使用核磁共振光谱法和多元统计分析检测特级初榨橄榄油中掺入粗橄榄油和精炼橄榄油的情况。
Detection of extra virgin olive oil adulteration with lampante olive oil and refined olive oil using nuclear magnetic resonance spectroscopy and multivariate statistical analysis.
作者信息
Fragaki Georgia, Spyros Apostolos, Siragakis George, Salivaras Emmanuel, Dais Photis
机构信息
NMR Laboratory, Department of Chemistry, University of Crete, 714 09 Iraklion, Crete, Greece.
出版信息
J Agric Food Chem. 2005 Apr 20;53(8):2810-6. doi: 10.1021/jf040279t.
High-field 31P NMR (202.2 MHz) spectroscopy was applied to the analysis of 59 samples from three grades of olive oils, 34 extra virgin olive oils from various regions of Greece, and from different olive varieties, namely, 13 samples of refined olive oils and 12 samples of lampante olive oils. Classification of the three grades of olive oils was achieved by two multivariate statistical methods applied to five variables, the latter being determined upon analysis of the respective 31P NMR spectra and selected on the basis of one-way ANOVA. The hierarchical clustering statistical procedure was able to classify in a satisfactory manner the three olive oil groups. Subsequent application of discriminant analysis to the five selected variables of oils allowed the grouping of 59 samples according to their quality with no error. Different artificial mixtures of extra virgin olive oil-refined olive oil and extra virgin olive oil-lampante olive oil were prepared and analyzed by 31P NMR spectroscopy. Subsequent discriminant analysis of the data allowed detection of extra virgin olive oil adulteration as low as 5% w/w for refined and lampante olive oils. Further application of the classification/prediction model allowed the estimation of the percent concentration of refined olive oil in six commercial blended olive oils composed of refined and virgin olive oils purchased from supermarkets.
采用高场31P核磁共振(202.2 MHz)光谱法对来自三个等级橄榄油的59个样品进行分析,其中包括来自希腊不同地区、不同橄榄品种的34个特级初榨橄榄油,13个精炼橄榄油样品和12个粗橄榄油样品。通过对五个变量应用两种多元统计方法实现了对三个等级橄榄油的分类,这五个变量是在对各自的31P NMR光谱进行分析后确定的,并基于单因素方差分析进行选择。层次聚类统计程序能够以令人满意的方式对三个橄榄油组进行分类。随后对选定的五个油变量进行判别分析,可将59个样品按质量无误地分组。制备了特级初榨橄榄油-精炼橄榄油和特级初榨橄榄油-粗橄榄油的不同人工混合物,并通过31P NMR光谱进行分析。随后对数据进行判别分析,可检测出精炼橄榄油和粗橄榄油中低至5% w/w的特级初榨橄榄油掺假情况。分类/预测模型的进一步应用能够估算从超市购买的由精炼橄榄油和初榨橄榄油组成的六种市售混合橄榄油中精炼橄榄油的浓度百分比。