Classification of potatoes according to their cultivated field by SVM and KNN approaches using an electronic nose

Ali Amkor (Sultan Moulay Slimane University)
Noureddine El Barbri (Sultan Moulay Slimane University)

Bulletin of Electrical Engineering and Informatics
Vol 12, No 3: June 2023

In this article, we propose a homemade electronic nose to distinguish between two types of potatoes: the first type is traditionally treated with donkey and sheep manure, and the other type is treated with chicken manure. The proposed tool consists of a network of commercial metal oxide sensors, a data acquisition card, and a personal computer for data pre-processing and processing. Two methods were used, namely, support vector machines (SVM) and k-nearest neighbors (KNN) with 5-fold cross-validation and which achieved the same success rate of 97.5%. These results demonstrate that our concept, which is quick, simple, and inexpensive, can discriminate between potatoes based on the method of fertilization used in the field.