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The evaluation of the nutritional quality of common wild edible fungi in Yunnan Province

文献类型： 外文期刊

作者： Du, Lijuan 1 ; Ye, Yanping 1 ; Lin, Tao 1 ; Li, Maoxuan 1 ; Bi, Yanan 1 ; Li, Qiwan 1 ; Liu, Hongcheng 1 ;

作者机构： 1.Yunnan Acad Agr Sci, Inst Qual Stand & Testing Tech, Kunming, Peoples R China

2.Yunnan Acad Agr Sci, Inst Qual Stand & Testing Tech, Kunming 650250, Peoples R China

关键词： nutritional evaluation; wild edible fungi; Yunnan Province

期刊名称：JOURNAL OF FOOD SCIENCE （ 影响因子：3.9； 五年影响因子：4.0 ）

ISSN： 0022-1147

年卷期： 2023 年 88 卷 5 期

页码：

收录情况： SCI

摘要： There are huge resource reserves of wild edible fungi richer in their varieties in Yunnan Province which is located on plateau of low latitude and possesses unique various climate environments and bigger vegetative cover ratios. Moreover, nutrients and flavor substances in the same or various species of wild edible fungi differ greatly with the influence on different components from habitats and geographic areas. So, 5 common wild edible fungi were collected from different areas in Yunnan Province, and several findings were made from this research. Above all, through the evaluation of amino acids, these 5 fungi met the criteria for ideal protein by WHO/FAO, and the nutritional value of protein was ranked as matsutake > truffle > collybia albuminosa > bolete > chanterelle. Next, after the analysis of taste activity values, the ranking of taste was bolete > collybia albuminosa > truffle > matsutake > chanterelle. Subsequently, the ranking of characters was truffle > collybia albuminosa >bolete > matsutake > chanterelle through principal component analysis. Finally, truffle could be completely divided by Fisher discrimination analysis with a bigger difference from others, main in ash, protein, sugar, and polysaccharide, meanwhile, truffle and bolete could be completely divided by orthogonal projections to latent structures discrimination analysis, main in protein, crude fiber, fat, and amino acid. So, there was a more conspicuous difference in nutrients among fungi, through which nutrients combined with multivariate statistics analysis made possible the correct differentiation of small range categories in wild edible fungi, and the correct classification of small range of them could effectively be realized.

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