A new spectral simulating method based on near-infrared hyperspectral imaging for evaluation of antibiotic mycelia residues in protein feeds.

Autor: Ge C; College of Engineering, China Agricultural University, Beijing 100083, PR China. Electronic address: gechenjun@cau.edu.cn., Yang Z; College of Engineering, China Agricultural University, Beijing 100083, PR China. Electronic address: yangzengling@cau.edu.cn., Fan X; Institute of Quality Standard and Testing Technology for Agro-products of CAAS, Beijing 100081, PR China. Electronic address: fanxia@caas.cn., Huang Y; College of Engineering, China Agricultural University, Beijing 100083, PR China. Electronic address: hyping@cau.edu.cn., Shi Z; College of Engineering, China Agricultural University, Beijing 100083, PR China. Electronic address: shizhuolin@cau.edu.cn., Zhang X; College of Engineering, China Agricultural University, Beijing 100083, PR China. Electronic address: zhangxintong@cau.edu.cn., Han L; College of Engineering, China Agricultural University, Beijing 100083, PR China. Electronic address: hanlj@cau.edu.cn.
Jazyk: angličtina
Zdroj: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy [Spectrochim Acta A Mol Biomol Spectrosc] 2024 Oct 15; Vol. 319, pp. 124536. Date of Electronic Publication: 2024 May 25.
DOI: 10.1016/j.saa.2024.124536
Abstrakt: Antibiotic mycelia residues (AMRs) contain antibiotic residues. If AMRs are ingested in excess by livestock, it may cause health problems. To address the current problem of unknown pixel-scale adulteration concentration in NIR-HSI, this paper innovatively proposes a new spectral simulation method for the evaluation of AMRs in protein feeds. Four common protein feeds (soybean meal (SM), distillers dried grains with solubles (DDGS), cottonseed meal (CM), and nucleotide residue (NR)) and oxytetracycline residue (OR) were selected as study materials. The first step of the method is to simulate the spectra of pixels with different adulteration concentrations using a linear mixing model (LMM). Then, a pixel-scale OR quantitative model was developed based on the simulated pixel spectra combined with local PLS based on global PLS scores (LPLS-S) (which solves the problem of nonlinear distribution of the prediction results due to the 0%-100% content of the correction set). Finally, the model was used to quantitatively predict the OR content of each pixel in hyperspectral image. The average value of each pixel was calculated as the OR content of that sample. The implementation of this method can effectively overcome the inability of PLS-DA to achieve qualitative identification of OR in 2%-20% adulterated samples. In compared to the PLS model built by averaging the spectra over the region of interest, this method utilizes the precise information of each pixel, thereby enhancing the accuracy of the detection of adulterated samples. The results demonstrate that the combination of the method of simulated spectroscopy and LPLS-S provides a novel method for the detection and analysis of illegal feed additives by NIR-HSI.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024. Published by Elsevier B.V.)
Databáze: MEDLINE
Externí odkaz: