The objective of this work was to isolate and identify fungi associated with R. reniformis in cotton roots. Soil samples were collected in cotton fields naturally infested with R. reniformis and from cotton stock plants cultured in the greenhouse. Nematodes extracted from the soil were observed under the stereoscope, and discolored eggs and vermiform stages colonized with mycelia were cultured on 1.5% water agar supplemented with antibiotics, and incubated at 27°C. Identification of the nematophagous fungi was based on the morphological characters, and the ITS regions and 5.8S rDNA amplified by PCR using the primers ITS1 and ITS4. The parasitism percentage on vermiform nematodes from greenhouse samples was 21.2%, and the percentages from cotton fields in Limestone, Henry, and Baldwin counties in Alabama were 3%, 23.2%, and 5.6%, respectively. A total of 12 fungi were identified from R. reniformis vermiform stages and eggs. The most frequently isolated fungi were Arthrobotrys dactyloides (46%) and Paecilomyces lilacinus (14%), followed by Phoma exigua (4.8%), Penicillium waksmanii and Dactylaria brochophaga (3.6%), Aspergillus glaucus group (2.4%). Cladosporium herbarum, Cladosporium cladiosporioides, Fusarium oxysporum, Torula herbarum, Aspergillus fumigatus, and an unidentified basidiomycete were less frequent (1.2%). A high percentage (16.8%) of fungi from colonized nematodes was not cultivable on our media. Out of those 12 fungi, only four have been previously reported as nematophagous fungi: three isolates of Arthrobotrys dactyloides, and one isolate of Dactylaria brochopaga, Paecilomyces lilacinus, and Fusarium oxysporum. Molecular identification of Arthrobotrys dactyloides and Dactylaria brochopaga was consistent with the morphological identification, placing these two fungi in the new genus Drechslerella as proposed in the new Orbilaceae classification.

Rotylenchulus reniformis is the most damaging nematode pathogen of cotton in Alabama. It is easily introduced into cotton fields via contaminated equipment and, when present, is difficult and costly to control. A trial to monitor the natural migration of R. reniformis from an initial point of origin was established in 2007 and studied over two growing seasons in both irrigated and non-irrigated no-till cotton production systems. Vermiform females, juveniles and males reached a horizontal distance of 200 cm from the initial inoculation point, and a depth of 91 cm in the first season in both systems. Irrigation had no effect on the migration of vermiform females and juveniles, but males migrated faster in the irrigated trial than in the non-irrigated trial. Population density increased steadily in the irrigated trial during both years, exceeding the economic threshold of 1,000 per 150 cm3, but was highly correlated with rainfall in the non-irrigated trial. The average speed of migration ranged from 0- to 3.3-cm per day over 150 days. R. reniformis was able to establish in both the irrigated and non-irrigated trials in one season and to increase population density significantly.

We have adapted the Sherlock® Microbial Identification system for identification of plant parasitic nematodes based on their fatty acid profiles. Fatty acid profiles of 12 separate plant parasitic nematode species have been determined using this system. Additionally, separate profiles have been developed for Rotylenchulus reniformis and Meloidogyne incognita based on their host plant, four species and three races within the Meloidogyne genus, and three life stages of Heterodera glycines. Statistically, 85% of these profiles can be delimited from one another; the specific comparisons between the cyst and vermiform stages of H. glycines, M. hapla and M. arenaria, and M. arenaria and M. javanica cannot be segregated using canonical analysis. By incorporating each of these fatty acid profiles into the Sherlock® Analysis Software, 20 library entries were created. While there was some similarity among profiles, all entries correctly identified the proper organism to genus, species, race, life stage, and host at greater than 86% accuracy. The remaining 14% were correctly identified to genus, although species and race may not be correct due to the underlying variables of host or life stage. These results are promising and indicate that this library could be used for diagnostics labs to increase response time.