Department of Food and Environment Sciences Prof. G. Stagno d'Alcontres, University of Messina, V.le F. Stagno d'Alcontres, 31, I-98166 Messina, Italy.
Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2012;29(7):1021-9. doi: 10.1080/19440049.2012.674979. Epub 2012 Apr 13.
The content of chlorides, nitrites, nitrates, phosphates and sulphates was used to classify 45 donkey's milk samples collected from different Italian regions. A method employing ion exchange chromatography with conductivity detector and chemical suppression was used. The quantitative results indicated phosphates (569.4-1304.4 mg kg(-1)) and chlorides (545.9-1757.9 mg kg(-1)) as being the most abundant anions, followed by sulphates (109.5-200.7 mg kg(-1)). The concentrations of nitrites and nitrates were found to be lower at 5.6 and 5.5 mg kg(-1) respectively. The data set was subdivided into three groups according to the region of origin of milk, and was statistically evaluated by analysis of variance (ANOVA). Concentrations of chlorides and nitrites showed a significant difference among farms (p < 0.001). In a first discriminant analysis procedure, functions based on linear combinations of the log(e)-transformed element concentrations of anions were generated to classify donkey's milk samples from different regions. In an alternative approach, a three-step discriminant analysis procedure to classify a milk sample was tested. The results obtained led to a correct classification of donkey's milk samples based on their anions content with 91-98% of the samples being correctly classified. The procedure proved to be very simple, so it could be used as an evaluation method for the traceability of donkey's milk, thus defending this unique product against fraud or commercial disputes.
采用离子交换色谱法-电导检测-化学抑制法，对来自意大利不同地区的 45 份驴乳样本中的氯、亚硝酸盐、硝酸盐、磷酸盐和硫酸盐含量进行分析，以对其进行分类。定量结果表明，磷酸盐（569.4-1304.4mg/kg）和氯化物（545.9-1757.9mg/kg）的含量最丰富，其次是硫酸盐（109.5-200.7mg/kg）。硝酸盐和亚硝酸盐的浓度分别为 5.6mg/kg 和 5.5mg/kg，相对较低。根据乳源地区，将数据集分为三组，并通过方差分析（ANOVA）进行统计学评估。氯和亚硝酸盐的浓度在农场之间存在显著差异（p<0.001）。在首次判别分析过程中，基于阴离子的对数变换元素浓度的线性组合生成函数，以对来自不同地区的驴乳样本进行分类。在另一种方法中，测试了一种三步判别分析程序，以对牛奶样本进行分类。所得结果基于阴离子含量对驴乳样本进行了正确分类，91-98%的样本得到了正确分类。该程序非常简单，因此可作为驴乳溯源的评估方法，从而防止这种独特产品受到欺诈或商业纠纷的影响。
