Biology subjects

Mideros, S.

Publications and source records attributed to Mideros, S..

3 recordsLinked to original sources

bioRxiv2022

Virulence, Aggressiveness, and Fungicide Sensitivity of Phytophthora spp. Associated with Soybean in Illinois

Phytophthora root and stem rot (PRR), caused by Phytophthora sojae, is one of the most devastating oomycete diseases of soybean in Illinois. Single resistant genes (Rps) are used to manage this pathogen, but P. sojae has adapted to Rps causing failure of resistance in many regions. In addition to P. sojae, recent reports indicate that Phytophthora sansomeana could also cause root rot in soybean. Soil samples and symptomatic plants were collected across 40 Illinois counties between 2016 and 2018. Phytophthora sojae (77%) was more abundant than P. sansomeana (23%) across Illinois fields. Both species were characterized by virulence, aggressiveness, and fungicide sensitivity. Virulence of all isolates was evaluated using the hypocotyl inoculation technique in 13 soybean differentials. Aggressiveness was evaluated in the greenhouse by inoculating a susceptible cultivar and measuring root and shoot dry weight. On average, P. sojae isolates were able to cause disease on six soybean differentials. P. sojae was more aggressive than P. sansomeana. All isolates were sensitive to azoxystrobin, ethaboxam, mefenoxam, and metalaxyl. The characterization of the population of species associated with PRR will inform management decisions for this disease in Illinois.

plant biology↗

bioRxiv2022

The effect of Septoria glycines and fungicide application on the soybean phyllosphere mycobiome

Septoria brown spot (caused by Septoria glycines) is the most prevalent soybean disease in Illinois. It is common to use a foliar fungicide to control Septoria brown spot and other foliar diseases. The effects of fungicide on non-target organisms in the phyllosphere are unknown. To study the effect of S. glycines and fungicide application on the soybean phyllosphere mycobiome we sequenced full-length ITS and partial LSU region using oxford nanopore technologies. Sequencing produced 3,342 operational taxonomic units (OTUs). The richness of the fungal community significantly increased with the developmental stage. The soybean lines significantly affected the mycobiome diversity at the early developmental stage but not at the reproductive stages. S. glycines did not significantly affect the alpha diversity but some significant changes were observed for the beta diversity. At the R5 stage, fungicide application significantly changed the composition of the fungal community. The fungicide treatment significantly decreased the proportion of several fungal reads, but it increased the proportion of Septoria. The core microbiome in soybean leaves was composed of Gibberella, Alternaria, Didymella, Cladosporium, Plectosphaerella, Colletotrichum, and Bipolaris. Network analysis identified significant interactions between Septoria reads and Diaporthe, Bipolaris and two other taxonomic units. In this study, we set Septoria as the target organism and demonstrated that metabarcoding could be a tool to quantify the effect of multiple treatments on the fungal phyllosphere community. Better understanding the dynamics of the phyllosphere microbiome is necessary to start untangling late-season diseases of soybean.

plant biology↗

bioRxiv2019

Effect of Septoria brown spot on soybean yield in Illinois

Brown spot caused by Septoria glycines is a prevalent foliar disease in all soybean production areas. Application of foliar fungicides after bloom reduces the disease severity, yet yield responses are not consistent among locations and years. Our research goal was to determine the effect of different levels of Septoria brown spot on yield. Different levels of disease severity were effectively obtained in the field by weekly application of chlorothalonil for three, six, and nine times after disease inoculation at V3/V4 stage. Fungicide treatments had a significant effect on vertical progress and chlorotic area with no statistically significant effect on yield. Soybean yield was negatively correlated with vertical progress of the disease (r = -0.36). The vertical progress was the best linear predictor of yield. Based on this model, when the vertical progress of brown spot at R6 increased by 10%, the yield decreased by 142.13 kg/ha (3.4%). A variance component analyses of our data showed that location was the most critical factor, illustrating the significant effect of local environmental conditions on the disease. Power analyses indicated that at least eight locations are needed to detect an effect of 269 kg/ha. Our results provide useful information to improve the experimental design for future experiments addressing the yield constrain by late season diseases of soybean.

plant biology↗