“…These characteristics in the agronomic aspect influence their germination capacity [ 10 ], while in industrial processes they directly influence grinding, cooking, nutrition and appearance [ 11 ]. The shape and size descriptors of the seeds can be analyzed by image analysis using statistical techniques such as descriptive statistics, principal components, Euclidean distance, Mantel correlation test and supervised machine learning, with the image analysis technique being effective for detect biometric differences between seeds [ 12 ]. Likewise, computer vision techniques are being used to evaluate the morphometric and colorimetric characteristics of seeds that describe the shape, size and textural features of the seeds [ 13 ], and there are also studies on morpho characterizations, colorimetric measurements of biological species [ 14 ], in addition the images are being used to analyze the texture, morphology and color of the vein, there are studies that use images of the seed, considering attributes such as perimeter, area, diameter and centroid, are used to analyze the quality of the seeds using machine learning [ 15 ].…”