Extension Philosophy and Goals
As an agronomist, I strive to provide decision makers with relevant and rigorously tested information to support the design and implementation of strategies to improve farm profitability and sustainability. My aim is to put the latest scientific knowledge and data analytics at the fingertips of those whose decisions influence the landscape, and to build understanding across sectors and interests groups. Farmers, crop consultants, agribusiness professionals, and the wider public, often seek to obtain distinct outcomes from agricultural production, and I believe it to be the duty of the extension professional to be aware of this.
Therefore, I tailor my outreach accordingly in order to provide a message that is relevant to broad and diverse audiences. I will seek to strengthen the educational opportunities for producers and agricultural professionals by developing extension programming that promotes integrated understanding of concepts of agronomy, soil and atmospheric sciences, and apply it to answer real-world crop management questions. I also focus on addressing topics at the interface of agriculture and computational research, aiming to enhance learners’ data management skills and interpretation of software-based recommendations.
Linking extension to research
Simulation models are widely used around the world to support research and on-farm decision-making, and they will continue to be an integral part of my own research. Integrating simulation models into extension and teaching programming will enhance learning about complex processes and how these are affected by environmental and management factors. Although operating models requires substantial training, which realistically cannot be achieved within the span of a course, opportunities exist to design more learning-friendly, interactive platforms built around the models.
My experience as a contributor to the Forecast and Assessment of Cropping sysTemS (FACTS) project, a multidisciplinary effort that provides publicly available in-season predictions of soil dynamics and crop yields, has made me aware of the challenges to design decision-support tools. Not only the underlying science and assumptions need to be robust, but successful tools also should be easy-to-use and provide relevant, timely information, well targeted to producers’ needs. I envision my extension program to be at the forefront of this development, actively seeking collaborations with experts in pedagogy and information technologies to turn these models into more effective experiential learning tools. I look forward to elaborate on this vision during future discussions.