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Current science projects researched in Institute of Plant Protection – NRI that are financed
by The National Centre for Research and Development (NCBR)
"Grapevine Viruses in Polish Vineyards – Diagnostics and the Use of Immunity Inducers to Enhance the Immunity and Health-Promoting Properties of Grapes"
The project is funded by the National Centre for Research and Development under the Innoglobo program (4th call).
Acronym: IMMU-Grape-VIR
Implementation period: September 1, 2025 - August 31st, 2028
Contract: INNOGLOBO/4/80/IMMU-Grape-VIR/2025 of October 22nd, 2025
Eligible costs for the national consortium: PLN 1,196,725.00
Funding from the National Centre for Research and Development: PLN 1,196,725.00
Eligible costs for the Institute of Plant Protection – National Research Institute: PLN 837,125.00
Contractors:
Institute of Plant Protection – National Research Institute – Leader
University of Life Sciences in Lublin
International project partner:
Loewe Biochemica, Germany
Project manager for the Institute of Plant Protection – National Research Institute (PIB): Dr. DSc Aleksandra Obrępalska-Stęplowska, prof. IOR-PIB (Department of Molecular Biology and Biotechnology)
The main objectives of the project will be to monitor the occurrence of plant viruses on grapevines in vineyards in Poland, develop rapid diagnostic protocols for detecting these viruses, and describe the impact and determine the dose of selected RIs on the ripening and metabolic changes in grapevine plants and fruit, along with the induction of resistance to selected viruses that pose a threat to grapevine cultivation in temperate climates. The project will analyze grapevines from vineyards in various geographical areas in Poland for the presence of viruses.
As a result of the project, monitoring for the presence of four selected viruses will be conducted. In collaboration with a foreign industry representative (a diagnostic company from Germany), diagnostic protocols will be developed, validated, and their effectiveness confirmed in practice. During the three years of the project, the monitoring carried out, together with the determination of the virome using the NGS technique, will allow for the determination of the dynamics of the occurrence of viral pathogens in Poland, which will contribute to determining the potential threat of the spread of viral diseases in Polish vineyards.
"Artificial Intelligence for the Identification of Undesirable Phenomena in Crop and Plant Protection"
On March 1st, 2024, the project "Artificial Intelligence for the Identification of Undesirable Phenomena in Crop and Plant Protection" began. It was funded by the National Centre for Research and Development (NCBR) under the INFOSTRATEG-VI/0014/2023/A call, which runs until February 28th, 2027.
The total cost of the AI4CROP project is PLN 6,841,645.80, including PLN 5,656,945.64 in subsidies.
Agreement No. INFOSTRATEG6/0014/2023/A of September 2nd, 2024.
Eligible costs for the Institute of Plant Protection – National Research Institute: PLN 1,437,375.
Project Manager for the Institute of Plant Protection – National Research Institute: Prof. Dr. Jolanta Kowalska (Department of Organic Agriculture and Environmental Protection)
Contractors from the Institute of Organic Agriculture – National Research Institute:
- Dr. Andrzej Wójtowicz (Department of Mycology),
- Lidia Łopatka (Department of Organic Agriculture and Environmental Protection),
- Rafał Nowaczyk, M.Sc. Eng. (CBRA - PSD in Winna Góra),
- Dr. Joanna Krzymińska (Department of Organic Agriculture and Environmental Protection).
The project is being implemented under Topic No. 6 of the competition – "Selective Plant Protection Scenarios."
The consortium includes the following entities:
1) 4ROBOT spółka z ograniczoną odpowiedzialnością – Leader,
2) Actuaro Sp. z o. o.,
3) Institute of Plant Protection – National Research Institute in Poznań
The main goal of the innovative AI4Crop project is dedicated to the Polish Artificial Intelligence (AI) sector and the development of solutions for direct application in precision agriculture. R&D work will lead to the implementation of: 1/ an individual, innovative monitoring system that distinguishes crop responses to pathogens, pests, and drought; this system will be based on spectral images and coordinated by an ANN; 2/ methods for creating maps indicating areas in crop fields at risk of diseases, pests, and drought, including division into areas requiring intervention (critical, endangered, preventive); 3/ ANN models for real-time diagnosis (recognizing current threats) and forecasting (including risk modeling based on forecasted weather conditions); 4/ An automation system for intelligent spraying, capable of integration with field sprayers (including a selective spray control algorithm using orthophotomap data, an algorithm for positioning spray elements in space and determining their trajectories). These key innovations will serve as the basis for developing new standards for selective protection of conventional and organic crops.
Technology Concept Description
The main objectives of the technology are early disease detection and precise and effective protective treatments for selected pathogens and pests in wheat and potato plantations. The technology is built on four basic functional elements: a database of patterns – images of healthy and diseased plants with varying disease severity; a monitoring kit (UAV + spectral camera + ANN module); a map of plantation infections; and a modernized field sprayer with adjustable application rate and spot spraying capability, compatible with a hazard map.
"Intelligent System for Recognizing Undesirable Phenomena on Plantations"
The project "Intelligent System for Recognizing Undesirable Phenomena on Plantations", funded by the National Centre for Research and Development (NCBR) as part of the INFOSTRATEG competition, will begin on March 1st, 2025. The project ends on February 29, 2028.
Agreement: INFOSTRATEG6/0024/2023/A dated August 2nd, 2024.
Annex No. 1/2024 dated October 25th, 2024.
The total implementation cost of the SYSTROP project is PLN 6,648,800.00, including PLN 5,948,960.00 in subsidies.
Eligible costs for the National Research Institute (IOR – PIB): PLN 816,750.
Project Manager from the Institute of Plant Protection – National Research Institute: Dr. Wojciech Kubasik (Department of Monitoring and Signalling of Agrophages )
Contributors from the Institute of Plant Protection – National Research Institute:
- Dr. DSc Paweł Bereś, Prof. IOR – National Research Institute (TSD Rzeszów),
- Dr. DSc Eng Przemysław Strażyński (Department of Entomology and Agricultural Pests),
- Dr. Katarzyna Pieczul (Department of Mycology),
- M.Sc Eng Ilona Świerczyńska (Department of Mycology).
The project is being implemented under Topic 6 of the competition – "Scenarios for Selective Plant Protection."
The consortium includes the following entities:
1) Łukasiewicz Research Network – Poznań Institute of Technology – Leader,
2) IDFS spółka z ograniczoną odpowiedzialnością,
3) Institute of Plant Protection – National Research Institute in Poznań.
The project aims to develop a fully functional system based on artificial intelligence algorithms for recognizing undesirable phenomena in plantations, such as plant diseases, harmful insect outbreaks, and problems related to moisture and soil nutrient deficiencies. The detection system, enriched with additional data, such as GNSS positioning and meteorological data, will provide a comprehensive tool for crop monitoring and planning agrotechnical treatments.
The project will contribute to the creation of a comprehensive test database, the development of research potential in the field of artificial intelligence and embedded vision, and the development of new, more efficient and effective tools to support growers in monitoring and caring for crops.
Developing an automatic detection system based on artificial intelligence to monitor plantation conditions can be a valuable tool for farmers without specialized agricultural knowledge. By utilizing cameras, additional sensors, and developed decision-making algorithms, the system will significantly accelerate and improve the detection and diagnosis of nutrient deficiencies or excesses, diseases, and pests, enabling the advance planning of appropriate preventative and intervention measures or their implementation during the same machine pass, in real time.
