DIVINE Pilot 1 - Case Study

DIVINE Pilot 4 Case Study - Potential effects of agricultural data sharing on traditional Olive and Almond Plantations

Pilot Overview

Pilot scale - Application of Data-driven decision on 5 Ha. in Olive Plantation (2 x Land Parcels and 17,5 Ha. in Almond Plantation (6 x Land Parcels). Olives are an important crop for Spain, who is the leading global producer of olive oil and a major producer of table olives. Optimisation of production and increased digitisation are key priorities. Harvest variability, increased costs and droughts are some of the challenges faced by these sectors. This pilot was based on olive and almond farms in Andalucia, one of the main regions for production in Spain. Both olive and almond sectors represent a fundamental pillar of the Spanish agrifood sytem. Spain is the world leader in olive oil production which accounts for 70% of EU production and 45% of global production, At the regional level, olive oil production is concentrated in Andalusia representing 80% of the total national production. This sector has also a significant social, environmental and territorial impact, since more than 350.000 farmers cultivate olive groves generating more than 32 million workdays per season. Also Spain is the second world largest producer of almonds and demand is increasing. Almond cultivation covers a total area exceeding 700.000 hectares in Spain. This surface area represents more than 30% of the world’s total almond cultivation area. Andalusia is the main producing Autonomous Region, concentrating more than 30% of the total area of production.

Target Stakeholders & Problems to be Addressed

This pilot is targeted principally at Olive and Almond farmers, Agricultural advisors, Agri-transforming cooperatives and Public administrations. The pilot actions address limited and fragmented data-sharing which stifles productivity improvements and harvest optimisations. The pilot innovations are designed to address a number of key priorities;

  • Improve sustainable practices with optimised weeding, reduced number of cuts and reduced carbon footprint. Data analytics and technologies facilitate soil carbon sequestration analysis, as well as automated demonstration of CAP compliance requirements (detection of green cover via satellite imagery.

Key Activities

Specifically, the pilot case study includes meteorological data sources (Southern Spain Meteorological Network with over 100 weather stations) and other private data sources on productivity, water performance, irrigations, biofertilizer inputs, mechanical labour and inputs, pest control etc communicated to the Divine DSS.

A large amount of data points are collected.

  • +100 Weather stations - Historical available data in numerical format:

    Maximum Temperature, HH:MM Maximum Temperature, Minimum Temperature, HH:MM Minimum Temperature, Average Temperature, Maximum Humidity, Minimum Humidity, Average Humidity, Wind speed, Wind direction, Rainfall, ETo – Evapotranspiration, Solar Radiation

  • On site Davis instruments measuring device permitting measurement of micro-climatic conditions in crops. Available data includes.

    Wind speed, wind direction, outdoor temperature, Outdoor humidity, temperature sensation, dew point, current and accumulated rainfall (daily, monthly and annual), Rainfall intensity, Solar radiation, evapotranspiration, soil temperature sensors, soil moisture sensors, leaf Wetness Sensors, accumulated Heat, accumulated Frost.

  • Miscellaneous

    Satellite imagery, CAP field notebook, FMIS data, drone imagery data collection

Advanced analytics & decision support for production optimisation includes;

  • Use of machine learning to predict temperature, humidity, precipitation and sunlight
  • Trend analysis and autocorrelation for key meteorological metrics

Outcomes & Impact

Integrated datasets incorporating on-farm sensors, meteorological data, satellite and drone imagery and field notebook inputs provide a comprehensive set of indicators to optimize farm management including. Decisions support is enhanced by predictive weather analytics. NDVI- based decision support providing tree and grass insights to guide irrigation and weeding decisions with 5-day values available, vegetation classification model distinguishing grass and trees and SOC soil organic carbon estimation model. Improved irrigation practices and optimised yields result in more sustainable farming. These NDVI tools simplify demonstration of some CAP requirements

Across all impact categories, the results show a consistent reduction in environmental pressures in 2025 compared with 2024, with decreases generally ranging between –21% and –30%. These reductions occur despite an increase in almond production in 2025, indicating that the system achieved better environmental efficiency per functional unit.

Notably, several impact categories linked to emissions and resource use—such as global warming potential (–25% fossil; –30% biogenic), land-use related climate impacts (–29%), eutrophication (–28%), and ecotoxicity (–23 to –24%)—show substantial improvements. Reductions are also visible in human toxicity indicators (–22% to –27%), ionising radiation (–22%), and water deprivation potential (–26%), demonstrating an overall decline in environmental burdens.