Aerial Remote Sensing Surveys of Fusarium Wilt of Cotton Near El Paso, Texas

Wednesday, January 9, 2019: 10:30 AM
Galerie 1 (New Orleans Marriott)
Chenghai Yang , USDA-ARS
Thomas Isakeit , Texas A&M University
Robert L. Nichols , Cotton Incorporated
Fusarium wilt of cotton, caused by the fungus Fusarium oxysporum f. sp. vasinfectum (FOV), is a widespread cotton disease. The highly virulent FOV race 4 (FOV4) was found in California in early 2001 and in the Texas-New Mexico border area near El Paso, Texas in 2017. A remote sensing aerial survey was performed in 2017 and a second one was conducted on September 19, 2018, about one year apart from the first survey. The intent of the surveys was to map the distribution and severity of this introduced disease in the area and to assess the progression of the disease across years. An aircraft equipped with multispectral and hyperspectral imaging systems was flown at approximately 5000 ft above ground level over three suspected areas: a 3800-acre area to the northwest of El Paso, Texas and a large 39,000-acre area and a small area of 2500 acres to the southeast of El Paso. Over 600 pairs of normal color and near-infrared images were acquired from the three areas, and the multispectral images for each of the areas were mosaicked to create orthomosaics. Images from portions of FOV4-infested fields were used to illustrate the spatial and spectral characteristics of FOV4-infested areas as compared to root-knot nematode infestations and soil variability. Plants infected early in the season were dead as evidenced by bare soil exposure. The images are being visually examined to identify probable FOV4-infested fields for ground confirmation. These aerial surveys provide useful information for faster and more effective identification of FOV4 infestations in the Texas-New Mexico border area. Multiple aerial surveys should be conducted during the growing season to monitor the progression of the disease in conjunction with ground truthing. Meanwhile, more research is needed to evaluate multispectral and hyperspectral imagery for identifying FOV4 from other coexisting races and stresses.