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Identification of Cold Spots Using Non-Destructive Hyperspectral Imaging Technology in Model Food Processed by Coaxially Induced Microwave Pasteurization and Sterilization

机译:使用非破坏性高光谱成像技术对模型食品中的同轴诱导微波巴氏杀菌和灭菌过程中的冷点进行识别

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摘要

The model food in this study known as mashed potato consisted of ribose (1.0%) and lysine (0.5%) to induce browning via Maillard reaction products. Mashed potato was processed by Coaxially Induced Microwave Pasteurization and Sterilization (CiMPAS) regime to generate an F0 of 6–8 min and analysis of the post-processed food was done in two ways, which included by measuring the color changes and using hyperspectral data acquisition. For visualizing the spectra of each tray in comparison with the control sample (raw mashed-potato), the mean spectrum (i.e., mean of region of interest) of each tray, as well as the control sample, was extracted and then fed to the fitted principal component analysis model and the results coincided with those post hoc analysis of the average reflectance values. Despite the presence of a visual difference in browning, the Lightness (L) values were not significantly ( < 0.05) different to detect a cold spot among a range of 12 processed samples. At the same time, hyperspectral imaging could identify the colder trays among the 12 samples from one batch of microwave sterilization.
机译:本研究中的模型食品称为土豆泥,由核糖(1.0%)和赖氨酸(0.5%)组成,可通过美拉德反应产物引起褐变。土豆泥通过同轴诱导微波巴氏杀菌和灭菌(CiMPAS)方案进行处理,以产生6-8分钟的F0,并通过两种方法对后处理食品进行分析,包括测量颜色变化和使用高光谱数据采集。为了可视化每个托盘与对照样品(生土豆泥)的光谱,提取每个托盘以及对照样品的平均光谱(即感兴趣区域的平均值),然后将其送入拟合主成分分析模型,结果与事后对平均反射率值的分析相吻合。尽管在褐变方面存在视觉差异,但在12个经过处理的样品范围内,检测到冷点的明度(L)值没有显着差异(<0.05)。同时,高光谱成像可以从一批微波灭菌中识别出12个样品中较冷的样品盘。

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