基于逐步回归模型的池塘养殖环境环丙沙星暴露水平预测模型的构建  

Construction of a prediction model for ciprofloxacin exposure level in aquaculture pond environment based on stepwise regression model

作　　者：高玉晓 陈曦 马志远 方龙香 裘丽萍[2,3,4,5] 孟顺龙 宋超[1] GAO Yuxiao;CHEN Xi;MA Zhiyuan;FANG Longxiang;QIU Liping;MENG Shunlong;SONG Chao(Wuxi Fisheries College,Nanjing Agricultural University,Wuxi 214081,China;Freshwater Fisheries Research Center,Chinese Academy of Fishery Sciences,Wuxi 214081,China;Laboratory of Quality&Safety Risk Assessment for Aquatic Products on Environmental Factors(Wuxi),Ministry of Agriculture and Rural Affairs,Wuxi 214081,China;Key Open Laboratory of Inland Fishery Ecological Environment and Resources,Chinese Academy of Fishery Sciences,Wuxi 214081,China;Key Laboratory of Control of Quality and Safety for Aquatic Products,Ministry of Agriculture and Rural Affairs,Beijing 100141,China)

机构地区：[1]南京农业大学无锡渔业学院,江苏无锡214081 [2]中国水产科学研究院淡水渔业研究中心,江苏无锡214081 [3]农业农村部水产品质量安全环境因子风险评估实验室(无锡),江苏无锡214081 [4]中国水产科学研究院内陆渔业生态环境和资源重点开放实验室,江苏无锡214081 [5]农业农村部水产品质量安全控制重点实验室,北京100141

出　　处：《农业环境科学学报》2025年第3期750-758,共9页Journal of Agro-Environment Science

基　　金：中央公益性科研单位基本科研项目(2023JBFM02);无锡市水产品中新型抗生素污染物的鉴定及快速检测技术开发项目(K20231029);现代产业技术体系项目(CARS-46)。

摘　　要：为实现对池塘养殖水体中环丙沙星残留量的短期预测,采用高效液相色谱串联质谱联用技术,对太湖流域养殖池塘的水体和沉积物样本进行恩诺沙星(ENR)与环丙沙星(CIP)残留量分析。通过详细的数据分析,揭示了池塘水体中恩诺沙星含量、环丙沙星含量以及沉积物中恩诺沙星含量、环丙沙星含量之间的线性相关性数据,并进一步重点考察了关键理化指标(温度、溶氧、pH,以及样品的悬浮物含量、总氮、总磷和高锰酸盐指数)与以下4个过程的相互作用关系:(1)沉积物恩诺沙星含量与环丙沙星含量;(2)水体恩诺沙星含量与环丙沙星含量;(3)水体恩诺沙星含量与沉积物恩诺沙星含量;(4)沉积物环丙沙星含量与水体环丙沙星含量。通过细致的变量筛选与计算,最终构建了沉积物中环丙沙星含量的预测模型:C_(CIP)^((sed))=0.647+0.191C_(ENR)^((sed))-1.358CTP,该模型的决定系数(R)为0.805,具有一定的预测价值;同时,还建立了沉积物中环丙沙星含量预测水体中环丙沙星含量的预测模型:C_(CIP)^((wat))=-0.413-0.017C_(CIP)^((sed))-0.063A+0.174B,其R达到了0.646,显示出良好的预测准确性。模型的构建为水产池塘养殖水体中环丙沙星残留量的有效监控提供了技术支撑,可通过沉积物中环丙沙星的含量预估水体中环丙沙星的含量。This study aims to achieve short-term prediction of ciprofloxacin(CIP)residue levels in aquaculture pond water.High-performance liquid chromatography tandem mass spectrometry(HPLC-MS/MS)was employed to analyze the residues of enrofloxacin(ENR)and CIP in water and sediment samples collected from aquaculture ponds in the Taihu Lake basin.Through comprehensive data analysis,this study revealed significant linear correlations between ENR and CIP concentrations in both pond water and sediment matrices.Furthermore,we systematically investigated the interactions between key physicochemical parameters(temperature,dissolved oxygen,pH,suspended solids,total nitrogen,total phosphorus,and permanganate index)and the following four processes:(1)the relationship between sediment ENR and CIP concentrations;(2)the correlation between water column ENR and CIP levels;(3)the interaction between water column ENR and sediment ENR concentrations;and(4)the association between sediment CIP and water column CIP levels.Through meticulous variable selection and calculation,a predictive model for CIP concentration in sediments was established:C_(CIP)^((sed))=0.647+0.191C_(ENR)^((sed))-1.358CTP,with a correlation coefficient(R)of 0.805,indicating its predictive value.Additionally,a predictive model for CIP concentration in pond water based on sediment CIP content was formulated:C_(CIP)^((wat))=-0.413-0.017C_(CIP)^((sed))-0.063A+0.174B with a correlation coefficient R of 0.646,demonstrating good predictive accuracy.The development of these models provides technical support for the effective monitoring of CIP residue levels in aquaculture pond water.By the CIP content in sediments,an estimation of CIP levels in the pond water can be achieved.

关 键 词：环丙沙星 恩诺沙星 回归模型 预测模型 

分 类 号：X714[环境科学与工程—环境工程]