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1 January 2018 Geographic Information System for Pigweed Distribution in the US Southeast
Reginald S. Fletcher, Krishna N. Reddy
Author Affiliations +
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.

Nomenclature: Palmer amaranth, Amaranthus palmeri S. Wats. AMAPA; pigweeds, Amaranthus spp.; redroot pigweed, Amaranthus retroflexus L. AMARE; tall waterhemp, Amaranthus tuberculatus (Moq.) Sauer AMATU

© Weed Science Society of America, 2018.
Reginald S. Fletcher and Krishna N. Reddy "Geographic Information System for Pigweed Distribution in the US Southeast," Weed Technology 32(1), 20-26, (1 January 2018). https://doi.org/10.1017/wet.2017.118
Received: 13 October 2017; Accepted: 1 December 2017; Published: 1 January 2018
KEYWORDS
freeware
National Agricultural Statistics Data
open-source software
QGIS
surveys
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