Nieuwsbericht 29 June 2022

Sense of Field project: combining phenotypic & environmental information

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

In this challenging context, SESVanderHave, VITO and Biometris decided to collaborate and submit a project proposal called 'Sense of Field' to VLAIO, Agentschap Innoveren en Ondernemen.
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

  1. combine data obtained from weather stations, soil sensors and UAV imaging in genomic selection models to enable a better consideration of environmental data in our 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. 
  2. 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 we 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.



VITO's counting algorithm

Often field technicians were counting manually the number of beets that were emerging after sowing. This counting was very labor intensive and also prone to mistake.
VITO developed an algorithm to count emerged beets and gaps. The new algorithm allows a better precision and time & money savings.

Next to drone based information, VITO is also providing satellite information on the test field locations to get insights into the natural heterogeneity of the fields. This can be relevant for both existing trials, to better estimate the role of the environment to the yield calculation and even before, to select those fields with minimal heterogeneity.