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Papers by KR Reddy
Weed Technology, 2004
Two experiments, one focusing on preemergence (PRE) herbicides and the other on postemergence (PO... more Two experiments, one focusing on preemergence (PRE) herbicides and the other on postemergence (POST) herbicides, were conducted and repeated in time to examine the utility of hyperspectral remote sensing data for discriminating common cocklebur, hemp sesbania, pitted morningglory, sicklepod, and soybean after PRE and POST herbicide application. Discriminant models were created from combinations of multiple indices. The model created from the second experimental run's data set and validated on the first experimental run's data provided an average of 97% correct classification of soybean and an overall average classification accuracy of 65% for all species. These data suggest that these models are relatively robust and could potentially be used across a wide range of herbicide applications in field scenarios. From the data set pooled across time and experiment types, a single discriminant model was created with multiple indices that discriminated soybean from weeds 88%, on ave...
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Field Crops Research, 2005
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Environmental and Experimental Botany, 2007
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Agriculture, Ecosystems & Environment, 1995
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Annals of Botany, 2004
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Journal of New Seeds, 2007
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Agronomy Journal, 2004
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Agronomy Journal, 2012
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Weed Technology, 2004
Two experiments, one focusing on preemergence (PRE) herbicides and the other on postemergence (PO... more Two experiments, one focusing on preemergence (PRE) herbicides and the other on postemergence (POST) herbicides, were conducted and repeated in time to examine the utility of hyperspectral remote sensing data for discriminating common cocklebur, hemp sesbania, pitted morningglory, sicklepod, and soybean after PRE and POST herbicide application. Discriminant models were created from combinations of multiple indices. The model created from the second experimental run's data set and validated on the first experimental run's data provided an average of 97% correct classification of soybean and an overall average classification accuracy of 65% for all species. These data suggest that these models are relatively robust and could potentially be used across a wide range of herbicide applications in field scenarios. From the data set pooled across time and experiment types, a single discriminant model was created with multiple indices that discriminated soybean from weeds 88%, on ave...
Bookmarks Related papers MentionsView impact
Field Crops Research, 2005
Bookmarks Related papers MentionsView impact
Environmental and Experimental Botany, 2007
Bookmarks Related papers MentionsView impact
Agriculture, Ecosystems & Environment, 1995
Bookmarks Related papers MentionsView impact
Annals of Botany, 2004
Bookmarks Related papers MentionsView impact
Journal of New Seeds, 2007
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Agronomy Journal, 2004
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Agronomy Journal, 2012
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