A Qualitative Analysis of the Machine Learning Methods in Food Adultery: A Focus on Milk Adulteration Detection

V. Surya and A. Senthilselvi

Food adultery is the process where the quality is compromised by adding certain chemicals or other substitutions which when consumed causes health hazards. The process includes not only the purposeful addition of additives but also the contamination occurring in growing stage, storage and when distributed. Adulteration has become a big business. We belong to a land where our ancestors taught that “food is medicine”. Milk is one of the important foods consumed irrespective of age that ranges from infants till old people. On the contrast, in recent business era, milk is getting adulterated in more complicated ways that bypass the normal tests and hence there is a huge demand for a cutting-edge technology for detecting the same. Application of Artificial Intelligence has emerged in many diverse fields not limiting to identification of food adulteration. This paper gives a gist of most important and significant researches that are carried on in the detection of adulterated food, particularly milk using the techniques of machine learning. A special attention is kept on the Machine Learning techniques that are designed specifically to detect the milk adulteration.

Volume 12 | Issue 7

Pages: 543-551

DOI: 10.5373/JARDCS/V12I7/20202037