Two dimensional correlation spectroscopy combined with ResNet: Efficient method to identify bolete species compared to traditional machine learning
文献类型： 外文期刊
作者： Yan, Ziyun 1 ; Liu, Honggao 2 ; Li, Tao 4 ; Li, Jieqing 1 ; Wang, Yuanzhong 5 ;
作者机构： 1.Yunnan Agr Univ, Coll Resources & Environm, Kunming 650201, Yunnan, Peoples R China
2.Yunnan Agr Univ, Coll Agron & Biotechnol, Kunming 650201, Yunnan, Peoples R China
3.Zhaotong Univ, Zhaotong 657000, Peoples R China
4.Yuxi Normal Univ, Coll Resources & Environm, Yuxi 653199, Peoples R China
5.Yunnan Acad Agr Sci, Inst Med Plants, Kunming 650223, Yunnan, Peoples R China
关键词： Bolete; FT-NIR; Chemometrics; 2DCOS; ResNet
期刊名称：LWT-FOOD SCIENCE AND TECHNOLOGY （ 影响因子：6.056； 五年影响因子：6.295 ）
ISSN： 0023-6438
年卷期： 2022 年 162 卷
页码：
收录情况： SCI
摘要： Different species of bolete have different nutritional and medicinal value, which leads to the phenomenon of shoddy in the market from time to time. Therefore, consumers need a fast and effective detection method to identify their species. In this paper, different data pretreatment was carried out for the Fourier transform near infrared (FT-NIR) spectra, and the modeling results of partial least squares discrimination analysis (PLS-DA), support vector machines (SVM) and residual neural network (ResNet) were compared. The results show that PLS-DA and SVM models need a suitable combination of pretreatment for spectral data. The purpose is to improve the accuracy of the model and avoid over fitting. After spectral pretreatment, the accuracy of PLS-DA model were improved to 99.63% and 97.38% respectively. In order to ensure that the SVM model does not have the risk of over fitting, the accuracy of the SVM model after pretreatment were reduced to 98.5% and 93.63%. The ResNet model was established based on the original spectrum. The accuracy of the model was 100%, and there is no over fitting phenomenon, which is one of the advantages of the model. Comparing the above three models, ResNet is the best model for bolete species identification.
- 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
-
Effect of drying temperature on composition of edible mushrooms: Characterization and assessment via HS-GC-MS and IR spectral based volatile profiling and chemometrics
作者：Zheng, Chuanmao;Li, Jieqing;Zheng, Chuanmao;Wang, Yuanzhong;Liu, Honggao
关键词：Boletus bainiugan; HS-SPME-GC-MS; VOCs; 2DCOS; Chemometrics; Quality estimation
-
The method based on ATR-FTIR spectroscopy combined with feature variable selection for the boletus species and origins identification
作者：Ji, Zhiyi;Li, Jieqing;Ji, Zhiyi;Wang, Yuanzhong;Liu, Honggao
关键词：feature variable selection; food safety; mid-infrared spectroscopy; species identification; traceability; wild boletus
-
Identification of geographical origins of Gastrodia elata Blume based on multisource data fusion
作者：Liu, Hong;Li, Jieqing;Liu, Hong;Wang, Yuanzhong;Liu, Honggao
关键词：2DCOS images; ATR-FTIR; data fusion; FT-NIR; Gastrodia elata Blume; geographical discrimination
-
A fast method for predicting adenosine content in porcini mushrooms using Fourier transform near-infrared spectroscopy combined with regression model
作者：Deng, Guangmei;Li, Jieqing;Deng, Guangmei;Wang, Yuanzhong;Liu, Honggao
关键词：Fourier transform near-infrared spectroscopy; Porcini mushrooms; Adenosine; Partial least squares regression
-
Application of ATR-FTIR and FT-NIR spectroscopy coupled with chemometrics for species identification and quality prediction of boletes
作者：Zheng, Chuanmao;Li, Jieqing;Zheng, Chuanmao;Wang, Yuanzhong;Liu, Honggao
关键词：Boletes; Amino acid metabolomics; LC-MS; FT-NIR; ATR-FTIR; 2DCOS
-
The genus Litsea: A comprehensive review of traditional uses, phytochemistry, pharmacological activities and other studies
作者：Li, Guangyao;Li, Guangyao;Li, Zhimin;Wang, Yuanzhong
关键词：L.; traditional uses; chemical components; pharmacological activities
