Recent trends of multi-source and non-destructive information for quality authentication of herbs and spices
文献类型: 外文期刊
作者: Xu, Yulin 1 ; Zhang, Jinyu 1 ; Wang, Yuanzhong 1 ;
作者机构: 1.Yunnan Acad Agr Sci, Med Plants Res Inst, Kunming 650200, Peoples R China
2.Yunnan Univ, Sch Agr, Kunming 650504, Peoples R China
关键词: Herbs and spices; Non-destructive techniques; Multi -source information; Data processing; Data fusion; Quality authentication
期刊名称:FOOD CHEMISTRY ( 影响因子:9.231; 五年影响因子:8.795 )
ISSN: 0308-8146
年卷期: 2023 年 398 卷
页码:
收录情况: SCI
摘要: The growing concerns about the quality and safety of herbs and spices among consumers have increased the demand for technical testing. Recently, non-destructive analysis techniques have been widely studied and applied. Generally, a single technology has certain limitations, which are not enough to fully describe the characteristics of complex products (dynamic or complex structure). Combining non-destructive analysis tech-nology (multi-source information) can overcome the above problems. The present review focused on applying multi-source and non-destructive information on herbs and spices quality authentication, including vibration spectroscopy and electronic sensor technologies. Then summarized and analyzed the authentication process for issues such as adulteration, contents prediction, geographical traceability, process and products analysis, and identification variety. Additionally, we presented trends in quality authentication, discussed the challenges and prospects, and made recommendations. This investigation provided clear evidence for the superiority of the quality authentication methods for herbs and spices based on multi-source and non-destructive information.
- 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
-
ResD-Net: A model for rapid prediction of antioxidant activity in gentian root using FT-IR spectroscopy
作者:Li, Xiaokun;Zeng, Pan;Wu, Xunxun;Yang, Xintong;Liu, Peizhong;Diao, Yong;Lin, Jingcang;Liu, Peizhong;Wang, Yuanzhong
关键词:Antioxidant activity; FT-IR; Gentian; Deep Learning; Chemometrics
-
Development of machine learning models using multi-source data for geographical traceability and content prediction of Eucommia ulmoides leaves
作者:Zhang, Yanying;Zhang, Yanying;Zhu, Xinyan;Wang, Yuanzhong
关键词:Machine learning; Eucommia ulmoides leaves; Geographical traceability; Content prediction; Quality evaluation
-
ATR-FTIR Spectroscopy Preprocessing Technique Selection for Identification of Geographical Origins of Gastrodia elata Blume
作者:Liu, Hong;Li, Jieqing;Liu, Hong;Wang, Yuanzhong;Liu, Honggao
关键词:ATR-FTIR spectroscopy; data preprocessing; DD-SIMCA; Gastrodia elata Blume; GBM; PLS-DA; SVM
-
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
-
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
-
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