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用于预测具有不同性质的猪粪中土霉素、环丙沙星和磺胺嘧啶吸附的定量模型。

Quantitative models for predicting adsorption of oxytetracycline, ciprofloxacin and sulfamerazine to swine manures with contrasting properties.

机构信息

Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, Beijing 100081, PR China.

China Waterborne Transport Research Institute, Beijing 100088, PR China.

出版信息

Sci Total Environ. 2018 Sep 1;634:1148-1156. doi: 10.1016/j.scitotenv.2018.04.114. Epub 2018 Apr 12.

DOI:10.1016/j.scitotenv.2018.04.114
PMID:29660871
Abstract

Understanding antibiotic adsorption in livestock manures is crucial to assess the fate and risk of antibiotics in the environment. In this study, three quantitative models developed with swine manure-water distribution coefficients (LgK) for oxytetracycline (OTC), ciprofloxacin (CIP) and sulfamerazine (SM1) in swine manures. Physicochemical parameters (n=12) of the swine manure were used as independent variables using partial least-squares (PLSs) analysis. The cumulative cross-validated regression coefficients (Q) values, standard deviations (SDs) and external validation coefficient (Q) ranged from 0.761 to 0.868, 0.027 to 0.064, and 0.743 to 0.827 for the three models; as such, internal and external predictability of the models were strong. The pH, soluble organic carbon (SOC) and nitrogen (SON), and Ca were important explanatory variables for the OTC-Model, pH, SOC, and SON for the CIP-model, and pH, total organic nitrogen (TON), and SOC for the SM1-model. The high VIPs (variable importance in the projections) of pH (1.178-1.396), SOC (0.968-1.034), and SON (0.822 and 0.865) established these physicochemical parameters as likely being dominant (associatively) in affecting transport of antibiotics in swine manures.

摘要

了解抗生素在畜禽粪便中的吸附对于评估抗生素在环境中的归趋和风险至关重要。本研究采用猪粪-水分配系数(LgK),建立了三种定量模型,用于预测土霉素(OTC)、环丙沙星(CIP)和磺胺甲噁唑(SM1)在猪粪中的分布。采用偏最小二乘(PLS)分析,选择猪粪理化参数(n=12)作为自变量。三个模型的累积交叉验证回归系数(Q)值、标准偏差(SD)和外部验证系数(Q)分别为 0.761-0.868、0.027-0.064 和 0.743-0.827,表明模型内部和外部预测能力较强。pH、可溶性有机碳(SOC)和氮(SON)以及 Ca 是 OTC 模型的重要解释变量,pH、SOC 和 SON 是 CIP 模型的重要解释变量,而 pH、总有机氮(TON)和 SOC 是 SM1 模型的重要解释变量。pH(1.178-1.396)、SOC(0.968-1.034)和 SON(0.822 和 0.865)的高 VIPs(投影变量重要性)表明这些理化参数可能在影响抗生素在猪粪中的传输中起主导作用(关联)。

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