Evaluation of Fourteen Bread Wheat (Triticum aestivum L.) Genotypes by Observing Gas Exchange Parameters, Relative Water and Chlorophyll Content, and Yield Attributes under Drought Stress

Abstract

Water scarceness is a major threat to wheat productivity under changing climate scenarios, especially in arid and semi-arid regions. However, growing drought-tolerant wheat genotypes could be a sustainable option to enhance wheat productivity under drought stress conditions. The aim of this study was to evaluate the effect of mild to severe drought stress on gas exchange parameters, relative water content, SPAD-chlorophyll value, and yield-related parameters of 14 wheat genotypes being cultivated in arid to semi-arid areas on large scale. The genotypes were grown in earthen pots under three drought levels, namely (1) control-well watered, (2) mild water stress, i.e., 60% water holding capacity, and (3) severe water stress, i.e., 40% water holding capacity. The drought was imposed from the jointing stage to physiological maturity. Drought significantly decreased net photosynthesis, stomatal conductance, relative water contents, 100-grain weight, and grain yield in all genotypes. However, the reduction percentage was different in different genotypes under drought stress compared with well-watered conditions. The highest relative water content (65.2%) was maintained by the genotype Galaxy-2013, followed by AAS-2011 (64.6%) and Johar-2016 (62.3%) under severe drought conditions. Likewise, Galaxy-2013 showed the highest net photosynthesis and stomatal conductance under severe drought conditions. The highest grain yield per plant (6.2 g) and 100-grain weight (3.3 g) was also recorded in Galaxy-2013 under severe drought conditions, while the highest grain yield under well-watered conditions was recorded in Johar-2016, followed by Galaxy-2013. These results suggest that wheat variety Galaxy-2013 could be cultivated extensively to obtain good wheat yield under limited water conditions.

1. Introduction

Drought stress is a major limiting factor for crop production systems worldwide, especially under arid and semi-arid areas [1]. Arid and semi-arid regions in Asia have faced acute water shortages for the last few decades, becoming a challenging task for agriculture and water management experts [2]. Now, drought is considered the most important factor affecting crop yield. More devastatingly, the predicted climate change may enhance the frequency of drought, which may increase crop production losses [3].

Our food source mainly depends on cereals. Their production is significantly affected by drought stress [4]. In changing climate scenarios, wheat production decreases because of acute water deficiency in wheat-producing areas [5]. Drought affects the wheat yield throughout the growing season to some extent, but more yield losses occur during reproductive and grain-filling phases [6]. The yield losses of wheat during the reproductive phase due to drought might be due to its deleterious effects on morphological and physiological traits. Drought stress adversely affects root depth [7], may accelerate leaf senescence [8], oxidative damage to photosynthetic machinery [9], and decrease carbon dioxide fixation [10]. It may also affect the assimilate translocation rate [10], resulting in a reduced grain set [11]. Reduced chlorophyll causes chlorosis, leads to a reduction in photosynthesis [12]. Drought adversely affects carbon fixation due to leaf stomata’s closure, reducing the production of photo-assimilates [13]. Decreased stomatal conductance is the main cause of the reduction in photosynthesis during drought conditions [14]. However, at later stages, drought leads to tissue dehydration which may cause metabolic injury [8]. It also reduces leaf relative water content (RWC) and stomatal conductance, which ultimately leads to reducing growth and biomass production [15,16].

In addition to physiological and morphological traits, drought also affects traits that confer drought resistance in the specific environment may be very distinct. Drought causes grain loss because of pollen sterility and abscisic acid accumulation in spikes of drought susceptible wheat genotypes [17]. Last but not least, drought stress could significantly affect wheat kernels milling [18], flour quality [19], dough kneading [20,21], and the entire breadmaking process [6]. Being a major cereal crop in Pakistan, the wheat yield must be improved to fulfill the growing population’s increasing food demands [22]. For this reason, the selection and use of drought-stress resistant cultivars able to guarantee suitable yields and flour quality, is essential [23]. The response of plants to drought stress depends on different factors, such as growth stages, length and severity of stress, and a cultivar’s genetic makeup [24].

Drought stress can occur at any growth stage depending upon the local environmental conditions [3]. Thal region in Punjab Pakistan is an important region regarding wheat cultivation, and this region is also facing drought problems. This region experienced severe drought during 2000–2002 during the rabi season and affected 28% of the area [25]. Thal region comes under arid as well as irrigated area which receives about 234 mm annual rainfall [26]. To tackle drought in this region, adopting drought-tolerant genotypes is one of the most sustainable ways to reduce the impacts of different intensities of dry spells on wheat production [23]. A lot of work has been done to maximize wheat production by adopting different drought mitigating practices. However, no information is available regarding suitable varieties grown in drought-prone arid areas of Punjab province to obtain better genetic potential. To facilitate farmers of arid regions (Thal zone), the present study was conducted to evaluate the effect of drought stress on the tested wheat genotypes to find high-yielding wheat genotypes under limited water conditions in the Thal region of Punjab, Pakistan.

2. Materials and Methods

2.1. Experimental Site and Soil Characteristics

This study was conducted in a green-house at the College of Agriculture, Bahauddin Zakariya University, Layyah, Pakistan. For the experiment, a mixture of soil and farmyard manure (FYM) (3:1 (w/w)) was used. The soil was sandy loam having pH 8.1, electrical conductivity (EC) 2.28 dSm⁻¹, organic matter content 0.49%, available P 7 ppm, and available K 92 ppm.

2.2. Experimental Design and Treatments

Seeds of 14 wheat genotypes, consisted of new and old locally cultivated varieties, was obtained from Ayub Agricultural Research Institute (AARI) Faisalabad, and Arid Zone Research Institute (AZRI) Bhakkar, Punjab, Pakistan. The tested wheat genotypes were: Ujala-2016, Gold-2016, Johar-2016, Galaxy-2013, Ehsan-2016, Fath-e-Jang, Saher-2006, Gandum-1, Panjab-2011, AAS-2011, AS-2002, Faisalabad-2008, Lasani-2008, and Shafaq-2006. Moreover, three drought treatments of Galaxy-2013, i.e., (1) well-watered (control), (2) mild drought stress (60% water holding capacity (WHC)), and (3) severe drought stress (40% WHC), were tested. Pots were arranged in a factorial, completely randomized design (CRD) with three replications. The complete set of genotypes is presented in

Table 1. List of genotypes with their planting region, origin and year of release used in this study.

Sr. No.	Genotype	Planting Region	Origin	Year of Release
01	Ujala-2016	Irrigated areas of Punjab	AARI-Faisalabad	2016
02	Gold-2016	Irrigated areas of Punjab	RARI Bahawalpur	2016
03	Johar-2016	Irrigated areas of Punjab	RARI Bahawalpur	2016
04	Galaxy-2013	Irrigated areas of Punjab	AARI-Faisalabad	2013
05	Ehsan-2016	Rainfed areas of Punjab	BARI-Chakwal	2016
06	Fath-e-Jang-16	Rainfed areas of Punjab	BARI-Chakwal	2016
07	Saher-2006	Irrigated areas of Punjab	AARI-Faisalabad	2006
08	Gandum-1	All over Punjab	NIBGE-Faisalabad	2016
09	Panjab-2011	Irrigated areas of Punjab	AARI-Faisalabad	2011
10	AAS-2011	Irrigated areas of Punjab	RARI Bahawalpur	2011
11	AS-2002	Irrigated areas of Punjab	AARI-Faisalabad	2002
12	Faisalabad-2008	Irrigated areas of Punjab	AARI-Faisalabad	2008
13	Lasani-2008	Irrigated areas of Punjab	AARI-Faisalabad	2008
14	Shafaq-2006	Irrigated areas of Punjab	AARI-Faisalabad	2006

.

2.3. Plants Growing

The earthen pots (12 cm in diameter and 60 cm in height) were filled with 10 kg of sieved soil and FYM at a ratio of 3:1, respectively. Ten seeds per pot were sown uniformly at a depth of 2 cm. After germination of seeds, five seedlings per pot were maintained till maturity. Fertilizer application was done following the recommended dose, i.e., nitrogen (N) at 0.25 g as urea, phosphorus (P) at 0.4 g as di-ammonium phosphate, and potassium (K) at 0.35 g pot⁻¹ as potassium sulphate was applied as basal dose, while the remaining half dose of N as urea at 0.25 g pot⁻¹ was applied at jointing stage. Drought was imposed from the jointing stage and maintained till crop maturity.

2.4. Maintenance of Water Holding Capacity

For measuring soil WHC/field capacity (FC), the gravimetric method was followed as described by [27]. Before sowing the seed, three soil samples were collected from each pot and measured for their fresh weight. After that, the samples were oven-dried at 105 °C till constant weight. After drying, three representative samples were taken and saturated with distilled water to make a saturated paste. FC was determined by the following formula, as proposed by [27]:

$$FC=\frac{saturation \% age of soil samples taken}{2}$$

(1)

Through this formula, 100%, 60%, and 40% WHC were calculated, which was maintained throughout the experiment by weighing the pots. The difference in weight was corrected by applying the required amount of water according to the calculation.

2.5. Measurement of Relative Water Content (RWC) and SPAD-Chlorophyll Value

To measure RWC, fully expanded younger leaves from each treatment were collected. The leaf surface was gently dried using tissue paper, then wrapped in polythene bags and brought to the laboratory. Leaf samples were weighed to obtain leaf fresh weight (FW). The samples were then soaked in plastic tubes containing distilled water and left overnight in the dark. The next morning, these leaves were carefully bloated with tissue paper and weighed to determine the turgid weight (TW). Leaves were then dried at 70 °C till constant weight using a hot air oven. Dried leaves were then weighed to record dry weight (DW). RWC was calculated by following the formula as described by [28].

RWC (%) = (FW − DW)/(TW − DW) × 100

(2)

The SPAD-Chlorophyll value was estimated by using a portable SPAD-502 Chlorophyll Meter (Minolta Co., Ltd., Osaka, Japan). For this purpose, randomly selected 10 plants from each treatment were used to measure the chlorophyll content. The reading was taken from the flag leaf at the anthesis stage from three different points (bottom, middle, and tip of the leaf) and then averaged to get the final SPAD-Chlorophyll value.

2.6. Gas Exchange Characteristics

Gas exchange characteristics, including stomatal conductance (g), net photosynthesis (Pn), and transpiration rate (E), were recorded from fully expanded flag leaf for each treatment at the anthesis stage by using an infra-red gas analyzer (IRGA) Leaf Chamber Analyzer (Type LCA-4, USA). The measurements were made from 10:00 a.m. to 11:59 a.m. on a sunny day under a CO₂ concentration of 400 μmol mol⁻¹ [29].

2.7. Yield and Related Traits

Five representative plants were randomly selected from each pot, and fertile tillers were counted manually, then averaged to find tillers per plant. At maturity, the plant height from five plants was measured from stem base to the ear’s tip using a meter scale and then averaged. Similarly, five spikes were randomly selected from each pot, and their length was measured with the help of a ruler and worked out their average. The same spikes were used to calculate the number of spikelets in each spike, and their mean was worked out. These five plants were harvested manually from each pot, sun-dried for six days. After drying, the weight of whole plants was measured on electrical balance and averaged to get biological yield per plant. After measuring biological yield, five spikes from each pot were threshed manually, and grains were cleaned, weighed, and averaged to obtain the grain yield per plant. Similarly, from the same threshed grains, 100 grains were counted manually from each pot and weighed to measure 100-grain weight.

2.8. Statistical Analysis

Data collected on all parameters were analyzed using Statistix software (Version 8.1. USA). Tukey’s HSD test at 5% probability level for 2-way ANOVA was applied to compare the treatment means [30]. Further data were processed in Microsoft Excel-2010 to get values of standard error (±S.E.) as well as bar graphs for a graphical representation of data.

3. Results

3.1. Growth Parameters

3.1.1. Relative Water Content and SPAD-Chlorophyll Value

Data indicated that the RWC was higher under well-watered conditions in all genotypes while reduced under both mild and severe drought conditions in all genotypes (

Table 2. Effect of different drought levels on relative water contents (%) and SPAD-chlorophyll of wheat genotypes.

Genotypes (G)	Relative Water Contents (%)				SPAD-Chlorophyll Value
	WW	MD	SD	Means (G)	WW	MD	SD	Means
Ujala-2016	77.0 b–d	66.3 e–k	53.3 o–p	65.5 EF	53.1	52.0	50.6	51.9 DE
Gold-2016	73.1 c–e	62.6 h–n	56.2 n–p	64.0 F	55.6	54.0	52.7	54.1 A–C
Johar-2016	85.7 a	71.2 d–g	62.3 i–n	73.1 A	56.3	52.4	50.8	53.2 CD
Galaxy-2013	73.1 c–e	67.1 e–j	65.2 f–l	68.5 A–D	59.4	53.3	54.1	55.6 A
Ehsan-2013	82.0 ab	69.7 d–h	58.3 l–p	70.0 A–C	54.5	53.7	51.8	53.3 CD
Fath-e-Jang	81.5 ab	72.0 d–f	57.5 m–p	70.3 A–C	54.4	52.9	52.2	53.2 CD
Saher-2006	72.5 c–f	68.4 e–i	60.1 j–o	66.9 B–D	52.8	50.0	49.4	50.7 E
Gandum-1	80.7 ab	70.7 b–g	58.2 l–p	69.9 A–C	55.0	53.6	51.4	53.3 CD
Punjab-2011	82.7 ab	68.4 e–i	61.0 j–n	70.7 A–C	55.7	53.9	53.3	54.3 AC
AAS-2011	81.5 ab	72.4 c–f	64.6 g–m	72.9 A	54.5	52.8	52.0	53.1 CD
AS-2002	79.5 a–c	61.9 i–n	55.4 n–p	65.6 C–D	56.0	53.7	51.8	53.8 BC
FSD-2008	85.0 a	71.3 d–g	61.9 i–n	72.7 A	55.2	53.8	53.8	54.3 A–C
Lasani-2008	85.1 a	70.5 d–g	52.3 p	69.3 A–D	56.1	55.0	53.0	54.7 A–C
Shafaq-2006	84.8 a	70.1 d–g	59.2 k–p	71.4 AB	56.0	55.5	54.1	55.2 AB
Means drought (D)	80.3 A	68.8 B	59.0 C		55.3 A	53.3 B	52.2 C
LSD (p ≤ 0.01) for drought (D)			1.96		0.77
LSD for G	4.24				1.66
LSD (D × G)	7.35				NS

D = drought; G = genotype; WW = well–watered; MD = mild drought; SD = severe drought. Means not sharing the same letters differ significantly at p ≤ 0.01, NS = Non-significant.

). It was observed that the genotype Johar-2016 maintained the highest RWC under well-watered and mild drought conditions, while the genotype Galaxy-2013 maintained the highest RWC under severe drought conditions (Table 2). In contrast, the genotype Lasani-2008 was observed with the lower RWC under severe drought stress conditions (Table 2). Similarly, various drought levels significantly affected the SPAD-chlorophyll value of wheat genotypes. Higher SPAD-chlorophyll value was observed under well-watered conditions while it was significantly reduced under drought conditions. Various wheat varieties also exhibited differences in chlorophyll content, and the maximum SPAD-Chlorophyll content was recorded in Galaxy-2013, while the minimum chlorophyll content was recorded in Saher-2006. However, the interaction effect of wheat genotypes with different drought levels was found to be non-significant (Table 2).

3.1.2. Gas Exchange Parameters

The gas exchange parameters such as net photosynthesis (Pn), stomatal conductance (gs), and transpiration rate (E) were reduced under both drought stress conditions compared with control (well-watered). Decreases of 30% and 70% for Pn, of 45% and 81% for gs, and of 45% and 80% for E were observed under mild drought and severe drought conditions, respectively (Figure 1, Figure 2 and Figure 3). The highest Pn, gs, and E were observed in the genotype Galaxy-2013 followed by Johar-2016 under severe drought conditions (Figure 1, Figure 2 and Figure 3). These parameters decreased in all cultivars, but in drought-resistant one, they decreased to a lesser extent.

3.2. Yield and Yield-Related Traits

Various drought treatments, wheat varieties, and their interaction significantly affected the yield and yield-related traits such as plant height, spike weight, grains per spike, 100-grain weight, and grain yield (

Table 3. Effect of different drought levels on plant height and fertile tillers per plant of wheat genotypes.

Genotypes (G)	Plant Height (cm)				Fertile Tillers Plant−1
	WW	MD	SD	Means (G)	WW	MD	SD	Means
Ujala-2016	65.5 c–k	64.0 c–k	60.9 g–l	63.5 DE	4.42 d–i	4.00 g–m	3.50 lm	3.97 D
Gold-2016	65.8 b–k	61.0 g–l	60.8 g–l	62.5 DF	5.33 ab	5.25 a–c	3.58 k–m	4.72 AB
Johar-2016	80.6 a	58.7 i–m	56.9 k–m	65.4 CE	5.42 a	4.17 f–l	3.83 i–m	4.47 A–C
Galaxy-2013	80.6 a	72.5 a–f	66.3 b–k	73.1 A	5.42 a	4.67 b–g	4.50 d–i	4.86 A
Ehsan-2013	62.2 f–k	59.8 i–m	58.1 i–m	60.0 EF	4.92 a–e	4.42 d–i	3.50 lm	4.28 CD
Fath-e-Jang	63.5 d–k	62.0 f–k	61.7 g–k	62.4 D–F	4.33 e–j	4.17 f–l	3.50 lm	4.00 D
Saher-2006	60.6 h–l	58.7 i–m	50.3 lm	56.5 F	4.25 e–k	4.08 g–m	4.08 g–m	4.14 CD
Gandum-1	64.2 c–k	57.4 j–m	60.8 g–l	60.8 D–F	4.83 a–f	4.17 f–l	3.67 j–m	4.22 CD
Punjab-2011	73.2 a–e	63.9 d–k	61.0 g–k	66.0 B–E	5.08 a–d	4.25 e–k	3.83 i–m	4.39 B–D
AAS-2011	74.6 a–c	62.7 e–k	59.2 i–m	65.5 C–E	4.67 b–g	4.08 g–m	3.67 j–m	4.14 CD
AS-2002	70.8 a–h	68.1 b–i	49.8 m	62.9 DE	4.58 c–h	4.17 f–l	3.42 m	4.06 CD
FSD-2008	70.5 a–h	65.1 c–k	63.2 d–k	66.3 BD	5.08 a–d	3.92 h–m	4.08 g–m	4.36 B–D
Lasani-2008	73.4 a–d	68.4 b–i	67.9 b–j	69.9 A–C	4.83 a–f	4.25 e–k	3.83 i–m	4.31 B–D
Shafaq-2006	76.4 ab	71.4 a–g	68.6 b–i	72.1 AB	4.58 c–h	4.00 g–m	3.50 lm	4.03 D
Means drought (D)	70.1 A	63.8 B	60.4 C		4.84 A	4.26 B	3.75 C
LSD (p ≤ 0.01) for drought (D)			2.85		0.20
LSD for G	6.17				0.43
LSD (D × G)	10.68				0.74

D = drought; G = genotype; WW = well–watered; MD = mild drought; SD = severe drought. Means not sharing the same letters differ significantly at p ≤ 0.01.

,

Table 4. Effect of different drought levels on spike length and spikelets per spike of wheat genotypes.

Genotypes (G)	Spike Length (cm)				Spikelet Per Spike
	WW	MD	SD	Means (G)	WW	MD	SD	Means
Ujala-2016	10.3 ns	9.6	8.0	9.3 B–D	18.0 b–e	16.7 d–g	15.7 g	16.8 E
Gold-2016	10.1	9.0	8.9	9.4 B–D	18.0 b–e	17.0 c–g	16.0 f–g	17.0 DE
Johar-2016	12.1	8.7	8.5	9.8 A–C	23.0 a	18.3 b–d	17.3 b–g	19.6 A
Galaxy-2013	10.8	10.3	9.7	10.3 AB	19.0 a	18.7 b–c	17.7 b–f	18.4 BC
Ehsan-2013	9.7	8.7	8.4	8.9 CD	18.7 bc	17.7 b–f	16.7 d–g	17.7 E
Fath-e-Jang	9.6	8.3	7.8	8.6 D	17.7 b–f	17.7 b–f	17.7 b–f	17.7 E
Saher-2006	10.4	8.9	7.8	9.0 CD	17.7 b–f	17.7 b–f	17.7 b–f	17.7 E
Gandum-1	11.5	9.3	8.4	9.7 A–C	18.7 bc	17.7 d–f	16.7 d–g	17.7 E
Punjab-2011	11.1	10.0	9.7	10.3 AB	19.0 b	18.0 b–e	16.7 d–g	17.9 B–D
AAS-2011	10.8	9.5	9.3	9.9 A–C	19.0 b	17.7 b–f	16.7 d–g	17.8 B–D
AS-2002	12.0	10.0	9.5	10.5 A	18.7 bc	17.3 b–g	16.3 e–g	17.4 DE
FSD-2008	10.1	9.3	9.2	9.6 A–D	18.0 b–e	17.3 b–g	16.0 f–g	17.1 DE
Lasani-2008	11.0	10.1	9.7	10.2 AB	18.0 b–e	17.0 c–g	16.3 e–g	17.1 DE
Shafaq-2006	10.3	8.7	8.0	9.0 CD	22.7 a	17.0 c–g	16.3 e–g	18.7 AB
Means drought (D)	10.7 A	9.3 B	8.8 C		19.0 A	17.5 B	16.7 C
LSD (p ≤ 0.01) for drought (D)			0.47		0.45
LSD for G	1.02				0.98
LSD (D × G)	NS				1.70

D = drought; G = genotype; WW = well–watered; MD = mild drought; SD = severe drought. Means not sharing the same letters differ significantly at p ≤ 0.01.

,

Table 5. Effect of different drought levels on spike weight and grains spike⁻¹ of wheat genotypes.

Genotypes (G)	Spike Weight (g)				Grains Per Spike
	WW	MD	SD	Means (G)	WW	MD	SD	Means
Ujala-2016	1.54 c–f	1.33 m–o	1.31 n–q	1.39 B–D	34.3 e	26.3 f–k	24.3 i–k	28.3 E
Gold-2016	1.58 c	1.26 p–s	1.25 q–s	1.36 C–E	36.0 de	27.3 f–j	25.3 g–k	29.6 C–E
Johar-2016	1.80 a	1.31 n–p	1.30 m–q	1.47 A	42.0 a	27.7 f–i	25.3 g–k	31.7 A–C
Galaxy-2013	1.69 b	1.41 i–l	1.38 lm	1.49 A	39.0 a–d	29.7 f	27.7 f–i	32.1 A
Ehsan-2013	1.55 c–e	1.40 i–l	1.31 n–q	1.42 B	40.7 a–d	28.7 fg	25.7 g–k	31.7 A–C
Fath-e-Jang	1.57 cd	1.33 m–o	1.30 o–q	1.40 BC	39.7 a–c	28.7 fg	25.0 h–k	31.1 A–D
Saher-2006	1.45 h–j	1.36 l–n	1.33 m–o	1.38 B–D	34.0 e	28.0 f–h	25.3 g–k	29.1 DE
Gandum-1	1.50 e–h	1.38 k–n	1.31 n–q	1.40 B–D	41.7 a	27.7 f–i	26.0 g–k	31.8 AB
Punjab-2011	1.46 g–i	1.33 m–o	1.29 o–r	1.36 DE	41.0 ab	28.7 fg	26.7 f–k	32.1 AB
AAS-2011	1.46 g–i	1.25 p–s	1.22 s	1.31 F	40.0 ab	28.0 f–h	23.3 k	30.4 A–E
AS-2002	1.45 h–k	1.35 l–o	1.29 o–r	1.36 C–E	40.7 ab	28.0 f–h	25.0 h–k	31.2 A–D
FSD-2008	1.46 g–i	1.31 n–q	1.23 rs	1.33 EF	39.3 a–d	26.0 g–k	25.3 g–k	30.2 A–E
Lasani-2008	1.48 f–h	1.39 j–m	1.23 s	1.36 C–E	38.0 b–d	26.0 g–k	25.3 g–k	29.8 B–E
Shafaq-2006	1.52 d–g	1.33 m–o	1.30 o–q	1.38 CD	36.3 c–e	26.3 f–k	24.0 j–k	28.9 E
Means drought (D)	1.54 A	1.34 B	1.29 C		38.8 A	27.6 B	25.3 C
LSD (p ≤ 0.01) for drought (D)			0.017		0.97
LSD for G	0.038				2.11
LSD (D × G)	0.065				3.66

D = drought; G = genotype; WW = well–watered; MD = mild drought; SD = severe drought. Means not sharing the same letters differ significantly at p ≤ 0.01

and

Table 6. Effect of different drought levels on 100-grain weight and grain yield per plant of wheat genotypes.

Genotypes (G)	100-Grain Weight (g)				Grain Yield (g Plant−1)
	WW	MD	SD	Means (G)	WW	MD	SD	Means
Ujala-2016	3.4 f–i	3.0 j–o	3.0 j–o	3.13 C–E	6.8 d–g	5.3 i–o	4.6 l–o	5.5 D
Gold-2016	3.4 e–i	3.4 g–i	3.1 i–n	3.29 BC	8.5 bc	6.6 d–h	4.5 no	6.5 A–C
Johar-2016	4.1 a	3.7 b–e	3.2 h–l	3.67 A	9.8 a	5.5 i–o	5.0 j–o	6.7 AB
Galaxy-2013	4.1 a	3.4 d–h	3.3 h–j	3.60 A	9.2 ab	6.6 d–h	6.2 e–i	7.3 A
Ehsan-2013	3.8 bc	3.2 h–k	2.8 n–q	3.28 BC	7.6 cd	6.2 e–i	4.6 l–o	6.1 B–D
Fath-e-Jang	3.6 c–g	3.2 h–l	2.8 n–q	3.21 B–D	6.8 d–g	5.5 h–o	4.5 m–o	5.6 D
Saher-2006	3.3 g–i	2.9 l–p	2.6 q	2.95 E	6.2 e–i	5.6 h–n	5.4 i–o	5.7 CD
Gandum-1	3.9 a–c	3.3 gi	2.8 o–q	3.33 B	7.2 de	5.8 g–k	4.8 j–o	5.9 B–D
Punjab-2011	3.9 a–c	2.9 k–o	2.9 m–q	3.23 B–D	7.4 cd	5.7 h–l	5.0 j–o	6.0 B–D
AAS-2011	3.7 b–d	3.2 h–m	2.9 n–q	3.25 BC	6.8 d–g	5.1 i–o	4.5 no	5.5 D
AS-2002	3.9 ab	3.2 h–l	2.6 pq	3.26 BC	6.6 d–h	5.6 h–m	4.4 o	5.5 D
FSD-2008	3.6 c–g	2.9 n–q	2.7 o–q	3.06 DE	7.4 cd	5.1 i–o	5.0 j–o	5.9 CD
Lasani-2008	3.6 c–g	3.3 g–i	2.8 n–q	3.25 BC	7.2 de	5.9 f–j	4.7 k–o	5.9 B–D
Shafaq-2006	3.7 b–f	3.2 h–l	3.0 j–o	3.28 BC	6.9 d–f	5.3 i–o	4.5 l–o	5.6 D
Means drought (D)	3.7 A	3.2 B	2.9 C		7.4 A	5.7 B	4.8 C
LSD (p ≤ 0.01) for drought (D)			0.08		0.3
LSD for G	0.17				0.64
LSD (D × G)	0.30				1.12

D = drought; G = genotype; WW = well–watered; MD = mild drought; SD = severe drought. Means not sharing the same letters differ significantly at p ≤ 0.01.

). The highest plant height values, spike weight, grains per spike, 100-grain weight, grain yield, and biological yield were obtained under well-watered conditions. At the same time, all these parameters were significantly reduced under mild and severe drought conditions. The maximum plant height was recorded in Johar-2016 and Galaxy-2013, followed by Shafaq-2006 under well-watered conditions. The minimum plant height was recorded in AS-2002, followed by Saher-2006 under severe drought conditions (Table 3). Furthermore, drought levels and genotypes significantly affected the number of fertile tillers per plant. Plants produced more fertile tillers under well-watered conditions and fewer fertile tillers under both drought regimes. Under severe drought conditions, Galaxy-2013 produced the maximum fertile tillers while AS-2002 produced the minimum fertile tillers per plant (Table 3).

Drought and genotypes had a significant effect on the spike length of wheat, while their interaction was found non-significant. It was observed that the length of spikes was increased under well-watered conditions, while it was reduced under drought conditions. Among genotypes, Johar-2016 produced the longest spikes, while Fath-e-Jang produced the smallest spikes (Table 4). Similarly, the maximum number of spikelets per spike was recorded in Johar-2016, followed by Shafaq-2006 under well-watered conditions. In contrast, the minimum number of spikelets per spike was recorded in Ujala-2016 under severe drought conditions (Table 4). Likewise, the spike weight and grains per spike were increased under well-watered conditions while reduced under drought conditions. The genotype Galaxy-2013 produced the heavier spike (1.38 g) with more number grains (27.7), while AAS-2011 produced the lightest spike (1.22 g) with fewer grains (23.3) under severe drought conditions (Table 5).

Furthermore, 100-grain weight of wheat was also affected significantly by various drought levels, genotypes, and their interaction. It was significantly increased under well-watered conditions than in under drought conditions. An approximately 54% reduction in 100-grain weight was recorded under severe drought conditions compared with well-watered conditions (Table 6). Among the genotypes, Johar-2016 and Galaxy-2013 were found to have the maximum 100-grain weight, while Saher-2006 with minimum 100-grain weight. The genotype Galaxy-2013 produced 21% higher 100-grain weight, while AS-2002 produced less 100-grain weight under severe drought conditions (Table 6). Grain yield was also significantly affected by drought, genotypes, and their interaction. As compared to well-watered conditions, it was reduced by 30% under mild drought and 54% under severe drought conditions. The genotype Galaxy-2013 produced the maximum grain yield per plant, while AS-2002 produced the minimum grain yield per plant. It was noted that Galaxy-2013 produced 30% more yield than the least yielded variety AS-2002 under severe drought conditions. A reduction of 41% in grain yield per plant was noted in AS-2002 under severe drought conditions (Table 6). Similarly, various drought levels and genotypes significantly affected the biological yield per plant. The maximum biological yield was recorded in Galaxy-2013, followed by Johar-2016, and the minimum biological yield was recorded in AAS-2011 (

Table 7. Effect of different drought levels on biological yield per plant of wheat genotypes.

Genotypes (G)	Biological Yield (g Plant−1)
	WW	MD	SD	Means (G)
Ujala-2016	13.9 c–j	12.4 d–m	11.8 h–m	12.7 CD
Gold-2016	17.6 ab	15.3 bc	11.5 i–m	14.8 AB
Johar-2016	18.8 a	13.1 c–m	12.2 e–m	14.7 AB
Galaxy-2013	18.0 a	14.3 c–h	14.0 c–i	15.4 A
Ehsan-2013	15.3 bc	14.8 cd	11.6 i–m	13.9 BC
Fath-e-Jang	13.4 c–m	12.8 c–m	11.3 k–m	12.5 CD
Saher-2006	13.6 c–k	12.4 d–m	12.2 e–m	12.7 CD
Gandum-1	14.4 c–g	12.9 c–m	12.0 f–m	13.1 CD
Punjab-2011	14.7 c–e	12.4 d–m	12.2 e–m	13.1 CD
AAS-2011	13.6 c–l	11.9 g–m	11.4 j–m	12.3 D
AS-2002	13.5 c–m	12.8 c–m	11.0 m	12.4 CD
FSD-2008	14.8 cd	12.7 d–m	11.5 i–m	13.0 CD
Lasani-2008	14.9 cd	14.5 c–f	12.2 e–m	13.8 BC
Shafaq-2006	13.6 c–k	11.8 h–m	11.0 lm	12.2 D
Means drought (D)	14.9 A	13.0 B	12.0 C
LSD (p ≤ 0.01) for drought (D)			51.8
LSD for G	0.68
LSD (D × G)	2.5

D = drought; G = genotype; WW = well–watered; MD = mild drought; SD = severe drought. Means not sharing the same letters differ significantly at p ≤ 0.01.

). Galaxy-2013 produced 21% more biological yield than AS-2002. However, AS-2002 was the most susceptible genotype to drought and produced 27% less biomass under severe drought conditions (Table 7).

3.3. Relationship between the Physiological, Gas Exchange, and Yield Parameters

Under well-watered conditions, significant and positive correlations (

Table 8. Correlation between the physiological, gas exchange, and yield-related traits under well-watered conditions.

	RWC	Chl	PH	FT	SL	Sk	SW	GPS	HGW	GY	B	Pn	Gs
Chl	0.645 *
PH	0.364	0.767 **
FT	0.535 *	0.710 **	0.553 *
SL	0.332	0.361	0.51	0.276
Sk	0.373	0.351	0.652 *	0.296	0.402
SW	0.619 *	0.479	0.449	0.584 *	0.183	0.529
GPS	0.236	0.378	0.312	0.416	0.476	0.244	0.208
HGW	0.557 *	0.714 **	0.645 *	0.557 *	0.614 *	0.525	0.48	0.484
GY	0.625 *	0.671 **	0.565 *	0.902 **	0.271	0.443	0.875 **	0.336	0.568 *
B	0.558 *	0.616 *	0.466	0.894 **	0.236	0.332	0.824 **	0.206	0.435	0.977 **
Pn	0.627 *	0.539 *	0.484	0.603 *	0.061	0.3	0.673 **	0.117	0.434	0.715 **	0.675 **
Gs	0.625 *	0.668 **	0.599 *	0.563 *	0.206	0.244	0.718 **	0.075	0.462	0.715 **	0.667 **	0.813 **
E	0.614 *	0.579 *	0.563 *	0.632 *	0.133	0.281	0.727 **	0.078	0.443	0.760 **	0.722 **	0.896 **	0.863 **

RWC = relative water contents; Chl = SPAD-chlrophyll; PH = Plant height; FT = Fertile tillers; SL = Spike length; Sk = Spikelet per spike; SW = Spike weight; GPS = Grains per spike; HGW = Hundred grain weight; GY = Grain yield; BY = Biological yield; Pn = Net Photosynthesis; Gs = Stomatal conductance; E = Transpiration rate. * significant; ** highly sig-nificant.

) were found between physiological traits (RWC and Chl), and these traits were also significantly correlated with gas exchange (Pn, gs, and E) and yield-related parameters (GW, GY, and BY). Similarly, Pn, gs, and E were significantly correlated each other and also with BY and GY.

Table 9. Correlation between the physiological, gas exchange, and yield-related traits under mild stress conditions.

	RWC	Chl	PH	FT	SL	Sk	SW	GPS	GW	GY	BY	Pn	Gs
Chl	0.504
PH	0.4	0.231
FT	0.347	0.0.211	0.258
SL	0.563 *	0.329	0.930 **	0.764 **
Sk	0.599 *	0.588 *	0.633 *	0.307	0.599 *
SW	0.527	0.391	0.580 *	0.472	0.525	0.706 **
GPS	0.334	0.201	0.211	0.213	0.183	0.329	0.488
GW	0.676 **	0.359	0.258	0.376	0.34	0.489	0.656 *	0.167
GY	0.692 **	0.493	0.528	0.33	0.540 *	0.845 **	0.709 **	0.589 *	0.661 **
B	0.376	0.528	0.976 **	0.865 **	0.935 **	0.542 *	0.555 *	0.21	0.279	0.493
Pn	0.875 **	0.542 *	0.466	0.258	0.527	0.794 **	0.639 *	0.591 *	0.415	0.529	0.376
Gs	0.601 *	0.540 *	0.607 *	0.376	0.664 **	0.610 *	0.743 **	0.415	0.524	0.527	0.529	0.632 *
E	0.589 *	0.132	0.403	0.201	0.529	0.512	0.670 **	0.462	0.601 *	0.403	0.436	0.669 **	0.900 **

RWC = relative water contents; Chl = SPAD-chlrophyll; PH = Plant height; FT = Fertile tillers; SL = Spike length; Sk = Spikelet per spike; SW = Spike weight; GPS = Grains per spike; HGW = Hundred grain weight; GY = Grain yield; BY = Biological yield; Pn = Net Photosynthesis; Gs = Stomatal conductance; E = Transpiration rate. * significant; ** highly sig-nificant.

shows the correlations under mild water-stressed conditions, revealing that the RWC had significantly positive correlations with Pn, Gs, and E, and yield-related parameters like GW and GY. It was noted that Chl did not have significant correlations with yield-related parameters under mild stress, although it was significantly correlated with SK, Pn, and Gs (Table 9). On the other hand, under severe water stress conditions, very strong and positive correlations were observed between the RWC and Chl. Interestingly, both parameters were equally correlated with Pn, Gs, and E. The same was observed with SW, GY, and BY. All the gas exchange parameters also significantly correlated with GY and BY (

Table 10. Correlation between the physiological, gas exchange, and yield-related traits under severe drought conditions.

	RWC	Chl	PH	FT	SL	Sk	SW	GPS	GW	GY	B	Pn	Gs
Chl	0.774 **
PH	0.670 **	0.869 **
FT	0.788 **	0.845 **	0.213
SL	0.557 *	0.359	0.544 *	0.485
Sk	0.757 **	0.728 **	0.637 *	0.574 *	0.593 *
SW	0.405	0.13	0.387	0.305	0.349	0.158
GPS	0.474	0.519	0.554 *	0.623 *	0.529	0.422	0.555 *
GW	0.786 **	0.710 **	0.554 *	0.621 *	0.469	0.879 **	0.235	0.462
GY	0.800 **	0.748 **	0.697 **	0.941 **	0.542 *	0.538 *	0.602 *	0.730 **	0.619 *
B	0.614 *	0.550 *	0.703 **	0.787 **	0.625 *	0.256	0.451	0.593 *	0.373	0.833 **
Pn	0.536 *	0.769 **	0.737 **	0.749 **	0.387	0.49	0.213	0.387	0.41	0.697 **	0.633 *
Gs	0.587 *	0.633 *	0.405	0.681 **	0.464	0.465	0.33	0.464	0.49	0.684 **	0.542 *	0.743 **
E	0.589 *	0.681 **	0.391	0.639 *	0.451	0.564 *	0.207	0.285	0.469	0.602 *	0.554 *	0.714 **	0.905 **

RWC = relative water contents; Chl = SPAD-chlrophyll; PH = Plant height; FT = Fertile tillers; SL = Spike length; Sk = Spikelet per spike; SW = Spike weight; GPS = Grains per spike; HGW = Hundred grain weight; GY = Grain yield; BY = Biological yield; Pn = Net Photosynthesis; Gs = Stomatal conductance; E = Transpiration rate. * significant; ** highly sig-nificant.

).

4. Discussion

The current study revealed that the RWC under well-watered conditions showed the highest values, which remarkably reduced under mild and severe drought conditions (Table 2). Out of 14 tested genotypes, Galaxy-2013 maintained the highest RWC under severe drought conditions, followed by AAS-2011, which showed their tolerance to severe drought stress and might be due to genetic differences, making them superior to other studied genotypes. The association between higher RWC and drought tolerance for various wheat varieties has already been reported [31,32], which elaborates that drought-tolerant varieties maintained more water contents under limited water availability [33]. Water retention under drought stress conditions could be a desired trait. However, when the plants keep closing their stomata, it may decrease the transpiration rate, affecting the uptake and transport of nutrients [34]. It was observed that plants exhibited the maximum SPAD-chlorophyll values under well-watered conditions. In contrast, the values were reduced when the crop experienced drought stress, and the minimum values were recorded under severe drought conditions (Table 2). A reduction in chlorophyll content under drought conditions was observed in different crop plants, including wheat, by another research [35]. However, the genotype Galaxy-2013 produced the highest SPAD-chlorophyll value under severe drought conditions (Table 2), which illustrates that Galaxy-2013 is a drought-tolerant variety staying green longer period which is the main character of drought-tolerant varieties. In contrast, reduced chlorophyll contents were observed in drought-sensitive wheat cultivars (Table 2). It has already been documented that some wheat varieties have undergone a reduction in chlorophyll contents under drought stress [36]. Reduction in photosynthetic pigments, including chlorophyll in wheat with the increasing water stress, was observed previously [37,38]. However, drought-tolerant genotypes retained many photosynthetic pigments under drought stress [38,39,40]. Drought stress can destroy or reduce chlorophyll content and inhibit its synthesis [41].

Photosynthesis plays a major role in the growth and yield of crop plants. Variation in photosynthetic pigments is the key indicator of the rate of photosynthesis in plants grown under water deficit [3]. It is well known that plant exposure to drought stress decreases the photosynthetic crop rate, including cereals [42]. In our study, different photosynthetic and gas exchange parameters, including Pn, gs, and transpiration rate, were reduced under drought stress conditions compared with the well-watered condition (Table 3). Chlorophyll is the main contributing factor towards photosynthesis rate; hence, decreases in net photosynthesis might be due to reduced chlorophyll contents under severe drought conditions (Table 1 and Table 2). In addition to chlorophyll, another contributing factor for reduced Pn is limited CO₂ diffusion due to early stomatal closure under drought stress [43]. Stomatal conductance was also reduced in our study under drought stress, which might be due to the closure of stomata to combat drought [44]. Stomatal closure limits water loss through transpiration and helps plants to conserve water during water stress [44]. Drought affects photosynthesis pigments differently depending on the variety. Genotypes with higher chlorophyll content have a more photosynthetic rate due to their genetic make-up under drought stress [45]. The same was observed in the current study, as Galaxy-2013 being a drought-tolerant variety, has higher net photosynthesis and stomatal conductance under severe drought (Figure 1 and Figure 2). A high photosynthetic rate and stomatal conductance in drought-tolerant cultivars were also reported in [33].

Yield and yield-related traits were reduced when the drought was imposed, and its effect was more significant under severe drought conditions compared with non-stressed or controlled treatments (Table 3, Table 4, Table 5 and Table 6). Amongst all wheat cultivars, the maximum fertile tillers, spikelets per spike, grains per spike, 100-grain weight, grain yield, and biological yield were recorded in Galaxy-2013, followed by Johar-2016 under severe drought conditions (Table 3, Table 4, Table 5 and Table 6). Enhanced yield and yield-related traits in Galaxy-2013 might be due to improved chlorophyll contents and photosynthetic and gas exchange parameters under severe drought conditions (Table 2; Figure 1, Figure 2 and Figure 3). Decreased yield in drought-sensitive genotypes might be due to a reduction in chlorophyll as well photosynthetic parameters. It has been studied that under low water stress conditions, plants maintain their internal moisture through stomatal closure, resulting in a reduction of gas exchange parameters [46]. On the contrary, low transpiration in drought-sensitive genotypes due to stomata closure may reduce uptake of water from the soil solution, reducing nutrient uptake and ultimately reduced grain yield [34]. Meanwhile, in the case of drought-tolerant genotypes, a higher grain yield was due to sustained photosynthesis [47]. A reduction in the growth and metabolic activities leads to a reduction in agronomic and yield attributes under water deficit conditions [48]. Such a reduction in grain yield under severe drought compared with well-watered conditions might also be due to less retention of RWC, reflecting fewer metabolic activities (Table 2) [49]. The genotypes with reduced leaf water loss are believed to be more drought tolerant and are less affected by water losses through evapotranspiration, thus able to conserve more water content and improve its yield [50]. Reduced CO₂ assimilation and transpiration rate, stomatal closure, RWC, and increased malondialdehyde content were observed in all cultivars under severe drought. However, drought-tolerant cultivars retained higher RWC and Pn, which ultimately improved grain yield [33].

The magnitude of correlations was stronger under severe water stress conditions than under mild and normal stress conditions. In a water-stress environment, sensitive physiological processes like turgor pressure, cell enlargement, division, and differentiation affect plant growth [51]. Under such conditions, the stomatal conductance is also decreased due to the reduction of leaf RWC, which reduces the net photosynthesis. The same was observed in our studies, where RWC was strongly correlated with gas exchange parameters under both extreme conditions (well water, Table 8; severe water stress, Table 10), and the same was responded in stronger correlations with the GY and BY. The significant and positive correlations between Pn, gs, and E under all treatments (Table 8 and Table 9) explain that the higher gs under normal water conditions than under severe stress condition might improve the access of CO₂ into the chloroplast and resulted in more Pn and E. Regardless of the dynamics of stomatal conductance, all three parameters are strongly correlated with each other, and this can be observed in our findings (Table 8 and Table 9). These results are also consistent with the findings in wheat [52], rice [53], and peanut [54].

5. Conclusions

The current study suggested that wheat variety Johar-2016 performed well under well-watered conditions by maintaining higher RWC, stomatal conductance, and net photosynthesis. In comparison, Galaxy-2013 performed well under both mild and severe drought conditions by maintaining higher RWC, stomatal conductance, and net photosynthesis, which resulted in a higher grain yield than other genotypes under severe drought conditions. Therefore, under arid to semi-arid conditions, the farmers may grow wheat variety Galaxy-2013 to receive a better economic yield.