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Spectral reflectance curves to distinguish soybean from common cocklebur (Xanthium strumarium) and sicklepod (Cassia obtusifolia) grown with varying soil moisture

Published online by Cambridge University Press:  20 January 2017

W. Brien Henry ,
David R. Shaw ,
Kambham R. Reddy ,
Lori M. Bruce  and
Hrishikesh D. Tamhankar
David R. Shaw
Affiliation:
Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS 39762
Kambham R. Reddy
Affiliation:
Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS 39762
Lori M. Bruce
Affiliation:
Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762
Hrishikesh D. Tamhankar
Affiliation:
Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762
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Abstract

Experiments were conducted to examine the use of spectral reflectance curves for discriminating between plant species across moisture levels. Weed species and soybean were grown at three moisture levels, and spectral reflectance data and leaf water potential were collected every other day after the imposition of moisture stress at 8 wk after planting. Moisture stress did not reduce the ability to discriminate between species. As moisture stress increased, it became easier to distinguish between species, regardless of analysis technique. Signature amplitudes of the top five bands, discrete wavelet transforms, and multiple indices were promising analysis techniques. Discriminant models created from data set of 1 yr and validated on additional data sets provided, on average, approximately 80% accurate classification among weeds and crop. This suggests that these models are relatively robust and could potentially be used across environmental conditions in field scenarios.

Keywords

Soybean, Glycine max (L.) MerrLeaf water potentialspectral reflectance curvesNDVIRVISAVIDVINDVIgIPVIMSI
Type
Weed Management
Information
Weed Science , Volume 52 , Issue 5 , October 2004 , pp. 788 - 796
Copyright
Copyright © Weed Science Society of America 

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