Countering the Threat of Bioterrorism in Iowa

One of the basic tenets of plant biosecurity is that the presence, actual or predicted distribution, intensity, and economic impact of any yield-reducing factor(s) must be known. The development of a real-time, GIS-based (geographic information system) reporting system for new and emerging agricultural pathogens and pests is extremely relevant in the era of agricultural bioterrorism. The goal is to establish a real-time, GIS database network to report, monitor, map (temporally and spatially), and predict the spread of new and emerging plant diseases and pests. This database network can also be used to geospatially and temporally monitor endemic pathogens/pests. Diagnostic records from the Regional Diagnostic Centers coupled with remote sensing, GIS, GPS, atmospheric transport models, and weather-based GIS risk prediction models, offers an integrated system of technologies to help ensure the production of a safe and affordable US food supply

1994 Monterey-Santa Cruz Counties Crop Report

The Monterey and Santa Cruz Crop Report from 1994 featuring statistics from the year and creative artwork highlighting the figures.https://digitalcommons.csumb.edu/samfarr_issues/1010/thumbnail.jp

Huts as Classrooms: A Memoir by Two Who Inhabited the Puckerbrush

The origins of the Appalachian Mountain Club’s educational programs at its huts in the White Mountains of New Hampshire, told by AMC’s first education director, John Nutter, and a former hut system manager, W. Kent Olson

Severe risk for Stewart\u27s disease

Stewart\u27s disease of corn, also known as Stewart\u27s wilt, is caused by the bacterium Pantoea stewartii. The 2000 growing season is predicted to be a very severe year for this disease, largely because of six successive winters with above-average monthly temperatures that have favored the survival of the insect vector for this disease, the corn flea beetle (Chaetocnema pulicaria). There are commonly two stages to the disease. Initially, leaf lesions that are off-green to yellow extend along the leaf veins, followed by mild-to-severe early seedling blight symptoms

Quantification of Temporal and Spatial Dynamics of Bean pod mottle virus at Different Spatial Scales

Bean pod mottle virus (BPMV) is the most prevalent virus infecting soybean (Glycine max) in the United States; however, the temporal and spatial dynamics in BPMV at varying spatial scales has not been elucidated. To quantify the temporal and spatial dynamics of BPMV at a field scale, a quadrat-based method was developed in which six soybean rows, each consisting of 30-cm-long quadrats, were established within soybean cv. NE3001 field plots (i.e., 150 quadrats per plot) in BPMV-inoculated and non-inoculated plots. Quadrats were sampled by selecting the youngest fully expanded leaflet from each of four plants within each quadrat beginning 25 days after planting, and continued at 8- to 11- day intervals until crop senescence. Leaf sap was extracted from each 4-leaflet (bulked) sample (from each quadrat), and tested for presence of the BPMV by ELISA. Quadrat position (plot, row, and quadrat number) and the date of sampling that each quadrat first tested positive for BPMV was recorded and mapped. The rate of BPMV incidence in 2006 ranged from 0.09 to 0.12 logits/day, indicating that BPMV incidence was doubling every 5.3 to 7.7 days in 2006. Doubling times for BPMV incidence in 2007 were slower, ranging from 17.3 to 34.7 days. Analysis of spatial patterns using ordinary runs revealed that BPMV-infected quadrats were predominantly clustered within both BPMV-inoculated and non-inoculated plots throughout both growing seasons. In addition to within field plot studies, a threeyear statewide disease survey (2005-2007) was conducted in Iowa to quantify county and field scale BPMV prevalence and incidence by systematically selecting 30 plants/soybean field (8 to 16 soybean fields per county). Leaf samples were then tested for BPMV by ELISA and county-level BPMV incidence maps were generated using ArcGIS software. End-of-season BPMV prevalence was 39/96 counties in 2005 (40%), 90/99 counties in 2006 (90.1%), and 74/99 counties in 2007 (74.7%). The incidence of BPMV within Iowa counties ranged from 0 to 100% and BPMV incidence significantly increased statewide from north to south. Spatial autocorrelation (dependence) analysis using Moran’s I revealed clustering for BPMV incidence among Iowa counties, indicating that BPMV incidence among counties was not random. The elucidation of the within-field temporal and spatial dynamics of BPMV and the statewide geographic distribution of BPMV in Iowa has important implications with regards to sampling, plant disease forensics, BPMV management, and risk prediction of BPMV