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A Literature Review on Machine Learning in The Food Industry

Author

Listed:
  • Furkan Açıkgöz
  • Leyla Zeynep Verçin
  • Gamze Erdoğan

Abstract

Machine Learning (ML) has become widespread in the food industry and can be seen as a great opportunity to deal with the various challenges of the field both in the present and near future. In this paper, we analyzed 91 research studies that used at least two ML algorithms and compared them in terms of various performance metrics. China and USA are the leading countries with the most published studies. We discovered that Support Vector Machine (SVM) and Random Forest outperformed other ML algorithms, and accuracy is the most used performance metric.

Suggested Citation

  • Furkan Açıkgöz & Leyla Zeynep Verçin & Gamze Erdoğan, 2023. "A Literature Review on Machine Learning in The Food Industry," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 11(2), pages 207-222, December.
    • Handle: RePEc:anm:alpnmr:v:11:y:2023:i:2:p:207-222
    DOI: https://doi.org/10.17093/alphanumeric.1214699
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    More about this item

    Keywords

    Classification; Food Industry; Machine Learning; Support Vector Machine;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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