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解析微型近红外光谱测量中的误差源:以饲料为例。

Unravelling error sources in miniaturized NIR spectroscopic measurements: The case study of forages.

机构信息

Università degli Studi dell'Insubria, Science and High Technology Department, 22100, Como, Italy.

Universitat Rovira i Virgili, Department of Analytical Chemistry and Organic Chemistry, 43007, Tarragona (Catalonia), Spain.

出版信息

Anal Chim Acta. 2022 Jun 8;1211:339900. doi: 10.1016/j.aca.2022.339900. Epub 2022 May 4.

Abstract

The use of miniaturized NIR spectrometers is spreading over the scientific literature with a particular focus on developing methods as rapid and easy-to-use as possible and following the philosophy of green analytical chemistry. Several applications and studies are typically presented by comparing results obtained with benchtop instrumentation even when the analytical strategies are substantially different. Indeed, analytical applications that include the use of miniaturized instrumentation are subject to several sources of variability that need to be known at the time of method development. In this study, different statistical strategies were employed to understand the features and limitations of handheld NIR instruments. Because of the high interest in real applications, a common type of hygroscopic powder sample was selected: forages. A step-by-step methodology is presented to statistically address the different issues to consider in order to obtain realistic models when using miniaturized NIR spectrometers. We demonstrate how a careful evaluation of the sources of variability related to an experiment can help in the understanding of the system under study in order to obtain a more reliable development of the method and consciously choose the analytical parameters and strategies of analysis. The results were also compared with those achieved on the same dataset from a benchtop system in order to provide references analogous with those in the literature.

摘要

微型近红外光谱仪的使用在科学文献中不断普及,特别注重开发尽可能快速易用且符合绿色分析化学理念的方法。尽管分析策略有很大的不同,但通常通过比较台式仪器获得的结果来呈现几个应用和研究。事实上,包括使用微型仪器在内的分析应用受到多种需要在方法开发时了解的变异性来源的影响。在这项研究中,采用了不同的统计策略来了解手持式近红外仪器的特点和局限性。由于对实际应用的高度关注,选择了一种常见的吸湿粉末样品:饲料。提出了一种逐步的方法,从统计学角度解决了在使用微型近红外光谱仪时需要考虑的不同问题,以获得现实的模型。我们展示了如何仔细评估与实验相关的变异性来源,以帮助理解研究中的系统,从而更可靠地开发方法,并有意识地选择分析参数和分析策略。还将结果与来自台式系统的相同数据集上获得的结果进行了比较,以提供与文献中类似的参考。

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