Shallots are an essential plant for the commercial and home industries included in the Allium genus. Choosing the type of onion based on the characteristics is very easy for humans to do but not easy for humans to do in the spice industry; therefore, machines will replace human limitations in recognizing the type of shallots in the spice industry. Inspired by the success of research on the classification of shallots using SVM, we propose CNN to tackle the problem of classifying types of shallots based on shape and texture features. This study uses the CNN method's performance to categorize different varieties of shallots based on their shape and texture features. In a shallot classification test, our approach promises higher accuracy and lower loss than standard machine techniques.