A Literature Review on Machine Learning in The Food Industry

Furkan Açıkgöz, Leyla Zeynep Verçin and Gamze Erdoğan

Alphanumeric Journal, 2023, vol. 11, issue 2, 207-222

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.

Keywords: Classification; Food Industry; Machine Learning; Support Vector Machine (search for similar items in EconPapers)
JEL-codes: C46 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:anm:alpnmr:v:11:y:2023:i:2:p:207-222

DOI: 10.17093/alphanumeric.1214699

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