Abstract
In Tamil Nadu, groundnut is an essentialand major oilseed crop, mainly grown under rainfed conditions. The changes in weather parameters might affect the productivity of groundnut. Hence, crop yield forecasting based on weather parameters is essential for proper planning, decision-making, and buffer stocking policy formulation. As for the data with multicollinearity, penalized regression models i.e.Ridge, Least Absolute Selection and Shrinkage Operator (LASSO) and Elastic Net (ENet), are better alternatives to classical linear regression. The data on weather parameters such as maximum temperature(Tmax), minimum temperature (Tmin), morning relative humidity (RH I), evening relative humidity (RH II), and rainfall were collected for 29 years from1991-2019. The weather indices approach was used in this study. The collected data were partitioned into training, and testing datasets and the hyperparameters of penalized regression models were tuned using cross-validation. The performance of the models wasevaluated using an adjusted coefficient of determination (R2adj), Root Mean Squared Error (RMSE), normalized RMSE (nRMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) as the goodness of fit criteria. The results revealed that all the Penalized regression models provide a better fit to data. The SMLR and ENet were found to predict with better accuracy. Hence, these methods can be used for groundnut yield forecasting during Kharif season for the Coimbatore district of Tamil Nadu.
Highlights
Groundnut is one of the most essentialoilseed crops of India
A timely and reliable forecast of crop yield is of great importance for monsoon-dependent countrieslike India, where the economy is mainly based on agricultural production (Vinaya et al, 2017)
The main objective of our study is to develop and select a statistical groundnut yield forecasting model for the Coimbatore district of Tamil Nadu with the predictive performance and efficiency of the developed models
Summary
Groundnut is one of the most essentialoilseed crops of India. In Tamil Nadu, it is annually grown in about 0.35 million hectares with about 0.98 million tons production. In Tamil Nadu, two-thirds of the groundnut cultivation area is under rainfed condition and the remaining one-third is under irrigated condition. The overall growth of the Indian economy relies on the performance of agriculture, which depends, upon the weather conditions every year. A timely and reliable forecast of crop yield is of great importance for monsoon-dependent countrieslike India, where the economy is mainly based on agricultural production (Vinaya et al, 2017)
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