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United States Department of Agriculture

Agricultural Research Service

Title: Mapping Phymatotrichum Root Rot of Cotton Using Airborne Three-Band Digital Imagery

Authors
item YANG, CHENGHAI
item Fernandez, Carlos - TEXAS A&M-CORPUS CHRISTI
item Everitt, James

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 11, 2005
Publication Date: October 25, 2005
Citation: Yang, C., Fernandez, C.J., Everitt, J.H. 2005. Mapping phymatotrichum root rot of cotton using airborne three-band digital imagery. Transactions of the ASAE. 48(4):1619-1626.

Interpretive Summary: Cotton root rot is a serious and destructive disease that significantly reduces cotton yield and lowers lint quality. The objective of this study was to evaluate airborne three-band digital imagery for detecting and mapping root rot infestations in cotton fields. Image analysis indicated airborne imagery effectively and accurately identified root rot infested areas within the fields. The mapping procedures and maps presented in this study have practical implications for site-specific management of cotton root rot.

Technical Abstract: Phymatotrichum root rot, caused by the fungus, Phymatotrichum omnivorum, is a serious and destructive disease that significantly reduces cotton yield and lowers lint quality. Cultural practices are commonly recommended for the control of cotton root rot, and fungicides and fumigants that may suppress the disease have also been used. Because of the high costs of these chemicals, their use may be economically feasible only when the infested portions of the field are treated. The objective of this study was to evaluate airborne multispectral imagery for detecting and mapping root rot areas in cotton fields for site-specific management of the disease. One center pivot irrigated field and one rainfed field near Corpus Christi, Texas, were selected for this study. Airborne three-band digital imagery was taken from the two fields shortly before harvest in 2001 when the infested areas with wilted and dead plants were almost fully pronounced for the season. The imagery was georeferenced and then classified into healthy and root rot areas using unsupervised classification. Accuracy assessment on the classification maps for the two fields indicated airborne imagery effectively and accurately identified root rot areas within the fields. Ground samples taken from the fields showed that cotton yield and some lint quality indices were significantly lower in root rot areas than in healthy areas. Buffer zones around the root rot areas were generated to account for the spread of cotton root rot on the classification maps. The mapping procedures and maps presented in this study will be useful for site-specific management of the disease.

Last Modified: 9/10/2014
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