Prediction of the Corn Grains Yield through Artificial Intelligence

Varela N.; Silva J.; Pineda O.B.; Cabrera D. · Procedia Computer Science (2020) · DOI: 10.1016/j.procs.2020.03.080

Resumen

Currently, the determination of the quality of the cereals is done manually by grain classifier experts prior to the marketing stage. In this paper we present a web software tool that allows determining the quality level of a corn sample automatically from an image of it. Image processing algorithms were implemented to correct distortions caused mainly by the capture process. The K-Means classification algorithm was used and a function was developed to calculate the hectolitre weight in relation to the sample area. The results obtained by the application for grades 1 and 2, are close to those measured by the experts. However, those for grade 3 have not been similar since the subsamples selected were not representative.

Instituciones: Universidad Peruana de Ciencias Aplicadas