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	<title>UAS &#8211; BIOENGINEER.ORG</title>
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		<title>Drone Data Reveals the Critical Wheat Growth Window That Predicts Yield</title>
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		<pubDate>Tue, 06 Oct 2026 19:24:05 +0000</pubDate>
				<category><![CDATA[Agriculture]]></category>
		<category><![CDATA[drones]]></category>
		<category><![CDATA[Explainable AI]]></category>
		<category><![CDATA[high-throughput phenotyping]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[NDVI]]></category>
		<category><![CDATA[phenology]]></category>
		<category><![CDATA[plant breeding]]></category>
		<category><![CDATA[precision agriculture]]></category>
		<category><![CDATA[UAS]]></category>
		<category><![CDATA[vegetation indices]]></category>
		<category><![CDATA[wheat]]></category>
		<category><![CDATA[yield prediction]]></category>
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					<description><![CDATA[A multi-year Texas study combining drone imaging, machine learning, and explainable AI shows that wheat yield is best predicted from spectral data collected in a narrow window around heading, allowing breeders to slash flight frequency without losing accuracy.]]></description>
		
		
		
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