View of Evaluation of wheat germplasm for drought tolerance using morpho-physiological approaches

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Evaluation of wheat germplasm for drought tolerance using morpho- physiological approaches

Ikam Muhammad¹, Muhammad Shuaib^2*, Naila Hadayat³, Alia Gul⁴, Muhammad Romman⁵, Khaist Begam⁶, Shazia Sakhi⁷, Badshah Alam⁶, Sahib Gul Afridi⁸, Adnan

Ghani⁹, Ali Sultan Khan¹⁰, Abdur Rauf¹¹, Noshin Shafqat⁶, Naseer Ali Shah¹², Siraj Bahadar¹³

1 Laboratory of Plant Metabolic Engineering, Faculty of Life Science and Technology, Kunming University of Science and Technology, China 2School of Ecology and Environmental Science, Yunnan University, Kunming, China

3Department of Botany, Division of Science and Technology, University of Education Lahore, Pakistan 4Department of Botany, Hazara University, Pakistan

5Department of Botany, University of Chitral, Pakistan

6Department of Biotecnology and Genetic Engineering, Hazara University, Manshera, Pakistan 7Centre for Plant Science and Biodiversity, University of Swat, Kp-Pakistan 8Department of Biochemistry, Abduwali Khan University, Mardan, Pakistan

9Department of Agriculture, University of Swabi, Pakistan

10Ryan Institue, Department of Microbiology, School of Natural Sciences, National University of Ireland, Galway, H91 CF50, Ireland 11Department of Botany, Abduwali Khan University, Mardan, Pakistan

12Department of Bioscience, COMSATS University, Islamabad, Pakistan 13College of Forestry, Hainan Univerity, Haikou, 570228, China Corresponding author email: Muhammad Shuaib: [email protected]

ABSTRACT

The main constraint to wheat production around the world is drought stress and is the most serious problem to the agriculture of Pakistan. The present study was planned for evaluation of wheat genotypes for drought using morphological parameters and proline accumulation as selection criteria for drought tolerance. Fifty-two wheat genotypes were evaluated under stress conditions. The experiment was performed in a randomized complete block design (RCBD) with three replications. Analysis of variance exposed significant dissimilarity for every trait. The genotypes 10835, 10832, 11881 and 11863 outperformed for most of the yield associated trait under stress condition. Proline contents were found more in drought stress than stress-free plants. 11878 genotype have highest proline content (376.505) followed by 10835(276.242) which is drought resistant variety. The genotypes 10835, 10832, 11881, 11863, 11878, Saleem-2000 and Suleman-96 are recommended for incorporation in a breeding program for drought condition and improved varietal development.

Keywords

Morphological; Physiological; Proline; Wheat; Germplasm; Drought Tolerance

Introduction

The most significant cereal crop of Pakistan is Wheat (Triticum aestivum L.). It is a staple diet for more than one-third of the world population and among all cereal crop, it provides more calories and protein to the world diet (Abd-El-Haleem et al., 2009). In Pakistan, wheat is the most stable food and occupies an essential position in agriculture strategies. About 90% of the world’s wheat production consists of the three species; T. durum (durum or macaroni wheat), T.

compactum (club wheat) and T. aestivum L. (common wheat) (Mahmood et al., 2006; Shuaib et a., 2021). Yield is the complex trait and is a result of the value of yield components as well; plant height, number of grain per spike, number of spikelets per spike, grain weight per spike and other parameters and it’s influenced by genotype and agro-ecological conditions (Drezner et al.

2007). Researchers have identified several morphological parameters such as plant height, grain yield, etc (Goral et al., 2005). The economic importance of wheat has generated intense cytogenetic and genetic studies in the past decades that have resulted in a wealth of information and tools which have been used to develop wheat cultivars with increased yield, improved quality and enhanced biotic and abiotic stress tolerance (Carver, 2009). Inadequate water is the chief constraint to wheat production worldwide (Ashraf and Harris, 2005). Drought stress shrinks the nutrient uptake in plants (Baligar et al., 2001). It is now well clear that drought-stressed

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plants show a range of physiological, biochemical and molecular alterations to flourish under water restricted conditions (Arora et al., 2002).Water stress experienced by a wheat crop during growth phases is known to have cumulative effects expressed as a decrease in total biomass as compared to well-watered conditions (Mirbahar et al., 2009). The decreased growth rate is caused mainly by a reduction in radiation use efficiency when the drought was at various growth stages such as tillering, booting, earing, anthesis and grain development stages (Wang et al., 2004).

The plant which experienced drought showed certain morphological and biochemical changes which eventually caused either functional harm to plant organs or loss of plant parts (Khan et al., 2001; Husman et al., 2000). Water stress at anthesis stage decreases pollination and number of grains per spike which results in the lessening of grain yield (Zhang et al., 2001).

Proline is one of the osmolytes, which boost faster than other amino acids in plants under water stress and facilitate the plants to maintain the cell turgor (Valentovic et al., 2006). Therefore, increasing proline concentration can be used as an evaluating parameter for irrigation scheduling and for screening drought-resistant varieties (Bates et al., 1973; Gunes et al., 2008). Plant height is an important consideration for many wheat growers and plant breeders developing cultivars to meet grower needs (Budak et al., 1995; Baenziger et al., 2004a).

During the grain filling period in Pakistan, the temperature usually exceeds over the optimum limits resulting in instability in wheat yield. Grain filling proceeds steady and robust in the range of 25-28°C. During March/April the flowering and grain filling are routinely exposed to warming temperatures (maximum 28-38°C). Yield reduction is higher especially in late-planted crop or in high temperature during grain filling (Khan, 2004). Drought is one of the most important abiotic stresses that severely affect and reduce the yield and productivity of food crops worldwide up to 70% (Kaur et al., 2008; Thakur et al., 2010; Akram, et al., 2013). A physiological approach would be the most attractive way to develop new varieties (Araus et al., 2008). Drought is multidimensional stress affecting plants at various levels of their organization.

Drought affects morphological, physiological and biochemical processes in plants resulting in growth inhibition, stomatal closure with consecutive reduction of transpiration, decrease in chlorophyll content and inhibition of photosynthesis (Demirevska, 2008) making it the largest single factor for yield reduction globally (Narusaka et al., 2003).

morphological characters such as root length, spike number per m-2, tillering, grain number per spike, awn length, 1000 grain weight, peduncle length, spike weight, number of fertile tillers per plant, stem weight, grain weight per spike are affected wheat tolerance to moisture shortage in the soil (Passioura, 1977; Levitt, 1980; Kramer, 1983; Jhonson et al., 1983; Moustafa et al., 1996; Plaut et al., 2004; Blum, 2005). Among these characters, morphological traits are commonly used to evaluate genetic variation because their measurements are simple (Najaphy et al., 2012). Physiological studies of wheat have indicated that flag leaf contribution towards grain weight accounts for 41- 43% of dry matter in the kernel at maturity and are the major photosynthetic site during the grain filling stage (Ibrahim and Elenein, 1977).

Under various environmental stresses, high accumulation of proline is a characteristic feature of most plants (Rhodes et al., 1999; Ozturk and Demir, 2002; Hsu et al., 2003; Kavi-Kishore et al., 2005). Its accumulation is generally correlated with stress tolerance because tolerant species accumulate more proline as compared to sensitive ones. For example, salt-tolerant alfalfa (Fougere et al., 1991; Petrusa and Winicov, 1997) and drought tolerant wheat (Nayyar and Walia, 2003) have a greater amount of proline than the sensitive cultivars. Exogenous application of proline is known to induce abiotic stress tolerance in plants (Claussen, 2005; Ali et

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al., 2007), because proline may well protect protein structure and membranes from damages, and reduce enzyme denaturation (Iyer and Caplan, 1998; Saradhi et al., 1995; Smirnoff and Cumbes, 1989). Proline also acts as a regulatory or signaling molecule to activate a genotype of responses (Maggio et al., 2002). Proline storage is as well beneficial for plants as a source of nitrogen (Hare et al., 1998).

It is well described (Verbruggen et al., 2008) that under stress conditions many plant species accumulate proline as an adaptive response to adverse conditions. Although a clear-cut relationship between proline accumulation and stress adaptation has been questioned by some authors (Hare et al., 1997), it is generally believed that the increase in proline content following stress injury is beneficial for the plant cell.Although the developmental accumulation of proline in reproductive organs has been repeatedly reported and seems to be a widespread phenomenon among plant species, its functional meaning still matters of debate. An obvious function of proline in development may be the protection of developing cells from osmotic damages, especially in those developmental processes, such as pollen development and embryogenesis, in which tissues undergo spontaneous dehydration. As an alternative possibility, proline has been proposed to provide energy to sustain metabolically demanding programs of plant reproduction.

In a similar way, proline is used in animal systems to fuel the initial phase the most energy dependent of the flight of many insects, such as bees and butterflies (Micheu et al., 2000).

The possibility that the time of flowering may be affected by proline, either developmentally- or stress-induced, is an old idea supported by a limited number of reports and based on the belief that stress can induce flowering. An involvement of proline in flower transition, for example, was suggested in Sinapis alba, (Bernier et al., 1981) kiwi-fruit, (Walton et al., 1991) tobacco, (Trovato et al., 2001), (Kavi-Kishor et al., 1995), (Mauro et al., 1996) tomato (Bettini et al., 2003) and Vigna aconitifolia. (Saxena et al., 2008). Two recent papers by (Mattioli et al., 2008) however, raised the possibility that modulations of low proline concentration localized in apical meristems may signal optimal conditions for the plant to flower, while higher concentrations of proline might be interpreted by the plant as a stress signal and induce adaptive responses, including late flowering.

Methods Plant material

The current research work was performed under field circumstances of Mansehra at Hazara University during. Fifty-two genotypes of common wheat consisting of genotypes and varieties collected from different regions of Pakistan and were examined for proline accumulation under stress condition and yield-associated traits.

Morphological study

These fifty-two wheat genotypes and varieties were grown at most favorable sowing time in Randomized Complete Block Design (RCBD) having three replications. Morphological study of fourteen parameters was carried out. The data was collected on three randomly selected plants in each row for different morphological parameters i.e. plant height, number of tillers, peduncle length, spike length, number of spikelet per spike, number of grains per spike, flag leaf area, biological yield, 1000 grains weight, yield per plant, spike density, harvest index, powdery mildew disease percentage and days to maturity.

Induction of Water Stress

All the genotypes were grown in controlled conditions for proline determination. The genotypes were sown in pots having 17 cm in height and 15 cm width. A mixture of clay, sand and organic fertilizer (1:1:1) was added to pots containing 5 seeds. Thinning was carried out after

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germination. The controlled pots were provided with stress conditions until the plants became wilting. The leaves were detached for further proline determination in the laboratory.

Determination of Proline Content of Leaves

Proline content of flag leaves was estimated at both stages i.e. control and stress following the method of Bates et al. (1973).

Reagents  Acid ninhydrin,3% sulfosalicylic acid, Glacial acetic acid,Toluene Acid Ninhydrin:

Warm 1.25g ninhydrin in 30ml glacial acetic acid and 20ml of 6 molar phosphoric acid in a water bath. Store at 4 ºC for 24 hours.3% aqueous sulfosalicylic acid. Add 3g of sulfosalicylic acid in 100ml distilled water to make it 3% aqueous sulfosalicylic acid.

Steps

 Take 0.5g plant leaves. Add 5ml 3% sulfosalicylic acid during leaves crushing. Add 5ml 3% sulfosalicylic acid after leaves crushing in a test tube.  Filter the mixture through What man

#2 filter paper. Take 0.5ml filtrate in a boiling test tube, add 2ml glacial acetic acid and react with 2ml acid ninhydrin in a boiling water bath. React the extract with 5ml toluene. Mix thoroughly on a vortex mixer. Allow warming to room temperature. Measure the absorbance at 515 nm against toluene blank, using a spectrophotometer.

Results Plant height

Analysis of variance exposed that there exists significant dissimilarity for plant height between different varieties as well as amongst two treatments. According to control environment maximum height were found in Siren-2010(101) followed by 10798 (90) and Lasani-08(89) while minimum height was observed in 10830(24) while under stress condition maximum height was observed in Siren-2010 (98) followed by Hashim (53) and 10808(52) while minimum height was found in10830 (21)(Fig.3).

No of tillers per plant

Analysis of variance exposed that there exists significant dissimilarity for a number of tillers between different varieties as well as amongst two treatments while the interaction was non- significant. According to control environment maximum number of tillers were found in 10874(9) followed by 10852(9) and 11780(8) while minimum number of tillers were observed in 10835(1.66) while under stress condition maximum no of tillers were observed in 10852 (8) followed by 10874(8) and 10832 (7), 11780 (7) while minimum number of tillers were observed in 10835 (1) (Fig. 4)

Peduncle length

Analysis of variance shown that there exists a difference for peduncle length between different varieties as well as amongst two treatments. According to control environment maximum peduncle length were found in Saleem-2000 (78cm) followed by 10830 (75cm) and siren-2010 (44cm) while minimum peduncle length was observed in 11860(7cm) and 10833(7cm) while according to stress condition maximum peduncle length were found in Siren-2010(41cm) followed by 11879(37cm) and 11863(37cm) while minimum peduncle length was found in 10833 (4cm) (Fig. 5).

Spike length

Analysis of variance exposed that there exists dissimilarity for spike length between different varieties as well as amongst two treatments. According to control environment, a maximum number of spike length were found in 10832(13) and 10771(12.33) followed by 10845(12),

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10835(12) while a minimum number of spike length were observed in 10833(5). While according to stress condition a maximum number of spike length were observed in 10771(11.5) followed by 10832(11.16) and 11868(11.16) while the minimum number of spike length were observed in genotype 11879(5) (Fig. 6).

No of spikelets/spike

Data regarding no of spikelets/spike was found significant among all the varieties and conditions.

According to controlled environment maximum number of spikelet/spike were found in 10800(22.66) followed by 10849(22.66) and 10832(21.16), while minimum number of spikelet/spike was witnessed in UQAB-2000(11), while according to stress condition maximum number of spikelet/spike were witnessed in 10800(21.33) followed by10849(20.33) and 10835(20) while minimum number of spikelet/spike were witnessed in PS-85 (Fig.7).

No of grains/spike

Examination of variance exposed that there exists dissimilarity for no of grains/spike between different varieties as well as amongst two treatments. According to control atmosphere maximum amount of grains/spike were found in 11881(72.83) followed by 10845(72.33) and 10832(64.66) while minimum amount of grains/spike were found in ZAM (19) while according to stress condition maximum no of grains/spike were observed in 11881(70.33) followed by 10845(69.16) while lowest amount of grains per spike were observed in ZAM(17) (Fig.8).

Flag leaf area

Examination of variance exposed that there exists highly significant dissimilarity for flag leaf area between different varieties as well as amongst two treatments. According to control condition maximum flag leaf area were found in 10835(47.36) followed by 11863(44.4) and Saleem-2000(42.92) while minimum flag leaf area was observed in 11873(5.32) while in stress condition maximum flag leaf area were found in 10835(46.36) followed by 11863(43.4) and Saleem-2000(41.92) while minimum flag leaf area was observed 11873(4.32) (Fig.9).

Biological yield

Examination of variance exposed that there exists highly significant dissimilarity for biological yield between different varieties as well as amongst two treatments. According to control environment biological yield were found in 11863(32.66) followed by 10771(28.36) and 10759(25.8) while minimum biological yield was observed in 11860 (8.33) while under stress condition maximum biological yield were observed in 10759(24.8) followed by 10845(24.73) and 11881(24.66) while minimum biological yield was observed in genotype 11873(7.36) (Fig.

10).

1000 grains weight

Study of variance exposed that there exists highly significant dissimilarity for 1000 grains weight between different varieties as well as amongst two treatments. Maximum thousand grains weight were observed in control atmosphere in 11878(128) followed by 11863(124) and 10835(114) while minimum 1000 grains weight were observed in 11875(0.1). While under stress condition maximum 1000 grains weight were observed in 11878(125) followed by 11863(121) and 10835(111) while minimum 1000 grains weight were observed in genotype 10800(26) (Fig.11).

Yield/plant

Examination of variance exposed that there is highly significant dissimilarity for yield/plant between different varieties and genotypes as well as amongst two treatments. According to the control environment maximum yield/plant was found in 10832(15.5) followed by 11863(15.46) and 10771(15.2) while minimum yield/plant was observed in 11860(3.86). While under stress

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condition maximum yield/plant were observed in 10832(14.5) followed by 11863(14.46) and 10771(14.2) while minimum yield/plant was observed in genotype 11860(2.86) (Fig.12).

Spike density

Data regarding spike density showed a highly significant difference among all the genotypes and treatments. According to the control environment, maximum spike density was found in 10835(3.21) followed by 10808(2.8) and 10852(2.72) while a minimum number of spikes were observed in 10759(1.27). According to stress situations, the highest spike density was examined in 10835(3.11) then 10808(2.66) and 10852(2.59) while the lowest spike density was examined in 10759(1.27).

Harvest Index

Data regarding harvest index showed a highly significant difference among all the genotypes and treatments. According to the control environment, Maximum harvest index was found in 11875 followed by 10848 and 10832 while minimum harvest index was observed in 11878 while in stress situation maximum harvest index were found in 10832 (12) then 11881(11) and 10845(11) while lowest harvest index was found in 10808(4) (Fig.14).

Powdery mildew Disease %

Statistical analysis of data showed that there exists highly significant dissimilarity for powdery mildew disease % between different varieties as well as amongst two treatments. Under control situation highest disease percentage (90) was observed in 11866, 10819, Pak-81 followed by Uqab-2000(80), 10852(80) and Hashim (80) while minimum disease percentage (1) was observed in, PS-85, 11881, Saleem-2000, Khyber-87, 10854, 11864, 10845 and Suleman-96.

Under stress condition, maximum disease percentage (90) was observed in 10833, 10803 and 11863 while minimum disease percentage (2) was observed in 11877 and 11860 (Fig.15).

Days to maturity

Data regarding days to maturity showed an extremely significant difference between all the genotypes and treatments. Under normal condition maximum days to maturity were found in 10853(203) followed by 10803 (200) while minimum days to maturity were observed in 10832(187) while under stress condition maximum days to maturity were observed in 10824(202.7) followed by 10849(199.7) while minimum days to maturity were observed in 10832(186) (Fig.16).

Proline content

A statistical study of data revealed that there is a highly significant difference for proline content between different genotypes as well as between two treatments. According to control environment maximum proline content were found in Suleman 96(35.56) followed by 11878(26.752) and 11874(20.74) while minimum proline content were observed in 10808(3.78) while under stress condition maximum proline content were observed in 11878(377.13) followed by Saleem-2000(284.39) and 10835(275.96) while minimum proline content was observed in 10798(8.22) (Fig.17).

Correlation studies

The correlation was worked out among plant height, no f tillers, peduncle length, flag leaf area, 1000 grains weight, disease%, days to maturity, spike length, yield/plant, harvest index. Plant height is significant and positively correlated with peduncle length, spike length, no of grains/spike, flag leaf area, biological yield, yield/plant and days to maturity but plant height is negatively correlated with no of tillers,1000grains weight, and harvest index. No of tillers are significant and positively correlated with no of grains/spike, biological yield, yield/plant, harvest index while negatively correlated with 1000 grains weight, plant height and days to maturity.

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Peduncle length is significant but positively correlated with plant height, spike length, no of spikelet/spike, no of grain/spike, flag leaf area, biological yield, yield/plant, and proline content.

Spike length is significant but positively correlated with plant height, peduncle length, no of spikelet/spike, no of grains/spike, flag leaf area, biological yield, yield/plant, and proline content.

No of spikelet/spike is significant but positively correlated with spike length, peduncle length, no of grains/spike, flag leaf area, biological yield, yield/plant, and proline content. No of grains/spike is significant but positively correlated with plant height, no of tillers, peduncle length, spike length, no of spikelet/spike, flag leaf area, biological yield, yield/plant, and proline content while negatively correlated with days to maturity. Flag leaf area is significant and positively correlated with plant height, peduncle length, spike length, no of spikelet/spike, no of grain/spike, biological yield, yield/plant, spike density, disease, and proline content but it is negatively correlated with days to maturity. Biological yield is significant and positively correlated with plant height, no of tillers, spike length, no of spikelet/spike, no of grain/spike, flag leaf area, yield/plant, and proline content. Biological yield is significant and negatively correlated with days to maturity.

1000 grains weight is significant and positively correlated with spike density, disease, and proline content. While negatively correlated with plant height, no of tillers. Yield/plant is significant and positively correlated with harvest index but negatively correlated with days to maturity. Yield/plant is non-significant and positively correlated with spike density and disease%. Spike density is highly significant and positively correlated with flag leaf area, 1000 grains weight, disease%, and proline content. Harvest index is significant and positively correlated with no of tillers, yield/plant negatively correlated with plant height, disease%, days to maturity proline content.

The disease is significant and positively correlated with flag leaf area,1000 grain weight, spike density, days to maturity and proline content while negatively correlated with harvest index.

Days to maturity is significant and positively correlated with plant height and disease while negatively correlated with no of tillers, no of grain/spike, flag leaf area, biological yield, yield/plant, and spike density. Proline content is significant and positively correlated with peduncle length, spike length, no of spikelet/spike, no of grain/spike, flag leaf area, biological yield,1000 grains weight, spike density, and disease while negatively correlated with harvest index.

Cluster analysis

Dendogram (Fig 18) shows that there are four main clusters A,B,C and D. Cluster A have 46 varieties and genotypes that is 11865, 11874, 10874, UQAB-2000, 10818, 11864, 10821, 11780, ZAM, 11879, PAK-81, Lasani-08, 10798, 10800, Siren-2010, 10853, 10848, 10819, 10854, 10759, PS-85, Khyber-87, 11881, 10832, Kaghan, Haider 2000, KT-2000, Gomal, Atta Habib, 10845, 10808, 11877, 10852, 10833, 10849, 11868, 10755, 11860, 10830, 11873, 10833, 10803, 11866, 10771, 10824, 11875. Cluster B have 4 varieties and genotypes 11863, 10835, Suleman96, Hashim. Cluster C have 1 genotype Saleem 2000 and cluster D also have only 1genotype 11878.

Discussion

Wheat is the most important cereal crop in the world (Akbar, 2001; Zahid et al., 2003; Tunio, 2006), and the major source of food for the inhabitants of Pakistan (Chaudhary, 1999; Malik, 2006). Being the main staple food of the rapidly increasing population of Pakistan, wheat occupies a central position in the agricultural policies of the country. It contributes 12.5% to the value added in agriculture and 2.9% to GDP (Muhammad et al., 2005; Naeem et al., 2020).

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Pakistan is ranked 9th in wheat production (Anonymous., 2008). According to recent statistics, the average grain yield of wheat in Pakistan is 2379 kgha-1 which is much lower than other wheat growing countries of the world (Malik, 2006; Shuaib et al., 2020).

Many environmental stresses affect the growth of wheat but the drought is the main threat to the wheat crop. Drought stress often causes serious problems and is a major limitation to the productivity of the crop. Drought affects morphological, physiological and biochemical processes in plants resulting in growth inhibition, stomatal closure with consecutive reduction of transpiration, decrease in chlorophyll content and inhibition of photosynthesis (Demirevska, 2008).

Proline is one of the osmolytes, which increase faster than other amino acids in plants under water stress and help the plants to maintain the cell turgor (Valentovic et al., 2006). Therefore, increasing proline concentration can be used as an evaluating parameter for irrigation scheduling and for screening drought-resistant varieties (Gunes et al., 2008; Muhammad et al., 2020).

Under normal condition maximum plant height was found in siren-2010 (101cm) while under stress condition maximum plant height was found in siren-2010 (98cm). Maximum no of tillers was found in 10874(9) under normal condition but according to stress environment maximum, no of tillers were found in 10852 (8). According to controlled environment, the maximum peduncle length was found in Saleem-2000(78cm) while according to stress environment maximum peduncle length was found in siren-2010(41cm). According to control environment, maximum spike length was found in 10832(13). While under stress condition maximum spike length were observed in 10832 (12). According to controlled environment maximum number of spikelet/spike was found in 10800(23) while according to stress condition maximum number of spikelet/spike was observed in 10800(22).

According to normal environment, maximum number of grains/spike were found in 11881(73) while according to stress condition maximum no of grains/spike were observed in 11881(71).

According to normal condition maximum flag leaf area were found in 10835(47.36) while according to stress condition maximum flag leaf area was observed 10835(46.36). According to normal environment, biological yield was found in 11863(32.66) while according to stress condition maximum biological yield was observed in 10759(24.8). According to normal environment maximum, 1000 grains weight were found in 11878(128), while according to stress condition maximum 1000 grains weight were observed in 11878(125). According to normal environment maximum yield/plant were found in 10832(15.5), while according to stress condition maximum yield/plant were observed in 10832(14.5). According to normal environment, maximum spike density was found in 10835(3.21) while according to stress condition maximum spike density were observed in 10835(3.11). According to normal environment maximum of harvest, index was found in 11875, while according to stress condition maximum harvest index was observed in 10832 (12). Under normal condition, minimum disease percentage (1) was observed in 11881, Suleman-96 and Saleem-2000. Under stress condition, minimum disease percentage (2) was observed in 11877 and 11860. Under normal condition, minimum days to maturity were observed in 10832(187) while under stress condition minimum days to maturity were observed in 10832(186).

When we extract the proline content from different varieties we found maximum proline content in Suleman 96(35.834) followed by 11878(26.752) and Saleem-2000(23.930) according to control environment. But in case of stress environment, we found maximum proline content in 11878(376.505) followed by Saleem-2000(285.07) and 10835(276.242).

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Correlation between different traits is generally due to the presence of linked genes and epistatic effect of different genes. Environment plays an important role in correlation genetic and environmental causes of correlation combine together and give phenotypic correlation.

No of spikelet/spike is significant but positively correlated with spike length, no of tillers, no of grains/spike, flag leaf area,1000 grains weight, biological yield and yield/plant. A positive and significant correlation between a number of spikelets per spike and yield per plant is also reposted by Ashraf. et al., 2012.

Spike length is significant but positively correlated with no of spikelet/spike, no of grains/spike, flag leaf area, biological yield, yield/plant. (Iqbal et al., 2020; Sharma et al. (2003b) also reported similar results.

Spike length was in positive relationship at both phenotypic and genotypic levels with yield/plant.Also, it was positively correlated with number of grains/spike at both phenotypic and genotypic levels (Ashraf et al., 2012; Khan et al., 2021)

Grains/spike is an important yield component. According to my results, no of grains/spike is highly significant but positively correlated with flag leaf area, biological yield, yield/plant, no of spikelet/spike, spike length, peduncle length, plant height, and proline content negatively correlated with days to maturity. Quite identical results were obtained by Aycicek and Yildirim (2006).

Figures 10-18 shows that flag leaf area is significant and positively correlated with no of grain/spike, no of spikelet/spike, spike length, plant height, biological yield, yield/plant, spike density, and disease but it is negatively correlated with days to maturity and no of tillers. Kashif (2006) works also showed the correlation between plant height and flag leaf area was positive and significant (P ≤ 0.05) at both genotypic and phenotypic levels.

Yield/plant is significant and positively correlated with harvest index,1000 grains weight, biological yield, flag leaf area, no of grain/spike, no of spikelet/spike, spike length, peduncle lengt, and plant height but negatively correlated with days to maturity. (Baloch, et al., 2013) work also shows the correlation between spike length and grain yield/plant showed significantly positive association which indicated that an increase in spike length will markedly increase grain yield/ plant.

When we extract the proline content from different varieties we found maximum proline content in Suleman 96(35.834) followed by 11878(26.752) and Saleem-2000(23.930) according to control environment. Under stress environment, we found maximum proline content in 11878(376.505) followed by Saleem-2000(285.07) and 10835(276.242). The study also showed that proline contents are more in a stressed plant as compared to controlled plants. High proline content in wheat and other plants after water stress has been reported by Tatar and Gevrek (2008), Vendruscolo et al. (2007) and Errabii et al. (2006).

Conclusion

Genetic improvement of crops for drought tolerance requires a search for possible relationship of physiological and yield traits among the genotype for such traits. It has been observed that drought stress imposed at various growth stages causes different effects on crop plants. With respect to physiological and yield traits, drought stress imposed a significant impact on the traits.

The high yielding genotypes were 10835, 10832, 11863, 10771, and 11881. The genotypes 10835, 10832,11881 and 11863 showed good performance for most of the yield-related traits under stress conditions. Under stress condition, high proline accumulation found in 11878, Saleem 2000, 10835, and Suleman-96.

Conlfict of Interest

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All the authors daclare have no conflict of interest Acknowledgments

We all authors are thankful to the department of Genetics Hazara University for providing facilitities to conduct our research.

Funding

This research received no special grant from higher education commission (HEC), supported by Department of Genetics Hazara University, KPK, Pakistan

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Figures

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Figure. 3Under control and stress environment, Graphical illustration of plant height of wheat genotypes.

Figure. 4. Under control and stress environment, Graphical illustration of number of tillers of wheat genotypes 200

4060 10080 120

11873 11868 10808 11877 11862 10833 10852 10849 11860 10755 10821 10800 Lasani-08 10798 10803 11780 Siran-2010 ZAM 11879 Pak-81 11864 10824 UQAB-2000 10874 11865 11874 11875 11866 10759 10819 10853 11881 10845 10830 10848 10818 10854 10832 10771 PS-85 KT-2000 Atta Habib khyber-87 kaghan Gomal Haider 2000 Hashim Suleman 96 11863 Saleem 2000 10835 11878

plant height

varieties/genotypes T1 control T2 stress

01 2 34 5 6 78 9 10

no of tillers

varieties/genotypes

T1 control T2 stress

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Figure. 5.Under control and stress environment, Graphical illustration of peduncle length of wheat genotypes

Figure. 6. Under control and stress environment, Graphical illustration of spike length of wheat genotypes 0

10 20 30 40 50 60 70 80 90

peduncle length

02 4 6 8 10 12 14 16

spike length

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Figure. 7. Under control and stress environment, Graphical illustration of number of spikelet/spike of wheat genotypes

Figure. 8. Under control and stress environment, Graphical illustration of number of grains/spike of wheat genotypes 0

5 10 15 20 25

no of spikelet/spike

100 2030 4050 6070 8090

no of grains/spike

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Figure. 9. Under control and stress environment, Graphical illustration of flag leaf area of wheat genotypes

Figure. 10. Under control and stress environment, Graphical illustration of biological yield of wheat genotypes 0

10 20 30 40 50 60

flag leaf area

05 1015 2025 3035 40

biological yield