ArticleData in brief2025
Phenotypic data on seedling traits of hexaploid spring wheat panel evaluated under heat stress.
Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Advances in gene cloning and functional genomics approaches for wheat (Triticum aestivum L.) improvement.The plant genome · 2026Review
- Genome-wide association studies for identification of stripe rust resistance loci in diverse wheat genotypes.Frontiers in plant science · 2025Article
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7 authors.
Funding
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Abstract
Heat stress is the major abiotic stress affecting wheat at various developmental stages including seedling and reproductive stage. Heat stress at early developmental stages affects the seed germination and seedling establishment, thereby reduces grain yield per unit area. To overcome the negative impact of heat stress, it is crucial to identify the source of heat tolerant germplasm lines and also introduce them into breeding program. In this study, we evaluated 216 global diversity panel of hexaploid spring accessions comprising landraces and cultivars under non-heat stress (23 °C) and heat stress (36 °C) treatments. Phenotypic data was collected after 13 days of heat stress on various seedling traits, including coleoptile length (CL; cm), shoot length (SL; cm), root length (RL; cm), tiller number (TN), shoot fresh weight (SFW; mg), and root fresh weight (RFW; mg). Heat stress negatively affected all the seedling traits with maximum effect on RL (85.6 % reduction) and minimum effect on CL (15.44 %). However, the RN was increased by 20 % under heat stress. It was also noticed that the effect of heat stress was more on root traits (such as RL and RFW) as compared to shoot traits (such as SL and SFW). This suggests that compared to roots, shoots may have adaptive mechanisms such as transpiration cooling via stomatal regulation, to alleviate the negative impacts of heat stress. Moreover, the raw phenotypic data was subjected to mixed linear analysis to derive best linear unbiased estimates (BLUEs). BLUE values were further used to assess the intrinsic relationship among the seedling traits under non-heat stress (23 °C) and heat stress (36 °C) treatments. The dataset presented in this study serves a valuable source for identifying extremely tolerant lines for heat stress, which can be utilized in breeding program to develop heat resilient, high-yielding wheat cultivars. Moreover, this dataset helps in identifying potential genomic regions associated with improved heat stress tolerance, which can be incorporate in marker-assisted breeding of heat tolerant wheat varieties.
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