Symposium ‘Create value with your own data’

Donderdag 27 september
13:30 uur – 15:00 uur
Spreektaal: Engels

Spreker 1: Ton van Dijk (Sales manager collects data from all data sources that are available in covered cultivation. By centralizing and standardizing these different sources, you can use the data for analysis and thus optimization.
The developments that are going on now are very diverse and go very fast. In this way, new measuring techniques are rapidly emerging (sensors, drones, crop vehicles with measuring equipment, vision). The data is used for techniques such as machine learning and new growth models.

In order to be able to optimize your business results, a central data platform is needed . is that central platform where the data owner, the grower (very important!), determines which data goes to whom and for what purpose. For example, it may be that a drone makes very good images of a crop, but climate data is needed to enable optimal growth analysis. The automated transmission of the data and the presentation of the outcomes offer many opportunities for both the grower and the modeling engineers and the suppliers of the sensors.

Spreker 2: Dries Raymaekers (R&D Agricultural Applications)
Drone based, or drone assisted phenotyping has been demonstrated for many crops and traits with generally high accuracies in comparison to field based methods. However, the practical implementation into the experimental fields of plant breeders or public research facilities has been limited and results are not always consistent over the growing season or between different crops. The step towards fully exploiting the potential of drone based phenotyping requires (i) the simplification of data acquisition and data handling ,(ii) data analytics which are focussed to extract relevant agrometrics on micro-plot level and (iii) the integration within day-to-day workflows. Over the past 3 years, VITO has collaborated with plant breeders and public research facilities to develop a drone image processing workflow dedicated to experimental fields.  Plant height for wheat and corn plots, diseases in sugar beets and wheat trials, plant emergence for potatoes and spinach are just a few traits for which image analytics were provided and which resulted in agrometrics which reaches or even surpassed field based measurements.

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