大豆有机成分辅助矿物元素指纹特征产地溯源

为提高矿物元素指纹图谱技术对大豆产地溯源的稳定性和准确性。采用电感耦合等离子体质谱仪测定黑龙江嫩江及北安共168?份大豆及对应土壤样品中矿物元素含量并分别测定大豆中蛋白质、脂肪、可溶性总糖和灰分含量。结果表明，采用步进式方法筛选出的10?种特征指标建立的判别模型对训练集大豆产地的整体正确判别率为96.4%，其中对黑龙江嫩江、北安大豆产地的正确判别率分别为98.1%、95%。回代检验对验证集大豆产地的整体正确判别率为98.2%，其中对黑龙江嫩江、北安大豆产地的正确判别率分别为100%、96.7%。验证集中对黑龙江嫩江、北安大豆产地的整体正确判别率高于测试集两产地的正确判别率（98.2%＞96.4%），说明这7?种矿物元素和3?种有机成分是用于大豆产地判别的主要特征指标，携带了充分的产地判别信息。

Geographical Traceability of Soybeans by Organic Composition Combined with Mineral Element Fingerprint

This study aimed to improve the stability and accuracy of mineral element fingerprinting for the geographical traceability of soybean. In this experiment, the contents of mineral elements in 168 soybean samples and the corresponding soil samples from Nenjiang county and Bei’an county in Heilongjiang province were determined by inductively coupled plasma mass spectrometry (ICP-MS). The contents of protein, fat, total soluble sugar and ash were determined as well. The results showed that the discriminant model established based on 10 characteristic indicators (seven mineral elements plus three organic compounds) selected by the stepwise selection method has an overall accuracy rate of 96.4% for the training set. Besides, the discrimination accuracy for soybean samples from Nenjiang county and Bei’an county were 98.1% and 95%, respectively. The overall discrimination accuracy for the validation set was 98.2% in the back substitution test, and the discrimination accuracy for soybean samples from Nenjiang county and Bei’an county were 100% and 96.7%, respectively. The overall discrimination accuracy for the validation set were higher than the test set (98.2% > 96.4%) indicating that all ten characteristic indicators carry sufficient information about geographical traceability.