espfdigit

 

Project Number: 101157922
Project Acronym: E-SFPdigit

General information
Project title: Emergent soil, plant and food onsite digital services on chemical and biological contaminants
Starting date: 01/10/2024
Duration in months: 36

Budget NOA: € 272.500,00

Type of action: HORIZON-IA

Call (part) identifier: HORIZON-MISS-2023-SOIL-01-03

Topic: HORIZON-EUSPA-2023-SPACE-01-43: Copernicus-based applications for businesses and policy making

Keywords: Digital services, Food technology, Soil management, Pollution (water, soil), waste disposal and treatment, Agricultural engineering, food safety, Agriculture related to crop production, soil biology and cultivation

Website: -

CORDIS: -

EU LOGOFunded by the European Commission


E-SPFdigit is a 36-month innovation action project that will bring novel onsite digital tools already at TRL5 under systemic innovation, which will be further deployed, upscaled, field-tested and demonstrated to TRL7-8, in viticulture and horticulture applications, such as in vineyards and open-field vegetable cultivations, under different conditions, soils, and crops (tomato, potato). The consortium brings novel developments:

  • MIP-based electrochemical sensors coupled with SPME for on-site monitoring and analysis of specific PFAS-targeted molecules,
  • Multiplex organic Surface Plasmon Resonance optical on-site monitoring and analysis of pesticide residues,
  • IDE-based electrochemical sensors for onsite detection and quantification of heavy metals & micronutrients, and
  • UVC LED-based nutrient analysers for in-situ and real-time monitoring of soil water content.

The AI-driven digital tools in the field are model-calibrated using machine learning algorithms to improve the error distribution of a predictive model, ensuring reliability. In addition, E-SPFdigit brings an edge-based remote sensing framework via a robust, autonomous, self-navigating mobile robot and a high-performance unmanned aerial vehicle for in-field detection of soil parameters related to the aforementioned chemical and biological stressors. Finally, to predict the impact of pesticides, fertilisers and other chemical contaminants on the crop-soil-microbiome nexus, the project will use real-time in-field digital soil sensors combined with Earth observation data and causal machine learning. All on-field digital tools will be connected to a decision support system with blockchain and cybersecurity mechanisms, enabling informed decisions and automated decision making for IPM and INM, complemented by automated decision making for immediate soil management practices. Two living labs and five lighthouses will be established within the project, where the onsite digital tools will be field tested and evaluated in 5 food industries