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使用GA-SVR优化SERS检测血中的硫法醇残留物

Gaoliang Zhang^1,2, Zihan Ma², Chao Yan²

¹Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.

Foods (Basel, Switzerland)

|January 10, 2026

概括

一种新的表面增强拉曼光谱法 (SERS) 方法可以快速检测血中的硫法醇残留物. 这种先进的技术通过克服分析复杂的生物样本以检测兽药污染物的挑战来确保食品安全.

科学领域:

分析化学分析化学
食品科学食品科学食品科学
频谱学是一种光谱学.

背景情况:

禽类产品中的硫法醇残留物对人类健康和食品安全构成风险.
传统的检测方法在复杂的血基质上面临局限性.

研究的目的:

开发一种快速,灵敏的表面增强拉曼光谱法 (SERS) 方法,用于在血中检测硫法醇.
在复杂的生物矩阵中解决分析挑战.

主要方法:

合成和评估四个合基质 (金和银合物) 用于SERS增强.
优化了关键参数,包括电解质类型,基质体积和吸附时间.
使用基因算法支持向量回归 (GA-SVR) 模型与空气PLS和MSC预处理.

主要成果:

优化SERS方法在1157厘米^-1的最大强度使用金合物A.达到最大强度.
在GA-SVR模型显示高预测性能 (R²_p = 0.9278,RMSEP = 3.1552).
该方法表现出高特异性,最小的矩阵干扰和稳定性.

结论:

开发的SERS方法适用于可靠地检测血中的硫法醇残留物.
这种方法符合兽药药物监测的全球食品安全要求.

关键词:

在SERS检测检测.的血液是的血液.基因算法支持向量回归建模的遗传算法硫酸的残留物硫酸的残留物

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