Multifaceted Spinach Variety Classification: A Combined CNN-KNN Model Methodology

Spinach is a type of green vegetable leaf. It comes in different types and each one has its look. Sorting these kinds properly is very important for farming and breeding plans. In this study, a new way to classify types of spinach is suggested using combined models from Convolutional Neural Network (CNN) and K-Nearest Neighbors (KNN). These two different systems are combined to make the best use of both. This takes advantage of CNN's ability to find special features and KNN's learning based on individual cases. The set of 10,00 items is made up of spinach leaves sorted into three groups called All Green, Pusa Bharti, and Pusa Jyoti. This sorting was done based on important plant features. The mixed way works better than single classifiers. It's 97.1% accurate and strong in dividing different spinach types. The CNN part does best at seeing complex designs and positions of spinach pictures. The KNN part helps sort things better by looking for close examples in the feature space. The suggested system doesn't just help make spinach kinds better, it also looks promising for use in a bigger way with farm research and smart farming.