代谢物
多菌灵
化学
支持向量机
偏最小二乘回归
多元统计
色谱法
生物系统
分析化学(期刊)
人工智能
园艺
数学
杀菌剂
生物
计算机科学
生物化学
统计
作者
Jianglin Li,Da‐Wen Sun,Hongbin Pu,Digvir S. Jayas
出处
期刊:Food Chemistry
[Elsevier]
日期:2016-09-14
卷期号:218: 543-552
被引量:136
标识
DOI:10.1016/j.foodchem.2016.09.051
摘要
Surface-enhanced Raman scattering (SERS) imaging coupling with multivariate analysis in spectral region of 200 to 1800cm-1 was developed to quantify and visualize thiophanate-methyl (TM) and its metabolite carbendazim residues in red bell pepper (Capsicum annuum L.). Least squares support vector machines (LS-SVM) and support vector machines (SVM) models based on seven optimized characteristic peaks that showed SERS effects of TM and its metabolite carbendazim residues were employed to establish prediction models. SERS spectra with first derivative (1st) and second derivative (2nd) method were subsequently compared and the optimized model of 1st-LS-SVM acquired showed the best performance (RPD=6.08, R2P=0.986 and RMSEP=0.473). The results demonstrated that SERS imaging with multivariate analysis had the potential for rapid determination and visualization of the trace TM and its metabolite carbendazim residues in complex food matrices.
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