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Downloading the data farmers need, then visualizing, manipulating, and editing it that and more, this app does it all.
Armed with this data, farmers can isolate areas of their fields that are being negatively affected by insects, disease or lack of water.
According to the baseline data, farmers' primary information sources are extension workers and fellow farmers in their farmers' groups.
Using this data, farmers can then decide to replace trees that underperform, for example, or map out a plan to selectively harvest based on the size of a tree's fruits and its development stages.
Using the new data, farmers can opt to plant vegetables prized for their flavor, rather than appearance, and expand on a $2 billion annual market for the product in the U.S. alone.
According to the report - which is based on interviews and surveys as well as satellite and government data - farmers complained of sporadic water availability, the high cost of fuel to run irrigation pumps and a shortage of tillage equipment.
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Union Square Ventures is smack dab in the middle at No. 5. Much of the data Farmer used to analyze investor networks comes from CrunchBase.
When asked about what the future of farming looks like, Caleb Harper imagines a world filled with data scientist farmers, roboticist farmers, and plant chemist farmers.
Others are trying to bring big data to farmers without ever consulting with a farmer.
For example a paper by Dubey et al [ 30] studying risk of Toxoplasmosis on US farms collected interview data from farmers and collected blood and fecal specimens from animals and farmers as well as soil and water samples.
In the pooled data, the farmers from Kano (KANO), an irrigated rice producing area, devote more land to IRVs than farmers from other locations.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com