首页> 美国卫生研究院文献>Journal of Food Science and Technology >Application of FT-NIR spectroscopy for simultaneous estimation of taste quality and taste-related compounds content of black tea
【2h】

Application of FT-NIR spectroscopy for simultaneous estimation of taste quality and taste-related compounds content of black tea

机译:FT-NIR光谱法同时估算红茶的风味品质和与风味有关的化合物含量

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Fourier transform near-infrared spectroscopy (FT-NIR) coupled to chemometric algorithms such as back propagation (BP)-AdaBoost and synergy interval partial least square (Si-PLS) were deployed for the rapid prediction taste quality and taste-related components in black tea. Eight main taste-related components were determined via chemical analysis and Pearson correlations. The achieved chemical results of the eight taste-related components in black tea infusion were predicted based on 160 tea samples obtained from different countries. Prediction results revealed BP-AdaBoost models gave superior predictions, with all the correlation coefficients of the prediction set (Rp) > 0.76, and the root mean square error values of the prediction set (RMSEP) < 1.7% compared with Si-PLS models (0.71 ≤ Rp ≤ 0.94, 0.08% ≤ RMSEP ≤ 1.73%). This implies that FT-NIR combined to BP-AdaBoostis capable of being deployed for the rapid evaluation of black tea taste quality and taste-related components content simultaneously.Electronic supplementary materialThe online version of this article (10.1007/s13197-018-3353-1) contains supplementary material, which is available to authorized users.
机译:傅里叶变换近红外光谱(FT-NIR)结合化学计量学算法,例如反向传播(BP)-AdaBoost和协同区间偏最小二乘(Si-PLS),用于快速预测黑色中的味道质量和与味道相关的成分茶。通过化学分析和Pearson相关性确定了八个与味觉相关的主要成分。根据从不同国家获得的160个茶样品,预测了红茶中8种与味道相关的成分的化学结果。预测结果表明,与Si-PLS模型相比,BP-AdaBoost模型提供了更好的预测,预测集的所有相关系数(Rp)> 0.76,预测集的均方根误差值(RMSEP)<1.7%( 0.71≤Rp≤0.94,0.08%≤RMSEP≤1.73%。这意味着将FT-NIR与BP-AdaBoostis结合使用能够同时快速评估红茶的口感质量和与口感相关的成分含量。电子补充材料本文的在线版本(10.1007 / s13197-018-3353-1 )包含补充材料,授权用户可以使用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号