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| Tedeschi,Luis Orlindo; Fonseca,Mozart Alves; Muir,James Pierre; Poppi,Dennis P.; Carstens,Gordon E.; Angerer,Jay P.; Fox,Danny Gene. |
| ABSTRACT Despite tremendous advancements in the livestock sector, additional opportunities exist to improve even further livestock production around the globe. Forecasting is not an exact science and it relies heavily on past and current knowledge. Improvements in the nutritional sciences (both human and animal) include a better understanding of agents that cause deterioration of human health, improving the quality of animal products, applying effective fetal programming, developing new feeds and feeding strategies, and revisiting longstanding technologies. Improvements in the understanding of the rumen microbiome will enable scientists to increase the fermentation efficiency and, hopefully, select microbial species of greater interest. Improvements in... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Forecasting; Livestock; Ruminant; Solutions; Production; Vision. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017000500452 |
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| Tedeschi,Luis Orlindo; Cannas,Antonello; Fox,Danny Gene. |
| A mechanistic model that predicts nutrient requirements and biological values of feeds for sheep (Cornell Net Carbohydrate and Protein System; CNCPS-S) was expanded to include goats and the name was changed to the Small Ruminant Nutrition System (SRNS). The SRNS uses animal and environmental factors to predict metabolizable energy (ME) and protein, and Ca and P requirements. Requirements for goats in the SRNS are predicted based on the equations developed for CNCPS-S, modified to account for specific requirements of goats, including maintenance, lactation, and pregnancy requirements, and body reserves. Feed biological values are predicted based on carbohydrate and protein fractions and their ruminal fermentation rates, forage, concentrate and liquid... |
| Tipo: Info:eu-repo/semantics/article |
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| Ano: 2008 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982008001300020 |
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| Tedeschi,Luís Orlindo; Fox,Danny Gene; Sainz,Roberto Daniel; Barioni,Luís Gustavo; Medeiros,Sérgio Raposo de; Boin,Celso. |
| Mathematical models can be used to improve performance, reduce cost of production, and reduce nutrient excretion by accounting for more of the variation in predicting requirements and feed utilization in each unique production situation. Mathematical models can be classified into five or more categories based on their nature and behavior. Determining the appropriate level of aggregation of equations is a major problem in formulating models. The most critical step is to describe the purpose of the model and then to determine the appropriate mix of empirical and mechanistic representations of physiological functions, given development and evaluation dataset availability, inputs typically available and the benefits versus the risks of use associated with... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Cattle; Feeding; Nutrient; Requirement; Supply. |
| Ano: 2005 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162005000100015 |
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