Analysing production and environmental risks in arable farming systems: A mathematical approach
Introduction
Operating a farm firm in the arable sector in the Netherlands stands for more than just looking after the various crops. In the range operational–tactical–strategic decisions, which is often used as a classification for levels of planning, a farmer has to cover the whole management field of production, marketing and finance (Boehlje and Eidman, 1984; Davis and Olson, 1984; Huirne, 1990). Considering the whole farm organisation, most decisions across levels of planning are inter-related.
Due to a growing concern for the environment in Dutch society during the last decade, farmers have to extend their management field with another task: environmental management. Researchers designed IAFS (Integrated Arable Farming Systems) in order to reduce the dependency on chemical crop protection and to reduce the emission of fertilisers to the environment (Vereijken et al., 1994, Vereijken, 1992). IAFS research succeeded in integrating both economic and environmental goals. Practical research has proved IAFS to be implementable on farms, where production levels were according to the expectations (Wijnands, 1992, Janssens et al., 1994, Wijnands and van Dongen, 1997).
The hypothesis, derived from Dutch farming practice, that production risks of integrated farming systems are higher than those of conventional systems, is the background of this paper. Risk is considered as one of the delaying factors in the dissemination of IAFS in practice. This paper describes a method to combine several crop problems into one whole-farm level, the purpose of which is to analyse production risks between farming systems. The conceptual framework is presented together with examples.
Risk can be distinguished in normatively computable risk and the perception of risk by individuals (Smidts, 1990). In a project financed by the Dutch Ministry of Agriculture, Fisheries and Nature, normative analysis of risk is combined with empirical analysis of behavioural aspects that play a role in the adoption of IAFS. The normative comparison of risks started with an analysis of ongoing applied research on farming systems. Based on the disciplines of Operations Research, Production Ecology and Farm Management, this paper describes a method for the normative calculation of production risks, induced by natural circumstances, of different farming systems. In terms of management fields, this paper covers production and environmental management.
The model presented in this paper can be used: (1) to estimate risks of specific current or new farming systems, omitting innovations in the sector, using all possible natural conditions as model input, (2) to objectively compare farming systems under similar farm and management situations (risk included) and (3) to evaluate new techniques on their suitability for a farming system. Risk is portrayed by a value distribution of outcomes.
The outline of the paper is as follows. In Section 2we present the outline and theoretical background of the model. After a description of decision making and risk in crop husbandry a conceptual framework is presented. 3 Calculating risks at crop level, 4 Calculating risks at the whole farm levelpresent the model in its two main parts: (1) crop husbandry models for the several husbandry activities at the crop level, and (2) an LP model at the farm level. Special attention is given to the iterative procedure of adapting the decision at the crop level to the constraints imposed at the whole farm level. The model at farm level is also used to choose the management track for each aspect of crop husbandry, performing the best over all possible natural circumstances. Section 5evaluates the total model approach and its potential applications and provides major conclusions and priorities in further research.
Section snippets
Decision making in crop husbandry
Implementing crop husbandry for a whole farm comprises many aspects. For each aspect of crop husbandry (e.g. weed control in sugar beet or late blight control in ware potatoes), a strategy has to be made up. We define a strategy as a design for several years with respect to the organisation of crop husbandry on the farm, e.g. determining the equipment needed on the farm and planning labour supply and demand. A division ranging from `conventional' to `integrated' and `organic' strategies can be
Calculating risks at crop level
A model HM, describing a crop husbandry strategy, is based on a network that is directed by time stages. The network differs for each strategy. The path followed through the network (i.e. the management track) depends on weather conditions and on the tactic. In Fig. 2, J stages during one season and a multi-dimensional state (representing the situation of the crop and the weed, disease or nutrient situation) are distinguished. State s at stage j is determined by decision x (if–then relations,
Calculating risks at the whole farm level
In the model for calculating risks of different farming systems, the crop level and the level of the whole farm can be distinguished. Risk at crop level is calculated in the HMs. In this section, the integration of HMs into an LP model of the whole farm organisation (WF1) is described. The basic idea of WF1 is to select tactics so that the combination of all aspects of crop husbandry performs better on farm level. Each HM is one module in WF1. The required inputs, imposed by the execution of
Final remarks, discussion and conclusions
With the individual HM modules, management tracks for a single aspect of husbandry can be determined, accounting for differences in weather situation. Considering the natural circumstances during a range of seasons enables assessment of risks – in this case value distributions of required resources – of alternative strategies for these individual husbandry problems; both in economic terms (costs, input requirements) as in environmental terms (emission of fertiliser and pesticides). The HMs
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