Integrating phenotypic, physiological, and grain yield traits to evaluate drought tolerance in three bread wheat varieties

Integração de características fenotípicas, fisiológicas e de produtividade de grãos para avaliar a tolerância à seca em três variedades de trigo comum (Triticum aestivum)

Abstract

Water stress is one of the major global problems that limits the growth and production of various crops. This field study was carried out to evaluate the impact of different water irrigation requirements of 100% and 75% on three wheat varieties (Gimeza 12 and Sids 13, Sakha 94). Drought stress declines all growth criteria, photosynthetic pigment, yield, and yield attributes. At the same time, total soluble sugars, total free amino acids, and proline contents were improved. Decreasing the water irrigation requirement to 75% reduced virtual water content (VWC), total carbohydrate, and starch contents. The stress tolerance index (STI) was also evaluated. The opposite trend was documented in response to protein, gluten, Zeleny sedimentation, flavonoids, DPPH, and WP. There are different significant responses to drought among the three studied varieties. Sakha 94 surpassed other varieties in most studied parameters, followed by Gimeza 12, then Sids 13 variety. It’s worth mentioning that, Sakha 94 variety gave the highest values of all growth characters, yield and yield attributes, nutritional values of produced grain, and virtual water contents. Also, it gave the highest stress tolerance value, so it is considered the most tolerant variety to drought stress under the studied conditions.

Keywords:
wheat varieties; yield; nutritional values; flavonoids; antioxidant activities; water productivity

Resumo

O estresse hídrico é um dos principais problemas globais que limitam o crescimento e a produção de várias culturas. Este estudo de campo foi realizado para avaliar o impacto de diferentes níveis de irrigação (100% e 75%) sobre três variedades de trigo (Gimeza 12, Sids 13 e Sakha 94). O estresse por seca reduziu todos os critérios de crescimento, os níveis de pigmentos fotossintéticos, a produtividade e seus componentes de rendimento. Simultaneamente, os teores de açúcares solúveis totais, aminoácidos livres totais e prolina foram aumentados. A redução da irrigação para 75% da necessidade hídrica diminuiu o conteúdo de água virtual (VWC), os teores de carboidratos totais e amido. O índice de tolerância ao estresse (STI) também foi avaliado. Uma tendência oposta foi observada em relação aos teores de proteína, glúten, sedimentação de Zeleny, flavonoides, atividade DPPH e produtividade da água (WP). Foram observadas respostas significativamente distintas à seca entre as três variedades estudadas. A variedade Sakha 94 superou as demais na maioria dos parâmetros analisados, seguida pela Gimeza 12 e, posteriormente, pela Sids 13. Vale ressaltar que a variedade Sakha 94 apresentou os valores mais elevados para todas as características de crescimento, produtividade e seus componentes de rendimento, bem como para os valores nutricionais dos grãos produzidos e teores de água virtual. Além disso, apresentou o maior valor de tolerância ao estresse, sendo, portanto, considerada a variedade mais tolerante à seca nas condições estudadas.

Palavras-chave:
variedades de trigo; produtividade; valores nutricionais; flavonoides; atividades antioxidantes; produtividade da água

1. Introduction

Population growth and fluctuating consumer patterns require increased agricultural production and system changes. The world’s population is estimated to reach 9 billion people in 2050, and that will require more than a 62% increase in food production. The agricultural sector has to respond to this defiance. The obligatory rise in primary food production is anticipated to come from productivity gains (greater yields and better land-use intensities) rather than from area expansion. Also, the considerable shortage of arable land and water shortage, concomitant with the population growth rate in Egypt, are serious problems in Egypt (Abdalla et al., 2023). In Egypt, 97% of the land is desert. Only about 3.5 million ha out of about 100 million ha, the total land area, is used for agricultural production, comprising the reclaimed soil from the desert (El Sayed., 2021).

The harm to crop yield as a result of water scarcity stress is certain by several aspects, including the ability of the crop to tolerate drought stress, intensity, and duration (Muhammad et al., 2024). Water shortage at any stage can result in extensive yield loss (Huang et al., 2023). Drought occurs due to the imbalance between the water provided and the requirements. It is caused around the roots as a result of soil drying and around the leaf cells as a result of low air humidity and high temperature (Seleiman et al., 2021). The response of crops to water shortage conditions relies on the timescale assessed. Exposure to short-period induced responses is linked to the regulation of stomatal management, hydraulic conductance, osmotic adjustment among tissues, turgor pressure, osmolyte contents, and plant growth. Long-term responses are concomitant with crop cycle interval, cell-dehydration tolerance mechanisms, root architecture, leaf/root phenological cycles, grain abortion, nutrient distribution, and postponed senescence. These retorts aim to save water via stomatal closure (for stress prevention) while others' goal is to handle the low water status, such as osmoregulation (for stress acclimation) (Padilla et al., 2023).

Due to water scarcity, the absorption capability of roots is affected in parallel with nutrient uptake. Nitrogen, as an essential nutrient for plants, is required in large amounts. Uptake, transport, and translocation of phosphorus are also affected under water scarcity conditions. It minimizes NPK uptake in plants (Ur Rahman et al., 2024). There are diverse physiological tools to explain drought tolerance on physiological bases, like osmotic adjustment, osmoprotectant, antioxidation, and a scavenging defense system, which have been the most important bases responsible for drought tolerance (Seleiman et al., 2021). The harshness of drought is also vital; it anguishes all plant growth stages, consequently, resulting in significant yield loss (Ahluwalia et al., 2021).

Drought causes a decline in relative water content, leading to a decrease in stomatal conductance and stomata closure, consequently leading to humoral grain development and grain set (Frantová et al., 2022; Dubey et al., 2023; Elnajar et al., 2024). In this regard, Salgotra and Chauhan (2023) stated that a reduction in grain size occurs when drought occurs during the anthesis stage. As drought intensity increases, the grain yield and harvest index significantly decrease. The spike length, the grain number per spike, and the grain's weight are also affected by drought (Frantová et al., 2022; Li et al., 2024).

Harder‎ et al. (2023) evaluated the correlation between WUE and water scarcity based on eddy covariance measurements; they discussed that WUE was enriched under drought conditions. Moreover, the influence of drought on WUE is also related to the severity and duration of water scarcity (Farhan‎ et al., 2024). The correlation between meteorological drought and WUE has been surveyed to explain the effect of soil moisture drought on WUE and to aid in better understanding the response of water cycles to drought (Chen‎ et al., 2024).

Cereals such as wheat are considered the basis of a balanced diet in many countries. Wheat is rated as an energy source and comprises other important nutrients, containing proteins, fiber, and secondary components, such as minerals, lipids, vitamins, and phytochemicals. The perceptive features of wheat flour dough attained from the gluten protein complex allow it to be processed into pasta, bread, noodles, and numerous other forms of food, feeding worldwide (Sabença et al., 2021). Modification in the precipitation capacities, strength, and configurations delays wheat growth and productivity under such conditions. Thus, the evaluation of drought outcomes, through different growth developmental stages of wheat, on grain yield and quality traits has actual value (Yang‎ et al., 2024). Wheat is a strategic product in Egypt, and its assembly is a question of political stability (Abdalla et al., 2023). Moreover, Saad et al. (2023) concluded that variations in wheat growth parameters, yield and its attributes, grain productivity, stress tolerance index, virtual water content, and the overall nutritional levels of the produced grains were documented when exposed to 75% of the water irrigation requirements (WIR).

So, this study aims to evaluate the effect of deficit irrigation as an effective strategy to save and improve water productivity on the grain quality of three wheat varieties. It also compares among these varieties in their tolerance to water stress through growth parameters, photosynthetic pigment contents, osmoprotectant contents (total soluble sugars, proline, and total amino acids), yield and its attributes, grain productivity, stress tolerance index, virtual water content, the overall nutritional levels of produced grains and water productivity of them.

2. Materials and Methods

2.1. Materials

Grains of the wheat varieties (Gimeza 12, Sids 13, and Sakha 94) were obtained from the Agricultural Research Centre in Egypt. These wheat varieties were highly recommended for reclaimed sandy soil.

2.2. Experiment location

Two field studies were conducted during the winter seasons of 2021/2022 and 2022/2023. In the experimental farm of the National Research Center in the Nubaria district of Egypt (30_86'67" N 31_16'67" E, with a mean altitude of 21 m above sea level). The zone of the soil farm is anticipated to be arid or semi-arid. The climate data for the experimental site during the growth season are displayed in Figure 1.

Figure 1
The data achieved from the weather station fitted at the experimental station of Nubaria region, Egypt during successive seasons 2021/2022-2022/2023.

According to Chapman and Pratt (1987), the soil at the experimental site was reclaimed sandy soil, and mechanical and chemical analyses are described in Tables 1 and 2.

Table 1
Analysis of physical properties of soil.

Season	Constant Depth (cm)	Sand %	Silt%	Clay%
2021/2022	00 – 30	85.3	10.5	4.2
	30 – 60	81.2	13.6	5.2
2022/2023	00 – 30	81.3	13.4	5.3
	30 – 60	74.6	17.6	7.8

Table 2
Chemical and nutritional properties of soil in the experimental site.

Seasons	Constant Depth. (Cm)	pH	Electrical conductivity (ds/m)	Saturation Percentage	Anions (Milli-equivalents/liter)				Cations (Milli-equivalents/liter)				CaCo3 %	Organic Mater %
					CO3--	CO3-	Cl	SO4--	Ca++	Mg++	Na+	K+
2021/2022	00 – 30	7.84	1.17	32	--	0.50	8.40	1.11	1.80	0.90	7.1	0.20	1.00	0.40
	30 – 60	7.89	1.79	27	--	0.60	8.00	1.40	2.10	1.50	6.2	0.20	6.00	0.07
2022/2023	00– 30	7.95	1.59	23	--	0.32	12.70	1.98	4.00	1.80	9.0	0.20	1.90	0.38
	30 – 60	7.85	1.81	25	--	0.45	15.40	2.15	5.60	2.00	10.2	0.20	1.30	0.32

2.3. Experimental design

Wheat grains were swept away with distilled water, sterilized with 1% sodium hypochlorite solution for about 2 minutes, and swept away ‎ once more with distilled water. The trial was planned in a split-plot design with four replicates, in which the water irrigation requirements (WIR) 100% (WW) & 75% (WS), occupy the main plots, whereas wheat varieties (Gimeza-12, Sids-13, and Sakha 94) were located haphazardly in sub-plots. On 26^th November, wheat grains were cultivated in rows 3.5 m long, and the distance between rows was 20 cm apart; the plot area was 10.5 m² (3.0 m in width and 3.5 m in length) in the two seasons.

The recommended agricultural practices of sowing wheat under sandy soil conditions were done, with a seeding rate (140 Kg ha^-1). Calcium super-phosphate (15.5% P₂O₅) was added to the soil pre-sowing at a rate of 360 kg ha^-1. Nitrogen fertilizer as ammonium nitrate 33.5% at a rate of 180 Kg ha^-1 was added after plant emergence. It was divided into five equal doses before the 1^st, 2^nd, 3^rd, 4^th, and 5^th irrigation. Potassium sulfate (48.52% K₂O) at the rate of 120 kg ha^-1 was divided into two equal doses before the 1^st and 3^rd irrigation.

2.4. Water irrigation requirements

An irrigation system with a new sprinkler was approved every 5 days. The penman-Monteith equation was used to calculate the levels of two irrigation water requirements and crop coefficient according to (Allen et al., 1989). The average amount of irrigation water applied with the sprinkler irrigation system was 5950 and 4462.5 m³ha. ^-1 season^-1 as [100% (WW) & 75% (WS)] for two seasons of 2021/2022 and 2022/2023.

The irrigation water requirements were calculated as follows:

$$WIR=\left[\frac{E{T}_0\times Kc\times Kr\times {\text{I}}_{+}}{Ea}LR\right]\times 4.2$$ (1)

Where: WIR = water irrigation quantities m³ ha^-1

ET₀ = Evapotranspiration (mm day^-1)

I = the period between two irrigations, days

Kc = Crop coefficient.

Kr = Reduction factor (Keller et al., 1975).

LR = Leaching requirement = 10% of the total water requirement applied to the treatment.

Ea = Irrigation water efficiency, 90%.

The water management for the growth stages of the wheat crop during two successive winter seasons (2021/2022-2022/2023) was 5950 m3/ha. and 4462 m3/ha. for 100% and 75% WIR, respectively. The amount of rainwater that fell in the two growing seasons (2021/2022-2022/2023), where 926 m3 season-1 and 1043 m3 season- 1 for the first and second seasons, respectively. Total perception during the two growing seasons for wheat is deducted from the total amount of calculated water irrigation requirements at both levels, 100% and 75%.

2.5. Plant samples

Vegetative plant (before anthesis) samples were gathered 75 days after sowing for growth attributes in terms of plant height (cm), leaves no/tiller, tiller, and root fresh and dry weights (g). Samples of the plant were congregated for biochemical analysis, as photosynthetic pigments, total soluble sugars, proline, and free amino acids. At yield stage, the subsequent characteristics were documented on random samples of 10 girded plants in each plot to assess the following characteristics: Plant height (cm), spikelet no/spike, 1000 grains weight (g), grains yield/spike (g), straw yield (ton/ha), biological yield (ton ha^-1), grain yield (ton ha^-1), harvest index (HI), and the nutritional values of grains yield crop.

2.6. Virtual water content (VWC)

Virtual water content (VWC; the amount of water used in the production of tons of wheat grains) was measured as described by Sun et al. (2021):

$$\begin{array}{c}\text{Virtual water content}\left(\text{VWC}\right)\text{=}\\ \text{Water requirement}\left({\text{m}}^{\text{3}}{\text{ha}}^{\text{-1}}\right)\text{/}\\ \text{Grain productivity per unit area}\left({\text{tons ha}}^{\text{-1}}\right)\end{array}$$ (2)

2.7. The stress tolerance index (STI)

The stress tolerance index (STI) was sure as recorded by Poudel et al. (2021):

$$\begin{array}{c}\text{Stress tolerance index =}\\ \text{Grain yield under normal conditions}\\ \text{X grain yield under stress/}\\ \text{Grain yield under normal conditions}\end{array}$$ (3)

2.8. Water Productivity (WP)

At the final harvest, water productivity (WP) in kg mm^-1 ha^-1 of wheat plants was surveyed. It was calculated by Howell et al. (1990). It is recognized as the relationship between the grain yield and the quantity of irrigation water. WP in kg /mm/ha was calculated by the following:

$$WP=Ey/Et$$ (4)

Where WP is the Water productivity (kg/m³); Ey is the economic yield (kg ha^-1); Et is the total of irrigation water utilized, m³ha^-1 /season.

2.9. Biochemical analysis

Photosynthetic pigments were determined according to the method described by Lichtenthaler and Buschmann (2001). Total Soluble Sugars (TSS) were identified by Albalasmeh et al. (2013) and extracted followingGomez et al. (2002). Proline content was extracted and determined using Tamayo and Bonjoch's (2001). According to Kalsoom et al. (2016), free amino acids (FAA) have been extracted, outlined and determined using the ninhydrin reagent technique according to Verslues (2010).

The oven-dried samples (at 70 °C for 72 hours) were powdered. Analysis of total carbohydrates was implemented according to Herbert et al. (1971). The N, P, and K contents of the produced grains were measured by a method designated by Ohyama et al. (1991) protocol. The total flavonoid content was established following the spectrophotometric method described by Dewanto et al. (2002). The antioxidant activities (DPPH radical scavenging) were determined using the technique of Liyana-Pathirana and Shahidi (2005). The grain protein, starch, gluten, and Zeleny sedimentation index percentages were established as the methods of AACC (2000). The American Association of Cereal Chemists (using the non-destructive grain analyzer, Model Infratec TM 1241 Grain Analyzer, ISW 5.00 valid from S/N 12414500, 1002 5017/Rev.1, manufactured by Foss Analytical AB, Hoganas, Sweden.

2.10. Statistical analysis

The trial was organized in a completely randomized block design (CRBD) with 4 replicates. Agreed that the trend was similar at two seasons, the similarity test using Bartlett's equation was used to integrate the analyses of the two seasons. The data were analysed by analysis of variance using to MSTAT-C (1989) statistical analysis program. Means were compared by using the Least Significant Difference (LSD) test at a 5% probability level. Minitab (2013) ver. 17.1.0.0 for Windows was used to analyze the results. Data were also subjected to principal component analysis (PCA) and Pearson correlation coefficient.

3. Results

3.1. The effect of water irrigation requirement on three wheat varieties

3.1.1. Growth parameters

The data in Table 3 explored the effect of different water irrigation requirements (100% and 75% WIR) on the growth of three wheat varieties (Gimeza 12, Sids 13, and Sakha 94). The results show that lowering WIR to 75% induced a significant decrease in growth parameters of the three studied varieties as compared with plants irrigated with 100% WIR. There are significant variations among varieties in the above-mentioned parameters. Sakha 94 variety recorded the highest values of fresh and dry weights of both shoot and root under both levels of irrigation (100% and 75%) as compared with the other two varieties.

Table 3
Effect of water irrigation requirements on growth parameters of different varieties of wheat plants (Gimeza 12, Sids 13, and Sakha94).

Water Requirements (m3 ha-1.)	Varieties	Shoot length (cm)	Leaves no.	Shoot fresh wt (g)	Shoot dry wt (g)	Root fresh wt (g)	Root dry wt (g)
100%	Gimeza 12	43.33±0.333	4.00±0.00	1.49±0.093	0.48±0.069	0.60±0.062	0.29±0.034
	Sids 13	46.33±1.856	5.00±0.333	1.62±0.020	0.68±0.018	0.61±0.007	0.27±0.024
	Sakha94	37.00±0.882	5.67±0.333	1.93±0.283	0.71±0.033	1.81±0.036	0.63±0.031
75%	Gimeza 12	34.33±0.333	4.00±0.333	1.27±0.122	0.34±0.020	0.40±0.048	0.17±0.041
	Sids 13	33.33±1.528	4.00±0.000	1.31±0.169	0.46±0.041	0.48±0.029	0.23±0.033
	Sakha94	32.73±0.882	5.00±0.000	1.45±0.144	0.50±0.080	0.64±0.074	0.56±0.075
LSD 5%		4.16	0.03	0.031	0.003	0.034	0.01

3.3.2. Photosynthetic pigment

The results in Figure 2 show that all photosynthetic pigment contents decreased significantly under lower WIR (75%) at the three studied varieties. There are significant variations among varieties in their chlorophyll contents under both WIR levels. Sakha 94 variety was surpassed in its photosynthetic contents under both levels of water irrigation, as compared with the other two varieties. Gimeza 12 variety comes after Sakha 94 in terms of photosynthetic content, followed by the Sids 13 variety.

Figure 2
(A-D): Effect of water irrigation requirements on photosynthetic pigment contents (µg/100g fresh weight) A (Chlorophyll a) B (Chlorophyll b) C (Carotenoids) and D (Total pigments of different varieties of wheat plants (Gimeza 12, Sids 13, and Sakha94).

3.3.3. Change in osmoprotectants

The results in Figure 3 show that all osmoprotectant contents (TSS, Pro, and FAA) increased significantly under lower WIR (75%) at the three studied varieties. There are significant variations among varieties in their TSS, Pro, and FAA contents under both WIR levels. The Sakha 94 variety had higher TSS, Pro, and FAA contents than the other two varieties at both water irrigation levels.

Figure 3
(A-C): Effect of water irrigation requirements on (Osmoprotectant) A (total soluble sugar), B (proline) and C (free amino acids) (mg/100g fresh weight) of different varieties of wheat plants (Gimeza 12, Sids 13, and Sakha94) at vegetative stage.

3.3.4. Yield constituents

Results in Table 4 showed different water irrigation requirements (100% and 75% WIR) effect on yield and yield components (plant height, spike length, spikelets no./spike, spike wt., grain wt./spike, 1000 grain wt, straw, grain and biological yield (ton ha^-1), HI, VWC, and STI of three wheat varieties (Gimeza 12, Sids 13, and Sakha 94). The results showed that decreasing the water requirement to 75% decreased all studied parameters significantly as compared with well-watered plants (100%) in three varieties. There are significant variations in the yield parameters response among the three varieties under different water irrigation levels. Where Sakha 94 surpassed all studied yield parameters, except spike length, which recorded the highest values at Sids 13 variety under both levels of irrigation. Virtual water content exhibits a different pattern, where the lowest values were recorded with the Sakha94 variety, followed by the Gimeza 12 variety and the Sids 13 variety under both levels of irrigation. The magnitude of increments in 1000-grain wt., grain, straw, biological yields, and HI in Sakha 94 variety, respectively, reached 5.47%, 12.14%, 6.91, 9.07%, and 23.37% as compared with Gimeza 12 variety grown under 100% WIR. While the percentage of increments reached 9.55%, 14.47%, 2.63%, 7.32% and 13.63% at the same variety irrigated with 75% WIR. The same trend of the Sakha 94 variety was observed as compared with the Sids 13 variety with more or less a percentage of increments under both WIR treatments. Sakha 94 variety recorded the lowest VWC under both WIR levels; this decrement is parallel to the highest STI at 75% WIR. The decrease reached 21.20% at 75% WIR, accompanied by the highest value (0.952) of STI.

Table 4
Effect of water irrigation requirements on yield and yield components, virtual water content, and stress tolerance at harvest (Data are means of two seasons).of different varieties of wheat plants (Gimeza 12, Sids 13, and Sakha94).

Traits	Varieties																		LSD 5%
	Gimeza 12						Sids 13						Sakha 94
	Water Irrigation Requirements (m3ha-1.)
	100%			75%			100%			75%			100%			75%
Shoot length (cm)	62.75	±	0.368	58.33	±	0.580	59.01	±	0.188	54.81	±	2.333	68.67	±	0.471	62.00	±	3.786	1.03
Spike length (cm)	9.33	±	0.333	8.00	±	0.333	9.98	±	0.000	9.33	±	0.167	9.77	±	0.563	9.17	±	0.167	0.26
Spikelet No/spike	14.00	±	0.333	13.67	±	0.000	16.00	±	0.577	16.00	±	0.000	16.00	±	0.000	15.00	±	0.577	0.20
Spike Wt. (g)	3.09	±	0.059	2.71	±	0.035	3.07	±	0.125	2.31	±	0.101	3.11	±	0.074	2.85	±	0.205	0.03
Grains wt./ spike (g)	2.76	±	0.029	2.19	±	0.078	2.41	±	0.018	2.11	±	0.098	2.83	±	0.026	2.52	±	0.045	0.19
1000 grains wt. (g)	40.10	±	0.072	35.70	±	0.030	40.47	±	0.023	36.47	±	0.500	42.42	±	0.010	39.47	±	0.265	0.76
Straw yield ton ha-1.	7.14	±	0.038	6.84	±	0.061	7.17	±	0.089	6.76	±	0.024	7.67	±	0.022	6.98	±	0.023	0.02
Grains yield ton ha-1.	4.74	±	0.038	4.39	±	0.036	4.54	±	0.023	4.17	±	0.017	5.39	±	0.042	5.13	±	0.020	0.12
Biological yield ton ha-1.	11.88	±	0.060	11.23	±	0.052	11.71	±	0.033	10.93	±	0.026	13.06	±	0.046	12.12	±	0.023	0.16
harvest index HI %	36.65	±	0.140	37.95	±	0.208	37.49	±	0.095	37.48	±	0.251	47.83	±	0.336	43.94	±	0.243	0.75
Virtual water content VWC (m3. ton-1)	1255.54	±	7.899	1016.40	±	8.478	1310.57	±	4.892	1070.02	±	4.587	1103.08	±	10.210	869.28	±	5.555	26.92
Stress tolerance STI	0.00	±	0.000	0.93	±	0.060	0.00	±	0.000	0.92	±	0.105	0.00	±	0.000	0.95	±	0.013	0.01

The results in Figure 4 showed that decreasing the water irrigation requirement to 75% lowered carbohydrates and starch contents (%) and improved protein, gluten, and Zeleny sedimentation contents (%) in three varieties as compared with the control (100% WIR). Sakha 94 variety surpassed Gimeza 12 variety and Sids 13 variety in all studied nutritional values of wheat grain irrigated with either 100% or 75% WIR.

Figure 4
(A-E): Effect of water irrigation requirements and variety differences of wheat (Gimeza 12, Sids 13, and Sakha94) on grain nutritional values (%) A (carbohydrate) B (Starch) C (Protein) D (Glitein) and (Zeleny) at harvest.

The results (Figure 5) presented that decreasing WIR to 75% led to significant increases in flavonoids and antioxidant activities % as compared with corresponding controls (100% WIR). There are highly significant variations among the three varieties in their response to drought stress.

Figure 5
(A-B): Effect of water irrigation requirements and variety differences of wheat grains (Gimeza 12, Sids 13, and Sakha94) on (A) flavonoids and (B) antioxidant activities (%) at harvest.

Gimeza-12 variety significantly surpassed on their content of flavonoids and antioxidant activities % as compared with Sids-13 and Sakha 94 varieties in plants grown under well-watered (100% WIR) conditions. Sakha 94 variety has the highest values on both flavonoids and antioxidant activities % as compared with the other two varieties grown under stressed conditions (75% WIR).

The results also show that decreasing WIR to 75% led to significant increases in WP as compared with corresponding controls (100% WIR) of three varieties (Figure 6). There are highly significant variations in WP among three varieties of response to drought stress. Gimeza-12 variety surpassed significantly on WP content as compared with Sids-13 or Sakha 94 varieties in plants grown under either normal or stressed conditions. Sids 13 variety induced the highest WP value under well-watered conditions after Gimeza 12 variety. While the Sakha 94 variety induced the highest WP value under stressed conditions after the Gimeza 12 variety.

Figure 6
Effect of water irrigation requirements and variety differences of wheat grains (Gimeza 12, Sids 13, and Sakha94) on water productivity (%) at harvest (Data are means of two seasons).

3.4. Pearson correlation coefficient (PCC) heat map matrix, with significance levels and Principal Component Analysis

To convert data into a new coordinate system where the variance of the data is optimum along the principal components (PCs) in linear combinations of the original variables, the principal component analysis (PCA) is a useful method for data analysis and dimensionality reduction. According to this study, the second PC (PC2) explains the least significant amount of variation (24.39%), whereas the first PC (PC1) explains the largest overall variance (47.24%). More than 71.33% of the overall variation was shown by PCs 1 and 2 (Figure 7) The correlation coefficients between several characteristics and factors of wheat plants are shown in Figure 8. Strong negative correlations are denoted by a correlation value of -1, strong positive correlations by a correlation coefficient of 1, and no correlations are indicated by a correlation coefficient of 0. The summary of the correlations was, Grain yield per spike showed positive correlations with 1000-grain weight, grain yield/ha, biological yield/ha, carbohydrates %, starch %, virtual water content (WC), and harvest index (HI), but negative correlations with straw yield/ha, protein %, gluten %, flavonoids, DPPH%, water productivity (WP), total pigments, TSS, proline, and FAA. The 1000-grain weight was positively correlated with straw yield/ha, grain yield/ha, biological yield/ha, starch %, protein %, gluten %, total pigments, virtual WC, and HI, while showing negative correlations with carbohydrates %, flavonoids, DPPH%, WP, TSS, proline, and FAA. Straw yield/ha was positively associated with grain yield/ha, biological yield/ha, starch %, protein %, gluten %, flavonoids, DPPH%, and WP. Grain yield/ha was positively correlated with biological yield/ha, carbohydrates %, starch %, protein %, total pigments, virtual WC, and HI. Biological yield/ha showed positive correlations with carbohydrates %, starch %, protein %, gluten %, virtual WC, and HI. Carbohydrates % was positively correlated with protein %, WP, HI, TSS, proline, and FAA. Starch % showed positive correlations with protein %, gluten %, virtual WC, HI, and total pigments. Protein % was positively correlated with gluten %, DPPH%, virtual WC, TSS, proline, and FAA. Gluten % was positively associated with DPPH%, total pigments, virtual WC, and TSS. Flavonoids were positively correlated with DPPH%, WP, TSS, proline, and FAA, while DPPH% was positively correlated with WP, TSS, proline, and FAA. Water productivity (WP) was positively correlated with TSS, proline, and FAA, indicating strong interrelationships among yield, quality, and physiological traits.

Figure 7
Principal component analysis (PCA) of growth, physiological, biochemical, and grain yield ‎traits in the investigated three wheat cultivars (Sakha-9‎‏4 ‏‎(C1), Sids-13(C2) and Gmmizah-1‎‏2‏‎(C3) under ‎two water irrigation levels (w1 and w2) grown under sandy soil conditions. PCA loading plot of 19 ‎measured traits.‎

Figure 8
Correlogram analysis of all investigated traits of grains yield/ spike, 1000 grains wt., Straw yield/ha, Grain yield/ha, biological yield/ha, Carbohydrates %, Starch %, Protein %, Glutein %, Flavonoids, DPPH %, WP, Total pigment, virtual WC, HI, TSS, Proline, FAA as affected by drought stress at rates of (75, 100 %) of three wheat cultivars grown in sandy soil conditions.

4. Discussion

Drought represents a pronounced threat to crop production all over the world. This threat will be augmented in the structure of global climate change, as well as the regularity and rigor of different stresses. Additionally, drought may cause an injury in growth and crop production by more than 50% (Abdallah et al. 2020; Nazari et al., 2023).

In this connection, the results proved that decreasing WIR from 100% to 75% induced a significant reduction in most studied parameters (growth, yield components, carbohydrates, and starch of yielded grains) as compared with the control plant. At the same time, drought stress induced significant increases in some parameters (protein, gluten, Zeleny sedimentation, flavonoids & DPPH of yielded grains, and water productivity) under this study compared to well-watered plants. The reduction in growth, yield and its attributes according to drought stress may be due to their negative effect on vegetative growth, consequently affecting the yield component. These trends may also be discussed as the decline in nutrient availability or the physiological disruption triggered by the rise in osmotic stress associated with a drop in cell enlargement, cell turgor, cell volume, and eventually cell growth. Drought stress at any particular stage or during the entire growing season considerably reduced the growth, yield and components of yield in wheat crops (Nyaupane et al., 2024). These diminutions may be ascribed to the disturbed nutrient uptake efficiency and photosynthate translocation within the plant (Rehman‎ et al., 2021; Seleiman et al., 2021). In this regard, deficit irrigation induced a significant, gradual decrease in wheat growth and productivity. Fresh and dry weights and shoot and root lengths are considered critical criteria for indicating drought-tolerant wheat genotypes (Shahid et al., 2022). They added that mechanisms such as antioxidant defenses and osmoregulation can be established to be accountable for tolerance in wheat genotypes with variable shoot-root dry weight reduction (Shahid et al., 2022). Water shortage stress adjusts the osmotic potential of the cell, resulting in inefficient cell division and a loss in root and shoot fresh and dry weights (Tatar et al., 2020; Turan‎ et al., 2023; Bakry et al., 2024). In this connection, Amoah et al. (2019) stated that in wheat genotypes under drought stress, leaf and root dry weights dropped up to 35.75% and 67.67%, respectively. Recently, Omar et al. (2023) and Baghery et al. (2023) reported that drought stress caused the maximum drop in all growth parameters of wheat and sesame, respectively.

In this regard, wheat grains were more harmfully affected by deficit irrigation on the filling and development stages of wheat grains; this is concomitant with the gradual reduction in the harvest index values (Saad et al., 2023). The deleterious effects of deficit irrigation on crop productivity are studied on wheat (Ding et al., 2021; Bayisa ‎ et al., 2024) and maize Gao et al. (2025). Growth and yield constituents were also negatively affected by irrigation shortage, such as spike length and weight, spike number per plant, tiller number per unit area, and 1000-grain weight. The reduction in grain numbers for each spike was due to the effect of drought on several reproductive processes associated with grain formation. Also, the results of Ishfaq et al. (2024) stated that wheat yield under drought stress was reduced significantly by about 45%. They added that the higher yield in a well-watered environment might be due to a higher gains filling period and a greater number of wheat grains per spike. Therefore, under stressful circumstances, a positive correlation was observed amongst grain yield, grain filling duration, grain filling rate, grains for each spike, plant height, productive tillers for each plant, and spikelet numbers for each spike. Recently, Raza et al. (2025) concluded that water shortage affects wheat directly on yield and yield attributes; the yield drops due to persistent drought stress.

Water shortage from seedling to maturity lowered grain yield, specifically grain number for each head, number of fertile ears for each unit area, and dry matter weight. Hence, stress commonly depresses wheat grain yield and can decline the importance of other yield-contributing traits of commercial yield (Tatar et al., 2020). Diminishing the irrigation level for wheat plants from 100% to 75% of WIR led to significant reductions in wheat virtual water content (VWC). The stress tolerance index (STI) was also decreased significantly for all varieties when subjected to deficit irrigation. These results are in harmony with those obtained by Saad et al. (2023) on wheat varieties.

The decline in the total carbohydrates and starch contents in wheat grains in response to water deficiency may be due to the adjustment of metabolites to face the destructive effect of drought on chlorophyll contents and the transformation of metabolites from source to sink under stress conditions. These results are concomitant with the outcomes of Chauhan et al. (2023) and Spanic et al. (2025) on wheat plants. This change may act as a conventional metabolic signal as a response to water shortage stress, where the function of these sugars in this signaling is affected variously by stress power, either in their accumulation or decrease in their concentrations (Aubry et al., 2024).

According to starch content, Saha et al. (2022) reported that the reduction in starch during drought stress is due to less transfer of these compounds from the leaves and slower consumption due to starch hydrolysis and depends on the activity of hydrolytic enzymes. Moreover, due to the disturbance of physiological and biochemical processes of starch biosynthesis, drought stress hastens the onset and filling time of the grain and reduces the accumulation of starch (Lamlom et al., 2025) reduced the activity of critical enzymes and gene expression in connection with the transformation from sucrose to starch, which was the main reason for the decrease in starch content Sheng et al. (2023) which changes the productivity of wheat production. Moreover, Nyaupane et al. (2024) concluded that drought stress accelerated the grain-filling process and shortened its duration, which caused a drop-in starch accumulation time and earlier maturation than the control.

Drought stress significantly increased the contents of protein, gluten and Zeleny sedimentation ratio in this study as compared with the corresponding control. These results may be attributed to the harmful effect of drought on starch accumulation. The results are in good harmony with those obtained by Rekowski et al. (2021) who found that drought stress expressively improved protein content. Many authors suggested that the increase in grain protein percentage due to drought stress in wheat grains may be attributed to diminished starch accumulation Nyaupane et al. (2024). In this connection, Abd El-Aty et al. ‎ (2024) concluded that drought stress increased significantly protein, glutenin contents and zeleny index of several wheat genotypes. These results were accompanied by a deterioration in the grain yield and the thousand-kernel weight. Also, a positive correlation of grain protein content with dry and wet gluten content was reported by Hao et al. (2023). Moreover, Koua et al. (2021) and Chen‎ et al. (2023) concluded that drought stress disturbs the protein ratio to starch and increases the amount of protein per unit volume. Recently, the increase in protein content in response to drought stress during the grain-filling period can be due to the alteration of source-to-sink C partitioning; and consequently, interactions with metabolism and partitioning of N in both sources and sinks (Mahdavi et al., 2022). They also proposed momentous increases in Zeleny sedimentation volume, dry gluten content (DG), wet gluten content (WG), and gluten index (GI), which were found following stress.

Flavonoids and DPPH were remarkably increased with the severity of drought stress. Also, Netshimbupfe et al. (2023) established that water shortage encouraged the quantitative and qualitative stimulus of nutritional and bioactive compounds, phenolic acids, flavonoids, and antioxidants. In this regard, Mutha et al. (2021) reported that flavonoids represent 60% of total dietary phenolic compounds in plants. Moreover, Sharma et al. (2022) found that diverse secondary metabolites are excited by plants in several growth conditions to effectuate several cellular activities needed for physiological processes. The improvement of total phenolic content under drought stress was observed in medicinal plants Albergaria et al. (2020), rice, Kumar et al. (2023). Growth, genotype, species, developmental stage, environmental conditions, and physiology all control the type and concentration of a plant's secondary molecules (s) Sallam et al. (2022). Environmental stress fabricates the ROS when the plant is exposed to this stress condition and stimulates antioxidants, flavonoids, and secondary metabolites for plant protection against the detoxifying ROS and protects the protein, causing amino acid stabilization (Sallam et al., 2022). In addition, several studies proved the high correlation between total phenolic content and antioxidant activity (Masante et al., 2024). Generally, free radical scavenging capacity improved with the presence of promoting phenols in the plant extracts. This high correlation was recorded between antioxidant activity data from DPPH (Akullo et al., 2023: Ramadan et al., 2025).

The results indicated that WP increased significantly when plants were subjected to water deficits. Crop water productivity (CWP) expresses the link between crop productivity and the water used in crop production (Letseku‎ and Grove, 2022). In this regard, Weerarathne‎ et al. (2023) explained the correlation between WUE and drought stress; they postulated that WUE was enhanced under drought conditions. Some global-scale studies revealed that the effect of drought on WUE was contingent on vegetation types. When drought occurs, shrubland WUE tends to increase, whereas cropland and grassland WUE will decrease in most cases, while forest experiences both an increase and a decrease in WP (Asafadi et al. 2024). In this regard, the control of drought on WUE is also connected with the severity and duration of drought (Banibayat et al., 2022). In this regard, El Bassiouny et al. (2022) demonstrated that the ratio of grain yield to water used is inversely proportional to the intensity of water stress and linked with crop water productivity (WP) in general. Plants exposed to less WIR caused significant increases in water productivity as compared with control plants well WIR in wheat varieties. During water stress, stomatal closure leads to reduced leaf conductance, photosynthesis, and transpiration, leading to more conservative usage of water, resulting in higher WP in water-lacking plants, which might be a mechanism for improving resource use efficacy.

There are significant variations among three varieties under this study in their response to all the above-studied parameters. This variation may be due to their variation in genotypes, which affects the response of the plant to several stress conditions. These results proved the obtained data by Seleiman et al. (2021) who stated that, number of nutritional components of plants or grains as carbohydrates, protein contents are depend on agronomical practices, genotypes and drought stresses. Moreover, El-Bassiouny et al. (2022) proved that the variation in protein bands depends on the wheat variety, and exhibited that Gimeza 12 exceeded the Sids 13 variety by the rise in density, intensity, and number of protein bands. These outcomes were accompanied by the uppermost grain yield of Gimeza 12 than the Sids 13 variety. Moreover, Gimeza 12 variety was more lenient to water shortage than the Sids 13 variety.

5. Conclusion

In the present study, the growth and yield characteristics of three varieties of wheat grains were reduced due to water stress. The reduction in the growth and yield characteristics of stressed wheat varieties can be attributed to the plants grown under drought conditions having a lower stomatal conductance to conserve water. Consequently, CO2 fixation is reduced and decreases in photosynthetic pigments, carbohydrate accumulation, nitrogenous and phenolic compounds in the yielded grains. Water stress produced an opposing influence on plants through decreased growth, development, photosynthetic efficiency, and water status. Thus, plants use various techniques to increase growth efficiency to maintain the yield quality under stress. It worthy to conclude that, Sakha-94 variety contains the highest values of photosynthetic pigment contents, osmoprotectant contents which reflected as high growth, yield quantity and quality, virtual water content VWC and water productivity. So, it considers more tolerant to drought by producing the highest grain yield than other varieties (Gimeza-12 and Sids-13).

Data Availability Statement

The corresponding author can provide the datasets used and/or analyzed during the current work upon proper request.

References

• ABD EL-ATY, M., GAD, K., HEFNY, Y. and SHEHATA, M., 2024. Performance of some wheat (Triticum aestivum L.) genotypes and their drought tolerance indices under normal and water stress. Egyptian Journal of Soil Science, vol. 64, no. 1, pp. 19-30. https://doi.org/10.21608/ejss.2023.234140.1657
  » https://doi.org/10.21608/ejss.2023.234140.1657
• ABDALLA, A., STELLMACHER, T. and BECKER, M., 2023. Trends and Prospects of Change in Wheat Self-Sufficiency in Egypt. Agriculture, vol. 13, no. 1, pp. 7. https://doi.org/10.3390/agriculture13010007
  » https://doi.org/10.3390/agriculture13010007
• ABDALLAH, M.M.S., BAKRY, A.B., EL-BASSIOUNY, H.M.S. and ABD EL-MONEM, A.A., 2020. Growth, yield and biochemical impact of some anti-transpirants on sunflower plants grown under water deficit. Pakistan Journal of Biological Sciences : PJBS, vol. 23, no. 4, pp. 454-466. https://doi.org/10.3923/pjbs.2020.454.466 PMid:32363831.
  » https://doi.org/10.3923/pjbs.2020.454.466
• AHLUWALIA, O., SINGH, P.C. and BHATIA, R.A., 2021. Review on drought stress in plants: implications, mitigation and the role of plant growth promoting rhizobacteria. Resources of Environmental Sustainability, vol. 5, pp. 100032. https://doi.org/10.1016/j.resenv.2021.100032
  » https://doi.org/10.1016/j.resenv.2021.100032
• AKULLO, J.O., KIAGE-MOKUA, B.N., NAKIMBUGWE, D., NG’ANG’A, J. and KINYURU, J., 2023. Phytochemical profile and antioxidant activity of various solvent extracts of two varieties of ginger and garlic. Heliyon, vol. 9, no. 8, pp. e18806. https://doi.org/10.1016/j.heliyon.2023.e18806 PMid:37576272.
  » https://doi.org/10.1016/j.heliyon.2023.e18806
• ALBALASMEH, A.A., BERHE, A.A. and GHEZZEHEI, T.A., 2013. A new method for rapid determination of carbohydrate and total carbon concentrations using UV spectrophotometry. Carbohydrate Polymers, vol. 97, no. 2, pp. 253-261. https://doi.org/10.1016/j.carbpol.2013.04.072 PMid:23911443.
  » https://doi.org/10.1016/j.carbpol.2013.04.072
• ALBERGARIA, E.T., OLIVEIRA, A.F.M. and ALBUQUERQUE, U.P., 2020. The effect of water deficit stress on the composition of phenolic compounds in medicinal plants. South African Journal of Botany, vol. 131, pp. 12-17. https://doi.org/10.1016/j.sajb.2020.02.002
  » https://doi.org/10.1016/j.sajb.2020.02.002
• ALLEN, R.G., JENSEN, M.E., WRIGHT, J.L. and BURMAN, R.D., 1989. Operational estimates of reference evapotranspiration. Agronomy Journal, vol. 81, no. 4, pp. 650-662. https://doi.org/10.2134/agronj1989.00021962008100040019x
  » https://doi.org/10.2134/agronj1989.00021962008100040019x
• ALSAFADI, K., BASHIR, B., MOHAMMED, S., ABDO, H.G., MOKHTAR, A., ALSALMAN, A. and CAO, W., 2024. Response of ecosystem carbon–water fluxes to extreme drought in West Asia. Remote Sensing (Basel), vol. 16, no. 7, pp. 1179. https://doi.org/10.3390/rs16071179
  » https://doi.org/10.3390/rs16071179
• AMERICAN ASSOCIATION OF CEREAL CHEMISTS – AACC, 2000. Approved methods of the AACC 10th ed. St. Paul: AACC.
• AMOAH, J.N., KO, C.S., YOON, J.S. and WEON, S.Y., 2019. Effect of drought acclimation on oxidative stress and transcript expression in wheat (Triticum aestivum L.). Journal of Plant Interactions, vol. 14, no. 1, pp. 492-505. https://doi.org/10.1080/17429145.2019.1662098
  » https://doi.org/10.1080/17429145.2019.1662098
• AUBRY, E., CLEMENT, G., GILBAULT, E., DINANT, S. and LE HIR, R., 2024. Changes in SWEET-mediated sugar partitioning affect photosynthesis performance and plant response to drought. Physiologia Plantarum, vol. 176, no. 6, pp. e14623. https://doi.org/10.1111/ppl.14623 PMid:39535317.
  » https://doi.org/10.1111/ppl.14623
• BAGHERY, M.A., KAZEMITABAR, S.K., DEHESTANI, A. and MEHRABANJOUBANI, P., 2023. Sesame (Sesamum indicumL.) response to drought stress: susceptible and tolerant genotypes exhibit different physiological, biochemical, and molecular response patterns. Physiology and Molecular Biology of Plants : an International Journal of Functional Plant Biology, vol. 29, no. 9, pp. 1353-1369. https://doi.org/10.1007/s12298-023-01372-y PMid:38024952.
  » https://doi.org/10.1007/s12298-023-01372-y
• BAKRY, A.B., ABD EL-MONEM, A.A., ABDALLAH, M.M.S., AL-ASHKAR, N.M. and EL-BASSIOUNY, H.M.S., 2024. ‎‎Impact of titanium-dioxide and zinc-oxide nanoparticles in improving wheat productivity ‎under water stress conditions. SABRAO Journal of Breeding and Genetics, vol. 56, no. 2, pp. 823-837. https://doi.org/10.54910/sabrao2024.56.2.33
  » https://doi.org/10.54910/sabrao2024.56.2.33
• BANIBAYAT, A., GHORBANIZADEH, K.H. and ESLAMI, H., 2022. Drought monitoring in bivariate probabilistic framework for the maximization of water Use efficiency. Civil Engineering (Shiraz), vol. 46, no. 1, pp. 573-584. https://doi.org/10.1007/s40996-021-00589-9
  » https://doi.org/10.1007/s40996-021-00589-9
• BAYISA, G.D., AYANA, M., DINKA, M.O., HORDOFA, T. and MEKONNEN, B., 2024. Effect of Deficit Irrigation on Wheat (Triticum aestivum L.) Yield and Water Use Efficiency in the Semi-Arid Region of Awash Basin, Ethiopia. Air, Soil and Water Research, vol. 17, pp. 11786221241274019. https://doi.org/10.1177/11786221241274019
  » https://doi.org/10.1177/11786221241274019
• CHAPMAN, H.O. and PRATT, P.E., 1987. Methods of analysis for soils. Plants and Water University of California Agriculture. Science Priced Publication, vol. 4034, pp. 50.
• CHAUHAN, J., PRATHIBHA, M.D., SINGH, P., CHOYAL, P., MISHRA, U.N., SAHA, D., KUMAR, R., ANURAGI, H., PANDEY, S., BOSE, B., MEHTA, B., DEY, B., DWIVEDI, K.K., GUPTA, N.K. and SINGHAL, R.K., 2023. Plant photosynthesis under abiotic stresses: damages, adaptive, and signaling mechanisms. Plant Stress, vol. 10, pp. 100296. https://doi.org/10.1016/j.stress.2023.100296
  » https://doi.org/10.1016/j.stress.2023.100296
• CHEN, G., PENG, L., GONG, J., WANG, J., WU, C., SUI, X., TIAN, Y., HU, M., LI, C., HE, X., YANG, H., ZHANG, Q., OUYANG, Y., LAN, Y. and LI, T., 2023. Effects of water stress on starch synthesis and accumulation of two rice cultivars at different growth stages. Frontiers in Plant Science, vol. 14, pp. 1133524. https://doi.org/10.3389/fpls.2023.1133524 PMid:37180383.
  » https://doi.org/10.3389/fpls.2023.1133524
• CHEN, Z., QIN, H., ZHANG, X., XUE, H., WANG, S. and ZHANG, H., 2024. The impact of meteorological drought at different time scales from 1986 to 2020 on vegetation changes in the shendong mining area. Remote Sensing (Basel), vol. 16, no. 15, pp. 2843. https://doi.org/10.3390/rs16152843
  » https://doi.org/10.3390/rs16152843
• DEWANTO, V., WU, X., ADOM, K.K. and LIU, R.H., 2002. Thermal processing enhances the nutritional value of tomatoes by increasing total antioxidant activity. Journal of Agricultural and Food Chemistry, vol. 50, no. 10, pp. 3010-3014. https://doi.org/10.1021/jf0115589 PMid:11982434.
  » https://doi.org/10.1021/jf0115589
• DING, Z., ALI, E.F., ELMAHDY, A.M., RAGAB, K.E., SELEIMAN, M.F. and KHEIR, A.M., 2021. Modeling the combined impacts of deficit irrigation, rising temperature and compost application on wheat yield and water productivity. Agricultural Water Management, vol. 244, pp. 106626. https://doi.org/10.1016/j.agwat.2020.106626
  » https://doi.org/10.1016/j.agwat.2020.106626
• DUBEY, R., PANDY, B., SAWANT, S. and SHRIKE, P., 2023. Drought stress inhibits stomatal development to improve water use efficiency in cotton. Acta Physiologiae Plantarum, vol. 45, no. 2, pp. 30. https://doi.org/10.1007/s11738-022-03511-6
  » https://doi.org/10.1007/s11738-022-03511-6
• EL SAYED, L.M., 2021 [viewed 23 December 2025]. Determining an optimum cropping pattern for Egypt [online]. New Cairo: The American University in Cairo. AUC Knowledge Fountain. Thesis. Available from: https://fount.aucegypt.edu/retro_etds/2413
  » https://fount.aucegypt.edu/retro_etds/2413
• EL-BASSIOUNY, H.M.S., MAHFOUZE, H.A., ABDALLAH, M.M.S., BAKRY, B.A. and EL-ENANY, M.A.M., 2022. Physiological and molecular response of wheat cultivars to titanium dioxide or zinc oxide nanoparticles under water stress conditions. International Journal of Agronomy, vol. 2022, pp. 3806574. https://doi.org/10.1155/2022/3806574
  » https://doi.org/10.1155/2022/3806574
• ELNAJAR, M., ALDESUQUY, H., ABDELMOTELEB, M. and ELTANAHY, E., 2024. Mitigating drought stress in wheat plants (Triticum AestivumL.) through grain priming in aqueous extract ofSpirulina platensis. BMC Plant Biology, vol. 24, no. 1, pp. 233. https://doi.org/10.1186/s12870-024-04905-z PMid:38561647.
  » https://doi.org/10.1186/s12870-024-04905-z
• FARHAN, M., YANG, J., WU, T., WANG, S., ZHAO, X. and TARIQ, A., 2024. Impact assessment of agricultural droughts on water use efficiency in different climatic regions of punjab province pakistan using MODIS time series imagery. Hydrological Processes, vol. 38, no. 7, pp. e15232. https://doi.org/10.1002/hyp.15232
  » https://doi.org/10.1002/hyp.15232
• FRANTOVA, N., RABEK, M., ELZNER, P., STREDA, T., JOVANOVIC, I., HOLKOVA, L., MARTINEK, P., SMUTNA, P. and PRASIL, I.T., 2022. Different drought tolerance strategy of wheat varieties in spike architecture. Agronomy (Basel), vol. 12, no. 10, pp. 2328. https://doi.org/10.3390/agronomy12102328
  » https://doi.org/10.3390/agronomy12102328
• GAO, J., LI, L., DING, R., KANG, S., DU, T., TONG, L., KANG, J., XU, W. and TANG, G., 2025. Grain yield and water productivity of maize under deficit irrigation and salt stress: evidences from field experiment and literatures Agric. Agricultural Water Management, vol. 307, pp. 109260. https://doi.org/10.1016/j.agwat.2024.109260
  » https://doi.org/10.1016/j.agwat.2024.109260
• GOMEZ, L., RUBIO, E. and AUGÉ, M., 2002. A new procedure for extraction and measurement of soluble sugars in ligneous plants. Journal of the Science of Food and Agriculture, vol. 82, no. 4, pp. 360-369. https://doi.org/10.1002/jsfa.1046
  » https://doi.org/10.1002/jsfa.1046
• HAO, T., CHEN, R., JIA, J., ZHAO, C., DU, Y., LI, W., ZHAO, L. and DUAN, H., 2023. Enhancing wheat gluten content and processing quality: an analysis of drip irrigation nitrogen frequency. Plants, vol. 12, no. 23, pp. 3974. https://doi.org/10.3390/plants12233974 PMid:38068610.
  » https://doi.org/10.3390/plants12233974
• HARDER, P., HELGASON, W.D., JOHNSON, B. and POMEROY, J.W., 2023. Crop water use efficiency from eddy covariance methods in cold water-limited regions. Agricultural and Forest Meteorology, vol. 341, pp. 109657. https://doi.org/10.1016/j.agrformet.2023.109657
  » https://doi.org/10.1016/j.agrformet.2023.109657
• HERBERT, D., PHIPPS, P.J. and STRANGE, R.E., 1971. Chemical analysis of microbial cells. Methods in Microbiology, vol. 5B, pp. 209-344. https://doi.org/10.1016/S0580-9517(08)70641-X
  » https://doi.org/10.1016/S0580-9517(08)70641-X
• HOWELL, T.A., CUENCE, R.H. and SOLOMON, K.H., 1990. Crop yield response, in management of farm irrigation systems. In: G.J. HOFFMAN, T.A. HOWELL and K.H. SOLOMON, eds., Management of farm irrigation systems St. Joseph, MI, USA: ASAE, p. 31.
• HUANG, C., QIN, A., GAO, Y., MA, S., LIU, Z., ZHAO, B., NING, D., ZHANG, K., GONG, W., SUN, M. and LIU, Z., 2023. Effects of water deficit at different stages on growth and ear quality of waxy maize. Frontiers in Plant Science, vol. 14, pp. 1069551. https://doi.org/10.3389/fpls.2023.1069551 PMid:36818831.
  » https://doi.org/10.3389/fpls.2023.1069551
• ISHFAQ, N., WARAICH, E.A., AHMAD, M., HUSSAIN, S., ZULFIQAR, U., DIN, K.U., HAIDER, A., YONG, J.W.H., ASKRI, S.M.H. and ALI, H.M., 2024. Mitigating drought-induced oxidative stress in wheat (Triticum aestivum L.) through foliar application of sulfhydryl thiourea. Scientific Reports, vol. 14, no. 1, pp. 15985. https://doi.org/10.1038/s41598-024-66506-y PMid:38987560.
  » https://doi.org/10.1038/s41598-024-66506-y
• KALSOOM, U., BENNETT, I.J. and BOYCE, M.C., 2016. A review of extraction and analysis: methods for studying osmoregulants in plants. Journal of Chromatography & Separation Techniques, vol. 7, no. 1, pp. 1000315. https://doi.org/10.4172/2157-7064.1000315
  » https://doi.org/10.4172/2157-7064.1000315
• KELLER, J., KARMELI, D. and TRICKLE, D., 1975. Rain Bird Sp. Man. Glendora U.S.A..
• KOUA, A.P., OYIGA, B.C., BAIG, M.M., LEON, J. and BALLVORA, A., 2021. Breeding driven enrichment of genetic variation for key yield components and grain starch content under drought stress in winter wheat. Frontiers in Plant Science, vol. 12, pp. 684205. https://doi.org/10.3389/fpls.2021.684205 PMid:34484257.
  » https://doi.org/10.3389/fpls.2021.684205
• KUMAR, S., SEEM, K. and MOHAPATRA, T., 2023. Biochemical and epigenetic modulations under drought: remembering the stress tolerance mechanism in rice. Life (Basel, Switzerland), vol. 13, no. 5, pp. 1156. https://doi.org/10.3390/life13051156 PMid:37240801.
  » https://doi.org/10.3390/life13051156
• LAMLOM, S.F., ABDELGHANY, A.M., FAROUK, A.S., ALWAKEL, E.S., MAKLED, K.M., BUKHARI, N.A., HATAMLEH, A.A., REN, H., EL-SORADY, G.A. and SHEHAB, A.A., 2025. Biochemical and yield response of spring wheat to drought stress through gibberellic and abscisic acids. BMC Plant Biology, vol. 25, no. 1, pp. 5. https://doi.org/10.1186/s12870-024-05879-8 PMid:39748257.
  » https://doi.org/10.1186/s12870-024-05879-8
• LETSEKU, V. and GROVE, B., 2022. crop water productivity, applied water productivity and economic decision making. Water (Basel), vol. 14, no. 10, pp. 1598. https://doi.org/10.3390/w14101598
  » https://doi.org/10.3390/w14101598
• LI, J., LIANG, Z., LI, Y., WANG, K., NANGIA, V., MO, F. and LIU, Y., 2024. Advantageous spike-to-stem competition for assimilates contributes to the reduction in grain number loss in wheat spikes under water deficit stress. Agricultural Water Management, vol. 292, pp. 108675. https://doi.org/10.1016/j.agwat.2024.108675
  » https://doi.org/10.1016/j.agwat.2024.108675
• LICHTENTHALER, H.K. and BUSCHMANN, C., 2001. Chlorophylls and carotenoids: measurement and characterization by UV-VIS spectroscopy. In: R.E. WROLSTAD, T.E. ACRETE, H. AN, E.A. DECKER, M.H. PENNER, D.S. REID, S.J. SCHWARTZ, C.F. SHOEMAKER and P. SPORNS, eds. Current protocols in food analytical chemistry (CPFA) New York: John Wiley and Sons, pp. F4.3.1-F4.3.8.
• LIYANA-PATHIRANA, M. and SHAHIDI, F., 2005. Antioxidant activity of commercial soft and hard wheat (Triticum aestivum L.) as affected by gastric pH conditions. Journal of Agricultural and Food Chemistry, vol. 53, no. 7, pp. 2433-2440. https://doi.org/10.1021/jf049320i PMid:15796575.
  » https://doi.org/10.1021/jf049320i
• MAHDAVI, S., ARZANI, A., MIRMOHAMMADY MAIBODY, S.A.M. and KADIVAR, M., 2022. Grain and flour quality of wheat genotypes grown under heat stress. Saudi Journal of Biological Sciences, vol. 29, no. 10, pp. 103417. https://doi.org/10.1016/j.sjbs.2022.103417 PMid:36072014.
  » https://doi.org/10.1016/j.sjbs.2022.103417
• MASANTE, T., CAFA, S. and DI IORIO, A., 2024. Total polyphenol content and antioxidant activity of leaves and fine roots as indicators of drought resistance in the NativeQuercus roburand AlienQuercus rubra. Forests, vol. 15, no. 9, pp. 1647. https://doi.org/10.3390/f15091647
  » https://doi.org/10.3390/f15091647
• MINITAB, 2013. Minitab statistical software, release 17.1 for Windows, State College, Pennsylvania Minitab, Inc.
• MSTAT-C, 1989. Microcomputer Program for the Design, Arrangement, and Analysis of Agronomic Research East Lansing, East Lansing: Michigan State Univ.
• MUHAMMAD, M., WAHEED, A., WAHAB, A., MAJEED, M., NAZIM, M., LIU, Y.H., LI, L. and LI, W.J., 2024. Soil salinity and drought tolerance: an evaluation of plant growth, productivity, microbial diversity, and amelioration strategies. Plant Stress, vol. 11, pp. 100319. https://doi.org/10.1016/j.stress.2023.100319
  » https://doi.org/10.1016/j.stress.2023.100319
• MUTHA, R.E., TATIYA, A.U. and SURANA, S.J., 2021. Flavonoids as natural phenolic compounds and their role in therapeutics: an overview. Future Journal of Pharmaceutical Sciences, vol. 7, no. 1, pp. 25. https://doi.org/10.1186/s43094-020-00161-8 PMid:33495733.
  » https://doi.org/10.1186/s43094-020-00161-8
• NAZARI, M., GHASEMI-SOLOKLUI, A.A., KORDROSTAMI, M. and LATEF, A.A.H., 2023. Deciphering the response of medicinal plants to abiotic stressors: a focus on drought and salinity. Plant Stress, vol. 10, pp. 100255. https://doi.org/10.1016/j.stress.2023.100255
  » https://doi.org/10.1016/j.stress.2023.100255
• NETSHIMBUPFE, M.H., BERNER, J., VAN DER KOOY, F., OLADIMEJI, O. and GOUWS, C., 2023. Influence of Drought and Heat Stress on Mineral Content, Antioxidant Activity and Bioactive Compound Accumulation in Four African Amaranthus Species. Plants, vol. 12, no. 4, pp. 953. https://doi.org/10.3390/plants12040953 PMid:36840301.
  » https://doi.org/10.3390/plants12040953
• NYAUPANE, S., POUDEL, M.R., PANTHI, B., DHAKAL, A., PAUDEL, H. and BHANDARI, R., 2024. Drought stress effect, tolerance, and management in wheat – a review. Cogent Food & Agriculture, vol. 10, no. 1, pp. 2296094. https://doi.org/10.1080/23311932.2023.2296094
  » https://doi.org/10.1080/23311932.2023.2296094
• OHYAMA, T., ITO, M., KOBAYASHI, K., ARAKI, S., YASUYOSHI, S., SASAKI, O., YAMAZAKI, T., SOYAMA, K., TANEMURA, R., MIZUNO, Y. and IKARASHI, T., 1991. Analytical procedures of N, P, K contents in plant and manure materials using H₂SO₄-H₂O₂Kjeldahl digestion method. Niigata Daigaku Nogakubu Kenkyu Hokoku, vol. 43, pp. 110-120.
• OMAR, A.A., HEIKAL, Y.M., ZAYED, E.M., SHAMSELDIN, S.A.M., SALAMA, Y.E., AMER, K.E., BASUONI, M.M., ABD ELLATIF, S. and MOHAMED, A.H., 2023. Conferring of drought and heat stress tolerance in wheat (Triticum aestivumL.) genotypes and their response to selenium nanoparticles application. Nanomaterials (Basel, Switzerland), vol. 13, no. 6, pp. 998. https://doi.org/10.3390/nano13060998 PMid:36985894.
  » https://doi.org/10.3390/nano13060998
• PADILLA, Y.G., GISBERT-MULLOR, R., LOPEZ-GALARZA, S., ALBACETE, A., MARTINEZ-MELGAREJO, P.A. and CALATAYUD, A., 2023. Short-term water stress responses of grafted pepper plants are associated with changes in the hormonal balance. Frontiers in Plant Science, vol. 14, pp. 1170021. https://doi.org/10.3389/fpls.2023.1170021 PMid:37180400.
  » https://doi.org/10.3389/fpls.2023.1170021
• POUDEL, P.B., POUDEL, M.R. and PURI, R.R., 2021. Evaluation of heat stress tolerance in spring wheat (Triticum aestivumL.) genotypes using stress tolerance indices in western region of Nepal. Journal of Agriculture and Food Research, vol. 5, pp. 100179. https://doi.org/10.1016/j.jafr.2021.100179
  » https://doi.org/10.1016/j.jafr.2021.100179
• RAMADAN, A.A., EL-KARAMANY, M.F., ABDALLAH, M.M.S., BAKRY, A.B. and EL BASSIOUNY, H.M.S., 2025. Enhancing faba bean (Vicia faba) productivity under drought stress through modulation of physiological traits and antioxidant enzyme system using thiourea and hydrogel. BMC Plant Biology, vol. 25, no. 1, pp. 873. https://doi.org/10.1186/s12870-025-06904-0 PMid:40615955.
  » https://doi.org/10.1186/s12870-025-06904-0
• RAZA, M.A.S., MUHAMMAD, F., FAROOQ, M., ASLAM, M.U., AKHTER, N., TOLEIKIENĖ, M., BINOBEAD, M.A., ALI, M.A., RIZWAN, M. and IQBAL, R., 2025. ZnO-nanoparticles and stage-based drought tolerance in wheat (Triticum aestivumL.): effect on morpho-physiology, nutrients uptake, grain yield and quality. Scientific Reports, vol. 15, no. 1, pp. 5309. https://doi.org/10.1038/s41598-025-89718-2 PMid:39939384.
  » https://doi.org/10.1038/s41598-025-89718-2
• REHMAN, M., BAKHSH, A., ZUBAIR, M., REHMANI, M.I.A., SHAHZAD, A., NAYAB, S., KHAN, M., ANUM, W., AKHTAR, R., KANWAL, N., MANZOOR, N. and ALI, I., 2021. Effects of water stress on cotton (Gossypiumspp.) plants and productivity. Egyptian Journal of Agronomy, vol. 43, no. 3, pp. 307-315. https://doi.org/10.21608/agro.2021.89343.1272
  » https://doi.org/10.21608/agro.2021.89343.1272
• REKOWSKI, A., WIMMER, M.A., TAHMASEBI, S., DIER, M., KALMBACH, S., HITZMANN, B. and ZORB, C., 2021. Drought stress during anthesis alters grain protein composition and improves bread quality in field-grown iranian and german wheat genotypes. Applied Sciences (Basel, Switzerland), vol. 11, no. 21, pp. 9782. https://doi.org/10.3390/app11219782
  » https://doi.org/10.3390/app11219782
• SAAD, A.M., ELHABBAK, A.K., ABBAS, M.H.H., MOHAMED, I., ABDELRAHMAN, M.A.E., SCOPA, A. and BASSOUNY, M.A., 2023. Can deficit irrigation be an optimum solution for increasing water productivity under arid conditions? A case study on wheat plants. Saudi Journal of Biological Sciences, vol. 30, no. 2, pp. 103537. https://doi.org/10.1016/j.sjbs.2022.103537 PMid:36590750.
  » https://doi.org/10.1016/j.sjbs.2022.103537
• SABENCA, C., RIBEIRO, M., SOUSA, T., POETA, P., BAGULHO, A.S. and IGREJAS, G., 2021. Wheat/gluten-related disorders and gluten-free diet misconceptions: A Review. Foods, vol. 10, no. 8, pp. 1765. https://doi.org/10.3390/foods10081765 PMid:34441542.
  » https://doi.org/10.3390/foods10081765
• SAHA, D., CHOYAL, P., MISHRA, U.N., DEY, P., BOSE, B., MD, P., GUPTA, N.K.K., METHA, P.K., KUMAR, P., PANDEY, S., CHAUHAN, J. and SINGHAL, R.K., 2022. Drought stress responses and inducing tolerance by seed priming approach in plants. Plant Stress, vol. 4, pp. 100066-100079. https://doi.org/10.1016/j.stress.2022.100066
  » https://doi.org/10.1016/j.stress.2022.100066
• SALGOTRA, R.K. and CHAUHAN, B.S., 2023. Ecophysiological responses of rice (Oryza sativaL.) to drought and high temperature. Agronomy (Basel), vol. 13, no. 7, pp. 1877. https://doi.org/10.3390/agronomy13071877
  » https://doi.org/10.3390/agronomy13071877
• SALLAM, A.R., MAHDI, A.A. and FARROH, K.Y., 2022. Improving drought stress tolerance in potato Solanum tuberosum L. using magnetite and zinc oxide nanoparticles. Plant Cell Biotechnology and Molecular Biology, vol. 23, no. 37-38, pp. 1-16. https://doi.org/10.56557/pcbmb/2022/v23i37-387886
  » https://doi.org/10.56557/pcbmb/2022/v23i37-387886
• SELEIMAN, M.F., AL-SUHAIBANI, N., ALI, N., AKMAL, M., ALOTAIBI, M., REFAY, Y., DINDAROGLU, T., ABDUL-WAJID, H.H. and BATTAGLIA, M.L., 2021. Drought stress impacts on plants and different approaches to alleviate its adverse effects. Plants, vol. 10, no. 2, pp. 259. https://doi.org/10.3390/plants10020259 PMid:33525688.
  » https://doi.org/10.3390/plants10020259
• SHAHID, M.A., CHAUHDARY, J.N., USMAN, M., QAMAR, M.U. and SHABBIR, A., 2022. Assessment of water productivity enhancement and sustainability potential of different resource conservation technologies: a review in the context of Pakistan. Agriculture, vol. 12, no. 7, pp. 1058. https://doi.org/10.3390/agriculture12071058
  » https://doi.org/10.3390/agriculture12071058
• SHARMA, D., SHREE, B., KUMAR, S., KUMAR, V., SHARMA, S. and SHARMA, S., 2022. Stress induced production of plant secondary metabolites in vegetables: functional approach for designing next generation super foods. Plant Physiology and Biochemistry: PPB, vol. 192, pp. 252-272. https://doi.org/10.1016/j.plaphy.2022.09.034 PMid:36279745.
  » https://doi.org/10.1016/j.plaphy.2022.09.034
• SHENG, M., XIA, H., DING, H., PAN, D., HE, J., LI, Z. and LIU, J., 2023. Long-term soil drought limits starch accumulation by altering sucrose transport and starch synthesis in sweet potato tuberous root. International Journal of Molecular Sciences, vol. 24, no. 3, pp. 3053. https://doi.org/10.3390/ijms24033053 PMid:36769375.
  » https://doi.org/10.3390/ijms24033053
• SPANIC, V., DUVNJAK, J., HEFER, D. and D’AURIA, J.C., 2025. Changes in metabolites produced in wheat plants against water-deficit stress. Plants, vol. 14, no. 1, pp. 10. https://doi.org/10.3390/plants14010010 PMid:39795270.
  » https://doi.org/10.3390/plants14010010
• SUN, J.X., YIN, Y.L., SUN, S.K., WANG, Y.B., YU, X. and YANK, K., 2021. Review on research status of virtual water: the perspective of accounting methods, impact assessment and limitations. Agricultural Water Management, vol. 243, pp. 106407. https://doi.org/10.1016/j.agwat.2020.106407
  » https://doi.org/10.1016/j.agwat.2020.106407
• TAMAYO, P.R. and BONJOCH, N.P., 2001. Free proline quantification. In: M.J. REIGOSA, eds. Handbook of plant ecophysiology techniques Dordrecht, The Netherlands: Kluwer Academic Publishers, pp. 365-382. https://doi.org/10.1007/0-306-48057-3_22
  » https://doi.org/10.1007/0-306-48057-3_22
• TATAR, O., CAKALOGULLARI, U., AYKUT TONK, F., ISTIPLILER, D. and KARAKOC, R., 2020. Effect of drought stress on yield and quality traits of common wheat during grain filling stage. Turkish Journal of Field Crops, vol. 25, no. 2, pp. 236-244. https://doi.org/10.17557/tjfc.834392
  » https://doi.org/10.17557/tjfc.834392
• TURAN, M., EKINCL, M., ARGIN, S., BRINZA, M. and YILDRIM, E., 2023. Drought stress amelioration in tomato (Solanum lycopersicumL.) seedlings by biostimulant as regenerative agent. Frontiers in Plant Science, vol. 14, pp. 1211210. https://doi.org/10.3389/fpls.2023.1211210 PMid:37662171.
  » https://doi.org/10.3389/fpls.2023.1211210
• UR RAHMAN, S., QIN, A., ZAIN, M., MUSHTAQ, Z., MEHMOOD, F., RIAZ, L., NAVEED, S., ANSARI, M.J., SAEED, M., AHMAD, I. and SHEHZAD, M., 2024. Pb uptake, ac cumulation, and translocation in plants: plant physiological, biochemical, and molecular response: a review. Heliyon, vol. 10, no. 6, pp. e27724. https://doi.org/10.1016/j.heliyon.2024.e27724 PMid:38500979.
  » https://doi.org/10.1016/j.heliyon.2024.e27724
• VERSLUES, P.E., 2010. Quantification of water stress-induced osmotic adjustment and proline accumulation for arabidopsis thaliana molecular genetic studies. In: R. SUNKAR, ed. Plant stress tolerance Nova Jersey: Humana Press, pp. 301-315.. https://doi.org/10.1007/978-1-60761-702-0_19
  » https://doi.org/10.1007/978-1-60761-702-0_19
• WEERARATHNE, L.V.Y., JAHUFER, Z., SCHAUFELE, R., LOPEZ, I. and MATTEW, C., 2023. A comparative analysis of agronomic water-use efficiency and its proxy measures as derived from key morpho-physiological and supportive quantitative genetics attributes of perennial rye grass under imposed drought. Plant-Environment Interactions, vol. 4, no. 5, pp. 291-307. https://doi.org/10.1002/pei3.10123 PMid:37829998.
  » https://doi.org/10.1002/pei3.10123
• YANG, Y., LIU, X., ZHAO, Y., TANG, G., NAN, R., ZHANG, Y., SUN, F., XI, Y. and ZHANG, C., 2024. Evaluation of wheat drought resistance using hyperspectral and chlorophyll fluorescence imaging. Plant Physiology and Biochemistry : PPB, vol. 219, pp. 109415. https://doi.org/10.1016/j.plaphy.2024.109415 PMid:39729967.
  » https://doi.org/10.1016/j.plaphy.2024.109415

Edited by

• Editor:
  Takako Matsumura Tundisi

Publication Dates

• Publication in this collection
  31 Aug 2026
• Date of issue
  2026

History

• Received
  23 Dec 2025
• Accepted
  26 June 2026