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Home > TERATEC FORUM > Workshop 2
Workshop 2 - Wednesday, June 29 from 9:00 to 12:30
New approaches to big data analytics in agriculture
Use of "Deep Learning" in agriculture
The rise of numerical technologies enabled the development of decision support tools dedicated to players in agriculture. Such decision support tools can take various form, optimizing cultural practices, assisting plant breeding or forecasting crop productions on regional scales.
In order to be able to deliver a service adapted to each situation, a decision support tool must in addition to the knowledge of the climatic and pedologic environment, deals with two major elemnts : The assessment of the crop status at some date and a simulation engine able to project the crop state in the future, following the various cultural scenarii possible. For this purpose, a wide range of types of data are required : climatic data, pedologic data, phenotypic data, genotypic data ...
In parallel to the development of decision support tools, large data bases have been implemented by many players in agriculture : academic institutions, co-ops, seed companies... These data bases have an essential part in the development of next generation decision support tools that are more performing and that uses ever more sophisticated simulations of plant growth. For these new types of decision support tools, needs of HPC resources become significant to sustain the analysis of in-going data flow in relationship with CPU time consuming simulations of plant growth.
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Biographie : Denis Wouters s’occupe du développement de technologies numériques et HPC pour les acteurs industriels de la filière végétale chez CybeleTech depuis 2014. De formation en physique fondamentale, il a effectué une thèse en physique des particules au commissariat à l’énergie atomique à Saclay, un autre domaine où les méthodes d’analyse de données et l’utilisation de technologies numériques et HPC sont cruciales. |
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Jean-Pascal JEGU
Tel : +33 (0)9 70 65 02 10
jean-pascal.jegu@teratec.fr
Campus TERATEC
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