Enabling cross-European cooperation and innovation transfer
Enabling cross-European cooperation and innovation transfer
We are solidifying the transfer of scientific knowledge, innovative technologies and business know-how throughout Europe.
International cooperation between science, business and the public
Joint technology research, development and innovation projects
Innovation adaptation and use case development to fit market needs
Business development, commercialization and marketing consulting
The aim of the project is to create a technology that will enable the user to analyze the levels of protein, glycogen, fat and moisture in oysters with an accuracy/prediction rate higher than 0.9 (r2) and with a prediction error that does not exceed 0.4%. The time of a single analysis (including data collection, processing and analysis) carried out by a prototype shall not exceed 1 hour.
During the project, a technological prototype will be developed for the determination and estimation of protein, glycogen, fat and moisture concentrations in oysters based on NIR spectroscopy and algorithms for data analysis based on machine learning. The technology will include an accurate and detailed methodology for the preparation of the oyster sample, a description of the technical parameters of the hardware and the specifications required for the research, the procedure for performing the analysis, data collection, processing and analysis of the solution documentation.
The main problem that this project solves is the insufficient competitiveness of Benco Baltic d.o.o. on the local, international and global markets, which results from the insufficient innovative capacity of the company – inadequate level of innovation of processes and business organization, and inadequate tangible and intangible assets to ensure the commercialization of radical innovation on the global market – SOQA. The main goal of the project is to raise the SOQA innovation to the level of the beginning of commercialization, i.e. to the level of readiness for the market (TRL 9).
Project ID: E!13308
Total value of the project: 688.076,18 EUR
The total value of the HR part of the project: 331.897.71 EUR
Funds requested: 199.138,63 EUR
Date of the contract: 2020-06-29
Launched with the objective of assessing the impacts of digitalisation in agriculture, QuantiFarm will develop and deploy a framework to evaluate the effectiveness and performance of digital tools that promise to modernise farming.
The project’s ambition is to support the further deployment of digital tools as key enablers for enhancing economic, environmental and social sustainability. But first, it wants to convince farmers with evidence that it works. Thereafter, QuantiFarm aims to make these assessments and their impacts replicable, comparable and of practical use to farmers.
QuantiFarm’s strategy ensures that the project adequately encompasses and represents European diversity. In numbers, that means 30 test cases spanning over 20 countries in 10 (of the 11) biogeographical regions across Europe that will take place in 100 commercial farms from 7 agricultural sectors across 20 crops and animals.
Link to the project’s website: https://quantifarm.eu
XGain was developed to support the design and development of programs and interventions that address two of these main issues:
Based on real-life, real needs in real-time, XGain will deploy, explore and assess digital connectivity options by applying various technological solutions to a wide spectrum of geographical locations and sectors. XGain will utilise and analyse all different scenarios to identify and suggest optimal connectivity and edge computing solutions for rural communities and individual stakeholders.
XGain’s core ambition is to gather all the necessary “Rural Digital Connectivity” puzzle pieces into a Knowledge Facilitation Tool (Digital Platform). With an easy-to-use web-based interface, interested stakeholders can select “pieces of their puzzle” (requirements). Options like the sector of interest (e.g., Agriculture), service (e.g., Precision Farming), location needs (e.g., connectivity range) and scale (farm/community/regional) will be compiled as inputs and processed. In a consistent, efficient and effective way, XGain’s Knowledge Facilitation Tool will utilise user’s inputs and, based on the Knowledge “Gains”, will provide recommendations for the “best-fit” technological solutions that are both cost-effective and environmentally friendly, taking into consideration local-social aspects. Finally, XGain will identify existing and develop alternative business models adapted to real-life/real-needs conditions.
Link to the project’s website: https://xgain-project.eu
BENCO Baltic is initiating an innovation project in Croatia in order to create a solution for disease recognition in grapevines at an early stage. The targeted solution combines unmanned aerial vehicles, spectrometry and advanced analytical models into a complete solution for applications on the farm.
Grapevine spectral data is captured using high precision hyperspectral cameras mounted on drones. The data is then processed using advanced, custom-built analytical models, developed by using Machine Learning, Neural Networking and various other data analysis techniques. Once developed and commercialized, the solution will provide vineyards with crucial information on plant health and an interactive map that outlines problem areas in the field. The farmer would them be able to take timely action, plan targeted agrochemical use and thus reduce productivity loss.
The potential of the already developed base technology to be used in this project is currently being demonstrated and tested on-farm in one of the biggest EU agriculture and IoT innovations projects – the ‘Internet of Food & Farm 2020’ (IoF2020).
BENCO Baltic is participating in an international consortium to develop and demonstrate an innovative technological solution for oyster quality assessment on-site.
The approach chosen to address the market need for preventative oyster testing on-site utilizes NIR spectrometry in combination with machine learning and advanced data analysis techniques. The expected end result will be a service for rapid on-site assessment of oysters by scanning oyster flesh and uploading the data to a SaaS platform. The solution will help farmers assess oyster quality, growth conditions, evaluating potential risks and operational planning both at oyster growing and harvesting stages, as well as performing oyster quality and freshness monitoring and preventative screening down different supply chain stages.
The project has been co-financed by HAMAG-BICRO through the EUREKA program.
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