野生牛肝菌的营养价值及暴露风险关系到消费者的健康安全，并严重影响其市场稳定和贸易出口。本文采用电感耦合等离子体原子发射光谱法和傅里叶变换红外光谱法测定8种野生牛肝菌429份样品中12种元素的含量和光谱数据，分析元素含量特征及食用健康风险，同时基于元素含量、红外光谱、初级融合和中级融合数据分别建立偏最小二乘判别分析和支持向量机（SVM）判别模型，比较其鉴别效果。结果显示：野生牛肝菌富含Ca、Mg、Na、Zn等矿质元素，适量摄入可以补充人体营养需求，同时也应当注意部分牛肝菌的Cd暴露风险；基于中级融合建立SVM判别模型，其训练集和预测集正确率均为100%，能够快速、准确鉴别牛肝菌种类，有效避免因误采误食导致的中毒事件发生。系统性的对牛肝菌进行元素含量分析、健康风险评估和种类鉴别，为其品质安全评估和资源的开发利用提供参考。

The nutritional value and exposure risk of wild Boletaceae are related to consumers’ health and safety, and influence market stability and trade exports seriously. In this paper, the contents of 12 kind of element contents in eight wild Boletaceae (429 samples in total) were determined and their corresponding infrared spectra data were collected by inductively coupled plasma atomic emission spectroscopy and Fourier transform infrared spectrometry. The content characteristics of elements and edible health risk were analyzed. Meanwhile, partial least squares discriminant analysis and support vector machine (SVM) discriminant models were established using element contents, infrared spectroscopy, low-level data fusion and mid-level data fusion. The classification results were compared. The results demonstrated that wild Boletaceae were rich in Ca, Mg, Na, Zn and other mineral elements, and moderate intake can supplement the nutritional needs of human body. Meanwhile, attention should also be paid to the risk of heavy metal exposure of some Boletaceae. The SVM discriminant model based on mid-level data fusion has the accuracy of training set and test set of 100%, which could be a promising technique to rapidly and accurately discriminate the species of Boletaceae. It can effectively avoid the occurrence of poisoning incidents caused by accidental ingestion. Analyzing the element contents, assessing the health risk and identifying the species of Boletaceae systematically, can provide a reference for the quality safety assessment and the development and utilization of resources.

国家自然科学基金项目（31660591；21667031）；云南省教育厅科学研究基金项目（2018JS275）