Isoline pairs of hybrid corn, similar except for presence or absence of a Bt trait, were planted at eight sites across Alabama over three years. This

Soil bacterial communities have significant influence on soilborne plant pathogens and, thus, crop health. The present study focuses on ribotyping soil bacterial communities in different peanut-cropping sequences in Alabama. The objective was to identify changes in microbial assemblages in response to cropping sequences that can play a role in managing soilborne plant pathogens in peanut. Four peanut-cropping sequences were sampled at the Wiregrass Research Station, Headland, AL in 2006 and 2007, including continuous peanut, 4 years of bahiagrass followed by peanut, peanut-cotton, and peanut-corn-cotton. Soil sampling was done at early and mid-season and at harvest. Bacterial community structure was assessed using ribosomal intergenic spacer analysis (RISA) combined with 16S rRNA cloning and sequencing. RISA results indicated >70% dissimilarities among different cropping sequences. However, 90% similarities were noticed among replicated plots of the same cropping sequences. Cropping sequences and time of soil sampling had considerable effect on soil microbial community structure. Bahiagrass rotation with peanut was found to have the highest bacterial diversity, as indicated by a high Shannon Weaver Diversity index. Overall, higher bacterial diversity was observed with bahiagrass and corn rotations compared with continuous peanut. The bacterial divisions Proteobacteria, Acidobacteria, Firmicutes, Bacteroidetes, and Actinomycetes were the predominant bacterial phyla found in all peanut-cropping sequences. The Proteobacteria taxa in these soils were negatively correlated with the abundance of members of division Firmicutes but, conversely, had a significant positive correlation with Gemmatimonadetes taxa. The prevalence of the division Actinomycetes was negatively correlated with the relative abundance of members of division Verrucomicrobia. These results indicate complex interactions among soil bacteria that are important contributors to crop health.

Peanut (Arachis hypogaea L.) is an important food and oilseed crop worldwide. Yield and quality can be significantly reduced by foliar fungal diseases, such as early and late leaf spot diseases. Acceptable levels of leaf spot resistance in cultivated peanut have been elusive due to environmental interactions and the proper combination of QTLs in any particular peanut genotype. Resistance gene analogs, as potential resistance (R)-genes, have unique roles in the recognition and activation of disease resistance responses. Novel R-genes can be identified by searches for conserved domains such as nucleotide binding site, leucine rich repeat, receptor like kinase, and receptor like protein from expressed genes or through genomic sequences. Expressed R-genes represent necessary plant signals in a disease response. The goals of this research are to identify expressed R-genes from cultivated peanuts that are naturally infected by early and late spot pathogens, compare these to the closest diploid progenitors, and evaluate specific gene expression in cultivated peanuts. Putative peanut R-genes (381) were available from a public database (NCBI). Primers were designed and PCR products were sequenced. A total of 214 sequences were produced which matched to proteins with the corresponding R-gene motifs. These R-genes were mapped to the genome sequences of Arachis duranensis and Arachis ipaensis, which are the closest diploid progenitors for tetraploid cultivated peanut, A. hypogaea. Identification and association of specific gene-expression will elucidate potential disease resistance mechanism in peanut and may facilitate the selection of breeding lines with high levels of leaf spot resistance.

Target spot, caused by Corynespora cassiicola, has recently emerged as a problematic foliar disease of cotton. This pathogen causes premature defoliation during boll set and maturation that can subsequently impact yield, and on certain cotton cultivars loss can be substantial. This study sought to better understand target spot epidemics and disease-incited yield losses on cotton. In order to establish a range of disease, varying numbers of fungicide applications were made to each of two cotton cultivars in each of four site-years. Target spot intensity was rated over several dates beginning in late July or early August and continuing into September. Yield of seed plus lint (seed cotton) was recorded at harvest. When analyzed across cultivars, a second or third fungicide application increased yield compared with no treatment. Lack of significant yield response with a single fungicide application may have been due to timing of that application which preceded disease onset. The cultivar PhytoGen 499 WRF had consistently greater defoliation than any of the three Deltapine cultivars grown in each site-year. However, yields of both cultivars responded similarly to the fungicide regimes. Yield loss models based on late August defoliation were only predictive at site-years where conditions favored target spot development, i.e., abundant rain and moderate temperatures. Epidemic development fit the Gompertz growth model better than it did a logistic model. Knowledge of the underlying mathematical character of the epidemiology of target spot will prove useful for development of a predictive model for the disease.

Reliable prediction of aflatoxin occurrence in peanut is needed so that growers can make appropriate management decisions when contamination risk is high. The goal of this study was to develop such a prediction system. Aflatoxin concentrations were monitored in rainfed peanuts over 5 yr at the Wiregrass Research and Extension Center in SE Alabama; in each year, 4 planting dates subjected the crop to different temperatures and rainfall patterns. The first planting in each year was in late April with subsequent plantings scheduled at 2 wk intervals. Daily maximum temperatures averaged over the final 6 wk prior to inversion (MaxT.6wk) and cumulative 3-d-dry periods during the 4 wk prior to inversion (d3d.4wk) were better correlated to aflatoxin levels than other temperature and moisture variables including rain days and total precipitation. When MaxT.6wk > 31.5 C and d3d.4wk ≥17, there was a high risk (≥30% chance of >20 ppb) of aflatoxin contamination in peanuts; when neither of these conditions we...