Abstract
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.
Keywords: Climate research unit (CRU), Sea surface temperature (SST) , South Asia, National centers for environmental prediction (NCEP), Extreme climate, Climate change.
Received: 18 January 2021 / Revised: 22 February 2021 / Accepted: 24 March 2021/ Published: 12 April 2021
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].
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 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.
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.
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
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).
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 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=-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. |
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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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