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PCA-based algorithm for calibration of spectrophotometric analysers of food

机译:基于PCA的食物分光光度分析仪校准算法

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Spectrophotometric analysers of food, being instruments for determination of the composition of food products and ingredients, are today of growing importance for food industry, as well as for food distributors and consumers. Their metrological performance significantly depends of the numerical performance of available means for spectrophotometric data processing; in particular - the means for calibration of analysers. In this paper, a new algorithm for this purpose is proposed, viz. the algorithm using principal components analysis (PCA). It is almost as efficient as PLS-based algorithms of calibration, but much simpler.
机译:食物的分光光度分析仪,是用于测定食品和成分的组成的仪器,今天越来越重要,以及食品分销商和消费者。它们的计量性能显着取决于分光光度数据处理的可用方法的数值性能;特别是 - 用于校准分析仪的手段。在本文中,提出了一种新的算法,即viz。使用主成分分析(PCA)的算法。它几乎与基于PLS的校准算法一样高效,但更简单。

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