Optimizing wheat height to maximize yield has been an important aspect which is evident from a successful example of green revolution. Dwarfing genes (Rht) are known for yield gains due to lodging resistance and partitioning of assimilates into ear. The available and commercially exploited sources of dwarfism in Indian spring wheat are Rht1 and Rht2 genes inspite of availability of over 20 dwarfing genes. Rht8 a Gibberellic acid sensitive dwarfing gene is another reduced height gene commercially exploited in some Mediterranean countries. Two F2 populations segregating for Rht1 and Rht8 genes with each comprising 398 and 379 plants were developed by crossing European winter wheat cultivars Beauchamp and Capitole with Indian spring wheat cultivar PBW 621. Different genotypic combinations for Rht1 and Rht8 genes were selected from these populations through linked molecular markers and selected F3:4 lines were evaluated for various agronomic traits in a replicated trial. Reduction in plant height with Rht8 and Rht1 averaged 2.86% and 13.3% respectively as compared to the group of lines lacking dwarfing gene. Reduction was spread along all the internodes of wheat culm and reduction was lower as progress towards the lower internode. Grain number per spike and highest yield was observed in lines carrying only Rht1 gene. Reduction in plant biomass was observed with either of the dwarfing gene. Longest coleoptile length and seedling shoot length averaged 4.4 ± 0.09 cm and 19.5 ± 0.48, respectively was observed in lines lacking any of the dwarfing gene. Negligible reduction of 6.75% and 2.84% in coleoptile length and seedling shoot length, respectively was observed in lines carrying only Rht8 gene whereas F3:4 lines with Rht1 gene showed 21.64% and 23.35% reduction in coleoptile length and seedling shoot length, respectively. Additive effect of genes was observed as double dwarfs showed 43.31% and 43.34% reduction in coleoptile length and seedling shoot length.

The high performance and stability of wheat genotypes for yield, grain protein content (GPC), and other desirable traits are critical for varietal development and food and nutritional security. Likewise, the genotype by environment (G × E) interaction (GEI) should be thoroughly investigated and favorably utilized whenever genotype selection decisions are made. The present study was planned with the following two major objectives: 1) determination of GEI for some advanced wheat genotypes across four locations (Ludhiana, Ballowal, Patiala, and Bathinda) of Punjab, India; and 2) selection of the best genotypes with high GPC and yield in various environments. Different univariate [Eberhart and Ruessll’s models; Perkins and Jinks’ models; Wrike’s Ecovalence; and Francis and Kannenberg’s models], multivariate (AMMI and GGE biplot), and correlation analyses were used to interpret the data from the multi-environmental trial (MET). Consequently, both the univariate and multivariate analyses provided almost similar results regarding the top-performing and stable genotypes. The analysis of variance revealed that variation due to environment, genotype, and GEI was highly significant at the 0.01 and 0.001 levels of significance for all studied traits. The days to flowering, plant height, spikelets per spike, grain per spike, days to maturity, and 1000-grain weight were specifically affected by the environment, whereas yield was mainly affected by the environment and GEI. Genotypes, on the other hand, had a greater impact on the GPC than environmental conditions. As a result, a multi-environmental investigation was necessary to identify the GEI for wheat genotype selection because the GEI was very significant for all of the evaluated traits. Yield, 1000-grain weight, spikelet per spike, and days to maturity were observed to have positive correlations, implying the feasibility of their simultaneous selection for yield enhancement. However, GPC was observed to have a negative correlation with yield. Patiala was found to be the most discriminating environment for both yield and GPC and also the most effective representative environment for GPC, whereas Ludhiana was found to be the most effective representative environment for yield. Eventually, two NILs (BWL7508, and BWL7511) were selected as the top across all environments for both yield and GPC.

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All stage resistance to stripe rust races prevalent in India was investigated in the European winter wheat cultivar ‘Acienda’. In order to dissect the genetic basis of the resistance, a backcross population was developed between ‘Acienda’ and the stripe rust susceptible Indian spring wheat cultivar ‘HD 2967’. Inheritance studies revealed segregation for a dominant resistant gene. High density SNP genotyping was used to map stripe rust resistance and marker regression analysis located stripe rust resistance to the distal end of wheat chromosome 1A. Interval mapping located this region between the SNP markers AX-95162217 and AX-94540853, at a LOD score of 15.83 with a phenotypic contribution of 60%. This major stripe rust resistance locus from ‘Acienda’ has been temporarily designated as Yraci. A candidate gene search in the 2.76 Mb region carrying Yraci on chromosome 1A identified 18 NBS-LRR genes based on wheat RefSeqv1.0 annotations. Our results indicate that as there is no major gene reported in the Yraci chromosome region, it is likely to be a novel stripe rust resistance locus and offers potential for deployment, using the identified markers, to confer all stage stripe rust resistance.

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