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Identification of Damage in Pear Using Hyperspectral Imaging Technology by Cheng-Tao Su; Bin Li; Hai Yin; Ji-Ping Zou; Feng Zhang; Yan-De Liu is a Chemistry article available to read on EtoBox.

What is Identification of Damage in Pear Using Hyperspectral Imaging Technology about?

Crown pears are an important economic crop, but their quality and economy are seriously afected by the diferent levels of damage. To improve the overall quality of crown pears, sorting of crown pears with diferent levels of damage is required. However, there are some shortcomings in the traditional detection methods, such as low efciency and large error. Terefore, the hyperspectral technology was used to discriminate between sound and 3 diferent levels of damage (defned as level I, II, and III damage, respectively) of crown pears in this study. To improve the discriminatory accuracy of the model, absorbance (A) spectra and Kubelka-Munk (K-M) spectra were added to refectance (R) spectra. Te three spectra were pretreated; then, the partial least squares discriminant analysis (PLS-DA) model and the support vector machine (SVM) model were established to discriminate the crown pears with diferent levels of damage. Te results of the discriminant model show that the discrimination accuracy of the SVM based on R, A, and K-M spectra is higher than that of PLS-DA of them; the A-RAW-SVM model has the best discrimination performance with an overall discrimination accuracy of 100% for the test

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Author

Cheng-Tao Su; Bin Li; Hai Yin; Ji-Ping Zou; Feng Zhang; Yan-De Liu

Publisher

Hindawi Limited

Published

2022

Language

EN

Field

Chemistry (Physical Sciences)