Sensory Perception Systems and Machine Learning Methods for Pesticide Detection in Fruits

• Published in: Applied sciences Vol. 14; no. 17; p. 8074
• Main Authors: Durán Acevedo, Cristhian Manuel, Cárdenas Niño, Dayan Diomedes, Carrillo Gómez, Jeniffer Katerine
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2024
• Subjects: Agriculture; Chromatography; E-nose; E-tongue; Food chains; Food quality; Food security; Food supply; fruit pesticides; Fruits; Fungicides; Insecticides; machine learning; pattern recognition; Pesticides; Poisoning; Public health; Sensors; Strawberries; Toxicity; Vegetables; Colombia

In this study, an electronic tongue (E-tongue) and electronic nose (E-nose) systems were applied to detect pesticide residues, specifically Preza, Daconil, Curzate, Bricol, Accros, Amistar, and Funlate, in fruits such as cape gooseberries, apples, plums, and strawberries. These advanced systems pres...