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Proceedings Paper

Discrimination of varieties of apple using near infrared spectroscopy
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Paper Abstract

A new method for discrimination of apple varieties by means of infrared spectroscopy (NIRS) was developed. First, the characteristic spectra of apple were got through principal component analysis (PCA), the analysis suggested that the cumulative reliabilities of PC (principal component)1 and PC2 was more than 98%. The 2-dimensions plot was drawn with the scores of the first and the second principal components; it appeared to provide the best clustering of the vaneties of apple. PCA compressed thousands of spectral data into several variables that described the body of spectra; the several variables were applied as inputs to a back propagation neural network with one hidden layer. 75 samples with three varieties were selected randomly, then they were used to build BP-ANN model. This model had been used to predict the varieties of 15 unknown samples; the recognition rate of 100% was achieved. This model is reliable and practicable. So this paper could offer a new approach to the fast discrimination of apple varieties methods.

Paper Details

Date Published: 27 October 2006
PDF: 7 pages
Proc. SPIE 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine, 604727 (27 October 2006); doi: 10.1117/12.710930
Show Author Affiliations
Yong He, Zhejiang Univ. (China)
Xiaoli Li, Zhejiang Univ. (China)
Yongni Shao, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 6047:
Fourth International Conference on Photonics and Imaging in Biology and Medicine
Kexin Xu; Qingming Luo; Da Xing; Alexander V. Priezzhev; Valery V. Tuchin, Editor(s)

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