Application of Machine Learning for Detection of Food Spoilage

Food spoilage is a problem that has affected all of humanity since its existence, as the affected food either has undesirable odor or taste characteristics, or consumption is harmful to health. The signs of spoilage are sometimes difficult or impossible to detect by humans and can only be identified by special instruments and analytical methods. Machine learning could optimize existing methods here or enable completely new approaches. In this paper the current state of research regarding the application of machine learning methods for the detection of food spoilage is investigated based on a review of pertinent literature. The research shows that machine learning is used in combination with a wide variety of analysis techniques and provides good predictive performance.