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Comparison of chemometrics methods for assessing internal quality of pears on-line using visible/near infrared transmission technique
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.orgCitation: Food Processing Automation Conference Proceedings, 28-29 June 2008, Providence, Rhode Island 701P0508cd.
Authors: Tong Sun, Yibin Ying, Kuiwu Liu, Huirong Xu
Keywords: Keywords: visible/near infrared spectroscopy; internal quality; pear; on-line
Abstract: The objective of this research was to compare different chemometrics methods to assess internal quality of pears such as soluble solid content (SSC) and acidity (pH) on-line. Transmission spectra were collected by a fiber spectrometer in the wavelength range of 345~1040 nm, and the moving speed of fruits was 0.5 m s-1. Spectral pre-processing including derivative, standard normal variate transformation (SNV), multiplicative scatter correction (MSC) was used before calibration. Chemometrics methods such as stepwise multiple linear regression (SMLR), principal component regression (PCR), partial least squares (PLS), artificial neural networks (ANN) and least squares support vector machines (LS-SVM) were compared. The results show that Vis/NIR spectroscopy is feasible for measuring SSC and pH value of pears on-line, PLS and LS-SVM methods are superior to other methods for assessing internal quality of pears.