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.
View Article and Find Full Text PDFAnimal feeding operations (AFOs) have been implicated as potentially major sources of estrogenic contaminants into the aquatic environment due to the relatively minimal treatment of waste and potential mobilization and transport of waste components from spray fields. In this study a Bayesian network (BN) model was developed to inform management decisions and better predict the transport and fate of natural steroidal estrogens from these sites. The developed BN model integrates processes of surface runoff and sediment loss with the modified universal soil loss equation (MUSLE) and the soil conservation service curve number (SCS-CN) runoff model.
View Article and Find Full Text PDFThe inflow, transformation, and attenuation of natural steroid hormones and phytoestrogens and estrogenic activity were assessed across the lagoon/sprayfield system of a prototypical commercial swine sow operation. Free and conjugated steroid hormones (estrogens, androgens, and progesterone) were detected in urine and feces of sows across reproductive stages, with progesterone being the most abundant steroid hormone. Excreta also contained phytoestrogens indicative of a soy-based diet, particularly, daidzein, genistein, and equol.
View Article and Find Full Text PDFIntegr Environ Assess Manag
October 2014
Commercial swine waste lagoons are regarded as a major reservoir of natural estrogens, which have the potential to produce adverse physiological effects on exposed aquatic organisms and wildlife. However, there remains limited understanding of the complex mechanisms of physical, chemical, and biological processes that govern the fate and transport of natural estrogens within an anaerobic swine lagoon. To improve lagoon management and ultimately help control the offsite transport of these compounds from swine operations, a probabilistic Bayesian network model was developed to assess natural estrogen fate and budget and then compared against data collected from a commercial swine field site.
View Article and Find Full Text PDFIn this study, the distribution of steroid hormones, phytoestrogens, and estrogenic activity was thoroughly characterized within the anaerobic waste lagoon of a typical commercial swine sow operation. Three independent rounds of sampling were conducted in June 2009, April 2010, and February 2011. Thirty-seven analytes in lagoon slurry and sludge were assessed using LC/MS-MS, and yeast estrogen screen was used to determine estrogenic activity.
View Article and Find Full Text PDFConcentrated animal feeding operations (CAFOs) are a major source of airborne endotoxins, which are air pollutants that can cause adverse health effects to both on-site farmers and neighbors. Release of airborne endotoxins to the environment can be reduced using proper waste treatment and management technologies. In this study, the levels of endotoxins released from two swine CAFOs using conventional lagoon-sprayfield technology were compared to those of 15 farms using various alternative waste management technologies in North Carolina.
View Article and Find Full Text PDFMicrobial air pollution from concentrated animal feeding operations (CAFOs) has raised concerns about potential public health and environmental impacts. We investigated the levels of bioaerosols released from two swine farms using conventional lagoon-sprayfield technology and ten farms using alternative waste treatment and management technologies in the United States. In total, 424 microbial air samples taken at the 12 CAFOs were analyzed for several indicator and pathogenic microorganisms, including culturable bacteria and fungi, fecal coliform, Escherichia coli, Clostridium perfringens, bacteriophage, and Salmonella.
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