Using Group Collaborative Investigations to Develop Pasture Biomass Prediction Equations

Abstract

Graduates from agriculture/agribusiness courses need to understand the multidisciplinary nature of agriculture, to think critically and solve problems in the role of an agricultural advisor. Producers are being exposed to new technologies developed for integration into agricultural production systems. Producers require technical support from external sources such as advisors and consultants, to identify relevant technologies, identify potential constraints of the technology and to support adoption. Information from such technologies may not be relevant to the production system, potentially resulting in information that has limited relevance. It is important that students develop an understanding of the processes used to develop predictive relationships between data generated by technology and the production system. In this study, students worked as collaborative teams, to design and implement an investigation aimed at developing prediction equations for pasture biomass using NDVI and a range of measurable agronomic parameters. The investigation provided students with the opportunity to gain an understanding of the importance and relevance of information to build prediction equations, to develop critical evaluation skills, to identify limitations to the process, propose solutions, and to work as a team to achieve the desired outcomes.