Published on May 14th, 2019 | by Emergent Enterprise0
Machine Vision is the Newest Weapon Against Crop Loss
The world needs more food and more efficient ways to grow it. As Greg Nichols reports at ZDNet, machine learning and other combined technologies can work towards that goal by analyzing crops and weeds and guiding growers to optimal herbicide or pesticide application. It will also require less of these toxic chemicals which is good for the environment.
Like Terminator for weeds, precision ag combines computer vision, robots, and AI to get crops right.
Crop loss is devastating for farmers. With increasing ecological volatility, it’s also a fact of life.
But a host of new techniques known collectively as “precision agriculture” or “agricultural intelligence” can help. One company, Taranis, just unveiled a novel weed identification system that combines computer vision, satellite and drone imagery, and AI to tell farmers what kinds of weeds are attacking their crops in real time, empowering the farmers to fight back.
The scope of the global crop loss problem is staggering. Worldwide, farmers lose about $750B from crop loss each year. About a third of all food grown is lost.
For decades the solution has been heavy herbicide use. But there are over 8,000 species of weeds. Rather than target one offending species, farmers have often had no choice but use large doses of weed killer. As a result, herbicide and pesticide resistance is currently costing the industry something like $10 billion a year in the US alone.
Companies like Taranis, founded in 201, are capitalizing on advances in computer vision, machine learning, and commercial drone technology, and they’re coming up with novel solutions to help.
“With our team of 120 expert agronomists continuously training our AI Data Sets, Taranis now has the most comprehensive weed identification system of its kind,” said Ofir Schlam, CEO and Co-founder of Taranis. “We are making it easier than ever for farmers to identify thousands of weeds, furthering our mission to enable service providers, land managers, and producers to pre-emptively combat crop yield loss due to weeds, insects, disease, and more.”
Taranis’s platform starts with imagery collected from satellites, planes, and drones, providing three distinct resolution scales to mine data from. The combines combines the field imagery and is using AI deep learning technology to recognize crop health issues.