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P-ISSN: 2349-8528, E-ISSN: 2321-4902   |   Impact Factor: GIF: 0.565

International Journal of Chemical Studies

Vol. 8, Special Issue 3 (2020)
Predication of grain yield of rice using statistical model in Chhattisgarh plains


Author(s): Krishna Murari, Dr. GK Das, Jubuli Sahu and Dr. HV Puranik

Abstract: Rice is the chief agricultural product and one of the primary food sources for this reason, it is of pivotal importance for worldwide economy and development. Rice production in the Chhattisgarh is influenced by heat stress due to late sowing for optimization of yield, sowing at the appropriate time to fit the cultivar maturity length. The Statistical model was used to determine to assess the production potential for Raipur districts under varieties Mahamaya. The data analysis by SPSS and MS-Excel, it was found to be the most significant parameter for yield prediction of rice. Maximum temperatures for different decade are found predictors for the final yield in the end. Through SPSS model a simple linear equation has been determined for rice yield prediction in the area. With the help of weekly weather data, we find out correlation coefficient. On the basis of the identified significant weather parameters as independent variables and long term data of grain yield of Mahamaya variety, regression equation has developed. The equation the observed and predicted grain yields and significant results were drawn. The accuracy rate remained generally above 95% in experiment and present analysis of validation of regression model indicates only once in 2016-2017 this remained 96.7% or error is 3.3% during the last 10 years period. The prediction values are very close to the actual values of yield.

DOI: 10.22271/chemi.2020.v8.i3a.9750

Pages: 01-04  |  407 Views  9 Downloads

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How to cite this article:
Krishna Murari, Dr. GK Das, Jubuli Sahu and Dr. HV Puranik. Predication of grain yield of rice using statistical model in Chhattisgarh plains. International Journal of Chemical Studies. 2020; 8(3): 01-04. DOI: 10.22271/chemi.2020.v8.i3a.9750
International Journal of Chemical Studies