文献类型： 外文期刊
作者： Yan, Ziyun 1 ; Liu, Honggao 2 ; Li, Jieqing 1 ; Wang, Yuanzhong 3 ;
作者机构： 1.Yunnan Agr Univ, Coll Resources & Environm, Kunming 650201, Yunnan, Peoples R China
2.Zhaotong Univ, Zhaotong, Peoples R China
3.Yunnan Acad Agr Sci, Inst Med Plants, Kunming 650223, Yunnan, Peoples R China
关键词： Chromatography; deep learning; edible mushroom; quality evaluation; spectroscopic
期刊名称：CRITICAL REVIEWS IN ANALYTICAL CHEMISTRY （ 影响因子：6.535； 五年影响因子：6.657 ）
ISSN： 1040-8347
年卷期：
页码：
收录情况： SCI
摘要： Edible mushrooms are healthy food with high nutritional value, which is popular with consumers. With the increase of the problem of mushrooms being confused with the real and pollution in the market, people pay more and more attention to food safety. More than 167 articles of edible mushroom published in the past 20 years were reviewed in this paper. The analysis tools and data analysis methods of identification and quality evaluation of edible mushroom species, origin, mineral elements were reviewed. Five techniques for identification and evaluation of edible mushrooms were introduced and summarized. The macroscopic, microscopic and molecular identification techniques can be used to identify species. Chromatography, spectroscopy technology combined with chemometrics can be used for qualitative and quantitative study of mushroom and evaluation of mushroom quality. In addition, multiple supervised pattern-recognition techniques have good classification ability. Deep learning is more and more widely used in edible mushroom, which shows its advantages in image recognition and prediction. These techniques and analytical methods can provide strong support and guarantee for the identification and evaluation of mushroom, which is of great significance to the development and utilization of edible mushroom.
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