Vol. 11, Issue 3 (2023)
Model development for yield forecast through composite raw data technique and stepwise regression analysis (Forward method) for chickpea crop of Chhattisgarh plain zone
Author(s): Gendre S and Pandey KK
Abstract: The time series data on chickpea yield and weather variable viz. minimum maximum temperature, relative humidiy, sunshine, rainfall and wind velocity Weekly weather data over a span of 20 years data period (1998- 2017) for Dhamtari district of Chhattisgarh have been used in study. The model have been developed by Stepwise Regression analysis (forward method) and Multiple linear regression on Composite weather data. The Stepwise Regression model fitted on 14 generated weather variables along with T, i.e. 15 parameters have been used. The value of R2 found i.e. 92% for Dhamtari district for Chickpea crop and multiple regression analysis has been applied on five new generated composite weather variables along with T as independent variables and de- trend yield used as dependent variable. The value of R2 found 79% for Dhamtari district. The developed model has been validated by the the error parameters viz. MAE, MSE, RMSE, PE and PD along with maximum R2. The above techniques showing that both the models are very reliable for district level forecast for chickpea crop for the district under the Chhattisgarh plain zone of Chhattisgarh. The present study covers under the study of individual effect of weather variables.
Pages: 56-59 | 322 Views 65 Downloads
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How to cite this article:
Gendre S, Pandey KK. Model development for yield forecast through composite raw data technique and stepwise regression analysis (Forward method) for chickpea crop of Chhattisgarh plain zone. Int J Chem Stud 2023;11(3):56-59.
