Growing Returns

Selected tag(s): big data

Venture capitalists find rising market in rural America via data-loving farmers

Technology investors are discovering a new and largely untapped market: farmers in heartland America eager to fly drones, employ robots and crunch big data to boost their business.

In 2017, tech startups in the agriculture sphere raised $670 million to develop software management, big data analytics, automated equipment and other cutting-edge tools that help farmers grow crops with scientific precision, AgFunder reported. Agriculture is one of the last major sectors to experience the digital revolution and it’s a market ripe for growth.

New technology allows farmers to manage their fields down to the square foot – tracking plant health, soil moisture and estimated profit in real-time. That requires advanced software, sensors and state-of-the-art imaging technology.

A farmer flies a drone to aerially inspect crop health.

Precision agriculture could account for 80 percent of civilian drone use by 2020.

To meet such needs, investors raised more money for ag tech startups in 2017 than during the previous two years combined. Read More »

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How John Deere and Cornell can ensure big data benefits farmers and the environment

John Deere combine harvesting soybeans.

5 gigabytes of data is the equivalent of up to 1.6 million emails. (Photo credit: Flickr user Judd McCullum)

Modern farm equipment comes more outfitted than a fully loaded car. These precision farming machines are furnished with multiple sensors that collect data during planting, nutrient application and harvest. A typical farmer now has 5 gigabytes of data, five seasons’ worth, in storage.

This trove of data promises to revolutionize farming, giving farmers unparalleled insights for business and stewardship decisions. Unfortunately, the data collected tends to stay on equipment hard drives, greatly reducing its usefulness to farmers.

A new partnership between John Deere and Cornell University promises to change that. Ag-Analytics, a Cornell data platform, syncs with John Deere’s Operation Center and makes it easier than ever for farmers to access and analyze farm data. Cornell is the first university to integrate with John Deere, and the analytical tools now available to farmers include a crop insurance estimator and yield and risk management forecasts. Read More »

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Why privacy is an essential piece of agriculture’s big-data revolution

Your ag data has the possibility of being hackedData science in farm management is one of the biggest trends to hit both agriculture and Silicon Valley in recent years, with an explosion of technologies emerging to help farmers optimize everything from seeding to irrigation to fertilizer application.

As ag tech products grow more sophisticated, so too has the innovation trend evolved. What began as a slew of single-purpose tools has now evolved to include apps that integrate different types of information to give farmers a “dashboard” view of their land. And it includes new apps that can help multiple farmers pool their data to analyze a crop’s performance across a range of growing conditions, or to benchmark their input costs against one another.

The agriculture sector stands to gain insight from all this data. Farmers need metrics to help them figure out how to increase yields sustainably while improving soil health and protecting natural resources for future generations.

But they have valid concerns about sharing data. Read More »

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Who will protect farmers’ privacy in the big data boom?

shutterstock_171929321When it comes to technology and agriculture, policymakers are wrestling with the role government should play in protecting the intellectual property rights and privacy of farmers.

This discussion came to a head recently when the House Agricultural Committee held a hearing to examine the impacts of “big data” on the entire agricultural life cycle. With farmers and companies collecting and storing data on everything from fertilizer rate to yield to soil conditions, there are important concerns to consider: Is the data secure? Who owns analyzed data? Will companies sell the data to others or make new products based on sensitive information?

Ahead of this hearing I wrote a blog post detailing the hurdles farmers must overcome to fully integrate data as a way to increase the abundance and sustainability of modern food production. The main challenges I highlighted were:

  • Privacy: Farmers need to know they won’t be willingly revealing trade secrets when deciding to share data about their farming techniques.
  • Format: Not all data collection platforms use the same language, so a uniform way to understand what is being collected must be created.
  • Complexity: Many growers are intimidated by the vast quantity of data they collect, so we have to help them understand what matters and what doesn’t.

Read More »

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How to overcome big data’s barriers

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Credit: Flickr user Marcos Gasparutti

As I wrote earlier this week, data analytics technology has the potential to dramatically change the way we produce food, making it more abundant and sustainable. But a number of obstacles remain.

Here’s how we can address some of the biggest challenges and hasten ag’s big data revolution for the benefit of people and the planet.

1. Protecting privacy

Many growers have told me they are willing to share data – if they know exactly where it’s going and how it will be used, and if they can benefit from the data analysis that occurs. However, big concerns remain about data being used for regulatory compliance purposes, given to rival farmers, or shared with seed and fertilizer companies that would gain a competitive advantage. Read More »

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Ag’s big data explosion can benefit the environment too

Almost daily, I see new stories on how agribusinesses, entrepreneurs, and traditional technology companies are making big investments in precision agriculture tools and digital platforms that collect data from farms.

These data include information such as fertilizer rate, prescription accuracy, yield by square foot, seed type, and soil type. When analyzed at a large scale, the data can determine best practices for farm operations to maximize yield and minimize input costs.

This is an exciting trend, with big and small companies alike getting into the data game, and the tools used to collect this data becoming ubiquitous. And although these technologies weren’t necessarily started with sustainability in mind, they have tremendous potential to benefit the environment. Read More »

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A farmer’s perspective: 4 reasons why collecting data is important

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Kristin Duncanson

Thanks to GPS and the Internet, many farmers have been collecting data about their farms – water usage, inputs, crop yields – for over 20 years. Only in recent years has the term “big data” taken on a new meaning, given the plethora of new tools and technologies available today to help farmers collect and analyze data on all aspects of their farm operations.

This week also marks the launch of the first-ever Big Data Roundtable Series, an annual event that brings together experts from across the agricultural arena to discuss how major retailers can leverage data to improve business sustainability, and how growers can utilize measurement tools and analyze data to use fertilizer more efficiently and save on input costs.

Here, I ask Kristin Weeks Duncanson, a crop and livestock operator and member of the AGree advisory committee, to explain the value of collecting data for farm operations and the environment and why many farmers are still hesitant to collect data. Read More »

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Farmers know: You can’t manage what you don’t measure

Adapt-NIt is no surprise that information has value in the technology age. A recent article in the New York Times spotlights an Indiana farming family to show how information is shaping 21st century agriculture.

Kip Tom, a seventh-generation farmer, is riding the wave of agricultural consolidation that, since the 1980s, has led to bigger farms, bigger technology, and now, bigger data.

Bigger revenues have come along with this transition. Tom says better data analysis has raised his return on investment over seven percent – from 14 percent to 21.2 percent.

Read More »

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