Published on 8 July 2022
Challenging agricultural context
The sense of urgency for a sustainable agriculture, climate change, the Farm-to Fork strategy and the Common Agricultural Policy of the European Union force agriculture to undergo very fast and profound changes. SESVanderHave, as a suger beet breeder, has always been at the forefront of providing new sugar beet varieties which have higher resistance to diseases, lower environmental impact and higher yields to farmers.
Their challenge is preparing the next generation of sugar beet seeds, that are better adapted to environmental stresses like drought and heat, while maintaining their high level of yield and disease resistance. Luckily, innovative technological solutions are ahead!
Sense OF Field (SOF) project
The partners already have a long track record of bilateral collaboration in the past. In 2016, SESVanderHave and VITO started to work together on several projects related to drone-based phenotyping for disease monitoring, one of which was the BELSPO-funded BEETPHEN project. Since 2008, SESVanderHave and Biometris have been collaborating on the development of statistical methodology to support the sugar beet breeding program of SESVanderHave.
Goal of the SOF project
SESVanderHave already has a large pool of seeds that were selected based on genomic information and information from field trials. Now, with the help of drones, the associated technology and weather stations in the field, SESVanderHave experts can learn a lot more about what exactly happens between sowing and harvest. Thanks to all these Sense of Field parameters and models, they only need to follow up a certain number of plants and can predict their behavior. SESVanderHave can use this genomic selection to predict what type of sugar beet they should develop for a particular market, while taking factors such as heat and drought into account.
The goal of Sense of Field is to
- combine data obtained from weather stations, soil sensors and UAV imaging in genomic selection models to enable a better consideration of environmental data in their prediction models.
- These insights will be applied to genomic selection models to increase yield performance and environmental adaptability of the SESVanderHave product portfolio. This data-driven predictive breeding approach will provide the required insights to face climate change related challenges during the next decades.
- identify secondary sugar beet traits which are relevant to yield or adaptability to specific agro-ecological environments (ideotypes)
SESVanderHave is investing heavily in remote sensing and high-throughput technologies. Through the MAPEO platform, VITO's end-to-end solution to process, visualize and analyse drone data for various applications including phenotyping, VITO has monitored many field trials with drones over the growing seasons, delivering relevant information on crop cover, crop height and crop health.
Within the Sense of Field project the researchers are developing new plant traits which are relevant for the plant breeders, like crop count at different leaf stages, gap counting, time to row closure, Leaf Area Index, Leaf angle,... Once developed they will be integrated into MAPEO's operational processing chain.