分析测试学报2024，Vol.43Issue(7)：1032-1038,7.DOI:10.12452/j.fxcsxb.24032502
液态奶中镉、铜等重金属的光谱智能检测新方法研究
Research on a Novel Intelligent Spectral Methodology for Detection of Cadmium,Copper and Other Heavy Metals in Liquid Milk
摘要
Abstract
Heavy metal elements represent a significant threat to the quality safety of dairy products,making their rapid detection a focal point in food safety research.This paper introduces a novel detec-tion method,surface enhanced scanning laser induced breakdown spectrum(SES-LIBS),for im-proving the detection sensitivity and throughput of heavy metals in liquid milk.The SES-LIBS uti-lized the principle of metal displacement reactions to enrich trace heavy metal ions in specific areas above an active metal substrate.Subsequently,LIBS scanned the specific surface area of the metal substrate to collect trace heavy metal signals in liquid milk.The SES-LIBS was capable of avoiding the plasma cancellation with the improvement of detection sensitivity for trace heavy metal ions.To overcome both interference of sample collection and matrix in SES-LIBS signals,the paper devel-oped a reweighted characteristic spectrum driven auto-encoder siamese multitasking network(RCSD-ASMN),which accurately extracted spectral information of the interested analytes from complex and fluctuant LIBS signals.The results demonstrated that the SES-LIBS was capable of detecting multiple heavy metal elements such as Cd and Cu simultaneously,with limitation of detection of 0.11 mg/kg and 0.13 mg/kg,respectively.The linearity(R2)of the detected elements is not less than 0.97.These results revealed that the SES-LIBS methodology supressed cross-interference from different liq-uid milk substrates and heavy metal elements,presenting excellent detection accuracy and linearity.This would definitely provide a novel approach for high-throughput detection of heavy metals in liquid milk samples,which may well extend to other liquid systems.关键词
液态奶/重金属/表面富集扫描激光诱导击穿光谱/重加权光谱/自编码孪生多任务网络Key words
liquid milk/heavy metals/surface enhanced scanning laser induced breakdown spec-trum/reweighted characteristic spectrum/auto-encoder siamese multitasking network分类
化学化工引用本文复制引用
黄志轩,何天伦,郭祥,陈达..液态奶中镉、铜等重金属的光谱智能检测新方法研究[J].分析测试学报,2024,43(7):1032-1038,7.基金项目
国家自然科学基金资助(21973111) （21973111）
