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A novel analytical strategy for discriminating antibiotic mycelial residue adulteration in feed based on ATR-IR and
Shouxue Li1, Xia Fan2, Yalan Wu1
1College of Engineering, China Agricultural University, Beijing 100083, PR China.
Abstract:
The Antibiotic mycelial residue (AMR) contains antibiotic residue, there are safety risks if it is used illegally in feed. This study investigated the feasibility of qualitative identification of AMR in protein feed and self-prepared feed based on attenuated total reflection mid-infrared spectrum (ATR-IR) and microscopic infrared imaging. Cottonseed meal (CM), soybean meal (SM), distillers dried grains with solubles (DDGS), nucleotide residue (NR), oxytetracycline residue (OR) and streptomycin sulfate residue (SR) and two self-prepared feed (broiler and pig) were used as research objects. The results showed that there were characteristic peaks at 1614 cm-1, 1315 cm-1, 779 cm-1, 514 cm-1 in the ATR-IR spectra of AMR, which were related to calcium oxalate hydrate. After detection, the content of total calcium and calcium oxalate in AMR were higher than those in protein feed. ATR-IR can quickly realize the qualitative discrimination of pure material samples. The combination of ATR-IR and partial least squares discriminant analysis (PLSDA) was effective in discriminating AMR from CM and SM with a single component (the classification errors were 0), but it cannot meet the discrimination of AMR from the fermented protein feed (such as DDGS and NR, the classification errors were 0.10 and 0.12) and self-prepared feed with complex components. Compared with ATR-IR, microscopic infrared imaging was less affected by the sample complexity. Multi-component samples belong to physical mixing and will not affect the infrared spectra of each component. Therefore, microscopic infrared imaging combined with effective information extraction algorithms such as cosine similarity can distinguish OR in the fermented protein feed and self-prepared feed. The above results showed that the advantages of ATR-IR and microscopic infrared imaging were complementary, which provided a new idea for the discrimination analysis of illegal feed additives.
Insights
This study explored identifying antibiotic mycelial residue (AMR) in feed using infrared spectroscopy. Microscopic infrared imaging effectively detected residues in complex feeds, offering a new method for feed safety analysis.
Area of Science:
- Analytical Chemistry
- Food Science
- Spectroscopy
Background:
- Antibiotic mycelial residue (AMR) poses safety risks when illegally used in animal feed.
- Accurate identification of AMR in various feed types is crucial for ensuring feed safety.
Purpose of the Study:
- To investigate the feasibility of qualitatively identifying AMR in protein feed and self-prepared feed.
- To compare the effectiveness of attenuated total reflection mid-infrared spectrum (ATR-IR) and microscopic infrared imaging for AMR detection.
Main Methods:
- Utilized ATR-IR spectroscopy and microscopic infrared imaging to analyze various feed samples, including cottonseed meal, soybean meal, distillers dried grains with solubles, nucleotide residue, and specific antibiotic residues.
- Employed partial least squares discriminant analysis (PLSDA) and cosine similarity algorithms for data analysis.
Main Results:
- ATR-IR successfully discriminated AMR from simple protein feeds but struggled with complex fermented and self-prepared feeds.
- Microscopic infrared imaging demonstrated resilience to sample complexity, effectively distinguishing antibiotic residues in fermented and self-prepared feeds.
- Characteristic peaks related to calcium oxalate hydrate were identified in AMR, with higher calcium and calcium oxalate content compared to protein feeds.
Conclusions:
- ATR-IR and microscopic infrared imaging offer complementary strengths for AMR identification.
- Microscopic infrared imaging, combined with cosine similarity, provides a viable method for detecting illegal antibiotic residues in complex feed matrices.
- This research presents a novel approach for the discrimination analysis of illegal feed additives, enhancing feed safety protocols.
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