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

Abstract

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