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Can AI make farm practice smarter?

Can AI make farm practice smarter?
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Apr 11, 2023 · 21m 25s

Here are some of my learning points from this podcast: - Agmatix is trying to consolidate agronomic field trial data, through digitalisation, to make this data more available, to agricultural...

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Here are some of my learning points from this podcast:
  • Agmatix is trying to consolidate agronomic field trial data, through digitalisation, to make this data more available, to agricultural researchers, agronomists and farmers.
  • Agmatix has two main activities. First, the digitalisation of agricultural R&D, focusing on agronomic insights and especially field trial data, and second, interpreting and applying those data, to develop prescriptions for agronomists to share with farmers.
  • Both activities rely heavily on the use of smart algorithms, under the company’s Axiom platform.
  • Regarding the digitalisation of field trials, Agmatix has first had to standardise crop research data, including agricultural taxonomy, such as crop names (corn or maize?), as well as units of measurement (bushels or tonnes?); and research protocols and methods, such as soil depth in soil sampling trials.
  • With its standardised approach in place, it has gone on to digitalise more than 50 million field trials to date, covering more than 150 crops.
  • Research groups and agricultural companies can use this digitalised platform to organise their own field trials, using the standardised format to share results more easily, for example in collaborative projects. Agmatix says it has developed an open platform for plant nutrition, with various partners, based on more than 2,000 sources of field trials. The link is here: https://cropnutrientdata.net/
  • The second main activity of the company is to translate these insights from aggregated field trials into digital prescriptions, via its Crop Advisor decision support tool for agronomists.
  • Agmatix can use its ingested field trial data to develop models, to understand for example the risk factors governing eruption of a particular disease, which agronomists can then use in their work with farmers.
  • The standardised field trial data can help agronomists to deliver prescriptions according to local circumstances and practices, for example how to balance chemical inputs and farm practice to deliver a particular yield in a particular way, for example with the smallest carbon footprint.
  • By working with agronomists and farmers, Agmatix can also ground-truth its algorithms, and so improve their accuracy.
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Author Gerard Wynn
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