Water Stress Affects the Some Morpho-Physiological Traits of Twenty Wheat ( Triticum aestivum L.) Genotypes under Field Condition

: Water stress has become one of the foremost constraints to agricultural development, mostly in areas that are deﬁcient in water. A ﬁeld trial has been conducted to evaluate the performance of different twenty wheat genotypes under three stress treatments viz., control (T0) = normal watering, stress-1 (T1) = water stress from tillering up to maturity, and stress-2 (T2) = water stress from anthesis to maturity were used as treatments. The results revealed that a highly signiﬁcant ( p < 0.01) difference was observed among twenty wheat cultivars for morpho-physiological traits except for several tillers plant − 1 , spikeletspike − 1 , and relative water content. In the early days, 50% ﬂowering was noted in Anmole-91 (64.33 days) under (T0), while Anmol-91 showed a relative decrease (RD-1) ( − 2.34 days) at days 50% ﬂowering in (T1). The TJ-83 genotype showed an early response ( − 8.34 day) at days to 50% ﬂowering under stress-2 (T2), but TD-I ( − 3.34) was observed to be relatively tolerant. Underwater stress from tillering to maturity (T1) SKD-1 was found more susceptible ( − 36.7 days) than other cultivars. Wheat cultivar Soghat-90 showed maximum RD-1 ( − 24.7) for grain yield plant − 1 in stress-1 (T1) from tillering to maturity. Anmole-91, NIA-Sarang, and TD-I observed minimum was ( − 6) in the same water stress for various traits. Therefore, the ﬁndings of present work revealed that the best performing genotypes can be recommended for effective cultivation in future breeding programs.


Introduction
Wheat is a staple cereal food crop cultivated for the entire worldwide population [1]. Extensive land area in undeveloped countries often comes under sub-tropical areas, where water shortage is the main drawback to wheat crop yield. The lack of water significantly affects the morpho-physiological parameters of the wheat plant [2,3]. Wheat grains are rich in essential elements and good for the human diet globally. It has the most significant importance in Pakistan after rice cultivation [4]. Water scarcity is a big issue for healthy crop production, which affects the overall economy of Pakistan. It is observed that the Sustainability 2021, 13, 13736 2 of 15 north parts of the Sindh and a few areas of the Balochistan provinces are seriously facing a lack of water for sustainable agriculture. For better crop production, soil health, availability of water, tillage practices, weed management, plant density, fertilizer, salinity, crop rotation, plant genotype, etc. can be considered the main factors for better wheat crop growth and yield [5,6]. Improving water stress tolerance in crops has become a lengthy, laborious, time consuming and difficult task for adaptation in water shortage condition. Success for this task might be achieved by underlining crop water use efficacy. Larger leaf area, in addition to crop development, was found to be positively correlated with embryo size. Therefore, higher embryos may enhance early plant growth. The selection of cultivars that need low irrigation has also provided improved crop production under drought-resistant environments. In addition, water stress type research studies might be helpful in a breeding program for improving the qualitative and qualitative parameters of wheat genotypes as compared to other cereals under water stress conditions [7]. Water stress significantly decreases the main stem width, which therefore declines the quality of nodes/internodes width and total biomass due to reduction in width, which may cause the plant to produce short leaves, lees root proliferation, and lesser tillers. The water shortage condition affects several spikelets which were noted in positive association with low dry matter production. The spikelet spike −1 is associated with a decreased number of flowers. The reduction of grains in the main spike, seed mass, and grain production proposed diminished in terms of dry biomass build-up and as a result, decreased spike length and healthy seeds. Water stress also affects the enlargement of plant cells, which may produce unhealthy seeds and result in poor quality and low weight of the plant. Rathore [8] stated that while genotypes gave a great seed index and more constancy in production under drought, assortment for greater seed yield varieties would be effective under recommended application of irrigation water. At the stage of wheat, flowering water stress is considered a limiting factor of lower wheat production. The literature reported that to improve the water stress in the wheat genotypes is a big challenge for genetic engineers [9]. In this regard, correlation studies have too much significant importance for breeders to produce high-yielding varieties for normal cultivation under water deficit areas. Gupta [10] noted positive associations of water possible for leaf, plant height, leaf area, tiller, biomass, and grain yield. Previous research showed that a great decline in grain yield was observed during the flowering stage under water stress conditions. Drought stress during grain filling exposed a greater than 70% decline in grain output of wheat. Lesser decline in grain yield was noted when water stress was observed during growth stages. In the earlier studies, it was observed that the anthesis stage of the wheat crop has been found to be a very sensitive phenomenon of plants cultivation under water stress conditions [6]. In the former study, Faisal [11] assessed the morphological and physiological parameters of wheat varieties for water stress tolerance at the seedling stage. However, little is known about the morphological and physiological traits and its interaction between 20 wheat genotypes traits by using redundancy analysis cultivation under three water stress conditions. Therefore, the present study has aimed to evaluate the genetic role of some morpho-physiological characters of twenty wheat genotypes under different water stress conditions such as control, stress-1, and stress-2. It is hypothesized that the best performing genotypes will be suggested for a further breeding program.

Study Area and Experimental Set-Up
In the study, for screening of best water stress tolerant genotype, an ex-situ trial was performed during Rabi season at the trail field of Sindh Agriculture University Tandojam. The field was conducted in the field of the botanical experimental garden, near the central library at Sindh Agriculture University Tandojam three each replication and water treatment. Control (T0) was normal watering, T1 has water stress from tillering to maturity denoted as (Stress-1), and T2 has water stress from anthesis to maturity denoted as (Stress-2). The morpho-physiological traits are represented in Table 1. The study area of the experimental field is indicated in (Figure 1). The study flow diagram is represented in (Figure 2). Table 1. Morpho-physiological parameters were recorded in the 20 wheat genotypes.

Parameter Designation Code Description of the Parameter
Chlorophyll content CL The 2nd youngest leaf blade of the plant was detected by the SPAD−502 chlorophyll meter [12].
Flag leaf area (mm 2 ) FLA FLA was measured by a convenient laser Leaf area meter AG-51, great speed scanner with scan board and data logger.
Days to 50% flower D-50% The days to 50% flowering were noted from sowing to 50% flowering for individual wheat genotypes.
Days to 90% maturity D-90% The days to 90% maturity were recorded from sowing to 90% maturity for individual wheat genotypes.
Plants when physically were found mature, the date was recorded for individual genotype, and days were counted from sowing to 90% maturity.

Grain filling period GYP
The grain filling period was measured by subtracting the anthesis period from days to maturity of genotypes.
Plant height (cm) PH The PH was noted from the surface of the soil to the tip of a panicle after the maturity of genotypes.
Number of tiller per plant NTPP A number of tillers were counted in the field for each genotype.
Number of grain per spike NGPS Counted thrashed grains of a spike.
Number of spikelets per spike NSPS Spikelets were counted from each spike of the sample plant and noted.
Grain yield per plant (g): GYPP All spikes of a sample plant were threshed separately and then mixed and weight was taken as grain yield plant −1 .

Biological yield per plant BYPP
The sample plants at maturity were uprooted and their weight was noted in grams on digital top balance as biological yield plant −1 .

Geospatial Techniques
In this study high-resolution Google earth, Geo eye satellite image of 2021 has been used for making a map of the study area, the method of image rectifying has been carried out with the help of geo-referencing tool in Arc GIS 10.3.1, and digitization has been carried out for making shapefile of the study area (Table 1).

Geospatial Techniques
In this study high-resolution Google earth, Geo eye satellite image of 2021 has been used for making a map of the study area, the method of image rectifying has been carried out with the help of geo-referencing tool in Arc GIS 10.3.1, and digitization has been carried out for making shapefile of the study area (Table 1).

Statistical Analysis
The data have been analyzed by using Excel 2016 and Statistics (v8.1) for Windows. Redundancy analysis (RDA) among morpho-physiological parameters of twenty wheat genotypes has been also used to designed using CANOCO5. Analysis of variance has been carried out [14].

Results and Discussion
The present study was conducted to access wheat tolerance under water stress. Analysis of variance revealed that cultivars and their interaction with water treatments were significantly different (p > 0.01) for most of the studied traits. Cultivars showed different performances underwater treatments. Analysis of variance showed that a highly significant difference in morpho-physiological traits. Genotype × treatment was significantly different for physiological traits such as flag leaf area, relative water content, and chlorophyll content ( Table 2). Significant at * p < 0.05; ** p < 0.01 level and ns = non-significant.

Flag Leaf Area and Relative Water Content
As shown in (Table 6), the maximum flag leaf area was observed under normal watering (T0), showed in Anmole-91 (18,390) followed by NIA-Sarang (17,925) and SKD-I (17,233). The shortest flag leaf was showed in Sarsabz (12,854) and Moomal-02 (12,955), respectively. As shown in (Table 6) also revealed that the greater decrease in flag leaf area was shown in Anmole-91 (−6827) as compared to SKD-I (−6169) underwater stress-1 (T1). Whereas, the less affected were Soghat-90 (−1729) and Inqalab-95 (−1691) respectively. The greater flag leaf area was noted in NIA-Sarang, SKD-1, TJ-83, Abadgar-89, and Anmole-91. Water stress from anthesis to maturity was shown in (T2) as a result the variety Anmole-91 (−3565) indicated that the greater reduction in flag leaf area rather than NIA-Sarang (−2789) and Kohinoor (−2767). While the less reduction was noted in Imdad-05 (−270) and Soghat-90 (−614), respectively in the flag leaf area. Solomon and Labuschange [23] also studied water stress effects on morpho-physiological characters and reported that significant differences were found in genotypes, interactions, and water stress treatments. They stated that flag leaf area was significantly affected by water stress and that droughttolerant genotypes have fast early growth. Table 6. Impact of water stress on flag leaf area and relative water content of wheat genotypes.

Redundancy Analysis between the Morpho-Physiological Traits of Twenty Wheat Genotypes
Redundancy analysis (RDA) was performed to explore the association among the morpho-physiological traits viz., plant height, grain filling period, days to 50% flowering, days to 90% maturity, harvest index plant −1 , biological yield, 1000 grain weight, grain yield plant −1 , tillers plant −1 , number of grains spike −1 , number of spikelets spike −1 , relative water content, flag leaf area and chlorophyll content underwater treatment viz., control, stress-1 and stress-2 (Figure 3a-c). The RDA revealed that morpho-physiological traits of twenty can explain (32.87%) of the total variance. The results showed that grain yield per plant, number of grains per spike, number of spikelets per spike were clustered to gather with chlorophyll content, and observed far from plant height, harvest index per plant, grain filling period, and days to 50% flowering. In addition, 1000 grain weight, tillers per plant, biological yield per plant, and days to 90% maturity were clustered to gather with relative water content, and flag leaf area and far from plant height, harvest index per plant, grain filling period, and days to 50% flowering under control treatment (Figure 3a). The data in (Figure 3b) indicated that the RDA showed that morpho-physiological traits of twenty can explain (30.32%) of the total variance. The harvest index plant −1 , tillers plant −1 , grain yield plant −1, and days to 90% maturity were clustered to gather with chlorophyll content and observed far from the grain filing period. Furthermore, the number of spikelets spike −1 , biological yield plant −1 , number of grains spike −1 , and 1000 grain weight were clustered to gather with flag leaf area. Besides, days to 50% flowering and plant height were clustered to gather relative water content in stress-1 treatment. As shown in (Figure 3c) the RDA data indicated that the morpho-physiological traits of twenty can explain (29.94%) of the total variance in stress 2 treatment. The data revealed that 1000 grain weight, biological yield plant −1 , and grain yield plant −1 were clustered to gather with chlorophyll content, and found far from grain filling period, days to 90% maturity, harvest index plant −1 , and plant height. Moreover, the number of grains spike −1 , number of spikelets spike −1 , tillers plant −1 were clustered to gather with flag leaf area. Also, the days to 50% flowering was positively associated with relative water content. Likewise, Zerga [25,26] reported such a correlation in wheat. Besides, Gupta [10] found that two wheat genotypes indicated a positive correlation between leaf area and grain yield. Abdulkerim [18] stated that the interaction consequence of genotype and seed rate considerably affected thousand kernels weight, number of effective tillers and number of kernels spike −1 and wheat yield. Banerjee [27] observed that a significantly higher correlation between normalized water stresses tolerance index and thermal image-based stress indices in ten wheat genotypes. content, flag leaf area and chlorophyll content underwater treatment viz., control, stress-1 and stress-2 (Figure 3a-c). The RDA revealed that morpho-physiological traits of twenty can explain (32.87%) of the total variance. The results showed that grain yield per plant, number of grains per spike, number of spikelets per spike were clustered to gather with chlorophyll content, and observed far from plant height, harvest index per plant, grain filling period, and days to 50% flowering. In addition, 1000 grain weight, tillers per plant, biological yield per plant, and days to 90% maturity were clustered to gather with relative water content, and flag leaf area and far from plant height, harvest index per plant, grain filling period, and days to 50% flowering under control treatment (Figure 3a). The data in (Figure 3b) indicated that the RDA showed that morpho-physiological traits of twenty can explain (30.32%) of the total variance. The harvest index plant −1 , tillers plant −1 , grain yield plant −1, and days to 90% maturity were clustered to gather with chlorophyll content and observed far from the grain filing period. Furthermore, the number of spikelets spike −1 , biological yield plant −1 , number of grains spike −1 , and 1000 grain weight were clustered to gather with flag leaf area. Besides, days to 50% flowering and plant height were clustered to gather relative water content in stress-1 treatment. As shown in (Figure 3c) the RDA data indicated that the morpho-physiological traits of twenty can explain (29.94%) of the total variance in stress 2 treatment. The data revealed that 1000 grain weight, biological yield plant −1 , and grain yield plant −1 were clustered to gather with chlorophyll content, and found far from grain filling period, days to 90% maturity, harvest index plant −1 , and plant height. Moreover, the number of grains spike −1 , number of spikelets spike −1 , tillers plant −1 were clustered to gather with flag leaf area. Also, the days to 50% flowering was positively associated with relative water content. Likewise, Zerga [25,26] reported such a correlation in wheat. Besides, Gupta [10] found that two wheat genotypes indicated a positive correlation between leaf area and grain yield. Abdulkerim [18] stated that the interaction consequence of genotype and seed rate considerably affected thousand kernels weight, number of effective tillers and number of kernels spike −1 and wheat yield. Banerjee [27] observed that a significantly higher correlation between normalized water stresses tolerance index and thermal image-based stress indices in ten wheat genotypes.

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The advatage of the recommended wheat cultivars screenout was that the cultivars will response in grain yield under arid areas of Pakistan; • These cultivars will need lower inputs against irrigated areas; • The studied cultivars will take part in food security in drought prone areas; • The disadvantages of present study can be considered, namely that the studied cultivars may produce less grain yield in arid areas as compared to irrigated areas; • Lower biomass will be obtained under arid areas as compared to irrigated areas.

Conclusions
It was concluded that different water treatments affected some morpho-physiological traits of twenty wheat genotypes under the ex-situ condition. Indeed, the wheat cultivars showed the highest susceptibility under water stress from tillering to maturity (T1) in respect of normal watering (T0) and water stress-2 (T2) from anthesis to maturity. Though some wheat genotypes revealed high yield under water stress, it would be better to select wheat genotypes under normal watering. Kiran-95 genotype took a large period for grain filling as compared to Moomal-02 (54.33), Marvi, and Sarsabz under normal watering (T0). Besides, wheat cultivars Anmole-90, Chakwal-83, Faisalabad-85, NIA-Sarang, TJ-83, TD-1, and Sarsabz were found best performing lines as compared to other genotypes. It is suggested that the best performing genotypes must be focused on the mechanism and molecular level of research between morpho-physiological traits of twenty wheat genotypes under water deficit areas.