Agricultural Water Management 190 (2017) 31–41 2549

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Agricultural Water Management

journal homepage: www.elsevier.com/locate/agwat

Spinach biomass yield and physiological response to interactive

salinity and water stress
Selda Ors a , Donald L. Suarez b,∗
a
Ataturk University, Department of Agricultural Structures and Irrigation, 25240, Erzurum, Turkey
b
USDA-ARS Salinity Laboratory, 450 W. Big Springs Road, Riverside, CA 92507, USA

a r t i c l e i n f o a b s t r a c t

Article history: Critical shortages of fresh water throughout arid regions are forcing growers to decide among the fol-
Received 26 September 2016 lowing options, applying insufficient fresh water, causing water stress, applying saline water causing salt
Received in revised form 4 May 2017 stress or applying some combination minimizing saline water application, causing combined water and
Accepted 7 May 2017
salt stress. A comprehensive approach to manage drought and salinity is to evaluate the impact of water
stress and salt stress individually and then examine their interactions on plant production. To analyze
Keywords:
salinity and water stress responses and their interaction together on spinach growth, an experiment was
Stress
conducted from April 1 to May 21, 2013, using 6 different irrigation waters at electrical conductivity
Drought
WUE
(EC): 0.85, 4, 7, 9, 12, 15 dS m−1 . Soil moisture was recorded by sensors and stress treatments had the
Photosynthesis following soil water matric pressure control (−45 kPa), −200 to −300 kPa, and −400 to −500 kPa. We
Ion composition evaluated three replicates per treatment for yield, vegetative parameters, ion composition, and physio-
logical parameters. The results showed that the spinach yield response to salt and water stress was very
different. Spinach yield initially increased with salinity and subsequently decreased only when the irriga-
tion water was EC 9 dS m−1 and above (osmotic pressure of −310 kPa). In contrast, yield decreased at the
first water stress level (−230 kPa) relative to control. The additional presence of salinity stress decreased
the relative yield response due to water stress. Similarly under water stress the relative yield response
to increasing salinity was reduced. Although no model provided good prediction of stress response, the
best predictive model (relative error) was one that considered the response to multiple stresses as the
product of the response to the individual stresses.
Published by Elsevier B.V.

1. Introduction 2014; Obidiegwu et al., 2015; Zhan et al., 2015). Salinity, another
important abiotic stress limiting crop production is also increasing
Drought and salinity are the two major abiotic stresses dramat- in extent worldwide at an estimated rate of 1.5 million ha per year
ically limiting crop growth and productivity worldwide and the (Eynard et al., 2006) and is estimated to affect 23% of cultivated
area affected by these two stresses is still increasing (Wang et al., lands (Tanji and Wallender, 2012).
2003). The optimal approach to counter drought and salinity stress Drought, salinity, extreme temperatures and oxidative stress are
is development of tolerant crop varieties. Thus, it is important to often interconnected, and may induce similar cellular damage. For
understand the mechanisms of drought and salinity tolerance in example, drought and/or salinity are considered to be manifested
plants, both to develop new varieties and to develop management primarily as osmotic stress, resulting in the disruption of homeo-
practices to minimize the adverse effects. Drought is considered the stasis and ion distribution in the cell (Serrano et al., 1999; Zhu,
primary destructive, crop yield-limiting factor, and detailed knowl- 2001). The apparent similarity of the effects of salinity and drought
edge of its impact on plant growth regulation is crucial (Avramova has raised the question as to whether the same change in the plant
et al., 2015). The adverse impact on crop production may increase as water status caused either by salinity or by drought leads to the
climate change is predicted to increase the frequency and severity same yield reduction (Katerji et al., 2004).
of crop water stress, causing significant yield loss (Trenberth et al., Several studies have separately evaluated the effects of salinity
stress and drought stress expressed as osmotic and matric poten-
tial (De Pascale et al., 2007; Xu and Leskovar, 2015). A few studies
have evaluated the interaction of salinity and water application as
∗ Corresponding author.
related to yield (Shani and Dudley, 2001; Shani et al., 2007), interac-
E-mail address: Donald.Suarez@ars.usda.gov (D.L. Suarez).

http://dx.doi.org/10.1016/j.agwat.2017.05.003
0378-3774/Published by Elsevier B.V.
32 S. Ors, D.L. Suarez / Agricultural Water Management 190 (2017) 31–41

tions of salinity and leaf water potential (Katerji et al., 2009; Katerji Decagon, Pullman, WA, USA1 ) inserted at 10 cm depth. A total of 16
et al., 2011), consecutive salinity and non-saline (PEG) osmotic ECH2 O moisture sensors were used in the study. The ECH2 O mois-
treatments as a proxy for water (matric) stress (Nagy and Galiba, ture sensors were connected to a multiplexer (AM25T, Campbell
1995). However, there is very little information on plant response Sci., Logan, UT, USA), which in turn was connected to a data log-
where the matric stress was measured and controlled. Ahmed et al. ger (CR10X, Campbell Sci.) to record the sensor output. The water
(2013), examined salt and water stress interactions by withholding retention curve was determined using the pressure plate method
irrigation, allowing the water content to decrease to a soil moisture (Klute, 1986). The measured water contents from the sensors were
content of 4% where it remained for 10 more days. Previous stud- then converted to matric potential using the water retention curve.
ies thus either made periodic irrigations to saturate the soil and Drought treatments were designed with soil water matric pressure
then delayed subsequent irrigation, applied less quantities of water targets of D1 (−200 to −300 kPa), treatment D2 (−400 to −500 kPa)
to induce drought without measuring matric potential or induced and control D0 (no water stress, >−45 kPa).
drought at the end of the experiment. In these instances matric Plant photosynthetic rate (Pn), stomatal conductance (gs ), tran-
potentials were either unknown or fluctuated widely during the spiration rate (Tr ) and concentration of intercellular CO2 (Ci ), were
experiments. measured on the third fully expanded upper leaves along the right
Our objective in this study was to determine and then compare abaxial side of the leaf lamina between 10:00-11:00 am one week
the separate and interactive effects of water and salinity stress, before harvest using a portable Li-Cor 6400 Photosynthesis System.
conducting experiments under defined and essentially constant The measurement conditions were leaf chamber PAR (photosyn-
matric and osmotic stress over almost the entire life cycle of the thetically active radiation), 1100 ␮mol m−2 s−1 ; leaf to air vapor
plant (after seedling establishment). We also tested the hypothesis deficit pressure, 1.7–2.6 kPa, leaf temperature 20–22 ◦ C and cham-
that the effect of combined stress on yield can be represented by ber CO2 concentration 400 ␮mol mol−1 . The leaf greenness of the
multiplying the response to the individual stresses. spinach plants was determined by a portable chlorophyll meter
(SPAD-502; Konica Minolta Sensing, Inc., Japan) at the time of the
gas exchange measurements and given as leaf chlorophyll values.
2. Materials and methods SPAD measurements were made on the youngest, fully expanded
leaves, then averaged (Khan et al., 2003).1
The experiment was conducted outdoors with spinach (Spina- We measured the fresh weight of the above ground parts of
cia oleracea L., cv. Racoon) during the interval between 1 April- all plants (three rows) for each replication (three). A plant from
21 May 2013 at Riverside, Calif., (lat.33E58 24 , long. 117E58 12 ). each of three rows and for each replication (9 plants per treatment)
Seeds were sown directly in sand culture tanks, 10 cm apart and was also measured for root length, root weight, shoot height, num-
40 cm between rows. We planted three rows per tank in the outside ber of leaves, and leaf area. We measured the water consumption
large tanks at 1 April. The seedlings were later thinned to 25 plants from each of the reservoirs below the tank and combined these
per row. Sand culture tanks (1.5 × 3 × 2 m deep) were filled with data with the fresh weight yield to obtain the water use efficiency
sand mixed with 10% peat moss (at volume basis) with an average (WUE). WUE (g mm−1 ) was calculated by dividing the total plant
bulk density of 1.38 g cm−3 . Peat moss was added to increase the fresh weight (g) by the actual evapotranspiration (ETa in mm) as
water holding capacity of the sand. The sand mix had an average described by De Pascale et al. (2011). ETa of spinach grown in tanks
volumetric water content of 0.30 m3 m−3 . was calculated using a water balance equation where
Six different irrigation waters (mixed salt composition) at EC;
ETa = V/A (1)
0.85 (control), 4, 7, 9, 12, 15 dS m−1 were used in the experiment
(Table 1). Each plot was irrigated with solutions prepared in indi- and ETa is the actual evapotranspiration (mm), V is the water
vidual reservoirs (1.5 m diameter × 2.2 m deep) having a volume consumed by the crop (mm3 ) and A is the area of the experimental
of 4500 L. Irrigation solutions were pumped from the reservoirs to tank (mm2 ). The V is calculated from,
the tanks and then returned to the reservoirs through a subsurface
drainage system at the bottom of each tank, maintaining a uniform V = Vi − Vf ± S − D (2)
and constant salinity profile. Initial irrigations consisted of nutrient where Vi , and Vf and are the initial and final volumes (mm3 )
in the
solution made up in Riverside California U.S.A. tap water with nutri- reservoir system, respectively, D is the water volume discharged
ents added as (in mM): 2.5 Ca (NO3 )2 , 3.0 KNO3 , 0.17 KH2 PO4 , 1.5 out of the system and S is the change in sand tank moisture
MgSO4 , 0.05 Fe as sodium ferric diethylenetriamine pentaacetate content (mm3 ). Since we have a closed system (tank plus reser-
(NaFe-EDTA), 0.023 H3 BO3 , 0.005 MnSO4 , 0.0004 ZnSO4 , 0.0002 voir) with no discharge, D is zero. The experimental design was
CuSO4 , and 0.0001 H3 MoO4 . This solution served as the base nutri- a randomized complete block design with three replications for
ent solution. The base nutrient solution without added salts served yield, vegetative parameters, ion composition, and physiological
as a non-saline control (<1.0 dS m−1 ) in all experiments. As the parameters. All of the data obtained from the measurements were
water from each of the sand tanks drained back into its own irriga- evaluated statistically by analysis of variance to compare the effects
tion reservoir we were able to measure water use in each tank by of drought levels and irrigation waters using SPSS package software
measuring water volumes in the irrigation reservoirs. (SPSS, 2004). The differences among the means were compared
Final electrical conductivities of the saline irrigation waters using the Duncan multiple tests. General Linear Model analysis was
(ECiw ) of 4, 7, 9, 12, 15 dS m−1 were achieved by adding CaCl2 , performed to determine the relationship between selected param-
MgCl2 , NaCl2 , Na2 SO4 and base nutrients to tap water (Table 1). eters.
For calculation of the treatment salt concentrations we used the In order to evaluate the abiotic stress models with an additional
EXTRACT CHEM model (Suarez and Taber, 2012) that predicts the data set, we included data from a preliminary experiment con-
EC and osmotic pressure of input solution compositions. Salin- ducted during December 2012- March 2013. The general details of
ization was initiated after the first pair of true leaves was fully the salt tolerance aspect of the experiment are provided in Ors and
expanded on all the plants. Salts were added in 4 equal increments
over a period of 4 days to avoid osmotic shock to the seedlings.
Measurements of the water content (␪) of the substrate 1
Mention of trade names or commercial products in this publication is solely for
were accomplished using calibrated (ln(␪) = −6.99 + 16 V − 9.9V2, the purpose of providing specific information and does not imply recommendation
R2 = 0.91) dielectric soil moisture sensors (ECH2 O-10 probes, or endorsement by the U.S. Department of Agriculture.
 S. Ors, D.L. Suarez / Agricultural Water Management 190 (2017) 31–41 33

Table 1
Irrigation water composition of the salinity treatments.

Salinity level ECi (dS m−1 ) OP (kPa) Ca2+ Mg2+ Na+ SO4 2− Cl− K+ NO3 − K+ /Na+
−1
(mmolc L )

0.85 −40 3.44 0.81 1.75 1.45 0.92 3.2 5.2 1.82
4.0 −160 8 2 29 19.5 19.5 3.2 5.2 0.11
7.0 −250 17 8 48 36.5 36.5 3.2 5.2 0.07
9.0 −310 21 12 63 48 48 3.2 5.2 0.05
12.0 −450 30.2 15 87.7 64.5 65.3 3.2 5.2 0.036
15.0 −590 28.5 20 118 82.1 84.3 3.2 5.2 0.027

Fig. 1. ET0 and average daily temperature (obtained from local CIMIS station) as related to days from planting to harvest (Ors and Suarez, 2016).

Suarez, (2016). In addition to the data reported earlier on salin-

ity response, we also had treatments that combined salinity and
drought stress. The salinity levels for this experiment were 0.85,
4.0, 7.0, and 9.0 dS m−1 (Ors and Suarez, 2016). The drought lev-
els were similar to those of the main experiment described above,
D0, D1 and D2 levels correspond to soil water matric pressure of
>−45 kPa, −200 to −300 kPa, and −400 to −500 kPa, respectively.

3. Results and discussion

The climate data were obtained from CIMIS weather station

(California Irrigation management Information System, Weather
station no. 44, UC Riverside) that provides hourly calculations. Daily
mean ET0 values and growing periods as number of days are pre-
sented in Fig. 1 (Ors and Suarez, 2016). The ET0 values show the Fig. 2. Water content for water stress treatments (D0, D1, and D2) of the tanks
daily fluctuation and the general trend of increasing ET0 with time, measured by sensors.
which relates primarily with increasing air temperature, as shown
in Fig. 1.
As shown in Fig. 2 we were able to maintain relatively con-
stant water content for each of the three drought treatments. The
mean matric potentials in the root zone were calculated from
the water content (Fig. 2) and the water retention curve (Fig. 3).
The mean water contents were 0.16 (m3 m−3 ), 0.11 (m3 m−3 ) and
0.09 (m3 m−3 ), and the mean matric potentials were −44.6 kPa,
−231 kPa, and −446 kPa for the D0, D1 and D2 drought (matric)
stress treatments respectively.
The changes in water content and resultant salinity fluctuations
between the wetting and drying periods were relatively minor.
The volumetric water fluctuation in the non drought treatments
of between 0.17 after irrigation and 0.15 just before irrigation rep-
resents a change of 12%, in both water content and in EC soil water
(ECsw ), thus a mean ECsw of 6% greater than the ECiw . In a simi-
lar manner for the drought treatments D1 and D2, the volumetric
water content fluctuation was between 0.10–0.13 and between
0.08-0.10 respectively, corresponding to mean ECsw values being
6.5% and 5.% respectively greater than ECiw values. Fig. 3. Soil water retention curve determined with pressure plate apparatus.
34 S. Ors, D.L. Suarez / Agricultural Water Management 190 (2017) 31–41

Table 2 than the control. Yield loss at water stress of −230 kPa suggests
Two- way ANOVA of effects of drought (D) and salinity (S) and their interactions
that spinach is less sensitive to water stress than other vegetable
(DxS) on spinach plant.
crops, as they generally experience yield loss in the range of −20
Dependent variables D S DxS to −60 kPa (Taylor and Ashcroft, 1972).
Fresh weight 365.14*** 114.11*** 27.63*** Under the first level of water stress (D1), yields decreased rela-
Dry weight 185.37*** 70.71*** 15.08*** tive to the no water stress treatments (D0), at all salinity levels as
Shoot height 602.29*** 203.10*** 23.01*** shown in Fig. 4. However, the D1 treatments had no sharp yield loss
Root length 48.39*** 14.16*** 6.73***
due to salinity until EC 12 dS m−1 (Fig. 4). The highest fresh yield
Root weight 129.84*** 70.00*** 13.16***
Leaf number 40.28*** 32.11*** 16.43*** in D1 treatments were obtained at 7 dS m−1 and a large decrease
Leaf area 602.19*** 204.00*** 23.01*** occurred in yield at EC 12 dS m−1 and a further decrease at EC
Photosynthetic rate 21.29*** 27.09*** 3.98*** 15 dS m−1 .
Stomatal conductance 15.61*** 81.79*** 10.04***
Under more severe water stress (D2) the yields were lower
Chlorophyll content 2.56 ns 12.45*** 1.57 ns
under low salinity (relative to D0 and D1), but at high salinity the
F-values. NS: nonsignificant, *** ␣ = 0.001. yields were similar in the D1 and D2 treatments (Fig. 4). Addition-
ally under D2 water stress conditions, the highest salinity yields
were not significantly different than those of the control (Fig. 4).
3.1. Growth response to stress Thus, for spinach, moderate water stress resulted in reduced yield
but also reduced impact of salt stress as compared to non-drought
There is extensive information on the reduction in growth conditions.
related to salt stress for a large number of crops (Maas and Hoffman, The data showed that some salt stress improved yield, but
1977; Greive et al., 2012). Reduction in fresh weight due to drought that with increasing water stress the optimal salinity level was
stress has also been reported earlier for a number of plant species shifted to higher levels of salinity (osmotic stress). Additionally,
(Taylor and Ashcroft, 1972; Petropoulos et al., 2008; Álvarez et al., yield response to salinity and water stress were very different. At
2011; Čereković et al., 2014). Both salt (Greive et al., 2012) and moderate salinity stress (−250 kPa) yield increased relative to the
drought stress (Taylor and Ashcroft, 1972) vary widely among control, while at comparable water stress yield was decreased. At
plants, thus requiring crop specific information for modeling and higher salinity stress (−450 kPa) yield was only slightly below the
predictions. control (in the absence of water stress) while comparable water
The two-way ANOVA presented in Table 2 showed that there potential stress (in the absence of salt stress) were 65% lower than
were highly significant differences in fresh weight related to salin- the control. Thus spinach fresh weight was more adversely affected
ity and to drought. The interaction of salinity and drought was by water stress that salt stress at comparable pressure potentials.
also highly significant. Thus subsequent statistical analysis com- Additionally we conclude from the results of this experiment
pared data at either the same drought stress or the same salinity. that moderate salinity even in the presence of moderate water
As shown in Fig. 4, under, well watered conditions (D0), the plant stress increases yield of spinach raccoon cv. These results com-
fresh weight initially increased at moderate salinity levels and then pliment earlier reports in the absence of drought that show that
started to decrease. The yield decrease became significant at EC spinach has higher yield under mild salinity conditions (Downton
9 dS m−1 and was not significantly lower than the control until EC et al., 1985; Mazloomi and Ronaghi, 2012; Osawa, 1963; Speer and
15 dS m−1 . The highest fresh yield in D0 treatments was obtained Kaiser, 1991; Yousif et al., 2010; Yamada et al., 2016; Ors and Suarez,
at EC 4.0 dS m−1 and the lowest was at 15 dS m−1 . The observa- 2016)
tion that initial increases in salinity result in increased yield has
also been noted by others. For example, Yamada et al. (2016) found 3.2. Vegetative parameters
that sodium application increased yield of amaranthaceous plants
including Swiss card, beet and spinach, with spinach yield increas- The vegetative parameters, dry weight, shoot height, root
ing with NaCl application of up to 80 mmol L−1 . length, root weight, leaf number and leaf area of each treatment
The significant yield loss in our experiment below control yield are shown in Fig. 5. Dry weight of the spinach plants (Fig. 5a) had
occurred above ECiw 9 dS m−1 . Using the relationship determined the same trends with salinity and drought as fresh yield results
for our soil media, where volumetric water content of the saturation (Fig. 4). All vegetative parameters showed highly significant dif-
extract = 0.35 and the average volumetric water content of the non ferences with salinity and drought treatments and all salinity x
water stressed treatments after irrigation was 0.17 (see Fig. 2) then drought interactions were also highly significant (Table 2). We thus
for the control and salinity treatments ECe = 0.486x ECsw , where separate the salinity and drought treatments and analyze salinity
ECsw is the EC of the soil water in situ. The EC of the irrigation water effects at the three drought levels and drought effects at the individ-
increased slightly over time as related to concentration of salts dur- ual salinity levels. Increasing salinity resulted in first significantly
ing the experiment. Measured volume losses from the reservoirs increasing and then significantly decreasing shoot height (Fig. 5b),
resulted in mean salinity increases ranging from 7% for control to similar to plant fresh weight relations, with the effect being greater
2% for D2. Correcting for concentration increases over time in the under non-drought conditions. As shown in Fig. 5b shoot height was
reservoirs and changes in EC between irrigation cycles (ECsw 6% significantly greater under non-water stress treatment (D0) than
greater than ECiw ), the non drought ECsw values exceed the initial water stress treatments (D1, D2) for all salinity levels and D1 treat-
ECiw values by 13%. Thus the irrigation water of 9 dS m−1 EC corre- ments shoot heights were significantly greater than those of D2
sponds to an ECe of 4.9 dS m−1 .This value is greater than the salinity treatments for all but two salinity levels. Under severe water stress,
threshold value of EC = 2.0 dS m−1 cited in Greive et al. (2012) but intermediate salinity concentrations still had a favorable effect on
less than the value of 6 dS m−1 calculated from the hydroponic data shoot height but most differences were not significant (Fig. 5b).
of Yamada et al. (2016). However Greive et al. (2012) and Yamada Water stress caused significantly longer root length (Fig. 5c)
et al. (2016) did not specify the variety used and varietal differences across all salinity treatments, as compared to the non-stressed
may be large. Also, Ors and Suarez (2016) determined that spinach control treatment (D0). Root weight significantly decreased with
salt tolerance was seasonally dependent. increasing water stress for all salinity levels (Fig. 5d), however it
As shown in Fig. 4 in the absence of salt stress, water stress first increased then decreased significantly with increasing salin-
decreased yield. The D2 treatment was highly significantly lower ity, for all water stress treatments. These length and weight results
 S. Ors, D.L. Suarez / Agricultural Water Management 190 (2017) 31–41 35

Fig. 4. Spinach fresh weight yield as related to irrigation water salinity under different water stress conditions. Yield data from the D0 treatments is taken from Ors and Suarez
(2016). The D0, D1 and D2 treatments correspond to water potentials of −44.7 kPa,–231 kPa, and −446 kPa, respectively. Bars with different letters significantly differed at
P < 0.001. Different lower case letters indicate significant differences in fresh weight related to salinity at the same drought level. Different capital letters indicate significant
differences related to water stress at the same salinity level.

Fig. 5. Effects of increasing irrigation water salinity on dry weight, shoot height, root length, root weight, leaf number, leaf area of spinach under different drought stress levels,
The DO, D1 and D2 treatments correspond to water potentials of −44.7 kPa, −231 kPa, and −446 kPa, respectively. Values represent means ±SE. Bars with different letters
significantly differed at P < 0.001. Different lower case letters indicate differences related to salinity at the same drought level. Different capital letters indicate differences
related to water stress at the same salinity level.
36 S. Ors, D.L. Suarez / Agricultural Water Management 190 (2017) 31–41

indicate that there were changes in root structure to adapt to conditions Na, K, and Cl were reduced with water stress rela-
drought stress. Deep rooting was found to be a critical factor for tive to the non-stressed condition. Similarly, both salinity and
drought resistance, influencing the ability of the plant to absorb water stress significantly affected the Mg content of spinach leaves
water from the deeper layers of the soil (Franco et al., 2006, 2011). (Table 3), with Mg increasing with increasing salinity, consistent
Under water stress, roots develop a capillary structure and elongate with increasing Mg in the irrigation water. The intermediate water
to obtain water from depth. Thus it seems reasonable that under stress treatments (D1) with irrigation waters of EC 12 and 15 dS m−1
non water stress conditions root structure would be shorter and resulted in the highest plant Mg contents.
thicker. In agreement with this, thinner roots under drought stress
were reported earlier for Silene vulgaris by Franco et al. (2008).
Leaf number first significantly increased then significantly 3.4. Gas exchange measurements
decreased with increasing salinity, but the differences were rel-
atively small (Fig. 5e). Leaf number also decreased slightly (but Gas exchange measurements conducted two weeks before har-
significantly) with increasing water stress across all salinity lev- vest are shown in Fig. 6. Irrigation water salinity and water stress
els (Fig. 5e). Plant leaf area increased significantly with initial strongly affected leaf gas exchange parameters. Pn, Tr and gs were
increase in salinity level under non-water stress conditions and highly significant, as was the interaction (Table 2). Chlorophyll con-
then decreased significantly and rapidly further increase in salin- tent was highly significant for salinity but not for water stress
ity (Fig. 5f). Water stress decreased the leaf area as compared to (Table 2). As shown in Fig. 6a, photosynthesis first increased slightly
non-water stress treatment but even under severe water stress (non-significant) then subsequently decreased significantly in the
conditions (D2) intermediate salinity levels significantly increased non water stressed treatments. It is reported that photosynthesis
plant leaf area. Reduced plant size, leaf area, and leaf area index is among the primary processes affected by salinity (Munns et al.,
(LAI) are all plant mechanisms for moderating water use and reduc- 2006), and may be responsible for at least part of the yield reduction
ing injury under water stress (Blum, 2004; Mitchell et al., 1998). caused by salinity (Prior et al., 1992; Munns, 2002). Our photosyn-
thesis data are consistent with our yield data, in that there was no
reduction in both yield and photosynthesis until EC above 7 dS m−1 .
3.3. Ion concentrations However, in our results under water stress there was a reduc-
tion in yield but generally no reduction observed in photosynthesis
The content of all major ions in spinach leaves was signifi- (expressed per leaf area) under both saline and non-saline con-
cantly affected by salinity and water stress treatments (Table 3), but ditions (Fig. 6a). We conclude that for spinach, the yield loss
concentrations did not decrease to values that indicate deficiency that occurs with water stress is not attributed or associated with
(except for K and Mg under non-saline, high drought treatment). decreases in leaf photosynthesis rate. This is in contrast to ear-
Under well-watered conditions, Na and Cl increased with increased lier findings with chard (Delfine et al., 2003). They considered that
salinity treatments and K decreased. The irrigation water had a horticultural crops in Mediterranean climates have high growth
constant K level thus decreased leaf K was likely related to the rates sustained by high gas exchanges and thus, they are particu-
decreased K/Na ratio in the irrigation water (Table 1) and thus larly vulnerable to drought stress. In their experiment the reduction
plant ion competition. Spinach has been reported to utilize Na in growth rate occurred at the same time as the reduction in gas
for osmotic adjustment as well as K (Sugiyama and Okada, 1988). exchange.
Water stress in the absence of salt stress resulted in a small decrease Changes in transpiration rate in each treatment and experi-
in Ca concentration and decreased Mg, Na and K. Under saline ment are presented in Fig. 6b; as expected salt stress significantly

Fig. 6. Effects of increasing irrigation water salinity on Pn, Tr, gs , and chlorophyll content of spinach under different water stress levels, The DO, D1 and D2 treatments
correspond to water potentials of −44.7 kPa, −231 kPa, and −446 kPa, respectively. Bars with different letters significantly differed at P < 0.001. Different lower case letters
indicate differences related to salinity at the same drought level. Different capital letters indicate differences related to drought at the same salinity level.
 S. Ors, D.L. Suarez / Agricultural Water Management 190 (2017) 31–41 37

Table 3
Mineral composition of spinach leaves.

Drought Treatments EC Ca Mg Na K Cl S

dS m−1 mmol kg−1

D0 0.85 248a 628b 216e 3021a 269d 176c

4.0 188d 709a 632d 2937a 88317c 179c
7.0 204bcd 731a 903c 2998a 999bc 189b
9.0 220abc 768a 1278b 2346b 942bc 188b
12.0 223ab 737a 1386b 2329b 1114b 198a
15.0 192cd 733a 1752a 1994c 2300a 197a
D1 0.85 202bc 393d 117e 2430ab 433d 151d
4.0 208bc 612c 537d 2491ab 2387b 190cd
7.0 242ab 764ab 1043c 2674a 3197a 214bc
9.0 173c 705bc 13690b 2357b 1388c 235a
12.0 232ab 882a 10221c 2222b 1229c 228ab
15.0 255a 832a 1524a 1831c 1345c 218bc
D2 0.85 203bc 289c 113d 1912c 299b 88d
4.0 231ab 668b 784c 2497a 734ab 165bc
7.0 195c 623b 78079c 2219b 1382a 249a
9.0 227ab 643b 976b 1861c 1178a 204b
12.0 244a 794a 1371a 1971c 1338a 224ab
15.0 198c 816a 1477a 1822c 1346a 253a

Different letters indicate differences related to salinity at the same drought level. Values followed by the same letter are not significantly different at P ≤ 0.001.

decreased transpiration, and at all drought stress levels. The effect WUE. This means that for spinach there can be not only significant
of salinity under severe water stress (D2) was more evident com- yield increase but also significant water savings when irrigating
pared to effect of salinity under well- watered conditions (D0). with moderately saline water.
Differences related to drought under non-saline conditions were Under conditions of high salinity WUE is reduced, thus more
not significant (Fig. 6b). The stomatal conductance (gs ) data (Fig. 6c) water is required than assumed by the relation
was very similar to the Tr data, except that the gs decrease with
ETa Ya
increasing salinity was more pronounced. The severe reduction = (3)
in Tr and gs in response to salinity might represent an adaptive ETc Ymax
mechanism to cope with excess salt rather than merely a nega- Where ETa is measured ET, ETc is the crop ET at maximum yield and
tive consequence of it (Flanagan and Jefferies, 1989; Tattini et al., Ya and Ymax are the actual and maximum yield, respectively.
2002). Water stress did not reduce Tr and gs under non saline In contrast, there was no consistent trend in WUE related to
conditions (Fig. 6b and 6c), however salinity stress caused a sig- water stress, and significant effects occurred mostly at EC 7 and
nificant decrease for each drought level. These results indicate 9 dS m−1 where stress increased WUE. Thus water stress does not
that the spinach plant response to water and osmotic stress is appear to be a viable general strategy for saving water when grow-
indeed different, in agreement with the yield data discussed above. ing spinach. This is in contrast to the findings of Franco et al. (2006)
The sharp decrease in stomatal conductance with increased saline and Fernández et al. (2006) who reported higher WUE for drought
water irrigation even under severe water stress (D2) indicated that stressed plants. A likely explanation of this difference is that their
under water stress, salinity was still the more limiting factor on gs. results are expressed in terms of yield and water application while
Decreased stomatal conductance under salinity has been reported we measured water consumption under stress.
on spinach earlier (Delfine et al., 1998; Yousif et al., 2010).
SPAD values are proportional to the amount of chlorophyll
3.6. Modeling plant yield response to combined salinity and
present in the leaf (Ling et al., 2011). We observed a general
water stress
increase in chlorophyll with increasing salinity for all three water
stress treatments, as shown in Fig. 6d. Increasing water stress had
One model developed for predicting plant response to salinity
no statistically significant effect on chlorophyll content (Fig. 6d).
and drought stress is that of additive stress (Childs and Hanks, 1975)
Chlorophyll content is expected to decrease under stress condi-
where the response is related to the combined matric and osmotic
tions. However, an increase in chlorophyll content of the plant
potential; in this instance the following equations can be utilized,
under water stress was observed earlier with purslane (Rahdari
et al., 2012) and spinach (Xu and Leskovar, 2015). Our results are 1
also consistent with the almost constant chlorophyll content under ˛s =  b (4)
h
salt stress observed with cucumber (Yildirim et al., 2008) and sun- 1+ h50
flower (Liu and Shi, 2010).
S(h) = (˛s (h))Sp (5)

3.5. Water use efficiency Where ␣s is the dimensionless stress response function (relative
yield) h is the sum of osmotic and matric stress and h50 is the stress
As shown in Fig. 7 there were large differences in WUE related value at which there is a 50% yield loss, and b is an empirical fitting
to salinity. In all instances an initial increase in salinity increased parameter generally set to 3.0.
the WUE to approximately double the value of the control (Fig. 7a). An alternative model considers the response to stress to be addi-
Subsequent increases in salinity resulted in decreased WUE. The tive (van Genuchten, 1987). Thus
WUE did not change in a simple manner with increasing salinity
1
but it can be explained if we compare WUE (Fig. 7) to the yield ˛ s =  b (6)
data (Fig. 4). At each water stress level the WUE was positively and 1+ h
h 50
well related to the yield, moderate salinity increased both yield and
38 S. Ors, D.L. Suarez / Agricultural Water Management 190 (2017) 31–41

Fig. 7. Water use efficiency as related to salinity and water stress. Bars with different letters significantly differed at P < 0.001. Different lower case letters indicate differences
related to salinity at the same drought level. Different capital letters indicate differences related to drought at the same salinity level.

1 this case dY/dT is constant but the WUE decreases with decreasing
˛s =  b (7)
h
yield (because of the intercept of a finite ET at zero yield).
1+ h50 There is also considerable data that indicates that in a similar
manner, relative yield and relative transpiration are also linearly
And in this case,
related (Nimah and Hanks, 1973; Bresler and Hoffman, 1986), how-
S(h , h␸ ) = [1 − ((˛ (h␺ ) − 1) + (1 − ␣␸ (h␸ )))]Sp (8) ever this need not indicate that Y/ETa . is constant. Unlukara et al.
(2010) fit a linear relation (r2 = 0.97) between (ETmax − ETa)/ETmax
where Sp is the potential water uptake rate and S is the predicted and Ymax − Ya/Ymax , with a decrease in WUE from 4.8 g/L under non-
uptake rate. A third model, used in the UNSATCHEM model (Suarez saline conditions to a WUE of only 2.5 at EC = 7 dS m−1 for eggplant
and Simunek, 1996) uses a response function where the product of (fruit yield). A similar increase in WUE with increasing salinity can
the response to water and salt stress is calculated, using different be calculated from the yield- ET data given in Skaggs et al. (2006) for
response functions for matric and osmotic stress (h␺50 , and hϕ50 alfalfa and wheatgrass; they also obtain a linear relation between
respectively). yield and ET (r2 = 0.85).
S(h , h␸ ) = (˛ (h␺ )(˛␸ (h␸ )S p (9) In addition, other factors have been shown to greatly impact
WUE, such as nutritional status. Ritchie (1983) showed that increas-
Further, we can utilize the following yield function (Steward and ing N fertilization from 90 to 134 kg ha−1 of N caused a change in
Hagan, 1973; Suarez and Simunek, 1996) instead of Eq. (3) Y/ET of 15%; increases in P fertilization on wheat caused comparable
  changes as well.
Ya ETa
= 1 − B0 1− (10) The results of our study (Fig. 7) for spinach as well as studies with
Ymax ETp
other crops (Semiz et al., 2014) indicate that WUE is not constant
where B0 is the slope of the relative yield versus ETa -ETc and can vary considerably in relation to salinity. The differences
Using Eq. (10) we can correct for non-constant WUE. That WUE is between measured water consumption and calculated values using
not constant for spinach yield under salinity is demonstrated above Eq. (3) may be important if one uses yield to calculate water con-
in Section 3.5. Although it is convenient to characterize salt stress in sumption and then in turn matric stress, as most researchers have
terms of the ECe, comparison among experiments is feasible only in done.
well watered experiments of comparable soil texture. As described The response of yield to salt stress in the absence of matric stress
by the relationships above, plants respond to in situ salt and matric is shown in Fig. 8a. The yield increases from −40 kPa to −200 kPa
stress, hence modeling response is in units of osmotic or matric and then decreases, with hϕ50 at −465 kPa (from the fitted line). We
potential. used the fitted equation,
Dudley and Shani (2003) examined the relationship between  2
water application, salt stress and yield for a field melon experi- −( −x−216.234 )
Ya/Ymax = 176.436e 255.371
(11)
ment. They modeled the yield by optimizing the values of h␺50 , and
hϕ50 , assuming water uptake to be directly proportional to biomass to predict relative yield from osmotic pressure. The response to
yield. The soil h␺50 was thus calculated based on the water con- matric stress in the absence of salt stress shows a maximum yield
sumption estimated form the yield, and was not measured. The under no stress and a h␺50 at −400 kPa. Preliminary analysis sug-
UNSATCHEM formulation (Eq. (9)) provided a satisfactory repre- gests that matric potential stress is more detrimental that osmotic
sentation of their data. Another important difference between our salt stress. However, spinach is relatively unique in that low salin-
experiments and those of Dudley and Shani (2003) is that they var- ity does not produce the optimal yield and some increase in salinity
ied the quantities of water applied, independent of salinity stress is beneficial, thus the matric and osmotic stress functions are very
while we controlled water content (and thus water stress) rather different.
than irrigation quantities. Using the relationships in Fig. 8a and b as stress response func-
There is considerable data including that for corn, alfalfa, tions we next compare results from the combined stress treatments
sorghum (James et al., 1982) that indicate that yield and ET are lin- with the various model predictions. We examine only the data with
early related when insufficient rain or irrigation water is applied. In both osmotic and matric stress, meaning we did not use any of
 S. Ors, D.L. Suarez / Agricultural Water Management 190 (2017) 31–41 39

Fig. 8. The response of yield to salt stress in the absence of matric stress (a) and the response of yield to water stress in the absence of osmotic stress (b).

Fig. 9. Predicted and observed relative yield where predictions are based on a) adding the measured matric and osmotic potential and predicting yield from the osmotic
potential relationship, Eq. (5), b) adding the osmotic potential response and the matric potential response using the regression relationships from Fig. 8 using Eq. (8) and c)
multiplying the individual matric and osmotic response functions (Fig. 8) and using Eq. (9).

Table 4 ual responses from the stresses (Fig. 9b) results in over prediction
Fresh weight per plant (g) of the suplimentary spinach experiment (given as Exp1)
of relative yield. Using the multiplicative model improved yield
for combined water and salt stress.
predictions but there was still over prediction for the high rela-
Drought treatments kPa Salinity treatments (dS m−1 ) tive yield values (where the salinity response provides yield above
4 7 9 the control values). We attribute this relatively marginal prediction
capability to the complex spinach yield response at low salinity
Fresh weight (g)
(Fig. 8a). Predictions can be greatly improved by regression of the
D1 (−200) to (−300) 113.2 93.3 89.7 predictions and observations in Fig. 9a, b and c, but we attempted to
D2 (−400) to (−500) 55.9 62.4 59.
independently predict relative yield. Additional experiments with a
crop that has a less complex salinity response would enable further
the data shown in Fig. 8a and b, data where only one stress was evaluation and development of a combined abiotic stress response
imposed. Shown in Fig. 9a is the predicted and observed results model.
from the additive water and matric potential model (Eq. (5)), Fig. 9b
shows the results where the stresses are added (Eq. (8)), and Fig. 9c
shows the results where the individual response functions are mul- 4. Conclusion
tiplied (Eq. (9)).
We present spinach fresh yield data from this experiment Yield and physiological responses of Spinach plants (Spinacia
(Fig. 4), as well as results from a preliminary spinach experiment oleracea L., cv. Racoon) to osmotic and matric stress were very dif-
under similar conditions (data shown in Table 4), along with the ferent. Yield did not correlate in a simple manner with salinity. At
predictions based on the three models. moderate salt stress (−250 kPa) yield increased while at compara-
Using Duncan test we determined that for the combined data ble water stress yield decreased relative to the control. At high salt
sets from both experiments, there were no significant differences stress (−450 kPa) relative yields were only slightly below the con-
between model a (added potentials) and model b (added response) trol while at comparable water stress relative yields were 65% lower
but model c (multiplicative response) was significantly different than the control. Plants grown under water stress also experienced
(P < 0.05) than model a and b. Also, model c had the smallest mean% less sensitivity to salt stress than plants grown under non drought
error as compared to the data. Similar results were obtained using conditions, consistent with salinity response data observed earlier
data only from the main experiment (labeled Exp 2 in Fig. 9). In for other abiotic stresses. WUE initially increased with increasing
all instances (combining all data or analyzing the experiments salinity, then decreased in a manner mirroring the yield response to
separately) when ranking the fit model c had the smallest mean salinity. There was little effect of water stress on WUE. Increases in
error followed by model b and then model a. Adding the individ- WUE under water stress were observed only at intermediate salin-
40 S. Ors, D.L. Suarez / Agricultural Water Management 190 (2017) 31–41

ity, thus water stress is not likely viable for saving water unless Katerji, N., Mastrorilli, M., Lahmer, F.Z., Maalouf, F., Oweis, T., 2011. Faba bean
salinity is in the ECe range of 3–4.5 dS m−1 . productivity in saline–drought conditions. Eur. J. Agron 35, 2–12.
Khan, W., Prithiviraj, B., Smith, D.L., 2003. Photosynthetic responses of corn and
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