Botanical Studies (2009) 50: 35-42.
*
Corresponding author: E-mail: pra@tucbbs.com.ar; Tel:
0054-381-4239456; Fax: 0054-381-4330633.
INTRODUCTION
Drought and waterlogging are common adverse
environmental factors that affect the growth of plants and
are considered as the main
factors determining the global
geographic distribution of vegetation and restriction of
crop yields in agriculture (Schulze et al., 2005; Lin et al.,
2006). Symptoms of drought or waterlogging stresses
include photosynthesis decline, protein degradation,
slower leaf expansion, decreases in respiration and
biomass production, and stomatal closure, among others
(Kozlowski, 1997; Chai et al., 2001; Li and Li, 2005;
Henriques, 2008). However, under drought many species
respond by increasing the proportion of assimilates
diverted to root growth with the concomitant root/shoot
ratio increase (Sharp and Davies, 1989). In this condition
soil nutrients can be available to plants (McDonald and
Davis, 1996). Also, drought has been associated with
cell osmotic adjustment, which is accomplished by
accumulation of different compounds such as soluble
sugars, proline, glycine betaine, polyols, and other organic
compounds (Thomas, 1997; Chai et al., 2001). Soluble
sugars (sucrose, glucose and fructose) play a key role in
Physiological responses of quinoa (Chenopodium
quinoa Willd.) to drought and waterlogging stresses: dry
matter partitioning
Juan A. GONZALEZ
1
, Miriam GALLARDO
1
, Mirna HILAL
2
, Mariana ROSA
2
, and Fernando E.
PRADO
2,
*
1
Instituto de Ecologia (Botanica), Fundacion Miguel Lillo, Miguel Lillo 251 (4000) Tucuman, Argentina
2
Catedra de Fisiologia Vegetal, Facultad de Ciencias Naturales e IML, Miguel Lillo 205 (4000) Tucuman, Argentina
(Received October 1, 2007; Accepted June 25, 2008)
AbstrAct.
Quinoa (Chenopodium quinoa Willd.) plants responded differently to drought and
waterlogging. Plant and root dry weights (DW) were lower in both drought and waterlogging conditions
than in well-watered conditions, but the lowest values were obtained under waterlogging. However, the root
weight ratio (RWR: root dry weight per unit of plant dry weight) did not show significant changes in any
treatments. Leaf area (LA) and specific leaf area (SLA) were higher in drought than in waterlogging, but
drought and control treatments showed no significant differences. Conversely, specific leaf weight (SLW)
and relative water content (RWC) were higher under waterlogging than drought. However, between control
and waterlogging conditions, no a significant difference in RWC values emerged. In addition, the number of
leaves and height of plants remained unchanged in all treatments. The lowest content of total chlorophyll,
chlorophyll a and chlorophyll b was observed in waterlogging conditions while between control and drought
treatments there were no significant differences. Chlorophyll a/b ratio remained unchanged in all treatments.
Leaf nitrogen content, expressed per unit of leaf dry weight (N
m
), was lower in control plants and remained
unchanged under drought and waterlogging conditions. However, when it was expressed per unit of leaf
area (N
a
), waterlogging produced the highest value. In addition, soluble protein content was also higher in
waterlogging than in control and drought conditions. Proline content was higher under drought than in control
and waterlogging conditions; however, there was no a significant difference between control and waterlogging
treatments. Between control and drought treatments there were no differences in starch, sucrose or fructose
contents. Glucose and total soluble sugar contents were higher under drought than in well-watered conditions.
However, the highest amounts of soluble sugars and starch were found in waterlogging. Relationships between
soil water surplus and quinoa growth are discussed.
Keywords: Chenopodium quinoa; Chlorophyll; Drought; Dry matter partitioning; Nitrogen; Protein; Soluble
carbohydrates; Waterlogging.
Abbreviations: LA, leaf area; N
a
, leaf nitrogen content per unit of leaf area; N
m
, leaf nitrogen content per
unit of leaf dry weight; RWC, relative water content; RWR, root weight ratio; SLA, specific leaf area; SLW,
specific leaf weight.
PhySIOlOgy
pg_0002
36
Botanical Studies, Vol. 50, 2009
osmotic adjustment in many species; however, proline
only plays an important role in a few species, such as
potato and tomato (Escobar-Gutierrez et al., 1998; Bussis
and Heineke, 1998; Li and Li, 2005). Nevertheless, in
tomato proline represents only a small fraction of the total
osmotic solutes (Claussen, 2005). Additionally, proline is
very labile and accumulates in growing cells only after a
few weeks of drought while in mature tissues it appears to
be a symptom of imminent cell death.
Under waterlogging or flooding conditions plant
responses also include anatomical, morphological, and
metabolic alterations (Huang, 1997; Subbaiah and Sachs,
2003). During waterlogging the low oxygen concentration
in the rooting medium produces an inadequate oxygen
supply to the plant roots (Huang, 1997). Carbohydrate
metabolism and respiratory activity decreases, as well
as reductions of root and shoot growth, are common
symptoms of waterlogging stress (Zeng et al., 1999;
Subbaiah and Sachs, 2003). In this sense, we can say that
plants respond and adapt to different stresses through
various biochemical and physiological processes, thereby
acquiring stress tolerance. Thus, responses of plants to
combined stresses are neither independent nor specific
and so they can result in increases and/or overlapping
of stress effects. Consequently, to know plant responses
to combined stresses can be useful in understanding
the mechanisms allowing them to survive in adverse
conditions. Drought and waterlogging conditions normally
occur in several of the worlds' regions, including the South
America Andean region (Schulze et al., 2005). In fact,
global climate change and the El Nino and La Nina events
have severely altered rainfall distribution and intensity in
Andean arid regions of Argentina, Bolivia, Chile, Peru,
and Ecuador, during the last 20 years (Nunez et al., 1999,
Minetti and Gonzalez, 2006). Thus, heavy rains followed
by long drought periods are more and more frequent in
these regions, which alter the normal growth of both wild
and cultivated species (Grimm et al., 2000). On the other
hand, due to an increasing demand for foods with high
nutritional values in many countries, cultivation of quinoa
(Chenopodium quinoa Willd.), the ancestral Inca crop, has
surged.
Quinoa is a species that can tolerate different stresses
such as salinity, cold air, high solar radiation, night sub-
freezing temperatures, and different soil pHs (Risi and
Galwey, 1984; Gonzalez and Prado, 1992; Jacobsen et
al., 1998). It can also grow in arid and semiarid regions,
lowlands, brackish lands, and salt-water marshes (Jacobsen
et al., 1994). However, Gallardo and Gonzalez (1992)
have demonstrated that soil moisture plays an important
role in determining the time and rate of quinoa seed
germination and seedling growth. Nevertheless, studies
of the quinoa plant¡¦s ability to survive drought conditions
and waterlogging stresses are scarce. Thus, the aim of the
present work was to answer the following questions: 1)
How does quinoa respond physiologically to drought and
waterlogging. 2) Is the dry matter partitioning affected by
drought and waterlogging conditions. 3) Is quinoa well
adapted to growth under drought and waterlogging.
MATERIAlS AND METhODS
Plant material and growth conditions
Seeds of Chenopodium quinoa Willd. cv. Sajama were
surface sterilized with 2% (v/v) sodium hypochlorite
solution for 10 min and washed thoroughly with distilled
water. After this treatment seeds were germinated during
3 days in plastic boxes (28 ¡Ñ 20 ¡Ñ 5 cm) containing
moistened vermiculite as substrate. After this process
boxes were transferred to a greenhouse for 13 days.
Seedlings were supplied with a fourth-strength Hoagland
solution every 3 days. After this period intact plants were
transferred to 1000-mL plastic pots (one plant per pot)
containing a dry mixture of sandy clay soil (50% sand
and 50% clay). Pots were kept in a controlled growth
chamber under a 12-h photoperiod, 25/20¢XC (light/dark)
temperature regime, 60% relative humidity, and 430
£gmol m
-2
s
-1
photosynthetically active radiation (PAR)
provided by Philips TLD 36 W/83 white fluorescent tubes
(Philips Lighting, Buenos Aires, Argentina) for 50 days.
Three treatment sets with two replicates of 20 plants each
in a randomised block were designed: set one, drought
(watering every 12 days, equivalent to near -0.20 MPa
of soil water potential), set two, waterlogging (pots were
flooded with distilled water to 1 cm above soil surface),
and set three, control (watering every 2 days, equivalent
to near -0.05 MPa of soil water potential). Control and
drought stressed plants were watered with distilled water
in the morning on the correspondent day by using 170 mL
for each pot. At the 50
th
day, plants (control, drought, and
waterlogging pots) were harvested and divided into leaves,
stems, and roots prior to use in growth and chemical
analyses.
growth and dry matter partitioning
Dry weight (DW) was determined after drying plant
material for 48 h at 84¢XC. Leaf relative water content
(RWC) was determined as follows: discs (3.0 cm
2
) of
different leaves were taken from the middle of the lamina
(excluding major veins) and weighed to obtain fresh
weight (FW). After this process leaf discs were floated on
distilled water for 24 h at 15¢XC in the dark. Fully hydrated
leaf discs were removed and weighed to obtain the turgid
weight (TW). RWC was calculated as RWC (%) = (FW-
DW) / (TW-DW) ¡Ñ 100. Leaf area (LA) corresponding
to the second pair of leaves was estimated using digitised
images obtained with a 200E charged-coupled device
video camera (Videoscope International, Washington,
DC, USA) coupled to a Macintosh Quadra 700 computer.
Image analysis was performed with NIH Image 1.45
software (Rasband W, National Institute of Health,
Bethesda, MD, USA). Root weight ratio (RWR: root dry
weight per unit of plant dry weight) was determined as
the ratio of root dry weight to total plant dry weight (g
pg_0003
GONZALEZ et al. ¡X Quinoa responses to drought and waterlogging
37
g
-1
). Specific leaf area (SLA) was determined as the ratio
of leaf area to leaf dry weight of individual leaves (cm
2
g
-1
) while the specific leaf weight (SLW) corresponding
to 1/SLA was expressed as (mg cm
-2
). Plant height was
measured using a 100 cm rule.
Chemical analysis
Chlorophyll extraction (50 mg leaf FW) was performed
using 2 mL of dimethyl sulfoxide (12 h in the dark at 45
¢XC) according to the method of Chapelle and Kim (1992).
Chlorophyll content was calculated from absorbance val-
ues at 665 and 649 nm according to equations of Wellburn
(1994). Soluble sugars (glucose, fructose, and sucrose),
starch, and proline were extracted from 0.5 g leaf FW with
4 mL of 80% ethanol at 75¢XC according to the procedure
of Rosa et al. (2004). Total soluble sugars were deter-
mined by the phenol-sulphuric acid method (Dubois et al.,
1956); glucose was estimated by using a glucose oxidase-
peroxidase coupled assay according to Jorgensen and
Andersen (1973); fructose was measured by the method of
Roe and Papadopoulos (1954) and sucrose by the proce-
dure of Cardini et al. (1955). For starch measurement the
insoluble fraction remaining after ethanolic extraction of
soluble sugars was resuspended in 2 mL of 2.5 M NaOH
and boiled for 5 min. After cooling the solution pH was
adjusted to pH 4.5 with 2 M HCl, and the resulting gelati-
nised starch was hydrolysed 10 min at 50¢XC with buffered
Rhizopus mold amyglucosidase (15 IU mL
-1
in 0.1 M so-
dium acetate buffer, pH 4.5). After this process, starch was
measured as reducing sugars by Nelson's method (Nel-
son, 1944) and expressed in maltose equivalents. Soluble
protein was extracted from 0.5 g leaf FW with 2 mL of
50 mM sodium phosphate buffer (pH 7.4), containing 5
£gM MnSO
4
and 1 mM £]-mercapethanol. Soluble protein
content was determined by the method of Lowry et al.
(1951) using bovine serum albumin (BSA) as a standard.
Total nitrogen content was determined in a Kjeltec-auto
1030 analyser (Tecator, Hoganas, Sweden) after digestion
in sulphuric acid with potassium sulphate by the Kjeldahl
procedure using selenium sulphate as catalyst. Proline was
determined according to the Bates et al. (1973) procedure.
Statistical analysis
Values shown in tables are means of two independent
replicates. Comparisons between means were analyzed by
one-way ANOVA, along with Tukey's test at a p . 0.05
significance level (Zar, 1984).
RESUlTS
Plant growth and dry matter partitioning
Dry weight of the whole plant as well as of individual
parts was higher in control than under drought and
waterlogging conditions, but the lowest values were
observed under waterlogging. However, RWR (an
indicator of dry matter partitioning) did not show changes
in any treatments (Table 1). Plant height showed no great
differences across treatments, but waterlogging conditions
produced the lowest values (data not shown). Leaf area
and SLA were decreased under waterlogging stress (36.2%
and 26.2%, respectively), but they were not affected
by drought. By contrast, SLW (organic matter spent to
produce one cm
2
of leaf) was found to be higher under
waterlogging (4.2 mg cm
-2
) than in drought and control
treatments (2.4 mg cm
-2
and 2.7 mg cm
-2
, respectively)
(Table 2).
Table 2. Relative water content (RWC), leaf area (LA), specific leaf area (SLA), specific leaf weight (SLW) and number of leaves
of Ch. quinoa plants subjected during 50 days to 3 different watering regimes. Data are means of two independent replicates. Means
¡Ó standard deviations (SD) within each column followed by different letters are significantly different at 0.05 probability level (n = 6,
for each replicate).
Treatment
RWC (%)
LA (cm
2
)
SLA (cm
2
g
-1
) SLW (mg cm
-2
) Number of leaves
Control
97.5¡Ó1.4
a
56.3¡Ó2.4
a
405.7¡Ó28.5
a
2.7¡Ó0.2
a
11.0¡Ó0.4
a
Drought
70.3¡Ó1.4
b
53.8¡Ó4.1
a
411.6¡Ó31.2
a
2.4¡Ó0.1
a
11.3¡Ó0.5
a
Waterlogging
98.8¡Ó1.8
a
34.3¡Ó2.6
b
303.8¡Ó55.1
b
3.3¡Ó0.2
b
11.0¡Ó0.2
a
Table 1. Total plant DW, root DW, stem DW, leaf DW, inflorescence DW, and RWR (root dry weight per unit of plant dry weight)
of Ch. quinoa plants subjected during 50 days to 3 different watering regimes. Data are means of two independent replicates. Means
¡Ó standard deviations (SD) within each column followed by different letters are significantly different at 0.05 probability level (n = 6,
for each replicate).
Treatment
Total plant DW
(mg)
Root DW
(mg)
Stem DW
(mg)
Leaf DW
(mg)
Inflorescence DW
(mg)
RWR
(mg)
Control
400.2¡Ó16.3
a
84.1¡Ó5.7
a
147.4¡Ó5.2
a
149.5¡Ó10.5
a
17.6¡Ó1.2
a
0.21¡Ó0.03
a
Drought
347.6¡Ó14.0
b
74.8¡Ó6.4
b
126.5¡Ó5.0
b
130.7¡Ó11.8
b
15.6¡Ó1.6
a
0.21¡Ó0.05
a
Waterlogging 269.8¡Ó25.4
c
60.5¡Ó7.0
c
86.8¡Ó8.9
c
112.9¡Ó 6.7
c
9.6¡Ó2.3
b
0.22¡Ó0.02
a
pg_0004
38
Botanical Studies, Vol. 50, 2009
Chlorophyll and leaf nitrogen content
Total chlorophyll and chlorophyll a and b content
was lower in plants under waterlogging than in drought
and control, and contents of the latter two showed
no significant differences. Chlorophyll a / b ratios
remained unchanged across all treatments (Table 3).
Total chlorophyll to N
m
molar ratio for control, drought,
and waterlogging treatments were 0.0178, 0.0169 and
0.0149, respectively (data not shown). Leaf nitrogen
content expressed per unit of leaf DW (N
m
) did not show
significant differences between drought and waterlogging
stresses (1.33 mmol g
-1
DW and 1.30 mmol g
-1
D W,
respectively) while in control plants it was lower (1.26
mmol g
-1
DW). However, when the nitrogen content was
expressed per unit of LA (N
a
), obtained dividing N
m
by
SLA, the highest value was observed under waterlogging
(42.8 mmol m
-2
). Drought and control conditions showed
no significant differences (Table 3).
Carbohydrate, soluble protein, and proline
content
Leaf total soluble sugars, sucrose, glucose, fructose,
and starch contents were higher in waterlogging conditions
than in drought or control treatments. However, drought
showed higher values of total soluble sugars and glucose
than control while fructose, sucrose and starch contents
showed no significant differences. Leaf soluble protein
content was also higher under waterlogging than in
drought or control conditions. In addition, the lowest value
(70.6 mg g
-1
DW) was observed in control leaves. With
respect to proline content the highest value (0.47 mg g
-1
DW) was observed under drought while waterlogging
and control treatments revealed no significant differences
(Table 4).
DISCUSSION
Plants under drought and waterlogging stresses exhibit
growth reduction, low SLA, photosynthesis declination,
protein degradation, decrease in respiration and biomass
production, and stomatal closure when compared to
their well-watered counterparts (Kozlowski, 1997; Chai
et al., 2001; Li and Li, 2005). However, our results
showed higher values of SLA and chlorophyll content in
drought treatment than in waterlogging conditions while
there was no a significant difference between control
and drought treatments (Tables 2 and 3). According to
Walter et al. (1993) high values of SLA and chlorophyll
represent a lower metabolic cost to maintain a cm
2
of leaf
area and, consequently, higher productivity. Thus, the
productivity of quinoa plants appears to be more affected
by waterlogging conditions. On the other hand, leaf
nitrogen content has been recognised as a determinant of
net photosynthetic capacity, and a positive correlation is
usually observed between CO
2
assimilation rate and leaf
nitrogen content (Niinemets, 1997). In quinoa plants the
leaf nitrogen content, expressed as N
m
(nitrogen per unit of
leaf DW), did not differ between drought and waterlogging
treatments, but it was lower in the control treatment.
However, when it was expressed as N
a
(nitrogen per unit
of LA) the highest value was observed under waterlogging,
and there was no a significant difference between drought
and control treatments (Table 3). The lowest N
a
values
Table 3. Chlorophyll (total, a, b and a/b ratio) and leaf nitrogen (N
m
and N
a
) content in leaves of Ch. quinoa plants subjected during
50 days to three different watering regimes. Data are means of two independent replicates. Means ¡Ó standard deviations (SD) within
each column followed by different letters are significantly different at 0.05 probability level (n = 10, for each replicate).
Treatment
Total Chl
(mg g
-1
DW)
Chl a
(mg g
-1
DW)
Chl b
(mg g
-1
DW) Chl a/b
N
m
(mmol g
-1
DW)
N
a
(mmol m
-2
)
Control
21.3 ¡Ó 1.8
a
15.2 ¡Ó 0.5
a
5.0 ¡Ó 0.2
a
3.0 ¡Ó 0.1
a
1.26 ¡Ó 0.2
a
31.1 ¡Ó 3.4
a
Drought
20.1 ¡Ó 1.7
a
15.0 ¡Ó 0.8
a
5.1 ¡Ó 0.3
a
2.9 ¡Ó 0.1
a
1.33 ¡Ó 0.1
b
32.3 ¡Ó 4.2
a
Waterlogging 17.3 ¡Ó 0.4
b
13.0 ¡Ó 0.3
b
4.3 ¡Ó 0.2
b
3.0 ¡Ó 0.1
a
1.30 ¡Ó 0.4
b
42.8 ¡Ó 3.6
b
Table 4. Total soluble sugars, glucose, fructose, sucrose, starch, soluble protein, and proline content in leaves of Ch. quinoa plants
subjected during 50 days to three watering regimes. Data are means of two independent replicates. Means ¡Ó standard deviations (SD)
within each column followed by different letters are significantly different at 0.05 probability level (n =10, for each replicate).
Treatment
Total
sol. sugars Glucose Fructose Sucrose Starch* Soluble
protein
Proline
(mg g
-1
DW)
Control
4.6¡Ó0.1
a
1.2¡Ó0.08
a
0.93¡Ó0.10
a
0.79¡Ó0.06
a
39.9¡Ó3.6
a
70.6¡Ó3.1
a
0.37¡Ó0.05
a
Drought
5.2¡Ó0.2
b
1.5¡Ó0.10
b
0.94¡Ó0.08
a
0.78¡Ó0.05
a
42.0¡Ó4.8
a
80.5¡Ó2.9
b
0.47¡Ó0.03
b
Waterlogging 7.2¡Ó0.2
c
2.1¡Ó0.10
c
1.74¡Ó0.12
b
1.21¡Ó0.06
b
75.7¡Ó5.3
b
122.4¡Ó3.5
c
0.35¡Ó0.04
a
*Starch is expressed as mg maltose g
-1
DW.
pg_0005
GONZALEZ et al. ¡X Quinoa responses to drought and waterlogging
39
being observed under drought and control conditions
signifies that a larger surface area can be constructed
with the same plant nitrogen investment, and then plants
have a more extensive foliar display for interception and
light capture (Mendes et al., 2001). Consequently, we can
conclude that under drought or well-watered treatments the
leaves of quinoa are metabolically more efficient than in
waterlogging conditions. In this context, we also analysed
the effects of both stresses on growth parameters and dry
matter partitioning. Thus, in the waterlogging treatment
significant decreases in LA and DW accumulation in root,
stem, leaf, and inflorescence were observed when they
were compared with those under well-watered conditions.
By contrast, under drought a smaller decrease in DW
values was observed (Tables 1 and 2). Although decreases
in LA have been reported as a common effect of drought
stress (Lawlor and Leach, 1985), quinoa plants under
similar conditions do not exhibit a significant reduction in
LA (Table 2). Thus, our results could be in agreement with
the assumption of Zeng et al. (1999), who considered that
sacrifice of non-essential sinks such as root and stem may
be advantageous to survival under the extreme conditions
imposed by waterlogging or flooding, and with the finding
of Kozlowski (1997) who demonstrated that an excess of
soil water affects root and shoot growth as well as leaf
expansion. Also under prolonged drought stress many
plants develop a profuse radicular system in order to help
the water absorption, while under waterlogging or flooding
conditions some species develop a system of adventitious
roots in order to contribute to plant oxygenation (Visser et
al., 1996; Thomas, 1997; Li and Li, 2005). In this context,
increases in root weight ratio (RWR), an indicator of dry
matter allocation (van den Boogaard et al., 1997), have
been reported as a response of plants to drought stress
(Frensch, 1997; Munns, 2002). However, in our study
neither drought nor waterlogging conditions brought about
any changes in this parameter (Table 1). Consequently,
we suppose that in quinoa plants other physiological
adaptation mechanisms could be acting in response to
drought and waterlogging treatments. In addition, several
authors have proposed that leaf number can be used to
characterise plant assimilation capacity (Hoogenboom et
al., 1987). In the present study, however, no difference in
this parameter was observed.
Although accumulation of soluble sugars is particularly
significant in plants undergoing drought stress (Escobar-
Gutierrez et al., 1998; Chai et al., 2001; Munns, 2002; Li
and Li, 2005), high soluble sugar levels have also been
demonstrated in roots under flooding and waterlogging
conditions (Barta, 1988; Huang and Johnson, 1995,
Zeng et al., 1999). Nevertheless, unlike what occurs in
drought stress, sugar accumulation under waterlogging
has been attributed to the need to have an appropriate
carbohydrate supply for survival of plant tissues at the
low oxygen concentration found in waterlogged soils
(Barta, 1988; Guglielminetti et al., 1995; Subbaiah and
Sachs, 2003). However, the possibility that this is due
to the decrease in enzyme activities related to sucrose
cleavage cannot be dismissed. Inhibition of root invertase
and sucrose synthase activities at low oxygen levels has
been reported (Drew, 1997; Zeng et al., 1999). Thus, the
high soluble sugars and starch content observed in leaves
of quinoa plants under waterlogging (Table 4) could
be related to a reduction in carbohydrate sink strength
imposed by lower root respiration. In addition, the higher
soluble protein contents observed under these conditions
could be attributed to anaerobic stress protein (ASPs)
synthesis induced by root hypoxia (Blom and Voesenek,
1996; Subbaiah and Sachs, 2003). However, the higher
values in soluble sugars and proline observed in plants
under drought stress, when compared with their well-
watered counterparts, probably correspond to an osmotic
adjustment more than to a metabolic decrease. In this
context, our results could be in agreement with the find-
ings of Vacher et al. (1994), who demonstrated that quinoa
plants exhibit a high assimilation rate under drought stress.
Consequently, we can conclude that the soil water surplus
constitutes the main limiting factor in quinoa growth
and dry matter partitioning. Our results may have great
significance for farming done in frequently waterlogged
areas or dry lands. Our findings should also be of use in
further agricultural studies on quinoa waterlogging or
drought-tolerance.
Acknowledgements. This work was supported by grants
from Fundacion Miguel Lillo, Consejo de Investigaciones
de la Universidad Nacional de Tucuman (CIUNT), and
Agencia de Promocion Cientifica (PICT Cultivos Andinos
No 21153).
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