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Hyperspectral imaging for rapid evaluation and visualization of quality deterioration index of vacuum packaged dry-cured sausages

机译:高光谱成像可快速评估和可视化真空包装干腌香肠的质量劣化指数

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摘要

A rapid and nondestructive method to evaluate and visualize quality of vacuum packaged dry-cured sausages was developed using hyperspectral imaging (HS1) spectroscopy. Changes in physicochemical, microbiological and sensory attributes of the packaged dry-cured sausages were monitored during storage at 20 ℃. Discriminant factor analysis (DFA) could classify samples into different groups as a function of storage time. The quality deterioration index (QDI) of the packaged dry-cured sausages was signified and assigned to the individual DFA classified groups. HSI spectroscopy was used to collect both spectral data in the wavelength range of 380-1000 nm and spatial data of 68 x 68 pixels. Partial least squares (PLS) regression model was constructed to establish the relationship between the HSI hypercube data and the QDI. Distribution maps of the QDI were then constructed to visualize the quality attributes of the sausages. The color distribution map of the QDI enabled the identification of different qualities of the vacuum packaged sausages as a function of storage time. The results demonstrated that the HSI coupled with chemometric and image processing techniques can be used as a rapid and nondestructive method to evaluate quality of the sausages.
机译:使用高光谱成像(HS1)光谱技术开发了一种快速,无损的方法来评估和可视化真空包装的干腌香肠的质量。在20℃的贮藏过程中,对包装的干腌香肠的理化,微生物和感官属性进行了监测。判别因子分析(DFA)可以根据存储时间将样本分为不同的组。包装好的干腌香肠的质量恶化指数(QDI)表示出来,并分配给各个DFA分类组。 HSI光谱用于收集380-1000 nm波长范围内的光谱数据和68 x 68像素的空间数据。构建偏最小二乘(PLS)回归模型以建立HSI超立方体数据与QDI之间的关系。然后构建QDI的分布图以可视化香肠的质量属性。 QDI的颜色分布图使得能够根据存储时间来识别真空包装香肠的不同质量。结果表明,结合化学计量学和图像处理技术的HSI可以用作评估香肠质量的一种快速且无损的方法。

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