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- W2050184394 abstract "The use of Fourier transform near infrared spectrometry (FT-NIR) was explored as a toolto discriminate the pear samples of three different varieties (Xueqing, Cuiguan and Xizilv) whichwere mainly planted in Zhejiang province, China. Discriminant models were developed usingdiscriminant principal component regression (PCR) and partial least squares (PLS) regression, anddiscriminant analysis (DA) in three NIR spectral regions, respectively. 240 samples (80 samples ofeach variety) were separated into two sets: half for calibration and the remaining half for validation.Both PLS and DA calibration models developed in the region of 800-2500 nm gave high accuracy ofclassification for the calibration set, 100% samples were correctly classified. For validation, Cuiguanpears were classified correctly in 100% of cases, Xueqing and Xizilv were both 97.5% correctlyclassified (one sample of each variety misclassified) based on PLS discriminant mode. The validationresult based on DA model was still 100% correctly classified for each variety. The results of thisstudy indicated that FT-NIR had great potential for discriminating different varieties of fruits withoutdetection depending on chemical components." @default.
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- W2050184394 date "2006-01-01" @default.
- W2050184394 modified "2023-10-16" @default.
- W2050184394 title "Study on the Discrimination of Pear Variety by Using Near Infrared Spectroscopy" @default.
- W2050184394 doi "https://doi.org/10.13031/2013.21531" @default.
- W2050184394 hasPublicationYear "2006" @default.
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