Sauvant / van Milgen / Faverdin Modelling Nutrient Digestion and Utilisation in Farm Animals

1. st Auflage. 2011
ISBN: 978-90-8686-712-7
Verlag: Wageningen Academic
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 417 Seiten, eBook

For more than 30 years, modelling has been an important method for integrating, in a flexible, comprehensive and widely applicable way, basic knowledge and biological concepts on digestion and metabolism in farm animals. The purpose of this book is to present the 'state of art' in this area. The chapters are written by leading teams and researchers in this field of study, mainly from Europe, North America and Australasia. Considerable progress has been made in topics dealing with: modelling methods, feeding behaviour, digestion and metabolic processes in ruminants and monogastric animals. This progress is clearly illustrated by the emergence of a new paradigm in animal nutrition, which has moved from the aim to cover the requirements of the animal to explaining and predicting the responses of the animals to diets (e.g., productivity and efficiency, impact on quality of products, environmental aspects, health and well-being). In this book several chapters illustrate that through empirical models, meta-analysis is an efficient tool to synthesize information gathered over recent decades. In addition, compared with other books on modelling farm animal nutrition, two new aspects received particular attention: expanding knowledge of the individual animal to understanding the functioning and management of herds, and the consideration of the environmental impact of animal production. This book is a valuable source of information for researchers, nutritionists, advisors, and graduate students who want to have up-to-date and concise information on mathematical modelling applied to farm animals.

Zielgruppe

Research

Autoren/Hrsg.

Sauvant, D.

van Milgen, J.

Faverdin, P.

Friggens, N.

Inhaltsverzeichnis

Preface. Part 1 – Advances in methodological aspects of modeling. A generic framework for simulating agricultural production systems; R. Martin-Clouaire, J.-P. Rellier. Population based growth curve analysis: a comparison between models based on ordinary or stochastic differential equations implemented in a nonlinear mixed effect framework; A.B. Strathe et al. Regression procedures for relationships between random variables; M.S. Dhanoa et al. Extracting biologically meaningful features from time-series measurements of individual animals: towards quantitative description of animal status; N.C. Friggens et al. Turning a cow into a goat with a teleonomic model of lifetime performance; O. Martin, D. Sauvant. Techniques to facilitate metabolic modeling with reference to dairy cows; R.C. Boston et al. Implementation of a genetic algorithm for optimization within the Cornell Net Carbohydrate and Protein System framework; T.P. Tylutki et al. Assessing and optimizing the performance of a mechanistic mathematical model of the sheep mammary gland; C. Dimauro et al. A new development in pig growth modeling; P.C.H. Morel et al. Identifiability and accuracy: a closer look at contemporary contributions and changes in these vital areas of mathematical modeling; L.O. Tedeschi, R. Boston. Part 2 – Modeling feeding behavior and regulation of feed intake. Modeling short-term feeding behavior; B.J. Tolkamp et al. A new Nordic structure evaluation systems for diets fed to dairy cows: a meta analysis; P. Nørgaard et al. Modeling within-day variability in feeding behavior in relation to rumen pH: application to dairy goats receiving an acidogenic diet; S. Giger-Reverdin et al. Modeling of the effects of heat stress on some feeding behavior and physiological parameters in cows; T. Najar et al. Part 3 – Modeling fermentation, digestion and microbial interactions in the gut. A generic multi-stage compartmental model for interpreting gas production profiles; S. López et al. A mechanistic model of pH and gas exchanges in the rumen and its in vitro application; A. Serment, D. Sauvant. Modeling rumen volatile fatty acids and its evaluation on net portal fluxes in ruminants; P. Nozière et al. Representing tissue mass and morphology in mechanistic models of digestive function in ruminants; A. Bannink et al. Fluctuations in methane emission in response to feeding pattern in lactating dairy cows; L.A. Crompton et al. Prediction of methane production in beef cattle within a mechanistic digestion model; J.L. Ellis et al. Relationship between passage rate and extrinsic diet characteristics derived from rumen evacuation studies performed with dairy cows; S. Krizsan et al. Ability of mathematical models to predict faecal output with a pulse dose of an external marker in sheep and goat; A. Moharrery. Part 4 – Modeling interactions between nutrients and physiological functions: consequence on product quality and animal health. Dynamic modeling of contractile and metabolic properties of bovine muscle; N.M. Schreurs et al. An isotope dilution model for partitioning phenylalanine uptake by the liver of lactating dairy cows; L.A. Crompton et al. Modeling the effects of insulin and amino acids on the phosphorylation of mTOR, Akt, and 4EBP1 in mammary cells; J.A.D.R.N. Appuhamy, M.D. Hanigan. From metabolisable energy to energy of absorbed nutrients: quantitative comparison of models; C. Loncke et al. Developemtn of a heat balance model for cattle under hot conditions; V.A. Thompson et al. An interactive, mechanistic nutrition model to determine energy efficiency of lactating dairy cows; L.O. Tedeschi et al. The development and evaluation of the Small Ruminant Nutrition System; A. Cannas et al. A model of phosphorus metabolism in growing sheep; R.S. Dias et al. A generic stoichiometric model to analyse the metabolic flexibility of the mammary gland in lactating dairy cows; S. Lemosquet et al. Model development of nutrient utilization to represent poultry growth dynamics: application to the turkey; V. Rivera-Torres et al. Modeling energy utilization in poultry; N.K. Sakomura et al. Model to estimate lysine requirements of broilers; J.C. Siqueira et al. Prediction of Nellore empty body composition using indirect measurements; M.I. Marcondes et al. Part 5 – Extrapolating from the animal to the herd. Precision feeding can significantly reduce feeding cost and nutrient excretion in growing animals; C. Pomar et al. A herd modeling approach to determine the economically and environmentally most interesting dietary amino acid level during the fattening period; L. Brossard et al. Evaluation of two feeding strategies with a herd model integrating individual variability; L. Puillet et al. SIMBAL: a herd simulator for beef cattle; L. Pérochon et al. Modeling the impacts of climate change on suckling grass-based systems with the Pasture Simulation Model; A.-I. Graux et al. Part 6 – Modeling the environmental impact of animal production. The fate of dietary phosphorus in the digestive tract of growing pigs and broilers; M.P. Létourneau-Montminy et al. Modeling the profile of growth in monogastric animals; E. Kebreab et al. Effects of nutritional strategies on simulated nitrogen excretion and methane emission in dairy cattle; J. Dijkstra et al. A whole farm-model to simulate the environmental impacts of animal farming systems: MELODIE; X. Chardon et al. Development and validation of a biophysical model of enteric methane emissions from Australian beef feedlots; S.K. Muir et al. Index.