NEWS


15.07.2019

Estonia: Plant Biology Infrastructure Now Listed in National Roadmap and New Collaboration for Use of Big Data in Agricultural Research

TAIM

The Plant Biology infrastructure (TAIM) is listed in the Estonian Research Infrastructure Roadmap 2019, and Estonia now has a long-term programme for the use of agricultural big data – a collaboration between Agricultural Research Centre, Estonian University of Life Sciences, Estonian Crop Research Insititute, Tieto Estonia AS and E-Agronom OÜ.

Plant Biology Infrastructure Now Listed in Estonian Research Infrastructure Roadmap

The Plant Biology infrastructure (TAIM) is part of the Estonian Research Infrastructure Roadmap 2019. TAIM facilitates the implementation of research-based smart practices for the efficient use of plants, expanding the application fields of plants and developing precise agriculture solutions in Estonia.

Innovative monitoring and phenotyping technologies—different gas exchange systems, field sensors, monitoring masts and drones—allow to monitor the condition of plants or fields and collect data in real time. The planned developments combine the basic knowledge obtained from universities’ laboratories with practical plant breeding experience and large-scale crop tests of the Estonian Crop Research Institute and ensure knowledge transfer to the bioeconomy sector. TAIM is a collaboration between University of Tartu, Estonian University of Life Sciences, Tallinn University of Technology and Estonian Crop Research Institute.

 

Collaboration for Use of Big Data in Agricultural Research

Estonia now has a long-term programme for the use of agricultural big data, which is a collaboration between Agricultural Research Centre, Estonian University of Life Sciences, Estonian Crop Research Insititute, Tieto Estonia AS and E-Agronom OÜ.

The aim of the programme is the creation of a central electronic system to link and integrate existing data with analytical models and practical applications. This will help to create an added economic value to agricultural data, support development of precision and environmentally friendly farming. It will also facilitate the presentation of agricultural data in a more efficient way and aid more precise resource management (e.g. fertilisation advice based on soil data while taking into account the nutrient balance). The system is a basis for commercial applications.

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