Determination of the bruise degree for cherry using Vis-NIR reflection spectroscopy coupled with multivariate analysis

English version

Autoři: Yuanyuan Shao ^aff001; Guantao Xuan ^aff001; Zhichao Hu ^aff002; Zongmei Gao ^aff004; Lei Liu ^aff001
Působiště autorů: College of Mechanical and Electrical Engineering, Shandong Agricultural University, Tai’an, Shandong, China ^aff001; Nanjing Research Institute For Agricultural Mechanization, Ministry of Agriculture, Nanjing, Jiangsu, China ^aff002; College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, Missouri, United States of America ^aff003; Department of Biological Systems Engineering, Washington State University, Pullman, Washington, United States of America ^aff004
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0222633

Souhrn

Determination and classification of the bruise degree for cherry can improve consumer satisfaction with cherry quality and enhance the industry’s competiveness and profitability. In this study, visible and near infrared (Vis-NIR) reflection spectroscopy was used for identifying bruise degree of cherry in 350–2500 nm. Sampling spectral data were extracted from normal, slight and severe bruise samples. Principal component analysis (PCA) was implemented to determine the first few principal components (PCs) for cluster analysis among samples. Optimal wavelengths were selected by loadings of PCs from PCA and successive projection algorithm (SPA) method, respectively. Afterwards, these optimal wavelengths were empolyed to establish the classification models as inputs of least square-support vector machine (LS-SVM). Better performance for qualitative discrimination of the bruise degree for cherry was emerged in LS-SVM model based on five optimal wavelengths (603, 633, 679, 1083, and 1803 nm) selected directly by SPA, which showed acceptable results with the classification accuracy of 93.3%. Confusion matrix illustrated misclassification generally occurred in normal and slight bruise samples. Furthermore, the latent relation between spectral property of cherries in varying bruise degree and its firmness and soluble solids content (SSC) was analyzed. The result showed both colour, firmness and SSC were consistent with the Vis-NIR reflectance of cherries. Overall, this study revealed that Vis-NIR reflection spectroscopy integrated with multivariate analysis can be used as a rapid, intact method to determine the bruise degree of cherry, laying a foundation for cherry sorting and postharvest quality control.

Klíčová slova:

Principal component analysis – Biology and life sciences – Organisms – Eukaryota – Plants – Physical sciences – Research and analysis methods – Computer and information sciences – Mathematics – Fruits – Statistics – Mathematical and statistical techniques – Statistical methods – Physics – Spectrum analysis techniques – Classical mechanics – Reflection – Artificial intelligence – Machine learning – Support vector machines – Infrared spectroscopy – Near-infrared spectroscopy – Cherries – Apples

Zdroje

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Determination of the bruise degree for cherry using Vis-NIR reflection spectroscopy coupled with multivariate analysis

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