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© 2021 Conscientia Beam. All Rights Reserved. 

HEAT TOLERANCE STABILITY OF BREAD WHEAT GENOTYPES UNDER EARLY 
AND LATE PLANTING ENVIRONMENTS THROUGH STRESS SELECTION INDICES   

 

 

 Zeeshan Ahmad1+  
Muhammad Ishaq2 

Iqra Tahir3 
Adeel Khan4 

Kainat Jehan5 

1,3,4Department of Plant Breeding and Genetics, The University of 
Agriculture, Peshawar, Pakistan. 

 
 

2Cereal Crops Research Institute (CCRI), Pirsabak, Nowshera, Pakistan. 

 
5Department of Chemistry, Women University, Swabi, Pakistan. 

 
 

 
(+ Corresponding author) 

 

 ABSTRACT 
 
Article History 
Received: 18 January 2021 
Revised: 22 February 2021 
Accepted: 24 March 2021 
Published: 12 April 2021 
 

Keywords 
Triticum aestivum L. 
Stress selection indices 
Normal 
Late planting 
Genotype × environment 
interaction 
Correlation. 

 
A field study was conducted with an objective to assess thirty six wheat cultivars for 
tolerance, stability and enhancing productivity under optimum and stressed planting 
environments at Cereal crops Research Institute (CCRI), Nowshera, Pakistan during 
2017-18. Experiment was laid out in randomized complete block design using three 
replications. Pool analysis of variance exhibited highly significant (p≤0.01) variations 
among wheat genotypes, environments and G × E interactions for the under studied 
traits. In general, reduction in mean wheat genotypes for days to heading (19%) and 
grain yield (65%) was observed under stressed condition as compared to optimum 
planting environment. Across planting environments, highest grain yield was produced 
by wheat genotypes Pakistan-13 (3746 kg ha-1) closely followed by two other genotypes 
Zincol-2016 (3712 kg ha-1) and PR-122 (3671 kg ha-1). Various stress selection indices 
viz tolerance (TOL), mean productivity (MP), harmonic mean (HM), geometric mean 
productivity (GMP), stress tolerance index (STI), yield index (YI), stress susceptibility 
index (SSI) and yield stability index (YSI) were  employed for each genotype under 
both environments. Correlation coefficient analysis unveiled that days to heading and 
grain yield had positive significant association with GM, HM MP, YI and STI. 
Aforementioned stress selection indices were found effective tools for identification of 
stress tolerant genotypes under delayed planting. On the basis of these selection 
indices, wheat genotypes i-e Zincol-16, Pirsabak-13, PR-122 and Pakistan-13 were 
found high yielding stress tolerant which could be sown under non-stressed and 
stressed conditions and could be used in future wheat breeding schemes.  
 

Contribution/Originality: The paper’s primary contribution is finding more stable, heat tolerant and high 

yielding bread wheat genotypes across normal and late planting environments. This study documents is vital to 

wheat breeders to suggest these genotypes for stress environments directly or to use for the development of new 

genotypes for the changing climatic conditions. 

 

1. INTRODUCTION 

Wheat (Triticum aestivum L.) is member of cereal grass family Poaceae, an important staple food of about half of 

the world population. Wheat adds about 80% of the nutritional food value to our daily diet and consumed in 

countless ways by the population [1]. Consumption and demand of wheat is increasing day by day. This demand 

for food will have to be met by increasing yield per unit area or by devoting land to wheat [2]. 

Current Research in Agricultural Sciences 
2021 Vol. 8, No. 1, pp. 37-46. 
ISSN(e): 2312-6418 
ISSN(p): 2313-3716 
DOI: 10.18488/journal.68.2021.81.37.46 
© 2021 Conscientia Beam. All Rights Reserved. 

 
 
 

 
 
 

 

 
 
 
 

https://orcid.org/0000-0001-5367-9318
https://www.doi.org/10.18488/journal.68.2021.81.37.46


Current Research in Agricultural Sciences, 2021, 8(1): 37-46 

 

 
38 

© 2021 Conscientia Beam. All Rights Reserved. 

There are numerous factors that affect grain yield viz environmental conditions (stressed and non-stressed 

conditions, heat stress, and coldness), accelerated phasic development, increase in respiration, accelerated 

senescence,  sowing dates, reduction in photosynthesis,, varietal potential, poor agronomic management practices 

and their interactions [3]. Among these factors, heat stress is supreme, severely damaging grain yield and should 

be controlled by the breeder to overcome the drastic yield reduction in wheat. Wheat crop has been surviving such 

harsh conditions and stresses so that it can obtain various sensitive and stress perceiving mechanisms to regulate 

their physiology [4]. Nowadays, researchers are interested in crop responses towards environmental stresses like 

heat stress and it’s a big dilemma for them to breed for heat tolerant genotypes. To resolve this issue, breeders use 

diverse strategies of selecting relative heat tolerance and resistant genotypes in the targeted environments while 

some go for the mid way and select genotypes under both targeted stress and non-stress conditions [5]. 

The utmost task of the plant breeders is assessment and identification of noval climatic resilient genotypes 

having wider adoptability and better performance over diversified agro climatic conditions especially heat stress. 

Genetic improvement in wheat and developing stress tolerant genotypes requires information about the germplasm 

and identify genotypes that can grow best under optimum and stressed conditions. Under such circumstances 

several stress indices are used by breeders when genotypes are evaluated among both conditions. Mean productivity 

(MP), tolerance (TOL), harmonic mean (HM), stress susceptibility index (SSI), stress tolerance index (STI), yield 

index (YI), geometric mean productivity (GMP) and yield stability index (YSI) have all been employed to find out 

stable and tolerant genotypes under non-stress and stress conditions. 

The diversified response of genotypes to environmental conditions is termed as genotype by environment 

interactions which play a crucial role in determination of the genotypes under various environments. Presence or 

lack of significant genotype by environment interactions helps us in development of stable, high yielding genotypes 

for wider or specific agro-ecological adaptations [6]. There are different types of genotypes, some adopt themselves 

to broader environments while other lacks adaptability to diverse conditions and genotypes with consistent 

performance over wider range are consider more stable and high yielding [7]. The main theme of this specific 

breeding program is to understand the importance and causes of G × E interactions at all stages so that be used in 

selection and identification of desirable genotypes for that environments. In the current scenario, present 

experiment was conducted to investigate genotype by environment interactions and identify stress tolerant 

genotypes under optimum and stressed condition through stress selection indices.  

 

2. MATERIALS AND METHODS 

The experimental trial was conducted at Cereal Crops Research Institute (CCRI), Pirsabak-Nowshera, Pakistan 

(740 E and latitude 320 N) on a silt loam soil (pH=7.8) with an elevation of 288 meters, during Crop season 2017-

18. The genetic material compromised a total of thirty six wheat genotypes (six advance lines and thirty wheat 

cultivars) were acquired from all provinces of Pakistan Table 1. Breeding material was evaluated in a randomized 

complete block design (RCBD) with three replications as independent experiments under normal planting (non-

stressed) and late planting (stressed) conditions. Individual genotype was planted in four rows per plot, with three 

meters length and row to row spacing of 30 cm in each environment. The optimum date of planting was 09 

November, 2017 while, late planting was made on December 18, 2017. Standard cultural practices and crop 

husbandry practices were kept same for all the entries of wheat throughout the growing season in both the 

experiments. 

 

2.1. Statistical Analysis 

The collected data on days to maturity and grain yield were statistically analyzed according to the procedure 

suggested by Gomez and Gomez [8] using computer software SAS and SPSS package. Subsequently computing 

significant differences among the genotypes, environments and genotype × environment interactions, the means 



Current Research in Agricultural Sciences, 2021, 8(1): 37-46 

 

 
39 

© 2021 Conscientia Beam. All Rights Reserved. 

were further equated by using least significant difference (LSD) test at 5% level of probability. Beside this, the 

normal and late planting conditions were assumed as non-stress and stressed conditions to work out the following 

stress selection indices. 

       [9] 

      [9] 

          [10] 

      [11]  

                    [12]  

     [11]  

     [12]  

       [13]  

Where; 

Xn = Mean of a genotype for that trait in normal planting. 

Xl = Mean of a genotype for that trait in late planting. 

 = Grand mean for a particular trait in normal planting. 

= Grand mean for a particular trait in late planting. 

 

3. RESULTS AND DISCUSSION 

3.1. Analysis of Genotypic Variation 

Pool analysis of variance across both planting conditions (non-stressed and stressed) exhibited highly 

significant (p≤0.01) differences among the wheat genotypes, environments and genotype × environment 

interactions for days to heading and grain yield Table 2. The above results suggested that there is a substantial an 

inherent genetic variability existed among the genotypes. Significance of genotype by environment interactions 

revealed that these genotypes perform better and thus a sufficient scope is present for selecting various quantitative 

traits for improvement. Considerable amount of highly significant genetic diversity for wheat genotypes was also 

reported by Poudel, et al. [14]. Highly significant results for various wheat genotypes were indicated by Mehraban, 

et al. [15]; Jaiswal, et al. [16]. 

 

3.2. Means and Stress Selection Indices 

3.2.1. Days to 50% Heading 

Days to heading and maturity are likely important in wheat crop because the plants can be protected from the 

forth coming stress conditions and insect pests attack due to early heading and maturity.   



Current Research in Agricultural Sciences, 2021, 8(1): 37-46 

 

 
40 

© 2021 Conscientia Beam. All Rights Reserved. 

Table-2. Mean squares for days to heading and grain yield in wheat genotypes evaluated under normal (non-stressed) and late (stressed) sown 
conditions. 

Sources of Variation df Days to heading Grain yield 

Environment 1 35805.38** 125795906** 
Genotypes 35 26.29** 780914.9** 

Genotypes  × Environment 35 8.03* 359782.5** 
Error 140 5.29 123716.2 
CV - 2.13 11.25 

Note: *, ** = Significant at 5% and 1% level of probability, respectively, NS = Non-Significa. 

 

Table-3. Mean performance and stress selection indices of wheat genotypes for days to heading  evaluated under normal (non-stressed) and 
late (stressed) sown environments. 

Genotypes 
Days to heading 

(Days) MP TOL HM GMP YI STI SSI YSI 

Normal Late 

PR-114 160 135 147.50 25.00 146.44 146.97 1.01 1.20 0.96 0.84 

PR-118 163 134 148.00 29.00 146.58 147.29 1.00 1.21 3.92 0.82 

PR-119 161 136 148.08 25.17 147.01 147.55 1.01 1.21 3.44 0.84 

PR-122 163 134 148.42 28.83 147.02 147.71 1.00 1.22 3.89 0.82 

PR-123 159 132 145.17 27.33 143.88 144.52 0.98 1.16 3.78 0.83 

PR-124 160 134 146.92 26.83 145.69 146.30 1.00 1.19 3.68 0.83 

Paseena-17 159 134 146.08 25.17 145.00 145.54 1.00 1.18 3.48 0.84 

Khaista-17 163 136 149.17 27.33 147.91 148.54 1.01 1.23 3.69 0.83 

Wadan-17 160 135 147.25 25.50 146.15 146.70 1.00 1.20 3.50 0.84 

Pakhtunkhwa-15 159 133 145.92 26.83 144.68 145.30 0.99 1.18 3.70 0.83 

Pirsabak-15 159 132 145.50 27.00 144.25 144.87 0.99 1.17 3.73 0.83 

Pirsabak-13 161 133 146.75 27.50 145.46 146.10 0.99 1.19 3.76 0.83 

Shahkar-13 158 135 146.25 23.50 145.31 145.78 1.00 1.19 3.27 0.85 

Pirsabak-08 160 131 145.42 28.17 144.05 144.73 0.98 1.17 3.88 0.82 

Pirsabak-05 159 134 146.25 24.50 145.22 145.74 1.00 1.18 3.39 0.85 

Insaf 161 138 149.25 23.50 148.32 148.79 1.03 1.23 3.21 0.85 
NIFA-Aman 158 132 144.92 25.83 143.77 144.34 0.99 1.16 3.59 0.84 
NIFA-Lalma 163 135 148.58 28.17 147.25 147.91 1.00 1.22 3.80 0.83 
Borlaug-16 162 136 148.75 25.50 147.66 148.20 1.02 1.22 3.47 0.84 
Zincol-16 160 134 146.92 26.83 145.69 146.30 1.00 1.19 3.68 0.83 
Pakistan-13 161 136 148.33 25.67 147.22 147.78 1.01 1.22 3.50 0.84 
Ujala 161 135 147.92 25.83 146.79 147.35 1.01 1.21 3.53 0.84 
Faisalabad-08 157 135 146.00 22.00 145.17 145.59 1.01 1.18 3.08 0.86 
Fateh Jhang 160 137 148.25 23.50 147.32 147.78 1.02 1.22 3.23 0.85 
Ehsan 161 135 147.50 26.00 146.35 146.93 1.00 1.20 3.56 0.84 
Johar-16 157 132 144.08 25.17 142.98 143.53 0.98 1.15 3.53 0.84 
Gold-16 164 136 149.83 27.67 148.56 149.19 1.02 1.24 3.71 0.83 
Ghaneemat-e-
IBGE 

157 132 144.50 25.00 143.42 143.96 0.99 1.16 3.50 0.84 

KT-2000 161 135 147.92 25.17 146.85 147.38 1.01 1.21 3.44 0.84 
KT-17 162 134 147.75 27.83 146.44 147.09 1.00 1.21 3.78 0.83 
Israr-17 163 133 147.92 29.83 146.41 147.16 0.99 1.21 4.02 0.82 
Shahid-17 158 132 144.75 25.50 143.63 144.19 0.99 1.16 3.56 0.84 
NARC-11 157 130 143.33 26.33 142.12 142.73 0.97 1.14 3.69 0.83 
Amin-10 159 136 147.25 23.50 146.31 146.78 1.01 1.20 3.25 0.85 
Dharabi-11 162 135 148.17 27.33 146.91 147.54 1.00 1.21 3.71 0.83 
Benazir 158 133 145.67 25.33 144.57 145.11 0.99 1.17 3.51 0.84 
Means 159.99 133.91 146.95 26.09 145.79 146.37 1.00 1.19 3.51 0.84 

Note: TOL = Tolerance index. MP = Mean productivity, STI = Stress tolerance index, TSI = Trait stability index, TI = Trait index 

 



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Mean wheat genotypes and their interactions for days to heading ranged from 103 t0 112 days and 91 to 125 

days, respectively Table 3. Average over test environments, the minimum days to heading were counted for 

genotype Shahid-17 (103) days whereas maximum were recorded for genotype Fateh Jhang (112 days). 

Likewise, for genotype by environment interaction, wheat genotype shahid-17 (91 days) revealed minimum 

days to heading while maximum were exhibited by genotype Ehsan (125 days). In general, late planted wheat 

genotypes took minimum days to heading (95 days) as compared to optimum planting (121 days) resulted in a 

decline of 19.4% across both conditions. Wheat genotype Shahid-17 performed far better and out classed all other 

under both environments and their interactions. 

For days to heading data regarding stress selection indices are present in Table 4. In regard of mean 

productivity, most tolerant genotypes were Fateh Jhang (111.58 days),  Ehsan (111.50 days) and KT-2000 (111.00 

days) while least tolerance were observed in genotypes Shahid-17 (103.25 days) and Ghaneemat-e-IBGE(104.42 

days). Minimal favorable TOL index was recoded in genotypes Faisalabd-08 (21.00 days), Johar-16 (21.00 days) and 

Gold-16 (21.50 days) while unfavorable least tolerant genotypes were Israr-17 (30.17 days), Pirsabak-08 (29.50 

days) and PR-119 (29.00 days). In concern with harmonic mean, superior most tolerant genotypes were Gold-16 

(148.56 days), Insaf (148.32 days) and Khaista (147.91 days) while least tolerance were identified in genotypes 

NARC-11(142.12 days), Johar-16 (142.98 days) and Ghanemat-e-IBGE (143.42 days). Based on Geometric mean 

productivity, maximum values were displayed by genotypes Gold-16 (149.19 days), Insaf (148.79 days) and Khaista-

17 (148.54 days) whereas least tolerant genotypes were NARC-11 (142.73 days), Johar-16 (143.53 days) and 

Ghanemat-e-IBGE (143.96 days). Likely, maximum yield index value was observed for most tolerant wheat 

genotypes Borlaug-16, Fateh Jhang and KT-2000 with the same value of (1.04) each, while least tolerant genotypes 

were Shahid-17 (0.96) Pirsabak-08 (0.97) and PR-124 (0.98). Stress tolerance index determines the performance of 

genotypes under both conditions and larger value of STI shows greater stress tolerance and yield potential of 

genotypes. Similarly for stress tolerance index, the most tolerant wheat genotypes were Fateh Jhang (1.36), Ehsan 

(1.35) and KT-2000 (1.35) while less tolerance was observed in genotypes Shahid-17 (1.16) and Ghaneemat-e-IBGE 

(1.19). Stress Susceptibility Index values less than one (< 1) shows that genotypes are most stress tolerant under 

both conditions. In terms of stress susceptibility index, minimum favorable values were calculated for wheat 

genotypes PR-115 (0.96), Faisalabad-08 (3.08) and Insaf (3.21) while maximum unfavorable values were determined 

for least tolerant genotypes Israr-17 (4.02), PR-118 (3.92) and PR-122 (3.89). In terms of yield stability index, the 

top ranked most tolerant wheat genotypes were Faisalabad-08 Johar-16 and Gold-16 with the same value (0.82) 

while least tolerant genotypes were Pirsabak-08 (0.76), Israr-17 (0.76) and PR-119 (0.77). Our findings are in line 

with Poudel and Poudel [17] who disclosed alike results for decline in days to heading under two environments 

through stress selection indices. Due to less availability of water and photosynthetic activities, wheat crop did not 

perform well and thus accelerated days to heading under stressed conditions [18].  Alike findings for days to 

heading under optimum and late sowing was also computed by Ali, et al. [19]. 

 

3.2.2. Grain Yield 

The wheat genotypes varied from 2469 to 3746 kg ha-1 whereas genotype × environment interactions ranged 

from 1596 to 4767 kg ha-1 Table 5. Averaged over, maximum grains were produced by wheat genotype Pakistan-13 

(3746 kg ha-1). However, minimum was obtained from genotype NAARC-11 (2469 kg ha-1). Under test 

environments, normal planting (3888 kg ha-1) environment gave higher gran yield than late sowing (2362 kg ha-1) 

environment.  For genotype environment linkage, maximum grain yield was produced by wheat genotype Israr-17 

(4767 kg ha-1) whereas minimum yield was calculated for genotype Ghaneemat-e-IBGE (1596 kg ha). Wheat 

genotype Israr-17 and Pakistan-13 produced higher grain yield across both test environments and their interactions 

(GEI). 

 



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© 2021 Conscientia Beam. All Rights Reserved. 

Table-4. Mean performance and stress selection indices of wheat genotypes for grain yield evaluated under normal (nonstressed) and late 
(stressed) sown environments. 

Genotypes 
Grain yield 

(kg ha-1) MP TOL HM GMP YI STI SSI YSI 

Normal Late 

PR-114 4395.83 2063.50 3229.67 2332.33 2808.59 3011.78 0.87 1.63 1.35 0.47 

PR-118 4329.17 2695.83 3512.50 1633.33 3322.62 3416.24 1.14 2.09 8.28 0.62 

PR-119 4120.83 2179.17 3150.00 1941.67 2850.79 2996.66 0.92 1.61 10.35 0.53 

PR-122 4183.33 3158.33 3670.83 1025.00 3599.28 3634.88 1.34 2.37 5.38 0.75 

PR-123 4154.17 2525.00 3339.58 1629.17 3140.89 3238.71 1.07 1.88 8.61 0.61 

PR-124 3604.17 2608.33 3106.25 995.83 3026.44 3066.08 1.10 1.68 6.07 0.72 

Paseena-17 4725.00 2212.50 3468.75 2512.50 3013.78 3233.27 0.94 1.87 11.68 0.47 

Khaista-17 3937.50 2700.00 3318.75 1237.50 3203.39 3260.56 1.14 1.91 6.90 0.69 

Wadan-17 3879.17 2450.00 3164.58 1429.17 3003.23 3082.85 1.04 1.70 8.09 0.63 

Pakhtunkhwa-15 3287.50 2333.33 2810.42 954.17 2729.43 2769.63 0.99 1.37 6.37 0.71 

Pirsabak-15 3416.67 2529.17 2972.92 887.50 2906.68 2939.61 1.07 1.55 5.70 0.74 

Pirsabak-13 3333.33 2825.00 3079.17 508.33 3058.19 3068.66 1.20 1.69 3.35 0.85 

Shahkar-13 3358.33 2418.83 2888.58 939.50 2812.19 2850.13 1.02 1.46 6.14 0.72 

Pirsabak-08 4650.00 2637.50 3643.75 2012.50 3365.87 3502.05 1.12 2.20 9.50 0.57 

Pirsabak-05 3708.33 2562.50 3135.42 1145.83 3030.73 3082.63 1.08 1.70 6.79 0.69 

Insaf 3237.50 2141.67 2689.58 1095.83 2577.96 2633.18 0.91 1.24 7.43 0.66 

NIFA-Aman 3562.50 2316.67 2939.58 1245.83 2807.58 2872.83 0.98 1.48 7.68 0.65 

NIFA-Lalma 4733.33 2562.50 3647.92 2170.83 3324.96 3482.70 1.08 2.17 10.07 0.54 

Borlaug-16 4137.50 1966.67 3052.08 2170.83 2666.08 2852.56 0.83 1.46 11.52 0.48 

Zincol-16 4454.17 3029.17 3741.67 1425.00 3605.99 3673.20 1.28 2.42 7.03 0.68 

Pakistan-13 4554.17 2937.50 3745.83 1616.67 3571.40 3657.58 1.24 2.40 7.80 0.65 

Ujala 3512.50 2504.17 3008.33 1008.33 2923.84 2965.79 1.06 1.58 6.30 0.71 

Faisalabad-08 3695.83 2154.17 2925.00 1541.67 2721.86 2821.60 0.91 1.43 9.16 0.58 

Fateh Jhang 3762.50 1783.33 2772.92 1979.17 2419.76 2590.33 0.76 1.20 11.55 0.47 

Ehsan 4216.67 2670.83 3443.75 1545.83 3270.28 3355.89 1.13 2.02 8.05 0.63 

Johar-16 3079.17 1987.50 2533.33 1091.67 2415.73 2473.83 0.84 1.10 7.79 0.65 

Gold-16 4262.50 2348.33 3305.42 1914.17 3028.29 3163.82 0.99 1.79 9.86 0.55 

Ghaneemat-e-
IBGE 

3758.33 1595.83 2677.08 2162.50 2240.38 2449.01 0.68 1.08 12.64 0.42 

KT-2000 3445.83 2177.50 2811.67 1268.33 2668.63 2739.22 0.92 1.34 8.08 0.63 

KT-17 4162.50 2716.67 3439.58 1445.83 3287.64 3362.76 1.15 2.03 7.63 0.65 

Israr-17 4766.67 2357.67 3562.17 2409.00 3154.88 3352.34 1.00 2.01 11.10 0.49 

Shahid-17 3283.33 2116.67 2700.00 1166.67 2573.97 2636.23 0.90 1.25 7.80 0.64 

NARC-11 3166.67 1770.83 2468.75 1395.83 2271.45 2368.05 0.75 1.01 9.68 0.56 

Amin-10 3862.50 2033.67 2948.08 1828.83 2664.46 2802.68 0.86 1.41 10.40 0.53 

Dharabi-11 3400.00 1825.00 2612.50 1575.00 2375.12 2490.98 0.77 1.11 10.17 0.54 

Benazir 3841.67 2137.50 2989.58 1704.17 2746.72 2865.58 0.90 1.47 9.74 0.56 

Means 3888.31 2362.02 3125.17 1526.29 2921.92 3021.22 1.00 1.66 8.22 0.61 

Note: TOL = Tolerance index. MP = Mean productivity, STI = Stress tolerance index, TSI = Trait stability index, TI = Trait index 

 

For grain yield data regarding stress selection indices are present in Table 4. In regard of mean productivity, 

most tolerant genotypes were Pakistan-13 (3745.83 kg ha-1), Zincol-16 (93741.67 kg ha-1) and PR-122 (3670.83 kg 

ha-1) while least tolerance was observed in genotypes NARC-11 (2468.75 kg ha-1), Johar-16 (2533.33 kg ha-1) and 



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© 2021 Conscientia Beam. All Rights Reserved. 

Dharabi-11 (2612.50 kg ha-1). Minimal favorable TOL index was recoded in genotypes Pirsabak-13 (508.33 kg ha-1), 

Pirsabak-15(887.50 kg ha-1) and Pakhtunkha-15 (954.17 kg ha-1) while unfavorable least tolerance was indicated by 

genotypes Paseena-17 (2512.50 kg ha-1), Israr-17 (2332.33 kg ha-1) and PR-114 (2409.00 kg ha-1). In concern with 

harmonic mean, superior most tolerant genotypes were Zincol-16 (3605.99 kg ha-1), PR-122 (3599.28 kg ha-1) and 

Pakistan-13 (3571.40 kg ha-1) while least tolerance was identified in genotypes Ghaneemat-e-IBGE (2240.38 kg ha-

1), NARC-11 (2271.45 kg ha-1) and Dharbi-11 (2375.12 kg ha-1). Based on Geometric mean productivity, maximum 

values were displayed by genotypes Zincol-16 (3673.20 kg ha-1), Pakistan-13 (3657.58 kg ha-1) and PR-122 (3834.88 

kg ha-1) whereas least tolerant genotypes were NARC-11(2368.05 kg ha-1), Ghaneemat-e-IBGE (2449.01 kg ha-1) 

and Dharbi-11(2490.98 kg ha-1). Likely, maximum yield index value was observed for most tolerant wheat 

genotypes PR-122 (1.34), Zincol-16 (1.28) and Pakistan-13 (1.24) while less tolerance was recorded in genotypes 

Ghaneemat-e-IBGE (0.68), NARC-11 (0.75) and Fateh Jhang (0.76). Similarly for stress tolerance index, the most 

tolerant wheat genotypes were Pakistan-13 (2.42), Zincol-16 (2.40) and PR-122 (2.37) whereas least tolerant 

genotypes were NARC-11 (1.01), Ghaneema-e-IBGE (1.08) and Johar-16 (1.10). Stress Susceptibility index values 

less than one (< 1) shows that genotypes are most stress tolerant under both conditions. In terms of stress 

susceptibility index, minimum favorable values were calculated for wheat genotypes PR-115 (1.35), Pirsabak-13 

(3.35) and PR-122(5.38) while maximum unfavorable values were determined for least tolerant genotypes 

Ghaneemat-e-IBGE (12.64), Paseena-17 (11.68) and Borlug-16 (11.52). Stress tolerance index determines the 

performance of genotypes under both conditions and larger value of STI shows greater stress tolerance and yield 

potential of genotypes. In terms of yield stability index, the top ranked most tolerant wheat genotypes were 

Pirsabak-13 (0.85), PR-122 (0.75) and Pirsabak-15 (0.74) while least tolerant genotypes were Ghaneemat-e-IBGE 

(0.42), Fateh Jhang (0.47) and Paseena-17 (0.47).  Similar investigations regarding reduction in grain yield and 

stress selection indices under normal and late plating was also recorded by Ishaq, et al. [20]. Reduced grain yield 

under stressed conditions due to low photosynthetic activities and lesser water availability was concluded by 

Schmidt, et al. [21]. Our results are also in conformation with Khalil, et al. [22] who recorded reduced grain yield 

in wheat genotypes under stressed environments.   

 

3.3. Correlation Analysis 

 For optimum planting, days to heading revealed significant positive association with MP (r=0.875**), TOL 

(r=0.608**), HM (r=0.826**), GM (r=0.851**), YI (r=0.471**), STI (r=0.860**) and correlation was significant 

negative with TSI (r= -0.509**). Likewise under late planting, days to heading disclosed significant positive 

correlation with MP (r= 0.847**), HM (r=0.892**), GM (r=0.871**), YI (r=0.951**), STI (r=0.852**), YSI 

(r=0.432**) and significant negative with TOL (r= -0.357*) Table 5.  

 

Table-5. Correlation coefficient for days to heading and grain yield in wheat genotypes evaluated under normal (non-stressed) and late (stressed) 
sown conditions. 

Selection indices 
Days to heading Grain yield 

Normal Late Normal Late 

MP 0.875** 0.847** 0.883** 0.774** 
TOL 0.608** -0.357* 0.722** -0.360* 
HM 0.826** 0.892** 0.686** 0.934** 
GMP 0.851** 0.871** 0.791** 0.869** 
TI 0.471** 0.951** 0.385* 0.999** 
STI  0.860** 0.852** 0.790** 0.866** 
SSI 0.222ns -0.292ns 0.249ns -0.500** 
TSI -0.509** 0.432** -0.419* 0.669** 

Note: *, ** = Significant at 5% and 1% level of probability, respectively, NS = Non-Significant. 

 

For optimum planting, grain yield depicted significant positive relation with MP (r=0.883**), TOL (r=0.722**), 

HM (r=0.686**), GM (r=0.791**), YI (r=0.385*), STI (r=0.790**) and significant negative correlation with YSI (r=-



Current Research in Agricultural Sciences, 2021, 8(1): 37-46 

 

 
44 

© 2021 Conscientia Beam. All Rights Reserved. 

0.419*). Similarly under late planting, grain yield indicated significant positive association with MP (r=0.774**), 

HM (r=0.934**), GM (r=0.869**), YI (r=0.999**), STI (r=0.866**), YSI (r=0.669**) and significant negative 

relationship with TOL (r=-0.360*) and SSI (r=-0.500**). Similar findings were also disclosed by Dwivedi, et al. [23] 

for grain yield. Significant positive association of grain yield with different parameters was also reported by 

Khairnar and Bagwan [24]; Siddhi, et al. [25]. 

 

4. CONCLUSIONS AND RECOMMENDATIONS 

Analysis of variance revealed significant divergence among the tested genotypes under both planting 

environments (non-stressed and stressed) suggesting that these genotypes were having broader genetic base. Best 

genotypes in concern with grain yield were Pakistan-13, Zincol-16 and PR-122 under optimum and delayed planting. 

Decline in days to heading and grain yield was recorded when planting was delayed as compared to timely (non-

stressed) planting. Stress selection indices are found adequate tools for identification of desirable high yielding stable 

genotypes across both normal and stressed planting conditions. According to stress selection indices, high yielding 

stable and stress tolerant genotypes were i-e Zincol-16, Pirsabak-13, PR-122 Pakistan-13 that could be sown in both 

optimum and late planting conditions. Under both test environments (non-stress and stressed), positive significant 

association of days to heading and grain yield with stress selection indices i-e GM, HM MP, YI and STI disclosed 

that these indices are more effective in determination of genotypes under various environments (non-stress and 

stressed).   

 

Funding: This study received no specific financial support.    
Competing Interests: The authors declare that they have no competing interests.  
Acknowledgement: All the authors of this study are very thankful to CCRI (Cereal Crops 
Research Institute-Nowshera) and CIMMYT (International Maize and Wheat Improvement 
Centre-México) for the provision of genetic material, conduction of the experiment and full 
support throughout. 

 

REFERENCES 

[1] S. W. Van Es, "Too hot to handle, the adverse effect of heat stress on crop yield," Physiologia Plantarum, vol. 169 (4), 

pp. 499-500, 2020. Available at: https://doi.org/10.1111/ppl.13165. 

[2] T. Hura, "Wheat and Barley: Acclimatization to abiotic and biotic stress," International Journal of Molecular Science, vol. 

21 (7) pp. 21 ‒ 19, 2020. Available at: https://doi:10.3390/ijms21197423. 

[3] A. E. Habti, D. Fleury, N. Jewell, T. Garnett, and P. J. Tricker, "Tolerance of combine drought and heat stress is 

associated with transpiration and water soluble carbohydrates in wheat grains," Frontier Plant Science, vol. 11 (5), pp. 2-

9, 2020. Available at: https://doi: 10.3389/fpls.2020.568693 

[4] P. K. Singh, S. Prasad, A. K. Verma, B. Lal, R. Singh, S. P. Singh, and D. K. Dwivedi, "Screening for heat tolerant traits 

in wheat (Triticum aestivum L.) genotypes by physio-biochemical markers," International Journal Current Microbiology 

and Applied Science, vol. 9 (2), p. 2335 ‒ 2343, 2020. Available at: https://doi.org/10.20546/ijcmas.2020.902.265. 

[5] M. Janni, M. Gullì, E. Maestri, M. Marmiroli, B. Valliyodan, H. T. Nguyen, and N. Marmiroli, "Molecular and genetic 

bases of heat stress responses in crop plants and breeding for increased resilience and productivity," Journal of 

Experimental Botany, vol. 71 (13), pp. 3780-3802, 2020. Available at: https://doi:10.1093/jxb/eraa034. 

[6] S. A. Khan and G. Hassan, "Heritability and correlation studies of yield and yield related traits in bread wheat," Sarhad 

Journal of Agriculture, vol. 33 (1), pp. 103-107, 2017. 

[7] R. K. Bhardwaj, S. S. Gautam, and R. R. Saxena, "Adaptation of G × E interaction of wheat genotypes in chhattisgarh 

state through regression analysis," International Journal of Current Microbiology and Applied Science, vol. 7 (2), p. 4598 ‒ 

4604, 2018. 

[8] K.A. Gomez and A.A. Gomez. Statistical procedures for Agricultural Research. Canada: John Wiley and Sons Inc. pp: 20-

30, 1984. 



Current Research in Agricultural Sciences, 2021, 8(1): 37-46 

 

 
45 

© 2021 Conscientia Beam. All Rights Reserved. 

[9] A. Hossain, R. Sears, T. S. Cox, and G. Paulsen, "Desiccation tolerance and its relationship to assimilate partitioning in 

winter wheat," Crop Science, vol. 30 (2), pp. 622-627, 1990. 

[10] K. A. Schneider, R. Rosales‐Serna, F. Ibarra‐Perez, B. Cazares‐Enriquez, J. A. Acosta‐Gallegos, P. Ramirez‐Vallejo, N. 

Wassimi, and J. D. Kelly, "Improving common bean performance under drought stress," Crop Science, vol. 37 (3), pp. 

43-50, 1997. 

[11] G. C. J. Fernandez, "Effective selection criteria for assessing plant stress tolerance. In Proceedings of the international symposium 

on adaptation of vegetable and other food crops in temperature and water stress". Tainan, Taiwan: AVRDC Publication, 1992. 

[12] P. Gavuzzi, F. Rizza, M. Palumbo, R. Campanile, G. Ricciardi, and B. Borghi, "Evaluation of field and laboratory 

predictors of drought and heat tolerance in winter cereals," Canadian Journal of Plant Science, vol. 77(3), pp. 523-531, 

1997. 

[13] M. Bouslama and W. Schapaugh Jr, "Stress tolerance in soybeans. I. Evaluation of three screening techniques for heat 

and drought tolerance," Crop Science, vol. 24 (2), pp. 933-937, 1984. 

[14] M. R. Poudel, S. Ghimire, M. P. Pandey, K. H. Dhakal, D. B. Thapa, and H. K. Poudel, "Evaluation of wheat genotypes 

under irrigated, heat stress and drought conditions," Journal of Biological Today's World, vol. 9 (1), pp. 212, 2020. 

[15] A. Mehraban, A. Tobe, A. Gholipouri, E. Amiri, A. Ghafari, and M. Rostaii, "Evaluation of drought tolerance indices 

and yield stability of wheat cultivars to drought stress in different growth stage," World Journal of Environmental 

Bioscience, vol. 7 (1), pp. 8 ‒ 14, 2018. 

[16] B. Jaiswal, S. Prasad, R. Rani, S. Singh, A. Kumar, A. Kumar, and R. K. Yadav, "Evaluation of wheat (T. aestivum l.) 

lines at reproductive stage for heat stress tolerance," International Journal of Current Microbiology and Applied Science, 

vol. 7 (3), pp. 1350  ‒ 1357, 2018. 

[17] P. B. Poudel and M. R. Poudel, "A Review of Heat stress effects and tolerance in Wheat," Journal of Biology and Today's 

World, vol. 9 (4), pp. 1-6, 2020. Availaable at: https://doi:10.35248/2322-3308.20.09.217. 

[18] S. Schittenhelm, T. Langkamp‐Wedde, M. Kraft, L. Kottmann, and K. Matschiner, "Effect of two-week heat stress 

during grain filling on stem reserves, senescence, and grain yield of European winter wheat cultivars," Journal of 

Agronomy and Crop Science, vol. 206 (1), pp. 722-733, 2020. Available at: https: //doi:10.1111/jac.12410. 

[19] A. Ali, Z. Ullah, N. Ali, and M. M. Anjum, "Evaluation of wheat advanced lines for agronomic traits under vary sowing 

dates," Journal of Agriculture Research and Technology, vol. 7 (1), p. 1 ‒ 12, 2017. 

[20] M. Ishaq, G. Ahmad, K. Afridi, M. Ali, T. U. Khan, I. A. Shah, M. Khalid, N. Ahmad, B. Iqbal, B. Ahmad, M. A. 

Qureshi, A. Saleem, M. Miraj, and K. Din, "Assessment of genetic potential and stress selection indices for important 

yield related traits in bread wheat (T. aestivum L.)," Pure and Applied Biology, vol. 35 (5), pp. 22 ‒ 38, 2018. Available 

at: http://dx.doi.org/10.19045/bspab.2018.700129. 

[21] J. Schmidt, J. Claussen, N. Worlein, A. Eggert, D. Fleury, T. Garnett, and S. Gerth, "Drought and heat stress tolerance 

screening in wheat using computed tomography," Plant Methods, vol. 16 (15), p. 2 ‒ 7, 2020. Available at: 

https://doi.org/10.1186/s13007-020-00565-w. 

[22] I. H. Khalil, A. Wahab, D. Nayab, S. S. Ghani, M. Alam, Z. Ullah, and W. U. Khan, "Heritability and selection response 

for morphological and yield traits in normal and late planted wheat," International Journal of Agriculture and 

Environmental Research, vol. 2 (4), pp. 202 ‒ 211, 2017. 

[23] R. Dwivedi, S. Prasad, B. Jaiswal, A. Kumar, A. Tiwari, S. Patel, G. Pandey, and G. Pandey, "Evaluation of wheat 

genotypes (Triticum aestivum L.) at grain filling stage for heat tolerance," International Journal of Pure & Applied 

Bioscience, vol. 5  (2), pp. 971-975, 2017. 

[24] S. Khairnar and J. Bagwan, "Studies on genetic variability parameters and character association in bread wheat 

(Triticum aestivum L.) under timely and late sown environments of irrigated condition," Electronic Journal of Plant 

Breeding, vol. 9 (1), pp. 190-198, 2018. 

[25] S. Siddhi, J. B. Patel, and N. Patel, "Stability analysis in bread wheat (T. aestivum L.)," Journal of Pharmacology and 

Phytochemistry, vol. 7 (4), pp. 290-297, 2018. 



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Table-1. Detail of wheat advance lines of CCRI and cultivars used in the study. 

S.No.  Cultivars Institution/ 
Sources 

S.No. Cultivars Institution/ 
Sources 

1 PR-114 CCRI, Pirsabak 19 Borlaug-16 NARC, Islamabad 
2 PR-118 CCRI, Pirsabak 20 Zincol-16 NARC, Islamabad 
3 PR-119 CCRI, Pirsabak 21 Pakistan-13 NARC, Islamabad 
4 PR-122 CCRI, Pirsabak 22 Ujala AARI, Faisalabad 
5 PR-123 CCRI, Pirsabak 23 Faisalabad-08 AARI, Faisalabad 
6 PR-124 CCRI, Pirsabak 24 Fateh Jhang BARI, Chakwal 
7 Paseena-17 CCRI, Pirsabak 25 Ehsan AARI, Faisalabad 
8 Khaista-17 CCRI, Pirsabak 26 Johar-16 AARI, Faisalabad 
9 Wadan-17 CCRI, Pirsabak 27 Gold-16 AARI, Faisalabad 
10 Pakhtunkhwa-15 CCRI, Pirsabak 28 Ghaneemat-e-IBGE AUP, Peshawar 
11 Pirsabak-15 CCRI, Pirsabak 29 KT-2000 BARS, Kohat 
12 Pirsabak-13 CCRI, Pirsabak 30 KT-17 BARS, Kohat 
13 Shahkar-13 CCRI, Pirsabak 31 Israr-17 ARI, D.I.Khan 
14 Pisabak-08 CCRI, Pirsabak 32 Shahid-17 ARI, D.I.Khan 
15 Pirsabak-05 CCRI, Pirsabak 33 NARC-11 NARC, Islamabad 
16 Insaf NIFA, Peshawar 34 Amin-10 ARS S. Naurang 
17 NIFA-Aman NIFA, Peshawar 35 Dharabi-11 BARI Chakwal 
18 NIFA-Lalma NIFA, Peshawar 36 Benazir ARI. Tandojam 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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