Physiological Indices for the Selection of Drought-Tolerant Safflower Genotypes for Cultivation in Marginal Areas
1
East Azarbaijan Agricultural and Natural Resources Research and Education Centre, Horticulture and Crops Research Department, Agricultural Research, Education and Extension Organization (AREEO), Tabriz 5355179854, Iran
2
East Azarbaijan Agricultural and Natural Resources Research and Education Centre, Plant Protection Research Department, Agricultural Research, Education and Extension Organization (AREEO), Tabriz 5355179854, Iran
3
Institute of Forest Sciences, Faculty of Civil Engineering and Environmental Sciences, Białystok University of Technology, ul. Wiejska 45E, 15-351 Białystok, Poland
4
University Institute of Teacher Education (IUFE), University of Geneva, 24 Rue du Général-Dufour, 1211 Geneva, Switzerland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(12), 5106; https://doi.org/10.3390/app14125106
Submission received: 13 April 2024
/
Revised: 8 June 2024
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Accepted: 10 June 2024
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Published: 12 June 2024
(This article belongs to the Section Ecology Science and Engineering)
Abstract
:Safflower is known as a tolerant plant to abiotic stress factors. This study was conducted to introduce some physiological indices to improve drought-tolerant safflower genotypes for cultivation in marginal and arid areas. Six safflower genotypes were studied for two years (2017–2019) in the East Azarbaijan Agricultural and Natural Resources Research and Education Centre of Iran under non-stressed and low-water conditions from flowering to seed maturity. The occurrence of water deficits led to a significant decrease in relative water content (RWC), stomatal conductance (gs), osmotic adjustment (Oadj), water potential (WP) and agronomic water use efficiency (WUEa) and an increase in the water stress index (CWSI). In addition, the values of these traits differed significantly between the safflower genotypes. The correlations between the physiological traits and seed yield were significant. The regression relationships between seed yield and the above traits showed that CWSI, WP and WUEa had a strong relationship with seed yield under normal (R2 = 0.854, 0.801 and 0.856, respectively) and water deficit conditions (R2 = 0.931, 0.877 and 0.900, respectively). It can be concluded that the CWSI, WP and WUEa indices are able to select high-yielding and drought-tolerant safflower genotypes for the late season. Among the components of seed yield, the number of capitula per plant (r = 0.86) and seeds per capitula (r = 0.92), which were positively and significantly correlated with seed yield, played the main roles in the formation of seed yield. The Golemehr and Mec.295 genotypes achieved higher seed yields under normal (4676 and 4961 kg h−1, respectively) and water deficit conditions (3211 and 3385 kg h−1, respectively) and can be recommended for cultivation in marginal and arid areas.
1. Introduction
Among the various abiotic stress factors, water deficit is the one that most affects plant productivity, especially in marginal areas. Safflower, a deep-rooted plant of the Asteraceae family, is tolerant to dry and saline conditions [1]. It has been reported that safflower plants can grow under water deficit without a significant decrease in seed yield [2]. As a drought-tolerant crop, safflower produced a similar seed yield under irrigated and non-irrigated conditions in semi-arid (258.9 mm rainfall per year) and highland (1850 m above sea level) climates in Eastern Anatolia, Turkey [3]. The Crop Water Stress Index (CWSI) is used to quantify the water status of plants. Pasban Eslam [4] pointed out that leaf temperature is a suitable criterion for the selection of drought-tolerant safflower genotypes. Relative water content (RWC) is an important physiological parameter for measuring the drought stress tolerance of plants [5]. Irani et al. [6], who studied sainfoin (Onobrychis viciifolia Scop.) genotypes under drought stress and non-stressed conditions, reported that water deficit significantly decreased RWC, which affected forage production. Lovelli et al. [7] showed that seed yield of safflower was greatly reduced under drought stress when 100, 75, 50, 25 and 0 per cent of maximum evapotranspiration was restored. The results of a study showed that wheat genotypes with lower grain yield under severe water deficit conditions had lower water use efficiency (WUE), stomatal conductance and transpiration than others [8]. Evaluation of the growth and performance of durum wheat and triticale in the Mediterranean climate showed that triticale with higher stomatal conductance and transpiration efficiency had higher water and radiation efficiency in the dry season [9]. Osmotic adaptation (Oadj) is considered an important physiological mechanism of adaptation to water deficit in many crops [10]. It appears that Oadj may be an important mechanism of drought tolerance in plants such as safflower under drought conditions. Turner et al. [11] studied Oadj in chickpea lines and progeny from their crosses under late drought conditions and found that OA does not contribute to seed yield. They concluded that Oadj is not a suitable trait for the selection of water deficit-tolerant genotypes of chickpea. Kar et al. [12] found that the highest water use efficiency in safflower with mean values of 3.04 and 1.23 kg ha−1 mm−1 was achieved with three and one supplemental irrigation, respectively. The additional irrigation also had a significant influence on grain yield. Thus, a grain yield of 392 kg ha−1 was obtained with one irrigation and the yield was 48% higher with two irrigations than with a single irrigation, while a grain yield of 1258 kg ha−1 was obtained with three irrigations, 220% higher than with a single irrigation. The results of evaluation of safflower cultivars under water deficit stress at different reproductive stages showed that drought during flowering and bud formation resulted in a decrease in water use efficiency by 28.9 and 18.3 percent, respectively [13]. Faraji et al. [14] reported that WUE can be used as an indirect trait for the selection of water deficit-tolerant genotypes of oilseed rape (Brassica napus L.). The results of the study of safflower genotypes under pre-seasonal and seasonal irrigation showed that the differences between genotypes in WUE were insignificant and small [15].
Saini and Westgate [16] pointed out that all generative subphases of safflower respond to water deficit. Salem et al. [17] reported that moderate and severe drought stress significantly reduced the performance of safflower. The results of the evaluation of the six safflower lines under normal and drought conditions showed significant differences in leaf chlorophyll content, RWC, water potential and seed yield. The ability of some safflower lines to produce higher seed yield under drought conditions with higher leaf chlorophyll content, RWC and water potential was associated with their genetic traits [18]. Safflower is known to transfer a large percentage (65–92%) of its pre-flowering stored assimilates into seeds under drought stress at the end of the season [19]. The results of the evaluation of safflower cultivars under normal irrigation and drought stress during the seed-filling phase showed that water deficits significantly reduced seed yield in all genotypes by decreasing all components [20].
Shahrokhnia et al. [21] pointed out that water deficit stress in safflower plants reduces seed yield mainly by reducing all yield components due to reduced photosynthesis. Harish-Babu et al. [22] reported that the number of branches and capitula per plant are the most important effective traits for safflower yield and that they have the highest positive indirect effects on seed yield. The results of a path analysis of traits related to safflower seed yield showed that under normal conditions, the number of seeds in the capitulum, 1000-seed weight and stem diameter and under water deficit conditions, the number of seeds in the capitulum, 1000-seed weight, days to 50% flowering and capitulum diameter had the highest positive direct effects on seed yield [23]. Ebrahimian et al. [24], who studied safflower plants under water deficit, found that drought reduced seed yield by decreasing the number of seeds in the capitulum. The results of the evaluation of safflower genotypes under normal and saline field conditions showed that the number of capitula per plant, the number of seeds in the capitula, 1000-seed weight and seed yield decreased significantly under saline conditions. In addition, the number of capitula per plant was the strongest predictor of seed yield [25].
There are few reports on the response of safflower plants to drought stress in marginal areas early in the season. The aim of this study was to identify physiological traits for the selection of drought-tolerant safflower genotypes for cultivation in marginal and arid areas.
2. Materials and Methods
The study was conducted in the marginal soils (EC = 6.5 ds m−1, pH = 7.8, CEC = 17 C mol(+) kg−1) of the Agricultural and Natural Resources Research and Education Centre of East Azarbaijan (Khosrow-Shah Station), Iran (46°2′ E, 37°58′ N), during the growing seasons 2017–2019. The trial was conducted on loamy soil as a split plot based on a randomised complete block design with three replicates. Six winter thistle genotypes were evaluated under non-stressed and under water deficit conditions from mid-flowering to seed maturity. Plants were irrigated at MAD = 35–40% and MAD = 75–80% depletion of available soil water in the non-stressed and stressed plots, respectively (Table 1). The EC value of the irrigation water was 2.7 ds m−1. The prevailing weather conditions during the growing seasons are summarised in Table 2. The plot size was 5 × 1.8 m. The distance between the rows was 30 cm and the plants were placed 10 cm apart in a row. The sowing date was 15 September for the two years of the experiment.
The youngest, fully unfolded leaves were used to determine the physiological parameters. To calculate the RWC, the detached leaf discs (3 discs with a diameter of 20 mm) were first weighed as fresh weight (FW) and then the threshold weight (TW) was determined by floating them in distilled water at 5 °C for 4 h under low light. The dry weight (DW) was determined after the samples had been dried at 80 °C for 24 h. Fresh weight (FW), TW and DW were used to calculate RWC as RWC = FW − DW/TW − DW [26,27]. Stomatal conductance (gs) was determined using an AP4 leaf porometer (Delta-T Devices, Cambridge, UK). An infrared thermometer (class 2, Testo, Kirchzarten, Germany) was used to measure crown temperature. Its emissivity was set to 0.56 for the green leaf surface. Measurements were taken on five samples from each plot on the youngest fully developed leaves at 1200 to 1400 h [28,29]. The Crop Water Stress Index (CWSI) was determined using the following equation: CWSI = Tc − Twet/Tdry − Twet, where Tc is the actual canopy temperature, Twet (fully transpiring leaf with open stomata) is the temperature of leaves in the canopy that were sprayed with water on both sides one minute before measurement, and Tdry (non-transpiring leaf with closed stomata) is the temperature of leaves in the canopy that were laterally shielded with Vaseline oil [30,31]. The water potential (WP) of the leaves was measured using a DIK-7000 pressurised chamber (Ogawa Seiki Co., Ltd., Tokyo, Japan). Osmotic adjustment (Oadj) was determined according to the method of Turner [32]. Some of the leaf samples used to determine RWC were separated and placed in liquid nitrogen for rapid freezing.
After thawing, the samples were stored at −18 °C, the juice was extracted with a press and the osmotic potential (OP) of the sample was measured with an osmometric vapour pressure chamber (Westcor Inc., Logan, UT, USA) connected to a microvoltmeter. The OP at full turgor (OP100) was then estimated from the measured OP and the RWC by OP100 = OP × (RWC/100). Osmotic adjustment was determined as the difference between the OP100 at the beginning of the drying cycle, when the RWC was about 80 percent, and the OP100, when the RWC was about 60, for all genotypes. The agronomic water use efficiency (WUEa) was determined as the ratio between the seed yield and the total amount of water available, including rainfall and irrigation [13].
The plants were harvested on 28 July of the respective research year. To control the effects of the outdoor environment, the plants were removed from the sides of each plot before harvesting. Finally, the seed yield, the number of cups per plant, the number of seeds in a cup and the weight of 1000 seeds were measured. Ten plants from each plot were randomly selected and used to determine the plant components of seed yield. Statistical analyses of the data were performed using the SAS and SPSS Service Pack software v. 26 packages, for a total of 24 software packages.
3. Results
3.1. Physiological Characteristics, Seed Yield and Yield Components
The effects of drought stress on all analysed traits were significant (Table 3). The values of physiological and agronomic traits differed significantly between the winter thistle genotypes. The interaction effects between drought stress and genotype were also significant for all traits, except for the water stress index, osmotic adjustment and agronomic water use efficiency (Table 3).
Drought stress from flowering to seed maturity led to a significant reduction in all physiological (except for the water stress index, which increased) and agronomic traits in all genotypes analysed (Table 4). The trait values of the winter thistle genotypes differed significantly under all water conditions (Table 4). The results showed that the studied genotypes, Parnian with the higher CWSI value, had lower values in physiological and agronomic traits under all water conditions, except for 1000-seed weight (Table 4).
Golemehr also gave lower values for RWC and stomatal conductance. Golemehr, Mec.248 and Mec.295 under normal conditions and Golemehr, Mec.14, Mec.248 and Mec.295 under water deficit conditions had higher seed yields (Table 4).
3.2. Correlation among Traits
Positive and significant correlations were found between the analysed physiological traits (Table 5). Naturally, mentioned correlations were negative and significant for CWSI. The physiological traits except osmotic adjustment showed positive and significant correlations with seed yield (negative and significant for CWSI). The components of seed yield except 1000-seed weight with CWSI showed negative and significant correlation. RWC and stomatal conductance with capitula per plant, water potential with seeds per capitulum, and WUEa with capitula per plant and seeds in capitulum had positive and significant correlations. Seed yield correlated positively with cup size per plant and seeds in the cup (Table 5).
3.3. Regression Relationship between Seed Yield and Physiological Traits
The regression relationships between seed yield of safflower genotypes and physiological traits showed that water stress index, water potential and water use efficiency had a strong relationship with seed yield and had higher R2 coefficients under both normal and water deficit stress conditions. Stomatal conductance also showed a strong correlation with seed yield and had a remarkable R2 only under water deficit stress conditions (Figure 1).
4. Discussion
Water deficit stress during the reproductive phase of safflower genotypes led to a significant reduction in the studied physiological traits, including RWC, gs, Oadj, WP and WUEa, and to an increase in CWSI (Table 3 and Table 4). The values of the mentioned traits among safflower genotypes were significantly different (Table 3 and Table 4). Alizadeh-Yeloojeh and Saeidi [33] described that safflower germplasm contains different genetic material to improve seed yield, earliness and drought-tolerant varieties. Stomatal conductance decreased under drought and heat stress during the flowering and seed-filling stages. This led to a reduction in mesophyll conductance in oilseed rape [34]. As a result, the lower carbon uptake led to a lower seed yield in oilseed rape genotypes. The results of a study on safflower under water deficit stress at different growth stages showed that water supply at the flowering and capitulum development stages improved the water use efficiency and seed yield of safflower [35]. Pradawet et al. [36] studied maize crops under normal and dry stress conditions and found a significant correlation between the plant water stress index and stomatal conductance (R2 = 0.90). The results of measuring differences in canopy and air temperature of winter rye genotypes under normal and water deficit conditions showed that the mentioned index can detect differences in water deficit stress tolerance more accurately than the determination of the grain yield of rye [37]. The correlations between the physiological traits were positive (negative for CWSI) and significant (Table 5). They also showed positive (negative for CWSI) and significant correlations with seed yield (Table 5) (except for Oadj). The regression relationships between seed yield of safflower genotypes and physiological traits showed that CWSI, WP and WUEa had a strong relationship with seed yield and impressively high R2 coefficients under both normal and water deficit stress during flowering and seed filling stages. The regression analysis equations showed that more than 80 percent of the total variation in seed yield could be independently explained by CWSI, WP or WUEa under stress and non-stress conditions. These parameters can be used more reliably to predict seed yield under stress and non-stress conditions (Figure 1). It appears that a reduction in water availability under drought conditions through a decrease in water potential and stomatal conductance of leaves and an increase in leaf temperature in safflower genotypes reduces seed yield by reducing photosynthesis. In conclusion, water stress index, water potential and agronomic water use efficiency are able to select high-yielding and drought-tolerant safflower genotypes for the late season. Most of the world’s safflower production comes from marginal and arid areas. Therefore, water deficit stress, especially during the flowering and seed-filling phase, is the main limiting factor. Therefore, accurate, fast and cost-effective methods are needed to select drought-tolerant and high-yielding safflower genotypes. The cultivation of suitable safflower genotypes on marginal soils represents a valuable opportunity to prevent soil erosion and secure an economic income for farmers in threatened areas. The results of a study show that leaf temperature is a suitable criterion for the selection of drought-tolerant safflower genotypes [4]. The study of safflower genotypes under pre-season and in-season irrigation conditions showed that the differences between genotypes were insignificant and small for WUE [15]. It is known that safflower under drought stress translocates a large percentage (65–92%) of its pre-flowering stored assimilates into seeds at the end of the season [19]. Investigating safflower genotypes under normal and water deficit conditions, Bahrami et al. [38] recognised significant differences between them in seed yield under normal and drought stress conditions. They concluded that some drought tolerance indices such as stress tolerance index and geometric mean productivity can be used for screening drought-tolerant and high-yielding safflower genotypes.
Water deficit stress occurring during the flowering and seed-filling phase significantly reduced seed yield and its components in safflower genotypes. The extent of this reduction was significantly different among the different genotypes (Table 3 and Table 4). The correlation between seed yield and the number of capitula per plant (0.86) and the number of seeds per capitula (0.92) was positive and significant (Table 5). Thus, among the yield components, the two components mentioned played a more important role in seed yield than others. It appears that drought stress during the flowering and seed-filling stages reduces seed yield mainly by reducing the number of capitula per plant or the number of seeds in the capitula. Water deficit stress in safflower reduces seed yield mainly by reducing all yield components through the reduction in photosynthesis [21]. The number of plant branches and the number of capitula per plant were the most important traits affecting yield and had the greatest positive indirect effects on seed yield [22]. Ebrahimian et al. [24], who studied safflower plants under drought stress, indicated that drought reduces seed yield by reducing the number of seeds in the capitulum.
The values of physiological and agronomic traits differed significantly between the studied genotypes under non-stressed and water deficit stress conditions in marginal soil (Table 3 and Table 4). Parnian with the higher CWSI values had lower values for physiological and agronomic traits under all water conditions, with the exception of 1000-seed weight. This variety has genetically larger seeds. Golemehr, Mec.248 and Mec.295 under normal conditions and Golemehr, Mec.14, Mec.248 and Mec.295 under water deficit conditions had higher seed yields than others (Table 4). The availability of sufficient irrigation water is associated with high risk in marginal and arid areas. Therefore, safflower genotypes Golemehr and Mec.295, which have higher seed yield under both normal and water deficit conditions, can be recommended for cultivation in the mentioned areas (EC = 6.5 ds m−1, pH = 7.8, CEC = 17 C mol(+) kg−1).
5. Conclusions
The results of the evaluation of some physiological parameters under normal and water deficit stress during the flowering and seed-filling stages in safflower genotypes showed that drought significantly decreased relative water content, stomatal conductance, osmotic adjustment, water potential and agronomic water use efficiency and increased the water stress index of the plant. The values of the mentioned traits among safflower genotypes were significantly different. The correlations between the physiological traits were positive (negative for plant water stress index) and significant. They also showed positive (negative for water stress index) and significant correlations with seed yield (except for osmotic adjustment). The equations for the regression analysis showed that the water stress index, water potential or agronomic water use efficiency can independently explain more than 80 percent of the total variation in seed yield under all water conditions. These parameters can be used more reliably to predict seed yield under drought stress and non-stress conditions. It is concluded that water stress index, water potential and agronomic water use efficiency are able to select high-yielding and drought-tolerant safflower genotypes for the late season. The presence of positive and significant correlations between seed yield and the number of capitula per plant (0.86) and the number of seeds per capitula (0.92) indicates that the two yield components mentioned play a more important role in the formation of seed yield than others. Of the genotypes analysed, Golemehr and Mec. 295 have higher seed yields under both normal and water deficit conditions and can be recommended for cultivation in marginal, dry and saline areas.
Author Contributions
Conceptualisation, B.P.E., T.O. and L.B.; methodology, B.P.E.; software, B.P.E.; validation, B.P.E., T.O. and L.B.; formal analysis, B.P.E.; investigation, B.P.E., T.O., A.C.B. and L.B.; resources, T.O., A.C.B. and L.B.; data curation, B.P.E.; writing—original draft preparation, B.P.E., T.O. and L.B.; writing—review and editing, B.P.E., T.O., A.C.B. and L.B.; visualisation, B.P.E., T.O., A.C.B. and L.B.; supervision, B.P.E.; project administration, B.P.E.; funding acquisition, T.O. and L.B. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Data Availability Statement
The data presented in this study are available on request from the corresponding author.
Acknowledgments
The authors would like to thank the director and staff of Khosrow-Shah Agronomic Research Station for their support during the field work and Hassan Monirifar for his technical assistance in data analysis. The authors would also like to thank the University of Tabriz for providing facilities during this study.
Conflicts of Interest
The authors declare no conflicts of interest.
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Figure 1.
The regression relationships between the seed yield (kg/ha) of safflower genotypes as a linear or non-linear function with water stress index (a), relative water content (b), stomatal conductance (c), osmotic adjustment (d), water potential (e) and water use efficiency (f) under drought stress and non-stress conditions.
Figure 1.
The regression relationships between the seed yield (kg/ha) of safflower genotypes as a linear or non-linear function with water stress index (a), relative water content (b), stomatal conductance (c), osmotic adjustment (d), water potential (e) and water use efficiency (f) under drought stress and non-stress conditions.
Table 1.
Characteristics of soil water content in the experimental field (Khosrow-Shah Research Station, Iran).
Table 1.
Characteristics of soil water content in the experimental field (Khosrow-Shah Research Station, Iran).
| FC (%) | PWP (%) | AWC (%) | |||||
|---|---|---|---|---|---|---|---|
| Soil Depth (cm) | Year | 2017–2018 | 2018–2019 | 2017–2018 | 2018–2019 | 2017–2018 | 2018–2019 |
| 0–30 | 26.7 | 25.2 | 12.6 | 12.8 | 14.1 | 12.4 | |
| 30–60 | 20.8 | 20.4 | 10.0 | 11.4 | 10.8 | 9.0 | |
| 60–90 | 13.7 | 13.1 | 7.5 | 8.0 | 6.2 | 5.1 | |
FC = field capacity, PWP = permanent wilting point, AWC = available water capacity.
Table 2.
Weather records for two growing seasons during the experimental periods (Khosrow-Shah research station, Iran).
Table 2.
Weather records for two growing seasons during the experimental periods (Khosrow-Shah research station, Iran).
| Year | Month | Mean Minimum Air Temperature (°C) | Mean Maximum Air Temperature (°C) | Mean of Total Air Temperature (°C) | Sum of Rainfall (mm) | Sum of Evaporation from Class A Pan (mm) |
|---|---|---|---|---|---|---|
| 2017 | September | 17.1 | 34.2 | 25.7 | 0.0 | 311.2 |
| October | 7.6 | 22.7 | 15.2 | 10.5 | 170.1 | |
| November | 5.8 | 17.5 | 11.7 | 16.6 | 89.2 | |
| December | −4.3 | 6.5 | 1.1 | 26.4 | 1.7 | |
| 2018 | January | −1.0 | 9.1 | 4.1 | 21.5 | 0.0 |
| February | −2.3 | 7.8 | 2.8 | 80.0 | 0.0 | |
| March | 2.8 | 13.6 | 2.8 | 33.0 | 0.0 | |
| April | 5.8 | 19.2 | 12.5 | 48.9 | 120.0 | |
| May | 8.4 | 20.4 | 14.4 | 78.3 | 167.5 | |
| June | 13.6 | 28.5 | 21.0 | 27.2 | 260.0 | |
| July | 21.2 | 37.4 | 29.3 | 0.0 | 409.6 | |
| August | 21.3 | 37.0 | 29.2 | 0.0 | 385.0 | |
| September | 17.4 | 32.3 | 24.8 | 3.1 | 296.5 | |
| October | 11.6 | 26.2 | 18.9 | 5.5 | 167.0 | |
| November | −0.3 | 22.8 | 9.5 | 15.6 | 78.0 | |
| December | 1.7 | 9.2 | 5.5 | 80.3 | 0.0 | |
| 2019 | January | −2.1 | 6.2 | 2.1 | 15.8 | 0.0 |
| February | −0.8 | 7.2 | 3.2 | 62.3 | 0.0 | |
| March | 1.1 | 10.5 | 5.8 | 29.5 | 0.0 | |
| April | 5.1 | 14.7 | 9.9 | 96.3 | 9.6 | |
| May | 8.4 | 20.9 | 14.6 | 39.5 | 180.4 | |
| June | 16.3 | 30.8 | 23.6 | 4.6 | 300.9 | |
| July | 19.9 | 34.5 | 27.2 | 0.0 | 411.4 | |
| August | 20.4 | 35.1 | 27.7 | 0.0 | 407.7 |
Table 3.
Variances of traits measured in safflower genotypes in the period 2017–2019.
| Mean Squares | ||||||
|---|---|---|---|---|---|---|
| Source | df | Crop Water Stress Index | Relative Water Content | Stomatal Conductance | Osmotic Adjustment | Water Potential |
| Year (Y) | 1 | 0.001 | 0.0009 | 0.0008 | 0.009 | 0.0009 |
| Replication/Y | 4 | 0.001 | 0.0010 | 0.0010 | 0.002 | 0.0009 |
| Stress (S) | 1 | 1.376 ** | 0.2780 ** | 0.3740 ** | 12.417 ** | 3.6990 ** |
| S × Y | 1 | 0.001 | 0.0009 | 0.0010 | 0.009 | 0.0007 |
| Error1 | 4 | 0.001 | 0.0003 | 0.0008 | 0.003 | 0.0009 |
| Genotype (G) | 5 | 0.022 ** | 0.0120 ** | 0.0160 ** | 0.077 ** | 0.0310 ** |
| G × Y | 5 | 0.001 | 0.0007 | 0.0007 | 0.002 | 0.0003 |
| S × G | 5 | 0.001 | 0.0020 ** | 0.0020 ** | 0.003 | 0.0110 ** |
| S ×G × Y | 5 | 0.001 | 0.00009 | 0.0010 | 0.002 | 0.0004 |
| Error2 | 40 | 0.001 | 0.0005 | 0.0005 | 0.004 | 0.0003 |
| C.V (%) | 4.28 | 2.12 | 3.26 | 5.74 | 3.96 | |
| Source | df | Water Use Efficiency | Capitula per Plant | Seeds in a Capitulum | 1000-Seed Weight | Seed Yield |
| Year (Y) | 1 | 0.0003 | 0.500 | 3.920 | 0.245 | 8320.500 |
| Replication/Y | 4 | 0.0010 | 1.778 | 10.891 | 12.757 | 185,288.153 |
| Stress (S) | 1 | 0.1670 ** | 53.389 ** | 1226.776 ** | 64.980 * | 17,586,406.556 ** |
| S × Y | 1 | 0.0004 | 2.000 | 0.376 | 7.736 | 5904.222 |
| Error1 | 4 | 0.0002 | 1.111 | 3.869 | 6.038 | 77,433.264 |
| Genotype (G) | 5 | 0.0070 ** | 48.822 ** | 897.379 ** | 76.505 ** | 13,498,965.356 ** |
| G × Y | 5 | 0.0001 | 0.233 | 23.367 | 12.311 | 16,587.733 |
| S × G | 5 | 0.0005 | 3.722 ** | 97.742 ** | 32.080 ** | 684,142.322 ** |
| S ×G × Y | 5 | 0.0004 | 0.667 | 32.809 | 3.749 | 8738.922 |
| Error2 | 40 | 0.0003 | 0.644 | 13.193 | 8.153 | 65,866.975 |
| C.V (%) | 3.35 | 9.20 | 7.55 | 8.50 | 7.51 | |
*, ** Significant at p < 0.05 and <0.01, respectively.
Table 4.
Mean values of traits measured on safflower genotypes at different stress levels 2017–2019.
Table 4.
Mean values of traits measured on safflower genotypes at different stress levels 2017–2019.
| Stress Levels | Genotype | Crop Water Stress Index | Relative Water Content | Stomatal Conductance (cm s−1) | Osmotic Adjustment (MPa) | Water Potential (MPa) |
|---|---|---|---|---|---|---|
| Non-stressed | Padideh | 0.353 d | 0.76 a | 0.738 a | 1.508 bc | −0.24 bc |
| Golemehr | 0.338 d | 0.72 b | 0.622 c | 1.633 a | −0.21 a | |
| Mec.14 | 0.322 d | 0.76 a | 0.695 b | 1.592 ab | −0.21 a | |
| Mec.248 | 0.357 d | 0.75 a | 0.662 b | 1.525 bc | −0.23 ab | |
| Mec.295 | 0.330 d | 0.74 a | 0.682 b | 1.658 a | −0.20 a | |
| Parnian | 0.448 c | 0.72 b | 0.627 c | 1.450 c | −0.26 c | |
| Stressed | Padideh | 0.632 b | 0.66 c | 0.553 d | 0.642 f | −0.72 g |
| Golemehr | 0.615 b | 0.56 d | 0.497 ef | 0.783 de | −0.63 e | |
| Mec.14 | 0.613 b | 0.64 c | 0.553 d | 0.750 de | −0.64 ef | |
| Mec.248 | 0.625 b | 0.65 c | 0.547 d | 0.716 ef | −0.66 f | |
| Mec.295 | 0.603 b | 0.64 c | 0.530 de | 0.850 d | −0.59 d | |
| Parnian | 0.713 a | 0.56 d | 0.480 f | 0.642 f | −0.815 h | |
| LSD 5% | 0.0466 | 0.0203 | 0.0338 | 0.0987 | 0.0279 | |
| Stress Levels | Genotype | Water Use Efficiency (kg m−3) | Capitula per Plant | Seeds in a Capitulum | 1000-Seed Weight (g) | Seed Yield (kg h−1) |
| Non-stressed | Padideh | 0.53 b | 11.3 a | 52.4 b | 31.6 b-e | 3697 cd |
| Golemehr | 0.55 ab | 8.7 cd | 51.7 b | 31.1 c-e | 4676 ab | |
| Mec.14 | 0.55 ab | 10.7 ab | 51.8 b | 37.4 a | 4026 c | |
| Mec.248 | 0.54 ab | 11.5 a | 61.0 a | 34.1 a-d | 4508 b | |
| Mec.295 | 0.56 a | 9.8 bc | 60.3 a | 35.7 a-c | 4961 a | |
| Parnian | 0.49 c | 5.5 f | 36.3 e | 37.5 a | 1593 g | |
| Stressed | Padideh | 0.44 e | 9.0 cd | 41.4 de | 28.1 e | 2939 f |
| Golemehr | 0.45 de | 8.2 de | 50.9 b | 30.4 e | 3211 ef | |
| Mec.14 | 0.44 de | 7.2 e | 50.0 bc | 29.8 de | 3564 de | |
| Mec.248 | 0.44 de | 9.5 b-d | 43.9 cd | 32.5 e | 3364 de | |
| Mec.295 | 0.47 cd | 9.0 cd | 52.7 b | 34.5 a-d | 3385 de | |
| Parnian | 0.41 f | 4.3 f | 27.1 f | 36.4 ab | 1068 h | |
| LSD 5% | 0.026 | 1.253 | 5.671 | 4.458 | 400.7 | |
Different letters indicate a significant difference at (p < 0.05) determined by ANOVA with the comparison of means using Tukey’s HSD.
Table 5.
Simple correlation coefficients between traits measured in safflower genotypes in the period 2017–2019.
Table 5.
Simple correlation coefficients between traits measured in safflower genotypes in the period 2017–2019.
| Trait | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | |
|---|---|---|---|---|---|---|---|---|---|---|
| (1) | Crop Water Stress Index | −0.91 ** | −0.93 ** | −0.98 ** | −0.98 ** | −0.98 ** | −0.60 * | −0.65 * | −0.21 | −0.66 * |
| (2) | Relative water content | 0.95 ** | 0.88 ** | 0.90 ** | 0.87 ** | 0.63 * | 0.55 | 0.15 | 0.58 * | |
| (3) | Stomatal conductance | 0.88 ** | 0.90 ** | 0.87 ** | 0.65 * | 0.55 | 0.15 | 0.59 * | ||
| (4) | Osmotic adjustment | 0.99 ** | 0.95 ** | 0.46 | 0.55 | 0.32 | 0.55 | |||
| (5) | Water potential | 0.95 ** | 0.51 | 0.60 * | 0.28 | 0.58 * | ||||
| (6) | Water use efficiency | 0.65 * | 0.74 ** | 0.20 | 0.75 ** | |||||
| (7) | Capitula per plant | 0.82 ** | −0.17 | 0.86 ** | ||||||
| (8) | Seeds in a capitulum | −0.13 | 0.92 ** | |||||||
| (9) | 1000-seed weight | −0.23 | ||||||||
| (10) | Seed yield | |||||||||
*, ** Significant at p < 0.05 and <0.01, respectively.
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Pasban Eslam, B.; Chenari Bouket, A.; Oszako, T.; Belbahri, L. Physiological Indices for the Selection of Drought-Tolerant Safflower Genotypes for Cultivation in Marginal Areas. Appl. Sci. 2024, 14, 5106. https://doi.org/10.3390/app14125106
AMA Style
Pasban Eslam B, Chenari Bouket A, Oszako T, Belbahri L. Physiological Indices for the Selection of Drought-Tolerant Safflower Genotypes for Cultivation in Marginal Areas. Applied Sciences. 2024; 14(12):5106. https://doi.org/10.3390/app14125106
Chicago/Turabian StylePasban Eslam, Bahman, Ali Chenari Bouket, Tomasz Oszako, and Lassaad Belbahri. 2024. "Physiological Indices for the Selection of Drought-Tolerant Safflower Genotypes for Cultivation in Marginal Areas" Applied Sciences 14, no. 12: 5106. https://doi.org/10.3390/app14125106
APA StylePasban Eslam, B., Chenari Bouket, A., Oszako, T., & Belbahri, L. (2024). Physiological Indices for the Selection of Drought-Tolerant Safflower Genotypes for Cultivation in Marginal Areas. Applied Sciences, 14(12), 5106. https://doi.org/10.3390/app14125106
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