摘要
应用近红外光谱(NIR)和偏最小二乘法(PLS),建立了北虫草中虫草素的定量分析校正模型。分别采集北虫草子实体的近红外光谱图,应用TQ化学计量学分析软件,对不同化学计量学处理方法进行了比较,并对光谱区域,光谱预处理方法,主成分因子数进行筛选。依据预测效果确定了最佳的校正模型,虫草素含量的预测结果与HPLC检测结果的相关系数为0.9919,校正模型的定标均方差(RMSEC)为102 mg/kg、预测均方差(RMSEP)为281 mg/kg。本方法操作简便,快速无损,可用于北虫草中虫草素含量的快速检测。
The quantification model of determining the content of cordycepin in Cordyceps militaris was established by using near-infrared spectroscopy( NIR) combined with a partial least square( PLS) method. The comparison of principle component regression( PCR) and PLS,selection of spectroscopy wavenumber region and principal component factor number were studied.The best model was selected according to the prediction effect.The correlation coefficients of prediction,the root mean square error of calibration( RMSEC) and the root-mean-square error of prediction( RMSEP) of the model were 0.9919,102 mg/kg,281 mg/kg respectively. The proposed methods are simple,convenient,fast,and can be applied for detection of cordycepin in Cordyceps militaris.
出处
《食品工业科技》
CAS
CSCD
北大核心
2017年第14期16-19,共4页
Science and Technology of Food Industry
基金
国家重点研发计划(2016YFD0401201)
沈阳市科技计划项目(F14-198-4-00)
关键词
近红外光谱
北虫草
虫草素
偏最小二乘法(PLS)
主成分回归(PCR)
near-infrared spectroscopy(NIR)
cordycepin
Cordyceps militaris
partial least square(PLS)
principal component regression(PCR)