Farming options for The Netherlands explored by multi-objective modelling

Abstract Intensive agriculture in The Netherlands has a price in the form of environmental degradation and the diminution of nature and landscape values. A reorientation of farming is needed to find a new balance between economic goals and rural employment, and care for clean water and air, animal well-being, safe food, and the preservation of soil, landscape and biodiversity. The search for farm systems that meet such multiple goals requires a systematic combination of (a) agrotechnical, agroecological and agroeconomic knowledge, with (b) the stakeholders’ joint agreement on normative objectives, to arrive at conceptual new designs followed by (c) empirical work to test, adapt and refine these under real commercial farming conditions. In this paper explorative modelling at the whole farm level is presented as a method that effectively integrates component knowledge at crop or animal level, and outlines the consequences of particular choices on scientific grounds. This enables quantitative consideration of a broad spectrum of alternative farming systems, including very innovative and risky ones, before empirical work starts. It thus contributes to a transparent learning and development process needed to arrive at farm concepts acceptable to both entrepreneurs and society. Three case studies are presented to illustrate the method: dairy farming on sandy soils; highly intensified flower bulb industry in sensitive areas in the western Netherlands; and integrated arable farming. Trade-offs between economic and environmental objectives were assessed in all three cases, as well as virtual farm configurations that best satisfy specified priority settings of objectives. In two of the three cases the mutual reinforcement and true integration of modelling and on-farm empirical research appeared difficult, but for obvious reasons. Only in the flower bulb case was the explorative approach utilized to its full potential by involving a broad platform of stakeholders. The other two case studies lacked such formalised platforms and their impact remained limited. Three critical success factors for explorative modelling are identified: to cover a well-differentiated spectrum of possible production technologies; early timing of modelling work relative to empirical farm prototyping; and involvement of stakeholders throughout.

[1]  H. Miles,et al.  Crop Protection , 1954, Nature.

[2]  H. van Keulen,et al.  Soil–plant–animal relations in nutrient cycling: the case of dairy farming system ‘De Marke’ ☆ , 2000 .

[3]  Carlos Romero,et al.  Multiple Criteria Analysis for Agricultural Decisions , 1989 .

[4]  R. H. Miller,et al.  A History of Sustainable Agriculture , 1990 .

[5]  Edward P. K. Tsang,et al.  Foundations of constraint satisfaction , 1993, Computation in cognitive science.

[6]  H. van Keulen,et al.  Modelling of agricultural production: Weather, soils, and crops , 1986 .

[7]  R. Rabbinge,et al.  Long-Term Options for Land Use in the European Community , 1992 .

[8]  Andrzej Osyczka,et al.  Multicriterion Optimisation in Engineering , 1984 .

[9]  H. van Keulen,et al.  Determination of input and output coefficients of cropping systems in the European Community. , 1995 .

[10]  D. Pimentel,et al.  Sustainable Agricultural Systems , 2020 .

[11]  B. Habekotte.  TCG-CROP : een model voor berekening van produktie- en milieuvariabelen van verschillende gewassen ontwikkeld ten behoeve van het project 'Introductie geintegreerde akkerbouw' , 1994 .

[12]  P. H. Vereijken,et al.  A methodical way of prototyping integrated and ecological arable farming systems (I/EAFS) in interaction with pilot farms , 1997 .

[13]  J. Schans.  MGOPT_CROP, a multiple goal linear programming model for optimisation of crop rotations, version 1.0 : quantitative approaches in systems analysis , 1996 .

[14]  C. T. Hoanh,et al.  Exchange of methodologies in land use planning. , 1998 .

[15]  J. P. Rellier,et al.  Crop management planning as a fuzzy and uncertain constraint satisfaction problem , 1995 .

[16]  G.W.J. van de Ven,et al.  A mathematical approach to comparing environmental and economic goals in dairy farming on sandy soils in the Netherlands , 1996 .

[17]  H. van Keulen,et al.  Application of interactive multiple goal programming techniques for analysis and planning of regional agricultural development. , 1988 .

[18]  H.F.M. Aarts,et al.  De invloed van bodemeigenschappen en bemesting, op de opbrengst van mais en de emissies van ammoniak en nitraat , 1990 .

[19]  R. Rabbinge,et al.  Concepts in production ecology for analysis and quantification of agricultural input-output combinations , 1997 .

[20]  J. Schans,et al.  Modelmatige verkenning van mogelijkheden voor de geintegreerde akkerbouw : deelstudie voor het project "Introductie geintegreerde akkerbouw" , 1996 .