Periodic Reporting for period 2 - PestNu (Field -testing and demonstration of digital and space based technologies with agro-ecological and organic practices in systemic innovation)
Periodo di rendicontazione: 2023-04-01 al 2024-09-30
PestNu addresses the reduction of pesticides and nutrient loss through Digital and Space-based Technologies (DSTs) and Agro-ecological and Organic Practices (AOPs). Overreliance on hazardous pesticides and fertilizers causes environmental degradation, polluting water, soil, and air while negatively impacting biodiversity. Pesticide residues on fruits and vegetables also pose health risks. Despite investments in Integrated Pest Management, Integrated Nutrient Management, and Precision Farming tools, progress remains limited. Lack of EU-level harmonization, insufficient international standards, and low farmer adoption of regulations exacerbate the issue. Many precision farming tools and organic products lack real-world testing, highlighting the need for technical solutions to support small and medium-scale farmers in decision-making and management. PestNu’s societal impacts are significant. It reduces dependency on hazardous pesticides, promotes efficient organic farming, mitigates pesticide risks, and protects the environment and human health. PestNu minimizes nutrient loss from fertilizers, enhances sustainability, and supports the use of recycled materials in fertilizer production, fostering a circular economy and reducing reliance on imported nutrients. It ensures sufficient, safe, nutritious, and affordable food, addressing food security concerns while advancing food safety, new guidelines, policies, and standards. PestNu also facilitates digital transformation, enhancing food security and safety while nurturing students in sustainable practices. It reduces greenhouse gas emissions, excess fertilizers, and hazardous pesticide substances and promotes energy-efficient manufacturing. Economically, PestNu strengthens the EU’s industry, particularly small and medium enterprises, by fostering innovation, stimulating start-ups, creating jobs, and driving digitization. PestNu improves food system resilience to shocks and raises awareness among policymakers, businesses, and citizens about adopting innovative systemic solutions EU-wide, driving behavioral change and promoting sustainability.
PestNu conducted online surveys across nine EU countries, gathering 1,224 responses, revealing low F2F strategy awareness and practitioner skepticism.
PestNu also successfully completed its deployment (M1–M18), field testing, and demonstration (M19–M36) of five advanced DST tools:
a) AI Robotic Trap: Redesigned for shape, integrated with deep learning object detection and population prediction models for whiteflies-black aphids and Tuta Absoluta with accuracies of 89,1% and 97.7% respectively.
b) Satellite Imagery: Powered by AI to calculate vegetation indices in Greece and Spain, achieving >90% agro-anomaly diagnosis accuracy and enabling blockchain-based FSi food traceability certification.
c) Autonomous Agro-Robot: Navigated fields and greenhouses with 4-hour battery autonomy, detecting Botrytis cinerea in cucumbers (92%), tomatoes (79.41%), peppers (87.42%), and Tuta Absoluta (75%).
d) Nutrient Analyzers achieved over 92% accuracy for nitrite and nitrate, over 95% precision, and 90% accuracy for phosphate and ammonium.
e) The flow cytometer, finalized for field use, quantifies and classifies microalgae with 99.5% accuracy for two-unit distinction.
Regarding the Decision Support Systems-Integrated with blockchain and cybersecurity, the DSS utilized data from DST tools at demo sites, aquaponics, and open fields. Field evaluations showed it reduced pesticide use by 50%, increased crop yields, and lowered sample analysis costs by 70%, emphasizing its efficiency and sustainability.
Furthermore, PestNu successfully deployed (M1–M18), field-tested, and demonstrated (M19–M36) its AOP systems and products:
a) Agro-Wastewater System: Installed in greenhouse compartments, it produced on-site biofertilizers (10kg/5 days) using a biocatalysis process with microalgae. This setup enhanced microalgae growth, reduced nitrate levels by 74%, fully retained K, P, and Ca, and promoted circular economy principles. Also, a biofertilizer production protocol was developed.
b) Biopesticide: Fabricated from agrifood waste, it achieved a 50-liter production. In lettuce cultivation, it inhibited Botrytis germination at 2% and 1% concentrations, outperformed chemical pesticides, and increased yields by 0.3 kg/m² compared to untreated organic methods.
c) Integrated Fertilizer Programs: Designed for open-field trials in Greece and Spain, these programs reduced fertilizer use by 20%, carbon footprint by 10%, and improved nutrient efficiency by 20%. Organic IFP further reduced fertilization and carbon footprints but delivered slightly lower yields than conventional methods.
PestNu organizing workshops and training seminars that benefited over 1360 people. The dissemination strategy involved active participation in over 68 events. More than 49 scientific publications have submitted. Another notable achievement is the development of the PestNu Digital platform offers various services, and features a matchmaking tool for F2F stakeholders. Market studies were conducted to assess the potential adoption. Primary markets and key competitors were identified and examined. More than 140 LoI signed F2F organizations and 26 signed collaboration contracts with sister projects affiliated with the Green Deal, support PestNu framework in an active role in promoting methodologies, rallying policy makers and operational groups, and orchestrating roundtables at national workshops and clustering events. 30 practice abstracts and factsheets were produced for EIP-AGRI.
PestNu also successfully completed its deployment (M1–M18), field testing, and demonstration (M19–M36) of five advanced DST tools:
a) AI Robotic Trap: Redesigned for shape, integrated with deep learning object detection and population prediction models for whiteflies-black aphids and Tuta Absoluta with accuracies of 89,1% and 97.7% respectively.
b) Satellite Imagery: Powered by AI to calculate vegetation indices in Greece and Spain, achieving >90% agro-anomaly diagnosis accuracy and enabling blockchain-based FSi food traceability certification.
c) Autonomous Agro-Robot: Navigated fields and greenhouses with 4-hour battery autonomy, detecting Botrytis cinerea in cucumbers (92%), tomatoes (79.41%), peppers (87.42%), and Tuta Absoluta (75%).
d) Nutrient Analyzers achieved over 92% accuracy for nitrite and nitrate, over 95% precision, and 90% accuracy for phosphate and ammonium.
e) The flow cytometer, finalized for field use, quantifies and classifies microalgae with 99.5% accuracy for two-unit distinction.
Regarding the Decision Support Systems-Integrated with blockchain and cybersecurity, the DSS utilized data from DST tools at demo sites, aquaponics, and open fields. Field evaluations showed it reduced pesticide use by 50%, increased crop yields, and lowered sample analysis costs by 70%, emphasizing its efficiency and sustainability.
Furthermore, PestNu successfully deployed (M1–M18), field-tested, and demonstrated (M19–M36) its AOP systems and products:
a) Agro-Wastewater System: Installed in greenhouse compartments, it produced on-site biofertilizers (10kg/5 days) using a biocatalysis process with microalgae. This setup enhanced microalgae growth, reduced nitrate levels by 74%, fully retained K, P, and Ca, and promoted circular economy principles. Also, a biofertilizer production protocol was developed.
b) Biopesticide: Fabricated from agrifood waste, it achieved a 50-liter production. In lettuce cultivation, it inhibited Botrytis germination at 2% and 1% concentrations, outperformed chemical pesticides, and increased yields by 0.3 kg/m² compared to untreated organic methods.
c) Integrated Fertilizer Programs: Designed for open-field trials in Greece and Spain, these programs reduced fertilizer use by 20%, carbon footprint by 10%, and improved nutrient efficiency by 20%. Organic IFP further reduced fertilization and carbon footprints but delivered slightly lower yields than conventional methods.
PestNu organizing workshops and training seminars that benefited over 1360 people. The dissemination strategy involved active participation in over 68 events. More than 49 scientific publications have submitted. Another notable achievement is the development of the PestNu Digital platform offers various services, and features a matchmaking tool for F2F stakeholders. Market studies were conducted to assess the potential adoption. Primary markets and key competitors were identified and examined. More than 140 LoI signed F2F organizations and 26 signed collaboration contracts with sister projects affiliated with the Green Deal, support PestNu framework in an active role in promoting methodologies, rallying policy makers and operational groups, and orchestrating roundtables at national workshops and clustering events. 30 practice abstracts and factsheets were produced for EIP-AGRI.
PestNu has made significant strides in surpassing the current state of the art in pest management, robotics, blockchain and DSS. AI-based image processing algorithms were developed. A definition of evidence was established to validate the Blockchain's Food Sustainability index. A robot, a simulation was designed. A computer vision system was created to target pests. Employing SLM technology, components were fabricated. A robust, user-centric cloud-based DSS for Agriculture 4.0 architecture was designed. Additionally, a DLT framework was defined.The AI algorithms are expected to greatly improve the accuracy and speed of pest detection. The use of Blockchain is anticipated to enhance transparency and traceability. The advancements in robotics aim to automate and optimize farm management. The computer vision system, is expected to play a pivotal role in timely intervention and disease management. The use of 3D printing technology could potentially lead to reduced manufacturing costs. The DSS is anticipated to empower farmers with real-time data and insights about their farms. Finally, the deployment of DLT framework is expected to ensure data integrity and verification of DSTs. By decreasing dependency on hazardous pesticides, PestNu aims to contribute to a healthier environment and safer food sources. The reduction in nutrient loss from fertilisers will enhance their efficiency. PestNu’s progress will significantly enhance food security. The digital transformation PestNu brings will have wide-ranging effects on society and industry. Lastly, the results of this project will contribute to creating sustainable, safe, and attractive workplaces.