Development of a method using multispectral imagery and spatial pattern metrics to quantify stress to wheat fields caused by Diuraphis noxia
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.
multispectral image spatial pattern metrics diuraphis noxia plant stress remote sensing