Article ID Journal Published Year Pages File Type
84821 Computers and Electronics in Agriculture 2011 7 Pages PDF
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.

Research highlights▶ Stress to wheat field induced by Diuraphis noxia can be detected using multispectral image data. ▶ Stress detected may be a mixture of several stress factors that can include D. noxia, drought, and agronomic conditions. ▶ Spatial pattern metrics generated from multispectral image data was used to quantify and differentiate the types of stress found in wheat fields.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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