Seven big data lessons for farming

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Big data. If you haven’t yet heard that term dropped in casual conversation with other farmers, you likely will — soon.

It is the term commonly used to describe the colossal amounts of information that are being generated throughout the world at breakneck speed and that are becoming so large and complex that processing, assessing and storing it often prove challenging.

How big is big data? If the data now stored across the planet were printed in books, these books would cover the entire surface of the United States some 52 layers deep, according to Viktor Mayer-Schonberger and Kenneth Cukier, authors of a new book titled “Big Data: A Revolution That Will Transform How We Live, Work and Think.”

People and organizations across the planet are already harnessing this data to accomplish all sorts of things.

Three people who have witnessed the marriage of precision farming and big data within the last few years say farming is primed to benefit too.

Dr. John P. Fulton, an Auburn University professor of biosystems engineering who heads the Alabama Cooperative Extension System’s crops team; Simerjeet Virk, a bioystems research engineer at Auburn University; and Andrew Williamson, a British cereal crops producer and Nuffield Farming Scholar, contend that data compiled in real time are already providing producers with a clearer, more comprehensive picture of all facets of farming, whether this happens to be soil science, seed rates, fertilizer optimization or weed and pest control. 

They predict that this growing body of data will ultimately free producers of much of the day-to-day guesswork associated with farming. 

The three have identified seven major lessons farmers should draw from this Big Data revolution.

1. Big data will secure a considerably clearer farming picture.

Williamson, who farms more than 900 acres of cereal crops near Birmingham, England, is one of a growing number of producers around the world harnessing big data.  He began yield mapping in 2007, convinced that mapping offered “the quickest way to get a lot of data in order to move forward.”

He followed this with targeted soil sampling to determine a correlation between soil nutrient variability and yields.  He later began using a real-time sensor to apply in-crop nitrogen at varying rates based on the amounts of chlorophyll detected in the plants. 

Williamson further enhanced this picture by measuring the soil electrical conductivity to build prescription maps — a picture he has recently enhanced with pest, weed and yield data.

Virk says that the kind of refined farming pictures Williamson and other farmers around the world are compiling on the basis of farming data are destined to become even clearer in the future — not only clearer but better integrated.

“The next step will be a cloud-based system that integrates all facets of farming on behalf of producers,” he says.

2. Along with clarity comes diversity.

“The farming picture will not only become more refined but also more diverse,” says Fulton, who draws a comparison with the different ways individual homeowners manage their landscapes.

“Homeowners manage their yards very differently, but they’re getting the job done and all the yards look good,” he says.

“A similar trend will play out in row-crop farming,” he says. “The more farmers learn from their individual data streams, the more their individual farming practices will diverge, whether in terms of variety selection, seeding rates or whatever.

“Like homeowners, though, they will be getting the job done.”

3. Big data should be viewed as stored knowledge for lean times.

As Williamson sees it, his job as a farmer is to “convert energy generated by the sun into profitable crops.”

In a sense, a farming data stream should be viewed much the same way: As stored knowledge that can provide farmers with a clear, comprehensive picture of their farming operations — an especially valuable asset during down cycles, he says.

“If the cycle dips, we need to be on our game to make sure we’re doing the best we can when it’s difficult to make the margin,” Williamson says.

4. Big data is no substitute for farmer’s intuition.

Despite the promise of Big Data, Fulton stresses that the “number 1 data set will always be a farmer’s intuition.”

“There is no data more valuable than the insights a farmer has gained over 10, 20 or 30 years of experience,” he says. “The promise of big data will come from overlaying it with all the insights a farmer has gained through years of experience. 

Virk shares this view. In the end, farmers will always know more about their farming operations’ strengths and weaknesses than any software or machine, he says.

“The integrated farming picture that emerges from all these big data-related advances will ensure decision-making is easier, but in the final analysis the farmer’s intuition will still be the critical factor in all of this, he says.

5. Big data requires a mindset change.

Farmers are creatures of habit, Williamson says.  Most think that time spent in the field is more valuable than time invested peering into a computer screen.

Experience has taught him that time invested analyzing his farm data is just as important as time spent in the field.  Indeed, producers who opt to manage their own data rather than pay an analyst to do it should develop a new daily routine, he says.

“If you’re going to do it yourself, you had better be comfortable with spending more time on the computer,” he says.

According to Fulton, the big data revolution is also challenging Cooperative Extension to undertake its own transformation by developing an understanding of row-crop farming as a system of interrelated parts.

Much of the ACES crop team’s in-service training now emphasizes a multidisciplinary approach, underscoring how different disciplines — agronomy, economics, plant pathology and entomology, for example —comprise a comprehensive farming picture.

Fulton also believes Extension educators will serve a valuable role in the future showing producers how to make optimal use of their data stream by organizing it into a more seamless picture of their farming operation.

6. Big data will play a critical role in feeding the world.

Big data is gaining traction at an especially critical time in history as farmers gear up to feed an estimated 9 billion people by midcentury.

“This will require farmers to secure higher levels of production efficiency, and this can only be attained with more mechanization and other forms of technological adoption,” Fulton says.

Big data will fill much of this void by providing producers with a clearer understanding of how to match varieties to soil and climatic conditions along with strategies for reducing fertilizer, pesticide and herbicide applications, all with the aim of securing the highest levels of farming efficiency, he says.

7. Like it or not, big data is the new reality in farming.

While farmers will have some choices about how to participate in the coming big data revolution, they cannot afford the luxury of not participating, Fulton says.

“We’re already seeing new partnerships growing out of these changes at a steadily accelerating pace, and to be successful, farmers will need to be engaged with these emerging partnerships,” he says. “But it’s important that they ask the right questions before joining these partnerships and only partner with people and organizations that they trust.”


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k s sandhu    
india  |  September, 17, 2013 at 02:32 AM

No doubt, the farmers intuition generally over weighs,but it requires a lot of experience.The big data,on the other hand can be helpful to the next generation of the farmer,which can enable it to harvest the benefits of experiences of the previous generation(s) without exerting so much.In addition to this it will provide a strong platform to the researchers and extension scientists for drawing more reliable conclusions by integrating these data across the farmers,years and their crop cultivation practices.

Alexandra    
Syracuse, NY  |  September, 17, 2013 at 10:08 AM

I agree that intuition will be the number one resource for data, but I'm also excited to see how technology and farming can go hand in hand. There could be a great cross over with census data too to help project the market shifts that come with population changes as well. This kind of thinking can not only be geared towards higher yield, but tying in other big data for cross referencing projections of other kinds. Thanks for this article!


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