Genetic gain and G × E interaction in bread wheat cultivars representing 105 years of breeding in Pakistan
2022
Hanif, Uzma | Gul, Alvina | Amir, Rabia | Munir, Faiza | Sorrells, Mark E. | Gauch, Hugh G. | Mahmood, Zahid | Subhani, Abid | Imtiaz, Muhammad | Alipour, Hadi | Rasheed, Awais | He Zhonghu
It is important to understand the genetic gain achieved through selection of key yield traits for planning future breeding strategies in high yielding wheat cultivars. The aim of the present study was to characterize the genetic changes in morphological, physiological, and yield component traits under five irrigated and rain-fed environments using 24 wheat cultivars released from 1911 to 2016 in Pakistan. We evaluated these cultivars for genotype-by-environment (G×E) interaction by additive main effect and multiplicative interactions (AMMI) in five environments. There was a significant increase in grain yield (9.03 kg ha–1 year–1, 0.37%). Plant height was reduced linearly (-0.26 cm year−1, -0.33%). The traits waxiness, leaf rolling, harvest index, spike length and grains per spike significantly increased but the gain was only 0.16-2% per year. Analysis of variance (ANOVA) revealed that genotype, environment, and G×E interaction were highly significant (P <0.01) for all traits except relative chlorophyll content, biomass, days to maturity, and number of spikes per plot. AMMI-ANOVA analysis also showed that the first of three interaction principal components (IPC) was highly significant (P <0.01) for all traits. IPC1 and IPC2 accounted for >40% and >20% of the G×E interaction, respectively. Gene-specific markers identified the durable resistance gene Lr67/Yr46/Sr55/Pm46 in obsolete cultivars as early as 1910, whereas the photoperiod-insensitive allele Ppd-D1a and reduced height alleles Rht-B1b and Rht-D1b were present only in the post-1965 cultivars. Diversity analysis based on a 50 K SNP genotyping array clearly differentiated temporal patterns in 24 cultivars, which was correlated with the agronomic performance of the cultivars. This dataset provided detailed insight about the performance of historical wheat cultivars and could help in devising future wheat breeding strategies to focus on the traits contributing to grain yield and have slower rate of genetic progress.
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