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Monitoring chlorophyll during Tencha (the raw ingredient for matcha) processing is critical for determining the matcha's color and quality. The purpose of this study is to explore the mechanism of chlorophyll changes during Tencha processing and evaluate the viability of predicting its content by a portable near-infrared (NIR) spectrometer. The Tencha samples' spectral data were first preprocessed using various preprocessing techniques. Subsequently, iteratively variable subset optimization (IVSO), bootstrapping soft shrinkage (BOSS), and competitive adaptive reweighted sampling (CARS) were used to optimize and build partial least square (PLS) models. The CARS-PLS models achieved the best predictive accuracy, with correlation coefficients of prediction (Rp) = 0.9204 for chlorophyll a, Rp = 0.9282 for chlorophyll b, and Rp = 0.9385 for total chlorophyll. These findings suggest that NIR spectroscopy could be used as a surrogate for immediate quantification and monitoring of chlorophyll during Tencha processing. Copyright © 2023 Elsevier Ltd. All rights reserved.


Lihua Liu, Muhammad Zareef, Zhen Wang, Haoquan Li, Quansheng Chen, Qin Ouyang. Monitoring chlorophyll changes during Tencha processing using portable near-infrared spectroscopy. Food chemistry. 2023 Jun 30;412:135505

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PMID: 36716622

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