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Making sense of the data

An article summarising the technologies available for analysing farm data.
© EIT Food

Online software platforms can now provide a management system for farmers and agronomists that can analyse field level data and help optimise farm operations. These platforms use a combination of data from ‘traditional’ farm measurements along with data from ‘smart devices’ – digital devices such as weather stations or soil probes that are connected to the internet.

Such systems can provide decision support tools for specific crops that are based on the data gathered from a range of connected in-crop or on-tractor sensors. As well as this, they use algorithms to analyse satellite images to identify specific areas of poor crop growth due to water stress or altered spectral reflectance due to pest or disease damage.

The raw data gathered in these cases are of limited value on their own, but the analysis of these multiple measurements can provide timely agronomic advice and forecasting information. The analysis of these data forms the basis for precision farming techniques as they allow the identification of specific, spatially-explicit areas in need of improved management and, in combination with GPS technologies, allow the targeted delivery of precisely calculated inputs.

An overview of precision agriculture technologies (from Balafoutis et al. 2017 CC BY). Click to expand.

Here are some examples of online management systems for arable farming:

Gathering the data sent directly from connected machines in your fields into one central hub can make administrative tasks more efficient by generating reports and allowing secure data exchange with other people and organisations.

How do you think you may be able to use data from smart devices to help with your crop management? What advantages do smart devices offer compared to traditional data gathering techniques?

© EIT Food
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Innovation in Arable Farming: Technologies for Sustainable Farming Systems

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