Intensification of New Zealand beef farming systems

White, Todd; Snow, Val; King, W. M.

doi:10.1016/j.agsy.2009.08.003

Cited by 47 publications

(32 citation statements)

References 44 publications

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“…Increasing the intensity of production in beef systems generally increases total methane emissions (White et al, 2010), while lowering methane per kg of beef produced. However, management decisions can be made along the intensification spectrum as to how much to increase productivity and profitability versus reducing the environmental footprint.…”

Section: Discussionmentioning

confidence: 99%

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

Ash

Hunt

McDonald

et al. 2015

Agricultural Systems

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The financial health of beef cattle enterprises in northern Australia has declined markedly over the last decade due to an escalation in production and marketing costs and a real decline in beef prices. Historically, gains in animal productivity have offset the effect of declining terms of trade on farm incomes. This raises the question of whether future productivity improvements can remain a key path for lifting enterprise profitability sufficient to ensure that the industry remains economically viable over the longer term. The key objective of this study was to assess the production and financial implications for north Australian beef enterprises of a range of technology interventions (development scenarios), including genetic gain in cattle, nutrient supplementation, and alteration of the feed base through introduced pastures and forage crops, across a variety of natural environments. To achieve this objective a beef systems model was developed that is capable of simulating livestock production at the enterprise level, including reproduction, growth and mortality, based on energy and protein supply from natural C 4 pastures that are subject to high inter-annual climate variability. Comparisons between simulation outputs and enterprise performance data in three case study regions suggested that the simulation model (the Northern Australia Beef Systems Analyser) can adequately represent the performance beef cattle enterprises in northern Australia. Testing of a range of development scenarios suggested that the application of individual technologies can substantially lift productivity and profitability, especially where the entire feedbase was altered through legume augmentation. The simultaneous implementation of multiple technologies that provide benefits to different aspects of animal productivity resulted in the greatest increases in cattle productivity and enterprise profitability, with projected weaning rates increasing by 25%, liveweight gain by 40% and net profit by 150% above current baseline levels, although gains of this magnitude might not necessarily be realised in practice. While there were slight increases in total methane output from these development scenarios, the methane emissions per kg of beef produced were reduced by 20% in scenarios with higher productivity gain. Combinations of technologies or innovative practices applied in a systematic and integrated fashion thus offer scope for providing the productivity and profitability gains necessary to maintain viable beef enterprises in northern Australia into the future.Crown

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Section: Discussionmentioning

confidence: 99%

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

Ash

Hunt

McDonald

et al. 2015

Agricultural Systems

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“…The smallest spatial modelling unit was generally a field (Romera et al 2004;Pfister et al 2005). In a few cases, it was the so-called land unit, possibly aggregating several fields (Blazy et al 2010;Herve et al 2002) and in one case, the whole farm was treated as if it was a single paddock of pasture (White et al 2010). Animal processes were modelled at the scale of individual cows (Romera et al 2004), of average representative animals (Andrieu et al 2007;Martin et al 2011b), of the whole herd (White et al 2010).…”

Section: Computer Model Structurementioning

confidence: 99%

“…The biophysical models were either static (White et al 2010) or dynamic, operating on a time step of 1 year (Kerr et al 1999a, b), 1 week (Blazy et al 2010) or 1 day (Keating et al 2003), even when the related farm model was static (Martin et al 2011a). The remaining dynamic farm models had a time horizon ranging from one season (Cros et al 2003) to several years (Blazy et al 2010;Cacho et al 1995).…”

Section: Computer Model Structurementioning

confidence: 99%

“…Economic performance was assessed for instance with a net margin per hectare (Blazy et al 2010). Environmental goals for instance included grassland biodiversity (Jouven and Baumont 2008), pesticide use (Blazy et al 2010) and greenhouse gas emissions (White et al 2010). Social goals focused on the workload to ensure the feasibility of the farming systems designed (Herve et al 2002;Martin et al 2011b).…”

Section: Design Contextmentioning

confidence: 99%

See 1 more Smart Citation

Farming system design to feed the changing world. A review

Martin

Martin‐Clouaire

Duru

2012

Agron. Sustain. Dev.

118

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Agricultural production is unstable as a result of complex, dynamic and interrelated factors such as climate, markets and public policy that are beyond farmers' control. Farmers must therefore develop new farming systems incorporating innovations in objectives, organization and practices adapted to changing production contexts. As a consequence, agronomists have expanded the "farming system design" field of research. A variety of quantitative and qualitative design approaches have been developed to support the analysis of current farming systems and the design and evaluation of alternatives. A comprehensive literature assessment is lacking for this emerging field of agricultural science. Here we review 41 farming system design approaches using computer models. Our main findings are the following: (1) the reviewed literature do not make reference to the theoretical approaches from the field of design science. (2) Two categories of farming system approaches can be distinguished: optimisation approaches, and participatory and simulation-based approaches. These two categories are connected to two of the main design science theories. (3) For optimisation approaches, farming system design is mainly seen as a problem-solving process. Emphasis is placed on the computational exploration of the solution space by a problem-solving algorithm. (4) For participatory and simulation-based approaches, conceptualization of the design problem is central to the farming system design process. The subsequent exploration of the solution space relies on the creativity of humans. (5) Optimisation approaches, and participatory and simulationbased approaches are oriented towards the development of exploitative rather than exploratory innovations. Exploitative innovations involve the exploitation of available knowledge while exploration innovations build on knowledge created in the course of the design process.

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“…Dijkstra et al 1992;Li et al 1992;Kebreab et al 2004) as well as integrated whole-farm models (e.g. Little et al 2008;White et al 2010;Rotz et al 2011a) have been developed and implemented. Evaluation of management practices that reduce GHG emissions must be conducted at the farm scale using a whole-farm approach because implementation may yield synergistic and/or tradeoff effects among farm components, which impacts net farm GHG emissions (Janzen et al 2006;Gerber et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of greenhouse gas emissions from hog manure application in a Canadian cow–calf production system using whole-farm models

et al. 2016

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Abstract. The development of beneficial management practices is a key strategy to reduce greenhouse gas (GHG) emissions from animal agriculture. The objective of the present study was to evaluate the impact of time and amount of hog manure application on farm productivity and GHG emissions from a cow-calf production system using two whole-farm models. Detailed model inputs (climate, soil and manure properties, farm operation data) were collected from a 3-year field study that evaluated the following three treatments: no application of hog manure on grassland (baseline); a single application of hog manure on grassland in spring (single); and two applications of hog manure as fall and spring (split). All three treatments were simulated in a representative cow-calf production system at the farm-gate using the following whole-farm models: a Coupled Components Model (CCM) that used existing farm component models and the Integrated Farm System Model (IFSM). Annual GHG intensities for the baseline scenario were 17.7 kg CO 2 -eq/kg liveweight for CCM and 18.1 kg CO 2 -eq/kg liveweight for IFSM. Of the total farm GHG emissions, 73-77% were from enteric methane production. The application of hog manure on grassland showed a mean emission increase of 7.8 and 8.4 kg CO 2 -eq/kg liveweight above the baseline for the single and split scenarios, respectively. For the manured scenarios, farm GHG emissions were mainly from enteric methane (47-54%) and soil nitrous oxide (33-41%). Emission estimates from the different GHG sources in the farm varied between models for the single and split application scenarios. Although farm productivity was 3-4% higher in the split than in single application (0.14 t liveweight/ha), the environmental advantage of applying manure in a single or split application was not consistent between models for farm emission intensity. Further component and whole-farm assessments are required to fully understand the impact of timing and the amount of livestock manure application on GHG emissions from beef production systems.

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Intensification of New Zealand beef farming systems

Cited by 47 publications

References 44 publications

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

Boosting the productivity and profitability of northern Australian beef enterprises: Exploring innovation options using simulation modelling and systems analysis

Farming system design to feed the changing world. A review

Evaluation of greenhouse gas emissions from hog manure application in a Canadian cow–calf production system using whole-farm models

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