Using robust Bayesian network to estimate the residuals of fluoroquinolone antibiotic in soil
文献类型：SCI/SSCI论文
| 作者 | Li X. W.; Xie, Y. F.; Li, L. F.; Yang, X. F.; Wang, N.; Wang, J. F. |
| 发表日期 | 2015 |
| 关键词 | Antibiotic residue Bayesian network Fluoroquinolone antibiotic Intensive vegetable cultivation area vegetable cultivation area northern china metabolite ciprofloxacin veterinary antibiotics catastrophic risk spatial data manure enrofloxacin pharmacokinetics |
| 英文摘要 | Prediction of antibiotic pollution and its consequences is difficult, due to the uncertainties and complexities associated with multiple related factors. This article employed domain knowledge and spatial data to construct a Bayesian network (BN) model to assess fluoroquinolone antibiotic (FQs) pollution in the soil of an intensive vegetable cultivation area. The results show: (1) The relationships between FQs pollution and contributory factors: Three factors (cultivation methods, crop rotations, and chicken manure types) were consistently identified as predictors in the topological structures of three FQs, indicating their importance in FQs pollution; deduced with domain knowledge, the cultivation methods are determined by the crop rotations, which require different nutrients (derived from the manure) according to different plant biomass. (2) The performance of BN model: The integrative robust Bayesian network model achieved the highest detection probability (pd) of high-risk and receiver operating characteristic (ROC) area, since it incorporates domain knowledge and model uncertainty. Our encouraging findings have implications for the use of BN as a robust approach to assessment of FQs pollution and for informing decisions on appropriate remedial measures. |
| 出处 | Environmental Science and Pollution Research |
| 卷 | 22 |
| 期 | 22 |
| 页 | 17540-17549 |
| 语种 | 英语 |
| ISSN号 | 0944-1344 |
| DOI标识 | 10.1007/s11356-015-4751-9 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/43546]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Li X. W.,Xie, Y. F.,Li, L. F.,et al. Using robust Bayesian network to estimate the residuals of fluoroquinolone antibiotic in soil. 2015. |
入库方式： OAI收割
来源：地理科学与资源研究所
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