We have located links that may give you full text access.
Identification of antibiotic mycelia residue in protein rich feed using on near-infrared microscopy imaging.
Food Additives & Contaminants. Part A, Chemistry, Analysis, Control, Exposure & Risk Assessment 2018 May
Antibiotic mycelial residues (AMRs) added to animal feeds easily lead to drug resistance that affects human health and environment. However, there is a lack of effective detection methods, especially a fast and convenient detection technology, to distinguish AMRs from other components in animal feeds. To develop effective detection methods, two types of global Mahalanobis distance (GH) algorithms based on near-infrared microscopy (NIRM) imaging are proposed. The aim of this study is to investigate the feasibility of using NIRM imaging to identify AMRs in soybean meals. We prepared 15 mixed samples containing 5% AMRs using three types of soybean meals and four types of AMRs. The GH algorithm was used to identify non-soybean meals among the mixed samples. The hierarchical cluster analysis was employed to verify the recognition accuracy. The results indicate that use of the GH algorithm could identify soybean meals with AMR at a level as low as 5%.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app