Data-Driven Food Processing Extends to the Farm

Just like their food processing counterparts, U.S. food farmers are using data-based decisions to maximize production and increase profitability.

Robotic cucumber harvester. Source: www.ieee-ras.org
Robotic cucumber harvester. Source: www.ieee-ras.org

Smart machines, real-time communication, integrated networks, big data, high-speed processing—these technological advances sound familiar to today’s food & beverage processors, who are in the midst of transforming their manual and isolated operations to better compete on a global scale. But I bet you didn’t know that automation also is infiltrating food growing counterparts around the world—commercial farms, orchards, hatcheries, and the like. There are lessons to be learned from these efforts, because automating factories is actually easier than automating farms.

A 2009 article in The Economist (“Fields of Automation”) explained the challenges; namely, “far less predictable environments: the weather constantly changes, the light alters, the ground can turn from grass to mud, and there are animals and people wandering around. Moreover, unlike car parts, fruit does not come in standard sizes. It moves around on branches in the wind, changes shape and colour, and can be hidden by leaves. But improvements in vision and other sensing systems, coupled with the increase in the power of computing, have made robots cleverer, safer and more dexterous.”

The mechanical reaper transformed wheat threshing in the early 1800s, and GPS- and vision-based self-guided tractors and harvesters are available commercially today. So mechanical advances, even in the form of robots, are not new to agriculture. What is new in this new millennium is interest in the same data-driven technology that is transforming industrial operations.

“Technology advancements are making it possible for farmers, farm-equipment manufacturers or suppliers of feedstock (seeds, fertilizers, crop protection products) to gather data from a wide variety of sources, analyze it in the moment and use it to make critical business decisions and operational adjustments,” says Stefan Guertzgen, senior director of global industry marketing for chemicals at enterprise software vendor SAP. “Hence, collaborative data sharing, analysis and federation across such a networked ecosystem would benefit all stakeholders.”

Data is the Changing Face of Farming

Like industrial-scale food processing plants, most agriculture operations are highly complex mega-farm operations, either physically existing or digitally combined multi-site conglomerates, with extensive distribution networks and supply chains. “To survive against global competition these businesses must use their resources wisely and streamline the production process. They are constantly looking for ways to get better yields from less acreage and minimize the effects of rising costs in areas such as labor, equipment, land, and fuel,” says Guertzgen.

As with industry, other factors adding to the complexity of farm operations include highly volatile markets, less predictable conditions (in this case, climate) and increasing regulatory requirements.

“For these reasons and more, agriculture organizations are starting to take a data-driven approach to farming known as precision farming,” says Guertzgen. “Precision farming is a technology-based method of using data to make decisions that optimize overall farming practices, resources and yields.”

As agriculture has become more sophisticated, Guertzgen says, the amount of available data is growing exponentially. More information is available than ever before and it is coming at farmers from many different sources including smart machines, chemical companies, weather stations, laboratories and supply chain partners.

“In fact, it is estimated that more than 40 different variables are taken into account when estimating potential farm yield and productivity, such as variability in soil, weather, drainage patterns, etc. However, simply capturing and accessing the available information is not enough. The real value of data is uncovered when it is analyzed, shared and used to take meaningful action, says Guertzgen.

Turning Data into Decisions

Perhaps surprisingly, farmers are not reluctant adopters of technology, says Guertzgen. “Technology is turning the fields into a virtual mobile office, giving decision makers access to key farming parameters when it is needed most. Mobile devices, smart machines, high-speed processing capabilities, cloud computing and integrated networks empower modern and profit-oriented farmers to access information from any location, analyze it, share it and use it in the moment to make insightful decisions,” he says. For example, farmers are using data to know which types of seeds will work best in certain fields, how to prepare for predicted weather events, or add the exact amount of additional fertilizer to a specific crop.

In addition to enabling data-based decisions for optimizing land yield and productivity, technology also is changing farm communication and operations. Network systems and databases can be integrated and standardized, so farmers can quickly share information with key global players during planning, planting, in-season and harvesting. Additionally, access to farming related data in real-time is allowing suppliers to develop differentiated services that give famers a competitive advantage.

More specifically, says Guertzgen, technology is being used to:

Improve collaboration with vendors and suppliers. “From equipment makers, chemical manufactures, fertilizer and seed producers, to farm retailers, integrated technology systems facilitate an important exchange of data for more precision and transparent farming.”

Enable real-time, on-site communication. “Using various types of mobile devices, farmers can collect soil samples, analyze it while in the field, instantly share the information and discuss the results in real-time with agronomic advisors.”

Model and simulate results. “Powerful technology platforms can use vast amounts of historic and predicted data to create useful models and simulations for protecting crops from weather or understanding the possible impacts of planting decisions.”

Leverage best practices. “Planting the wrong crop, using the wrong supplier or improper maintenance on a piece of equipment can all lead to devastating consequences. Using technology to connect to the global farming community allows farmers to implement best practices.”

As for the “agribots”—which is what The Economist called the robotic technology making its way to farms—they are helping to increase efficiency and reduce the cost of production. According to the IEEE Robotics & Automation Society (RAS), farmers have started to experiment with autonomous systems that automate or augment operations such as pruning, thinning and harvesting, as well as mowing, spraying and weed removal.

“In the fruit tree industry, workers riding robotic platforms have shown to be twice as efficient as workers using ladders,” says the RAS. “Advances in sensors and control systems allow for optimal resource [management,] and integrated pest and disease management.”

Guertzgen says, “Farmers are acting more like entrepreneurs every day, looking to get the most from each investment and optimize ever acre. Their success, as well as the world’s ability to meet the projected food consumption needs, will be closely tied to the sophisticated analysis and use of data.” He cites the International Food and Policy Research Institute, which predicts “agricultural technologies could increase global crop yields as much as 67 percent, and cut food prices nearly in half by 2050,” (http://awgo.to/411).

The same increased productivity and streamlining of operations could be in the future for technology-savvy food manufacturers as well. The ability to aggregate and use data from many different sources will transform both industries, letting “plant managers” of all types make smarter, more insightful decisions.

Companies in this article
More in IIoT