Abstract
Visible/Near-infrared reflectance spectroscopy (Vis/NIRS) was applied to variety discrimination of juicy peach. A total of 75 samples were investigated for Vis/NIRS using a field spectroradiometer. Chemometrics was used to build the relationship between the absorbance spectra and varieties. Principle component analysis (PCA) was executed to reduce numerous wavebands into 8 principle components (PCs) as variables of stepwise discrimination analysis (SDA). After execution of SDA through variables selection with 21 samples as validation set, the final results shown an excellent performance of 100% varieties discrimination which was better than the one only predicted by using partial least squares (PLS) model. The results showed the potential ability of Vis/NIRS coupled with SDA-PCA algorithm to discriminate the varieties of juicy peach. The analysis model was rapid, objective and accurate.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Li, W.J., Mckim, J.M., Martin, R.A.: Development of Near-infrared Diffuse Reflectance Spectroscopy for Rapid Screening and Authentication of Chinese Material Medical. Analytical Sciences 17, 429–442 (2001)
Steuer, B., Schulz, H., Lager, E.: Classification and Analysis of Citrus Oils by NIR Spectroscopy. Food Chemistry 72, 113–117 (2001)
He, Y., Li, X.L., Shao, Y.N.: Quantitative Analysis of the Varieties of Apple Using Near Infrared Spectroscopy by Principal Component Analysis and BP Model. In: Zhang, S., Jarvis, R.A. (eds.) AI 2005. LNCS (LNAI), vol. 3809, pp. 1053–1056. Springer, Heidelberg (2005)
Slaughter, D.C.: Non-destructive Determination of Internal Quality in Peaches and Nectarines. Transactions of the ASAE 38(2), 617–623 (1995)
He, Y., Feng, S.J., Deng, X.F., Li, X.L.: Study on Lossless Discrimination of Varieties of Yogurt Using the Visible/NIR-spectroscopy. Food Research International 39(6), 645–650 (2006)
Wold, H., Krishnaiah, P.R. (eds.): 391–420. Academic Press, New York (1966)
Ramadan, Z., Hopke, P.K., Johnson, M.J., Scow, K.M.: Application of PLS and Back-Propagation Neural Networks for Theestimation of Soil Properties. Chemometrics and Intelligent Laboratory Systems 75, 23–30 (2005)
Martens, H., Naes, T.: Mulutivariate Calibration. Wiley, New York (1998)
Fisher, R.A.: The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics 7(2), 179–188 (1936)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wu, D., He, Y., Bao, Y. (2006). Fast Discrimination of Juicy Peach Varieties by Vis/NIR Spectroscopy Based on Bayesian-SDA and PCA. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_113
Download citation
DOI: https://doi.org/10.1007/11816157_113
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37271-4
Online ISBN: 978-3-540-37273-8
eBook Packages: Computer ScienceComputer Science (R0)