Abstract
Artificial neural networks (ANN) combined with PCA are being used in a growing number of applications. In this study, the fingerprint wavebands of apple were got through principal component analysis (PCA). 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 varieties of apple. The several variables compressed by PCA were applied as inputs to a back propagation neural network with one hidden layer. This BP 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 a PCA-BP model can be used to exactly distinguish the varieties of apple.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Suqin, S., Junming, T., Zimin, Y.: FTIR and Classification Study on Trueborn Tuber Dioscoreae Samples. Spectroscopy and Spectral Analysis 23(2), 258–261 (2003)
Wei, Y., Kelan, Y.: Study on the Characteristic and Significance of Capsaicinoid. Food Science 24(11), 105–108 (2003)
Sihong, W., Qifan, Y., Yanling, F.: Identification Studies of Wild and Cultivated Rhodiola Saccharinensis A. Bor and Rhodiola Angusta Nakai Taken from Changbai Mountains by Fourier Transform Infrared Spectrometry. Spectroscopy and Spectral Analysis 24(8), 957–959 (2004)
Savitzky, A., Golay, M.J.E.: Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Analytical Chem., 1627–1639 (1964)
Xiaoming, Q., Luda, Z., Xiaolin, D.: Quantitative Analysis Using NIR by Building PLS-BP Model. Spectroscopy and Spectral Analysis 23(5), 870–872 (2003)
Rich, E., Knight, K.: Connectionist Models. In: Shapiro, D.M., Murphy, J.F. (eds.) Artificial Intelligence, pp. 487–519. McGraw HillBook Co., Singapore (1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
He, Y., Li, X., Shao, Y. (2005). Quantitative Analysis of the Varieties of Apple Using Near Infrared Spectroscopy by Principal Component Analysis and BP Model. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_139
Download citation
DOI: https://doi.org/10.1007/11589990_139
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30462-3
Online ISBN: 978-3-540-31652-7
eBook Packages: Computer ScienceComputer Science (R0)