Image analysis of coffee seeds submitted to the LERCAFE test

Abstract

The aim of this experiment was to quantify the stained areas of coffee seeds submitted to the LERCAFE test using image analysis. The seeds used were of the Catuaí Vermelho IAC 99 and Paradise cultivars. The physiological quality of the lots was assessed using germination tests, moisture content and a germination speed index. The LERCAFE test was conducted using seeds without parchment immersed in a solution of 3% sodium hypochlorite for 3 hours. Color photographs (RGB) with a resolution of 5 MPx were taken of each seed. The seeds were visually evaluated, and the functions generated from the analyses of the stained and non-stained regions were quantified by the Matlab R2009b program. Classification models were developed based on the Fisher Linear Discriminant Function and the evaluation of the adequacy of the models confusion matrix between the visual references and the classification generated by the linear functions. The image analysis for the creation of Fisher’s linear discriminant function in the development of classifiers for the coffee seeds submitted to the LERCAFE test is potentially efficient; however, it remains necessary to test other discriminant functions and quantification methodologies.