Analysing production and environmental risks in arable farming systems: A mathematical approach

Buck, Alexander; Hendrix, E.M.T.; Schoorlemmer, H.B.

doi:10.1016/s0377-2217(99)00143-5

Cited by 14 publications

(2 citation statements)

References 6 publications

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“…De Buck et al (1999) analysed the role of risk in the adoption by farmers of new systems by means of a model that determines differences in production risks between conventional and sustainable farming systems. The model consists of two main parts: (I) crop husbandry models (HMs) for several husbandry activities at the crop level, and…”

Section: Normative Modellingmentioning

confidence: 99%

Modelling conventional and organic farming: a literature review

Acs

Berentsen

Huirne

2005

NJAS: Wageningen Journal of Life Sciences

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Literature shows a significant development of organic farming in Europe but with considerable differences between countries. These depend on general agricultural policy (the set of regulations and laws), specific policy incentives, and also on differences in consumer behaviour. This paper reviews scientific literature on the evaluation of the technical, economic and environmental aspects of conversion from conventional towards organic production. The methods and results of empirical and normative modelling studies at the farm level, with special regard to farm management and policy, are analysed. Empirical modelling studies show the importance of incentives and agricultural policy, and the usefulness of integrated modelling for determining the effects of different policies on farm management. Normative modelling shows the effects of new policy instruments and technology, and allows the high level of detail needed for what-if analysis. Normative models of conversion to organic farming confirm the importance of incentives and the agricultural policy context.

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Section: Normative Modellingmentioning

confidence: 99%

Modelling conventional and organic farming: a literature review

Acs

Berentsen

Huirne

2005

NJAS: Wageningen Journal of Life Sciences

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“…Bio-economic farm models have been frequently proposed by research as tool to assess agricultural emissions to the environment (Falconer and Hodge 2001 ; Vatn and others 1997 ; Wossink and others 2001 ) and effects of agriculture on landscape and biodiversity (Meyer-Aurich and others 1998 ; Oglethorpe and Sanderson 1999 ; Schuler and Kachele 2003 ). Bio-economic farm models have also been proposed to assess the performance of different farming systems (Berentsen 2003 ; De Buck and others 1999 ; Pacini 2003 ) or to evaluate the Common Agricultural Policy of the EU (Donaldson and others 1995 ; Onate and others 2007 ; Topp and Mitchell 2003 ). Here a Bio-Economic Farm Model (BEFM) is defined as a model that links farms’ resource management decisions to current and alternative production possibilities describing input-output relationships and associated externalities.…”

Section: Introductionmentioning

confidence: 99%

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Janssen

Louhichi

Kanellopoulos

et al. 2010

Environmental Management

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Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.

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