Assessment of soybean injury from glyphosate using airborne multispectral remote sensing
Article first published online: 27 JUN 2014
Published 2014. This article is a U.S. Government work and is in the public domain in the USA.
Pest Management Science
Volume 71, Issue 4, pages 545–552, April 2015
How to Cite
Huang, Y., Reddy, K. N., Thomson, S. J. and Yao, H. (2015), Assessment of soybean injury from glyphosate using airborne multispectral remote sensing. Pest. Manag. Sci., 71: 545–552. doi: 10.1002/ps.3839
- Issue published online: 12 MAR 2015
- Article first published online: 27 JUN 2014
- Accepted manuscript online: 29 MAY 2014 03:46AM EST
- Manuscript Accepted: 24 MAY 2014
- Manuscript Revised: 20 MAY 2014
- Manuscript Received: 28 OCT 2013
- crop injury;
- biological response;
- remote sensing;
- vegetation index
Glyphosate drift onto off-target sensitive crops can reduce growth and yield and is of great concern to growers and pesticide applicators. Detection of herbicide injury using biological responses is tedious, so more convenient and rapid detection methods are needed. The objective of this research was to determine the effects of glyphosate on biological responses of non-glyphosate-resistant (non-GR) soybean and to correlate vegetation indices (VIs) derived from aerial multispectral imagery.
Plant height, shoot dry weight and chlorophyll (CHL) content decreased gradually with increasing glyphosate rate, regardless of weeks after application (WAA). Accordingly, soybean yield decreased by 25% with increased rate from 0 to 0.866 kg AI ha−1. Similarly to biological responses, the VIs derived from aerial imagery – normalized difference vegetation index, soil adjusted vegetation index, ratio vegetation index and green NDVI – also decreased gradually with increasing glyphosate rate, regardless of WAA.
The VIs were highly correlated with plant height and yield but poorly correlated with CHL, regardless of WAA. This indicated that indices could be used to determine soybean injury from glyphosate, as indicated by the difference in plant height, and to predict the yield reduction due to crop injury from glyphosate. Published2014.Thisarticle is a U.S.Government work and is in the public domainin the USA.