AgTech, Sustainability

The Emergence of Artificial Intelligence in Agriculture

Amy Wu
5m

Anthem Ag is proud to highlight the work of Amy Wu of  From Farms to Incubators on a special series on AgTech and Artificial Intelligence in Agriculture

In California, the beige-colored landscape and brown hills speak volumes about the drought that continues to wreak havoc in the West. Signs reading “Pray for Rain” are commonly seen along the highways that ribbon through the region, including the Central Coast and Central Valley. The upside is that emerging AgTech innovations are rapidly helping to mitigate these difficult environments. Artificial intelligence in agriculture is a fast-emerging smart farming solution that is helping growers tackle farming challenges, including drought and increasing food production amidst unpredictable weather conditions.  

Artificial intelligence is often associated with self-driving cars and Poker playing computers, commonly referred to as AI Technology. Still, farming operations increasingly use it for crop and pest monitoring, predictive analytics, and overall water and farm management. When it comes to agricultural AI, which is an algorithm, it is often incorporated into existing innovations as an adaptation to this industry. 

For example, it may be part of a drone that takes aerial imaging of field crops to determine what percent are crops versus weeds. It may be incorporated into a machine that visually grades the quality of fruits and vegetables. Global tech companies such as IBM and academic institutions such as the University of California, Davis have entire divisions devoted to research related to AI and agriculture.  

“AI, I think it will become increasingly important in terms of enhanced functionality and ability to provide information,” says Dennis Donohue, executive director of the Western Growers Center for Innovation and Technology (WGCIT), noting that inflation and the supply chain bottlenecks on top of existing farming challenges mean that “AI is increasingly a part of the equation.”  

Precision Agriculture and Smart Farming 

GeoVisual Analytics is an ag-tech company that uses computer vision, AI and machine learning, and remote sensing capabilities to help its customers in agribusiness. The company, whose moniker is “Artificial Intelligence for Better Harvests,” uses drones, mobile phones, and airplanes that monitor fields and communicate field data in real-time. Aerial imagery shows the overall crop health and can spot plant diseases, and the data from the imagery can help farmers make more intelligent decisions and create sustainable models.   

“The big issues are labor and water when it comes to agriculture,” says Jeff Orrey, the Chief Science Officer at GeoVisual. AI enables farmers to make “more efficient use of all resources,” such as using nitrogen fertilizers. This boils down to increased efficiency and cost savings for farmers. This is essential for agriculture, as the inflation rate in the U.S. has hit the highest level in four decades; as a result, the cost of inputs such as gas for equipment, fertilizer, seeds, and pesticides has skyrocketed. The overall agriculture sector is looking towards automation as a solution to rising harvest costs caused by a severe labor shortage. The data GeoVisual collects from its customers helps the company create algorithms to serve growers better.  

“They (farmers) are also looking at automating thinning and weeding the crops, (and to do so) you must recognize the crop versus weed,” says Orrey. “That is what’s led to devices that are using computer vision and machine learning.”  

Since algorithms are built as a solution to the problem, it is essential to identify the problems.  

SWARM Engineering offers the Challenge Modeler a set of free templates to help farmers identify the specific pain points they are facing. The completed templates either go to SWARM for solutions that involve advanced AI and operational research algorithms, or the user can take it to their IT department, says Anthony Howcroft, the CEO and co-founder of SWARM.  

“What we have built is an engine that helps define the problem and uses a variety of algorithms to solve various food problems in the food supply chain, and almost everything in the food system chain is optimization,” he adds.  

The company’s mission statement includes “Democratizing AI.” In one case study, the question centers around how many animals from location X should we move to harvest facility Y? Another case study involves supply and demand. How to save costs if each purchase for commodity includes a spread of 40 plus grades of quality and there are varying logistic costs from each site. Howcroft asserts that the SAS platform has saved some clients millions of dollars.  

Growing a Better Vintage

While GeoVisual focuses on specialty crops for their value and SWARM has worked with grains and livestock, AI can be used across the board in all segments of agriculture, including vineyards.  

Ganesh Harinath, the founder and CEO of Fiducia, provides AI solutions to wineries. Harinath, who previously worked on AI as a chief technology manager at Verizon, has extended his skills and experience to agriculture. Harinath notes that computer vision can help determine how much irrigation is needed (areas that are overwatered and underwatered are marked), and drones can detect moisture content through aerial imaging.  

Specifically, Fiducia focuses on traceability in the wine industry by providing up-to-date information for consumers via QR codes. For example, wineries can connect with consumers through growers’ stories and provide up-to-date information on certifications and other pertinent data via a QR code. In another example, up-to-date information is communicated through a QR code on spinach bundles; if there is an outbreak of E. coli which the consumers learned from television, they can quickly scan the QR code and discard the spinach.  

Many in the agricultural industry have concluded that the benefits of AI in agriculture are manifold and will be increasingly woven into the food system to help farmers produce food for the growing international population. Now it is up to farmers to find ways to utilize the tool to their advantage.  

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