Comparing visible and near infrared ‘point’ spectroscopy and hyperspectral imaging techniques to visualize the variability of apple firmness
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy(2024)
摘要
In this work, visible and near-infrared ‘point’ (Vis-NIR) spectroscopy and hyperspectral imaging (Vis-NIR-HSI) techniques were applied on three different apple cultivars to compare their firmness prediction performances based on a large intra-variability of individual fruit, and develop rapid and simple models to visualize the variability of apple firmness on three apple cultivars. Apples with high degree of intra-variability can strongly affect the prediction model performances. The apple firmness prediction accuracy can be improved based on the large intra-variability samples with the coefficient variation (CV) values over 10%. The least squares-support vector machine (LS-SVM) models based on Vis-NIR-HSI spectra had better performances for firmness prediction than that of Vis-NIR spectroscopy, with the with the Rc2 over 0.84. Finally, The Vis-NIR-HSI technique combined with least squares-support vector machine (LS-SVM) models were successfully applied to visualize the spatial the variability of apple firmness.
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关键词
Apple firmness,Hyperspectral imaging,Visible and near-infrared spectroscopy,Intra-variability,Least squares-support vector machine,Visualization
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