caa a22 4500 463157699 CHVBK 20180406164739.0 cr unu---uuuuu 170326e20070301xx s 000 0 eng 10.1007/s00217-006-0342-9 doi (NATIONALLICENCE)springer-10.1007/s00217-006-0342-9 A new approach to discriminate varieties of tobacco using vis/near infrared spectra [Elektronische Daten] [Yongni Shao, Yong He, Yanyan Wang] Vis/near infrared reflectance spectroscopy appears to be a rapid and convenient non-destructive technique that can measure the quality and compositional attributes of many substances. Principal component analysis (PCA), which offered a qualitative analysis of tobacco samples, was used to analyze the clustering of tobacco samples. A new method combined wavelet transform (WT) with Artificial Neural Network (ANN) was presented to establish a discrimination model. The model regarded the compressed spectra data as the input of ANN, and 80 samples were selected randomly as calibration collection whereas the remaining 20 were being prediction collection. High correlation coefficient (r=0.999) was achieved, which was better than PCA-SRA-ANN and PLS-ANN. It indicated that WT combined with ANN is an available method for variety discrimination based on the Vis/NIR spectroscopy technology. Some sensitive wave bands were also analyzed to develop tobacco varieties discrimination apparatus through PLS models. Springer-Verlag, 2006 Vis/near infrared spectra nationallicence Tobacco nationallicence Principal component analysis (PCA) nationallicence Wavelet transform (WT) nationallicence Artificial neural network (ANN) nationallicence PLS-ANN nationallicence Shao Yongni College of Biosystems Engineering and Food Science, Zhejiang University, 310029, Hangzhou, China aut He Yong College of Biosystems Engineering and Food Science, Zhejiang University, 310029, Hangzhou, China aut Wang Yanyan College of Biosystems Engineering and Food Science, Zhejiang University, 310029, Hangzhou, China aut European Food Research and Technology Springer-Verlag 224/5(2007-03-01), 591-596 1438-2377 224:5<591 2007 224 217 https://doi.org/10.1007/s00217-006-0342-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00217-006-0342-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Shao Yongni College of Biosystems Engineering and Food Science, Zhejiang University, 310029, Hangzhou, China aut NATIONALLICENCE 700 1- He Yong College of Biosystems Engineering and Food Science, Zhejiang University, 310029, Hangzhou, China aut NATIONALLICENCE 700 1- Wang Yanyan College of Biosystems Engineering and Food Science, Zhejiang University, 310029, Hangzhou, China aut NATIONALLICENCE 773 0- European Food Research and Technology Springer-Verlag 224/5(2007-03-01), 591-596 1438-2377 224:5<591 2007 224 217 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer