title: [Study on the detection and pattern classification of pesticide residual on vegetable surface by using visible/near-infrared spectroscopy].
abstract: A nondestructive testing based on visible/near-infrared reflectance spectroscopy was put forward for the common high pesticide residues of green plants in the wavelength range from 600 to 1100 nm. Firstly, spectral features were extracted by wavelet transform from original spectral data. Secondly, the principal component analysis (PCA) was done in the further analysis of spectral characteristics. Thirdly, the two PCs were applied as inputs of artificial neural network, and a multi-neuron perceptron neural network was established. Finally, It was proved that the type of pesticide residues was effectively identified and showed by classification results. In short, the study provides a new approach to the detection of pesticide residues in vegetables and fruits.
authors: Institute of Science and Technology for Optoelectronic Information, Yantai University, Yantai, China. chenruisky@126.com
authors: Rui
authors: R
authors: Chen
authors: Jun
authors: J
authors: Zhang
authors: Xiao-long
authors: XL
authors: Li
mesh_terms: D005506:Food Contamination / Q000032:analysis*; D016571:Neural Networks, Computer; D010573:Pesticide Residues / Q000032:analysis*; D025341:Principal Component Analysis; D019265:Spectroscopy, Near-Infrared; D014675:Vegetables
chemical_list: D010573:Pesticide Residues