{"title":"Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopy","authors":"Jingxue Liu, J. Xin, T. Gao, Fengyi Li, Xie Tian","doi":"10.1080/19476337.2022.2128429","DOIUrl":null,"url":null,"abstract":"ABSTRACT This study attempted to measure the total polyphenols contents in Fuzhuan tea by near-infrared (NIR) spectroscopy coupled with an appropriate multivariate calibration method. Partial least squares (PLS), synergy interval PLS (si-PLS), and genetic algorithm-based PLS (ga-PLS) were carried out comparatively to calibrate regression models. The root mean square error of prediction (RMSEP), determination coefficient (Rp2), and P-value between the true and predicted values of prediction set were used to evaluate the performance of the final model. The ga-PLS model showed the best performance compared with the PLS and si-PLS models. The optimal model obtained Rp2 = 0.9996 and RMSEP = 0.0488 for the prediction set using only 37 spectral data points. No significant difference was observed between the true and predicted tea polyphenol contents in the prediction set (P > 0.05). NIR spectroscopy together with the ga-PLS algorithm can be used to rapidly predict the total polyphenol contents in Fuzhuan tea.","PeriodicalId":49084,"journal":{"name":"Cyta-Journal of Food","volume":"20 1","pages":"236 - 243"},"PeriodicalIF":2.1000,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cyta-Journal of Food","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1080/19476337.2022.2128429","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT This study attempted to measure the total polyphenols contents in Fuzhuan tea by near-infrared (NIR) spectroscopy coupled with an appropriate multivariate calibration method. Partial least squares (PLS), synergy interval PLS (si-PLS), and genetic algorithm-based PLS (ga-PLS) were carried out comparatively to calibrate regression models. The root mean square error of prediction (RMSEP), determination coefficient (Rp2), and P-value between the true and predicted values of prediction set were used to evaluate the performance of the final model. The ga-PLS model showed the best performance compared with the PLS and si-PLS models. The optimal model obtained Rp2 = 0.9996 and RMSEP = 0.0488 for the prediction set using only 37 spectral data points. No significant difference was observed between the true and predicted tea polyphenol contents in the prediction set (P > 0.05). NIR spectroscopy together with the ga-PLS algorithm can be used to rapidly predict the total polyphenol contents in Fuzhuan tea.
期刊介绍:
CyTA – Journal of Food is an Open Access journal that publishes original peer-reviewed research papers dealing with a wide range of subjects which are essential to the food scientist and technologist. Topics include: chemical analysis of food; additives and toxins in food; sensory, nutritional and physiological aspects of food; food microbiology and biotechnology; changes during the processing and storage of foods; effect of the use of agrochemicals in foods; quality control in food; and food engineering and technology.