Early detection of contamination and defect in foodstuffs by electronic nose: A review

Article ID	Journal	Published Year	Pages	File Type
5141522	TrAC Trends in Analytical Chemistry	2017	50 Pages	PDF

Abstract

Electronic nose (e-nose) has emerged as a potential instrument in various areas of food safety assessment for rapid early detection of contamination and defect in food production chain. E-nose is an innovative measurement system designed for detecting and discriminating complex odors through mimicking the working mechanism and the principal building blocks of the mammalian olfactory system. This paper describes a literature update of the applications of the e-nose for ensuring health and safety in the food industry. Finally, its future trend, perspectives and challenging problem are also mentioned.

Keywords

PNN MLR RBF NFs MLP KNN DFA PLS Fnn ICA ANN LVQ WNN FIS Neuro fuzzy system FCM k-Nearest Neighbors PCA SOM Cluster analysis Genetic algorithm Foodborne illness Electronic nose Adaptive resonance theory multivariate pattern analysis Independent component analysis Linear discriminant analysis Discriminant analysis Discriminant function analysis Principal component analysis LDA SPR Partial least squares Self Organizing Map Multiple linear regression principal component regression Fuzzy inference systems Probabilistic neural network Fuzzy neural network Artificial Neural Network Wavelet neural network Supervised pattern recognition mass spectrometer Radial basis function Fuzzy C-Means Support vector machine SVM Learning vector quantization ART PCR Multilayer perceptron Gas chromatography quality control