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Using remote sensing for identification of late-season grass weed patches in wheat

Published online by Cambridge University Press:  20 January 2017

Francisca López-Granados ,
Montse Jurado-Expósito ,
Jose M. Peña-Barragán  and
Luis García-Torres
Francisca López-Granados
Affiliation:
Institute for Sustainable Agriculture, CSIC, Apartado 4084,14080 Cordoba, Spain
Montse Jurado-Expósito
Affiliation:
Institute for Sustainable Agriculture, CSIC, Apartado 4084,14080 Cordoba, Spain
Jose M. Peña-Barragán
Affiliation:
Institute for Sustainable Agriculture, CSIC, Apartado 4084,14080 Cordoba, Spain
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Abstract

Field research was conducted to determine the potential of hyperspectral and multispectral imagery for late-season discrimination and mapping of grass weed infestations in wheat. Differences in reflectance between weed-free wheat and wild oat, canarygrass, and ryegrass were statistically significant in most 25-nm-wide wavebands in the 400- and 900-nm spectrum, mainly due to their differential maturation. Visible (blue, B; green, G; red, R) and near infrared (NIR) wavebands and five vegetation indices: Normalized Difference Vegetation Index (NDVI), Ratio Vegetation Index (RVI), R/B, NIR-R and (R − G)/(R + G), showed potential for discriminating grass weeds and wheat. The efficiency of these wavebands and indices were studied by using color and color-infrared aerial images taken over three naturally infested fields. In StaCruz, areas infested with wild oat and canarygrass patches were discriminated using the indices R, NIR, and NDVI with overall accuracies (OA) of 0.85 to 0.90. In Florida–West, areas infested with wild oat, canarygrass, and ryegrass were discriminated with OA from 0.85 to 0.89. In Florida–East, for the discrimination of the areas infested with wild oat patches, visible wavebands and several vegetation indices provided OA of 0.87 to 0.96. Estimated grass weed area ranged from 56 to 71%, 43 to 47%, and 69 to 80% of the field in the three locations, respectively, with per-class accuracies from 0.87 to 0.94. NDVI was the most efficient vegetation index, with a highly accurate performance in all locations. Our results suggest that mapping grass weed patches in wheat is feasible with high-resolution satellite imagery or aerial photography acquired 2 to 3 wk before crop senescence.

Keywords

Wild oat (Avena fatua L. AVEFA and A. sterilis L. AVEST)canarygrass (Phalaris paradoxa L. PHAPA and P. minor Retz PHAMI)ryegrass, Lolium rigidum Gaudin LOLRIwheat, Triticum durum L. ‘Mexicali.’Hyperspectralmultispectralsite-specific weed managementvegetation indices
Type
Weed Management
Information
Weed Science , Volume 54 , Issue 2 , April 2006 , pp. 346 - 353
Copyright
Copyright © Weed Science Society of America 

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