A hybrid classifier for postharvest grading of Nutmeg seeds

Nutmeg seed quality grading is an essential process that plays a crucial role in ensuring the consistency and safety of nutmeg-based products. It helps to promote fair trade practices and sustainability in the nutmeg industry, making it a vital component of the global spice trade. The seed quality grading primarily considers various characteristics of seed images. Shape, color, and texture are among the key image attributes that are extracted for analysis. The features that are created rely heavily on manual labor and are somewhat limited in scope. As a result, these features often do not perform well when applied to a broader set of data. This can lead to significant discrepancies in the final discrimination results. In the present research, a complex Convolutional Neural Network (CNN) was proposed, which integrates a classifier based on Support Vector Machine (SVM). The primary goal of this approach is to improve the accuracy of classifying dried nutmegs into either good or bad categories.