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		<title>AI Reads Sugarcane Stalks to Measure Hidden Insect Damage</title>
		<link>https://bioengineer.org/ai-reads-sugarcane-stalks-to-measure-hidden-insect-damage/</link>
		
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		<pubDate>Wed, 07 Oct 2026 13:32:41 +0000</pubDate>
				<category><![CDATA[Agriculture]]></category>
		<category><![CDATA[convolutional neural networks]]></category>
		<category><![CDATA[crop pests]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[Diatraea saccharalis]]></category>
		<category><![CDATA[economic injury level]]></category>
		<category><![CDATA[image segmentation]]></category>
		<category><![CDATA[injury severity]]></category>
		<category><![CDATA[integrated pest management]]></category>
		<category><![CDATA[precision agriculture]]></category>
		<category><![CDATA[Sphenophorus levis]]></category>
		<category><![CDATA[sugarcane]]></category>
		<category><![CDATA[YOLOv11]]></category>
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					<description><![CDATA[Brazilian researchers used a YOLO-based deep learning model to quantify internal insect injury in sugarcane stalks, showing that continuous injury severity, not mere pest presence, predicts measurable losses in stalk weight, height and internode number.]]></description>
		
		
		
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