ARS | Publication request: Development of a method using multispectral imagery and spatial pattern metrics to quantify stress to wheat fields caused by Diuraphis noxia

Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 15, 2010
Publication Date: January 10, 2011
Citation: Backoulou, G., Elliott, N.C., Giles, K., Phoofolo, M., Catana, V. 2011. Development of a method using multispectral imagery and spatial pattern metrics to quantify stress to wheat fields caused by Diuraphis noxia. Computers and Electronics in Agriculture. 75:64-70.

Interpretive Summary: The Russian wheat aphid is an important pest of winter wheat and barley that has caused an annual economic loss estimated at over 1 billion dollars since it first appeared in the United States. The objective of this study was to determine the potential of combining multispectral imagery with spatial pattern recognition to identify and spatially differentiate infestations in wheat fields. Multispectral images were acquired using a multispectral camera mounted in a fixed wing aircraft. Russian wheat aphid injury, drought, and agronomic conditions were identified as major causes of stress in wheat fields. Seven statistics were computed for each stress factor. The analysis of the statistics quantitatively differentiated the three types of stress. Detection and differentiation of wheat field stress may help in mapping stress and may have implications for site specific monitoring systems to identify Russian wheat aphid infestations and help to target pesticide applications. The importance of this research was in developing a method by which the cause of stress detected in multispectral imagery could be determined.

Technical Abstract: The Russian wheat aphid, Diuraphis noxia, is an important pest of winter wheat, Triticum aestivum, and barley, Hordeum vulgare that has caused an annual economic loss estimated at over 1 billion dollars since it first appeared in the United States. The objective of this study was to determine the potential of combining multispectral imagery with spatial pattern recognition to identify and spatially differentiate D. noxia infestations in wheat fields. Multispectral images were acquired using an MS3100-CIR multispectral camera. D. noxia, drought, and agronomic conditions were identified as major causes for stresses found in wheat fields. Seven spatial metrics were computed for each stress factor. The analysis of spatial metrics quantitatively differentiated the three types of stress found within wheat fields. Detection and differentiation of wheat field stress may help in mapping stress and may have implications for site specific monitoring systems to identify D. noxia infestations and help to target pesticide applications.