{"id":33775,"date":"2018-11-13T17:42:39","date_gmt":"2018-11-13T22:42:39","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/round-down-john-deere-brings-machine-vision-to-precision-agriculture\/"},"modified":"2018-11-13T18:14:01","modified_gmt":"2018-11-13T23:14:01","slug":"round-down-john-deere-brings-machine-vision-to-precision-agriculture","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/round-down-john-deere-brings-machine-vision-to-precision-agriculture\/","title":{"rendered":"Round Down: John Deere Brings Machine Vision to Precision Agriculture"},"content":{"rendered":"

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Source: James Vincent, \u201cJohn Deere Is Buying an AI Startup to Help Teach Its Tractors How to Farm,\u201d The Verge, September 7, 2017,
\nhttps:\/\/www.theverge.com\/2017\/9\/7\/16267962\/automated-farming-john-deere-buys-blue-river-technology<\/a>, accessed November 2018<\/h6>\n

“Take one man and put him on a tractor, and we can do the work of 8 to 10 people.”<\/em> – Clint Bigham, Blue River client [1]<\/a><\/p>\n

With global food demand slated to increase up to 98% by 2050\u00a0[2]<\/a>, farming yield en route to drop 2-3% due to climate change [3]<\/a>, and a superweed crisis emerging in response to reliance on a narrow range of herbicides\u00a0[4]<\/a>, the agriculture industry faces an unprecedented need for innovation. Recent years have seen a spate of consolidation and investment, with a record $10.1B pouring into agricultural technology (\u201cag-tech\u201d) startups in 2017. Last year also featured a bumper crop of acquisitions, including purchases of farm software company Granular by DowDuPont for $300M and agricultural robotics startup Blue River by Deere & Company for $305M.\u00a0[5]<\/a><\/p>\n

These acquisitions typify two dominant trends in the farming industry: continuing progress in \u201cprecision agriculture\u201d, the use of sensors and algorithms to manage site-specific crop and soil variability\u00a0[6]<\/a>, and the emerging space of agricultural machine learning. The latter industry is expected to grow 23.2% year-over-year through 2023, concentrated in crop monitoring, robotics, irrigation, and farm drones.\u00a0[7]<\/a> With data availability multiplying 1000-fold in the past two decades and software reaping concomitant performance improvements, machine learning investment over the next decade will prove not merely beneficial but indispensable to agricultural companies\u2019 survival.\u00a0[8]<\/a><\/p>\n

Deere & Company, the world\u2019s largest farm equipment manufacturer with $29.7B in 2017 revenues\u00a0[9]<\/a>, is an established leader in precision agriculture and innovator in autonomous navigation. The company\u2019s pioneering AutoTrac™ guidance system, together with competitors, is used in 60-70% of U.S. farm acreage\u00a0[10]<\/a>. The Blue River acquisition enhances Deere\u2019s technological portfolio, enabling its tractors to identify specific crops and weeds using the same deep learning algorithms underlying facial recognition\u00a0[11]<\/a>. Now used in lettuce production with 10% US adoption, Blue River\u2019s software replaces the current standard of broad-based Roundup sprays, made costlier and less effective by herbicide-resistant \u201csuper-pests\u201d, with micro-sprays the size of postage stamps. Technology director Willy Pell claims that the successor for cotton will reduce herbicide usage by 90%. Soybean- and corn-specific products, as well as harvesting and seed-planting products that incorporate soil type and crop size, are currently under development.\u00a0[12]<\/a><\/p>\n