Harvesting Data to Maximize Crop Yields
By Alfredo Patron, executive vice president of business development, TeamViewer
Special to The Digest
In 1850, approximately six out of every ten Americans worked in agriculture,1 much of it for their own consumption. During that era, even people holding other jobs understood just about everything that had to do with farming. Food products sold from stores and carts looked pretty much the same way they did when they were raised or grown on the farm — not the carefully sanitized, processed, de-boned, shrink-wrapped, and bar-coded products we’re accustomed to now.
Today, agriculture represents just three percent of the American workforce. And the understanding of how farming works is embarrassingly meager among the nation’s urban dwellers — a population whose impressions of farms come from a combination of TV commercials featuring 1940s-era pickup trucks and popular children’s songs. So, for many, it may come as a surprise to learn that the agricultural industry, despite its sharp decline in employment, has become one of the most productive, most data-driven segments of our economy.
At least partly due to the chronic shortage of farm labor, agriculture is evolving into a far more capital-intensive industry with sophisticated equipment replacing and augmenting much of what had been previously done by individual workers in order to scale up in size. The capital requirements associated with successful operations have led to many small family farms consolidating into much larger corporate ones. The results? A combination of advanced and often pricey technologies that are reshaping the industry with smart farms, using precision agriculture to enhance crop yields.
These advances in agricultural technology are actually quite timely because the need to increase crop production is real and ongoing. According to the U.N. Food and Agricultural Organization, food production worldwide will need to increase by another 70 percent over the next few decades just to feed the global population, which is expected to reach 11.2 billion by 2050.2
To date, there are no commercial farms run entirely by autonomous machinery. However, prototypes of different automated farm equipment have been under development for several years now.
- Self-driving tractors are among the early candidates for automation, featuring GPS navigation, IoT connectivity for remote monitoring, and radar for object detection. Other developers, however, are looking to make the implements pulled by those tractors — tillers, spreaders, rakes, and so on — self-propelled, eliminating the need for conventional or even unconventional tractors.
- Seeding — which requires planting to precise soil depths as well as appropriate spacing between plants — is another candidate for automation. Combining geo-mapping with sensor data about soil qualities (i.e., acidity, density, moisture, and nutrient levels) can give high-tech seeding equipment the information required to optimize growth.
- Watering and irrigation systems, informed by IoT sensors installed at different field locations to measure moisture levels, are being coupled with popular drip irrigation systems to protect crop health and conserve water.
- Weeding and pest control are also well-suited for automation. Cameras and sensors — combined with machine learning and artificial intelligence — are being integrated into self-propelled robotic devices. This helps protect crop health by distinguishing weeds from crops as well as insect pests from pollinating insects.
- Harvesting crops presents a particular challenge because the window for completing a harvest is usually very limited, and weather conditions can affect the progress. However, engineers are working on specialty harvesters to overcome those challenges. Panasonic, for example, has created a tomato-picking robot outfitted with sophisticated cameras and software to identify a tomato’s ripeness by its color, shape, and location.
- Drones are also being used to assess crop health, soil quality, and planting locations. Some are being tested with spray and planting attachments to distribute nutrients and seeds from the air.
- Sensor systems can be installed in silos and grain elevators to alert farmers of moisture and heat issues that could damage stored crops.
Indeed, essentially every element of the agriculture value chain is now being seen as attractive business opportunities by startup technology companies, established farm equipment producers, and innovative partnerships, among others. Although the fruits of some of the more visionary robotic projects may not ripen until well into the future, the current generation of equipment is already being adapted to support smart farming initiatives.
Specialized farm software is widely available from different vendors to fine-tune applications of key agricultural commodities using data from strategically located, wirelessly connected digital sensors. They include programs to manage the timing, volume, and placement of seed, fertilizer, water, and other materials needed to optimize plant growth. That data can also be used to generate yield predictions.
However, nobody currently offers an all-inclusive solution. Different elements of smart farm technology — innovative platforms integrated into industrial hardware components from sensors to irrigation systems to actual farming trucks — are the outcome of formal partnerships and product integrations. These solutions put into action can help remote assist and remote operate a global farming operation reducing downtime, finding efficiencies on how to deploy and use resources and get a higher output.
Any technical issues that arise can be monitored, controlled, and handled by specialists — even if they’re hundreds of miles away — through remote access and control technology. The resulting harvest of high-value farm information is being translated into an abundance of healthy foods — all while making the best, most efficient use of available resources.
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Category: Top Stories, Thought Leadership
