Abstract：
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.
摘要：
抗生素菌丝体残留物(AMR)含有抗生素残留物。如果牲畜过量摄入AMR，它可能会导致健康问题。为了解决当前NIR-HSI中像素尺度掺杂浓度未知的问题，本文创新性地提出了一种新的光谱模拟方法，用于蛋白质饲料中AMR的评价。四种常见的蛋白饲料(豆粕(SM)，含可溶物的干酒糟（DDGS），棉籽粕（CM），选择核苷酸残基（NR）和土霉素残基（OR）作为研究材料。该方法的第一步是使用线性混合模型（LMM）模拟具有不同掺杂浓度的像素的光谱。然后，基于模拟像素谱结合基于全局PLS评分的局部PLS(LPLS-S)建立了像素尺度OR定量模型(该模型解决了由于校正集的0%-100%含量而导致的预测结果的非线性分布问题).最后,该模型用于定量预测高光谱图像中每个像素的OR含量。计算每个像素的平均值作为该样品的OR含量。该方法的实施可以有效克服PLS-DA无法实现对2%-20%掺假样品中OR的定性鉴定的问题。与通过平均感兴趣区域的光谱建立的PLS模型相比，这种方法利用每个像素的精确信息，从而提高掺假样品检测的准确性。结果表明，模拟光谱法和LPLS-S的结合为NIR-HSI检测和分析非法饲料添加剂提供了一种新的方法。
