title: Prediction of total viable counts on chilled pork using an electronic nose combined with support vector machine.
abstract: The aim of this study was to predict the total viable counts (TVC) in chilled pork using an electronic nose (EN) together with support vector machine (SVM). EN and bacteriological measurements were performed on pork samples stored at 4 °C for up to 10 days. Bacterial numbers on pork were determined by plate counts on agar. Principal component analysis (PCA) was used to cluster EN measurements. The model for the correlation between EN signal responses and bacterial numbers was constructed by using the SVM, combined with partial least squares (PLS). Correlation coefficients for training and validation were 0.94 and 0.88, respectively, which suggested that the EN system could be used as a simple and rapid technique for the prediction of bacteria numbers in pork.
authors.affiliation: College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China.
authors.forename: Danfeng
authors.initials: D
authors.lastname: Wang
authors.forename: Xichang
authors.initials: X
authors.lastname: Wang
authors.forename: Taiang
authors.initials: T
authors.lastname: Liu
authors.forename: Yuan
authors.initials: Y
authors.lastname: Liu
mesh_terms: D000818:Animals; D058491:Bacterial Load; D004581:Electronics / Q000295:instrumentation*; D005516:Food Microbiology; D018857:Food Packaging / Q000379:methods; D061353:Food Storage / Q000379:methods; D016018:Least-Squares Analysis; D008460:Meat / Q000382:microbiology*; D025341:Principal Component Analysis; D012034:Refrigeration; D060388:Support Vector Machine; D013552:Swine