RESUMO
In this work, a new method has been developed to detect adulterations in avocado oil by combining optical images and their treatment with deep learning algorithms. For this purpose, samples of avocado oil adulterated with refined olive oil at concentrations from 1 % to 15 % (v/v) were prepared. Two groups of images of the different samples were obtained, one in conditions considered as bright and the other as dark, obtaining a total of 1,800 photographs. To obtain these images under both conditions, the exposure or shutter speed of the camera was modified (1/30 s for light conditions and 1/500 s for dark conditions). A residual neural network (ResNet34) was used to process and classify the images obtained. A different model was developed for each condition, and during blind validation of the models, â¼95 % of the images were correctly classified.
