ResD-Net: A model for rapid prediction of antioxidant activity in gentian root using FT-IR spectroscopy
文献类型： 外文期刊
作者： Li, Xiaokun 1 ; Zeng, Pan 1 ; Wu, Xunxun 1 ; Yang, Xintong 1 ; Lin, Jingcang 2 ; Liu, Peizhong 1 ; Wang, Yuanzhong 3 ; Diao, Yong 1 ;
作者机构： 1.Huaqiao Univ, Sch Med, Quanzhou 362021, Peoples R China
2.Quanzhou Med Coll, Quanzhou 362000, Peoples R China
3.Yunnan Acad Agr Sci, Inst Med Plants, Kunming, Peoples R China
关键词： Antioxidant activity; FT-IR; Gentian; Deep Learning; Chemometrics
期刊名称：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY （ 影响因子：4.4； 五年影响因子：3.9 ）
ISSN： 1386-1425
年卷期： 2024 年 310 卷
页码：
收录情况： SCI
摘要： Gentian, an herb resource known for its antioxidant properties, has garnered significant attention. However, existing methods are time-consuming and destructive for assessing the antioxidant activity in gentian root samples. In this study, we propose a method for swiftly predicting the antioxidant activity of gentian root using FT-IR spectroscopy combined with chemometrics. We employed machine learning and deep learning models to establish the relationship between FT-IR spectra and DPPH free radical scavenging activity. The results of model fitting reveal that the deep learning model outperforms the machine learning model. The model's performance was enhanced by incorporating the Double -Net and residual connection strategy. The enhanced model, named ResD-Net, excels in feature extraction and also avoids gradient vanishing. The ResD-Net model achieves an R2 of 0.933, an RMSE of 0.02, and an RPD of 3.856. These results support the accuracy and applicability of this method for rapidly predicting antioxidant activity in gentian root samples.
- 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
-
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
-
Simulation of suitable habitats and geographic tracing based on medicinal and edible plants with Gastrodia elata Bl. as an example
作者：Li, Chaoping;Wang, Yuanzhong;Li, Chaoping;Shen, Tao;Liu, Honggao
关键词：Suitable habitats; Chemometrics; Origin authentication; Correlation; Gastrodia elata Bl.
