Supporting strategic thinking of smallholder dairy farmers using a whole farm simulation tool

Abstract

This article investigates how a one-to-one support process based on the use of a whole dairy farm simulation tool helps both farmers to reflect on their production strategies and researchers to better understand the farmers' contexts of action and decision. The support process consists of a minimum of four discussion sessions with the farmer: designing the Initial Scenario and formulating a diagnosis, building and simulating the Project Scenario corresponding to the objective targeted by the farmer, building and comparing alternative scenarios proposed both by the farmer and the researcher, and evaluating the process with the farmer. The approach was tested with six smallholder farmers in Brazil. It is illustrated with the example of one farmer who aimed to develop his milk production by more than doubling his herd size on the same cultivated area. Two other examples illustrate the diversity of issues addressed with this approach. The first estimates the sensitivity of economic results to price variations of milk and concentrates. The second compares two scenarios in terms of forage supply autonomy. The discussion assesses the outcomes of the approach for farmers in terms of response to their specific issues and of knowledge acquired. The research outputs are discussed in terms of the value and limits of using simulation tools within both participatory action research and advisory processes.

Crop–livestock integration beyond the farm level: a review

“…Given this lack of knowledge on crop-livestock integration beyond the farm level, dedicated decision support systems (DSS) have never been developed. Available DSS dealing with crop-livestock integration (e.g., farm models like Martin et al 2011;Le Gal et al 2013) are focused on the farm level and consequently do not take into account organizational aspects among farms. Thus, these DSS are not relevant to support development of crop-livestock integration beyond the farm level based on organizational coordination among farms.…”

Factors driving growers’ selection and implementation of an apple crop protection strategy at the farm level

“…Such advice can also take into account risk management processes when growers' risk perceptions regarding alternative methods prevent them from changing their practices (Mitchell and Hutchison, 2009). Modeling tools at the farm level can then be used to evaluate ex-ante the consequences of an innovative scenario on farm functioning and performance (Le Gal et al, 2013;Dogliotti et al, 2014). This approach can be jointly conducted by researchers, advisors and growers in the framework of co-innovation or participatory research processes, which better meet the stakeholders' requirements and address specific issues (Faure et al, 2014).…”

Relevancy and role of whole-farm models in supporting smallholder farmers in planning their agricultural season

“…This kind of tool represents decision outputs, such as cropping plans, crop management or herd diets, rather than decisions rules. This simple modelling structure is meant to be easier to understand, but it requires the use of some approximations (Le Gal et al, 2013). For instance, crop yields are not calculated based on mechanistic biophysical equations as in a crop model, but are directly entered by the model user.…”

“…They prove even more useful when the farmers are considering plans to develop their production systems. This tool type fully responds to the exploratory objective on which the prospective thinking of the farmer, in interaction with the researcher, is based (Kerr et al, 1999;Le Gal et al, 2013;Martin et al, 2013). It also allows certain technical knowledge of farmers to be improved and to situate innovations in the specific context of a farm.…”

“…Ideally, model developers should consider whether their tool actually helps farmers in managing their production systems (Keating and McCown, 2001), yet few do so (Le Gal et al, 2011;Dogliotti et al, 2014). Moreover, in the decision support case studies reported, multiple decision support tools have rarely been used since researchers usually focus their studies on one model type, for instance optimization (Dogliotti et al, 2014) or a stock and flow simulation tool (Le Gal et al, 2013).…”