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Modelling preference and diet selection patterns by grazing ruminants: a development in a mechanistic model of a grazing dairy cow, MINDY

Author:
Gregorini, P., Villalba, J. J., Provenza, F. D., Beukes, P. C., Forbes, J. M.
Source:
Animal production science 2015 v.55 no.3 pp. 360-375
ISSN:
1836-0939
Subject:
dairy cows, diurnal variation, dynamic models, ecology, food choices, forage, foraging, grazing, mechanistic models, metabolism, prediction, rumen fermentation, selection response, sheep
Abstract:
The work presented here represents additions to the mechanistic and dynamic model of a grazing dairy cow (MINDY). The additions include a module representing preference and selection, based on two theories, namely, post-ingestive feedback and discomfort. The model was evaluated by assessing its ability to simulate patterns of preference and selection in response to a variety of feeding management. The improvements detailed here enable a realistic simulation of patterns of food selection by grazing ruminants, based on a range of feeding situations from different studies with cattle and sheep. These simulations indicate that the concepts encoded in MINDY capture several of the underlying biological mechanisms that drive preferences and selective behaviour. Thus, simulations using MINDY allow prediction of daily and diurnal patterns of selection based on preference, derived from some post-ingestive feedbacks and total discomfort. Estimates of herbage intake and parallel measurements of ingestive behaviour, rumen function and metabolism in grazing ruminants pose experimental and technical difficulties, and matching these processes to animal preference and selective behaviour is a greater challenge. As a consequence, advances in knowledge of foraging behaviour and dietary choice are slow and costly. On completion of more thorough testing, MINDY can be used as a tool for exploratory mechanistic research, to design and organise experimental programs to address a range of factors that control intake and its ecology, helping advance knowledge faster and at a low cost.
Agid:
1204356