Open AccessQualitative Determination of Pesticide Residues in Purple Cabbage Based on Near Infrared Spectroscopy
Author(s) -
Min Li,
Linju Lu,
Xiaoxin Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1884/1/012015
Subject(s) - pesticide residue , pesticide , avermectin , chemistry , support vector machine , qualitative analysis , agronomy , biology , artificial intelligence , computer science , qualitative research , anatomy , social science , sociology
A qualitative detection model of pesticide residues based on near infrared spectroscopy and support vector machine (SVM) classification is proposed in this paper. The model was used to identify the pesticide free purple cabbage and pesticide containing purple cabbage. Cypermethrin, matrine and avermectin were selected respectively, and the ratio of pesticide and water was 1:100. The correct rates of classification and identification were 90%, 100% and 100%, respectively. The experimental results show that the model has high accuracy and universality for qualitative analysis of pesticide residues in purple cabbage. This paper presents an effective method for rapid and nondestructive detection of pesticide residues in vegetables.