PREDICTING HEADER LOSS AND TOTAL GRAIN LOSS OF A MINI COMBINE HARVESTER (JD12GD) USING REGRESSION MODEL

Publication Date : 26/03/2021

Author(s) :

H. I. Abdullahi, M. S. Abubakar, O. A. Salihu.

Volume/Issue :

Volume 16

Issue 3

(03 - 2021)

Abstract :

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.

No. of Downloads :

About BayeroJet

The new Bayerojet Journal is designed to be able to manage the increasing number of published articles. The new system will allow the publishers as well as the Bayerojet team to make publishing more efficient. If you wish to publish an article it will be very easy. All you have to do is to submit your paper online and wait to the review before it will be finally published. You can manage your articles and send new versions at any time. Browse through our page to find out more.