Variability studies for yield and its components under heat stress condition in wheat [Triticum aestivum (L.)]

Introduction

Wheat (Triticum aestivum L.) is one of the most extensively cultivated cereal crops worldwide and serves as a primary staple food for a significant portion of the global population. Its adaptability across diverse agro-climatic zones has made it a cornerstone of food security, contributing substantially to caloric and protein intake in both developed and developing nations (Curtis et al., 2002; Shiferaw et al., 2013) [1,2] . Beyond its role in human nutrition, wheat also underpins rural livelihoods, agricultural economies, and international trade, making its sustained production a critical priority in the face of increasing global food demand. The rapid growth of the global population, projected to exceed 9 billion by mid-century, is expected to drive wheat demand to unprecedented levels (Ray et al., 2013) [3] . Meeting this demand is challenging, as climate variability increasingly threatens production stability. Among the abiotic stresses affecting wheat, terminal heat stress -characterized by exposure to elevated temperatures during reproductive and grain-filling stages -poses a particularly serious constraint. Even moderate rises in temperature can shorten developmental phases, impair photosynthesis, reduce grain filling duration, and ultimately depress yields (Wardlaw et al., 1989; Farooq et al., 2011) [4,5] . Previous estimates suggest that each 1 °C increase during sensitive stages can result in yield losses of 4-6%, highlighting the urgency of developing cultivars capable of maintaining performance under warming environments (Asseng et al., 2015) [6] . The impact of heat stress on wheat is multifaceted. Physiological processes such as chlorophyll stability, canopy temperature regulation, and efficiency of photosystem II are adversely affected, which translates into reduced biomass accumulation and lower grain weight (Reynolds et al., 2009; Wahid et al., 2007) [7,8] . At the morphological level, traits including plant height, spike length, tiller number, and grain number per spike may also be compromised. Importantly, the extent of yield reduction is not uniform across genotypes, indicating the presence of exploitable genetic variability for stress tolerance (Joshi et al., 2007) [9] . Identifying and utilizing such variability is essential for developing cultivars that can sustain productivity under latesown or high-temperature conditions. Genetic improvement of wheat for heat tolerance relies on understanding the heritable variation in both yield-attributing traits and stress-responsive physiological characteristics. Traits such as canopy temperature depression, chlorophyll content, normalized difference vegetation index (NDVI), and chlorophyll fluorescence have proven useful as indirect selection criteria because they provide insight into the plant's ability to withstand heat while maintaining productivity (Pinto & Reynolds, 2015) [10] . Similarly, grain filling rate and duration are critical determinants of final yield under stress, as they directly influence grain weight and biomass partitioning (Dias & Lidon, 2009) [11] . The effectiveness of selection for these traits depends on their variability, heritability, and the nature of gene action involved. High heritability coupled with high genetic advance is particularly desirable, as it reflects additive genetic effects that can be directly exploited in breeding programs (Falconer & Mackay, 1996) [12] . Despite considerable progress in wheat breeding, the pace of yield gain is insufficient to counterbalance the negative impacts of climate change (Ray et al., 2013) [3] . Strengthening breeding strategies with a focus on stress-adaptive traits offers a sustainable pathway for enhancing resilience. Therefore, assessing genetic variability and identifying reliable selection indices under heat-stressed environments remain essential steps toward breeding high-yielding and climate-resilient wheat cultivars.

Materials and Methods

Experimental material

Sixty diverse genotypes of wheat were used in this experiment. The genotypes 1 to 57 were procured from Borlaug Institute for South Asia (BISA), Ludhiana, India. The check variety HD 2931 and DBW 222 procured from IARI, New Delhi and the check variety LOK 1 was procured from Wheat Research Station, Bardoli, Navsari Agricultural University, Gujarat, India and, India. The sixty genotypes studied in this investigation are listed in Table 1.

Experimental location

The study was conducted at the College Farm of N. M. College of Agriculture, Navsari Agricultural University, Navsari. The experimental site is located at 20°37′ N latitude and 72°54′ E longitude, with an elevation of about 11.98 m above mean sea level. This location falls within the "South Gujarat Heavy Rainfall Zone (AEZ III)." The soil of the site is characterized as medium black cotton soil and is classified under the order Inceptisols according to soil taxonomy. It has medium to poor drainage conditions, with a pH ranging from 7.5 to 7.8, and is considered fairly suitable for wheat cultivation.

Experimental detail

The field trial was conducted with two different sowing dates: 17 December 2024 (E1) and 5 January 2024 (E2). In both cases, the crop was exposed to heat stress, with the later sowing experiencing comparatively stronger terminal heat stress. The climatic conditions during the crop growth period were typical of the respective sowing months. The experiment was laid out in a Randomized Block Design (RBD) with two replications. A total of sixty genotypes were planted in paired rows of 3 m length, maintaining a row spacing of 20 cm in both sowings. Recommended agronomic practices were followed uniformly across treatments.

Parameters studies

Observations were recorded for traits such as days to heading, days to anthesis, days to maturity, plant height (cm), number of effective tillers per plant, spike length (cm), grains per spike, 1000-grain weight (g), grain yield per plant (g), biological yield per plant (g), harvest index (%), grain filling duration, and grain filling rate across both seasons. In the second sowing date (E2), additional physiological parameters were measured, which included canopy temperature depression (°C) at anthesis and 15 days after anthesis, chlorophyll content index at anthesis and 15 days after anthesis, chlorophyll fluorescence index at anthesis and 15 days after anthesis, as well as normalized difference vegetation index (NDVI) at anthesis and 15 days after anthesis. The collected data were subjected to analysis of variance (ANOVA) and further used to assess mean performance and estimate genetic variability parameters such as PCV, GCV, heritability, and genetic advance.

Results and Discussion

Mean performance under December and January sown condition Analysis of variance (ANOVA) showed significant differences among genotypes for most of the studied traits under both sowing environments, indicating the presence of substantial genetic variability. Such variability forms the basis for selection and improvement under heat stress conditions. Sixty wheat genotypes were evaluated under two late-sowing environments: December (E1) and January (E2). Significant variation was observed among genotypes for phenological, morphological, yield, and physiological traits, indicating substantial genetic diversity.

In wheat breeding programs aimed at developing heat-tolerant varieties with higher yield potential, understanding genotypic performance under stress conditions is essential. The present study highlighted the impact of terminal heat stress on phenology, growth, yield, and physiological traits across sixty wheat genotypes under two late-sown environments: December (E1) and January (E2 Notably, some genotypes maintained relatively higher yield and physiological performance under stress. GS\2022-23\8040, HTWYT\2022-23\45, and 13HZW\2022-23\433 showed superior grain yield, extended grain filling duration, and higher NDVI and CCI under E2, indicating better heat tolerance. These genotypes completed photosynthetic activity efficiently during grain filling, allowing better assimilate accumulation despite heat stress.

Genetic Variability

The analysis of genetic variability among sixty wheat genotypes under late-sown heat stress conditions revealed significant differences in the extent of genotypic (GCV) and phenotypic (PCV) variation for various traits. Both sowing environments (E1 and E2) exhibited a reduction in the magnitude of genetic variability under higher terminal heat stress, reflecting the environmental influence on trait expression. Phenological traits such as days to heading, days to anthesis, and days to maturity exhibited relatively low GCV and PCV across both environments, indicating that these traits are largely influenced by genetic makeup with minimal environmental interference. For example, DH in E1 showed a GCV of 8 [13, 14. 15, 16, 17] . Morphological traits including plant height, spike length, and effective tillers per plant displayed low to moderate variability. Plant height recorded GCV of 3.01% and PCV of 6.39% in E1, which slightly increased to 3.69% and 6.73% in E2. Spike length showed a GCV of 4.24% (E1) and 4.57% (E2), while effective tillers per plant exhibited moderate variation with GCV ranging from 7.63% to 8.95% and PCV from 11.15% to 12.86%. This suggests that while heat stress reduces overall plant stature, there remains some genotypic differentiation that can be exploited for breeding. Similar finding were observed by (Kumar et [25,21,26,27] . Physiological traits measured under the more stressful E2 environment revealed relatively higher variability, highlighting the adaptive potential among genotypes. Canopy temperature depression (CTD) showed a GCV of [28] for days to heading and by Patel et al. (2022) [29] for day to anthesis.

Similarly, days to maturity (DM) showed high heritability (83.68%) but low GAM (9.1%), indicating environmental influence. These findings are confirmed with the result of Bhatt et al. (2023) [30] . In January, DH, DA, and DM showed slightly lower heritability (79.09%, 76.31%, and 57.52%, respectively) and low GAM (7.29%, 7.26%, and 3.93%), reflecting moderate environmental impact, which limits selection efficiency for these traits.

Plant height (PH) was strongly influenced by the environment, with low heritability (22.09%) and low GAM (2.91%) in December, and moderate heritability (30.01%) with low GAM (4.16%) in January, indicating limited response to selection. Effective tillers per plant (ET) showed moderate heritability (48.42% in December and 46.79% in January) and moderate GAM (12.83% and 10.75%), suggesting potential for improvement through selection. Tomar et al (2019) [21] , Shehrawat et al. (2021) [26] and Sharadhi et al. (2023) [31] obtained similar results. Spike length (SL) had moderate to low heritability (33.20% in December and 29.81% in January) with low GAM (5.03% and 5.14%), reflecting limited scope for selection. Grains per spike (GS) exhibited high heritability (63.86%) and moderate GAM (13.45%) in December is confirmed with the findings of Azimi et al. (2017) [13] , while low heritability (29.85%) and low GAM (4.47%) in January, highlighting strong environmental effects under severe heat stress.

For yield-related traits, 1000-grain weight (TGW) showed moderate heritability (50.45%) and low GAM (7.03%) in December, while in January heritability was high (70.67%) with low GAM (8.64%), indicating predominance of non-additive gene action with limited selection potential. Biological yield (BY) exhibited moderate heritability (48.2%) and moderate GAM (18.44%) in December, whereas in January both heritability (79.92%) and GAM (34.09%) were high, suggesting additive gene action and significant scope for improvement.

Harvest index (HI) had moderate heritability in both periods (31.97% in December and 38.74% in January) with low to moderate GAM (9.41% and 15.81%), indicating partial environmental influence. Grain yield (GY) showed moderate heritability (49.78% in December and 57.97% in January) coupled with high GAM (20.07% and 20.79%), demonstrating substantial potential for genetic improvement even under heat stress. These results are in agreement with (Sapi et al. 2017 and Lamara et al. 2022) [14,32] . Physiological traits reflected varying responses. Grain filling duration (GFD) had moderate heritability (30.02% in December and 30.66% in January) with low GAM (4.13% and 3.51%), indicating non-additive control. The result was match up with the findings of Jain et al. (2017) [33] and Alemu et al. (2020) [34] .

In contrast, grain filling rate (GFR) displayed high heritability (64.15%) and high GAM (25.96%) in December, and moderate heritability (55.39%) with high GAM (20.64%) in January, highlighting additive gene action and good selection response. Similar findings for this character were also reported by Islam et al. (2017) [25] . Canopy temperature depression (CTD) showed very high heritability both at anthesis (96.47%) and 15 days after anthesis (98.04%) with high GAM (42.23% and 79.17%), reflecting strong genetic control and minimal environmental influence. The present results are in agreement with Patel et al. (2022) [29] .

Conclusion

The present study revealed substantial genetic variability among sixty wheat genotypes under late-sown heat stress conditions, with significant reductions observed in most phenological, morphological, yield, and physiological traits under higher temperature stress. Traits such as days to heading, anthesis, maturity, plant height, spike length, grains per spike, 1000-grain weight, grain yield, and biological yield were notably affected, reflecting accelerated crop development and restricted assimilate accumulation under terminal heat. Despite this, certain genotypes maintained higher yield and physiological performance, indicating inherent heat tolerance. Analysis of heritability and genetic advance showed that traits including grain filling rate, canopy temperature depression, biological yield, and NDVI at 15 days after anthesis exhibited high heritability coupled with moderate to high genetic advance, suggesting predominant additive gene action and considerable potential for direct selection. In contrast, plant height, spike length, early-stage chlorophyll content, and chlorophyll fluorescence were strongly influenced by the environment, limiting the effectiveness of phenotypic selection. Overall, the study identifies key traits and promising genotypes that can be exploited in wheat breeding programs aimed at enhancing heat tolerance, yield stability, and physiological resilience under terminal heat stress conditions.

Acknowledgement

AcknowledgementsThe authors acknowledge NAU, Navsari for providing experimental land and other necessary facilities for conducting the experiment. We appreciate the facilities, resources, and research assistance provided by the Department of Genetics and Plant Breeding, N.M. College of Agriculture, NMCA, NAU, Navsari. We extend our gratitude to all parties who supported this study and contributed to the preparation of this article.

References

1. Curtis BC, Rajaram S, Macpherson HG. Bread wheat: improvement and production. FAO Plant Production and Protection Series No. 30. Rome: FAO; 2002. p. 12-15.
2. Shiferaw B. Crops that feed the world 10. Past successes and future challenges to the role played by wheat in global food security. Food Secur. 2013;5:291-317.
3. Ray DK, Mueller ND, West PC, Foley JA. Yield trends are insufficient to double global crop production by 2050. PLoS One. 2013;8(6):e66428.
4. Wardlaw I, Dawson I, Munibi P, Fewster R. The tolerance of wheat to high temperatures during reproductive growth. I. Survey procedures and general response patterns. Aust J Agric Res. 1989;40(1):1-13.
5. Farooq M, Bramley H, Palta JA, Siddique KHM. Heat stress in wheat during reproductive and grain-filling phases. Crit Rev Plant Sci. 2011;30(6):491-507.
6. Asseng S, Ewert F, Martre P, Rötter RP, Lobell DB, Cammarano D. Rising temperatures reduce global wheat production. Nat Clim Change. 2015;5:143-147.
7. Reynolds M, Foulkes MJ, Slafer GA, Berry P, Parry MA, Snape JW, et al. Raising yield potential in wheat. J Exp Bot. 2009;60(7):1899-1918.
8. Wahid A, Gelani S, Ashraf M, Foolad MR. Heat tolerance in plants: an overview. Environ Exp Bot. 2007;61(3):199223.
9. Joshi AK, Mishra B, Chatrath R, Ferrara GO, Singh RP. Wheat improvement in India: present status, emerging challenges and future prospects. Euphytica. 2007;157:431446.
10. Pinto RS, Reynolds MP. Common genetic basis for canopy temperature depression under heat and drought stress associated with optimized root distribution in bread wheat. Theor Appl Genet. 2015;128:575-585.
11. Dias AS, Lidon FC. Evaluation of grain filling rate and duration in bread and durum wheat under heat stress after anthesis. J Agron Crop Sci. 2009;195(2):137-147.
12. Falconer DS, Mackay TFC. Introduction to quantitative genetics. 4th ed. Harlow: Longman; 1996.
13. Azimi AM, Marker S, Bhattacharjee I. Genotypic and phenotypic variability and correlation analysis for yield and its components in late sown wheat (Triticum aestivum L.). J Pharmacogn Phytochem. 2017;6(4):167-173.
14. Sapi S, Marker S, Bhattacharjee I. Correlation and path coefficient analysis of some quantitative traits in bread wheat. J Pharmacogn Phytochem. 2017;6(4):258-262.
15. Neeru B, Panwar IS, Singh V. Genetic parameters of variability and path analysis in wheat under timely and late sown conditions. Int J Curr Microbiol Appl Sci. 2017;6(7):1914-1920.
16. Bhanu AN, Arun B, Mishra VK. Genetic variability, heritability and correlation study of physiological and yield traits in relation to heat tolerance in wheat (Triticum aestivum L.). Biomed J Sci Tech Res. 2018;2(1):2112-2116.
17. Chandramaniya CP, Kale B, Bhattacharya S, Patel DS, Makwana DV. Genetic architecture for heat tolerance in bread wheat (Triticum aestivum L.). Plant Arch. 2025;25(1):128-135.
18. Kumar J, Kumar M, Kumar A, Singh SK, Singh L. Estimation of genetic variability and heritability in bread wheat under abiotic stress. Indian J Pure Appl Biosci. 2017;5(1):156-163.
19. Meles B, Mohammed W, Tsehaye Y. Genetic variability, correlation and path analysis of yield and grain quality traits in bread wheat (Triticum aestivum L.) genotypes at Axum, Northern Ethiopia. J Plant Breed Crop Sci. 2017;9(10):175185.
20. Raaj N, Singh SK, Kumar A, Kumar A. Assessment of variability parameters in wheat in relation to terminal heat tolerance. J Pharmacogn Phytochem. 2018;7(6):2155-2160.
21. Tomar P, Chand P, Maurya BK, Singh SK, Singh R, Kumar P, Yadav MK. Estimation of variability and genetic parameters for yield and quality traits in spring wheat (Triticum aestivum L.). J Pharmacogn Phytochem. 2019;8(4):2006-2009.
22. Kanwar A, Agrawal AP, Sharma DJ, Agrawal HP. Genetic parameters of variation and correlation analysis in wheat under terminal heat stress. J Pharmacogn Phytochem. 2020;9(5):1795-1798.
23. Poudel MR, Poudel PB, Puri RR, Paudel HK. Variability, correlation and path coefficient analysis for agromorphological traits in wheat genotypes (Triticum aestivum L.) under normal and heat stress conditions. Int J Appl Sci Biotechnol. 2021;9(1):65-74.
24. Poonia MK, Kumar A, Kumar V, Bhanu AN, Kumar S. Genetic variability and character association analysis for seed yield and its attributes in wheat (Triticum aestivum L.). Int J Plant Soil Sci. 2023;35(9):123-131.
25. Islam AU, Chhabra AK, Dhanda SS, Peerzada OH. Genetic diversity, heritability and correlation studies for yield and its components in bread wheat under heat stress conditions. J Agric Vet Sci. 2017;12(1):71-77.
26. Shehrawat S, Kumar Y. Genetic architecture of morphophysiological traits in wheat accessions under terminal heat stress. Ekin J Crop Breed Genet. 2021;7(1):34-42.
27. Singh V, Mishra A, Sharma G, Ahalawat S, Singh RK. Correlation and path coefficient analysis for yield and its attributing traits in wheat (Triticum aestivum L.) genotypes. Int J Environ Clim Change. 2024;13(8):1944-1951.
28. Zewdu D, Mekonnen F, Geleta N, Abebe K. Genetic variability, heritability and genetic advance for yield and yield related traits of bread wheat (Triticum aestivum L.) genotypes. Int J Econ Plants. 2024;11(1):38-47.
29. Patel NS, Patel JB, Raval LJ. Genetic variability study in bread wheat (Triticum aestivum L.) under normal and late sown conditions. Biol Forum Int J. 2022;14(2):948-954.
30. Bhatt B, Jaiswal JP, Khan R, Joshi S, Chaudhary D. Assessment of genetic variability for morpho-physiological and yield traits in bread wheat (Triticum aestivum L.). Int J Environ Clim Change. 2023;13(11):2283-2291.
31. Sharadhi GP, Avinashe H, Dubey N, Danalakoti K, Ghosh S, Sachan S, et al. Correlation and path analyses in F₄ segregating populations of bread wheat for grain yield and its attributes. SABRAO J Breed Genet. 2023;55(5):1-10.
32. Lamara A, Fellahi ZEA, Hannachi A, Benniou R. Assessing the phenotypic variation, heritability and genetic advance in bread wheat (Triticum aestivum L.) candidate lines grown under rainfed semi-arid region of Algeria. Rev Fac Nac Agron Medellin. 2022;75(3):10107-10118.
33. Jain N, Marker S, Kanwar S. Assessment of genetic variability in late sown wheat (Triticum aestivum L.) germplasm. Chem Sci Rev Lett. 2017;6(22):1295-1300.
34. Alemu YA, Anley AM, Abebe TD. Genetic variability and association of traits in Ethiopian durum wheat (Triticum turgidum L. var. durum) landraces at Dabat Research Station, North Gondar. Cogent Food Agric. 2020;6(1):1778604.