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A partial least squares-based approach to assess the light penetration depth in wheat flour by near infrared hyperspectral imaging
Journal of Near Infrared Spectroscopy ( IF 1.6 ) Pub Date : 2019-12-06 , DOI: 10.1177/0967033519891594
Antoine Laborde 1, 2 , Benoît Jaillais 3 , Ryad Bendoula 4 , Jean-Michel Roger 4 , Delphine Jouan-Rimbaud Bouveresse 1 , Luc Eveleigh 5 , Dominique Bertrand 6 , Anthony Boulanger 2 , Christophe BY Cordella 1
Affiliation  

Near infrared hyperspectral imaging technique has been used for adulteration detection in food samples for several years. However, the sensor cannot screen beyond a certain material thickness. This work studies a method to determine the penetration depth of near infrared radiations in the context of detection. The case of wheat flour in a polylactic acid sample holder is investigated. A sample holder is specially designed to have the wheat flour thickness vary from 0.5 to 3.5 mm. Hyperspectral images are acquired and the partial least squares regression method is used to determine the amount of polylactic acid in each spectrum. Partial least squares prediction results are interpreted using sensor considerations and the Kubelka–Munk theory. Thereafter, the Kubelka–Munk model is fitted and the penetration depth is determined for each wavelength using the reflectance profiles. Similarities between these results and partial least squares regression coefficients lead to the conclusion that partial least squares, combined with the near infrared spectra, is able to characterize the detection depth. The value is calculated by fitting two linear models on the partial least squares prediction results. As a result, 1.80 mm is found to be the detection depth, defined as the maximum thickness of wheat flour to ensure the detection of polylactic acid through the background. Reflectance profiles also show that the penetration depth is highly dependent on the wavelength. This study aimed at providing a method that could be used to evaluate the penetration depth and the detection depth in other contexts than a polylactic acid target in wheat flour.

中文翻译:

一种基于偏最小二乘法的近红外高光谱成像评估小麦面粉透光深度的方法

近红外高光谱成像技术已被用于食品样品中的掺假检测多年。但是,传感器不能屏蔽超过一定的材料厚度。这项工作研究了一种在检测背景下确定近红外辐射穿透深度的方法。研究了聚乳酸样品架中小麦粉的情况。样品架专门设计用于小麦粉厚度从 0.5 到 3.5 毫米不等。获取高光谱图像并使用偏最小二乘回归方法确定每个光谱中聚乳酸的量。使用传感器考虑因素和 Kubelka-Munk 理论解释偏最小二乘预测结果。此后,拟合 Kubelka-Munk 模型,并使用反射率曲线确定每个波长的穿透深度。这些结果与偏最小二乘回归系数之间的相似性导致偏最小二乘结合近红外光谱能够表征检测深度的结论。该值是通过在偏最小二乘预测结果上拟合两个线性模型来计算的。结果发现1.80 mm是检测深度,定义为小麦粉的最大厚度,以确保通过背景检测聚乳酸。反射曲线还显示穿透深度高度依赖于波长。
更新日期:2019-12-06
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