Rice Classification and Quality Detection Success with Artificial Intelligence Technologies

Creative Commons License

Çınarer G., Erbaş N., Öcal A.

BRAZILIAN ARCHIVES OF BIOLOGY AND TECHNOLOGY, cilt.67, sa.1, ss.1-14, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 67 Sayı: 1
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1590/1678-4324-2024220754
  • Dergi Adı: BRAZILIAN ARCHIVES OF BIOLOGY AND TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Animal Behavior Abstracts, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Veterinary Science Database, Directory of Open Access Journals
  • Sayfa Sayıları: ss.1-14
  • Yozgat Bozok Üniversitesi Adresli: Evet

Özet

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.