Multi-Year Study of the Temporal Variability of Fusarium Oxysporum F. SP. Vasinfectum Races As Influenced By Cotton Cultivar in the National Cotton Fusarium Wilt Evaluation Field in Alabama.

Thursday, January 9, 2020: 4:00 PM
211-212 (JW Marriott Austin Hotel)
David R Dyer , Auburn University
Kathy S. Lawrence , Auburn University
Fusarium wilt of cotton, caused by the fungal pathogen Fusarium oxysporum f. sp. vasinfectum (FOV), can be found in cotton globally.  Different races and genotypes have been documented infecting cotton and inducing symptoms of wilting, stunting, chlorosis and necrosis of leaves, vascular discoloration, and even plant death. Some races are more commonly found causing disease at certain times of the cotton season, such as race 4 in the western part of the country, commonly infecting and causing stand reductions in the early part of the season.  This study was initiated to determine the in-season and between season temporal variability of FOV races on selected Upland, Pima, and Acala cotton cultivars with known susceptibility or resistance to RKN and certain FOV races in a field with documented multiple FOV races. Plants exhibiting symptoms of FOV infection were collected from the field for fungal isolation at weekly intervals for the first six weeks and bi-weekly for the remainder of the season.  From each FOV isolate collected from the field, portions of the Translation elongation factor (EF-1α), β-tubulin (Bt) and the phosphate permease (PHO) were sequenced to identify the race designation for each isolate of FOV.  Of the samples collected in 2018, a total of 7 races and genotypes were identified (race 1, 2, and 8; genotypes MDS-12, LA 108, LA 110, LA127/140).  Of the samples collected only MDS-12 and LA 127/140 had a greater portion of their samples collected in the early season (67% and 75% respectively), first 6 weeks.  All other races and genotypes were found at a higher density in the latter part of the growing season mostly from the end of August until defoliation.  Race identification and data analysis are ongoing for samples collected in 2019 to determine the temporal distributions of FOV in the field.