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Automated Image Processing Could Aid Crop Evals

Automated Image Processing Could Aid Crop Evals

By Scott Schrage

Sunlight allows crops to engage photosynthesis and produce the yields that become food, feed, fiber and fuel.

That light gets captured by leaves. More upright leaves allow plants to use light more efficiently while casting less shade on neighbors, allowing growers to fit more plants into a field. Leaf angles also change when crops are deprived of water, making them a useful telltale for comparing how genetic lines respond to drought.

Unfortunately, measuring leaf angles is labor-intensive and time-consuming. Though automated systems exist, most work best in chambers that fail to mimic field conditions.

Nebraska's James Schnable and colleagues developed an image-processing framework, Leaf Angle eXtractor, that quantifies leaf angles from time-lapse photography of plants. Experiments with corn and sorghum plants showed that Leaf Angle eXtractor could discern minute-to-minute shifts in individual leaves—even from medium-resolution photos—that corresponded with rolling, wilting and other common signs of water deprivation.

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Border View Farms is a mid-sized family farm that sits on the Ohio-Michigan border. My name is Nathan. I make and edit all of the videos posted here. I farm with my dad, Mark and uncle, Phil. We also have a part-time employee, Brock. My dad started the farm in 1980. Since then we have grown the operation from just a couple hundred acres to over 3,000. Watch my 500th video for a history of our farm I filmed with my dad.

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