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An object-oriented Bayesian network approach for establishing swine manure-borne natural estrogenic compounds budget

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A facility-wide estrogen budget model was developed to assess the excretion of natural estrogens by swine in a commercial swine farrowing concentrated animal feeding operations (CAFO) in North Carolina, using an object oriented Bayesian network (OOBN) approach. The OOBN model is the combination of twelve objects of Bayesian network models, which characterize the estrogen budget flows based on the sow reproductive cycle (i.e., pre-estrus, estrus, and lactation) for the three natural estrogen types [estrone (E1), 17β-estradiol (E2), and estriol (E3)] within each barn. This OOBN model provides a mechanism to quantify the levels of the natural estrogens and their probabilistic distributions with regard to estrogen type, waste sources such as urine, feces, and recycling lagoon slurry, and animal reproductive status. Moreover, the OOBN model allows us to assess the overall contribution of natural estrogen compounds from each operational unit of the CAFO, while accounting for the uncertainties. Results from the OOBN model indicate a rank order of lactating sows N gestating sows N breeding sows in terms of contribution of estrogen loads to the total natural estrogen budget. As to estrogen type, E1 was found as the major estrogen metabolite with the summed concentrations of urine, feces, and flushing slurry wastes exceeding 3000 ng/l N 90% of the time. As to waste sources, the flushing slurry waste was found to be a major contributor of the estrogen budget compared with urine and feces wastes from barn animals.

Impact/Purpose

This paper presents a quantitative model for evaluating the fate and transport of estrogens in the waste of a commercial swine CAFO.

Citation

Lee, B., S. Kullman, E. Yost, L. Worley-Davis, AND K. Reckhow. An object-oriented Bayesian network approach for establishing swine manure-borne natural estrogenic compounds budget. Elsevier BV, AMSTERDAM, NETHERLANDS, 639:815-825, (2018). [DOI: 10.1016/j.scitotenv.2018.05.209]

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DOI: An object-oriented Bayesian network approach for establishing swine manure-borne natural estrogenic compounds budget
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Last updated on June 16, 2020
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