摘要
目的研究基于中红外光谱(mid infrared spectroscopy,MIRS)技术定性判别有机微量元素添加剂掺假的可行性。方法以甘氨酸铁螯合物和硫酸亚铁为研究对象,分析样品的中红外光谱,解析不同样品光谱的特异性;建立偏最小二乘判别(partial least squares discriminant analysis,PLS-DA)校正模型对掺假样品进行判别,并比较不同预处理方法、全光谱与特征波段对校正模型判别效果的影响。结果甘氨酸铁螯合物与硫酸亚铁光谱差异显著,主要分布在(3500~3000)cm^-1、(1600~1300)cm^-1、(1300~1000)cm^-1、(660~550)cm^-1,通过采用平滑(smoothing,SM)、归一化(normalization,Norm)与一阶导数(first derivative,FD)相结合的方法对光谱进行预处理,结合1300 cm^-1~1000 cm^-1波段建立的PLS-DA校正模型判别效果最优,校正集的判别正确率为97.5%,验证集的判别正确率为100.0%,对外部样品的判别正确率达到92.7%。结论中红外光谱技术结合化学计量学方法能够对甘氨酸铁螯合物的掺假进行准确判别。
Objective To study the feasibility of qualitative identification of adulteration of organic trace element additives based on mid infrared spectroscopy(MIRS).Methods Taking glycine chelate iron and ferrous sulfate as research objects,the middle infrared spectra of samples were analyzed,and the specificity of the spectra of different samples was analyzed.A partial least squares discriminant analysis(PLS-DA)calibration model was established to discriminate adulterated samples,and the effects of different pretreatment methods,full spectrum and feature bands on the discriminant effect of the calibration model were compared.Results The spectra of ferrous glycine chelate and ferrous sulfate were significantly different,mainly ranging from(3500-3000)cm^-1,(1600-1300)cm^-1,(1300-1000)cm^-1,(660-550)cm^-1.The spectra were preprocessed by smoothing(SM),normalization and first derivative(FD)methods,and PLS-DA correction model was established for the 1300 cm^-1-1000 cm^-1 bands.The discriminant accuracy of the correction set was 97.5%,the discriminant accuracy of the verification set was 100.0%,and the discriminant accuracy of the external sample reached 92.7%.Conclusion Middle infrared spectroscopy combined with stoichiometry can accurately distinguish the adulteration of glycine chelate iron.
作者
石晓妮
田静
贾铮
徐思远
樊霞
SHI Xiao-Ni;TIAN Jing;JIA Zheng;XU Si-Yuan;FAN Xia(Key Laboratory of Agricultural Product Quality and Safety Research of Ministry of Agriculture,Institute of Quality Standard and Testing Technology for Agro-Products,Chinese Academy of Agricultural Sciences,Beijing 100081,China)
出处
《食品安全质量检测学报》
CAS
2020年第9期2733-2738,共6页
Journal of Food Safety and Quality
基金
“十三五”国家重点研发计划项目(2016YFF0201105)
中国农业科学院创新工程。
关键词
甘氨酸铁螯合物
中红外光谱
偏最小二乘判别法
掺假判别
glycine chelate iron
middle infrared spectrum
partial least squares discrimination analysis
adulteration discriminant
