Rice Classification and Quality Detection Success with Artificial Intelligence Technologies

Abstract

Rice is the most consumed and the most traded food in the world, and so it is very important for it to be classified correctly by its qualities. In this study, the success situation in the classification of rice by qualities with information technologies systems was aimed. In the study, the feature selection process was applied by making statistical analyzes of the features obtained from the images of two different rice species. The classification process was carried out with five different Artificial Intelligence (AI) algorithms using 6 different morphological features. When the results and performance values are examined, it was viewed that the Support Vector Machine (SVM) algorithm gave the highest accuracy in classification with 93.53%. The obtained Area Under the Curve (AUC) values showed that a very high classification result of 99.18% was accomplished. It was detected that morphological features were very important parameters in classifying rice varieties with the AI algorithms. It is accepted that this study will be important in accelerating the process of product classification which is one of the main components of agricultural marketing and classifying correctly crops.

Keywords:
agribusiness; agricultural marketing; artificial intelligence; crop classification; quality detection

HIGHLIGHTS

• Accelerating the process of product classification and to classifying correctly crops by qualities.

• Provides the opportunity to offer products in accordance with different consumer groups and market conditions.

• It is views that a very high classification result of 99.18% is accomplished by machine learning algorithms analysis values.

• This model shows that it can also be applied to other crops.