Python based portable system for fast characterisation of foods based on spectral analysis

Abstract

Global population has quadrupled over the last century, determining an increase in food demand and food production. Food quality has a huge impact in the quality of our health and well-being. Moreover, in recent years has developed a lot of interest due to the new scientific discoveries. Food quality is nowadays not just a regulated by legislation, but a way of life. Evolution of technology made possible integration of food quality processes with spectrometry and artificial intelligence. The quality of results and time consumption are fundamental when discussing about food conditions. Portability is essential in food quality control outside of factories. In this paper, we propose a portable system, using Jetson TX2 Module, that can identify the spectral component of four classes for this study case. Coffee and purées have been chosen, to determine their class, using machine learning algorithms.