Measuring the Distance and Effects of Weather Conditions on the Dispersal of Nothopassalora personata.

Nothopassalora personata is one of the most economically severe pathogens of peanut in the United States. The fungus primarily relies on wind and rain for dispersal, which has been documented up to 10 m from an inoculum source. Spore traps have been used in a wide variety of pathosystems to study epidemiology, document detection, develop alert systems, and guide management programs. The objective of this study was to use spore traps and N. personata-specific qPCR primers to quantitatively evaluate dispersal of N. personata conidia at distances up to 70 m from an infected peanut field and to examine relationships between quantities captured and weather variables. Impaction spore samplers were placed at 4, 10, 30, 50, and 70 m from peanut fields at the Edisto Research and Education Center (six fields) and commercial peanut fields in Barnwell and Bamberg counties (one field each) from 2020 to 2022. Following initial detection, samples were collected at a 48-, 48-, 72-h interval until harvest. N. personata conidia were detected at all locations and distances, documenting dispersal up to 70 m from an inoculum source. This result is a reminder that volunteer management is crucial when rotating peanut in nearby fields. A model for predicting log spore quantities was developed using temperature and humidity variables. Temperature variables associated with observed sampling periods had a negative correlation with N. personata quantities, whereas parameters of relative humidity and mean windspeed were positively correlated.

Critical role for uricase and xanthine dehydrogenase in soybean nitrogen fixation and nodule development.

De novo purine biosynthesis is required for the incorporation of fixed nitrogen in ureide exporting nodules, as formed on soybean [Glycine max (L.) Merr.] roots. However, in many cases, the enzymes involved in this pathway have been deduced strictly from genome annotations with little direct genetic evidence, such as mutant studies, to confirm their biochemical function or importance to nodule development. While efforts to develop large mutant collections of soybean are underway, research on this plant is still hampered by the inability to obtain mutations in any specific gene of interest. Using a forward genetic approach, as well as CRISPR/Cas9 gene editing via Agrobacterium rhizogenes-mediated hairy root transformation, we identified and characterized the role of GmUOX (Uricase) and GmXDH (Xanthine Dehydrogenase) in nitrogen fixation and nodule development in soybean. The gmuox knockout soybean mutants displayed nitrogen deficiency chlorosis and early nodule senescence, as exemplified by the reduced nitrogenase (acetylene reduction) activity in nodules, the internal greenish-white internal appearance of nodules, and diminished leghemoglobin production. In addition, gmuox1 nodules showed collapsed infected cells with degraded cytoplasm, aggregated bacteroids with no discernable symbiosome membranes, and increased formation of poly-ß-hydroxybutyrate granules. Similarly, knockout gmxdh mutant nodules, generated with the CRISPR/Cas9 system, also exhibited early nodule senescence. These genetic studies confirm the critical role of the de novo purine metabolisms pathway not only in the incorporation of fixed nitrogen but also in the successful development of a functional, nitrogen-fixing nodule. Furthermore, these studies demonstrate the great utility of the CRISPR/Cas9 system for studying root-associated gene traits when coupled with hairy root transformation.

Spatial Associations of Key Lepidopteran Pests With Defoliation, NDVI, and Plant Height in Soybean.

In soybean, Glycine max (L.) Merrill, production, losses to, and control costs for insect pests can be significant limiting factors. Although the heterogeneity of pests has typically been ignored in traditional field management practices, technological advancements have allowed for site-specific pest management systems to be developed for the precise control of pests within a field. In this study, we chose to determine how the in-field distributions of the larvae of three major lepidopteran pests [velvetbean caterpillar Anticarsia gemmatalis (Hübner) (Lepidoptera: Erebidae), soybean looper Chrysodeixis includens (Walker) (Lepidoptera: Noctuidae), and green cloverworm Hypena scabra (Lepidoptera: Erebidae) (Fabricius)] were spatially associated with defoliation, Normalized Difference Vegetation Index (NDVI), and plant height in soybean. Spatial analysis by distance indices (SADIE) of data from two South Carolina soybean fields in 2017 and 2018 revealed a limited number of spatial aggregations for insect datasets. However, 14% and 6% of paired plant-insect datasets were significantly associated or dissociated, respectively. NDVI was found to be more associated with pest distributions than soybean plant heights and defoliation estimates, and the majority of all plant-insect associations and dissociations occurred in the first 4 wk of sampling (late July-early August). If changes are to be implemented regarding how a pest is managed, critical factors explaining the spatial distribution of pests must be identified. Results from this study advocate for the relationship between early-season distributions of pests and important plant variables such as NDVI to be further investigated to better determine the strength of the correlations across years and sites.

Associating Site Characteristics With Distributions of Pestiferous and Predaceous Arthropods in Soybean.

Although site-specific pest management has the potential to decrease control costs and environmental impact associated with traditional pest management tactics, the success of these programs relies on the accurate characterization of arthropod distributions within a crop. Because potential correlation of insect counts with remotely sensed field attribute data could help to decrease the costs associated with and need for fine-scale spatial sampling, we chose to determine which within-field variables would be informative of soybean arthropod counts in an attempt to move toward site-specific pest management in this crop. Two soybean fields were grid-sampled for pestiferous and predaceous arthropods, plant productivity estimates, and abiotic variable characterization in 2017-2018. Negative binomial, zero-inflated models were used to estimate presence and counts of soybean arthropod taxa based on normalized difference vegetation index (NDVI), soybean plant height, soil electrical conductivity (ECa), elevation, and calendar week. Among all variables, calendar week was the most reliable predictor of arthropod counts, as it was a significant predictor for a majority of all taxa. Additionally, counts for a majority of pestiferous taxa were significantly associated with distance from the field edge, elevation, soybean plant height, and NDVI. Although site-specific pest management has the potential for reduced management inputs and increased profitability over conventional management (i.e., whole-field) practices, management zones must first be clearly defined based on the within-field variability for the variables of interest. If site-specific pest management practices are to be applied in soybean, calendar week (and associated soybean phenology), soybean plant height (and associated elevation), and NDVI may be useful for describing the distributions of pests, such as kudzu bug, Megacopta cribraria (Hemiptera: Plataspidae) (Fabricius), green cloverworm, Hypena scabra (Lepidoptera: Erebidae) (Fabricius), velvetbean caterpillar, Anticarsia gemmatalis (Lepidoptera: Erebidae) (Hübner), and soybean looper, Chrysodeixis includens (Lepidoptera: Noctuidae) (Walker).