Nardin Raffaello, Tamasi Gabriella, Baglioni Michele, Bisozzi Flavia, Consumi Marco, Costa Jessica, Fattori Giacomo, Tozzi Cristiana, Riccaboni Angelo, Rossi Claudio
Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via Aldo Moro 2, 53100 Siena, Italy.
Centre for Colloid and Surface Science (CSGI), University of Florence, Via della Lastruccia 3, 50019 Sesto Fiorentino, Firenze, Italy.
ACS Food Sci Technol. 2024 Oct 28;4(11):2585-2599. doi: 10.1021/acsfoodscitech.4c00231. eCollection 2024 Nov 15.
To fight counterfeits and to protect the consumer, the interest in certifying the origin of agricultural goods has been steadily growing in the last years. While numerous works focus on the finished product, an aspect often overlooked is the origin of the raw materials and the direct correlation between chemicals in the soil and the plants. With inductively coupled plasma mass spectrometry (ICP-MS) analysis, trace and ultratrace elements in Sangiovese grapes (the main component of Chianti wine) were measured and their levels were used to investigate the geographical origin of the samples. This was achieved despite the extreme closeness of some of the vineyard partners of this study (10-20 km range) by computing a multivariate model using selected elements as levels. The model was then validated on samples coming from different zones of the Chianti area, with good results for discriminating even extremely close regions.
为打击假冒伪劣产品并保护消费者,近年来,对农产品产地认证的关注一直在稳步增长。虽然众多研究聚焦于成品,但一个常被忽视的方面是原材料的产地以及土壤中的化学物质与植物之间的直接关联。通过电感耦合等离子体质谱(ICP-MS)分析,测定了桑娇维塞葡萄(基安蒂葡萄酒的主要成分)中的痕量和超痕量元素,并利用这些元素的含量来研究样本的地理来源。尽管本研究中的一些葡萄园合作伙伴距离极近(范围在10 - 20公里),但通过使用选定元素的含量计算多变量模型,仍实现了这一目标。然后,该模型在来自基安蒂地区不同区域的样本上进行了验证,在区分甚至极为相近的区域方面取得了良好效果。