Facultad de Cs. Químicas-ICYTAC, Universidad Nacional de Córdoba-CONICET , Ciudad Universitaria, 5000 Córdoba, Argentina.
J Agric Food Chem. 2013 Apr 24;61(16):3763-73. doi: 10.1021/jf305258r. Epub 2013 Apr 11.
The aim of this study was to investigate if elemental and isotopic signatures of Argentinean wheat can be used to develop a reliable fingerprint to assess its geographical provenance. For this pilot study we used wheat cultivated at three different regions (Buenos Aires, Córdoba, and Entre Ríos), together with matching soil and water. Elemental composition was determined by ICP-MS. δ(13)C and δ(15)N were measured by isotopic ratio mass spectrometry, while (87)Sr/(86)Sr ratio was determined using thermal ionization mass spectrometry. Wheat samples from three sampling sites were differentiated by the combination of 11 key variables (K/Rb, Ca/Sr, Ba, (87)Sr/(86)Sr, Co, Mo, Zn, Mn, Eu, δ(13)C, and Na), demonstrating differences among the three studied regions. The application of generalized Procrustes analysis showed 99.2% consensus between cultivation soil, irrigation water, and wheat samples, in addition to clear differences between studied areas. Furthermore, canonical correlation analysis showed significant correlation between the elemental and isotopic profiles of wheat and those corresponding to both soil and water (r(2) = 0.97, p < 0.001 and r(2) = 0.96, p < 0.001, respectively). To our knowledge, this is the first report demonstrating the correspondence between soil, water, and wheat samples using different statistical methods, showing that wheat elemental and isotopic compositions are mainly related to soil and irrigation water characteristics of the site of growth.
本研究旨在探讨阿根廷小麦的元素和同位素特征是否可用于开发可靠的指纹图谱,以评估其地理来源。在这项初步研究中,我们使用了在三个不同地区(布宜诺斯艾利斯、科尔多瓦和恩特雷里奥斯)种植的小麦,以及匹配的土壤和水。通过电感耦合等离子体质谱法(ICP-MS)测定元素组成。通过同位素比质谱法测量 δ(13)C 和 δ(15)N,而 (87)Sr/(86)Sr 比值则通过热电离质谱法测定。三个采样点的小麦样品通过 11 个关键变量(K/Rb、Ca/Sr、Ba、(87)Sr/(86)Sr、Co、Mo、Zn、Mn、Eu、δ(13)C 和 Na)的组合进行区分,表明三个研究地区之间存在差异。广义 Procrustes 分析的应用表明,在种植土壤、灌溉水和小麦样品之间有 99.2%的一致性,此外,研究区域之间也存在明显差异。此外,典型相关分析表明,小麦的元素和同位素特征与土壤和水的相应特征之间存在显著相关性(r(2) = 0.97,p < 0.001 和 r(2) = 0.96,p < 0.001,分别)。据我们所知,这是首次使用不同的统计方法报告证明土壤、水和小麦样品之间的对应关系,表明小麦的元素和同位素组成主要与生长地点的土壤和灌溉水特征有关。