title: Differentiation of Chinese robusta coffees according to species, using a combined electronic nose and tongue, with the aid of chemometrics.
abstract: Electronic nose and tongue sensors and chemometric multivariate analysis were applied to characterize and classify 7 Chinese robusta coffee cultivars with different roasting degrees. Analytical data were obtained from 126 samples of roasted coffee beans distributed in the Hainan Province of China. Physicochemical qualities, such as the pH, titratable acidity (TA), total soluble solids (TSS), total solids (TS), and TSS/TA ratio, were determined by wet chemistry methods. Data fusion strategies were investigated to improve the performance of models relative to the performance of a single technique. Clear classification of all the studied coffee samples was achieved by principal component analysis, K-nearest neighbour analysis, partial least squares discriminant analysis, and a back-propagation artificial neural network. Quantitative models were established between the sensor responses and the reference physicochemical qualities, using partial least squares regression (PLSR). The PLSR model with a fusion data set was considered the best model for determining the quality parameters.
authors.affiliation: Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, Hainan 571533, China; National Center of Important Tropical Crops Engineering and Technology Research, Wanning, Hainan 571533, China; Key Laboratory of Genetic Resources Utilization of Spice and Beverage Crops, Ministry of Agriculture, Wanning, Hainan 571533, China. Electronic address: dongwenjiang.123@163.com.
authors.forename: Wenjiang
authors.initials: W
authors.lastname: Dong
authors.affiliation: Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, Hainan 571533, China; National Center of Important Tropical Crops Engineering and Technology Research, Wanning, Hainan 571533, China; Key Laboratory of Genetic Resources Utilization of Spice and Beverage Crops, Ministry of Agriculture, Wanning, Hainan 571533, China. Electronic address: zjp-68068@163.com.
authors.forename: Jianping
authors.initials: J
authors.lastname: Zhao
authors.affiliation: Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, Hainan 571533, China; National Center of Important Tropical Crops Engineering and Technology Research, Wanning, Hainan 571533, China. Electronic address: hnhrs@126.com.
authors.forename: Rongsuo
authors.initials: R
authors.lastname: Hu
authors.affiliation: Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, Hainan 571533, China; Key Laboratory of Genetic Resources Utilization of Spice and Beverage Crops, Ministry of Agriculture, Wanning, Hainan 571533, China. Electronic address: 437433465@qq.com.
authors.forename: Yunping
authors.initials: Y
authors.lastname: Dong
authors.affiliation: Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wanning, Hainan 571533, China; National Center of Important Tropical Crops Engineering and Technology Research, Wanning, Hainan 571533, China; Key Laboratory of Genetic Resources Utilization of Spice and Beverage Crops, Ministry of Agriculture, Wanning, Hainan 571533, China. Electronic address: tlh3687@163.com.
authors.forename: Lehe
authors.initials: L
authors.lastname: Tan
mesh_terms: D002681:China; D040503:Coffea / Q000737:chemistry* / Q000235:genetics; D003069:Coffee / Q000737:chemistry* / Q000235:genetics; D016002:Discriminant Analysis; D062609:Electronic Nose / Q000706:statistics & numerical data*; D016571:Neural Networks, Computer; D025341:Principal Component Analysis; D013045:Species Specificity
chemical_list: D003069:Coffee
keywords: Chemometrics; Classification; Coffee; Data fusion; Electronic nose; Electronic tongue