Rice Classification and Quality Detection Success with Artificial Intelligence Technologies

被引:3
|
作者
Cinarer, Gokalp [1 ]
Erbas, Nizamettin [2 ]
Ocal, Abdurrahman [2 ]
机构
[1] Yozgat Bozok Univ, Fac Engn, Yozgat, Turkiye
[2] Yozgat Bozok Univ, Yozgat Vocat Sch, Yozgat, Turkiye
关键词
agribusiness; agricultural marketing; artificial intelligence; crop classification; quality detection;
D O I
10.1590/1678-4324-2024220754
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Digital Technologies and Artificial Intelligence Technologies in Education
    Barakina, Elena Y.
    Popova, Anna, V
    Gorokhova, Svetlana S.
    Voskovskaya, Angela S.
    EUROPEAN JOURNAL OF CONTEMPORARY EDUCATION, 2021, 10 (02): : 285 - 296
  • [22] Advances in Artificial Intelligence and Blockchain Technologies for Early Detection of Human Diseases
    Shammi, Shumaiya Akter
    Ghosh, Pronab
    Sutradhar, Ananda
    Shamrat, F. M. Javed Mehedi
    Moni, Mohammad Ali
    Oliveira, Thiago Eustaquio Alves de
    IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2025, 12 (01): : 210 - 237
  • [23] Trust and Success of Artificial Intelligence in Medicine
    Miklavcic, Jonas
    BOGOSLOVNI VESTNIK-THEOLOGICAL QUARTERLY-EPHEMERIDES THEOLOGICAE, 2021, 81 (04): : 935 - 946
  • [24] Enhancing the success of IVF with artificial intelligence
    不详
    LANCET DIGITAL HEALTH, 2023, 5 (01): : E1 - E1
  • [25] Implementation of a Fruit Quality Classification Application Using an Artificial Intelligence Algorithm
    Chen, Ming-Chih
    Cheng, Yin-Ting
    Liu, Chun-Yu
    SENSORS AND MATERIALS, 2022, 34 (01) : 151 - 162
  • [26] Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages
    Viejo, Claudia Gonzalez
    Torrico, Damir D.
    Dunshea, Frank R.
    Fuentes, Sigfredo
    BEVERAGES, 2019, 5 (04):
  • [27] Real time fruits quality detection with the help of artificial intelligence
    Priya, Punna Sai
    Jyoshna, Naga
    Amaraneni, Sireesha
    Swamy, Jagannadha
    MATERIALS TODAY-PROCEEDINGS, 2020, 33 : 4900 - 4906
  • [28] Application of artificial intelligence technologies in metallographic analysis for quality assessment in the shipbuilding industry
    Emelianov, Vitalii
    Zhilenkov, Anton
    Chernyi, Sergei
    Zinchenko, Anton
    Zinchenko, Elena
    HELIYON, 2022, 8 (08)
  • [29] Advances in artificial intelligence-based technologies for increasing the quality of medical products
    Srivastava, Nidhi
    Verma, Sneha
    Singh, Anupama
    Shukla, Pranki
    Singh, Yashvardhan
    Oza, Ankit D.
    Kaur, Tanvir
    Chowdhury, Sohini
    Kapoor, Monit
    Yadav, Ajar Nath
    DARU-JOURNAL OF PHARMACEUTICAL SCIENCES, 2024, 33 (01)
  • [30] Artificial intelligence for classification and regression tree based feature selection method for network intrusion detection system in various telecommunication technologies
    Kumar, Neeraj
    Kumar, Upendra
    COMPUTATIONAL INTELLIGENCE, 2024, 40 (01)