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Adaptable Multivariate Calibration Models for Spectral Applications

机译:光谱应用的自适应多元校准模型

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摘要

Multivariate calibration techniques have been used in a wide variety of spectroscopic situations. In many of these situations, spectral variation can be partitioned into separate classes. For example, suppose that multiple spectra are obtained from each of a number of different objects wherein the level of the analyte of interest varies within each object over time. h such situations, the total spectral variation observed across all measurements has two distinct general sources of variation: intraobject and interobject. One might want to develop a global multivari-ate calibration model that predicts the analyte of interest accurately both within and across objects, including new objects not involved in developing the calibration model. However, this goal might be hard to realize if the inter-object spectral variation is complex and difficult to model. If the intraobject spectral variation is consistent across objects, an effective alternative approach might be to develop a generic intraobject model that can be adapted to each object separately. This paper contains recom-mendations for experimental protocols and data analysis in such situations. The approach is illustrated with an example involving the noninvasive measurement of glu-onse using near-infrared reflectance speciroscopy. Exten-sions to calibration maintenance and calibration transfer are discussed.
机译:多元校准技术已用于多种光谱情况。在许多情况下,频谱变化可分为不同的类别。例如,假设从多个不同的物体中的每个物体获得了多个光谱,其中感兴趣的分析物的水平在每个物体内随时间变化。在这种情况下,在所有测量中观察到的总光谱变化具有两个不同的一般变化源:物体内和物体间。可能需要开发一种全局多元校准模型,该模型可以准确地预测对象内部和对象之间的目标分析物,包括不涉及开发校准模型的新对象。但是,如果对象间频谱变化复杂且难以建模,则可能难以实现该目标。如果对象内的光谱变化在各个对象之间是一致的,则一种有效的替代方法可能是开发可分别适用于每个对象的通用对象内模型。本文包含针对这种情况下的实验方案和数据分析的建议。举例说明该方法,该方法涉及使用近红外反射光谱法对葡萄糖进行无创测量。讨论了校准维护和校准传输的扩展。

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