Olive growing faces major challenges due to climate change and the increasing demand for sustainable and profitable production. One of the main issues affecting olive groves is the efficient management of fungal diseases.
Traditionally, the approach to combating these diseases has been the application of phytosanitary treatments, which imply a high economic cost and a significant environmental impact (for example, we usually apply four treatments during the year). However, the digitalisation of agriculture opens a new era, not only in production management, but also in the phytosanitary management of olive groves.
This is where GO OLIVITECH comes into play. Its goal is to revolutionise plant health management in olive groves through the use of automatic aerobiological sensors, big data analysis and predictive models. By anticipating the emergence of diseases, OLIVITECH aims to optimise phytosanitary treatments.
How does OLIVITECH work?
The system developed by OLIVITECH integrates meteorological, aerobiological and phenological data to establish a predictive model of the evolution of diseases in olive groves. Its technical approach is based on three fundamental pillars:
Real-Time Monitoring with Aerobiological Collectors
- The samplers collect air samples and identify spores of key pathogens.
Phenological and Meteorological Data Integration
In addition to aerobiological information, OLIVITECH incorporates data on:
- Olive Phenology: Analyses the different stages of crop development to identify critical periods of susceptibility to diseases.
- Weather Conditions: Monitors temperature, relative humidity and precipitation, which are key factors in the spread of fungal pathogens.
- Symptomatology History: Assesses disease occurences from previous campaigns to improve the accuracy of the predictive model.
Predictive Modelling and Early Warning Tools
All the information collected is processed using data mining and machine learning algorithms, enabling:
- Prediction of fungal attacks one week in advance.
- Identification of critical sporulation thresholds to recommend or rule out treatments.
- Optimisation of pesticides use, reducing unnecessary applications.
In our experience, having a personalised alert system gives us a new level of insight into the crop, allowing us to take action at the right time and avoid unnecessary treatments.
Technical and economic benefits of OLIVITECH
If we focus on an economic and environmental point of view, we can highlight the following:
- Reduced Production Costs
- Fewer chemical treatments.
- Reduced working hours and use of machinery.
- Improved efficiency in the application of treatments.
- Enhanced Sustainability and Regulatory Compliance
- Lower pollution of water, soil, and air due to reduced use of phytosanitary products.
- Supports production under ecological criteria.
- Lower environmental impact and better alignment with the Common Agricultural Policy (CAP) 2023-2027.
- Improved Competitiveness of the Olive Sector
- Advanced management tool based on precision agriculture.
- Greater resulience to climate change and emerging phytosanitary threats.
- Increased profitability and access to new export markets.
Who is involved in the OLIVITECH project?
The OLIVITECH Task Force is made up of a consortium of entities from different fields:
- Universities and Research Centres
- University of Vigo (UVigo)
- University of Córdoba (UCO)
- Olive Sector Companies
- Innovation and applied technology
- Coordination and knowledge transfer
Funding and institutional support
OLIVITECH is an innovation project within the framework of the Strategic Plan of the Common Agricultural Policy (PEPAC) 2023-2027, 80% financed by the European Agricultural Fund for Rural Development (EAFRD) of the European Union and 20% by the Ministry of Agriculture, Fisheries and Food (MAPA), with a total budget of €551,196.27 and a total grant of €543,206.47.
Conclusion: A More Precise Future for Olive Groves
The advancement of precision agriculture and the integration of aerobiological technology with predictive models allow us to evolve towards more efficient and sustainable disease control. Undoubtedly, we will have more tools to make management much more efficient as we can make decisions based on real data.
By making data-driven decisions through a more efficient management. We can minimise costs and environmental impacts based on real data without compromising olive oil production and quality.