Ariyama Kaoru, Aoyama Yoshinori, Mochizuki Akashi, Homura Yuji, Kadokura Masashi, Yasui Akemi
Center for Food Quality, Labeling and Consumer Services, Saitama Shintoshin Godo Chosa Kensa Building, 2-1 Shintoshin, Chuo-ku, Saitama City 330-9731, Japan.
J Agric Food Chem. 2007 Jan 24;55(2):347-54. doi: 10.1021/jf062613m.
Onions (Allium cepa L.) are produced in many countries and are one of the most popular vegetables in the world, thus leading to an enormous amount of international trade. It is currently important that a scientific technique be developed for determining geographic origin as a means to detect fraudulent labeling. We have therefore developed a technique based on mineral analysis and linear discriminant analysis (LDA). The onion samples used in this study were from Hokkaido, Hyogo, and Saga, which are the primary onion-growing areas in Japan, and those from countries that export onions to Japan (China, the United States, New Zealand, Thailand, Australia, and Chile). Of 309 samples, 108 were from Hokkaido, 52 were from Saga, 77 were from Hyogo, and 72 were from abroad. Fourteen elements (Na, Mg, P, Mn, Co, Ni, Cu, Zn, Rb, Sr, Mo, Cd, Cs, and Ba) in the samples were determined by frame atomic adsorption spectrometry, inductively coupled plasma optical emission spectrometry, and inductively coupled plasma mass spectrometry. The models established by LDA were used to discriminate the geographic origin between Hokkaido and abroad, Hyogo and abroad, and Saga and abroad. Ten-fold cross-validations were conducted using these models. The discrimination accuracies obtained by cross-validation between Hokkaido and abroad were 100 and 86%, respectively. Those between Hyogo and abroad were 100 and 90%, respectively. Those between Saga and abroad were 98 and 90%, respectively. In addition, it was demonstrated that the fingerprint of an element pattern from a specific production area, which a crop receives, did not easily change by the variations of fertilization, crop year, variety, soil type, and production year if appropriate elements were chosen.
洋葱(Allium cepa L.)在许多国家都有种植,是世界上最受欢迎的蔬菜之一,因此国际贸易量巨大。目前,开发一种科学技术来确定地理来源以检测欺诈性标签非常重要。因此,我们开发了一种基于矿物分析和线性判别分析(LDA)的技术。本研究中使用的洋葱样本来自日本主要的洋葱种植地区北海道、兵库和佐贺,以及向日本出口洋葱的国家(中国、美国、新西兰、泰国、澳大利亚和智利)。在309个样本中,108个来自北海道,52个来自佐贺,77个来自兵库,72个来自国外。通过框架原子吸收光谱法、电感耦合等离子体发射光谱法和电感耦合等离子体质谱法测定了样本中的14种元素(钠、镁、磷、锰、钴、镍、铜、锌、铷、锶、钼、镉、铯和钡)。利用LDA建立的模型来区分北海道与国外、兵库与国外以及佐贺与国外的地理来源。使用这些模型进行了十折交叉验证。北海道与国外之间交叉验证获得的判别准确率分别为100%和86%。兵库与国外之间的判别准确率分别为100%和90%。佐贺与国外之间的判别准确率分别为98%和90%。此外,研究表明,如果选择合适的元素,作物从特定产区接收的元素模式指纹不会因施肥、作物年份、品种、土壤类型和生产年份的变化而轻易改变。