PREDICTING HEADER LOSS AND TOTAL GRAIN LOSS OF A MINI COMBINE HARVESTER (JD12GD) USING REGRESSION MODEL
Publication Date : 26/03/2021
Harvest losses in combine harvester and any other harvesting machine pose great problem in the agricultural production, and any machinery developed for harvesting must have objective of reducing the harvest losses to the minimum value. A multiple linear regression models for predicting header loss and total grain loss were developed for Atilla and Norman-Borloug wheat variety with respect to moisture content and forward speed. The values of the coefficient of determination R2 for header loss and total grain loss were 0.943 and 0.8184 respectively for Atilla wheat variety and 0.915 and 0.7977 respectively were obtained for Norman-Borloug wheat variety. This indicates a strong agreement between the predicted values of (header loss and total grain loss) and the observed values.
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