Computer Imaging For Early Detection of Greenhouse Diseases
Ecoation’s software learns what a healthy leaf looks like and will detect and mark any leaf that doesn’t meet that criteria. Photo: ecoation
While imaging has been widely adopted in the leafy greens sector, producers growing ornamentals, tomatoes, cucumbers, peppers, and strawberries are also bringing this technology into the greenhouse, writes Andy Wilcox at Greenhouse Grower.
If an experienced grower has one plant in front of them, and their mission is to grow that one plant well, they don’t need imaging to do that. But what about when they have 10 million plants?
Adam Greenberg, CEO of IUNU, explains that imaging and AI is really about helping the grower scale how they already know to grow. The idea is to take established processes and equipment from other areas and adapt them to controlled-environment agriculture (CEA), providing a usable tool to the grower.
“We are bringing widely-used technology from other industries, computer vision, and machine learning, into the greenhouse,” says Mauricio Manotas, Chief Revenue Officer at Ecoation.
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What it means is a big step forward for growers. Computer vision and AI are proving themselves as valuable tools in many areas of CEA, particularly for the early detection of pests and diseases.
Read more at Greenhouse Grower.
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