No abstract

Heat and drought stresses have negative impacts on wheat yield and growth worldwide, causing up to 60% and 40% yield losses, respectively, but their combined effect can cause severe losses. The present study aimed to identify the high-yielding genetic resources tolerant to drought and/or heat stresses under climate change scenarios. The field trials on 42 genotypes were conducted at three locations in four environments (normal TSIR-NS, drought TSRF-DR, heat LSIR-HT, and heat and drought combined LSRF-DHT) each for two consecutive years. Yield contributing traits were recorded in all the experiments and all the locations: SI (susceptibility index) and STI (stress tolerance index) were also estimated. GY (Grain yield) was severely affected by LSRF-DHT (48.6%), followed by TSRF-DR (23.6%) and LSIR-HT (16.8%). GY had a positive correlation with BM (biomass), HI (harvest index), and TGW (1000-grain weight) under all environments and negative with DH (days to heading) (LSIR-HT and LSRF-DHT). Stepwise regression analysis revealed a higher contribution of BM and HI towards GY under all environments. GW (grain weight/spike) contributed under LSIR-HT and LSRF-DHT, and GN (grain number/spike) under TSIR-NS and TSRF-DR. GFD (grain-filling duration), TGW, and PTL (productive tillers) contributed under all conditions except LSRF-DHT. WS 2016-4 was the only genotype that yielded high under all the conditions. WS 2016-12 and CNM 16-1 were tolerant to heat and drought stresses and high yielding. HINDI 62, HTW 11, and QBP 1606 were less sensitive to all the stresses but low yielding. Overall, out of 30 tolerant genotypes (10 of each category), 19 adapted to escape mechanism which is irrespective of their yielding level. The study demonstrated the potential of identified genotypes in wheat breeding for climate resilience and the traits imparting tolerance to these genotypes.

Wheat (Triticum aestivum L.) is a staple food crop for the global human population, and thus wheat breeders are consistently working to enhance its yield worldwide. In this study, we utilized a sub-set of Indian wheat mini core germplasm to underpin the genetic architecture for seed shape-associated traits. The wheat mini core subset (125 accessions) was genotyped using 35K SNP array and evaluated for grain shape traits such as grain length (GL), grain width (GW), grain length, width ratio (GLWR), and thousand grain weight (TGW) across the seven different environments (E1, E2, E3, E4, E5, E5, E6, and E7). Marker-trait associations were determined using a multi-locus random-SNP-effect Mixed Linear Model (mrMLM) program. A total of 160 non-redundant quantitative trait nucleotides (QTNs) were identified for four grain shape traits using two or more GWAS models. Among these 160 QTNs, 27, 36, 38, and 35 QTNs were associated for GL, GW, GLWR, and TGW respectively while 24 QTNs were associated with more than one trait. Of these 160 QTNs, 73 were detected in two or more environments and were considered reliable QTLs for the respective traits. A total of 135 associated QTNs were annotated and located within the genes, including ABC transporter, Cytochrome450, Thioredoxin_M-type, and hypothetical proteins. Furthermore, the expression pattern of annotated QTNs demonstrated that only 122 were differentially expressed, suggesting these could potentially be related to seed development. The genomic regions/candidate genes for grain size traits identified in the present study represent valuable genomic resources that can potentially be utilized in the markers-assisted breeding programs to develop high-yielding varieties.