首页> 外文期刊>Dynamic Chiropractic >Determination of catechin as main bioactive component of gambir (Uncaria gambir Roxb) by FT-NIR Spectroscopy
【24h】

Determination of catechin as main bioactive component of gambir (Uncaria gambir Roxb) by FT-NIR Spectroscopy

机译:FT-NIR光谱法测定儿茶素作为甘比尔(Uncaria gambir Roxb)的主要生物活性成分

获取原文
获取外文期刊封面目录资料

摘要

Catechin, an abundant component within gambir, is the main determinant of gambir quality. The general method to determine catechin is time consuming, costly and produces chemical residual. The objective of this study was to develop NIR calibration model which could be used to predict catechin content of gambir efficiently. Calibration model was established using partial least square (PLS) algorithm by investigating 3 different pre-treatment methods which were normalization between 0 and 1 (n01) first derivative Savitzky-Golay 9 points (dg1) and n01 in combination with dg1 (n01, dg1). Determination of optimum factors number was conducted based on predicted residual error sum square in validation set (V-set PRESS) values and consistency. This study found that pre-treatment n01, dg1 was the best method to produce calibration model. Quality of the best model was shown by (1) high coefficient correlation (r) = 0.91, (2) low standard error of calibration set (SEC) = 2.53% and standard error of validation set (SEP) = 2.44%, (3) slight difference between SEC and SEP. This study demonstrated that FT-NIR spectroscopy could be used as a tool for predicting the catechin content in gambir. It could replace expensiveness and time as well as effort consuming reference method.
机译:儿茶素是甘比尔内的丰富成分,是甘比尔质量的主要决定因素。确定儿茶素的一般方法耗时,昂贵且会产生化学残留物。这项研究的目的是开发可用于有效预测甘比尔中儿茶素含量的NIR校准模型。使用偏最小二乘(PLS)算法,通过研究3种不同的预处理方法建立校准模型,这些方法在0和1(n01)一阶导数Savitzky-Golay 9点(dg1)和n01之间与dg1(n01,dg1)进行标准化)。最佳因子数的确定是基于验证集(V-set PRESS)值和一致性中的预测残余误差和平方进行的。这项研究发现,预处理n01,dg1是产生校正模型的最佳方法。最佳模型的质量由(1)高系数相关性(r)= 0.91,(2)校正组的低标准误差(SEC)= 2.53%和验证组的标准误差(SEP)= 2.44%,(3 )与SEC和SEP之间的细微差别。这项研究表明,FT-NIR光谱可以用作预测甘布兰中儿茶素含量的工具。它可以取代昂贵,费时和费力的参考方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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