Whole-farm Model Research Articles

A whole-farm model for economic analysis in a goat production system in Mexico

In north-central Mexico, the production of goat meat is associated to summer cultivation crops for family consumption. The objective of this study was to construct a simulation model for the economic analysis in this goat–agricultural system. Linear programming was used to optimize system net income. Several scenarios were generated varying the price scenario (1992 and 1995) and the use of technology (traditional and recommended). The approach visualized the system general response and the impact of a subsidizing program. The model was limited to a maximum cultivation area of 64 ha and a maximum herd of 200 does. The model proved that recommended technology in 1992 increased the net income of the system, but it did not in 1995. In both cases, it was necessary to buy maize stubble to supply the requirements of dry matter animal intake. Traditional technology was more versatile to goat meat and maize stubble's price changes. The model selected a cultivated area of 64 ha for the 1992 price scenario as well as for 1995 when subsidies were included. However, as subsidies were removed in 1995 the model output was only 8 ha. When the surface of rainfed crops was 16 ha or more, the use of technology helped to increase the net income. Thus, subsidy policy induced an expansion of the agricultural cultivated area in the system. On the other hand, the largest incomes for all the modeled scenarios were noted when the herd size was maintained at 100 does. The scenarios presented express the rationality in the process of decision making by farm owners. For instance, they prefer grain crops instead of forages cultivation due to the subsidy policy; they do not use recommended technology since it is not rewarded economically; and they embrace the traditional system because it is more flexible to price changes.

‘Why do farmers do it?’ Validating whole-farm models

With whole-farm models, it is usually hard to know how representative the models are of reality. No rigorous validation procedure seems to have been proposed. There has always been a dilemma between descriptive power and tractability. The outcome has been to resort to a confused mix of expert opinion and normative attitude. Discrepancies between model output and farmers' behaviour have usually been interpreted in against farmers, by considering them to be in some way sub-optimal or insufficiently informed. In traditional systems where the rationale of production behaviour can vary widely, it may pay to first understand their rationale before applying normative principles or recommending new technologies. We use a case study in Mexico to illustrate a procedure allowing for such an assessment of our understanding. The procedure, though based on the use of linear programming, is independent of the modelling technique.

Lessons from a Decade of Whole‐Farm Modeling in Western Australia

Many management decisions made by farmers depend on factors external to the particular crop or livestock enterprise directly affected. Issues that arise at the level of the whole farm, such as the allocation of limited resources between alternative enterprises, can be especially difficult to analyze. Whole-farm models of various types provide a vehicle for better understanding these issues and decisions. In Western Australia, a particular whole-farm model, (Model of an Integrated Dryland Agricultural System) MIDAS, has been an influential tool for research prioritization, extension, education, and other uses for over a decade. The purpose of this article is to outline experiences in the development and use of MIDAS with a view to providing guidance to others commencing or contemplating development of similar models. The discussion starts with points on whole-farm planning and whole-farm modelling in general, and then considers a wide range of issues arising out of the several versions of the MIDAS model.

Information needs for long-run forward business planning — experiences with the Top Management Farm Business Simulator

The importance of risk assessment in evaluating existing and new farm operations and new projects is emphasized in this paper. The Top Management Farm Business Simulator is a whole-farm financial-planning model that simulates up to 250 observations of farm income, expenses, cash flows and net worth for periods of up to 15 yr, using stochastic product prices and yields. Individual probability functions, as well as cross-correlations among stochastic variables, can be specified. Key words: Risk assessment, financial planning, crop management

Economic analysis of the long-term consequences of farming practices in the barley cropping area of Jordan

The sustainability of agricultural practices is an important determinant of the ability to meet the growing food needs of future generations in developing countries. But sustainable agricultural practices will not be adopted by farmers unless current farm income levels are maintained. The Erosion Productivity Impact Model (EPIC), a whole-farm model, and budget analysis are used to evaluate both the short-run profitability and the long-run sustainability of a number of agricultural practices in the Mafraq region of Jordan. While only a few technologies exceed current practices in terms of short-run benefits, a number of technologies provide long-term benefits due to enhanced soil productivity. A combination of technologies, such as a fertilized barley-vetch rotation (instead of the traditional barley-weedy fallow rotation), may provide the most feasible means of maintaining current farm incomes while also enhancing the sustainability of area agriculture.

Impact of diversification on household income and risk: A whole-farm modelling approach

Despite the progress made in agriculture reflected in a record food grain production largely through a technological revolution, vast areas under dryland agriculture have not still moved away from the cyclical pattern of peaks and troughs in output. This pattern has to be changed for sustained growth; and accelerated development. Diversification of farming into livestock rearing provides an opportunity to augment farm income and to reduce income risk, particularly in dryland areas where income from crop husbandry is unstable. This study is based on the time series cross-section data drawn from village level studies project of ICRISAT, hyderabad, India in the dryland tract of peninsular India. The risk efficient plans are derived using a quadratic risk programming model. The model results suggest that raising of milch animals on the farm not only increases the level of expected level of income but also reduces the magnitude of income risk.

Evaluating and adapting new technologies in a high-risk agricultural system—Niger

This study modeled the introduction of new early cultivars of millet and cowpea, higher cowpea densities, and various fertilization strategies. Model results were then compared with farmer behavior before and after the availability of these new technologies. The model correctly identified the two new technologies being adopted by farmers. Then further runs of the adaptive model identified several research-extension strategies to increase the adoption of fertilization. Some recommendations to researchers and extension agents were made. The intraseasonal adaptive decision-making process of farmers was modeled with a one-year, discrete stochastic sequential programming whole-farm model.

Soil and moisture management in Mali: a case study analysis for West Africa

Abstract In order for farmers to accept improved soil and water management practices, new technologies must be appropriate to the specific site conditions found in the farm setting and be consistent with farmers' objectives and available resources. A whole-farm modeling analysis of this problem is described. Preliminary estimates of the benefits of increased soil moisture conservation for representative low-resource farmers in Mali are presented. If farmers could improve rainfall infiltration from currently low rates of about 40% up to 60%, and use small amounts of chemical fertilizers, disposable income could increase two to four times depending on rainfall. Income could be increased another 50% if the infiltration rate was raised to 80%. Food grain production could increase 60 to 90% with improved moisture conservation and fertilizer use.

Economics of Chemically Conditioned Alfalfa on Michigan Dairy Farms

ABSTRACT ALFALFA drying models for standard and chemical conditioning were integrated with a whole-farm model of the dairy-forage system. Simulation was used to evaluate benefits and costs of chemical conditioning over 25 years on representative Michigan dairy farms. Conditioning with potassium carbonate can be economical in hay production, but uneconomical in haylage production. An economically-optimum application rate of 500 L/ha was determined for first cutting with optimum rates of 200 and 300 L/ha on second and third cuttings. Use of a heavy swath during field drying caused the treatment to be less effective and uneconomical.