Deciphering the G x E interaction involved in milling quality of pigeon pea (Cajanus cajan) derived from interspecific hybridization

Abstract An important pulse crop, pigeon pea is primarily grown in tropical and sub-tropical climates worldwide and is a rich source of protein and dietary fibre. In India, about 80% of the pulses produced are eaten as dhal (dehusked splits), recovery of dhal plays a major role in the pulse milling industry and it increases when pulse grains are pre-treated to loosen the husk before milling. Since quality traits are highly influenced by the environment, to select stable genotypes for yield and quality traits, multi-environment trials (MET) must be carried out to study genotype × environment interaction (GEI). In the current study, seeds from inter-specific crosses derived lines involving wild species (Cajanus scarabaeoides, Cajanus acutifolius and Cajanus cajanifolius) and cultivated parental lines (ICPL 84023, Pant A134, and UPAS120) were examined for three years with pre-milling treatment and without pre milling treatment for dhal yield and hulling efficiency. The combined ANOVA revealed the existence of ample variation for all the milling quality traits among the lines derived from interspecific hybridization. The gain hardness showed a positive and significant association with the dhal yield and hulling efficiency. The AMMI and GGE analysis was employed to identify the stable genotype among the interspecific lines for dhal yield and hulling efficiency. The AMMI revealed the presence of significant G x E interaction for the milling traits. GGE grouped the pre-milling treated environment into a mega environment and distinguished it from pre-milling untreated environments. The genotypes derived from Cajanus scarabaeoides were found better under untreated environments while C. cajanifolius derived lines were found best under a pre-milling treated environment. The genotype G12 derived from the UPAS120 x C. cajanifolius was found most stable genotype with high dhal yield and hulling efficiency based on AMMI, GSI, ASV and GGE analysis.