Mental models and participatory research to redesign extension programming for organic weed management

Supervisors

Marleen Riemens (PRI Wageningen UR)
Egbert Lantinga (FSE Wageningen UR)

Introduction

Weed management is one of the top concerns of organic producers; however, little is known about the efficacy of actual control practices on organic farms and how farmers decide what to do. It is not known why ecological approaches to weed management are underutilized. In this project we will determine the knowledge, beliefs, perceptions, and attitudes that underlie weed management practices and outcomes amongst organic farmers in the Netherlands. The goal of this project is to answer questions such as the following: a) what practices are being used on organic farms and how do they vary regionally, and according to independent variables such as market access, farm size and capitalization, b) are organic farmers likely to be satisfied with the imperfect control possible through ecological and physical approaches, or do they hold subconcious expectations for control similar to that possible with synthetic herbicides, c) What is the knowledge level regarding weed biology and management approaches, d) What are the learning preferences and preferred sources of weed control information, and to whom would organic farmers first turn for assistance with managing weeds, and e) how do knowledge, beliefs and attitudes affect weed management practice and ultimately the weed communities that occur in their fields, and (f) do the actual costs of different control methods match their levels of adoption or rejection?

Procedures

In-depth mental models of organic farmers will be developed through interviews. Biophysical data (seed bank) will be gathered from their farms. The mental models and biophysical data will be coupled, together with survey data on weed management activities resulting in a greater understanding of the costs, benefit and potential of these technologies

Experiences gained

  • Collect and analyse interview data on weed management
  • Collect and analyse weed seed bank data
  • Become familiar with mechanical weed control techniques in the Netherland
  • Statistical analysis and interpretation of result
  • Scientific writing