Spectroscopy and machine learning in food processing survey

Abstract

For food safety, quality control from the foodstuff production to the tasting of foods is needed and should be simple and non-destructive. Recent and notable non-destructive measurements of food and agricultural products are based on optical and spectroscopic techniques. Spectroscopy, meets the requirements of industrial applications for continuous quality control and process monitoring. Hence, this article covers a survey of recent research works, highlighting the application of spectroscopy and machine learning in food processing from bibliographic database. The survey was based on relevant articles, obtained from scientific database and evaluated selected research works based on survey inquires, the assessment included food processing problem addressed (varieties classification, origin identification, adulteration and quality control), types of spectroscopy used, machine learning models applied to solve the particular problem and keyword analysis to show the perspective of the research.