Literature DB >> 34435928

Application of Identification and Evaluation Techniques for Edible Mushrooms: A Review.

Ziyun Yan1, Honggao Liu2, Jieqing Li1, Yuanzhong Wang3.   

Abstract

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.

Entities:  

Keywords:  Chromatography; deep learning; edible mushroom; quality evaluation; spectroscopic

Year:  2021        PMID: 34435928     DOI: 10.1080/10408347.2021.1969886

Source DB:  PubMed          Journal:  Crit Rev Anal Chem        ISSN: 1040-8347            Impact factor:   6.535


  1 in total

1.  A Small Sample Recognition Model for Poisonous and Edible Mushrooms based on Graph Convolutional Neural Network.

Authors:  Li Zhu; Xin Pan; Xinpeng Wang; Fu Haito
Journal:  Comput Intell Neurosci       Date:  2022-08-12
  1 in total

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