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        <identifier>oai:figshare.com:article/33951331</identifier>
        <datestamp>2026-09-21T15:32:49Z</datestamp>
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          <dc:title>Hyperspectral profiles of wild oat (&lt;em&gt;Avena fatua&lt;/em&gt; L.) inbred lines</dc:title>
          <dc:creator>Connor Nelle (25081786)</dc:creator>
          <dc:creator>Barbara Keith (22908770)</dc:creator>
          <dc:creator>Lucas Wright (25081789)</dc:creator>
          <dc:creator>Wyatt Medina (25081792)</dc:creator>
          <dc:creator>Justin Vetch (25081795)</dc:creator>
          <dc:creator>Timothy Seipel (25081798)</dc:creator>
          <dc:creator>William Dyer (25081801)</dc:creator>
          <dc:creator>Paul Nugent (25081804)</dc:creator>
          <dc:creator>Jennifer Lachowiec (23927328)</dc:creator>
          <dc:subject>Agricultural, veterinary and food sciences</dc:subject>
          <dc:subject>Weeds</dc:subject>
          <dc:subject>Herbicides</dc:subject>
          <dc:subject>Remote sensing</dc:subject>
          <dc:subject>Avena fatua</dc:subject>
          <dc:subject>unoccupied aerial system</dc:subject>
          <dc:subject>Hyperspectral imaging</dc:subject>
          <dc:subject>Agricultural sciences</dc:subject>
          <dc:description>&lt;p&gt;This dataset consists of processed hyperspectral datacubes of inbred&lt;em&gt; &lt;/em&gt;lines &lt;em&gt;Avena fatua&lt;/em&gt; L. (wild oats) that varied in herbicide resistance. Hyperspectral reflectance data was collected on single leaves in the greenhouse using a moving stage and on whole plants in the field using an airborne sensor. Two separate pipelines were devised to extract and process plant spectra from the benchtop and airborne datasets respectively. Greenhouse and field data were aligned to a single reference spectra to enable comparison. Processed datacubes were used to explore the performance of machine learning models to classify lines for herbicide resistance. This dataset is a valuable resource for training models to both classify wild oat for herbicide resistance and generally distinguish weeds from background pixels.&lt;/p&gt;</dc:description>
          <dc:date>2026-08-29T00:00:00Z</dc:date>
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          <dc:identifier>10.5061/dryad.vdncjszbg</dc:identifier>
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