Park B.,Integrative Biosciences Graduate Program in Bioinformatics and Genomics |
Martin F.,U.S. Department of Agriculture |
Geiser D.M.,Integrative Biosciences Graduate Program in Bioinformatics and Genomics |
Geiser D.M.,Pennsylvania State University |
And 16 more authors.
Phytopathology | Year: 2013
The online community resource Phytophthora database (PD) was developed to support accurate and rapid identification of Phytophthora and to help characterize and catalog the diversity and evolutionary relationships within the genus. Since its release in 2008, the sequence database has grown to cover 1 to 12 loci for .2,600 isolates (representing 138 described and provisional species). Sequences of multiple mitochondrial loci were added to complement nuclear loci-based phylogenetic analyses and diagnostic tool development. Key characteristics of most newly described and provisional species have been summarized. Other additions to improve the PD functionality include: (i) geographic information system tools that enable users to visualize the geographic origins of chosen isolates on a global-scale map, (ii) a tool for comparing genetic similarity between isolates via microsatellite markers to support population genetic studies, (iii) a comprehensive review of molecular diagnostics tools and relevant references, (iv) sequence alignments used to develop polymerase chain reaction-based diagnostics tools to support their utilization and new diagnostic tool development, and (v) an online community forum for sharing and preserving experience and knowledge accumulated in the global Phytophthora community. Here we present how these improvements can support users and discuss the PDfs future direction. © 2013 The American Phytopathological Society.
PubMed | University of Otago, J. Craig Venter Institute, ZedX Inc., Albert Ludwigs University of Freiburg and 9 more.
Type: | Journal: Trends in ecology & evolution | Year: 2016
Evidence indicates that, despite some critical successes, current conservation approaches are not slowing the overall rate of biodiversity loss. The field of synthetic biology, which is capable of altering natural genomes with extremely precise editing, might offer the potential to resolve some intractable conservation problems (e.g., invasive species or pathogens). However, it is our opinion that there has been insufficient engagement by the conservation community with practitioners of synthetic biology. We contend that rapid, large-scale engagement of these two communities is urgently needed to avoid unintended and deleterious ecological consequences. To this point we describe case studies where synthetic biology is currently being applied to conservation, and we highlight the benefits to conservation biologists from engaging with this emerging technology.
Sikora E.J.,Auburn University |
Allen T.W.,Mississippi State University |
Wise K.A.,Purdue University |
Bergstrom G.,Cornell University |
And 47 more authors.
Plant Disease | Year: 2014
Existing crop monitoring programs determine the incidence and distribution of plant diseases and pathogens and assess the damage caused within a crop production region. These programs have traditionally used observed or predicted disease and pathogen data and environmental information to prescribe management practices that minimize crop loss. Monitoring programs are especially important for crops with broad geographic distribution or for diseases that can cause rapid and great economic losses. Successful monitoring programs have been developed for several plant diseases, including downy mildew of cucurbits, Fusarium head blight of wheat, potato late blight, and rusts of cereal crops. A recent example of a successful disease-monitoring program for an economically important crop is the soybean rust (SBR) monitoring effort within North America. SBR, caused by the fungus Phakopsora pachyrhizi, was first identified in the continental United States in November 2004. SBR causes moderate to severe yield losses globally. The fungus produces foliar lesions on soybean (Glycine max) and other legume hosts. P. pachyrhizi diverts nutrients from the host to its own growth and reproduction. The lesions also reduce photosynthetic area. Uredinia rupture the host epidermis and diminish stomatal regulation of transpiration to cause tissue desiccation and premature defoliation. Severe soybean yield losses can occur if plants defoliate during the mid-reproductive growth stages. The rapid response to the threat of SBR in North America resulted in an unprecedented amount of information dissemination and the development of a real-time, publicly available monitoring and prediction system known as the Soybean Rust-Pest Information Platform for Extension and Education (SBR-PIPE). The objectives of this article are (i) to highlight the successful response effort to SBR in North America, and (ii) to introduce researchers to the quantity and type of data generated by SBR-PIPE. Data from this system may now be used to answer questions about the biology, ecology, and epidemiology of an important pathogen and disease of soybean. © 2014 The American Phytopathological Society.
Brosnan J.T.,University of Tennessee at Knoxville |
Breeden G.K.,University of Tennessee at Knoxville |
Elmore M.T.,University of Tennessee at Knoxville |
Zidek J.M.,ZedX Inc.
Weed Technology | Year: 2011
Bermudagrass is a troublesome weed of zoysiagrass golf-course fairways. Field research was conducted in 2009 and 2010 evaluating bermudagrass suppression with applications of fluazifop plus triclopyr at various timings. Three rates of fluazifop (0.10, 0.21, and 0.32 kg ai ha -1) were applied with triclopyr (1.12 kg ae ha -1) once six thresholds of growing-degree-day accumulation (GDD10C) had been reached: 200, 450, 825, 1,275, 1,775, and 2,250 GDD10C. Yearly accumulated GDD10C values were calculated with a base temperature of 10 C beginning on 1 January. Applications at 200 and 2,250 GDD10C suppressed bermudagrass ≥90% at 5 WAT each year. Increased rates of fluazifop did not provide additional bermudagrass suppression at these timings. Cooling accumulation models may be needed to time fall applications, as the 1,775 GDD10C timing in 2009 provided similar bermudagrass suppression to the 2,250 GDD10C timing in 2010. Late-spring and midsummer applications at 450 GDD10C, 825 GDD10C, and 1,275 GDD10C only suppressed bermudagrass 4 to 16% at 6 wk after treatment (WAT) in 2009 and 0 to 57% at 6 WAT in 2010. Zoysiagrass injury measured <25% for all timings and decreased to 0 to 7% by 5 WAT each year. Future studies should evaluate bermudagrass suppression with other herbicides with the use of growing-degree-day and cooling accumulation models. © Weed Science Society of America.
Isard S.A.,Pennsylvania State University |
Barnes C.W.,Pontifical Catholic University of Ecuador |
Hambleton S.,Agriculture and Agri Food Canada |
Ariatti A.,Pennsylvania State University |
And 4 more authors.
Plant Disease | Year: 2011
Between 2005 and 2009, millions of U.S. and Canadian soybean acres that would have received fungicide application remained untreated for soybean rust due to information disseminated through the Integrated Pest Management Pest Information Platform for Extension and Education (ipmPIPE), increasing North American producers' profits by hundreds of millions of dollars each year. The results of our analysis of Phakopsora pachyrhizi urediniospores in rain collections, aerobiology model output, and observations of soybean rust spread in 2007 and 2008 show a strong correspondence between spore collections and model predictions for the continental interior of North America, where soybean is an important crop. The analysis suggests that control practices based on up-to-date maps of soybean rust observations and associated commentary from Extension Specialists delivered by the ipmPIPE may have suppressed the number and strength of inoculum source areas in the southern states and retarded the northward progress of seasonal soybean rust incursions into continental North America. The analysis further indicates that spore trapping and aerobiological modeling can reduce our reliance on the costly Sentinel Plot Network while maintaining the effectiveness of the ipmPIPE system for soybean rust management. © 2011 The American Phytopathological Society.
Walls J.T.,Pennsylvania State University |
Caciagli P.,National Research Council Italy |
Tooker J.F.,Pennsylvania State University |
Russo J.M.,ZedX Inc. |
And 2 more authors.
Computers and Electronics in Agriculture | Year: 2016
Since the 1980s, expert decision support systems (DSSs) have been explored for enhancement of agricultural decision-making. Combinations of expert DSSs and cyber-age technology, such as mobile devices, is increasing adoption and accuracy of these systems and will allow DSSs to be easily modified to incorporate new information and web-based resources as they become available. Using barley yellow dwarf (BYD), a disease complex caused by several aphid-vectored viruses, as a model system we created a DSS for winter wheat growers based on dependency networks. At key points throughout the growing season the networks interpret how field conditions may affect management recommendations for BYD in winter wheat. To address nine possible management recommendations the networks analyze 72,387 combinations of input field conditions. This method of decision modeling can potentially be used to provide support to enable the efficient management of other crop pests and diseases and enable a more sustainable agroecosystem. The DSS was created for use in a mobile device app which will produce real-time recommendations, emulating disease management experts. Coupling this expert DSS with high resolution weather, pest, and disease forecasts will prove to be a powerful management tool in the future. © 2016