Development of predictive equations for thermal conductivity of compost bedding

• Autor(a) principal: Damasceno, Flávio A.
• Data de Publicação: 2021
• Outros Autores: Taraba, Joseph L., Day, George B., Black, Randi A., Bewley, Jeffrey M., Fernandes, Tales J., Oliveira, Carlos E. A., Andrade, Rafaella R., Barbari, Matteo, Ferraz, Patrícia F. P., Leso, Lorenzo
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFLA
• Texto Completo: http://repositorio.ufla.br/jspui/handle/1/48922
• topic: Bedding material; Dairy cow; Modeling; Prediction; Thermal properties

Among animal facilities, compost-bedded pack (CBP) barns have attracted a lot of attention from milk producers and the scientific community. Systematic investigation of the main thermal properties utilizing sawdust in CBP barns is of environmental and economic relevance. In this paper, the aim was to (a) develop predictive equations for the thermal conductivity (k) of compost bedding as a function of moisture content (MC), the degree of compaction (DCo), and particle size (PS); and (b) investigate the links between k and depth within bedding material. Samples of compost bedding materials were collected from 42 commercial CBP barns distributed throughout Kentucky (USA). From these predictive equations, it was possible to understand how the MC, DCo, and PS of the bedding materials may influence the behavior of k. These results are very useful for solving obstacles to simulate and predict the variable outcomes of the compost bedding materials process in CBP barns, allowing for its optimization, consequently reducing the time and energy spent on their optimization and allowing for simulation and assessment of compost bedding process modifications. The results of the current study may have important implications in the design and management of bedded pack barns.