Phenotyping & Remote Sensing to Facilitate Min. Data Set Requirements - 2020 CoP Convention Session
Channel: CGIAR Platform for Big Data in Agriculture
Date: 2020-10-28

Crop models can require extensive and/or intensive data sets to drive simulations as well as for calibration purposes. While some of the information is straightforward, such as agronomic performance traits (e.g. yield, phenology) as well as weather data, other types of data require significant resources such as green area index, light interception and water and nitrogen availability in the soil. As a result, the vast majority of field data sets are not ‘model friendly’, lacking key inputs required for simulation purposes. This workshop will discuss ideas on how the digital technologies such as remote sensing for high throughput phenotyping can supplement or potentially serve as proxies for some of the harder to phenotype traits required, in different modelling contexts.

Speakers:
-Matthew Reynolds 
-Kai Sonder 
-Davide Cammarano 
-Heidi Webber