基于稀土元素和稳定同位素指纹的枸杞道地性表征

Authentic characterization of Lycium barbarum based on the fingerprint characteristics of rare earth elements and stable isotope

中文关键词:  产地溯源  稀土元素  稳定同位素  成熟期  枸杞

英文关键词:source tracing  rare earth elements  stable isotope  Lycium barbarum

中文摘要:

      目的 探讨稀土元素结合C、N稳定同位素在枸杞原产地判别中的可行性, 为枸杞地理标志产品保护提供技术支撑。方法 采集宁夏、甘肃、青海和新疆4个产区共232份枸杞样本, 采用电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)及元素分析-稳定同位素比值质谱法(elementary analysis-isotope ratio mass spectrometers, EA-IRMS)测定枸杞中14种稀土元素及C、N稳定同位素比值, 结合化学计量学方法分析了监测指标在枸杞发育过程中的变化规律, 构建了枸杞产地判别模型。结果 随着枸杞发育, 稀土元素及C、N稳定同位素具有明显的变化规律: La呈先降低再升高再降低的趋势, Sc呈先升高后降低的趋势, Ce、Nd、Y、Pr、Yb、Dy、Gd、Sm、Eu、Tb、Ho、Tm 12种稀土元素及δ15N呈先降低后升高的趋势; 除Eu、Yb和Tm元素外, 其他稀土元素在4个枸杞产区或部分产区间存在显著差异, δ13C、δ15N在部分产区间存在显著差异; 主成分分析可提取出5个主成分, 前2个主成分可有效区分新疆、青海的枸杞样品, 宁夏和甘肃的样品不能有效区分; 采用Fisher线性判别分析方法构建了基于La、Nd、Sc、Y、Pr、Eu、Yb、Dy、Gd、Tb、Ho、Tm、δ13C、δ15N 14个指标的枸杞产地判别模型, 判别模型正确判别率在90.0%以上。结论 基于稀土元素和C、N稳定同位素指纹的差异可以有效鉴别不同产地的枸杞。

英文摘要:

      Objective To explore the feasibility of rare earth elements combined with C and N stable isotope in the identification of origin of wolfberry, and provide technical support for the protection of geographical indication products of wolfberry. Methods A total of 232 samples of Lycium barbarum were collected from Ningxia, Gansu, Qinghai and Xinjiang, the content of 14 kinds of rare earth elements and the ratios of C and N stable isotope in Lycium barbarum were determined by inductively coupled plasma mass spectrometry (ICP-MS) and elementary analysis-isotope ratio mass spectrometers (EA-IRMS). The variation rules of monitoring indexes during the development of Lycium barbarum were analyzed with stoichiometric method, and the discriminant model of Lycium barbarum origin was constructed. Results With the development of Lycium barbarum, the changes of rare earth elements and stable isotopes of C and N were obvious: La decreased first and then increased and then decreased, Sc increased first and then decreased, Ce, Nd, Y, Pr, Yb, Dy, Gd, Sm, Eu, Tb, Ho, Tm and δ15N decreased first and then increased. Except for Eu, Yb and Tm, there were significant differences in other rare earth elements among 4 or some Lycium barbarum producing areas, and δ13C and δ15N were significant differences in some producing areas. Principal component analysis could extract 5 principal components, the first two principal components could be used to distinguish the samples from Xinjiang and Qinghai, but could not be used to distinguish the samples from Ningxia and Gansu. Fisher linear discriminant analysis method was used to construct a Lycium barbarum habitat identification model based on 14 indicators: La, Nd, Sc, Y, Pr, Eu, Yb, Dy, Gd, Tb, Ho, Tm, δ13C, δ15N, the correct discriminant rate of the discriminant model was more than 90.0%. Conclusion Based on the differences of rare earth elements, C and N stable isotope fingerprints, Chinese wolfberry from different habitats can be effectively identified.