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    Ficha del GO PREDIVÍ sobre un modelo de predicción de cosecha vitivinícola a través del big data

    El proyecto está basado en el uso de tecnologías big data y machine learning para poder desarrollar modelos de predicción que anticipen información sobre la evolución de parámetros de calidad y volúmenes de cosecha para el sector vitivinícola. Para tal fin, se ha utilizado la información que tienen disponibles las empresas y organizaciones participantes en el proyecto referentes a históricos de producciones, parcelarios, controles de maduración, muestreos, etc. que conjuntamente con las variables obtenidas en la campaña (meteorología, imágenes satélites...) permiten la realización de la predicción. El modelo creado ha mejorado mucho la eficiencia (reducción de costes ligados a las prisas de muestra en parcela) en la predicción de las dos variables estudiadas con unos errores en torno al 10%. El modelo tiene una potente capacidad de aprendizaje que asegura la reducción del error con futuras campañas.

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    Projet

    PREDIVÍ: big data-based wine harvest prediction model

    PREDIVÍ: big data-based wine harvest prediction model

    Localisation
    • Spain
    Auteurs
    • INNOVI Association of Innovative Companies
    Objectif
    • Communication
    • Dissemination
    Type de fichier
    Document
    Taille du fichier
    322 kB
    Publié sur
    01-10-2021
    Langue originale
    Spanish
    Site officiel du projet
    PREDIVÍ: big data-based wine harvest prediction model
    License
    CC BY
    Mots-clés
    • sector vitivinicola
    • big data
    • machine learning
    • modelo predictivo

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    A Bio-inspired Multilayer Drainage System

    Document

    Agricultural run-off and subsurface drainage tiles transport a significant amount of nitrogen and phosphorus leached after fertilization. alchemia-nova GmbH in collaboration with University of Natural Resources and Life Sciences, Vienna developed two multi-layer vertical filter systems to address the agricultural run-off issue, which has been installed on the slope of an agricultural field in Mistelbach, Austria. While another multi-layer addressing subsurface drainage water is implemented in Gleisdorf, Austria. The goal is to develop a drainage filter system to retain water and nutrients. Both multi-layer filter systems contain biochar and other substrates with adsorption properties of nutrients (nitrogen, phosphorus). The filter system can be of practical use if an excess of nutrients being washed out is of concern in the fields of the practitioner by keeping the surrounding waters clean. This approach may result in economic value by re-using the saturated biochar as fertilizer and improving the soil structure, thus increasing long-term soil fertility. Link: https://wateragri.eu/a-bio-inspired-multilayer-drainage-system/

    • Drainage System
    • water treatment system
    • retain water
    • drainage filter system

    NANOCELLULOSE MEMBRANES FOR NUTRIENT RECOVERY

    Document

    This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 858735This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 858735. FACTSHEET NANOCELLULOSE MEMBRANES FOR NUTRIENT RECOVERY Key information Functionalized nanocellulose membranes can take up nitrate and phosphate. These membranes can be put in a water treatment unit. As the membranes are biobased, degradable materials, they can after use be added to the soil, thus returning the leached nutrients back for their original purpose providing fertilizers (nutrient recycling).

    • Biobased nutrient capture
    • agricultural drainage water
    • nanocellulose-based membrane
    • runoff treatmen
    • nutrient-rich membrane

    Environmental monitoring within greenhouse crops using wireless sensors

    Document

    Because variables such as temperature and humidity have a profound effect on the activity of crop pests, diseases and natural enemies, the ability to monitor environmental conditions within a crop has always been important for crop protection.

    • Brassica
    • IPM
    • monitoring
    • pest
    • crop
    • diagnostics
    • detection
    • decision support
    • application
    • techniques
    • sprayer
    • drone
    • UV
    • sensors
    • environmental conditions
    • greenhouse
    • case study
    • temperature
    • humidity