Emergent soil, plant and food onsite digital services on chemical and biological contaminants
Sector: Water Supply and Storage • Location: Greece, Cyprus, Spain, France, Portugal, Ireland, Netherlands, Serbia, Italy
Source: EU Funding & Tenders Portal
E-SPFdigit 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 in Greece and Spain in soil-contaminated areas (located near mines, offensive industries, highways, floodwaters). E-SPFdigit brings novel developed: i) MIP-based electrochemical se
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ongoing |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | E-SPFdigit 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 in Greece and Spain in soil-contaminated areas (located near mines, offensive industries, highways, floodwaters). E-SPFdigit brings novel developed: i) MIP-based electrochemical sensors coupled with SPME for on-site monitoring and analysis of dedicated to PFAS targeted molecules, ii) Multiplex organic Surface Plasmon Resonance optical biosensors for onsite pesticides residues monitoring and analysis, iii) IDE-based electrochemical sensors for onsite detection and quantification of heavy metals & micronutrients, and iv) UVC LED -based nutrient analysers for soil water content in-situ and real time monitoring. The AI-driven onsite digital tools will be model calibrated using machine learning algorithms to improve error distribution of a predictive model, ensuring reliability. Also, E-SPFdigit brings an edge-based remote sensing framework via a robust autonomous mobile robot self-navigating and a heavy-duty unmanned aerial vehicle for in-field detection of soil parameters regarding the aforementioned chemical and biological stressors. Finally, to predict pesticide and fertiliser and other chemical contaminants impacts on crop-soil-microbiome nexus, the project will use on-field real-time digital ground sensors combined with Earth Observation data and causal machine learning. All the onsite digital tools will be interconnected with a Decision Support Systems with blockchain and cybersecurity mechanisms enabling informed decisions and automated decision making for IPM and INM, enhanced with automated decision making for immediate soil management practices. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
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