Verified the rapid evaluation of the edible safety of wild porcini mushrooms, using deep learning and PLS-DA
文献类型： 外文期刊
作者： Li Wang 1 ; Liu, Honggao 4 ; Li, Tao 5 ; Li, Jieqing 2 ; Wang, Yuanzhong 1 ;
作者机构： 1.Yunnan Acad Agr Sci, Med Plants Res Inst, Kunming 650200, Yunnan, Peoples R China
2.Yunnan Agr Univ, Coll Resources & Environm, Kunming 650201, Yunnan, Peoples R China
3.Yunnan Agr Univ, Coll Agron & Biotechnol, Kunming, Yunnan, Peoples R China
4.Zhaotong Univ, Coll Agron & Life Sci, Zhaotong, Peoples R China
5.Yuxi Normal Univ, Coll Resources & Environm, Yuxi, Peoples R China
关键词： porcini; food safety; deep learning; FT-NIR; Cd
期刊名称：JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE （ 影响因子：3.639； 五年影响因子：3.803 ）
ISSN： 0022-5142
年卷期：
页码：
收录情况： SCI
摘要： BACKGROUND How to quickly identify poisonous mushrooms is a worldwide problem, because poisonous mushrooms and edible mushrooms have very similar appearances. Even some edible mushrooms must be processed further before they can be eaten. In addition, mushrooms from different geographical origins contain different levels of heavy metals. Eating frequent mushrooms with excessive heavy metal content can also cause food poisoning. This information is very important and needs to be informed to consumers in advance. Through the demand for the safety of porcini mushrooms in the Yunnan area we propose a hierarchical identification system based on Fourier-transform near-infrared (FT-NIR) spectroscopy to evaluate the edible safety of porcini species. RESULTS We found that deep learning is the most effective means to identify the edible safety of porcini, and the recognition accuracy was 100%, by comparing two pattern recognition tools, deep learning and partial least square discriminant analysis (PLS-DA). Although the accuracy of the PLS-DA test set is 96.10%, the poisonous porcini is not allowed to be wrongly judged. In addition, the cadmium (Cd) content of Leccinum rugosiceps in the Midu area exceeded the standard. Deep learning can trace Le. rugosiceps geographic origin with an accuracy of 100%. CONCLUSION The overall results show that deep learning methods based on FT-NIR can identify porcini that is at risk of being eaten. This has useful application prospects in food safety. (c) 2021 Society of Chemical Industry.
- 相关文献
作者其他论文 更多>>
-
Rapid determination of geographical authenticity of Gastrodia elata f. glauca using Fourier transform infrared spectroscopy and deep learning
作者：Deng, Guangmei;Li, Jieqing;Deng, Guangmei;Wang, Yuanzhong;Liu, Honggao
关键词：Gastrodia elata f. glauca; Fourier transform infrared spectroscopy; Deep learning; Data driven version of soft independent; modeling of class analogy
-
Rapid prediction of nucleosides content and origin traceability of Boletus bainiugan using Fourier transform near-infrared spectroscopy combined with chemometrics
作者：Deng, Guangmei;Li, Jieqing;Deng, Guangmei;Wang, Yuanzhong;Liu, Honggao
关键词：Fourier transform near-infrared spectroscopy; Nucleoside compounds; Climatic factors; Two-dimensional correlation spectroscopy; Residual neural networks
-
Predicting the suitable habitat distribution of Polygonatum kingianum under current and future climate scenarios in southwestern Yunnan, China
作者：Hu, Xiaoyan;Yang, Shaobing;Li, Zhimin;Wang, Yuanzhong;Hu, Xiaoyan
关键词：Polygonatum kingianum; Maximum entropy model; Species distribution; Suitable habitat; Geographical traceability
-
Histopathological and Transcriptional Changes in Silkworm Larval Gonads in Response to Chlorfenapyr Exposure
作者：Li, Tao;Hu, Changxiong;Liu, Zenghu;Li, Qiongyan;Fan, Yonghui;Liao, Pengfei;Liu, Min;Yang, Weike;Li, Xingxing;Dong, Zhanpeng
关键词：
Bombyx mori ; chlorfenapyr; reproductive development; drug metabolism; hormone biosynthesis -
Geographical origin identification of Dendrobium Officinale based on FT-NIR and ATR-FTIR spectroscopy
作者：Han, Jiaqi;Hu, Qiang;Wang, Yuanzhong
关键词：Spectral analysis; Data fusion; Two-dimensional correlation spectroscopy; The residual convolutional neural network; Dendrobium officinale Kimura & Migo
-
Classification of bolete species and drying temperature using LC-MS and infrared spectroscopy and simultaneous prediction of their major compounds using chemometrics
作者：Zheng, Chuanmao;Li, Jieqing;Zheng, Chuanmao;Wang, Yuanzhong;Liu, Honggao
关键词：Boletes; Organic acids; Postharvest drying; Species identification; Quality assessment
-
Infrared spectroscopy combined with machine learning: A fast method for origin tracing and dry matter content prediction of Dendrobium officinale Kimura et Migo
作者：Feng, Yangna;Feng, Yangna;Yang, Shaobing;Wang, Yuanzhong
关键词：FT-NIR; ATR-FTIR; Dendrobium officinal; Prediction; Origin tracing
