Detection of lard in butter using Raman spectroscopy combined with chemometrics
作者： Osman Taylan , Nur Cebi , Mustafa Tahsin Yilmaz , Osman Sagdic , Ahmed Atef Bakhsh
DOI: 10.1016/J.FOODCHEM.2020.127344
关键词: Food additive 、 Partial least squares regression 、 Raman spectroscopy 、 NUTRITION&DIETETICS 、 Principal component regression 、 Chemistry 、 Chemometrics 、 Pcr analysis 、 Principal component analysis 、 Chromatography
摘要: Abstract There is a contentious need for robust and rapid methodologies maintaining the authenticity of foods food additives. The current paper presented new Raman spectroscopy-based methodology detection quantification lard in butter. Hierarchical cluster analysis (HCA) principal component (PCA) were successfully performed classification discrimination butter lard-adulterated samples. Strong pattern was observed HCA analysis. Also, partial least squares regression (R2 = 0.99) applied Quite favorable prediction capabilities cross-validation PLS PCR adulteration levels between 0% 100% fat (w/w). spectroscopy coupled chemometrics employed effectively samples with easy, robust, effective, low-cost reliable application quality control
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