基于微阵列等电聚焦电泳与曼哈顿算法的动物源性饲料筛查研究OA
Screening of Animal-derived Feed Materials via Microarray Isoelectric Focusing and Manhattan Distance Similarity Algorithm
基于微阵列等电聚焦电泳(mIEF)对动物源性饲料原料进行筛查研究.首先,优化了饲料样本的mIEF流程,包含样本前处理、水化上样、mIEF分离以及在线成像等,解决了饲料样本由于成分复杂以及高盐环境带来的干扰.其次,通过重复实验获取15种动物源性饲料的375个mIEF特征图谱,构建了基于mIEF数据的饲料指纹图谱数据库.最后,结合曼哈顿距离相似度算法对未知饲料样本进行比对分析,实际样本鉴别准确率达84.3％,验证了方法的可行性.相比传统饲料鉴定方法,mIEF技术结合曼哈顿算法具有高通量、高分辨率、操作简便且成本低的优势,为饲料溯源与质量安全控制提供了新路径.
This paper conducts a study on the identification of animal-derived feed materials based on microarray isoelectric focusing(mIEF).At first,a series of optimizations were carried out on the whole process of mIEF for screening of feed materials,which included sample pretreatment,rehy-dration loading,mIEF separation,and online imaging successfully solving the problems caused by the complex composition and high-salt content of feed materials.Secondly,through repeated experi-ments,375 mIEF patterns of 15 kinds of animal-derived feeds were obtained,and a feed pattern da-tabase based on mIEF data was constructed for further similarity analysis.Finally,the similarity al-gorithm of Manhattan distance was selected for the comparison and analysis of unknown feed samples,the screening accuracy of actual samples was up to 84.3％,further verifying the technical feasibility of this method.Compared to conventional methods for feed screening,the mIEF technology integrat-ed with the Manhattan algorithm offers advantages of high-throughput,high-resolution,simplified operation,and lower costs,providing a novel approach for feed traceability and quality and safety control.
卢秀楠;田佑吏;刘伟文;张强;许旭;曹成喜
上海应用技术大学 化工与能源技术学部,上海 201418上海交通大学自动化与智能感知学院,上海 200240上海交通大学自动化与智能感知学院,上海 200240上海交通大学自动化与智能感知学院,上海 200240上海应用技术大学 化工与能源技术学部,上海 201418上海交通大学自动化与智能感知学院,上海 200240
化学化工
等电聚焦电泳饲料原料饲料筛查曼哈顿距离
isoelectric focusingfeed materialsfeed screeningManhattan distance
《分析测试学报》 2026 (1)
40-49,10
国家自然科学基金项目(22104082,31727801)国家资助博士后研究人员计划(GZC20241027)
评论