食品科学 ›› 2021, Vol. 42 ›› Issue (10): 290-296.doi: 10.7506/spkx1002-6630-20191104-039

• 安全检测 • 上一篇    下一篇

美味牛肝菌矿质元素富集能力及产地鉴别

陈凤霞,杨天伟,李杰庆,刘鸿高,范茂攀,王元忠   

  1. (1.云南农业大学资源与环境学院,云南 昆明 650201;2.云南省农业科学院药用植物研究所,云南 昆明 650200;3.云南省热带作物科学研究所,云南 景洪 666100;4.云南农业大学农学与生物技术学院,云南 昆明 650201)
  • 出版日期:2021-05-25 发布日期:2021-06-02
  • 基金资助:
    国家自然科学基金地区科学基金项目(31660591);云南省农业基础研究联合专项面上项目(2018FG001-033)

Mineral Enrichment Capacity and Geographical Origin Identification of Boletus edulis

CHEN Fengxia, YANG Tianwei, LI Jieqing, LIU Honggao, FAN Maopan, WANG Yuanzhong   

  1. (1. College of Resources and Environmental Sciences, Yunnan Agricultural University, Kunming 650201, China; 2. Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, China;3. Yunnan Institute for Tropical Crop Research, Jinghong 666100, China;4. College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650201, China)
  • Online:2021-05-25 Published:2021-06-02

摘要: 研究美味牛肝菌矿质元素含量及富集规律,建立偏最小二乘判别分析(partial least squares discrimination analysis,PLS-DA)光谱数据融合模型鉴别美味牛肝菌不同产地。测定云南省内6 个产地美味牛肝菌和生长土壤样品的矿质元素,同时采集近红外光谱和紫外光谱信息。根据矿质元素含量及富集系数分析美味牛肝菌对矿质元素的积累特征和富集能力。采用平滑(Savitzky-Golay,SG)、二阶导数(second derivatives,2D)、标准正态变换(standard normal variables,SNV)、多元散射校正(multiple scattering correction,MSC)等对光谱数据进行预处理。运用PLS-DA建立单一光谱与数据融合产地分类模型。结果表明:美味牛肝菌富含K、P元素,相同元素不同产地之间存在显著性差异,其中Na元素含量差异较大,最高含量是最低含量的20.70 倍;6 个产地土壤中Fe元素含量最大,可能与云南富含Fe金属离子的酸性土壤有关;美味牛肝菌中P、K、Zn富集能力较强,其中P的富集系数达到4.63;光谱数据预处理中,近红外光谱和紫外光谱的最佳预处理结果为SG+2D、SG+MSC,预测集正确率为88.46%和96.15%;中级融合模型效果最佳,通过Hottelling T2检测法检验,所有样品未超过95%置信区间,模型训练集正确率100.00%,预测集正确率92.31%。对美味牛肝菌进行矿质元素、富集规律及产地鉴别研究有利于合理利用云南野生食用菌资源。

关键词: 美味牛肝菌;矿质元素;富集系数;数据融合;产地鉴别

Abstract: The objectives of this research were to 1) determine the mineral element contents and enrichment characteristics of Boletus edulis and 2) establish a model using partial least squares-discrimination analysis (PLS-DA) combined with spectral data fusion for identifying different geographical origins of B. eduils. The mineral elements of B. edulis and soil samples from six producing areas in Yunnan province were determined and the near-infrared and ultraviolet spectral information was collected. The accumulation characteristics and enrichment capacity of mineral elements by B. edulis were analyzed based on mineral element contents and enrichment coefficient. Savitzky-Golay (SG), second derivatives (2D), standard normal variables (SNV) and multiple-scattering correction (MSC) were used to pre-process spectral data. A monospectral data model was established using PLS-DA. The results showed that B. edulis was rich in K and P, and all tested minerals varied with the geographical origin with the highest Na level being 20.70 times as great as the lowest level. The content of Fe in soils from the six producing areas was the largest, which may be related to the acidity of the soils. The enrichment capacity of P, K and Zn in B. edulis was strong, with an enrichment factor of 4.63 for P. The optimal pretreatment methods for near-infrared and ultraviolet spectra were SG + 2D and SG + MSC, giving an accuracy for the prediction set of 88.46% and 96.15%, respectively. The intermediate fusion model had the best prediction performance. The Holtelling T2 test revealed that all samples fell within the 95% confidence interval, and the accuracy for the training and prediction sets was 100.00% and 92.31%, respectively. The results obtained in this study will be useful for the rational utilization of wild edible fungi resources in Yunnan.

Key words: Boletus edulis; mineral elements; enrichment coefficient; data fusion; geographical origin identification

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