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Research Project: Aerial Application Technology for Sustainable Crop Production

Location: Aerial Application Technology Research

Title: Using airborne imagery to monitor cotton root rot infection before and after fungicide treatment

Author
item Yang, Chenghai
item Odvody, Gary - Texas A&m Agrilife
item Minzenmayer, Richard - Texas A&m Agrilife
item Nichols, Robert - Cotton, Inc.
item Isakeit, Thomas - Texas A&m University
item Thomasson, Alex - Texas A&m University

Submitted to: Proceedings of the Annual Precision Ag Conference
Publication Type: Proceedings
Publication Acceptance Date: 2/6/2015
Publication Date: 6/8/2015
Citation: Yang, C., Odvody, G., Minzenmayer, R., Nichols, R., Isakeit, T., Thomasson, A. 2015. Using airborne imagery to monitor cotton root rot infection before and after fungicide treatment. Proceedings of the Annual Precision Ag Conference. International Society of Precision Agriculture. Online.

Interpretive Summary: Recent research has shown that a commercial fungicide, flutriafol, has potential for the control of the destructive cotton root rot disease. To effectively and economically control this disease, it is necessary to identify infected areas within the field so that variable rate technology can be used to apply fungicide only to the infected areas. This study employed airborne multispectral imagery to monitor cotton root rot infection in cotton before and after fungicide treatment to the soil. Image classification results for a 105-ha field showed that the fungicide reduced root rot infection from 17 percent in 2001 and 2011 under natural infection to less than 2 percent in 2013 with fungicide treatment at planting. These results further confirmed that the fungicide is effective and will allow producers and researchers to refine current application methods and rates for more effective control of the disease.

Technical Abstract: Cotton root rot is a severe soilborne disease that has affected cotton production for over a century. Recent research has shown that a commercial fungicide, flutriafol, has potential for the control of this disease. To effectively and economically control this disease, it is necessary to identify infected areas within the field so that variable rate technology can be used to apply fungicide only to the infected areas. The objective of this study was to use airborne imagery to monitor cotton root rot infection in cotton before and after fungicide treatment to the soil. A 105-ha irrigated cotton field with a historically consistent spatial pattern of infection was selected for this study. Airborne multispectral imagery with visible and near-infrared wavebands was taken from the field in 2001 and 2011 under natural root rot infection and again in 2013 with uniform flutriafol treatment at planting. The imagery was rectified and then classified into infected and noninfected zones using unsupervised classification. The classification results showed that the fungicide treatment reduced root rot infection from approximately 17% in both 2001 and 2011 to less than 2% in 2013. Although overall spatial patterns of infection between 2001 and 2011 were similar, there were slight changes in the locations of infected areas. A change detection analysis showed that 9.0% of the field was infected in both years, while 8.0% of the field was infected only in 2001 and 8.5% only in 2011. Thus a total of 25.5% of the field was infected in either 2001 or 2011. Change detection also showed that the infection in 2013 occurred within the infected areas in either 2001 or 2011, indicating a higher rate of fungicide may be needed to more effectively control the fungus with the season. Results from this study demonstrate that airborne multispectral imagery in conjunction with image classification techniques can be a useful tool not only for detecting and mapping cotton root rot infection, but also for assessing the efficacy of fungicide treatments and for optimizing site-specific treatment plans.