2023, Vol. 8, Special Issue 4
Regression weather-yield models for western-zonal cotton yield prediction of Haryana
Author(s): Aditi, Pushpa, Chetna and Darvinder Kumar
Abstract: The preharvest forecasts are useful for farmers to decide in advance their prospects and course of action. This study focuses on the multiple linear regression method for evaluating yield prediction of cotton in the districts of Bhiwani, Hisar, Fatehabad and Sirsa of Haryana to develop pre-harvest models for cotton yield. The data of cotton yield and weather parameters
viz., minimum and maximum temperature, sunshine hours, relative humidity and rainfall of 39 years from the period 1980-81 to 2019-20 was collected from HARSAC (Haryana Space Application Center) and College of Agriculture, HAU, Hisar. The time period from 2014-15 to 2019-20 was excluded from the construction of models used for model validation. In all the phases for the districts during evaluation, zonal yield models including CCT and meteorological factors consistently gave good results for cotton yield prediction and outperformed the other models with reduced error metrics.
Pages: 123-127 | Views: 186 | Downloads: 6Download Full Article: Click HereHow to cite this article:
Aditi, Pushpa, Chetna, Darvinder Kumar. Regression weather-yield models for western-zonal cotton yield prediction of Haryana. Int J Stat Appl Math 2023;8(4S):123-127.
