HEMICAL PROPERTIES OF MO, FE AND CIC OF THE SOIL THROUGH ARTIFICIAL INTELLIGENCE AND IMAGE ANALYSIS

Abstract

The development of a system capable of estimating the organic matter, iron and capacity for cationic exchange of the soil, through the use of Artificial Neural Network (ANN) and principal component analysis (PCA), is presented. The variables used to perform the analysis were texture, HSL color histogram and RGB of the images, which were correlated with the properties obtained in conventional lab analyses.