12 October 2007 Discrimination of planting area of white peach based near-infrared spectra and chemometrics methods
Author Affiliations +
White peach is a famous peach variety for its super-quality and high economic benefit. It is originally planted in Yuandong Villiage, Jinhua County, Zhejiang province. By now, it has been planted in many other places in southeast of China. However, peaches from different planting areas have dissimilar quality and taste, which result in different selling price. The objective of this research was to discriminate peaches from different planting areas by using near-infrared (NIR) spectra and chemometrics methods. Diffuse reflectance spectra were collected by a fiber spectrometer in the range of 800-2500 nm. Discriminant analysis (DA), soft independent modeling of class analogy (SIMCA), and discriminant partial least square regression (DPLS) methods were employed to classify the peaches from three planting areas 'Jinhua', 'Wuyi', and 'Yongkang' of Zhejiang province. 360 samples were used in this study, 120 samples per planting area. The classifying correctness were above 92% for both DA and SIMCA mdoels. And the result of DPLS model was slightly better. By using DPLS method, two 'Jinhua' peaches, three 'Wuyi' peaches, and three 'Yongkang' peaches were misclassified, the accruacy was above 95%. The results of this study indicate that the three chemometrics methods DA, SIMCA, and DPLS are effective for discriminating peaches from different planting areas based on NIR spectroscopy.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaping Fu, Xiaping Fu, Yibin Ying, Yibin Ying, Ying Zhou, Ying Zhou, Huirong Xu, Huirong Xu, Lijuan Xie, Lijuan Xie, Xuesong Jiang, Xuesong Jiang, "Discrimination of planting area of white peach based near-infrared spectra and chemometrics methods", Proc. SPIE 6761, Optics for Natural Resources, Agriculture, and Foods II, 676111 (12 October 2007); doi: 10.1117/12.733273; https://doi.org/10.1117/12.733273

Back to Top