• Spectroscopy and Spectral Analysis
  • Vol. 31, Issue 4, 924 (2011)
YU Chun-xia1、*, MA Xiang2, ZHANG Ye-hui1, LI Jun-hui1, ZHAO Long-lian1, XU Li1, WEN Ya-dong2, WANG Yi2, and ZHANG Lu-da3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: Cite this Article
    YU Chun-xia, MA Xiang, ZHANG Ye-hui, LI Jun-hui, ZHAO Long-lian, XU Li, WEN Ya-dong, WANG Yi, ZHANG Lu-da. Tobacco Plant Parts Similarity Analysis Based on Near-Infrared Spectroscopy and SIMCA Algorithm[J]. Spectroscopy and Spectral Analysis, 2011, 31(4): 924 Copy Citation Text show less

    Abstract

    The appearance features of tobacco reflect its inner quality.Many factors, such as different plant parts, variety and maturity, provide standard and foundation for tobacco production processing.According to the different position of tobacco plant parts, tobacco plants leaves can be divided into five parts as tip, upper-middle, middle, lower-middle and priming leaf respectively.Five hundred tobacco leaf samples (100 each for one of five tobacco plant parts) from Yunnan province in 2008 were collected using near infrared spectroscopy, which all belong to tobacco varieties of K326.The similarity analysis of tobacco plant parts was carried out using mathematical model of SIMCA similarity analysis.The conclusion showed that the tobacco plant parts similarity results based on near-infrared spectroscopy corresponded to the relative tobacco plant parts in Yunnan province.The farther two tobacco plant parts were away from each other, the lower the similarity of corresponding parts was.And the similarity results of djacent tobacco plant parts were different.The study discussed a method of confirming PC numbers and realized the quantitative similarity analysis between classes.It is instructive in replacement or adjustment of tobacco leaf blending and evaluation of tobacco industrial grading.
    YU Chun-xia, MA Xiang, ZHANG Ye-hui, LI Jun-hui, ZHAO Long-lian, XU Li, WEN Ya-dong, WANG Yi, ZHANG Lu-da. Tobacco Plant Parts Similarity Analysis Based on Near-Infrared Spectroscopy and SIMCA Algorithm[J]. Spectroscopy and Spectral Analysis, 2011, 31(4): 924
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