DETERMINATION OF THE OPTIMUM MATURITY OF NEW RICE FOR AFRICA USING ARTIFICIAL NEURAL NETWORK
Abstract
The New Rice for Africa (NERICA) is a child birth of research to improve upon the production of rice in sub-Sahara Africa due to challenges of shortages in agricultural food production. Two major varieties were obtained, for low lands and uplands. NERICA-4 is commonly suited for uplands and has delicious taste as compared to the other upland varieties. However, the problem of loss of grains at harvest which translates to low productivity amongst other factors needs to be addressed. In this paper, about 750m2 farm land was cultivated with NERICA-4 rice variety and 60 images at different maturity period with ten features extracted, preprocessed and processed using MATLAB2018Ra software. The processed images were classified using Artificial Neural Network to determine the optimum maturity period based on visual properties. 93.30% classification accuracy was obtained. This shows that when made operational, the loss of grains can be drastically reduced and productivity increased
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