Deciphering Traits Association and Regression Analysis in Rice (Oryza sativa L.) under Saline Soils
P. Hima Bindu *
Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad, Telangana-500030, India.
R.M. Sundaram
ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana-500030, India.
G. Shiva Prasad
Agricultural Research Station, Kampasagar, Nalgonda, Telangana-508001, India.
K. Sumalini
Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad, Telangana-500030, India.
C.H. Damodar Raju
Rice Breeding, Regional Agricultural Research Station, Warangal, Telangana-506007, India.
*Author to whom correspondence should be addressed.
Abstract
Salt stress adversely affects plant growth and development. Various strategies have been employed to enhance the production and productivity of plants to salt stress. Expression of complex traits like yield is the result of interaction of several yield contributing features, correlation analysis and regression were conducted in an experiment involving 86 rice genotypes to determine relationship of seed yield and its component traits. The experiment was conducted during Rabi, (November – April 2020-2021) at Agricultural Research Station Kampasagar, Telangana, India. The genotypes were transplanted in the naturally formed salinity screening block to analyze the tolerance under salinity situations. The 10 characters observed are as shown as follows: Mortality percentage, days to 50 per cent flowering, plant height, panicle length, number of productive tillers, the number of grains per panicle, unfilled grains per panicle, spikelet sterility, 1000 grain weight and seed yield per plant were recorded. Correlation analysis revealed that number of productive tillers, panicle length and total number of grains per panicle had positive significant association with seed yield per plant, selection for these traits will improve seed yield. Analysis using linear regression revealed that, in general, the seed yield showed the linear and quadratic relationships with other traits, and number of productive tillers, panicle length and 1000 grain weight showed the robust relationship. Among all the yield contributing traits, the number of productive tillers and panicle length had the highest contribution to the seed yield. It is crucial to give priority to traits that exhibit significant positive correlations and traits showing highest contribution to the seed yield during selection process. This approach will yield rewarding results in the development of high-yielding cultivars suitable for salinity conditions.
Keywords: Rice, correlation, regression, salinity, seed yield