Pattern formation of dried droplets of milk during different processes and classifying them using artificial neural networks

Abstract

Two methods, one experimental and one based on artificial intelligence/deep learning (AI/DL) are explored in this paper for possible identification of adulteration, coagulation and spoilage of dairy milk. The unique patterns formed by dairy-milk colloids under three conditions – dilution, coagulation and staling and observed using confocal laser scanning microscopy are reported here. The patterns act as a fingerprint to the various stages of coagulation/dilution/spoilage of milk colloids. A deep-learning algorithm is then applied to the patterns thus obtained, and the results of AI/DL based identification of patterns is reported here.

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