gathered in 2006 the ground water salinity
in the Tepela area measured up to a 2450 µS/cm+/- 1098.12 and at present it sits at
1460 µS/cm+/- 860.98 (Table 3.3). Apart from the dyke/Causeway construction, a
bridge has also been constructed to allow people to cross the large central lake
without having to go around. Once again this large construction relative to the small
island size may have contributed to changes in salinity levels of the island as
explained above.
Figure 3.6. The Tepela area where pulaka
is being once again cultivated in hope of
reviving the plantation.
As seen from graph 3.6, highest ground water salinity on the island is 1500 µS/cm
+/- 860.98, which lies well in the fresh ground water zone of 1500-2500 µS/cm.
Statistical analysis of the 2006 and 2010 ground water salinity levels showed there is
no significant difference between the two readings.
By Shiwangni Rao
74
Despite the relatively fresh ground water in the pulaka pits on Niutao, the pits were
not being used up to its potential productivity, meaning the pits were poorly
cultivated, but growing reasonably well. It was observed that the plants in the shady
regions or on the shady outskirts of the pits were growing better than those plants
exposed to full sunshine. Apart from pulaka vegetation other crops such as
breadfruit, banana and sugarcane were also growing quite well in this area.
Location: Niutao Date: 05/08/2010 Weather: Fine
Map 3.5 (Top) Niutao. Map 3.6 (Bottom) GPS located Pulaka pits on Nanumag
Lololuli
Talo Sualiki
Matakakaka
Vaipulaka Lasi
Tepela
Pua Te Talo
75
Tab
le 3
.3 P
ulak
a pi
t sal
inity
on
Nui
tao
Pit N
ame
G
PS
Con
duct
ivity
uS/
cm
Pit a
rea
Not
es/O
bser
vatio
ns
poin
t1
poin
t 2
poin
t 3
poin
t 4
poin
t 5
poin
t 6
Mea
n SD
EV
Vai
pula
ka
Las
i 06
06’
41.9
”S
177
20’3
2.5”
E 58
0 44
0 43
0 11
70
630
450
616
283
poor
pi
t pl
enty
w
eeds
an
d pl
ants
no
t in
op
timum
hea
lth
Tep
ela
06 0
6’38
.1”S
17
7 20
’33.
2”E
450
1190
20
50
2060
24
80
530
1460
86
0 av
erag
e he
alth
of p
it
Pua
te
talo
06
06’
43.4
”S
177
20’4
9.6”
E 19
30
350
460
330
410
410
648
629
plen
ty w
eeds
Lol
ouli
06 0
6’29
.4”S
17
7 21
’01.
5”E
560
620
390
400
550
440
493
95
aver
age
pit,
som
e su
gar
cane
als
o pr
esen
t on
pit
Tal
o Su
alik
i 06
06’
45.1
”S
177
21’0
1.0”
E 66
0 53
0 44
0 47
0 52
0 51
0 52
1 75
av
erag
e pi
t
Mat
akak
a 06
06’
42.0
”S
177
20’9
2.8”
E 55
0 63
0 54
0 43
0 42
0 49
0 51
0 79
he
alth
y pi
t
T
otal
70
8 37
3
The
abov
e ta
ble
show
s the
reco
rded
gro
und
wat
er sa
linity
leve
l of N
iuta
o. T
he h
ighe
st gr
ound
wat
er sa
linity
was
foun
d to
be
at th
e Te
pela
are
at 1
460
µS/c
m w
hile
Mat
akak
a ha
d th
e lo
wes
t at 5
10 µ
S/cm
. The
mea
n is
land
gro
und
wat
er sa
linity
was
foun
d to
be
708.
33 µ
S/cm
with
a
stan
dard
dev
iatio
n of
373
.47.
76
Graph 3.5. The above graph shows mean ground water salinity levels (with standard
deviation bars) of Nuitao in the various Pulaka pits. The Tepela has the highest salinity level
while Lolouli and Matakakaka share the lower values
Graph 3.6. Graph showing the comparison of mean ground water salinity levels (with
standard deviation bars) between 2006 (Webb, 2007) and 2010 data, with the Tepela pit
showing a decrease in the salinity level while the rest show an overall increase.
0
500
1000
1500
2000
2500
Vaipulaka Lasi
Tepela Pua te talo
Lolouli Talo Sualiki
Matakaka
Elec
tric
al c
ondu
ctiv
ity μ
S/cm
Pulaka Pit
Pulaka Pit Salinity on Niutao 2010
0 500
1000 1500 2000 2500 3000 3500 4000
Elec
tric
al c
ondu
ctiv
ity μ
S/cm
Pulaka Pit
Ground water Salinity in Niutao
2010
2007
77
3.4.4 Nui Nui is another island with healthy pits, and also a rich Pulaka diversity. Thirteen
cultivars of pulaka can be found on this island, and the tradition of pulaka farming is
very much alive. Running North-South the small island has an elongated oval shape,
8.05 km in length and 3.22 km width with a total landmass of 3.24km2 (Dunn, 1976).
Ground water salinity was found to be 610.28 µS/cm+/- 250.55 in 2010 and 209.2
µS/cm+/-169.89 in 2006, (Table 3.4). Statistical analysis of the 2006 and 2010
ground water salinity showed that there was no significant difference between the
two readings. Also ground water salinity level in Nui was found to be well within the
fresh water zone.
Location: Nui
Date: 23/07/2010
Weather: Fine
78
Map 3.7 (Top) Nui. Map 3.8 (Bottom) GPS located Pulaka pits on Nui.
Tabontebike
Vaipulaka Lasi
Pit 5
Vaipulaka Foliki
Vaipulaka ate Faifeau
79
Tab
le 3
.4 P
ulak
a pi
t sal
inity
on
Nui
Pit N
ame
GPS
C
ondu
ctiv
ity u
S/cm
Pit a
rea
Not
es/O
bser
vatio
ns
poin
t1
poin
t 2
poin
t 3
poin
t 4
poin
t 5
poin
t 6
Mea n
SDE
V
Tab
onte
pik
e 07
14’
26.5
”S
177
08’5
3.6”
E 70
0 67
0 45
0 65
0 68
0 49
0 60
6 10
7 D
alo
grow
n on
rai
sed
isle
ts.
No
othe
r cr
op, h
alf
fallo
w f
ield
. Soi
l da
rk a
nd l
oam
y in
nat
ure.
Pit
is
exte
nsiv
ely
expo
sed
to su
nlig
ht
Vai
pula
ka
Las
i I
07 1
4’31
.9”S
17
708’
50.5
”E
520
510
530
490
520
550
720
37
left
fallo
w a
s no
com
post
pre
sent
an
d lo
ts o
f wee
d. H
as b
anan
a an
d br
eadf
ruit
trees
w
hich
no
t at
op
timum
he
alth
. So
il m
ainl
y ca
lcar
eous
and
pit
expo
sed
II
07
14’
32.2
”S
1770
8’51
.6”E
64
0 68
0 70
0 71
0 64
0 67
0
he
alth
y pi
t
III
07 1
4’33
.6”S
17
708’
57.7
”E
980
1190
16
90
1300
15
30
1030
le
ft fa
llow
, hi
gh
chlo
rosi
s on
le
aves
of p
lant
s
IV
07 1
4’34
.1”S
17
708’
58.7
”E
400
420
390
430
400
380
heal
thy
pit
Vai
pula
ka
Folik
i
07 1
4’39
.7”S
17
708’
55.4
”E
600
570
630
530
620
660
601
42
heal
thy
pit
but
ther
e w
as
not
muc
h w
ater
pr
esen
t to
do te
stin
g
80
Vai
pula
ka ate
Faife
au
07 1
4’39
.0”S
17
708’
55.1
”E
780
750
720
690
760
800
636
56
heal
thy
pit
II
07 1
4’36
.8”S
17
708’
54.1
”E
580
540
450
570
490
510
heal
thy
pit
Pit 5
07
14’
35.4
”S
1770
8’54
.8”E
47
0 49
0 42
0 50
0 45
0 43
0 48
5 68
po
or p
it, lo
ts o
f wee
d pr
esen
t and
no
wor
k se
ems t
o be
don
e on
it
II
07 1
4’36
.2”S
17
708’
54.6
”E
530
540
540
570
550
490
heal
thy
pit
III
07 1
4’36
.5”S
17
708’
54.6
”E
580
460
340
380
570
430
has b
een
left
fallo
w
T
otal
61
0 25
0
The
abov
e ta
ble
show
s th
e gr
ound
wat
er s
alin
ity le
vels
on N
ui. T
he h
ighe
st gr
ound
wat
er s
alin
ity w
as r
ecor
ded
at 7
20.8
3 µS
/cm
in V
aipu
laka
Lasi
I w
hile
the
low
est w
as re
cord
ed in
Pit
5 at
485
.56
µS/c
m. T
he m
ean
grou
nd w
ater
salin
ity w
as fo
und
to b
e 61
0.28
µS/
cm w
ith a
stan
dard
devi
atio
n of
250
.55
81
Graph 3.7. Mean ground water salinity levels (with standard deviation bars) of Pulaka pit
on Nui showing low variability with Vaipulaka Lasi having the highest value and Pit 5 with
the lowest.
Graph 3.8. The above graph depicts a comparison of the mean ground water salinity levels
(with standard deviation bars) of 2006 (Webb, 2007) and 2010 salinity values on Nui, the
values show and overall increase in salinity except for Pit 5.
0
200
400
600
800
1000
1200
Tabontepike Vaipulaka Lasi I
Vaipulaka Foliki
Vaipulaka ate Faifeau
Pit 5
Elec
tric
al c
ondu
ctiv
ity μ
S/cm
Pulaka Pit
Pulaka Pit Salinity on Nui 2010
0
200
400
600
800
1000
1200
Tabontepike Vaipulaka Lasi I
Vaipulaka Foliki
Vaipulaka ate Faifeau
Pit 5
Elec
tric
al c
ondu
ctiv
ity μ
S/cm
Pulaka Pit
Ground water Salinity in Nui
2010
2007
82
3.4.5 Funafuti The capital island of Tuvalu, Fongafale is the longest and the narrowest of all the
nine atoll islands in the archipelago. It is a North-south running oval shaped atoll
with a total landmass of 2.43 Km2 (Dunn, 1976). The high ground water lens is the
product of the limited landmass of the islands. That makes this ground water lens
highly vulnerable to any form of pollution, construction and earthworks and
environmental change such as changes in rainfall and temperature. Fongafale having
Funafuti as the capital has over the years experienced much construction of buildings
and houses (Dunn, 1976; Webb, 2007).
Funafuti has survived bombing and military upheaval of World War II and the
associated earth works and construction of the island airstrip. Funafuti is struggling
to keep its pulaka cultivation culture alive with limited resources.
Figure 3.7. Very healthy pulaka plants that
grow in Funafuti.
The pulaka plantations area is clustered in the centre of the island where according to
Ghyben-Herzberg principle (Rozell, 2007) (Woodraffe, 1989) the ground water is
the deepest. However farmers claim that the daily tides do have a noticeable impact
on the plants suggesting that the islands ground water lens may be shallow.
Fongafale happens to have the highest recorded ground water salinity levels (Table
3.5, Graph 3.9) compared to the other islands of Tuvalu. The highest salinity
recorded in 2010 was 14790 µS/cm+/-1020.27 compared to 6570 µS/cm+/- 678 in
By Shiwangni Rao
83
2006 giving a difference of 162 % in the ground water salinity, for the highest
recorded salinity. The island has experienced a mean 79 % increase in the ground
water salinity having an overall average of 6749 µS/cm +/- 3703.14 in 2010
compared to the 3774 µS/cm+/- 1749.94 in 2006 (Table 3.7). There is a significant
difference in the mean ground water salinity levels between 2006 and 2010 (p=0.04).
This high salinity in Fongafale is in agreement with Webb (2007) in citing Falkland
(1999) where it has been stated that ground water salinity levels are too high for
human consumption and use. Also that Funafuti virtually has no fresh ground water
lens present due to the course material constituents of the island.
Webb (2007) states that pulaka has been seen to tolerate up to 2000 µS/cm but dies
out at 3000 µS/cm which in comparison to the recorded 14790 µS/cm is quite low.
Looking at the high salinity values for Funafuti in both the 2006 and 2010 survey it
is a possibility that pulaka in fact does have high salt tolerance or salinity tolerance
has been induced in the plants over the number of years of high ground water
salinity. Furthermore, table 3.5 shows that Pulaka is quite healthy in the pit of
highest salinity level 14790µ S/cm+/-1020.27 (Figure 3.7) and according to the
farmers on Funafuti a particular cultivar the ‘Pulaka Kula” seems to show higher
tolerance in comparison to other cultivars (Figure 3.8).
Apart from this, some other factors that may be affecting the survival of these plants
could be the amount of rainfall and evapotranspiration rate. However the above
stated factors biological and climatic are only assumptions of the possibilities and
needs a detailed investigation.
Figure 3.8 Pulaka Kula, one of the cultivars of
Giant swamp Taro found on Funafuti claimed to be
salt tolerant by farmers.
84
Location: Funafuti- Fongafale
Date:19/07/2010 and 27/07/2010
Weather: Fine
Map 3.9 (Top) Fongafale atoll. Map 3.10 (Bottom) GPS located Pulaka pits on Funafuti,
Fongafale.
Southern Pit
Central Pit t
Northern Pit
85
Tab
le 3
.5 P
ulak
a pi
t sal
inity
on
Funa
futi
Pit
Nam
e G
PS
Con
duct
ivity
µS/
cm
Pit A
rea
Not
es/O
bser
vatio
ns
poin
t1
poin
t 2
poin
t 3
poin
t 4
poin
t 5
poin
t 6
Mea
n SD
VE
Sout
hern
pi
t
08 3
1’26
.8’S
17
9 11
’45.
1”E
7880
82
90
7800
81
30
7950
78
90
7990
.00
18
4.07
av
erag
e he
alth
of p
it, h
ighl
y ex
pose
d to
sunl
ight
, not
muc
h w
ater
in p
it
08 3
1’27
.5’S
17
9 11
’45.
5”E
2240
23
40
1540
19
70
2370
17
80
2040
.00
33
5.08
po
or p
it, lo
ts o
f wee
d
08 3
1’27
.8’S
17
9 11
’45.
1”E
4640
47
80
4880
47
50
4830
47
20
4766
.67
84
.30
poor
pits
with
hal
f lef
t fal
low
an
d so
me
othe
r veg
etat
ion
like
bana
na a
nd b
read
frui
t.
08 3
1’28
.0’S
17
9 11
’46.
1”E
1250
42
40
1350
41
90
1380
12
70
2280
.00
14
99.7
1
poor
pits
with
hal
f lef
t fal
low
an
d so
me
othe
r veg
etat
ion
like
bana
na a
nd b
read
frui
t.
Cen
tral
pi
t
08 3
1’17
.5’S
17
9 11
’53.
0”E
1434
0 16
130
1390
0 14
950
1580
0 13
620
1479
0.0
0 10
20.2
7
Ver
y he
alth
y pi
t, al
so h
as a
la
rge
num
ber o
f ban
ana
plan
ts.
loca
ted
clos
e to
hou
sing
wel
l at
tend
ed
08 3
1’17
.8’S
17
9 11
’53.
0”E
9810
10
660
1043
0 52
20
6230
75
80
8321
.67
23
09.7
0
heal
thy
pit,
soil
has a
no
ticea
ble
amou
nt o
f whi
te
calc
areo
us so
il
08 3
1’20
.1’S
17
9 11
’52.
4”E
8340
81
70
8500
78
00
4030
24
90
6555
.00
26
08.7
3 sm
all h
ealth
y pi
t, w
ith a
lot o
f ba
nana
tree
s
86
08 3
1’24
.8’S
17
9 11
’47.
9”E
1080
0 91
20
6130
67
20
5610
87
00
7846
.67
20
14.4
8 V
ery
heal
thy
pit,
loca
ted
in a
ve
ry sh
ady
area
08 3
1’23
.7’S
17
9 11
’45.
0”E
1105
0 11
300
1003
0 11
130
1133
0
1096
8.0
0 53
7.14
po
or p
it, e
xpos
ed to
sunl
ight
co
nsta
ntly
08 3
1’26
.0’S
17
9 11
’46.
6”E
8730
96
00
6770
13
130
9557
.50
26
59.5
4 he
alth
y pi
t loc
ated
too
clos
e to
pi
gger
y
Nor
ther
n pi
t 08
31’
16.4
’S
179
11’5
4.3”
E 46
00
3810
63
20
5000
41
00
5630
49
10
946
very
hea
lthy
pit,
loca
ted
clos
e to
hou
sing
wel
l atte
nded
08 3
1’15
.9’S
17
9 11
’53.
6”E
3190
24
90
2740
28
20
2310
25
60
2685
30
6
Hal
f of t
he p
it is
thor
ough
ly
culti
vate
d w
hile
the
othe
r is l
eft
fallo
w. W
ell e
xpos
ed to
su
nlig
ht, n
o co
mpo
stin
g pr
esen
t at t
he ti
me
of v
isit.
Lo
amy
soil.
08 3
1’17
.0’S
17
9 11
’52.
6”E
5090
54
20
5270
56
00
3900
48
50
5021
60
7 A
vera
ge h
ealth
of p
it w
ell
com
post
ed.
Tot
al
6748
37
03
Th
e ab
ove
tabl
e sh
ows
the
reco
rded
dat
a of
the
grou
nd w
ater
sal
inity
and
the
obse
rvat
ions
mad
e on
Fun
afut
i. Th
e hi
ghes
t sal
inity
w
as fo
und
in th
e So
uthe
rn p
it at
147
90µS
/cm
whi
le th
e lo
wes
t was
foun
d in
the
cent
ral p
it at
228
0 µS
/cm
. The
mea
n gr
ound
wat
er
salin
ity w
as fo
und
to b
e at
674
8.63
µS/
cm w
ith a
stan
dard
dev
iatio
n of
370
3.14
.
87
Graph 3.9. Mean ground water salinity levels (with standard deviation bars) on Funafuti,
with one of the central pit s with highest value and southern pit with the lowest. Funafuti has
the highest ground water salinity values compared to the rest of the islands.
Graph 3.10. The above graph is a comparison of the mean ground water salinity levels
(with standard deviation bars) of 2006 (Webb, 2007) and 2010 data of ground water salinity
values on Funafuti showing an overall increase in the ground water salinity levels on the
island.
0 2000 4000 6000 8000
10000 12000 14000 16000
Southern pit Central pit Northen pit Elec
tric
al C
ondu
ctiv
ity μ
S/cm
Pulaka Pit
Pulaka Pit Salinity on Funafuti 2010
0
2000
4000
6000
8000
10000
12000
14000
16000
Southern pit Central pit Northen pit
Elec
tric
al c
ondu
ctiv
ity μ
S/cm
Pulaka Pit
Ground water Salinity in Funafuti
2010
2007
88
3.4.6 Nukulaelae Nukulaelae consists of 14 islets of which Fangaua is the chosen residential island
while another significant island Motutala is used for pulaka cultivation. This atoll is
11.26 Km long and 4.02 Km wide with a total land area of approximately 1.6 Km2
(Dunn, 1976). Pulaka cultivation takes place on the southern end of the island and on
another smaller islet. Motutala has natural swamps present such as those found in the
Tepela area on Niutao. The people of Nukulaelae have put in place a small structure
to prevent salt water from entering the pulaka pits. Unfortunately this construction
does not address the issues of ground water lens in fact it might have disturbed the
transition zone of the fresh ground water lens and the sea water.
From the data gathered it was found that there was no significant difference in the
ground water salinity levels measured in 2006 and 2010. 2010 ground water salinity
levels ranged from 8530 µS/cm+/- 1681.62 to 725 µS/cm+/- 114.85, with a mean
ground water salinity of 2823.39 µS/cm+/- 2606.54. While in 2006 survey recorded
the highest value as 2446 µS/cm+/- 1072.51 and the lowest at 398.57 µS/cm+/-
369.11 with mean ground water salinity at 1235.58 µS/cm+/-783.09. Webb (2007) in
his survey found that the pit, Viapulaka mataafale on Nukulaelae had extremely high
salinity unlike the rest of the salinity values which rested well between 444+/-378 to
908+/- 384 µS/cm. Looking at the 2010 data the Vaipulaka a Toe pit on Nukulaelae
has elevated salinity followed by Vaipulaka Mataafale. Except for the two pits
Vaipulaka a toe and Vaipulaka ite Fakai the rest of the values fall below the 2006
salinity levels or just slightly above.
89
Location: Nukulaelae
Date: 11/08/2010
Weather: Cloudy
Map 3.11 (Top) Nukulaelae atoll. Map 3.12 (Bottom) GPS located Pulaka pits on Motutala
Islet, Nukulaelae. Map 3.13 (next page) GPS located Pulaka pits on Nukulaelae main islet.
90
Vaipulaka ite Fakai
Vaipulaka a Uputaua
Vaipulaka I mataafale
Vaipulaka a Toe
91
Tab
le 3
.6 P
ulak
a pi
ta sa
linity
on
Nuk
ukla
elae
Pit N
ame
G
PS
Con
duct
ivity
uS/
cm
Not
es/
Obs
erva
tions
poin
t1
poin
t 2
poin
t 3
poin
t 4
poin
t 5
poin
t 6
Mea
n SD
EV
Nuk
ulae
lae
V
aipu
laka
a
toe
9 22
”36.
31”S
17
9 48
”38.
74”E
10
410
9550
90
60
8060
55
20
8580
85
30
1681
av
erag
e pi
t
Vai
pula
ka a
U
puta
ua
9 22
”37.
33”S
17
9 48
”38.
12”E
11
10
1480
13
70
1790
11
50
1440
99
0 45
1
II
9 22
”39.
26”S
17
9 48
”37.
69”E
62
0 66
0 69
0 53
0 52
0 53
0
Vai
pula
ka I
mat
aafa
le
9 22
”27.
52”S
17
9 48
”31.
44”E
74
0 88
0 56
0 64
0 81
0 72
0 72
5 11
4
Vai
pula
ka
ite F
akai
9
22”1
8.65
”S
179
48”2
9.46
”E
2620
23
90
3160
32
00
2970
31
70
2918
33
8
Mot
utal
a Is
let
V
aipu
laka
I M
otul
ata
9 21
”02.
81”S
17
9 48
”59.
59”E
11
10
780
720
740
790
1160
95
2 16
1 H
ealth
y pi
t
II
9 22
”05.
03”S
17
9 48
”59.
91”E
87
0 86
0 88
0 84
0 86
0 88
0
III
9 22
”06.
49”S
17
9 48
”38.
74”E
11
90
1160
11
70
1040
10
20
1080
av
erag
e pi
t
Tot
al
2823
26
06
Th
e ta
ble
abov
e is
the
colle
cted
dat
a on
pul
aka
pit s
alin
ity o
n N
ukul
aela
e an
d ot
her o
bser
vatio
ns. T
he h
ighe
st sa
linity
was
foun
d in
th
e Va
ipul
aka
a to
e at
853
0 µS
/cm
and
the
low
est i
n Va
ipul
aka
I mat
aafa
le a
t 725
µS/
cm. T
he m
ean
grou
nd w
ater
sal
inity
of t
he
isla
nd w
as fo
und
to b
e 28
23.3
9 µS
/cm
with
a st
anda
r dev
iatio
n of
282
3.39
.
92
Graph 3.11. The above graph depicts the mean ground water salinity levels (with standard
deviation bars) in the Pulaka pit on Nukulaelae, Vaipulaka a toe with the highest salinity
values and Vaipulaka Mataafale with lowest.
Graph 3.12. Comparison of the mean ground water salinity levels (with standard deviation
bars) of 2006 (Webb, 2007) and 2010 data of the ground water salinity levels on Nukulaelae
showing an overall increase in the salinity levels with Vaipulaka a Toe with the highest
recorded increase.
0.00
2000.00
4000.00
6000.00
8000.00
10000.00
12000.00
Vaipulaka a toe
Vaipulaka a Uputaua
Vaipulaka I mataafale
Vaipulaka ite Fakai
Vaipulaka I Motutala El
ectr
ical
con
duct
ivity
μS/
cm
Pulaka Pit
Pulaka pit salinity on Nukulaelae 2010
0.00
2000.00
4000.00
6000.00
8000.00
10000.00
12000.00
Vaipulaka a toe
Vaipulaka a Uputaua
Vaipulaka I mataafale
Vaipulaka ite Fakai
Vaipulaka I Motutala
Elec
tric
al c
ondu
ctiv
ity μ
S/cm
Pulaka Pit
Ground water Salinity In Nukulaelae
2010
2007
93
3.4.7 Rainfall- Ground Water Recharge Rainfall plays a significant role in the recharge of the ground water lens. The Tuvalu
Metrological Centre based in Funafuti, records weather data for Funafuti only. Data
obtained from the Tuvalu Metrological Centre shows that the mean rainfall for the
duration of the study was 118+/- 76mm in Funafuti. While average rainfall for the
2006 study was 294+/- 150mm, giving an overall 59.94 % difference (Table 3.7).
Meaning that at the time of survey for the 2006 study there was more rainfall
compared to the present 2010 survey in Funafuti, this is one factor that can result in
lower salinity values for 2006 compared to 2010.
Table 3.7 Comparison of average rainfall for 2006 and 2010
Month Mean Rainfall SDEV Monthly Rainfall Average - 2006 January 383 170 February 393 189 March 407 196 April 59 133 May 231 124
Total 294 150 Monthly Rainfall Average - 2010 July 172 86 August 64 48
Total 118 76
Average monthly rainfall record for the duration of study in 2006 (Webb, 2007) and
2010 with their calculated standard deviation.
94
3.4.8 Tuvalu Ground Water Salinity There was no significant difference in ground water salinity levels in Tuvalu
between 2006 and 2010 (p=0.18). However, looking at the six islands separately
Funafuti had significant difference at α=0.05 in the ground water salinity levels
between the 2006 and 2010 readings. Nanumea and Nanumaga experienced seawater
inundation according to the locals caused by cyclones and king tides over the years.
However, rainfall since these events has resulted in recovery of the fresh ground
water lens. However, it is likely that if another wave event inundates these pits they
will again become saline.
Nui and Nukulaelae also have ground water salinity values that are within the
boundaries of fresh water to mildly brackish. For Nukulaelae having its ground water
salinity values falling within the mildly brackish zone is largely due to the effects of
two pits, the rest of the pits have salinity values in the fresh water range. Funafuti
which has the highest ground water salinity places it in the brackish water range. It
also has the only increase in ground water salinity between 2006 and 2010 with the
mean ground water salinity of 6749 µS/cm+/-3703.14 and an overall increase of
78.83 %.
Although Funafuti has brackish ground water giant swamp taro is still persisting on
Funafuti, ranging from very healthy to very poor pits. Funafuti gives an interesting
opportunity to investigate the apparently high salinity tolerance level of Pulaka here,
as the island not only has brackish ground water but the soil present on the island is
fairly poor as well.
In Niutao, the Tepela area was subjected to heavy construction and earthworks
following which the island had an elevated level in the Tepela ground water salinity
and the pits in the area became unproductive. Tepela area had the highest salinity
values above the standard fresh water limit of 1500-2500 µS/cm (Webb, 2007). The
rest of the recorded values fell in the fresh water zone.
95
While this survey has given a glimpse of the status of ground water salinity in
Tuvalu, showing that there was no change in ground water salinity except for one
island between 2006 and 2010. Further monitoring and research is needed, as this
change accounts only for ‘snap-shot’ measurements made at two points in time 2006
and 2010. Continuous monitoring of ground water salinity levels would enable a far
better understanding of the relationship between salinity and other important
variables such as tide, weather, storms and rainfall to be developed.
Table 3.8 Comparison of 2006 and 2010 ground water salinity levels
Island 2006 2010 F probability
Nanumea 608+/- 137 597+/-165 1.00
Nanumaga 744+/-634 473+/-116 0.25
Niutao 471+/-947 708+/-373 0.44
Nui 209+/-170 610+/-251 0.13
Funafuti 3774+/-1750 6749+/-3820 0.02
Nukulaelae 1236+/-783 2823+/-2606 0.63
The above table contains the islands average (total all pit means divided by total number of pits) salinity and the f probability of statistical difference on the islands surveyed
96
G
raph
3.1
3. G
roun
d w
ater
salin
ity le
vels
in th
e si
x isl
ands
of T
uval
u, F
unaf
uti h
avin
g th
e hi
ghes
t sal
inity
leve
ls fo
llow
ed b
y N
ukul
aela
e N
iuta
o
and
so o
n.
-200
0 0
2000
4000
6000
8000
1000
0
1200
0
1400
0
1600
0
Nan
ume
Nan
umag
a N
iuta
o N
ui
Funa
futi
Nuk
ulae
lae
Electrical Conductivity μS/cm
2010
Gro
undw
ater
Sal
inity
leve
l in
Tuva
lu
97
0
2000
4000
6000
8000
1000
0
1200
0
1400
0
1600
0
Vaipulaka …Vaipulaka a Ranford
Vaipulaka ate Faifeau Unknown 1 Unknown 2
Vaipulak I Tokelau Vaipulak I Toga
II
Vaipulaka Lasi Tepela
Pua te talo Lolouli
Talo Sualiki Matakaka
Tabontepike Vaipulaka Lasi I Vaipulaka Foliki
Vaipulaka ate Faifeau Pit 5
Southern pit
Central pit
Northen pit
Vaipulaka a toe Vaipulaka a Uputaua
Vaipulaka I mataafale Vaipulaka ite Fakai
Vaipulaka I Motutala
Nan
umea
N
anum
aga
Niu
tao
Nui
Fu
nafu
ti N
ukul
aela
e
Electrical conductivity (μS/cm)
Loca
tion
Com
paris
ion
of 2
006
& 2
010
Gro
und
wat
er sa
linity
leve
ls
2010
2007
Gra
ph 3
.14.
Com
paris
on o
f the
200
6(W
ebb,
200
7) a
nd 2
010
data
for a
ll th
e Pu
laka
pits
on
all t
he is
land
s, w
ith F
unaf
uti h
avin
g th
e hi
ghes
t
salin
ity m
easu
res f
ollo
wed
by
Nuku
lael
ae
98
3.5 CONCLUSION
Giant swamp taro (Cyrtosperma merkusii) or Pulaka cultivation is a very strenuous task, it
requires much care and attention and takes time to grow, but if well attended the plant can still
be grown in many areas in Tuvalu. It is interesting to note the apparent high salinity tolerance
of cultivars grown in Funafuti.
Residents fear the rise in sea level will lead to a rise in ground water salinity. However, there
are other factors that contribute to increase in salinity. These are human induced factors such
as construction, earthworks, population pressure, and development pressure (engineering,
ground water pumping, etc.). Factors which may exacerbate saline intrusion include natural
disasters and rainfall variability.
Furthermore, as seen from the discussions with the local farmers, high ground water salinity is
not the sole reason for the decreased pulaka production in Tuvalu. Other contributing factors
exist such as land issues, presence of a male farmer in the family, migration, the preference of
modern food due to its accessibility and convenience, or the general desire for a modern
lifestyle and social status. These factors have a significant impact on the traditional framing
throughout the Pacific and Tuvalu is no exception.
As seen from the results ground water salinity levels have shown no significant difference in
Nanumea, Nanumaga, Nui, Niutao and Nukulaelae. Funafuti recorded a significant increase in
ground water salinity between 2006 to 2012. Except for Funafuti and Nukulaelae the rest of
the islands have ground water salinity level fall below the limit of fresh water zone of 1500-
2500 µS/cm (Webb, 2007). On the other hand, with the factors affecting this salinity it is hard
to say that if this difference in ground water salinity would persist, decrease or increase even
further.
99
Solving the issue of increasing ground water salinity presents major obstacles; Tuvalu has
small islands with small land masses which results in small and fragile ground water lens that
can be easily disturbed. Engineering methods to protect the fresh ground water lens would be
very costly and not likely to be successful.
While at the moment there is no perfect solution to the issue of ground water salinity, food
security on the island can be supported by sustainable use of agro-biodiversity. Evaluating the
different cultivars of pulaka will provide farmers with the information as to variation in
salinity tolerance. However before they can evaluated, they must be conserved.
A holistic approach to agro biodiversity includes:
- Promoting cultivation of all the cultivars and encouraging farmers to plant as many
cultivars of pulaka as possible
� Competitions that promote the diversity of local food crop.
� Agricultural programs that aid farmers by promoting local food crops
� Solving land issues and allocating land to farmers
� Exchange of cultivars with other countries in the Pacific
- Traditional knowledge conservation involves conserving all the knowledge in relation
to giant swamp taro such as cultivation, preparation, recipes, traditional usage and
values. Also includes myths legends, stories, songs, poems, cultivars of giant swamp
taro, how to differentiate between cultivars, its harvest time and its maturity age.
Conservation using traditional knowledge entails:
� Documentation
� Exchanging traditional knowledge possibly through workshop programs
� Passing the knowledge to the younger generations by the elders
100
� Incorporating the knowledge in the school curriculums
� Awareness through competitions, posters, broadcasting, workshops and speeches.
Furthermore, one of the scientific approaches to addressing the threat to food security in
Tuvalu and the other Pacific atoll islands in the region is development of a salt tolerant
cultivar of giant swamp taro. There is an urgent need to develop this particular crop as salt
tolerant, not only to ensure food security but also the preservation and conservation of the
atoll communities’ culture, tradition and identity.
As a final point, to find the perfect solution the problem has to be perfectly understood.
Ground water salinity and its resulting effect on pulaka production, needs more exhaustive
investigation to be fully understood. As it’s a complex phenomenon and research into the
plant physiology and plant-soil relation is required to determine the physical and biological
aspects involved in pulaka growth.
101
4.0 DEVELOPMENT OF A RAPID IN VITRO SCREENING
METHOD VERSUS IN VIVO SCREENING
4.1 INTRODUCTION
Screening for potential salt tolerance traits in giant swamp taro cultivars presents a door of
opportunity for developing a buffer to the effects of climate change and sea level rise. In vitro
testing allows giant swamp taro cultivars that show salt tolerance in situ such as the Pulaka
Kula to be screened and fully utilized. It is also faster than conventional methods and is not as
expensive or complex as the DNA marker assisted screening methods. Investigating screening
methodologies such as these, present the best way forward into understanding the dynamics of
island ecology and solving the big problems, small islands and countries such as Tuvalu face.
The development of a screening methodology for salinity tolerance included the evaluation of
different salinity levels, the nature of the salt solution applied and the method of application.
Two types of salt solutions were used, the standard NaCl that is used in salinity screening
experiments and the Artificial Sea Water (ASW) to mimic the effects of sea water inundation
and ground water lens intrusion. This experiment was conducted on two group of giant
swamp taro cultivars from Kiribati, namely the larger cultivar group ‘Ikaraoi’ and the smaller
‘Katutu’.
4.2 METHOD
As the available planting material was limited, different accessions of the same group of
cultivars were combined, namely accessions CM/KB 05 and 06 for Ikaraoi and CM/KB 9 and
10 for Katutu. These accessions were obtained from the Secretariat of the Pacific Community
(SPC), Centre for Pacific Crops and Trees (CePaCT). These accessions were imported by
CePaCT from Kiribati in 2009. Suckers were prepared for importation by trimming the plant
to 10x10cm at the acaulescent stem where the petiole and corm fused of which 5cm is corm.
102
The trimmed suckers were washed thoroughly with water, dead plant tissues removed and
then tightly wrapped in paper and sealed in cartons for import. Upon arrival these suckers
were trimmed and a meristem of 0.5cm removed for initiation. This meristem was then
washed in 70% ethanol for one minute, followed by 10% bleach for 10 minutes, and then 5%
bleach for 5 minutes and finally sterile water twice for 15 minutes. After this sterilization
process the meristem was then cultured on solid basal MS (Murashige and Skoog, 1962)
media of pH around 5.6-5.8. The accessions were selected based on the number of plants
available.
4.2.1 Multiplication The initial number of plants obtained from the SPC-CePaCT, were multiplied to obtain the
desired number of plants for the in vitro and in vivo testing this began in April, 2010.
Multiplication/ bulking-up were achieved using taro tissue culture multiplication technique
established by CePaCT. The methodology consists of a three step cycle whereby plantlet (of
at least 1.5cm height) initiation is carried out in agar basal MS (Murashige and Skoog, 1962
with 30g/L sugar). After a standard three to four weeks of initiation the plantlet was
transferred to MS medium containing 0.50mg/L thidiazuron (TDZ). Then after another three
to four weeks of culture the plants were transferred to MS medium containing 0.80 mg/L 6-
benzylaminopurine (BAP). This procedure effectively increased the number of plants
available for experimentation in three months at an average of 30% increase per month on the
initial number. All transfers of plant material were done in a Laminar airflow cabinet using
sterilized forceps and scalpel. Each plant was removed and cleaned by removing dead and old
plant tissues then the plants were trimmed down to a height of 3cm with 0.5cm corm attached.
After cleaning the plants were subcultured into growth medium; care was taken to avoid
unnecessary movement and therefore contamination. After multiplication the in vitro
experiment began in August, 2010.
103
4.2.2 In Vitro Five different levels of salinity were tested namely 0.5% (5ppt), 1.0% (10ppt), 1.5% (15ppt)
and 2.0% (20ppt) salt plus the control, 0% (0ppt) salt. These salinity levels were based on the
salinity level giant swamp taro has been seen to tolerate which is up to 5ppt and the extreme it
would have to encounter in cases of seawater inundation which may be up to 20-30ppt. Two
types of salt solution were compared in this experiment, namely Artificial Sea Water (ASW)
and Sodium Chloride (NaCl) salt solution. For the ASW, the different salinity levels under
evaluation were prepared from a stock solution. While the NaCl solutions were made directly
from pure NaCl. ASW was used as one salt solution, as a substitute for sea water in an
attempt to be more representative of the atoll situation where intruding sea water is the cause
of ground water salinity increment. The ASW was prepared by adding 13.96g of NaCl, 0.39g
KCl, 2.25g MgSO4 .7H2O and 3.80g MgCl2 to 100ml double distilled water (Nyman, 1983).
Aliquots from this ASW stock were used to make the various salinity concentrations. For the
NaCl solutions, salt was weighed respectively and added to double distilled water (Table 4.1).
This ASW recipe is based on the four major salts found in sea water, namely sodium chloride,
potassium chloride, magnesium sulfate and magnesium chloride.
Application of these salt solutions was carried out in two ways. With the first approach salt
solutions were added to the medium as it was prepared and then autoclaved. With the second
approach salt solutions were applied to the top of the medium right after the plants had been
subcultured on to medium (Figure 4.1). Plants of at least 3-4cm height were used for the in
vitro experiment.
104
Figure 4.1 In vitro Experiment treatment combination structure
Table 4.1 Salt solution mixtures
Salinity ppt % salinity NaCl ASW Stock
5 0.50% 5g/L 5ml/L
10 1.00% 10g/L 10ml/L
15 1.50% 15g/L 15ml/L
20 2.00% 20g/L 20ml/L
cultivars treated with
the 5 salinity levels
Type of salt
solution
solution application
In vitro multiplic
ation
adding salt
solution while
making medium
NaCl Ikaraoi
Katutu
ASW Ikaraoi
Katutu
adding salt
solution after
subculturing
NaCl Ikaraoi
Katutu
ASW Ikaraoi
Katutu
105
Once prepared, the salt solutions were added to the medium according to the two methods
described, namely, either mixed with the basal MS (Murashige and Skoog, 1962 with 30g/L
sugar) then autoclaving at 1.05kg/cm2 (15psi) and 121ºC, or applied to the autoclaved medium
after it has been prepared. For the latter, 5ml of each salt solution was pipetted into separate
6cm x 2cm tin screw cap glass bottles, which were autoclaved and the salt solution in it was
added on top of the basal MS after subculturing. For both approaches liquid MS (without
agar) with a pH of approximately 5.6-5.8 and 6cm x 7cm glass bottles with polycarbonate
screw lids were used.
The control for the two experiments was the same 0% salt containing basal MS. Plants were
subject to salinity treatments on an incremental basis with intervals of 0.5% salt (ASW /
NaCl) per week, until the final salinity levels was reached. This prevented the plants from
suffering shock due to a sudden increase in salinity. The salinity increments were applied in a
staggered fashion so that once the final salinity level was reached for each treatment the
duration of that treatment would be the same (Table 4.2). For example for the 2.0% salt
treatment, culture in 0.5% salt increment started in week one and continued until week 4.
While for the 1.5% salt treatment salinity the increment started on the second week and
continued for three weeks whereby it reached its final salinity level in the fourth week.
Similarly for 1.0% salt treatment, salinity applications began in the third week and ended in
the fourth week (Table 4.3). Plants were subcultured into fresh media for each incremental
increase of 0.5% using the two salt solution application approaches.
106
Table 4.2 Salinity increment
weeks Final Salinity %
1 2 3 4
0.5% 0.5% 0.5% 0.5% 2.0
0.5% 0.5% 0.5% 1.5
0.5% 0.5% 1.0
0.5% 0.5
0
For each treatment combination, five replicates were prepared (Table 4.3). Plants were placed
out randomly in blocks according to replicate number. The experiment proper began after
each treatment had reached the desired salinity level and was conducted for eight weeks. The
in vitro experiment cultures were kept in CePaCT’s growth room, illuminated for 16 hour
photoperiods with Gro Lux tube lights at a light intensity of 4.4mW cm-2 and 25+/-2ºC room
temperature. Plant response to the various salinity treatments was evaluated by taking
morphology measurements on a weekly basis, namely plant height, number of leaves
emerging, number of suckers emerging, corm size, root size and number of dying leaves. The
initial and final plant weights were measured at the beginning and at the end of the eight week
experimental period. The toxicity of the salinity levels was assessed by measuring the
chlorophyll content of leaves at the end of the experiment. Number of contamination (fungal
and bacterial colonies) on individual plant cultures was also recorded during the eight week
experimental period.
107
Table 4.3 In vitro experimental design
Method Cultivar Group
Treatment T1 0%salt (0g/L)
T2 0.5%salt (5g/L)
T3 1%salt (10g/L)
T4 1.5%salt (15g/L)
T5 2.0%salt 2(0g/L)
NaCl (M1)
Ikaraoi 5 5 5 5 5 Katutu 5 5 5 5 5
no. of plants 10 10 10 10 10 NaCl (M2)
Ikaraoi 5 5 5 5 5 Katutu 5 5 5 5 5
no. of plants 10 10 10 10 10 ASW (M1)
Ikaraoi 5 5 5 5 5 Katutu 5 5 5 5 5
no. of plants 10 10 10 10 10 ASW (M2)
Ikaraoi 5 5 5 5 5 Katutu 5 5 5 5 5
no. of plants 10 10 10 10 10 Total plants per treatment 40 40 40 40 40 Total plants = 200
4.2.3 In Vivo Plants were subjected to five different levels of salt, namely 0.5%, 1.0%, 1.5%, 2.0% plus the
control 0% salt (Figure.4.4). As with the in vitro method artificial sea water was used to
mimic sea water as closely as possible. Plants were potted in 50 10x10cm black pots which
stood in saucers to avoid run-off of the applied salt solutions. Pots were filled with 250 mL of
Yates’s advance seedling common potting mix and CePaCT’s procedure for transferring the
tissues cultured plants into the pots was followed. This included washing the growth medium
gently off the plants ensuring that no part of the plant was damaged. The plants used in this in
vivo experiment were at least 6cm in size from the base to the apex of the plant when removed
108
from the tissue culture bottles. The plants were firmly planted in the pots and a clear plastic
bag was used to cover the plants to allow them to acclimatize to the environment and prevent
shock and dehydration. Plastic bags were removed progressively over a one month period. For
example plastic bags were removed for an hour the first day, the following day they were
removed for two hours and so on until it was completely removed. Plants were watered with
40ml of tap water three times a week. From the time of transfer into the pots, the plants were
kept in a shaded green house in the CePaCT at approximately 25+/-2ºC and after three months
transferred to a typical green netted green house at approximate temperature of 27+/-2 ºC. In
this green house plants were watered with 50ml of tap water three times a week. Plants were
allowed to acclimatize for another month in this green house, and then 50ml of salt solution
was applied on an incremental basis of 0.5% salt per week for four weeks. The experiment
was carried out for two months after the five months of transfer and acclimatization phase of
the plants.
Table 4.4 In vivo Experimental Design
Cultivar Group
Treatment
T1 T2 T3 T4 T5
0% salt
(0g/L)
0.5% salt
(5g/L)
1.0% salt
(10g/L)
1.5% salt
(15g/L)
2.0% salt
(20g/L)
Katutu 5 5 5 5 5
Ikaraoi 5 5 5 5 5
no. of plants per
treatment 10 10 10 10 10
Total no. of
plants 50
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4.2.4 Evaluation Parameters For both the in vitro and the in vivo experiments the effects of the treatments were assessed
mainly on the morphology of the plant except for the chlorophyll content measurement. The
morphological traits assessed were height, number of leaves emerging, the number of suckers
emerging, the corm size, root size and number of leaves dying. These traits were measured
weekly, while weight was measured monthly due to the low degree of change. The
chlorophyll content was measured at the end of the experiment. Contamination rates for the in
vitro plants were assessed weekly to determine the effectiveness of method of application.
Parameters such as height, corm size and weight were measured with a ruler or weighed on a
bench top scale. For the in vitro tissues, measurements were taken from outside the culture
bottles as both the liquid media and bottle are transparent and removing the plants would have
caused contamination and plant death. Height was measured from the tip of the tallest leaf to
the base of the petiole/stem, where corm growth begins. Corm was measured from the base of
the petiole/stem, where corm growth begins to the corm base. Measurement of the roots was
more difficult unlike that of plant height and corm size, as roots tended to coil in the small
culture bottles, once they grew beyond 3cm. Hence roots were measured from base to root tip
until they became too coiled to be measured in which case estimates of length were recorded.
A digital bench top scale was used for weight measurements. The average weight of a culture
bottle with the required media was subtracted from the weight of the culture bottles with
media and plant, to obtain the actual plant weight at an accuracy of +/-0.001g.
The criteria used for counting an emerging leaf were when a leaf’s full leaf blade length
(though not fully opened) became visible. When visually estimated leaves displayed 50%
chlorosis, the leaf was counted as dead. The number of suckers was recorded if a sucker
measured at least 0.5cm in length from base to tip. Contamination was recorded when spots of
fungal or bacterial growth became visible at a colony diameter of 1-2mm.
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4.2.4.1 Chlorophyll Content
After two months of exposure to the various treatments, leaves were analysed for chlorophyll
content. 1 gram of leaf was soaked for 2 minutes in 5 ml of 80% acetone (80 ml acetone plus
20 ml distilled water). This was done to soften the leaves and allow for easy extraction of the
chlorophylls. After two minutes the acetone was drained and the leaves ground using a mortar
and pestle with 2 ml of 80% acetone. The extracted juice of 1.5 ml was then centrifuged in a
micro centrifuge at 8000 revolutions per minute for 15 minutes at 5 °C. The supernatant was
then transferred using a micropipette into a cuvette. The chlorophyll content was determined
by measuring absorbency at two wavelengths Abs 664 and Abs 647 in spectrophotometer.
The spectrophotometer was first loaded with the blank or controls (80% acetone) then the
other supernants were loaded and readings recorded. After each reading the cuvettes were
rinsed with 80% acetone twice and once with the next supernant that was to be loaded; this
prevented contamination of the supernetants from the residue left in the cuvettes.
From this reading chlorophyll content was calculated by;
Total Chlorophyll (µg/ml/g) = [7.04(Abs 664)+20.27(Abs 647)] x V/W
V= volume of the leaf extract (ml)
W = fresh weight of leaf (g)
4.2.5 Data Analysis The data was analysed using the Genstat statistics software and SPSS. The total plant
response and the two cultivar group responses were compared against the five salinity levels
using ANOVA followed by a Tukey’s post hoc test and liner regression analysis for the in
vitro and in vivo. This included measurements of plant height, number of leaves, and number
of suckers, root size, corm size, and number of dying leaves, weight and chlorophyll content.
111
A non-parametric Mann Whitney U (Wilcoxon rank sum) test was used to analyse the number
of fungal contaminations recorded with the two methods of salinity application to the growth
medium for the in vitro.
For the in vivo a percentage survival analysis was also done looking at the number of plants
that were alive when the experiment ended.
4.3 RESULTS
Plants can tolerate up to 2.38 ppt of salt which is mildly brackish water, anything above 2.38
ppt maybe fatal (Munns and Tester, 2008). This experiment tested 0% , 0.5%, 1.0%, 1.5% and
2.0% salt concentration which translate to 0 ppt, 5 ppt, 10 ppt, 15 ppt and 20 ppt of salt
concentration. This is in line with sea water that has a salinity level of 35-36 ppt. As stated
earlier giant swamp taro Cyrtosperma merkusii has been reported to tolerate salinities slightly
more than 2 ppt (Webb, 2007) however, until now there have been no specific investigations
carried out to confirm this.
4.3.1 In Vitro Comparisons were done of the different salinity levels, the nature of the salt solution applied
and the method of salt solution application. These comparisons were done in respect to the
two cultivar groups individually and combined. A 100% survival rate was recorded for the
range of salinity levels tested, whether using NaCl solution or ASW.
For the in vitro salt tolerance screening experiments, plants were replanted to a new medium
on a weekly basis for three weeks to allow for the incremental increasing of the salinity levels
until the treatment level was attained. In addition, no water is lost to the environment outside
the culture bottles in an in vitro system; hence plants were subjected to constant salinity
levels.
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4.3.1.1 Cultivar Group Response
To assess the plant response of the two groups of cultivars Analysis Of Variance (ANOVA)
was employed as this allowed the incorporation and accountability of the various factors
affecting the experiment. For example, in this particular case the two cultivar groups were
assessed in their response to the five salinity levels. Their individual response to the five
salinities was compared for significant difference that may exist. For the two groups tested in
the experiment, their response of biomass and toxicity was analysed this showed that, no
significant difference existed in majority of the tested parameters. Tukey’s post hoc analysis
was carried out on those parameters that did show significant difference. Table 4.5 shows the
result of the analysis that indicates that significant difference existed randomly between
salinity levels. Tukey’s post hoc analysis showed the Ikaraoi mean difference in corm size of
1.5% salt was higher in comparison to 0% and 0.5% salt, followed by 2% salt in comparison
to 0% salt (p<0.05). Also the mean difference of 2% salt was significantly more than 0.5%
salt for number of dying leaves. For Katutu significant differences existed in height where
0.5%salt showed a higher significant difference in mean than 0% salt. 1% salt showed higher
mean difference in number of suckers and corm size compared to 0% salt. For weight 0.5%
salt had a higher mean difference compared to 1.5% salt (p<0.05).
Table 4.5 Mean of cultivar group measured parameters when subjected to the five
salinity levels. Values are mean+/-standard error of 20 replicates. Mean values in each
column not sharing a common letter differ significantly (p<0.05) from each other (Tukey’s
Post Hoc test)
Katutu
% Salt Height No. Suckers Corm Size Weight 0 -0.78+/-0.28a 0.80+/-0.17a 0.82+/-0.09a -0.42+/-0.05ab 0.5 0.33+/-0.23b 1.45+/-0.31ab 0.87+/-0.08ab -0.16+/-0.11ab 1 -1.95+/-0.23ab 2.7+/-0.39b 1.28+/-0.11b -0.20+/-0.21ab 1.5 -0.63+/-0.28ab 2.00+/-0.44ab 1.12+/-0.13ab -0.24+/-0.19ab 2 -0.17+/-0.2ab 2.00+/-0.44ab 1.11+/-0.13ab -0.33+/-0.08a
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F 3.79 3.73 0.249 2.49 df 99 99 95 99 p 0.007 0.007 0.034 0.048 Ikaraoi %salt Corm Size No. Dying leaves 0 0.74+/-0.05a 2.6+/-0.11ab 0.5 0.93+/-0.09ab 1.7+/-0.24b 1 1.08+/-0.12ac 2.0+/-0.25ab 1.5 1.36+/-0.11c 2.4+/-0.28ab 2 1.21+/-0.12bc 2.7+/-0.25a F 5.79 3.14 df 90 99 p 0 0.018
4.3.1.2 Plant Response
As for the combined response of the varieties, from table 4.6 it can be seen that for the eight
measured parameters for biomass and toxicity only plant height, number of suckers and corm
size show significant difference (p<0.05). Further analysis through Tukey’s test showed that
for height 0.5% salt had higher mean difference compared to 0% salt followed by 1.5% salt
(p<0.05). While for number of suckers 1% salt had more suckers followed by 1.5% salt , then
2% salt in comparison to 0% salt (p<0.05). For corm size 1.5% salt had the highest mean
difference compared to 0% and 0.5% salt, followed by 1% and 2% salt compared to 0% salt.
To see if these significant difference in mean show any significant trend a liner regression
analysis was carried out. This showed that height and root had no significant trend, while
number of suckers, corm size and number of dying leaves showed an increase with increase in
salt concentration (Graph 4.1, 4.2, 4.3).
The number of suckers increased with increases in salinity levels from 0 to 2% in both ASW
and NaCl, similar to the results achieved by Abdel-hardy in 2006. Munns and Tester (2008)
114
outline the benchmark of salt tolerance in plants in two stages, tolerance of osmotic stress and
tolerance of ionic stress. According to them tolerance to osmotic stress is achieved when
plants are able to produce new leaves in response to increased salinity levels, while ionic
tolerance is achieved when plants do not have early senescence of leaves. The experiment
showed that in the presence of salinity levels up to 2% salt or 20 ppt plants were able to
produce suckers and increase corm size with the trade-off of a nonlethal decrease in number
of leaves content. Elimination of old leaves and emergence of new suckers may be a means of
salt tolerance strategy for giant swamp taro. By eliminating old leaves where NaCl
accumulates to toxic levels and investing in new suckers that have young leaves which are
expanding and hence diluting NaCl concentrations (Munns and Tester, 2008) the plant
reduces its net NaCl concentration. This is similar to the results achieved by Nyman (1983)
where the taro callus was pale yet the callus produced leaves and survived.
The experiment had a 100% survival rate at all salinity concentrations with no prominent
wilting. This is in line with the bench mark of salinity tolerance in plants by Munns and
Tester (2008) which indicates that in vitro both the Ikaraoi and the Katutu group of cultivars
were able to survive salinity levels of up to 2% salt which is approximately 56% sea water.
The above response of plants to the various salinity levels is also in line with Zhu (2001) of
plants exhibiting salt tolerance; according to him plants respond to increased salinity by
detoxification, homeostasis and growth regulation. ROS which is produced in the chloroplast,
under salt stress conditions damages the photosynthetic apparatus, enzymes and cellular
membrane, detoxification is seen in the in vitro experiment as the plants under these
conditions were able to photosynthesis and produce new suckers. Plants also did not show
wilting which indicates that salt ions did not accumulate to a toxic level, hence exhibiting
homeostasis. Also, with no reduction in height and emerging of new suckers the plants
showed good growth regulation. These positive responses to the salt levels tested has also
been seen in salt tolerance screening of salt tolerant plants by Fatokun et al (2002) in cowpeas
and in wild einkom wheat by Yesayan et al (2009) and Colmer et al (2006) .
115
Table 4.6 Mean of plant response measured parameters when subjected to the five
salinity levels. Values are mean+/-standard error of 40 replicates. Mean values in each
column not sharing a common letter differ significantly (p<0.05) from each other (Tukey’s
Post Hoc test)
%Salt Height No. Suckers Corm Size Root Size No. Dying leaves
0 0.29+/-0.17a 0.70+/-0.13a 0.78+/-0.05a 3.64+/-0.18a 2.5+/-0.01ab 0.5 0.49+/-0.17b 1.35+/-0.24ab 0.90+/-0.6ab 2.76+/-0.22b 1.9+/-0.18b 1 0.15+/-0.15ab 1.9+/-02.8b 1.18+/-.08bc 3.12+/-0.25ab 2.2+/-0.18ab 1.5 0.17+/-0.17a 1.8+/-0.31b 1.24+/-0.08c 3.14+/-0.24ab 2.45+/-0.17ab 2 0.33+/-0.15ab 1.78+/-0.26b 1.15+/-0.08bc 3.45+/-0.22ab 0.99+/-0.15a F 1.09 3.89 6.91 2.36 3.66 df 199 199 186 186 199 p 0.002 0.005 0.000 0.055 0.007
Graph 4.1 shows significant positive trend in number of suckers in relation to salt concentrations in liner regression analysis
variety=CM910
Fitted and observed relationship
variety=CM56
0
-0.5
6
4
2
2.01.5
7
3
5
1
1.00.50.0
% salt
variety=CM910
variety=CM56
116
variety=CM910
Fitted and observed relationship
variety=CM56
4
2
0
2.01.5
3
1.0
5
1
-0.5 0.50.0
% salt
Graph 4.2 shows
significant positive
trend in corm size and
salt concentrations in
liner regression
analysis.
Graph 4.3 shows
significant positive
trend in number of
dying leaves and salt
concentrations in liner
regression analysis.
variety=CM910
variety=CM56
variety=CM910
variety=CM56
variety=CM910
Fitted and observed relationship
variety=CM56
2.0
1.0
0.0
2.01.5
1.5
1.0
2.5
0.5
-0.5 0.50.0
% salt
117
4.3.1.3 Comparison of Salt Solutions Applied
NaCl which is the most common and abundant salt (Arzani, 2008) was tested against artificial
sea water which is the main source of salt in the rise of the ground water salinity levels in the
small atoll islands (White and Falkland, 2010). Despite the difference in the two salts
constituents both had the same impact on the plants (Table 4.7).
This similarity of plant response to NaCl and ASW may be due to the percentage of the
constituent salts present in the artificial seawater. NaCl dominates the constituents of seawater
as it makes up an average 68.43% of the salts present in it. While the other salts namely
calcium chloride, magnesium chloride and potassium chloride form a small fraction (Bedjaian
and Loukhovitskaya, 2011). This high percentage of NaCl and its ions Na+ and Cl- are the
most detrimental of the four major salts present in sea water (Arzani, 2008), hence NaCl
would have had the most impact. Consequently the NaCl used in isolation and the NaCl
present in the artificial seawater which is 80.6% of its total molecular weight, would have
similar impact on the plants, as such either ASW or NaCl can be used in a salt screening
experiment without compromising the experiment.
Table 4.7 Plant Response to ASW and NaCl
Parameter f
Probability
Mean
ASW NaCl
Height 0.61 0.11+/-0.16 0.05+/-0.16
no. leaves 0.51 12.09+/-0.15 1.99+/-0.15
no. suckers 0.26 1.86+/-0.27 1.55+/-0.27
corm 0.21 1.08+/-0.09 0.97+/-0.09
root 0.23 2.72+/-0.25 3.02+/-0.25
No. dying leaves 0.88 2.36+/-0.17 2.34+/-0.17
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Weight 0.46 -0.42+/-0.12 -0.51+/-0.12
chlorophyll content 0.48 15.71+/-1.71 14.48+/-1.71
With respect to the two salt solutions tested ASW and NaCl, table 4.7 summarizes the ANOVA results
of the response plants had to the two types of salt solutions (ASW and NaCl) applied in the various
concentrations. The table also shows the f probabilities of the measured parameters.
4.3.1.4 Comparison of the Method of Salinity Application
Use of tissues culture and in vitro techniques requires great care as the cultures can be easily
contaminated and as a result die out. Therefore, in any screening methodology conducted in
vitro it is essential that proper techniques such as subculturing and solution application be
critically analysed to avoid contamination and loss of samples. This experiment tested two
approaches to the salt (ASW and NaCl) solution application; the first approach was direct
application of the salt solution to the medium while mixing, followed by autoclaving. The
second approach was salt solution application to the medium following subculture of the plant
in the medium. Within the duration of the experiment a total of four contaminations were
recorded where salt solution was mixed in medium and 14 contaminations where salt solution
was applied from on top after subculturing. The contaminations were mainly white fungus
that appeared on the medium; the fungus initially present as spots grows and covers the plant
resulting in deteriorated plant health and death.
Where salt solution was applied from “on top” there is significantly more contamination
compared to where solution was “made with media”. A total of 77.8% more contamination
results when salt solution was poured from on top after subculturing at significance of
statistical difference of 0.013. Post hoc analysis could not be carried out as there are only two
groups for comparison (Table.4.8).
The second approach allows for human handling errors to occur increasing the chance of
contaminants to enter the culture. In the first approach the salt solution is already added to the
119
medium which is then sterilized, after which plants are subcultured onto the medium. In the
second approach, plants are subcultured into the prepared medium and then the salt solution is
poured on top. This requires extra movement and increases the time window during which the
nutrient rich medium is exposed to the outside atmosphere in the Laminar airflow and hence
the increased contamination rate. Thus mixing testing solutions with the medium during
preparation is a safer approach that does not compromise the experiment samples or the
results.
Table 4.8 Contamination Rate according to application method
Application of Solution Contamination
Approach 1 ( salt solutions mixed with media) 4
Approach 2 (salt solutions poured from on top after subculturing) 14
Significance probability 0.013
4.3.2 In Vivo In vivo treatments were planned to be conducted for eight weeks. However, after three weeks
the plants were affected by the salinity and started to die, hence the experiment was concluded
and results recorded. Due to the approach used in the building up to the final salinity level
only the first four treatments were established with 2% omitted. Of the four salinity treatments
1% and 1.5% had zero percent survival hence limited parameters were available for
measurement such as the number of leaves emerging, rooting, dying leaves and chlorophyll
content. There were no significant measurements available for height, corm, and weight due
to the premature conclusion of the experiment and no suckers had emerged in the short period
of time. This was the same for all the four treatments.
120
Unlike in vitro, the plants in the in vivo did not grow so well. After a successful
acclimatization phase of four months in the green house, plants were not able to tolerate the
salinity levels. From the second week of the incremental phase plants started to wilt with
heavy chlorosis of leaves, by the third week of the increment phase plants had died out. This
allowed only three increments to occur, the highest being 1.5% salt. Therefore the final
salinity levels tested in vivo were 0%, 0.5%, 1.0% and 1.5%. Artificial seawater was used as
the salt solution, to mimic the actual scenario faced by giant swamp taro on the atoll islands.
Conducting experiments in vitro allows control over the environmental factors such as
temperature, light, heat and moisture. While with in vivo experiments in the green house,
these factors cannot be controlled, leaving plants exposed to the elements of nature (Munns
and James, 2003). The green house was located in an elevated area where it was quite windy;
however one side of the green house was against an excavated hill, shielding it form the wind
and sun. In the first week it was noticed that plants on this shielded side were fresher and had
water remaining in their saucers while plants on the side exposed to wind and sun were not.
Water loss due to evaporation and transpiration is one of the factors that might have resulted
in the low survival rate of the plants in the green house. Evaporation and transpiration reduces
the amount of water in the pots and moisture in the soil, resulting in an increase in the initial
salt concentrations. Table 4.9 reports the salinity levels measured in the pots at the end of the
experiments which shows a significant increase in the salt concentrations from the applied
0.5% to 1% , from the applied 1% to 3% and from 2% to 5% salt.
Table 4.9 Pre and post experiment salinity levels
Pre salinity % Post salinity % The table shows the pre salinity percentage which is the initial salinity levels applied to the plants and the post salinity percentage which is the salinity level recorded from the pot saucers or effluent after the experiment.
0 0
0.5 1
1 1.5
1.5 1.5
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Furthermore, in vitro plants are subjected to optimum conditions such as temperature, light
intensity, wave length and duration (Hughes, 1981). While in vivo, plants are exposed to
variable temperatures, humidity, light intensity and duration (Arzani, 2008). In an in vitro
culture complex reactions with temperature, heat, light and growth medium result in a gaseous
phase in the culture bottles (Hughes, 1981). An in vivo system lacks this and instead the
porous soil gives greater surface area to volume ratio for evaporation to take place. All of
these factors not only add to water loss from plant and soil, but also affects the physiological
mechanisms operating to maintain plant ionic and osmolic homeostasis (Zhu, 2001).
Looking at the 100% survival rate of the control where no salt was applied it can be seen that
the plants had successfully acclimatized, hence salinity application before plants could
acclimatize can be ruled out as a cause of the low survival rate. After the application of the
three salinity levels plant health started to deteriorate resulting in death, as can be seen by the
60% survival rate in 0.5% salt and the zero percent survival rate of 1.0% and 1.5% salt (Table
4.10). This was the same for both the cultivars and when combined the same results were
achieved for the overall plant response (Table 4.12).
4.3.2.1 Cultivar group response
Since the plants of the 1.0% and 1.5% salt had died out analysis was done on the control as
“no salt” to the 0.5% salt as “salted”. Comparison of the two cultivar groups showed that they
both had the same response to the applied salinity levels of 0% and 0.5% salt (Table 4.10).
There was no increase in corm size or production of suckers in any of the treatments for either
of the cultivars in the three weeks, thus these parameters were not evaluated. Of the four
evaluated parameters of number of leaves, rooting size, number of dying leaves and
chlorophyll content, none recorded f probabilities less than 0.05. Indicating that, none of the
evaluated parameters of the two group of cultivars have any significant difference. Both had
the same response to the salinity levels tested. This similarity in response also stands with
their rate of survival when subjected to the increased levels of salinities. Both the cultivars
122
have the same response to the subject salinity levels with 100% survival at 0% salt,
decreasing to 60% survival at 0.5% and 0% survival rate at 1.0% and 1.5% salt (Table 4.11).
Table 4.10 Cultivar group response to the salinity levels
Parameter f probability Ikaraoi Katutu
No. Leaves 0.437 2.23+/-0.69 2.28+/-0.71
Root 1 1.750+/-0.47 1.75+/-0.47
dying leaves 0.681 3.9+/-0.79 3.7+/-0.82
Chlorophyll 0.828 20.26+/-1 22.26+/-1
The above table is the summary of the calculated ANOVA values with comparison of the two
cultivar groups Ikaraoi and Katutu. It has the f probabilities or the probability of any
significant difference of the number of leaves, rooting, and number of dying leaves and
chlorophyll content of the two cultivar groups.
Table 4.11 Percentage survival rate of the two group of cultivars
Cultivar group % salt no alive no. dead % survival
Ikaraoi 0 5 0 100
0.5 3 2 60
1 0 5 0
1.5 0 5 0
Katutu 0 5 0 100
0.5 3 2 60
1 0 5 0
1.5 0 5 0
The above table represents the percentage survival rate of the five replicate of the two group
of cultivars Ikaraoi and Katutu to the various salinity levels
123
4.3.2.2 Plant response
With a f probability of less than 0.05, rooting size, number of leaves emerging and number of
leaves dying has significant differences in the response to the two salinity levels. Number of
leaves emerging and number of leaves dying increases with increase in salinity, while rooting
decreases. Roots in the 0% salt treatment were fibrous, healthy and well developed while the
roots in the 0.5% salt treatment had died/melted towards the root tips but the majority of the
root system was alive and healthy. However, there was no significant difference in the
chlorophyll content (p>0.05). In plants subjected to 0.5% it was seen that while old leaves
wilted and died, new leaves had sprouted. Furthermore, despite the wilting of old leaves the
chlorophyll content of the new leaves was the same as the control plants (p= 0.863) (Table
4.12).
With wilting of leaves it can be said that the plants had experienced the first stress, the
osmotic stress, this response is consistent with many experiments such as the work done by
Antonio and Weber in 1999 to Aghaeri in 2008. Following the osmotic stress, ionic stress
takes its toll resulting in early senescence of old leaves. However at 0.5% salt some level of
ionic and osmotic homoeostasis might have been obtained resulting in new shoots. Thus, it
can be seen that all the plants subjected to 0% salt survived while those subjected to higher
salinities died out such as 0.5 % salt where 4 plants died, while all the plants of 1.0 % salt and
1.5% died giving a percentage survival rate of 0% (Table 4.13). The two cultivars Ikaraoi and
Katutu cannot survive salinity levels of more than 0.5% (5ppt) of artificial sea water in vivo.
Therefore more experiments need to be done on these groups of cultivars of giant swamp taro
to find cultivars that can tolerate salinity levels of more than 0.5% (5 ppt) (Figure 4.2).
Table 4.12 Plant response to the various salinity levels
Parameter f probability 0% 0.50%
No. Leaves 0.04 2+/-0.47 2.5+/-0.85
Root 0.002 2+/-0.47 1.5+/-0.53
124
dying
leaves
0.001 1.6+/-0.52 6+/-0.47
Chlorophyll 0.863 19.48+/-1 23.05+/-1
The above represents the calculated Anova values of the number of leaves emerging, rooting,
number of dying leaves and chlorophyll content with their respective mean values. These
calculated f probabilities and means are of the total plant response to the various salinity
levels tested. Post hoc analysis could not be carried out as there are only two groups for
comparison.
Table 4.13 Percentage survival rate of the various salinity levels
% salt no alive no. dead % survival
0 10 0 100
0.5 6 4 60
1 0 10 0
1.5 0 10 0
The above shows the percentage survival rate of the ten replicates of the plants to the subjected
salinity levels of 0%, 0.5%, 1.0% and 1.5% salt.
Figure 4.2 Overall
morphological
responses to salt
applications, plants
from the left; 0%, 0.5%,
1.0% and 1.5% salt.
125
5.0 DISCUSSION
Giant swamp taro is a local food crop of the Pacific and an everyday food source for the atoll
islands, and is also a neglected and underutilized crop species in the region. Neglected in the
sense that only the traditional farmers in the atolls islands cultivate it and even here its use is
now fast being eroded by changing preferences of food and life style. Coupled with the effects
of climate change, giant swamp taro is threatened through loss of its diverse range of cultivars
and traditional cultivation knowledge. It is disturbing to see that despite the importance of this
unique food crop in terms of food security, traditions and identity, the scientific and common
knowledge of the crop is limited and restricted by the lack of research.
This research reveals some of the very important factors that have led to the drop in giant
swamp taro diversity and production. As seen in the Tuvalu case study climate change may be
one such factor as increases in sea level and the increased frequency and intensity of storms
likely threaten this crop. Disturbance in the ground water lens or seawater inundation results
in increased ground water salinity levels. Coastal erosion due to sea level rise may be another
contributing factor, however the effect of coastal erosion or displacement on the fresh ground
water lens is relativity under-investigated and needs further research.
Apart from climate change, anthropogenic factors are also large contributors to the decline in
giant swamp taro production and the erosion of traditional knowledge. These anthropogenic
factors consist of direct impacts on the fresh water lens and impact on the giant swamp taro.
Direct impact on the fresh water lens such as in the case of Funafuti includes disturbances
caused by construction, pollution, development pressure, extraction and population pressure
(Webb, 2007). This causes enhanced mixing in the transition zone of the lens. While impacts
on the giant swamp taro include land allocation and disputes, preference of an easier lifestyle,
white collar jobs and western foods that are easier to cook and does not require the strenuous
task of cultivation.
126
The case study survey on Tuvalu gives a glimpse of the incidence of ground water salinity
levels. It was seen that in overall comparison to 2006 salinity levels in 2010 were slightly
higher on one island. From the survey it was found that giant swamp taro was able to tolerate
salinity values well above those stated in past literature works (Dunn, 1976; Webb, 2007;
Manner, 2009) which was also seen in the in vitro and in vivo experiment. Giant swamp taro
cultivars from Tuvalu had been collected during the survey and so were not available for the
salt screening experiments as giant swamp taro takes a long time to grow and to multiple. This
was especially evident on Funafuti where the highest ground water salinity levels and the
second highest percentage increase in salinity were found. Nui ground water salinity values
fell well in between the fresh water zone of 1500-2500 µS/cm. Similarly for Niutao which had
quite fresh overall ground water, while Nanumaga and Nanumea had no change in salinity
levels.
Atoll islands in Tuvalu have a small low lying topography, making their ground water lens
highly vulnerable, variation in groundwater salinity levels existed. This is due to the variation
in size, amount of development pressure, population pressure and natural disasters
experienced by the atoll islands. For example Funafuti has the highest groundwater salinity
levels as it has the most vulnerable topography, it has also experienced the most development
and populations pressures. While, Nanumaga has experienced no increase in ground water
salinity as it has a wider topography and has not experienced extensive development and
population pressures.
Moreover, apart from the finds of the salinity survey, the in vitro and in vivo salt tolerance
screening also provided significant information. Both the in vitro and in vivo experiments
showed that no significant difference in response to rise in salinity levels exist between the
two cultivar groups Ikaraoi and Katutu. It also revealed that this two groups of cultivars
could tolerate all the four salinity levels up to 2% or 20ppt in vitro. While in vivo the two
group of cultivars could only tolerate up to 0.5% or 5ppt. In vitro results also revealed that no
127
significant difference existed between the impacts of sodium chloride and artificial sea water
on the plants. Also that mixing salt solution while making the growth medium resulted in
77.8% less contamination compared to applying salt solutions after subculturing.
The difference in salinity tolerance response of plant in vitro and in vivo is due to the type of
exposure the plants get in the two systems. In an in vivo system plants are exposed to variable
temperature, light intensity, photoperiod duration, humidity, heat and wind, while in vitro
systems are enclosed with optimum growth conditions. This exposure in an in vivo system
causes unaccounted increase in salinity as soil and plant water evaporates, dehydration,
disturbances in plant ion and osmotic homeostasis, hence resulting in lower salt tolerance seen
in plants in vivo than in vitro.
The giant swamp taro salt tolerance rapid screening methodology used in the research, is
practical enough for the Pacific where there is lack of technical and financial resources. This
rapid screening methodology basically involves screening in vitro and in vivo with either
sodium chloride or artificial sea water at five equal interval levels of salinities which can be
subjected to change depending on the aim of the experiment. While the methodology used
gives a strong foundation for rapid salt tolerance screening, there is still a lot of improvement
that needs to be done. The methodology can be improved by using larger sample populations
and using cultivars instead of group of cultivars for both in vitro and in vivo. Also constant
monitoring of soil salinity levels in an in vivo system is needed to avoid unaccounted
increases in applied salinity levels.
The ground water salinity survey from Tuvalu revealed that the swamp taro can tolerate
8000µS/cm (5.36ppt), which is more than the 3000µS/cm (2.01ppt) (Dunn,1997, Webb, 2007)
limit stated in past literature. Also both the in vitro and in vivo showed similar results, where
swamp taro effectively tolerated 5ppt of salt. Hence it can be said that the giant swamp taro
has the capacity to tolerate 5ppt of salt.
128
6.0 CONCULSION
Despite the many factors affecting the decline in traditional knowledge and production, the
status of the giant swamp taro can be improved. Farmers need to be encouraged to pay more
attention to their crops and take pride in cultivating the many cultivars. Local authorities need
to take more initiative in working with farmers to revive the culture of giant swamp taro
production. This action from farmers and governments would not only increase the diversity
of giant swamp taro but also increase the variation of climate ready traits present in the crop
gene pool. This variation is essential in development of improved crop cultivars that can
buffer against not only climate change but also pest and diseases. This can be achieved by
education, awareness, genetic resource sharing and conservation. For example the Tuvalu
ground water salinity survey and giant swamp taro descriptor development in Pohnpei, carried
out in the research acted as a mechanism for creating awareness, promoting genetic resource
sharing and conservation. The giant swamp taro cultivars collected from Tuvalu and Pohnpei
while doing the research are now being conserved and duplicated at CePaCT.
Government and the local authorities can promote education, awareness of giant swamp taro
and its cultivation by incorporating this knowledge in the local school curriculums. Gardening
competitions in schools that assess the diversity and health of giant swamp taro can help get
the younger generation to get involved. This would result in students wanting to learn more
about how to cultivate the crop, the cultivars present and how to distinguish between them,
hence keeping the traditional knowledge alive.
Awareness can also be created by actively involving farmers and women in the atoll islands in
creating farm gene banks and in workshops that promote cultivation of local food crops.
Governments can promote and encourage, scholarship and funding providers such as AusAid
and European Unions to focus on capacity building and research on giant swamp taro. This
would ensure food security and expand the current scientific knowledge base of the crop in
areas of drought and salt tolerance.
129
Furthermore, to encourage and expand the diversity range, sharing of genetic resources is
important. Hence local government’s willingness towards sharing of giant swamp taro
cultivars is essential, as this sharing of genetic resources also leads to ex suit conservation.
Finally, with the many key information provided on ground water salinity, cultivar descriptor
and the rapid screening methodology atoll island communities can now better deal with the
impacts of climate change. This can be done by classifying and screening the diverse range of
cultivars for variation in salt tolerance. In doing so, not only can we develop salt tolerant
crops but we can also ensure food security and security of the traditions of the Pacific island
countries.
130
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140
ANNEX
TRADITIONAL KNOWLEDGE
While giant swamp taro is not famous in poetry, dances and songs it does have its own
legend. Strangely enough quite often farmers have found an octopus in their giant swamp taro
pits and these octopuses are not just lying around, they are found hugging the taro plant. How
these octopuses get to the pits is quite a mystery. Legend has it that the octopus and the giant
swamp taro are brothers and sisters, according to the legend this link is formed on the
resemblance of the suckers present on the octopus legs and the fruiting flower of the taro. This
could mean that it is the sibling link that attracts the octopus to the taro pits.
Figure 2.22 (left) Octopus.
Figure 2.23 (right) mature giant
swamp taro flowers with berries.
Another relation of the giant swamp taro to the Octopus given by the Tuvaluan farmers
where they call the compost soil around giant swamp taro ‘ulu feke’ meaning Octopus head,
however the reason for this is unknown (Iese, 2005). Apart from this the majority of the
traditional knowledge is mainly about its cultivation and harvest that can be found in the
sections 3.3.
141
Ikaraoi Cultivar Group Response
In vitro Ikaraoi
%
Salt
INITIAL (week 1) FINAL (week 8)
NaCl Salt
Solution
ASW Salt
Solution
NaCl Salt
Solution
ASW Salt Solution
0%
Salt
0.5%
1.0%
142
1.5%
2.0%
143
Multiple Comparisons
Height Tukey HSD
(I) VAR00002
(J) VAR00002 Mean Difference
(I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound
dimension2
0%
dimension3
0.5% -.45000 .28059 .499 -1.2303 .3303
1% .27000 .28059 .871 -.5103 1.0503
1.5% -.09000 .28059 .998 -.8703 .6903
2% -.28500 .28059 .848 -1.0653 .4953 0.5%
dimension3
0% .45000 .28059 .499 -.3303 1.2303 1% .72000 .28059 .085 -.0603 1.5003 1.5% .36000 .28059 .702 -.4203 1.1403 2% .16500 .28059 .977 -.6153 .9453
1%
dimension3
0% -.27000 .28059 .871 -1.0503 .5103 0.5% -.72000 .28059 .085 -1.5003 .0603 1.5% -.36000 .28059 .702 -1.1403 .4203 2% -.55500 .28059 .285 -1.3353 .2253
1.5%
dimension3
0% .09000 .28059 .998 -.6903 .8703 0.5% -.36000 .28059 .702 -1.1403 .4203 1% .36000 .28059 .702 -.4203 1.1403 2% -.19500 .28059 .957 -.9753 .5853
2%
dimension3
0% .28500 .28059 .848 -.4953 1.0653 0.5% -.16500 .28059 .977 -.9453 .6153 1% .55500 .28059 .285 -.2253 1.3353 1.5% .19500 .28059 .957 -.5853 .9753
144
Multiple Comparisons leaves Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0SALT 0.5SALT .40000 .25854 .535 -.3190 1.1190
1.0SALT .20000 .25854 .938 -.5190 .9190 1.5SALT .15000 .25854 .978 -.5690 .8690 2SALT -.05000 .25854 1.000 -.7690 .6690
0.5SALT 0SALT -.40000 .25854 .535 -1.1190 .3190 1.0SALT -.20000 .25854 .938 -.9190 .5190 1.5SALT -.25000 .25854 .869 -.9690 .4690 2SALT -.45000 .25854 .414 -1.1690 .2690
1.0SALT 0SALT -.20000 .25854 .938 -.9190 .5190 0.5SALT .20000 .25854 .938 -.5190 .9190 1.5SALT -.05000 .25854 1.000 -.7690 .6690 2SALT -.25000 .25854 .869 -.9690 .4690
1.5SALT 0SALT -.15000 .25854 .978 -.8690 .5690 0.5SALT .25000 .25854 .869 -.4690 .9690 1.0SALT .05000 .25854 1.000 -.6690 .7690 2SALT -.20000 .25854 .938 -.9190 .5190
2SALT 0SALT .05000 .25854 1.000 -.6690 .7690 0.5SALT .45000 .25854 .414 -.2690 1.1690 1.0SALT .25000 .25854 .869 -.4690 .9690 1.5SALT .20000 .25854 .938 -.5190 .9190
145
Multiple Comparisons suckers Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.650 .468 .636 -1.95 .65
1% -.500 .468 .822 -1.80 .80 1.5% -1.000 .468 .213 -2.30 .30 2% -.950 .468 .260 -2.25 .35
0.5% 0% .650 .468 .636 -.65 1.95 1% .150 .468 .998 -1.15 1.45 1.5% -.350 .468 .945 -1.65 .95 2% -.300 .468 .968 -1.60 1.00
1% 0% .500 .468 .822 -.80 1.80 0.5% -.150 .468 .998 -1.45 1.15 1.5% -.500 .468 .822 -1.80 .80 2% -.450 .468 .872 -1.75 .85
1.5% 0% 1.000 .468 .213 -.30 2.30 0.5% .350 .468 .945 -.95 1.65 1% .500 .468 .822 -.80 1.80 2% .050 .468 1.000 -1.25 1.35
2% 0% .950 .468 .260 -.35 2.25 0.5% .300 .468 .968 -1.00 1.60 1% .450 .468 .872 -.85 1.75 1.5% -.050 .468 1.000 -1.35 1.25
146
Multiple Comparisons corm Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.1894 .1425 .674 -.586 .208
1% -.3424 .1425 .124 -.739 .055 1.5% -.6156* .1403 .000 -1.007 -.225 2% -.4653* .1384 .010 -.851 -.080
0.5% 0% .1894 .1425 .674 -.208 .586 1% -.1529 .1481 .840 -.566 .260 1.5% -.4261* .1461 .035 -.833 -.019 2% -.2759 .1442 .318 -.678 .126
1% 0% .3424 .1425 .124 -.055 .739 0.5% .1529 .1481 .840 -.260 .566 1.5% -.2732 .1461 .341 -.680 .134 2% -.1229 .1442 .913 -.525 .279
1.5% 0% .6156* .1403 .000 .225 1.007 0.5% .4261* .1461 .035 .019 .833 1% .2732 .1461 .341 -.134 .680 2% .1503 .1421 .827 -.246 .546
2% 0% .4653* .1384 .010 .080 .851 0.5% .2759 .1442 .318 -.126 .678 1% .1229 .1442 .913 -.279 .525 1.5% -.1503 .1421 .827 -.546 .246
*. The mean difference is significant at the 0.05 level.
147
Multiple Comparisons root Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% .9494 .4151 .159 -.207 2.106
1% .5729 .4151 .642 -.584 1.730 1.5% .6922 .4089 .444 -.447 1.831 2% -.0221 .4032 1.000 -1.145 1.101
0.5% 0% -.9494 .4151 .159 -2.106 .207 1% -.3765 .4316 .906 -1.579 .826 1.5% -.2572 .4256 .974 -1.443 .929 2% -.9715 .4201 .151 -2.142 .199
1% 0% -.5729 .4151 .642 -1.730 .584 0.5% .3765 .4316 .906 -.826 1.579 1.5% .1193 .4256 .999 -1.067 1.305 2% -.5950 .4201 .619 -1.766 .576
1.5% 0% -.6922 .4089 .444 -1.831 .447 0.5% .2572 .4256 .974 -.929 1.443 1% -.1193 .4256 .999 -1.305 1.067 2% -.7143 .4139 .424 -1.868 .439
2% 0% .0221 .4032 1.000 -1.101 1.145 0.5% .9715 .4201 .151 -.199 2.142 1% .5950 .4201 .619 -.576 1.766 1.5% .7143 .4139 .424 -.439 1.868
148
Multiple Comparisons Dying Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% .9000 .3336 .062 -.028 1.828
1% .6000 .3336 .381 -.328 1.528 1.5% .2500 .3336 .944 -.678 1.178 2% -.1000 .3336 .998 -1.028 .828
0.5% 0% -.9000 .3336 .062 -1.828 .028 1% -.3000 .3336 .897 -1.228 .628 1.5% -.6500 .3336 .300 -1.578 .278 2% -1.0000* .3336 .028 -1.928 -.072
1% 0% -.6000 .3336 .381 -1.528 .328 0.5% .3000 .3336 .897 -.628 1.228 1.5% -.3500 .3336 .832 -1.278 .578 2% -.7000 .3336 .229 -1.628 .228
1.5% 0% -.2500 .3336 .944 -1.178 .678 0.5% .6500 .3336 .300 -.278 1.578 1% .3500 .3336 .832 -.578 1.278 2% -.3500 .3336 .832 -1.278 .578
2% 0% .1000 .3336 .998 -.828 1.028 0.5% 1.0000* .3336 .028 .072 1.928 1% .7000 .3336 .229 -.228 1.628 1.5% .3500 .3336 .832 -.578 1.278
*. The mean difference is significant at the 0.05 level.
149
Multiple Comparisons weight Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.2290 .2155 .825 -.828 .370
1% .0575 .2155 .999 -.542 .657 1.5% -.1525 .2155 .954 -.752 .447 2% .0385 .2155 1.000 -.561 .638
0.5% 0% .2290 .2155 .825 -.370 .828 1% .2865 .2155 .674 -.313 .886 1.5% .0765 .2155 .997 -.523 .676 2% .2675 .2155 .727 -.332 .867
1% 0% -.0575 .2155 .999 -.657 .542 0.5% -.2865 .2155 .674 -.886 .313 1.5% -.2100 .2155 .866 -.809 .389 2% -.0190 .2155 1.000 -.618 .580
1.5% 0% .1525 .2155 .954 -.447 .752 0.5% -.0765 .2155 .997 -.676 .523 1% .2100 .2155 .866 -.389 .809 2% .1910 .2155 .901 -.408 .790
2% 0% -.0385 .2155 1.000 -.638 .561 0.5% -.2675 .2155 .727 -.867 .332 1% .0190 .2155 1.000 -.580 .618 1.5% -.1910 .2155 .901 -.790 .408
150
Multiple Comparisons Chlorophyll Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.0851 1.6748 1.000 -4.743 4.572
1% .3699 1.6748 .999 -4.288 5.027 1.5% .2893 1.6748 1.000 -4.368 4.947 2% .7089 1.6748 .993 -3.949 5.366
0.5% 0% .0851 1.6748 1.000 -4.572 4.743 1% .4550 1.6748 .999 -4.203 5.112 1.5% .3744 1.6748 .999 -4.283 5.032 2% .7940 1.6748 .990 -3.863 5.452
1% 0% -.3699 1.6748 .999 -5.027 4.288 0.5% -.4550 1.6748 .999 -5.112 4.203 1.5% -.0806 1.6748 1.000 -4.738 4.577 2% .3390 1.6748 1.000 -4.318 4.997
1.5% 0% -.2893 1.6748 1.000 -4.947 4.368 0.5% -.3744 1.6748 .999 -5.032 4.283 1% .0806 1.6748 1.000 -4.577 4.738 2% .4196 1.6748 .999 -4.238 5.077
2% 0% -.7089 1.6748 .993 -5.366 3.949 0.5% -.7940 1.6748 .990 -5.452 3.863 1% -.3390 1.6748 1.000 -4.997 4.318 1.5% -.4196 1.6748 .999 -5.077 4.238
151
Katutu Cultivar Group Response
In vitro Katutu
%
Salt
INITIAL (week 1) FINAL (week 8)
NaCl Salt
Solution
ASW Salt
Solution
NaCl Salt
Solution
ASW Salt
Solution
0%
Salt
0.5%
1.0
%
152
1.5
%
2.0
%
153
Multiple Comparisons height Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -1.11000* .35088 .017 -2.0858 -.1342
1% -.58500 .35088 .459 -1.5608 .3908 1.5% -.15500 .35088 .992 -1.1308 .8208 2% -.95000 .35088 .060 -1.9258 .0258
0.5% 0% 1.11000* .35088 .017 .1342 2.0858 1% .52500 .35088 .567 -.4508 1.5008 1.5% .95500 .35088 .058 -.0208 1.9308 2% .16000 .35088 .991 -.8158 1.1358
1% 0% .58500 .35088 .459 -.3908 1.5608 0.5% -.52500 .35088 .567 -1.5008 .4508 1.5% .43000 .35088 .737 -.5458 1.4058 2% -.36500 .35088 .836 -1.3408 .6108
1.5% 0% .15500 .35088 .992 -.8208 1.1308 0.5% -.95500 .35088 .058 -1.9308 .0208 1% -.43000 .35088 .737 -1.4058 .5458 2% -.79500 .35088 .165 -1.7708 .1808
2% 0% .95000 .35088 .060 -.0258 1.9258 0.5% -.16000 .35088 .991 -1.1358 .8158 1% .36500 .35088 .836 -.6108 1.3408 1.5% .79500 .35088 .165 -.1808 1.7708
*. The mean difference is significant at the 0.05 level.
154
Multiple Comparisons leaves Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.15000 .29182 .986 -.9615 .6615
1% .25000 .29182 .912 -.5615 1.0615 1.5% .20000 .29182 .959 -.6115 1.0115 2% -.50000 .29182 .431 -1.3115 .3115
0.5% 0% .15000 .29182 .986 -.6615 .9615 1% .40000 .29182 .648 -.4115 1.2115 1.5% .35000 .29182 .752 -.4615 1.1615 2% -.35000 .29182 .752 -1.1615 .4615
1% 0% -.25000 .29182 .912 -1.0615 .5615 0.5% -.40000 .29182 .648 -1.2115 .4115 1.5% -.05000 .29182 1.000 -.8615 .7615 2% -.75000 .29182 .084 -1.5615 .0615
1.5% 0% -.20000 .29182 .959 -1.0115 .6115 0.5% -.35000 .29182 .752 -1.1615 .4615 1% .05000 .29182 1.000 -.7615 .8615 2% -.70000 .29182 .125 -1.5115 .1115
2% 0% .50000 .29182 .431 -.3115 1.3115 0.5% .35000 .29182 .752 -.4615 1.1615 1% .75000 .29182 .084 -.0615 1.5615 1.5% .70000 .29182 .125 -.1115 1.5115
155
Multiple Comparisons suckers Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.650 .519 .721 -2.09 .79
1% -1.900* .519 .004 -3.34 -.46 1.5% -1.200 .519 .151 -2.64 .24 2% -1.200 .519 .151 -2.64 .24
0.5% 0% .650 .519 .721 -.79 2.09 1% -1.250 .519 .123 -2.69 .19 1.5% -.550 .519 .827 -1.99 .89 2% -.550 .519 .827 -1.99 .89
1% 0% 1.900* .519 .004 .46 3.34 0.5% 1.250 .519 .123 -.19 2.69 1.5% .700 .519 .662 -.74 2.14 2% .700 .519 .662 -.74 2.14
1.5% 0% 1.200 .519 .151 -.24 2.64 0.5% .550 .519 .827 -.89 1.99 1% -.700 .519 .662 -2.14 .74 2% .000 .519 1.000 -1.44 1.44
2% 0% 1.200 .519 .151 -.24 2.64 0.5% .550 .519 .827 -.89 1.99 1% -.700 .519 .662 -2.14 .74 1.5% .000 .519 1.000 -1.44 1.44
*. The mean difference is significant at the 0.05 level.
156
Multiple Comparisons corm Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.0537 .1597 .997 -.498 .391
1% -.4578* .1620 .045 -.909 -.007 1.5% -.3011 .1597 .333 -.746 .144 2% -.2850 .1577 .376 -.724 .154
0.5% 0% .0537 .1597 .997 -.391 .498 1% -.4041 .1640 .108 -.861 .052 1.5% -.2474 .1618 .546 -.698 .203 2% -.2313 .1597 .598 -.676 .213
1% 0% .4578* .1620 .045 .007 .909 0.5% .4041 .1640 .108 -.052 .861 1.5% .1567 .1640 .874 -.300 .613 2% .1728 .1620 .823 -.278 .624
1.5% 0% .3011 .1597 .333 -.144 .746 0.5% .2474 .1618 .546 -.203 .698 1% -.1567 .1640 .874 -.613 .300 2% .0161 .1597 1.000 -.429 .461
2% 0% .2850 .1577 .376 -.154 .724 0.5% .2313 .1597 .598 -.213 .676 1% -.1728 .1620 .823 -.624 .278 1.5% -.0161 .1597 1.000 -.461 .429
*. The mean difference is significant at the 0.05 level.
157
Multiple Comparisons root Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% .7863 .4413 .390 -.442 2.014
1% .4489 .4475 .853 -.797 1.694 1.5% .3021 .4413 .959 -.926 1.530 2% .3750 .4356 .910 -.837 1.587
0.5% 0% -.7863 .4413 .390 -2.014 .442 1% -.3374 .4531 .945 -1.598 .924 1.5% -.4842 .4469 .815 -1.728 .760 2% -.4113 .4413 .884 -1.639 .817
1% 0% -.4489 .4475 .853 -1.694 .797 0.5% .3374 .4531 .945 -.924 1.598 1.5% -.1468 .4531 .998 -1.408 1.114 2% -.0739 .4475 1.000 -1.319 1.172
1.5% 0% -.3021 .4413 .959 -1.530 .926 0.5% .4842 .4469 .815 -.760 1.728 1% .1468 .4531 .998 -1.114 1.408 2% .0729 .4413 1.000 -1.155 1.301
2% 0% -.3750 .4356 .910 -1.587 .837 0.5% .4113 .4413 .884 -.817 1.639 1% .0739 .4475 1.000 -1.172 1.319 1.5% -.0729 .4413 1.000 -1.301 1.155
158
Multiple Comparisons dying Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% .1500 .3024 .988 -.691 .991
1% .0000 .3024 1.000 -.841 .841 1.5% -.1500 .3024 .988 -.991 .691 2% -.4500 .3024 .573 -1.291 .391
0.5% 0% -.1500 .3024 .988 -.991 .691 1% -.1500 .3024 .988 -.991 .691 1.5% -.3000 .3024 .858 -1.141 .541 2% -.6000 .3024 .282 -1.441 .241
1% 0% .0000 .3024 1.000 -.841 .841 0.5% .1500 .3024 .988 -.691 .991 1.5% -.1500 .3024 .988 -.991 .691 2% -.4500 .3024 .573 -1.291 .391
1.5% 0% .1500 .3024 .988 -.691 .991 0.5% .3000 .3024 .858 -.541 1.141 1% .1500 .3024 .988 -.691 .991 2% -.3000 .3024 .858 -1.141 .541
2% 0% .4500 .3024 .573 -.391 1.291 0.5% .6000 .3024 .282 -.241 1.441 1% .4500 .3024 .573 -.391 1.291 1.5% .3000 .3024 .858 -.541 1.141
159
Multiple Comparisons weight Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.2580 .2065 .723 -.832 .316
1% -.2225 .2065 .818 -.797 .352 1.5% .3185 .2065 .538 -.256 .893 2% -.0890 .2065 .993 -.663 .485
0.5% 0% .2580 .2065 .723 -.316 .832 1% .0355 .2065 1.000 -.539 .610 1.5% .5765* .2065 .049 .002 1.151 2% .1690 .2065 .924 -.405 .743
1% 0% .2225 .2065 .818 -.352 .797 0.5% -.0355 .2065 1.000 -.610 .539 1.5% .5410 .2065 .075 -.033 1.115 2% .1335 .2065 .967 -.441 .708
1.5% 0% -.3185 .2065 .538 -.893 .256 0.5% -.5765* .2065 .049 -1.151 -.002 1% -.5410 .2065 .075 -1.115 .033 2% -.4075 .2065 .287 -.982 .167
2% 0% .0890 .2065 .993 -.485 .663 0.5% -.1690 .2065 .924 -.743 .405 1% -.1335 .2065 .967 -.708 .441 1.5% .4075 .2065 .287 -.167 .982
*. The mean difference is significant at the 0.05 level.
160
Multiple Comparisons chloro Tukey HSD (I) salt (J) salt Mean
Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% .9656 1.4986 .967 -3.202 5.133
1% .5020 1.4986 .997 -3.665 4.669 2% .3215 1.4986 1.000 -3.846 4.489 2% .4041 1.4986 .999 -3.763 4.571
0.5% 0% -.9656 1.4986 .967 -5.133 3.202 1% -.4637 1.4986 .998 -4.631 3.704 2% -.6442 1.4986 .993 -4.812 3.523 2% -.5615 1.4986 .996 -4.729 3.606
1% 0% -.5020 1.4986 .997 -4.669 3.665 0.5% .4637 1.4986 .998 -3.704 4.631 2% -.1805 1.4986 1.000 -4.348 3.987 2% -.0979 1.4986 1.000 -4.265 4.069
2% 0% -.3215 1.4986 1.000 -4.489 3.846 0.5% .6442 1.4986 .993 -3.523 4.812 1% .1805 1.4986 1.000 -3.987 4.348 2% .0826 1.4986 1.000 -4.085 4.250
2% 0% -.4041 1.4986 .999 -4.571 3.763 0.5% .5615 1.4986 .996 -3.606 4.729 1% .0979 1.4986 1.000 -4.069 4.265 2% -.0826 1.4986 1.000 -4.250 4.085
161
Total Plant Response
In vivo plants after salt application
% salt Groups
Ikaraoi Katutu 0%
control
0.5%
1.0%
162
Multiple Comparisons HEIGHT Tukey HSD (I) SALT
(J) SALT
Mean Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.78000* .23310 .009 -1.4218 -.1382
1% -.15750 .23310 .961 -.7993 .4843 1.5% -.12250 .23310 .985 -.7643 .5193 2% -.61750 .23310 .066 -1.2593 .0243
0.5% 0% .78000* .23310 .009 .1382 1.4218 1% .62250 .23310 .062 -.0193 1.2643 1.5% .65750* .23310 .042 .0157 1.2993 2% .16250 .23310 .957 -.4793 .8043
1% 0% .15750 .23310 .961 -.4843 .7993 0.5% -.62250 .23310 .062 -1.2643 .0193 1.5% .03500 .23310 1.000 -.6068 .6768 2% -.46000 .23310 .283 -1.1018 .1818
1.5% 0% .12250 .23310 .985 -.5193 .7643 0.5% -.65750* .23310 .042 -1.2993 -.0157 1% -.03500 .23310 1.000 -.6768 .6068 2% -.49500 .23310 .214 -1.1368 .1468
2% 0% .61750 .23310 .066 -.0243 1.2593 0.5% -.16250 .23310 .957 -.8043 .4793 1% .46000 .23310 .283 -.1818 1.1018 1.5% .49500 .23310 .214 -.1468 1.1368
*. The mean difference is significant at the 0.05 level.
1.5%
163
Multiple Comparisons LEAVES Tukey HSD (I) SALT (J) SALT dimension4
Mean Difference (I-J)
Std. Error Sig.
95% Confidence Interval Lower Bound
Upper Bound
dimension2 0% dimension3 0.5% .12500 .19942 .971 -.4241 .6741 1% .22500 .19942 .791 -.3241 .7741 1.5% .17500 .19942 .905 -.3741 .7241 2% -.27500 .19942 .642 -.8241 .2741
0.5% dimension3 0% -.12500 .19942 .971 -.6741 .4241 1% .10000 .19942 .987 -.4491 .6491 1.5% .05000 .19942 .999 -.4991 .5991 2% -.40000 .19942 .267 -.9491 .1491
1% dimension3 0% -.22500 .19942 .791 -.7741 .3241 0.5% -.10000 .19942 .987 -.6491 .4491 1.5% -.05000 .19942 .999 -.5991 .4991 2% -.50000 .19942 .093 -1.0491 .0491
1.5% dimension3 0% -.17500 .19942 .905 -.7241 .3741 0.5% -.05000 .19942 .999 -.5991 .4991 1% .05000 .19942 .999 -.4991 .5991 2% -.45000 .19942 .164 -.9991 .0991
2% dimension3 0% .27500 .19942 .642 -.2741 .8241 0.5% .40000 .19942 .267 -.1491 .9491 1% .50000 .19942 .093 -.0491 1.0491 1.5% .45000 .19942 .164 -.0991 .9991
164
Multiple Comparisons SUCKERS Tukey HSD (I) SALT
(J) SALT
Mean Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.650 .356 .362 -1.63 .33
1% -1.200* .356 .008 -2.18 -.22 1.5% -1.100* .356 .019 -2.08 -.12 2% -1.075* .356 .024 -2.06 -.09
0.5% 0% .650 .356 .362 -.33 1.63 1% -.550 .356 .535 -1.53 .43 1.5% -.450 .356 .714 -1.43 .53 2% -.425 .356 .755 -1.41 .56
1% 0% 1.200* .356 .008 .22 2.18 0.5% .550 .356 .535 -.43 1.53 1.5% .100 .356 .999 -.88 1.08 2% .125 .356 .997 -.86 1.11
1.5% 0% 1.100* .356 .019 .12 2.08 0.5% .450 .356 .714 -.53 1.43 1% -.100 .356 .999 -1.08 .88 2% .025 .356 1.000 -.96 1.01
2% 0% 1.075* .356 .024 .09 2.06 0.5% .425 .356 .755 -.56 1.41 1% -.125 .356 .997 -1.11 .86 1.5% -.025 .356 1.000 -1.01 .96
*. The mean difference is significant at the 0.05 level.
165
Multiple Comparisons CORM Tukey HSD (I) SALT
(J) SALT
Mean Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% -.1200 .1073 .797 -.416 .176
1% -.4029* .1081 .002 -.701 -.105 1.5% -.4551* .1065 .000 -.749 -.162 2% -.3738* .1051 .004 -.663 -.084
0.5% 0% .1200 .1073 .797 -.176 .416 1% -.2829 .1109 .084 -.588 .023 1.5% -.3351* .1093 .021 -.636 -.034 2% -.2538 .1079 .134 -.551 .044
1% 0% .4029* .1081 .002 .105 .701 0.5% .2829 .1109 .084 -.023 .588 1.5% -.0523 .1101 .990 -.356 .251 2% .0290 .1087 .999 -.271 .329
1.5% 0% .4551* .1065 .000 .162 .749 0.5% .3351* .1093 .021 .034 .636 1% .0523 .1101 .990 -.251 .356 2% .0813 .1072 .942 -.214 .377
2% 0% .3738* .1051 .004 .084 .663 0.5% .2538 .1079 .134 -.044 .551 1% -.0290 .1087 .999 -.329 .271 1.5% -.0813 .1072 .942 -.377 .214
*. The mean difference is significant at the 0.05 level.
166
Multiple Comparisons ROOT Tukey HSD (I) SALT
(J) SALT
Mean Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% .8844* .3120 .040 .025 1.744
1% .5200 .3143 .465 -.346 1.386 1.5% .5022 .3098 .486 -.351 1.356 2% .1913 .3056 .971 -.651 1.033
0.5% 0% -.8844* .3120 .040 -1.744 -.025 1% -.3644 .3224 .790 -1.253 .524 1.5% -.3823 .3179 .750 -1.258 .494 2% -.6932 .3139 .181 -1.558 .172
1% 0% -.5200 .3143 .465 -1.386 .346 0.5% .3644 .3224 .790 -.524 1.253 1.5% -.0178 .3202 1.000 -.900 .864 2% -.3287 .3162 .837 -1.200 .543
1.5% 0% -.5022 .3098 .486 -1.356 .351 0.5% .3823 .3179 .750 -.494 1.258 1% .0178 .3202 1.000 -.864 .900 2% -.3109 .3117 .856 -1.170 .548
2% 0% -.1913 .3056 .971 -1.033 .651 0.5% .6932 .3139 .181 -.172 1.558 1% .3287 .3162 .837 -.543 1.200 1.5% .3109 .3117 .856 -.548 1.170
*. The mean difference is significant at the 0.05 level.
167
Multiple Comparisons DYING Tukey HSD (I) SALT (J) SALT dimension4
Mean Difference (I-J)
Std. Error Sig.
95% Confidence Interval Lower Bound
Upper Bound
dimension2 0% dimension3 0.5% .5250 .2255 .140 -.096 1.146 1% .3000 .2255 .672 -.321 .921 1.5% .0500 .2255 .999 -.571 .671 2% -.2750 .2255 .740 -.896 .346
0.5% dimension3 0% -.5250 .2255 .140 -1.146 .096 1% -.2250 .2255 .856 -.846 .396 1.5% -.4750 .2255 .221 -1.096 .146 2% -.8000* .2255 .004 -1.421 -.179
1% dimension3 0% -.3000 .2255 .672 -.921 .321 0.5% .2250 .2255 .856 -.396 .846 1.5% -.2500 .2255 .802 -.871 .371 2% -.5750 .2255 .084 -1.196 .046
1.5% dimension3 0% -.0500 .2255 .999 -.671 .571 0.5% .4750 .2255 .221 -.146 1.096 1% .2500 .2255 .802 -.371 .871 2% -.3250 .2255 .602 -.946 .296
2% dimension3 0% .2750 .2255 .740 -.346 .896 0.5% .8000* .2255 .004 .179 1.421 1% .5750 .2255 .084 -.046 1.196 1.5% .3250 .2255 .602 -.296 .946
*. The mean difference is significant at the 0.05 level.
168
Multiple Comparisons WEIGHT Tukey HSD (I) SALT (J) SALT dimension4
Mean Difference (I-J)
Std. Error Sig.
95% Confidence Interval Lower Bound
Upper Bound
dimension2 0% dimension3 0.5% -.2435 .1520 .498 -.662 .175 1% -.0825 .1520 .983 -.501 .336 1.5% .0830 .1520 .982 -.335 .501 2% -.0252 .1520 1.000 -.444 .393
0.5% dimension3 0% .2435 .1520 .498 -.175 .662 1% .1610 .1520 .827 -.257 .579 1.5% .3265 .1520 .204 -.092 .745 2% .2183 .1520 .605 -.200 .637
1% dimension3 0% .0825 .1520 .983 -.336 .501 0.5% -.1610 .1520 .827 -.579 .257 1.5% .1655 .1520 .812 -.253 .584 2% .0573 .1520 .996 -.361 .476
1.5% dimension3 0% -.0830 .1520 .982 -.501 .335 0.5% -.3265 .1520 .204 -.745 .092 1% -.1655 .1520 .812 -.584 .253 2% -.1082 .1520 .953 -.527 .310
2% dimension3 0% .0252 .1520 1.000 -.393 .444 0.5% -.2183 .1520 .605 -.637 .200 1% -.0573 .1520 .996 -.476 .361 1.5% .1082 .1520 .953 -.310 .527
169
Multiple Comparisons CHLORO Tukey HSD (I) SALT
(J) SALT
Mean Difference (I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound 0% 0.5% .4402 1.1106 .995 -2.618 3.498
1% .4359 1.1106 .995 -2.622 3.494 1.5% .3054 1.1106 .999 -2.753 3.363 2% .5565 1.1106 .987 -2.502 3.615
0.5% 0% -.4402 1.1106 .995 -3.498 2.618 1% -.0043 1.1106 1.000 -3.062 3.054 1.5% -.1349 1.1106 1.000 -3.193 2.923 2% .1163 1.1106 1.000 -2.942 3.174
1% 0% -.4359 1.1106 .995 -3.494 2.622 0.5% .0043 1.1106 1.000 -3.054 3.062 1.5% -.1305 1.1106 1.000 -3.189 2.928 2% .1206 1.1106 1.000 -2.937 3.179
1.5% 0% -.3054 1.1106 .999 -3.363 2.753 0.5% .1349 1.1106 1.000 -2.923 3.193 1% .1305 1.1106 1.000 -2.928 3.189 2% .2511 1.1106 .999 -2.807 3.309
2% 0% -.5565 1.1106 .987 -3.615 2.502 0.5% -.1163 1.1106 1.000 -3.174 2.942 1% -.1206 1.1106 1.000 -3.179 2.937 1.5% -.2511 1.1106 .999 -3.309 2.807