In the context of the genetic improvement programs for the main agricultural crops (soybeans and corn), breeders face the enormous challenge of collecting a large amount of data about cultivars undergoing treatment under the programs.
This information is what they use to select the different cultivars and keep the best ones. However, cultivar characterization requires expensive machinery such as experimental harvesters, as well as long labor hours for the technicians involved in the process of gathering information.
Stand-alone terrestrial high-performance phenotyping platforms
Gbot has created a new type of tool that provides detailed crop characterization. To do so, it combined three technologies: robotics to automate data collection, artificial intelligence to develop models capable of obtaining accurate information on a multitude of crop traits from RGB images, and big data for managing large volumes of information.