Use of Mechanistic Nutrition Models to Identify Sustainable Food Animal Production

Abstract

To feed people in the coming decades, an increase in sustainable animal food production is required. The efficiency of the global food production system is dependent on the knowledge and improvement of its submodels, such as food animal production. Scientists use statistical models to interpret their data, but models are also used to understand systems and to integrate their components. However, empirical models cannot explain systems. Mechanistic models yield insight into the mechanism and provide guidance regarding the exploration of the system. This review offers an overview of models, from simple empirical to more mechanistic models. We demonstrate their applications to amino acid transport, mass balance, whole-tissue metabolism, digestion and absorption, growth curves, lactation, and nutrient excretion. These mechanistic models need to be integrated into a full model using big data from sensors, which represents a new challenge. Soon, training in quantitative and computer science skills will be required to develop, test, and maintain advanced food system models.

Energy: Protein Ratio in Ruminants: Insights from the Intragastric Infusion Technique

“…Recent years have shown the replacement of a factorial with a more mechanistic model of rationing based on studies to predict the flux of energy yielding nutrients [ 131 , 132 ] and protein [ 132 , 133 ] post-absorption. These systems describe constant turnover functions such as protein turnover in the muscle and viscera and triglyceride turnover in adipose tissue while assuming that requirements are a function not only of the present state but also prior feeding regime [ 134 ].…”

“…These systems describe constant turnover functions such as protein turnover in the muscle and viscera and triglyceride turnover in adipose tissue while assuming that requirements are a function not only of the present state but also prior feeding regime [ 134 ]. The application of such models on farm is however constrained by their high errors in predicting performance (liveweight gain, milk yield/day [ 131 , 134 ]).…”

Progress on Infrared Imaging Technology in Animal Production: A Review

“…The new round of information technology revolution represented by the Internet of Things, cloud computing, big data and artificial intelligence promotes the transformation of roughly traditional animal husbandry to knowledge-based, technology-based, and modernized intelligent animal husbandry. In addition, technological advantages have become an essential factor driving the rapid development of animal husbandry [ 3 , 4 ]. Intelligent animal husbandry urgently needs new technical means to be used in animal production to achieve accurate, real-time, and dynamic monitoring of animal physiological states [ 5 , 6 , 7 , 8 ].…”

Validation of in situ disappearance curves utilizing mathematical models for incubating fish meal and cottonseed mea

“…The use of different models to estimate nutrient degradability parameters and formulating hypotheses about the biological principles governing the separation of ruminal digestion, leads to the development of mathematical models, that have ability to describing the disappearance of the rumen. Using these models ruminal digestion of feed can be estimated and different nutritional systems can be compared (Hanigan & Daley, 2019;Lapierre, Larsen, Sauvant, Van Amburgh, & Van Duinkerken, 2018).…”