Oct 10 – 13, 2022
Universidade do Algarve
Europe/Lisbon timezone

GRAPEVINE project: hiGh peRformAnce comPuting sErvices for preVentIon and coNtrol of pEsts in fruit crops

Oct 13, 2022, 3:45 PM
30m
Auditório 1.5 (Complexo Pedagógico)

Auditório 1.5

Complexo Pedagógico

UALG - Campus da Penha
Extended Presentation (25' + 5' for questions) Design and implementation of Digital Twins IBERGRID Contributions

Speaker

Cecilia Grela Llerena (Fundación Pública Galega Centro Tecnolóxico de Supercomputación de Galicia (CESGA))

Description

Mildew is a highly destructive disease of grapevines, it appears in all grape-growing areas of the world where there is spring and summer rainfall at temperatures above 10ºC and highly affects the production.

GRAPEVINE (hiGh peRformAnce comPuting sErvices for preVentIon and coNtrol of pEsts in fruit crops) project has the objective to improve the current processes to detect in advance the phenological grape state, the mildew and other grapevine diseases with the development of a predictive model based on Machine Learning (ML) and Deep Learning (DL) techniques. GRAPEVINE wants to improve, in the first place, the evaluation and control of mildew in wine cultivation to reduce the amount of fungicide, and the number of its treatments, to introduce sustainability criteria in agricultural production, offering higher quality agricultural products safer for consumers.

To feed these ML and DL models the use of weather forecast simulations is necessary. All these models must be deployed in a coordinated way in a daily operation to provide on time information to the farmers. The use of advanced computational and data processing services is critical for the success of the project.

We present the GRAPEVINE project, the models, the software to orchestrate all these services (including data management activities and monitoring) and how the use of Cloud compute services of the European Open Science Cloud in the EGI-ACE project have provided a platform for the development of this innovative service for the farmers. This paper shows how the proposed architecture had a positive impact on the usage of the computational resources and how users can benefit from advanced infrastructures with lower effort and required know-how

Primary authors

Carlos Fernandez Sanchez (CESGA) Mr Carlos González Muñoz (ITAINNOVA) Cecilia Grela Llerena (Fundación Pública Galega Centro Tecnolóxico de Supercomputación de Galicia (CESGA)) Dr Charalampos Paraskevas (AUTH) Dr Dimitrios Moshou (AUTH ) F. Javier Nieto Mr Francisco José Lacueva Pérez (ITAINNOVA) Mr Francisco Landeira (CESGA) Mr Gorka Labata Lezaun (ITAINNOVA) Mr Iñigo Zubizarreta Nafarrate (ITAINNOVA) Mr Joaquín Balduque-Gil (University of Zaragoza) Dr Juan J. Barriuso (University of Zaragoza) Mr Konstantinos Kechagias (AUTH) Dr Paraskevi Vourlioti (AgroApps) Mr Rafael del Hoyo Alonso (ITAINNOVA) Mr Sergio García (ATOS) Mr Stylianos Kotsopoulos Mrs Theano Mamouka (AgroApps) Dr Xanthoula Eirini Pantazi (AUTH)

Presentation materials