Home Journals Articles Updates About
CN
image
收藏切换
Quantitative analysis of aflatoxin B1 in Triticum aestivum L. by near-infrared spectroscopy technology
收藏切换
PDF
Meng-Feng HU1, 2, Li-Li CAO1, 2, 3, Min PANG1, 2, 3, Chun GAO3, 4, Li XU3, 4, Shao-Tong JIANG1, 2, 3, Yan-Yan ZHAO1, 2, 3, *
Journal of Food Safety & Quality | 2025, 16(4) : 10 - 17
Less
收藏切换
Journal of Food Safety & Quality | 2025, 16(4): 10-17
• Special Topic: Grain and Oil Processing and Quality Safety •
Quantitative analysis of aflatoxin B1 in Triticum aestivum L. by near-infrared spectroscopy technology
Full
Meng-Feng HU1, 2, Li-Li CAO1, 2, 3, Min PANG1, 2, 3, Chun GAO3, 4, Li XU3, 4, Shao-Tong JIANG1, 2, 3, Yan-Yan ZHAO1, 2, 3, *
Affiliations
  • 1. School of Food and Biological Engineering, Hefei University of Technology, Hefei 230601, China
  • 2. Key Laboratory of Modern Processing of Agricultural Products of Anhui Province, Hefei 230601, China
  • 3. Intelligent Green Quality Selection Technology and Equipment for Agricultural Products Key Laboratory of Anhui Province Jointly Constructed Disciplines, Hefei 230601, China
  • 4. Jiexun Optoelectronic Technology Co of Anhui Province, Hefei 230012, China
Published: 2025-02-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20240930006
Outline
收藏切换

Objective To achieve rapid and non-destructive determination of aflatoxin B1 (AFB1) content in Triticum aestivum L. kernels by establishing a quantitative prediction model based on near-infrared spectroscopy technology. Methods The reflectance spectra of Triticum aestivum L. samples in the wavelength range of 900-1700 nm were collected, and the AFB1 content in Triticum aestivum L. was determined by high performance liquid chromatography. The raw spectral data of the Triticum aestivum L. samples were subjected to preprocessing, and the feature wavelengths were extracted in order to establish a prediction model. A model for predicting the AFB1 content was developed using a back propagation neural network (BPNN), random forest (RF), and support vector machine (SVM), the results of this model were compared with those of a full-wavelength modelling approach. Results The SVM model constructed following the application of multiplicative scatter correction (MSC) and competitive adaptive reweighted sampling (CARS) processing demonstrates superior performance compared to the other models and the full-band modelling model. Conclusion The combination of the CARS algorithm and the MSC-CARS-SVM model allows for the rapid and non-destructive detection of AFB1 content. The feasibility of using near-infrared spectroscopy for quantitative analysis of AFB1 content has been demonstrated, and this approach can be employed to assess the quality of Triticum aestivum L. during storage.

near-infrared spectroscopy technology  /  aflatoxin B1  /  quantitative analysis  /  non-destructive testing  /  Triticum aestivum L.
Meng-Feng HU, Li-Li CAO, Min PANG, Chun GAO, Li XU, Shao-Tong JIANG, Yan-Yan ZHAO. Quantitative analysis of aflatoxin B1 in Triticum aestivum L. by near-infrared spectroscopy technology[J]. Journal of Food Safety & Quality, 2025 , 16 (4) : 10 -17 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20240930006
Appendix
Less
Year 2025 volume 16 Issue 4
PDF
190
85
Cite this Article
BibTeX
Article Info
doi: 10.19812/j.cnki.jfsq11-5956/ts.20240930006
  • Receive Date：2024-09-30
  • Online Date：2025-07-21
  • Published：2025-02-25
Article Data
Affiliations
History
  • Received：2024-09-30
Funding
Affiliations
    1. School of Food and Biological Engineering, Hefei University of Technology, Hefei 230601, China
    2. Key Laboratory of Modern Processing of Agricultural Products of Anhui Province, Hefei 230601, China
    3. Intelligent Green Quality Selection Technology and Equipment for Agricultural Products Key Laboratory of Anhui Province Jointly Constructed Disciplines, Hefei 230601, China
    4. Jiexun Optoelectronic Technology Co of Anhui Province, Hefei 230012, China
References
Share
https://castjournals.cast.org.cn/joweb/spaq/EN/10.19812/j.cnki.jfsq11-5956/ts.20240930006
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House