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利用近红外高光谱数据和化学计量学对非活性整粒大麦、小麦和高粱的特性进行分析。

Characterisation of non-viable whole barley, wheat and sorghum grains using near-infrared hyperspectral data and chemometrics.

机构信息

Department of Food Science, Stellenbosch University, Private Bag X1, Matieland, (Stellenbosch) 7602, South Africa.

出版信息

Anal Bioanal Chem. 2011 Oct;401(7):2283-9. doi: 10.1007/s00216-011-5291-x. Epub 2011 Aug 13.

Abstract

Undesired germination of cereal grains diminishes process utility and economic return. Pre-germination, the term used to describe untimely germination, leads to reduced viability of a grain sample. Accurate and rapid identification of non-viable grain is necessary to reduce losses associated with pre-germination. Viability of barley, wheat and sorghum grains was investigated with near-infrared hyperspectral imaging. Principal component analyses applied to cleaned hyperspectral images were able to differentiate between viable and non-viable classes in principal component (PC) five for barley and sorghum and in PC6 for wheat. An OH stretching and deformation combination mode (1,920-1,940 nm) featured in the loading line plots of these PCs; this water-based vibrational mode was a major contributor to the viable/non-viable differentiation. Viable and non-viable classes for partial least squares-discriminant analysis (PLS-DA) were assigned from PC scores that correlated with incubation time. The PLS-DA predictions of the viable proportion correlated well with the viable proportion observed using the tetrazolium test. Partial least squares regression analysis could not be used as a source of contrast in the hyperspectral images due to sampling issues.

摘要

谷物的不良发芽会降低加工利用率和经济回报。发芽前(pre-germination)是指过早发芽,会导致谷物样本的活力降低。准确快速地识别无活力的谷物对于减少发芽前的损失是必要的。利用近红外高光谱图像研究了大麦、小麦和高粱谷物的活力。对清洗后的高光谱图像进行主成分分析,可在主成分(PC)五区分大麦和高粱的有活力和无活力类别,在 PC6 区分小麦的有活力和无活力类别。在这些 PC 的加载线图中,出现了一个 OH 伸缩和变形组合模式(1920-1940nm);这种基于水的振动模式是区分有活力/无活力的主要因素。偏最小二乘判别分析(PLS-DA)的有活力和无活力类别是根据与培养时间相关的 PC 得分来分配的。PLS-DA 对有活力比例的预测与使用四唑测试观察到的有活力比例高度相关。由于采样问题,偏最小二乘回归分析不能作为高光谱图像的对比度源。

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