Mathematical models in ruminant nutrition

Tedeschi, L. O.; Fox, D. G.; Sainz, Roberto Daniel; Barioni, L. G.; Medeiros, S. R. de; Boin, Celso

doi:10.1590/s0103-90162005000100015

Cited by 56 publications

(29 citation statements)

References 67 publications

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“…Later, several other models of lactating animals, mainly in cattle, have been published in the last 20 years (e.g. reviews in Sauvant, 1992 and1996;Chalupa et al, 2004;Tedeschi et al, 2005). The main objective of Baldwin's work was to provide, at the level of metabolic pathways and throughout the lactation cycle, a modelling framework to embed knowledge and a simulation tool to aid interpretation of experimental data.…”

Section: Introductionmentioning

confidence: 99%

A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 1. Trajectories of life function priorities and genetic scaling

Martin

Sauvant

2010

Animal

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The prediction of the control of nutrient partitioning, particularly energy, is a major issue in modelling dairy cattle performance. The proportions of energy channelled to physiological functions (growth, maintenance, gestation and lactation) change as the animal ages and reproduces, and according to its genotype and nutritional environment. This is the first of two papers describing a teleonomic model of individual performance during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. The conceptual framework is based on the coupling of a regulating sub-model providing teleonomic drives to govern the work of an operating sub-model scaled with genetic parameters. The regulating sub-model describes the dynamic partitioning of a mammal female's priority between life functions targeted to growth (G), ageing (A), balance of body reserves (R) and nutrient supply of the unborn (U), newborn (N) and suckling (S) calf. The so-called GARUNS dynamic pattern defines a trajectory of relative priorities, goal directed towards the survival of the individual for the continuation of the specie. The operating sub-model describes changes in body weight (BW) and composition, foetal growth, milk yield and composition and food intake in dairy cows throughout their lifespan, that is, during growth, over successive reproductive cycles and through ageing. This dynamic pattern of performance defines a reference trajectory of a cow under normal husbandry conditions and feed regimen. Genetic parameters are incorporated in the model to scale individual performance and simulate differences within and between breeds. The model was calibrated for dairy cows with literature data. The model was evaluated by comparison with simulations of previously published empirical equations of BW, body condition score, milk yield and composition and feed intake. This evaluation showed that the model adequately simulates these production variables throughout the lifespan, and across a range of dairy cattle genotypes.

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Section: Introductionmentioning

confidence: 99%

A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 1. Trajectories of life function priorities and genetic scaling

Martin

Sauvant

2010

Animal

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“…Um dos maiores problemas na construção de modelos matemáticos é o nível de agregação das equações (Tedeschi et al, 2005).…”

Section: Introductionunclassified

Validação de modelos matemáticos para predição de consumo voluntário e ganho em peso de bovinos

et al. 2011

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RESUMOAvaliou-se a utilização das equações do Cornell Net Carbohydrate and Protein System (CNCPS) e Nacional Research Council (NRC) nível 1 para predição de consumo de matéria seca e ganho em peso médio diário em condições tropicais de confinamento. Utilizou-se 23 bovinos mestiços Holandês/Zebu confinados em baias individuais com idade média de 20 meses e 260 kg de peso vivo no início do experimento. As dietas experimentais eram isonitrogenadas compostas por dois níveis de ingestão de energia com 50 ou 80% de inclusão de concentrado na base da matéria seca para os tratamentos médio (TM) e alto (TA), respectivamente. Observou-se respostas variáveis dos valores observados e preditos de consumo de matéria seca e ganho em peso em função dos níveis alimentares sendo que as melhores predições de consumo foram para o tratamento de médio nível de concentrado em que as equações de regressão apresentaram R 2 = 0,61 e 0,63 para o CNCPS e NRC, respectivamente. Os modelos foram ineficientes para predição do consumo de matéria seca no tratamento de alta inclusão de concentrado e não apresentaram predição acurada de ganho em peso médio diário em nenhuma das condições experimentais analisadas. SUMMARYWe evaluated the use of equations of the Cornell Net Carbohydrate and Protein System (CNCPS) and National Research Council (NRC) level 1 to predict the dry matter intake and daily weight gain in tropical conditions of feedlot. We used 23 crossbred steers Holstein / Zebu kept in individual stalls with a mean age of 20 months and 260 kg live weight at the start of the experiment. The experimental diets were isonitrogenous composed of two levels of energy intake with 50 or 80% of concentrate in dry matter basis for treatments medium (TM) and high (TA), respectively. Observed variable responses between the observed and predicted values for dry matter intake and weight gain depending on level of concentrate. The best estimate of dry matter intake occurred for the treatment of middle level of concentrate on which the regression equations presented R 2 = 0.61 and 0.63 for the CNCPS and NRC, respectively. The models were inefficient for predicting dry matter intake in the treatment of high concentrate inclusion and did not present accurate prediction of daily weight gain in any experimental conditions analyzed. INTRODUÇÃOOs modelos matemáticos são utilizados como ferramentas para estimar as exigências dos animais e o valor nutritivo dos alimentos em cada cenário de produção agrícola e,

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“…Mathematical models have been proven to be powerful tools for improving animal performance while reducing nutrient excretion (TEDESCHI et al, 2005). This improved "nutrient accounting" is made possible by utilizing the accumulated scientific knowledge of requirement of energy and nutrients of the animals and the supply of energy and nutrients to develop models that predict animal requirements and diet utilization in each unique production scenario.…”

Section: Introductionmentioning

confidence: 99%

“…The second most important step is determining the appropriate mix of empirical and mechanistic representations of physiological functions, given the availability of development and evaluation datasets, inputs typically available and the benefits versus the risks of use associated with increased sensitivity (TEDESCHI et al, 2005). Several mathematical models based on feeding standards or feed evaluation systems for sheep and goats have been developed by different countries.…”

Section: Introductionmentioning

confidence: 99%

A nutrition mathematical model to account for dietary supply and requirements of energy and nutrients for domesticated small ruminants: the development and evaluation of the Small Ruminant Nutrition System

2008

Self Cite

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-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. and changes in SBW of mature sheep. The SRNS for goats is suitable for predicting ME intake and the energy balance of lactating and non-lactating adult goats and the ADG of kids of dairy, meat, and indigenous breeds. The SRNS model is available at http://nutritionmodels.tamu.edu.

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Mathematical models in ruminant nutrition

Cited by 56 publications

References 67 publications

A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 1. Trajectories of life function priorities and genetic scaling

A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 1. Trajectories of life function priorities and genetic scaling

Validação de modelos matemáticos para predição de consumo voluntário e ganho em peso de bovinos

A nutrition mathematical model to account for dietary supply and requirements of energy and nutrients for domesticated small ruminants: the development and evaluation of the Small Ruminant Nutrition System

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