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Precision Agriculture Eats Data, CPU Cycles

Given their rural isolation, toiling miles away from the coastal centers of technology and finance, it’s easy to overlook the remarkable growth in productivity on the average farm. One look at a chart of corn yields, which have increased four-fold since the early 50′s, shows that farmers are marching to their own version of Moore’s Law. While past improvements were the result of better plant hybrids, fertilization and production equipment, information technology will be the key to sustaining and perhaps accelerating agricultural  productivity. Precision agriculture, a collection of data collection, analysis and prediction technologies that looks like something out of Google, not John Deere, describes a group of technologies designed to collect and analyze detailed information about growing and crop conditions that feed complex models designed to provide actionable recommendations to improve yields and reduce costs.

Historical Corn Grain Yields for Indiana and the U.S. - Corny News Network (Purdue University).clipular

Although precision agriculture is an important tool for feeding a growing planet while minimizing environmental damage, the motivation for farmers is less altruistic. According to Eduardo Barros, Accenture’s Global Products Agri-business Lead, data-driven decisions about irrigation, fertilization and harvesting can increase corn farm profitability by $5 to $100 per acre. Barros adds that a 6-month pilot study found precision agriculture improved overall crop productivity by 15%. It seems like a no-brainer for farmers if not for the nasty implementation details: new sensors and equipment for granular data measurement, data collection, integration with third-party data sources like weather models and satellite imagery, and number-crunching data analysis to produce recommendations. While not insurmountable hurdles for big corporate farms, the technology requirements and expertise are beyond the reach of smaller farmers, particularly in developing countries. Enter cloud services: the same technology equalizer that allows two-person startups to develop software using hundreds of servers can deliver sophisticated agricultural analytics to the family farm.

By combining aspects of IoT and big data, precision agriculture has a lot in common with burgeoning analytics applications in many other industries. The need for prodigious data collection, from many sources, associated storage and computational horsepower makes it a great fit for cloud services. Not only do shared services broaden the available market for precision agriculture, but the cloud enables agricultural crowdsourcing, by aggregating data from a wide variety of smaller operations to improve prediction models.

Source: Accenture

Although Barros didn’t discuss Accenture’s implementation specifics, given the amount of data collected and the episodic nature of model calculations, precision agriculture software is a great fit for IaaS platforms like AWS or Google Cloud. With a variety of services like NoSQL plus Hadoop data analysis and HPC compute grids, including support for GPU instances by AWS for parallelized number crunching, cloud infrastructure is an ideal way to develop precision agriculture software and deliver packaged services to customers like small farmers with few IT investments and little expertise.

Although relatively small, one estimate shows the precision agriculture market growing at over 13% per year hitting $3.7 billion by 2018, with the rate in emerging markets expected to exceed 25%. According to aninvestment bank report on precision agriculture, “The entire industry is realizing that a key value driver in the development of precision agriculture is data — collecting it, analyzing it, and using it.” Although data collection will remain a local problem, shared cloud services can accelerate the analysis and lower the barriers to farmers needing actionable intelligence. Precision agriculture will be an interesting field to monitor for both technological advancements and investment opportunities.

(Author: Kurt Marko, source – http://www.forbes.com/sites/kurtmarko/2015/08/25/precision-ag-cloud/2/)

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