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Is Big Data The Next Industrial Revolution In Farming?

Is data sparking a new era in agricultural productivity?

16Sep

The introduction of tractors to replace horses saw farming transform from a local, almost subsistence industry, to a mass market business. It allowed farmers to farm many times more land than they would have previously been able to and crop yields expanded as a result.

Today’s farmers may well have hit upon the next big revolution in farming, the element that will change the way food and crops are grown forever: Big Data.

The impacts of using data on farms has already had considerable impacts on the bottom lines of an industry that has historically tight margins. For instance, those who have adopted new data driven techniques have found their input costs reduced by 15% and their yields increase by 13%. When you consider that margins are so slim, it means that the work becomes considerably more profitable and worthwhile for the farmer.

Data is gathered from tractors and other modern farm equipment, almost all of which is equipped with sensors to help collect the relevant data. This data can then be used in real-time to help create environments where more money can be made and more crops can be grown. GPS tracking has a considerable bearing on data collection and helping to make sure that seeds are distributed effectively and evenly.

Business Insider spoke to Brian Marshall, a farmer from Missouri, who said that in addition to the myriad of computers in his tractor cab, he can take an iPad out of the tractor and identify where a seed may have been missed on the field and plant it by hand. It means complete coverage and less wasted land. In fact to help with this, tractors even utilize GPS to drive themselves, which are accurate to within an inch, meaning that human error when driving is also eliminated.

All of the data from planting, harvesting and maintaining crops is then held on servers and analyzed. This means that farmers can know what works and what doesn’t in particular areas, then plant and harvest accordingly.

The real power of this data may not be from the way that individual farmers utilize and analyze it though, instead through collecting this kind of data from thousands of farms and millions of hectares of land, it is possible to create models that can analyze down to a macro level. This can be taken from millions of use cases and huge amounts of data, meaning unprecedented accuracy.

Many people would question how much data a farm could really have, but Monsanto (one of the biggest agricultural companies in the world) claim that 7 gigabytes of data is collected from each acre of farmed land. This would mean that in the US alone there would be 620 Petabytes available about specific crops, soil types and growing conditions. Having the ability to build models around this data could see crop yields across the entire country increase, which at a time when pressure is on governments to allay growing fears about the amounts of food being produced, is significant.

The challenge to making this system work is the farmers themselves, who are quite rightly reluctant to hand over data to competitors when they are trying to sell the same product. This is combined with a distrust of what large companies are going to do with their data and what they will ultimately end up doing with it. Essentially, if the company ends up making a powerful analytics model to help farmers maximize profits, then they will essentially need to buy back something that their data has been used to create.

Overcoming this hurdle is going to be the major challenge for large agriculture companies, but the potential benefits of this being so important for the world, it is vital that they can demonstrate that they are willing to allay the fears of farmers for the greater good of agriculture. 

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