Identification of adaptable rice genotypes under diverse production environments using a multivariate statistical model

Basmati rice is sold at a higher price in both local and international markets due to its superior grain qualities. Identification of high performing adaptable genotypes under multi-environmental conditions very crucial sustain production. In the present research, sixteen were evaluated three diverse production environments i.e. transplanted (TPR), direct seeded (DSR), system intensification (SRI) during two consecutive kharif seasons. The experiment was laid down randomized block design with replications. primary objective this research identify stable different mean using GGE biplot model. Genotypes explained proportion (44.25 60.71 %) total sum squares while environment attributed only (7.71 23.26%). Genotype by interaction contributed 31.58% 36.77% variation for studied traits. Under DSR, Haryana Basmati-1 hulling%, milling%, head recovery% Improved Pusa 1 amylose content identified as specifically adapted genotypes. Likewise, SRI, HKR 98-476 hulling% recovery%, -1 found suitable These can be recommended commercial cultivation specific environments.