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Geographic Information System for Pigweed Distribution in the US Southeast

Published online by Cambridge University Press:  06 February 2018

Reginald S. Fletcher*
Affiliation:
Research Agronomist, US Department of Agriculture, Agricultural Research Service, Crop Production Systems Research Unit, P.O. Box 350, Stoneville, MS, USA
Krishna N. Reddy
Affiliation:
Research Plant Physiologist, US Department of Agriculture, Agricultural Research Service, Crop Production Systems Research Unit, P.O. Box 350, Stoneville, MS, USA
*
Author for correspondence: Reginald S. Fletcher, US Department of Agriculture, Agricultural Research Service, Crop Production Systems Research Unit, P.O. Box 350, Stoneville, MS 38776. (Email: reginald.fletcher@ars.usda.gov)

Abstract

In the southeastern United States, Amaranthus, or pigweed species, have become troublesome weeds in agricultural systems. To implement management strategies for the control of these species, agriculturalists need information on areas affected by pigweeds. Geographic information systems (GIS) afford users the ability to evaluate agricultural issues at local, county, state, national, and global levels. Also, they allow users to combine different layers of geographic information to help them develop strategic plans to solve problems. Furthermore, there is a growing interest in testing free and open-source GIS software for weed surveys. In this study, the free and open-source software QGIS was used to develop a geographic information database showing the distribution of pigweeds at the county level in the southeastern United States. The maps focused on the following pigweeds: Palmer amaranth, redroot pigweed, and tall waterhemp. Cultivated areas and glyphosate-resistant (GR) pigweed data were added to the GIS database. Database queries were used to demonstrate applications of the GIS for precision agriculture applications at the county level, such as tallying the number of counties affected by the pigweeds, identifying counties reporting GR pigweed, and identifying cultivated areas located in counties with GR pigweeds. This research demonstrated that free and open-source software such as QGIS has strong potential as a decision support tool, with implications for precision weed management at the county scale.

Type
Symposium
Copyright
© Weed Science Society of America, 2018 

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