The team at LandScan are the pioneers of the widely used GEM framework (Crop Performance = Genetics x Environment x Management) and have deployed it to real customers around the world since 2003.
The GEM framework has become an accepted and widely utilized model in hashtag#digitalagriculture. It’s in university lectures, company pitches and strategies, and even professional titles.
In early 2003, as part (Soil & Topography Information – STI) we licensed the genius biophysical model created by my Ph.D. major-professor, and mentor John Norman from UWMadison Biophysics called the Precision Agriculture Landscape Modeling System (PALMS). This model was at the center of a John Deere decision support tool that utilized digital soil data from STI in combination with weather data and airborne remote sensing to power the model. However, given the state of analytics and the limited processing capacity in 2003 John Norman and I created GEM as a simpler and more immediately useful derivative.
University of Wisconsin-Madison researchers (and others around the world) have studied the relationship between ‘G’ in the context of ‘M’ for a very long time when performing agronomic research. However ‘E’ was always fixed along with other actual or perceived ‘controls’ in test plots. By using biophysical principles it is possible, and very practical, to introduce ‘E’ as a variable that is characterized with much more granularity and used to iteratively adjust ‘G’ and ‘M’.
When Deere licensed STI technology in April 2005, GEM became an important part of the push to bring these concepts to the world. Lynn White, at the time President of John Deere Agri Services, gave the first public presentation on GEM in June 2006 in Argentina. The conference was attended and sponsored by many industry giants and peer reviewed publications began introducing GEM to the scientific community in 2007. Unfortunately the economic crash of 2008 put an end to the Agri Services endeavor as well as pretty much every other new hashtag#agtech initiative going at that time.
LandScan now uses the GEM framework as enabled by the hashtag#digitaltwin as a foundation for our decision-support system, the Root Cause Analytics (RCA) hashtag#rootcauseanalytics interactive simulator.
