小麦产地溯源的矿物元素指纹信息成因及变化机理

It could provide technical support for the supervison and management of special local products and geographical indications products to study the origin traceability of agricultural products. Multi-element fingerprinting technique is one of the effective techniques to study the origin traceability of agricultural products. The precondition of its application is to select and verify the element fingerprints mainly associated with geographical origin. It has been found that the concentrations of 50 elements in wheat grains are significantly different among different regions by randomly collecting a large number of samples from main wheat-producing areas of Hebei, Henan, Shandong, and Shaanxi provinces in previous studies. In this project, taking these 50 elements as the subject and three different locations from previously randomized sampling areas as experiment sites, ten different wheat varieties which are suitably grown in the three locations will be planted in all experiment sites for three years. The relationships of multi-element fingerprints between wheat grain and location, genotype, or harvest year will be analyzed. The contribution rates of location, genotype, harvest year, or their interactions to the variation of multi-element contents will be calculated. In addition, the relationships of concentrations of these 50 elements between wheat grain and topsoil or parent soil will be further studied. Through above analysis, the forming reason and changing mechanism of multi-element origin fingerprints will be made clear. The elemental indicators closely related to geographical origin will be selected. This project could provide theoretic basis for the study and application of identifying the geographical origin of agricultural products by multi-element fingerprinting technique.

农产品产地溯源研究能为名优特及地理标志产品的监管提供技术支撑。矿物元素指纹分析是用于农产品产地溯源的有效技术之一，筛选并确定与原产地密切相关的矿物元素是此技术应用的前提。本项目以前期在河北、河南、山东和陕西小麦主产区随机采集的大量小麦样本分析得出的地域之间有显著差异的50种矿物元素为研究对象，在前期采样区域内确定3个地域，选择10个适合在3个地域种植的小麦品种，设计小麦产地矿物元素指纹分析模型试验，连续进行3年。分析小麦籽粒矿物元素指纹与地域、基因型及年际的关系；解析地域、基因型、年际及其交互作用对小麦籽粒矿物元素指纹形成的贡献率；分析小麦籽粒矿物元素指纹与种植地域表层和母质土壤中矿物元素指纹的关系；明确地域之间矿物元素指纹形成的原因，揭示矿物元素产地溯源指纹信息变化机理。筛选出与小麦种植地域密切相关的矿物元素指纹信息，为农产品产地矿物元素指纹溯源技术的研究与应用提供理论依据。

分析环境和基因型对农产品中矿质元素指纹信息的影响，解析各因素对农产品矿质元素含量变异的贡献率，是阐释农产品矿质元素指纹信息成因及其在年际间稳定性的关键研究内容。研究发现利用矿质元素指纹分析技术鉴别小麦产地具有可行性；并且小麦籽粒中的矿质元素含量不仅与环境（地域和年际）密切相关，还受基因型影响。不同地域来源的小麦籽粒中矿质元素含量的差异是源于地域的差异，还是源于基因型的差异；随着种植品种的改变，不同地域的元素指纹信息特征是否会发生改变，尚不清楚；不同年际间相同地域来源的小麦元素指纹信息的变化研究相对较少。矿质元素指纹产地溯源技术应用于实践的关键是筛选出与地域密切相关的元素作为溯源指纹信息。本项目基于连续3年在3 个地域种植10个小麦品种的矿质元素产地溯源田间模型试验，以得到的270份小麦籽粒样品为试验材料，分析地域、基因型、年际对小麦籽粒中元素含量的影响；解析地域、基因型、年际及其交互作用对各元素含量变异的贡献率；筛选出受基因型、年际等因素影响较小，与地域密切相关的元素作为产地溯源的指纹信息。.从三个地区采集了2014/2015、2015/2016、2016/2017年10个基因型270个小麦样品，利用高分辨电感耦合等离子体质谱（HR-ICP-MS）测定元素（Mg，Al，Ca，Mn，Fe，Cu，Zn，As，Sr，Mo ，Cd，Ba，Pb）的含量。采用多因素方差分析，解析地域、基因型、年际及其交互作用对各元素的影响。通过计算各因素所占的方差百分比，发现Mn、Sr、Mo、Cd元素受地域方差贡献率最大，占总变异的34.2％、39.6％、35.0％和78.8％； Ba元素含量受基因型影响最大，占元素含量总变异的27.3％；其它因素受年际的影响最大。结合Pearson相关分析，发现小麦Mg、Ca、Mn、As、Sr、Mo、Cd等元素含量与土壤含量呈极显著相关（p < 0.01）。利用受地域因素影响最大且与土壤密切相关的Mn、Sr、Mo、Cd四种元素建立判别模型，整体正确判别率和交叉验证均达到98.5%，表明该法可更准确、有效地鉴别小麦籽粒的产地。