Research & Innovation
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Scientific Publications
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Innovations and Related Technologies
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Ongoing Projects
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Funding Opportunities
Reviews and Papers (last 5 years)
- Top 7 Tech Trends in Agriculture for 2024 & Beyond, ebook from infopulse
- Drone-based imaging sensors, techniques, and applications in plant phenotyping for crop breeding: A comprehensive review (2024, DOI: 10.1002/ppj2.20100)
- Non-chemical weed management: Which crop functions and traits to improve through breeding? (2024, DOI: 10.1016/j.cropro.2024.106631)
- High-throughput proximal ground crop phenotyping systems – A comprehensive review (2024, DOI: 10.1016/j.compag.2024.109108)
- Plant microphenotype: from innovative imaging to computational analysis (2024, DOI: 10.1111/pbi.14244)
- The State of the Art in Root System Architecture Image Analysis Using Artificial Intelligence: A Review (2024, DOI: 10.34133/plantphenomics.0178)
- A review of socio-metabolic research on circularity in agri-food systems and pathways to action (2024, DOI: 10.1007/s10705-024-10344-x)
- The hidden side of interaction: microbes and roots get together to improve plant resilience (2024, DOI: 10.1080/17429145.2024.2323991)
- Sustainable laser technology for the control of organisms and microorganisms in agri-food systems: a review (2024, DOI: 10.31545/intagr/177513)
- Nutrient deficiency effects on root architecture and root-to-shoot ratio in arable crops (2023, DOI: 10.3389/fpls.2022.1067498)
- Antibiotic resistance genes in food production systems support One Health opinions (2023, DOI: 10.1016/j.coesh.2023.100492)
- Adapting crop production to climate change and air pollution at different scales (2023, DOI: 10.1038/s43016-023-00858-y)
- From genes to policy: mission-oriented governance of plant-breeding research and technologies (2023, DOI: 10.3389/fpls.2023.1235175)
- Simplified environmental impact tools for agri-food system: A systematic review on trends and future prospective (2023, DOI: 10.1016/j.eiar.2023.107175)
- Grafting in plants: recent discoveries and new applications (2023, DOI: 10.1093/jxb/erad061)
- Machine learning versus crop growth models: an ally, not a rival (2023, DOI: 10.1093/aobpla/plac061)
- Enhancing climate change resilience in agricultural crops (2023, DOI: 10.1016/j.cub.2023.10.028)
- Plant root plasticity during drought and recovery: What do we know and where to go? (2023, DOI: 10.3389/fpls.2023.1084355)
- Approaches and determinants to sustainably improve crop production (2023, DOI: 10.1002/fes3.369)
- Digital transformation in the agri-food industry: recent applications and the role of the COVID-19 pandemic (2023, DOI: 10.3389/fsufs.2023.1217813)
- Crop phenotyping in a context of global change: What to measure and how to do it (2022, DOI: 10.1111/jipb.13191)
- Life cycle cost analysis of agri-food products: A systematic review (2022, DOI: 10.1016/j.scitotenv.2022.158012)
- Cold stress in plants: Strategies to improve cold tolerance in forage species (2022, DOI: 10.1016/j.stress.2022.100081)
- Advances in field-based high-throughput photosynthetic phenotyping (2022, DOI: 10.1093/jxb/erac077)
- High-throughput plant phenotyping: a role for metabolomics? (2022, DOI: 10.1016/j.tplants.2022.02.001)
- Plant disease severity estimated visually: a century of research, best practices, and opportunities for improving methods and practices to maximize accuracy (2022, DOI: 10.1007/s40858-021-00439-z)
- Functional–Structural Plant Models Mission in Advancing Crop Science: Opportunities and Prospects (2022, DOI: 10.3389/fpls.2021.747142)
- Genomics and breeding innovations for enhancing genetic gain for climate resilience and nutrition traits (2021, DOI: 10.1007/s00122-021-03847-6)
- Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data (2021, DOI: 10.1016/j.jplph.2020.153354)
- Looking for Root Hairs to Overcome Poor Soils (2021, DOI: 10.1016/j.tplants.2020.09.001)
- Close-range hyperspectral imaging of whole plants for digital phenotyping: Recent applications and illumination correction approaches (2020, DOI: 10.1016/j.compag.2020.105780)
- Quick microbial molecular phenotyping by differential shotgun proteomics (2020, DOI: 10.1111/1462-2920.14975)
- Photosynthesis in a Changing Global Climate: Scaling Up and Scaling Down in Crops (2020, DOI: 10.3389/fpls.2020.00882)
- Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives (2020, DOI: 10.1016/j.molp.2020.01.008)
- Phenotyping: New Windows into the Plant for Breeders (2020, DOI: 10.1146/annurev-arplant-042916-041124)
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Startups
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Technologies & Gadgets
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AI Applications in Agri-food Sector
Portugal
Tekagro
Technology for Agriculture (reliable, easy-to-use, and smart technological solutions that optimize operations and drive efficiency).
Denmark
Agrain
Transforms the spent grains from beer production into a versatile super flour, rich in protein and fibre.
The Netherlands
Farm21
Data-driven insights enable farmers to optimise their farming practices and become more efficient with water, crop protection, fertiliser, fuel and labour, helping them to cut costs.
Bulgaria
Bee Smart Technologies AD
Its main goal is to help beekeepers take better care of their bees through IoT (Internet of Things) solutions.
United Kingdom
Ace Aquatec
Company partners with world leading experts in different scientific fields to apply their breakthrough technology developments to aquaculture and marine industries.
Switzerland
NEMIS Technologies
Commitment to empower food producers to minimise microbiological risk by providing a unique lab-free detection system that is simple to use.
Kropie – a dashboard to manage your crops; use drones and sensors on farms and forests to monitor vegetation.
PlantEye F600 – patented PlantEye technology to combine 3D and Multispectral information, the F600 stands as one of the world’s leading sensor in the field of Plant Phenotyping.
PhenomeOne’s – mobile application for smartphones and tablets (supporting iOS and Android devices). It is designed for offline and online data collection in fields, such as observations and selections, including images.
Israel
AI driven image analysis technology systems for seed and grain quality prediction to maximize seed quality
Germany
Forecast solution using machine learning to combine historical data of catering businesses with additional external factors to calculate future sales figures, helping businesses to reduce food waste.
More information coming soon.
More information coming soon.