Longobardi F, Casiello G, Cortese M, Perini M, Camin F, Catucci L, Agostiano A
Dipartimento di Chimica, Università di Bari "Aldo Moro", Via Orabona 4, 70126 Bari, Italy.
Dipartimento di Chimica, Università di Bari "Aldo Moro", Via Orabona 4, 70126 Bari, Italy.
Food Chem. 2015 Dec 1;188:343-9. doi: 10.1016/j.foodchem.2015.05.020. Epub 2015 May 6.
The aim of this study was to predict the geographic origin of lentils by using isotope ratio mass spectrometry (IRMS) in combination with chemometrics. Lentil samples from two origins, i.e. Italy and Canada, were analysed obtaining the stable isotope ratios of δ(13)C, δ(15)N, δ(2)H, δ(18)O, and δ(34)S. A comparison between median values (U-test) highlighted statistically significant differences (p<0.05) for all isotopic parameters between the lentils produced in these two different geographic areas, except for δ(15)N. Applying principal component analysis, grouping of samples was observed on the basis of origin but with overlapping zones; consequently, two supervised discriminant techniques, i.e. partial least squares discriminant analysis and k-nearest neighbours algorithm were used. Both models showed good performances with external prediction abilities of about 93% demonstrating the suitability of the methods developed. Subsequently, isotopic determinations were also performed on the protein and starch fractions and the relevant results are reported.
本研究的目的是通过将同位素比率质谱法（IRMS）与化学计量学相结合来预测小扁豆的地理来源。对来自两个产地（即意大利和加拿大）的小扁豆样品进行分析，获得了δ(13)C、δ(15)N、δ(2)H、δ(18)O和δ(34)S的稳定同位素比率。中位数比较（U检验）突出显示，除δ(15)N外，这两个不同地理区域生产的小扁豆之间所有同位素参数均存在统计学上的显著差异（p<0.05）。应用主成分分析时，观察到样品按产地分组，但存在重叠区域；因此，使用了两种有监督判别技术，即偏最小二乘判别分析和k近邻算法。两种模型均表现良好，外部预测能力约为93%，证明了所开发方法的适用性。随后，还对蛋白质和淀粉组分进行了同位素测定，并报告了相关结果。
