Agradecimentos: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 88887.513974/2020-00 to A.N.O. and 88887.636115/2021-00 to G.M.S; and São Paulo Research Foundation (FAPESP) (2019/05718-3 to J.D) Ver menos

Abstract: Food safety and quality assessment mechanisms are unmet needs that industries and countries have been continuously facing in recent years. Our study aimed at developing a platform using Machine Learning algorithms to analyze Mass Spectrometry data for classification of tomatoes on organic and non-organic. Tomato samples were analyzed using silica gel plates and direct-infusion electrospray-ionization mass spectrometry technique. Decision Tree algorithm was tailored for data analysis. This model achieved 92% accuracy, 94% sensitivity and 90% precision in determining to which group each fruit belonged. Potential biomarkers evidenced differences in treatment and production for each group Ver menos