Open AccessStability analysis of rice (Oryza sativa L.) under different micro-environments
Author(s) -
Deepak Katkani,
S. K. Payasi,
Vinod Patel,
Jay Prakash Chamar
Publication year - 2021
Publication title -
oryza
Language(s) - English
Resource type - Journals
eISSN - 2249-5266
pISSN - 0474-7615
DOI - 10.35709/ory.2021.58.4.3
Subject(s) - panicle , mathematics , oryza sativa , adaptability , transplanting , linear regression , regression analysis , grain yield , yield (engineering) , stability (learning theory) , horticulture , agronomy , sowing , statistics , biology , ecology , biochemistry , materials science , metallurgy , gene , machine learning , computer science
The present research was undertaken to evaluate 32 rice genotypes for grain yield and its attributing traits under three micro-environments like., direct seeded condition (E-I), transplanting at spacing of 15 x 15 cm (E-II) and 25 x 15 cm (E-III). Adopting the Eberhart and Russell (1966) model, stability analysis of variance revealed significant differences among the genotypes for days to 50% flowering, days to maturity, plant height, panicle length, number of grains per panicle and flag leaf angle. Stability parameters for grain yield per plant indicated that the genotypes Rewa 1329-4-26-1, Rewa 1326-11-67-2 and Rewa 1326-16-1 had regression coefficient less than one and mean value higher than average mean this depicted that these genotypes have wider adaptability and suitability for all micro- environments and the genotypes Rewa 1329-4-123-11, Rewa 1328-18-16 and Rewa 1326-3-34-4 had regression coefficient less than one and deviation from regression around zero were identified as highly stable and best suited for poor management practices like, direct seeded condition.