{"title":"变量选择及近红外光谱法快速测定福专茶中茶多酚含量的影响","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":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"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\":null,\"pages\":null},\"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}","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}
Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopy
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.