Development of a mathematical model to study the impacts of production and management policies on the herd dynamics and profitability of dairy goats

Guimarães, Vinícius Pereira; Tedeschi, L. O.; Rodrigues, Marcelo Teixeira

doi:10.1016/j.agsy.2009.05.007

Cited by 26 publications

(19 citation statements)

References 42 publications

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“…These authors showed that there is no one-way relationship between variability in lifetime performance, the level of constraint influencing the livestock system and the type of production project. Tolerating or even seeking in-herd diversity can help buffer variations in the environment or reinforce herd adaptability to a project that is demanding from a biological viewpoint (Guimaraes et al, 2009 Modelling approach Several authors have pointed out the need to pay more attention to decision-making processes in simulation models to improve models as decision support systems (McCown, 2002;Garcia et al, 2005;Woodward et al, 2008). Others advocate the development of models linking farmers' decisions with the biological behaviour of females in the long term (Tichit et al, 2004 and.…”

Section: Simulation Resultsmentioning

confidence: 99%

An individual-based model simulating goat response variability and long-term herd performance

Puillet

Martin²,

Sauvant³

et al. 2010

Animal

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Finding ways of increasing the efficiency of production systems is a key issue of sustainability. System efficiency is based on long-term individual efficiency, which is highly variable and management driven. To study the effects of management on herd and individual efficiency, we developed the model simulation of goat herd management (SIGHMA). This dynamic model is individual-based and represents the interactions between technical operations (relative to replacement, reproduction and feeding) and individual biological processes (performance dynamics based on energy partitioning and production potential). It simulates outputs at both herd and goat levels over 20 years. A farmer's production project (i.e. a targeted milk production pattern) is represented by configuring the herd into female groups reflecting the organisation of kidding periods. Each group is managed by discrete events applying decision rules to simulate the carrying out of technical operations. The animal level is represented by a set of individual goat models. Each model simulates a goat's biological dynamics through its productive life. It integrates the variability of biological responses driven by genetic scaling parameters (milk production potential and mature body weight), by the regulations of energy partitioning among physiological functions and by responses to diet energy defined by the feeding strategy. A sensitivity analysis shows that herd efficiency was mainly affected by feeding management and to a lesser extent by the herd production potential. The same effects were observed on herd milk feed costs with an even lower difference between production potential and feeding management. SIGHMA was used in a virtual experiment to observe the effects of feeding strategies on herd and individual performances. We found that overfeeding led to a herd production increase and a feed cost decrease. However, this apparent increase in efficiency at the herd level (as feed cost decreased) was related to goats that had directed energy towards body reserves. Such a process is not efficient as far as feed conversion is concerned. The underfeeding strategy led to production decrease and to a slight feed cost decrease. This apparent increase in efficiency was related to goats that had mobilised their reserves to sustain production. Our results highlight the interest of using SIGHMA to study the underlying processes affecting herd performance and analyse the role of individual variability regarding herd response to management. It opens perspectives to further quantify the link between individual variability, herd performance and management and thus further our understanding of livestock farming systems.Keywords: simulation, herd, management, individual variability, dairy goat ImplicationsThe evaluation and design of sustainable livestock farming systems require predicting herd responses to management. This study describes a dairy goat herd model, representing dynamic interactions between management and individual biological processes. The model provides a...

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Section: Simulation Resultsmentioning

confidence: 99%

An individual-based model simulating goat response variability and long-term herd performance

Puillet

Martin²,

Sauvant³

et al. 2010

Animal

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“…Another important aspect is reproduction because it is directly connected to the ability of a farmer to expand its production (either by retaining more ani mals or obtaining new animal genetics) and consequently increase profitability by taking advantage of the economy of scale. Guimarães et al (2009) has indicated that preg nancy and mortality rates are the main variables affecting the expansion of dairy goat herds.…”

Section: Developing Agribusiness Models For the Tropical And Subtropimentioning

confidence: 99%

“…Besides the typical gestating, lactating, breeding animal stocks commonly assumed by the models based on Meadows (1970) work, Guimarães et al (2009) added a second dimension of aging chain complexity by creating up to five parturition stages. The gestating, lac tating, and breeding dynamics were modelled within each parturition component as shown in Fig.…”

Section: Agribusiness Modellingmentioning

confidence: 99%

“…Recently, Guimarães et al (2009) developed a SD model to understand how some biological aspects would impact the herd dynamics of dairy goats under a Brazilian pro duction scenario. Besides the typical gestating, lactating, breeding animal stocks commonly assumed by the models based on Meadows (1970) work, Guimarães et al (2009) added a second dimension of aging chain complexity by creating up to five parturition stages.…”

Section: Agribusiness Modellingmentioning

confidence: 99%

“…The gestating, lac tating, and breeding dynamics were modelled within each parturition component as shown in Fig. 2 of Guimarães et al (2009) work. Their work confirmed that reproductive and sanitary aspects of the dairy goat industry are crucial to ensure successful long life entrepreneurship.…”

Section: Agribusiness Modellingmentioning

confidence: 99%

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2011

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Small ruminants are important assets in several regions of the world. They account for more than half of the domesticated ruminants. Despite the growth in goat production in the world (more than 2% per ye. ar), research related to goat production is less than desired. One underused but potentially valuable approach for research on small ruminants is sim ulation modelling. Models of the components of small ruminant systems can enhance the financial returns and reduce negative environmental impacts. These models can be used to assess many dimensions of small ruminant production, from rumen dynamics to economic policies designed to support small ruminant production. Understanding the nutrition, pro duction, and economic policy feedback signals and planning ahead is crucial to build a robust and integrated production activity that can be managed under different production scenarios. System Dynamics (SD) is a computer-aided modelling methodology that can be used to perform policy analysis and decision support system (DSS) applied to dynamic problems arising in complex social, managerial, economic. or ecological dynamic systems characterized by interdependence, mutual interaction, information feedback. and circular causality. SD can be used as a modelling tool to aggregate knowledge to solve d ifferent types of problems that have a limited scope to a specific location or have broad trends of applications across locations and areas of science. Important issues of broad application include the bearings ofanimal production in the climate change and the impacts of climate change in animal production, alternative production scenarios ofanimal and crop integra tion, associations between animal production and business (economics, marketing). The trend of increasing small ruminants in tropical and subtropical regions and an increasing pressure on tropical and subtropical livestock systems to produce food, to feed livestock. and to produce energy crops warrants the development ofDSS to address issues such as what is the "real" benefits of livestock. the negative impacts livestock can have on greenhouse-gas emissions and the environment, and the effects ofclimate change on livestock systems.

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Development of a mathematical model to study the impacts of production and management policies on the herd dynamics and profitability of dairy goats

Cited by 26 publications

References 42 publications

An individual-based model simulating goat response variability and long-term herd performance

An individual-based model simulating goat response variability and long-term herd performance

Using System Dynamics modelling approach to develop management tools for animal production with emphasis on small ruminants

Applied Systems Analysis for Analysing Challenges in Construction Projects: A Methodological Approach

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