title: [Study on the projection method based on principal component of tobacco near-infrared spectrum and application in redrying model].
abstract: The present paper briefly describes the application of near-infrared spectroscopy technology in tobacco. Two methods for solving projection vector based on the principal component of near-infrared spectrum are reported. They are named as projection of basing on principal component and Fisher criterion by principal component analysis method (PPF_PCA for short) and projection of basing on principal component and Fisher criterion by solving eigenvalue (PPF_Eig for short), and they are studied and compared in the application and evaluation of the redrying model. The result of the first-dimensional projection on 9 kinds of tobacco leaf grading samples shows that, the diversity of the first-dimensional projection values of inter-class and intra-class by the PPF_PCA method is both larger than that by the PPF_Eig method, and the mean absolute deviation of the mean projection values of inter-class by the PPF_PCA method is about 1.26 times that of the PPF_Eig method. At the same time, this result is interpreted by using the contribution rate of the first-dimensional projection values. That is, the contribution rate of first-dimensional projection values by the PPF_PCA method is 93%, while the contribution rate of first-dimensional projection values by the PPF_Eig method is 77%. The former is about 1.21 times the later. Therefore, the first-dimensional projection values by PPF PCA method include more information of diversity of both inter-class and intra-class. The similarity of samples inter-class and the diversity of samples intra-class can be evaluated more objectively from first-dimensional projection figure(on 9 kinds of tobacco leaf grading samples, 33 kinds of tobacco leaf grading samples and 6 redrying blending models), so it is more convenient to be used as a reference for the redrying model of tobacco, and it has a good application prospect in other formulation design of agricultural products (traditional Chinese medicine etc.).
authors.affiliation: College of Information and Electrical Engineering, China Agricultural University, Beijing 100193, China. 52zz25@163.com
authors.forename: Shuai
authors.initials: S
authors.lastname: Tao
authors.forename: Xiang
authors.initials: X
authors.lastname: Ma
authors.forename: Jun-Hui
authors.initials: JH
authors.lastname: Li
authors.forename: Wen-Juan
authors.initials: WJ
authors.lastname: Zhang
authors.forename: Long-Lian
authors.initials: LL
authors.lastname: Zhao
authors.forename: Ya-Dong
authors.initials: YD
authors.lastname: Wen
authors.forename: Yi
authors.initials: Y
authors.lastname: Wang
authors.forename: Lu-Da
authors.initials: LD
authors.lastname: Zhang
mesh_terms: D018515:Plant Leaves / Q000145:classification; D025341:Principal Component Analysis; D019265:Spectroscopy, Near-Infrared; D014026:Nicotiana / Q000145:classification*