Sorghum [Sorghum bicolor (L.) Moench] is a very important crop in the arid and semi-arid tropics of India and African subcontinent. In the process of release of new cultivars using multi-location data major emphasis is being given on the superiority of the new cultivars over the ruling cultivars, while very less importance is being given on the genotype 9 environment interaction (GEI). In the present study, performance of ten Indian hybrids over 12 locations across the rainy seasons of 2008 and 2009 was investigated using GGE biplot analysis. Location attributed higher proportion of the variation in the data (59.3-89.9%), while genotype contributed only 3.9-16.8% of total variation. Genotype 9 location interaction contributed 5.8-25.7% of total variation. We could identify superior hybrids for grain yield, fodder yield and for harvest index using biplot graphical approach effectively. Majority of the testing locations were highly correlated. 'Which-wonwhere' study partitioned the testing locations into three mega-environments: first with eight locations with SPH 1606/1609 as the winning genotypes; second megaenvironment encompassed three locations with SPH 1596 as the winning genotype, and last mega-environment represented by only one location with SPH 1603 as the winning genotype. This clearly indicates that though the testing is being conducted in many locations, similar conclusions can be drawn from one or two representatives of each mega-environment. We did not observe any correlation of these mega-environments to their geographical locations. Existence of extensive crossover GEI clearly suggests that efforts are necessary to identify location-specific genotypes over multi-year and -location data for release of hybrids and varieties rather focusing on overall performance of the entries.

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Lack of appropriate donors, non-utilization of high throughput phenotyping and genotyping platforms with high genotype × environment interaction restrained identification of robust QTLs for grain protein content (GPC) in rice. In the present investigation a  BC 3 F 4 mapping population was developed using grain protein donor, ARC10075 and high-yielding cultivar Naveen and 190 lines were genotyped using 40 K Affimetrix custom SNP array with the objective to identify stable QTLs for protein content. Three of the identified QTLs, one for GPC ( qGPC1 . 1 ) and the other two for single grain protein content ( qSGPC 2. 1 , qSGPC7 . 1 ) were stable over the environments explaining  13%, 14% and 7.8% of the phenotypic variances, respectively. Stability and repeatability of these additive QTLs were supported by the synergistic additive effects of multi-environmental-QTLs. One epistatic-QTL, independent of  the  main effect QTL was detected over the environment for SGPC. A few functional genes governing seed storage protein were hypothesised inside these identified QTLs. The qGPC1 . 1 was validated by NIR Spectroscopy-based high throughput phenotyping in BC 3 F 5 population. Higher glutelin content was estimated in high-protein lines with the introgression of qGPC1 . 1 in telomeric region of short arm of chromosome 1. This was supported by the postulation of probable candidate gene inside this QTL region encoding glutelin family proteins.

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Barley (Hordeum vulgare L.) is an important feed purpose cereal grown under diverse production conditions and harsh environments. The present investigation was carried out to study performance of advanced breeding lines and identify superior genotypes of feed barley using multienvironment trial data from All India Coordinated Wheat and Barley Improvement Programme (AICW&BIP). Ninety three experimental genotypes and five released cultivars were tested across eleven locations during four years. Grain yield and other agronomic traits were analyzed. Stability and genotype superiority for grain yield and other traits were determined using genotype and genotype × environment (GGE) biplot analysis. The result showed that environment and genotype contributed 32.9 to 67.4% and 4.7 to 20.4% of the total variation, respectively. The genotype × environment interaction contributed 27 to 44% of total variation. The experimental genotypes showed arrays of variation for grain yield in each year, with mean values ranging from 2.12 to 5.36 t/ha. Twelve experimental genotypes were identified, which were either superior or equal performance to the best check based on their high yield and stability across environments. The locations Varanasi, Kanpur, Vijapur and Durgapura discriminated the genotypes more than other sites for grain yield and agronomic traits. The findings provided valuable information on wide adaptation of feed barley genotypes, which could be useful for barley improvement programmes.