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Using remote sensing to detect weed infestations in Glycine max

Published online by Cambridge University Press:  20 January 2017

Case R. Medlin ,
David R. Shaw ,
Patrick D. Gerard  and
Falba E. LaMastus
Case R. Medlin
Affiliation:
Department of Plant and Soil Sciences, 117 Dorman Hall, Box 9555, Mississippi State University, Mississippi State, MS 39762
Patrick D. Gerard
Affiliation:
Experimental Statistics, 151 Dorman Hall, Box 9653, Mississippi State University, Mississippi State, MS 39762-9653
Falba E. LaMastus
Affiliation:
Department of Plant and Soil Sciences, 117 Dorman Hall, Box 9555, Mississippi State University, Mississippi State, MS 39762
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Abstract

The objective of this research was to evaluate the accuracy of remote sensing for detecting weed infestation levels during early-season Glycine max production. Weed population estimates were collected from two G. max fields approximately 8 wk after planting during summer 1998. Seedling weed populations were sampled using a regular grid coordinate system on a 10- by 10-m grid. Two days later, multispectral digital images of the fields were recorded. Generally, infestations of Senna obtusifolia, Ipomoea lacunosa, and Solanum carolinense could be detected with remote sensing with at least 75% accuracy. Threshold populations of 10 or more S. obtusifolia or I. lacunosa plants m−2 were generally classified with at least 85% accuracy. Discriminant analysis functions formed for detecting weed populations in one field were at least 73% accurate in identifying S. obtusifolia and I. lacunosa infestations in independently collected data from another field. Due to highly variable soil conditions and their effects on the reflectance properties of the surrounding soil and vegetation, accurate classification of weed-free areas was generally much lower. Current remote sensing technology has potential for in-season weed detection; however, further advancements of the technology are needed to insure its use in future prescription weed management systems.

Keywords

Ipomoea lacunosa L. IPOLA, pitted morningglorySenna obtusifolia (L.) Irwin et Barnaby CASOB, sicklepodSolanum carolinense L. SOLCA, horsenettleGlycine max (L.) Merr., soybeanPrecision farmingsite-specific agriculturevariable-rate application
Type
Research Article
Information
Weed Science , Volume 48 , Issue 3 , June 2000 , pp. 393 - 398
Copyright
Copyright © Weed Science Society of America 

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Footnotes

Current address: Department of Botany and Plant Pathology, 1155 Lilly Hall, West Lafayette, IN 47907-1155

References

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