Progress 02/01/05 to 01/31/10
Outputs
OUTPUTS: This project has contributed significant new knowledge and tools to support the development of a National Agricultural Biosecurity Program to safeguard U.S. agriculture. The PIs have helped to establish a GIS, web-based delivery system to geospatially-display (map) where specific plant pathogens have been detected, identified, and confirmed. This web-based mapping system supports the Plant Diagnostics Information System (PDIS) and the National Plant Diagnostic Network (NPDN). Using soybean rust of soybean as a model pathosystem, we have developed the technology to locate (within 1.5 m) the locations (focal epicenters) where soybean rust was deliberately introduced into soybean plots. This was accomplished by developing and integrating GPS, GIS, and remote sensing technologies to detect pathogen-specific temporal and spatial signatures unique to soybean rust. The significance of this research is that it underpins the U.S. capability to surveil agricultural fields and experimental plots for the presence of high-consequence plant diseases throughout the globe, before threatening plant pathogens are introduced into the U.S. and before they can damage the U.S. agricultural economy. We have developed sampling protocols for both early detection and attribution (forensics) for other model pathosystems, including wheat leaf rust (a fungal pathogen), Bean pod mottle virus and Soybean mosaic virus (both viral pathogens), and Stewart's disease of corn (a bacterial pathogen). These model pathosystems were chosen because they behave (epidemiologically) like other plant pathogens that currently threaten U.S. agricultural biosecurity. To quantify the "strength of the inoculum source" from diseased crops, experiments were conducted to quantify the density of pathogen spores that can escape from diseased crop canopies (wheat) using a helium-filled weather balloon platform that was engineered to remotely operate six Rotorod spore samplers. This information provided new, critical information that is of tremendous value to research groups using atmospheric transport models to predict the long distance dispersal of plant pathogens. This is because, although the distance and direction of parcels of air can be predicted with great accuracy, the density of pathogen spores within parcels of air was largely unknown. Educational materials concerning the outputs for this plant biosecurity project have been prepared for a range of stakeholder communities. This information has been disseminated primarily through presentations for participants attending National Plant Diagnostic Network (NPDN) meetings, the Information Technology and Epidemiology NPDN Committees, National Soybean Rust Symposia participants, the Department of Defense-Telemedicine and Advanced Technology Research Center Surveillance Workshops, and oral presentations at Annual and Division Meetings of the American Phytopathological Society. Project findings and protocols have also been published in five book chapters, which concern the use of plant pathogens as potential weapons that threaten U.S. agricultural biosecurity. PARTICIPANTS: Participants for which training was provided include: Lu Liu (MSc. Student in Plant Pathology), Emmanuel Byamukama (Ph.D. student in Plant Pathology), Dr. Noha Holah (Postdoc, Plant Pathology), Andrew Gougherty (MSc. student in graduate program in Ecology and Evolutionary Biology), David Hagopian and Stephanie Konopka (Undergraduate Research Assistants), and several summer interns in the ISU Program for Women in Science and Engineering. Scientists who collaborated on the project include the Project Director, Dr. Forrest W. Nutter, Jr., Dr. Mark Gleason (Professor, Plant Pathology), Dr. S. Elwynn Taylor (Agricultural Meteorologist, Department of Agronomy), Dr. John Basart (Professor, Computer and Electrical Engineering), Dr. Will Baldwin (Information Technology, Associate Professor, Kansas State University), and Drs. David Wright and James Marois (University of Florida). TARGET AUDIENCES: The primary target audience for the project includes diagnosticians, extension specialists, forensic plant pathologists, epidemiologists, and other researchers involved in the mission and activities of USDA-CSREES, USDA-APHIS, and the National Plant Diagnostic Network (NPDN). The NPDN was established in 2002 by USDA-CSREES to serve as an early warning system for the detection of plant pathogens and pests that threaten U.S. agricultural biosecurity. PROJECT MODIFICATIONS: Not relevant to this project.
Impacts
This project has brought about new research collaborations with Dr. Scott Isard, The Pennsylvania State University, and with the Western Weather Working Group (WWWG), a group funded by the Western IPM Center. These new collaborations relate primarily to Objective 4 (development of atmospheric transport of plant pathogens), and Objective 5 (development of weather-based GIS disease/pest models to estimate the risk of infection/establishment beyond the point of initial pathogen detection). Outcomes also include the formation of a new weather working group (The North Central Weather Working Group, NCWWG), funded by the North Central IPM Center (February, 2008 to present). Outputs from the WWWG and NCWWG activities include collaboration on a joint publication on the evaluation and comparison of methods to model leaf wetness duration as affected by different crop canopies and climatic regions of the world (submitted). The accurate estimation of leaf wetness duration using models is a critical component of many disease warning systems. Experiments have been conducted to determine if a new pathogen outbreak was the result of a deliberate or a natural event for three model cropping systems (corn, soybeans, wheat). This has provided critical information on how to sample crops for the early detection of plant pathogens in U.S. crops as well as how to sample within and among disease foci for attribution (forensics). We have also characterized the changes in temporal and spatial patterns of plant pathogens over time and have addressed how this affects sampling for attribution. Proof of concept has been clearly demonstrated by developing integrated remote sensing, GPS, and GIS technologies for the early detection and accurate identification of the specific causes(s) of plant disease stress within crops. This finding resulted in a new paradigm that uses pathogen-specific temporal and spatial signatures to detect and identify specific plant pathogens with satellite imagery, and replaces the decades-old paradigm of attempting to obtain pathogen-specific spectral signatures. In 2008, methods were refined to quantify spore density in the atmosphere in vertical (above) and horizontal (down wind) directions relative to a diseased crop area. These were developed using small helium weather balloons, each equipped with 6 remotely-operated Rotorod spore samplers. Environmental variables (i.e. temperature, wind direction, vertical wind speed, horizontal wind speed, and relative humidity) affecting spore release (removal) and escape from diseased crop canopies, as well as elevation and GPS location, were all monitored and remotely recorded in real time. Data from this study fills knowledge gaps and will allow researchers to more accurately predict the density of pathogen spores escaping from diseased crop canopies, as well as the long-distance dispersal of spores.
Publications
- Byamukama, E., Robertson, A., and Nutter, F.W., Jr. 2010. Geospatial analyses of Bean pod mottle virus on soybean at different spatial scales. Phytopathology 100: xxx (Submitted).
- Byamukama, E., Robertson, A.E., Nutter, F.W. Jr. 2010. Identifying pre-plant risk factors for Bean pod mottle virus in Iowa. Phytopathology 100:S183.
- Nutter, F.W., Jr., Byamukama, E., Coelho-Netto, R.A., Eggenberger, S.K., Gleason, M.L., Gougherty, A., Holah, N., Robertson, A.E., and Van Rij, N. 2010. Integrating GPS, GIS, and remote sensing technologies with disease management principles to improve plant health. Pages xxx-xxx in: GIS Applications in Agriculture-Invasive Species, S. Clay, ed., Taylor & Francis Group LLC, Boca Raton, FL.
- Nutter, F.W. Jr., Holah, N.S., and Eggenberger, S.K. 2010. Developing integrated GPS, GIS, and satellite remote sensing technologies to locate the epicenters of plant disease foci. Page 56 in: 3rd Conference on Precision Agriculture, E.C. Oreke, ed. University of Bonn, Bonn, Germany.
- Nutter, F.W. Jr., Holah, N., Van Rij, N., Wright, D., Marois, J. 2010. Meeting the challenges of U.S. crop Biosecurity: Pre- and post threat introduction. Phytopathology 100:S181.
- Nutter, F.W., Jr., Van Rij, N., Eggenberger, S.K., and Holah, N. 2010. Spatial and temporal dynamics of plant pathogens. Pages 27-50 in: Precision Crop Protection - the Challenge and Use of Heterogeneity, E-C. Oerke. R. Gerhards, G. Menz, and R.A. Sikora, eds. Springer, NY, NY.
- Byamukama, E., Robertson, A., and Nutter, F.W. Jr. 2009. Abiotic and biotic risk factors associated with Bean pod mottle virus in Iowa. Phytopathology 99:S18.
- Kim, K. S., Taylor, S. E., Gleason, M. L., Nutter, F. W. Jr., Coop, L. B., Pfender, W. F., Seem, R. C., Sentelhas, P. C., Gillespie, T. J., Marta, A. D., and Orlandini, S. 2009. Spatial portability of leaf wetness duration models based on empirical approaches. Plant Dis. xxixxx (Accepted).
- Byamukama, E., Robertson, A. E., and Nutter, F.W., Jr. 2010. Quantification of temporal and spatial dynamics of Bean pod mottle virus at different spatial scales. Online. Plant Health Progress doi:10.109.1094/PHP-2010-05XX-01-SY.
- Byamukama E., Robertson, A. E., and Nutter, F. W., Jr. 2010. Quantifying the within-field temporal and spatial dynamics of Bean pod mottle virus in soybean. Phytopathology 99: xxx-xxx (Accepted).
- Coelho-Netto, R. A. and Nutter, F.W. Jr. 2010. Moko disease of banana: Use of GPS and GIS tools to map disease risk. Page 74 in: 3rd Conference on Precision Agriculture, E.C. Oreke, ed. University of Bonn, Bonn, Germany.
- Fletcher, J., Barnaby, N.G., Burans, J.P., Melcher, U., Nutter, F.W., Jr., Thomas, C., and Corona, F.M.O. 2010. Forensics plant pathology. Pages 89-105 in Microbial Forensics, 2nd edition, B. Budowle, S.E. Schutzer, R.G. Breeze, P.S. Keim, and S.A. Morse, eds. Elsevier Press, San Diego, CA.
- Gougherty, A., Welliver, R., Richwine, N., Nutter, F.W. Jr. 2010. Spatial and temporal analyses of Plum pox virus survey data. Phytopathology 100:S42.
- Holah, N.S., Marois, J., Wright, D., and Nutter, F.W. Jr. 2010. Spatial and temporal analyses to find the epicenters of soybean rust disease foci using remote sensing, GPS, and GIS technologies. Phytopathology 100:S186.
- Holah, N.S., Narvaez, D.F., Marois, J., Wright, D.C., Eggenberger, S.K., and Nutter, F.W. Jr. 2010. Plant disease detection using remote sensing and GIS. Proceedings of the 2010 ESRI User Conference, 12-16 July, San Diego, CA.
- Lu, X., Byamukama, E., Robertson, A., and Nutter, F. W., Jr. 2010. Prevalence, incidence and spatial dependence of Soybean mosaic virus in Iowa. Phytopathology 100:931-940.
- Lu, X., Robertson, A. E., and Nutter, F. W., Jr. 2010. Evaluating the importance of stem canker of soybean in Iowa. Plant Dis. 94:167-173.
- Nelson, M.E., Basart, J.P., and Nutter, F.W. Jr. 2010. Engineering payload designs for remote sensing applications for plant pathology using latex weather balloons. Phytopathology 100:S188.
- Nutter, F.W. Jr., Holah, N.S., Eggenberger, S.K., Byamukama, E., Wright, D.L., Marois, J., and Van Rij, N. 2009. Integrating GPS, GIS, and remote sensing technologies for improved crop Biosecurity. Pages 116-117 in: Proceedings of the 10th International Epidemiology Workshop, June, Cornell University, Geneva, N.Y. (ISBN).
- Nutter, F.W. Jr. 2009. Role of imagery, spatial pattern analysis, and sampling in plant pathogen forensics. Phytopathology 99:S160.
- Esker, P.D., Gibb, K.S., Dixon, P.M., and Nutter, F.W., Jr. 2007. Use of survival analysis and space-time point pattern analysis to improve the epidemiological understanding of the papaya-papaya yellow crinkle pathosystem. Plant Health Progress doi:10.1094/PHP-2007-0726-02-RS.
- Thomas, C., Coggeshall, A., Bostock, R., Luke, E., Hill, M., Creswell, T., Estep, C., Barber, D.D., Coop, L., Jepson, P., Beck, H., Nutter, F.W. Jr., and Madden, L. 2009. NPDN launches epidemiology analysis program 2009. Second National Meeting of the National Plant Diagnostic Network (NPDN), 6-10 December, Miami, FL.
- Liu, L. and Nutter, F.W., Jr. 2008. Quantifying the temporal and spatial spread of Pantoea stewartii in sweet corn. Phytopathology 98:S91 (Presented in 2007).
- Nutter, F. W., Jr., and Madden, L.V. 2008. Plant pathogens as biological weapons against agriculture. Pages 335-363 in: Beyond Anthrax: The Weaponization of Infectious Diseases. L. I. Lutwick and S. M. Lutwick, eds. Springer, NY, NY.
- Pethybridge, S.J., Esker, P.D., Dixon, P., Hay, F.S., Groom, T., Wilson, C.R., and Nutter, F.W., Jr. 2007. Quantifying loss caused by ray blight disease in Tasmanian pyrethrum fields. Plant Disease 91:1116-1121. This article was the Plant Disease Editor's pick of the month.
- Pethybridge, S.J., Hay, F., Esker, P.D, Wilson, C., and Nutter, F.W, Jr. 2007. Use of a multispectral radiometer for non-invasive assessments of foliar disease caused by ray light in pyrethrum. Plant Disease 91: 1397-1406.
- Esker, P.D., Harri, J., Dixon, P.M., and Nutter, F.W., Jr. 2006. Comparison of Models for forecasting of Stewart's disease of corn in Iowa. Plant Dis. 90: 1353-1357.
- Nutter, F.W., Jr., and Esker, P.D., and Coelho Netto, R.A. 2006. Disease assessment concepts and the advancement made in improving the accuracy and precision of plant disease data. European Journal of Plant Pathology 115: 99-103.
- Coelho Netto, R. A., and Nutter, F. W. Jr. 2005. Use of GPS and GIS technologies to map the prevalence of Moko disease of banana in the Amazonas region of Brazil. Pages: 431-436 in: 3rd International Bacterial Wilt Symposium, White River, South Africa, APS Press, St. Paul, MN.
- Nutter, F. W., Jr., and L. V. Madden. 2005. Plant diseases as a possible consequence of biological attacks. Pages 793-818 in: Biological Terrorism. R. A. Greenfield and M. S. Bronze, eds. Horizon Scientific Press, Caister Scientific Press, Norfolk, UK.
- Pethybridge, S. J., Esker, P. D., Hay, F. Wilson, C. and Nutter, Jr., F. W. 2005. Spatiotemporal description of epidemics caused by Phoma ligulicola in Tasmanian pyrethrum fields. Phytopathology 95:648-658.
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Progress 02/01/08 to 01/31/09
Outputs
OUTPUTS: This project has helped to successfully develop a GPS, web-based delivery system to geospatially-display (map) where specific plant pathogens have been detected, identified, and confirmed. Using Asian soybean rust as a model pathosystem, we were able to integrate and utilize GPS, GIS, and remote sensing technologies to locate (within 1.5 m) where Asian soybean rust was deliberately introduced into soybean plots. Using other model pathosystems, including wheat leaf rust (a fungal pathogen), Bean pod mottle virus and Soybean mosaic virus (both viral pathogens), and Stewart's disease of corn (a bacterial pathogen), we have developed sampling protocols for both early detection and attribution (forensics) to mimic similar plant pathogens that currently threaten U.S. agricultural biosecurity. We have completed Objective 3 of the project, which was to develop and integrate remote sensing, GPS, and GIS technologies to detect and correctly identify plant pathogens present in other countries before they occur in the U.S. Experiments were repeated to quantify the density of pathogen spores escaping from a diseased crop canopy (wheat) using helium-filled weather balloons equipped with a platform that housed six remotely-operated Rotorod spore samplers. This information provided new, critical information that is of tremendous value to research groups using atmospheric transport models to predict the long distance pathogen dispersal of plant pathogens. Educational materials concerning the outputs for this plant biosecurity project have been prepared for a broad audience. This information has been disseminated primarily through presentations for participants attending National Plant Diagnostic Network (NPDN) meetings, the Information Technology and Epidemiology NPDN Committees, National Soybean Rust Symposia participants, Department of Defense-Telemedicine and Advanced Technology Research Center Surveillance Workshops, and during Annual and Division Meetings of the American Phytopathological Society. Moreover, the second of two book chapters, both of which concern the use of plant pathogens as potential weapons, was published. PARTICIPANTS: Participants for which training was provided include: Lu Liu (MSc. Student in Plant Pathology), Emmanuel Byamukama (Ph.D. student in Plant Pathology), Dr. Noha Holah (Plant Pathology), Andrew Gougherty (MSc. student in graduate program in Ecology and Evolutionary Biology), David Hagopian and Stephanie Konopka (Undergraduate Research Assistants), and one summer intern in the ISU Program for Women in Science and Engineering. Scientists who collaborated on the project were Mark Gleason, Professor of Plant Pathology, S. Elwynn Taylor (Agricultural Meteorologist, Department of Agronomy), John Basart (Professor, Computer and Electrical Engineering), and Will Baldwin (Information Technology, Associate Professor, Kansas State University). TARGET AUDIENCES: The primary target audience for the project includes Diagnosticians, Extension Specialists, and Researchers involved in the mission and activities of the National Plant Diagnostic Network (NPDN), which was established in 2002 by USDA-CSREES to serve as an early warning system for the detection of plant pathogens and pests that threaten U.S. agricultural biosecurity. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
This project has brought about new research collaborations with Dr. Scott Isard, The Pennsylvania State University, and with the Western Weather Working Group (WWWG), a group funded by the Western IPM Center. These new collaborations will relate to Objective 4 (atmospheric transport of plant pathogens), and Objective 5 (development of weather-based GIS disease/pest models to estimate the risk of infection/establishment beyond the point of initial detection). Outcomes also include the formation of a new weather working group (The North Central Weather Working Group, NCWWG), funded by the North Central IPM Center as of February, 2008. Outputs from the WWWG and NCWWG activities include collaboration on a joint publication on the evaluation and comparison of methods to model leaf wetness duration as affected by different crop canopies and climatic regions of the world (submitted). The accurate estimation of leaf wetness duration using models is a critical component of many disease warning systems. Experiments concerning the temporal and spatial spread of plant pathogens deliberately vs. naturally introduced into three model cropping systems (corn, soybeans, wheat) provided critical information on how to sample crops for the early detection of plant pathogens in U.S. crops. We have also characterized the changes in spatial patterns of plant pathogens over time and have addressed how this affects sampling for attribution. Proof of concept has been clearly demonstrated in developing integrated remote sensing, GPS, and GIS technologies to detect and to accurately identify the specific causes(s) of plant disease(s) in crops. This finding changes the paradigm away from searching for pathogen- specific spectral signatures, to a new paradigm that uses pathogen-specific temporal and spatial signatures to detect and identify specific plant pathogens with satellite imagery. In 2008, methods were refined to quantify spore density in the atmosphere in vertical (above) and horizontal (down wind) directions relative to a diseased crop area. These were developed using small helium weather balloons, each equipped with 6 remotely-operated Rotorod spore samplers. Environmental variables (i.e. temperature, wind direction, vertical wind speed, horizontal wind speed, and relative humidity) affecting spore release (removal) and escape from diseased crop canopies, as well as elevation and GPS location, were all monitored and remotely recorded in real time. Data from this study fills knowledge gaps and will allow researchers to more accurately predict the density of pathogen spores escaping from diseased crop canopies, as well as the long-distance dispersal of spores.
Publications
- Byamukama, E., Robertson, A., and Nutter, F.W., Jr. 2008. Quantification of temporal and spatial dynamics of Bean pod mottle virus at different spatial scales. Phytopathology 98:S189.
- Byamukama, E., Robertson, A., and Nutter, F.W., Jr. 2008. Within-field spatial and temporal analysis of Bean pod mottle virus in Iowa. Phytopathology 98:S29.
- Kilburg, B. J., Byamukama, E., and Nutter, F.W., Jr. 2008. Quantifying the infectious period of bean leaf beetles and the latent period of Bean pod mottle virus in soybean. Department of Energy Science and Energy Research Challenge Competition, 9-10 November, Department of Energy Science National Research Laboratory, Oak Ridge, Tennessee.
- Liu, L., Block, C., and Nutter, F.W., Jr. 2008. Quantifying and comparing the aggressive ness of Pantoea stewartii isolates under different temperatures. Phytopathology 98:S92.
- Liu, L. and Nutter, F.W., Jr. 2008. Quantifying the temporal and spatial spread of Pantoea stewartii in sweet corn. Phytopathology 98:S91 (Presented in 2007). Lu, X., Robertson, A., Byamukama, E., and Nutter, F.W., Jr. 2008. Comparison of the prevalence and incidence of soybean mosaic virus in Iowa soybean fields during 2005 to 2007. Phytopathology 98:S94.
- Lu, X., Robertson, A., and Nutter, F.W., Jr. 2008. Quantification and comparison of components of aggressiveness of isolates of Diaporthe phaseolorum var. caulivora collected in Iowa soybean fields. Phytopathology 98:S95.
- Lutz, A.L., Liu, L., and Nutter, F.W., Jr. 2008. Quantifying the infectious period, aggressiveness, and spatial spread of Pantoea Stewartii. Iowa State University Program for Women in Science and Education Poster Presentations, 25 July, Molecular Biology Building, Iowa State University, Ames, IA.
- Nutter, F.W., Jr. and Byamukama, E. 2008. Modeling yield loss based on time of virus detection: a geostatistical, quadrat-based approach. Phytopathology 98:S189.
- Byamukama, E., Robertson, A., and Nutter, F.W., Jr. 2008. Spatial and temporal spread of Bean pod mottle virus (BPMV) and relationship between time of BPMV infection and soybean yield. Phytopathology 98:S202.
- Gongora-Canul, C., Nutter, F. W. Jr., and L. F. S. Leandro. 2008. Temporal dynamics of root and foliar symptoms of soybean sudden death syndrome at different inoculum densities. Southern Soybean Disease Workers 35th Annual Meeting, 12-13 March, Pensacola, Fl.
- Nutter, F.W., Jr., and L.V. Madden. 2008. Plant pathogens as biological weapons against agriculture. Pages 335-363 in: Bioterror: The Weaponization of Infectious Disease. L.I. Lutwick and S.M. Lutwick, eds. The Human Press Inc., Totowa, NJ.
- Pethybridge, S.J., Hay, F.S., Esker, P.D., Gent, D.H., Wilson, C.R., Groom, T., and Nutter, F.W., Jr. 2008. Disease of pyrethrum in Tasmania: Challenges and prospects for management. Plant Disease 92:1260-1272.
- Pethybridge, S.J., Hay, F., Esker, P.D., Groom, T., Wilson, C., Nutter, F.W., Jr. 2008. Visual and radiometric assessments for yield losses caused by ray blight in pyrethrum. Crop Science 48:343-352.
- Byamukama, E., Robertson, A., and Nutter, F.W., Jr. 2008. Bean pod mottle virus spatial pattern and its relationship with bean leaf beetle winter morality. Phytopathology 98:S202.
- Byamukama, E., Robertson, A., and Nutter, F.W., Jr. 2008. Integrating GPS, GIS, and geostatistics for risk assessment of Bean pod mottle virus in Iowa. Phytopathology 98:S28.
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Progress 02/01/07 to 01/31/08
Outputs
OUTPUTS: This project has successfully developed a global positioning system (GPS), web-based delivery system to geospatially-display (map) where specific plant pathogens have been detected, identified, and confirmed. Using wheat leaf rust (fungal pathogen), bean pod mottle virus (viral pathogen), and Stewart's disease of corn (bacterial pathogen), as model pathosystems, we are developing sampling protocols for the early detection and attribution (forensics) for similar plant pathogens that currently threaten U.S. agricultural biosecurity. We have completed Objective 3 of the project, which was to develop and integrate remote sensing, GPS, and GIS technologies to detect and correctly identify plant pathogens present in other countries before they occur in the U.S. Experiments to quantify the density of pathogen spores escaping from a diseased crop canopy (wheat) were quantified using helium weather balloons equipped with a platform that housed six remotely-operated Rotorod spore
samplers. This information has provided critical information that is of tremendous value to research groups using atmospheric transport models to predict the long distance pathogen dispersal of plant pathogens. Educational materials concerning the outputs for this plant biosecurity project have been prepared for a broad audience and this information has been disseminated primarily through presentations for participants attending National Plant Diagnostic Network (NPDN) meetings, the Information Technology and Epidemiology NPDN Committees, National Soybean Rust Symposia participants, Department of Defense-Telemedicine and Advanced Technology Research Center Surveillance Workshops, and during Annual and Division Meetings of the American Phytopathological Society. Moreover, two book chapters (one published, one in press) concerning the use of plant pathogens as potential weapons have been produced by this project.
PARTICIPANTS: Participants for which training was provided include Lu Liu (MSc. student in Plant Pathology), Emmanuel Byamukama (Ph.D. student in Plant Pathology), Khalil Ahmad (MSc. student in Engineering/Plant Pathology), Babk Safir (Ph.D. student in Agronomy), Michael Mansini (Undergraduate Research Assistant), two summer interns in the ISU Women in Science and Engineering Program (Ashley Bullard and Alex Cagneaux), and two students in the ISU George Washington Carver Minority Summer Internship Program (Geoffrey Turner and Chase Turner). Scientists who collaborated on the project were Mark Gleason, Professor of Plant Pathology, S. Elwynn Taylor (Agricultural Meteorologist, Department of Agronomy), John Basart (Professor, Computer and Electrical Engineering), and Will Baldwin (Information Technology, Associate Professor, Kansas State University).
TARGET AUDIENCES: The primary target audience for the project are Diagnosticians, Extension Specialists, and Researchers involved in the mission and activities of the National Plant Diagnostic Network (NPDN) that was established in 2002 by USDA-CSREES to serve as an early warning system for the detection of plant pathogens and pests that threaten U.S. agricultural biosecurity.
Impacts
This project has brought about new research collaborations with the Western Weather Working Group (WWWG), funded by the Western IPM Center, to address critical issues related to Objectives 4 (atmospheric transport of plant pathogens), and 5 (development of weather-based GIS disease/pest models to estimate the risk of infection/establishment beyond the initial detection) of this project. Outcomes also include the formation of a new weather working group (The North Central Weather Working Group, NCWWG), funded by the North Central IPM Center as of February, 2008. Outputs from the WWWG and NCWWG activities include collaboration on a joint publication on the evaluation and comparison of methods to model leaf wetness duration as affected by different crop canopies and climatic regions of the world. The accurate estimation of leaf wetness duration using models is a critical component of many disease warning systems. Experiments concerning the temporal and spatial spread of
plant pathogens deliberately vs. naturally introduced into three model cropping systems (corn, soybeans, wheat) provided critical information on how to sample crops for the early detection of plant pathogens in U.S. crops. We have also characterized the changes in spatial patterns of plant pathogens over time and have addressed how this affects sampling for attribution. Proof of concept has been clearly demonstrated in developing integrated remote sensing, GPS, and GIS technologies to detect and to accurately identify the specific cause(s) of plant disease(s) in crops. This finding changes the paradigm of searching for pathogen-specific spectral signatures, to a new paradigm that uses pathogen-specific temporal and spatial signatures to detect and identify plant pathogens with satellite imagery. Methods to quantify the density of spores in the atmosphere vertically above, and horizontally (down wind) from a diseased crop, were developed using small helium weather balloons that each
housed a payload of 6 remotely-operated Rotorod spore samplers. Environmental variables affecting spore release (removal) and escape from diseased crop canopies (i.e., temperature, wind direction, vertical wind speed, horizontal wind speed, and relative humidity), as well as elevation and GPS location, were all monitored and remotely recorded in real time. Data from this study fills the knowledge gaps that will allow researchers to more accurately predict the density of pathogen spores escaping from diseased crop canopies, as well as, the long-distance dispersal of spores.
Publications
- Thomas, C., Luke, E., Hill, M., Coggeshall, A., Beck, H., Barber, D., Jr., Baldwin, W., Estep, C., Tidwell, T., Coop, L., Luh, H., and Nutter, F.W., Jr. 2007. The NPDN epidemiology committee. Page 19 in: National Plant Diagnostic Network National Meeting, Orlando, Florida. 33 p.
- Ahmad, K., Basart, J., Rij, N.V., and Nutter, F.W., Jr. 2007. Analysis of the spatial and temporal spread of Asian soybean rust using GPS, GIS, and remote sensing satellite technologies. Iowa Geographic Information Council (IGIC) Annual Conference, 23-25 April, Sioux City, IA. (Oral Presentation)
- Ahmad, K., Basart, J., Rij, N.V., and Nutter, F.W., Jr. 2007. Development of early warning systems to improve US crop biosecurity. Iowa Geographic Information Council (IGIC) Annual Conference, 23-25 April, Sioux City, IA. (This poster was awarded First Place out of 40+ posters presented at the Iowa Geographic Information Council (IGIC) Conference).
- Ahmad, K, van Rij, N., Basart, J., and Nutter, F.W., Jr. 2007. Detecting and quantifying the temporal and spatial dynamics of plant pathogens using GPS, GIS, and remote-sensing technologies. Phytopathology 97:S137.
- Byamukama, E., Lu, X., Robertson, A., Nutter, F.W., Jr. 2007. Temporal and spatial patterns of Bean pod mottle virus at the county and field scales in Iowa. Department of Plant Pathology, Iowa State University, Ames, IA 50011. Phytopathology 97:S160.
- Byamukama, E., Robertson, A., and Nutter, F.W., Jr. 2007. Spatial patterns of bean pod mottle virus of soybean in Iowa. Page 30 in: Food Safety and Public Health: Production, Distribution, and Policy, Iowa State University Institute for Food Safety and Security Symposium, 12 April, Ames, IA.
- Byamukama, E., Robertson, A., and Nutter, F.W., Jr. 2007. Use of temporal and spatial data to quantify impact of bean pod mottle virus on soybean yield. Page 31 in: Food Safety and Public Health: Production, Distribution, and Policy, Iowa State University Institute for Food Safety and Security Symposium, 12 April, Ames, IA.
- Lu, X., Robertson, A.E., Byamukama, E., and Nutter, F.W., Jr. 2007. The prevalence, incidence, and spatial dependence of soybean mosaic virus in Iowa. Phytopathology 97:S68.
- Nutter, F.W., Jr. 2007. Model validation: what comes under the umbrella of validation concepts for pathogen/disease detection and forecasting models. Phytopathology 97:S147.
- Nutter, F.W., Jr. 2007. Use of GPS, GIS, and Remote Sensing Technologies in Plant Disease Management. 2nd European Conference on Precision Agriculture, 10-12 October, Bonn, Germany.
- Nutter, F.W., Jr., Ahmad, K., VanRij, N., and Basart, J. 2007. Detection of Asian soybean rust disease gradients in soybean using high resolution satellite imagery. Phytopathology 97:S85.
- Nutter, F.W., Jr. Byamukama, E., Robertson, A. 2007. Use of GPS, GIS, and geostatistics to develop pre-plant virus disease prediction models. 10th Plant Virus Epidemiology Symposium, 15-19 Oct. 07, ICRISAT, Patancheru, India.
- Stedman, J., Robertson, A., Byamukama, E., Nutter, F.W., Jr. 2007. Relationship between percent mortality predictions for bean leaf beetle overwintering populations and incidence of bean pod mottle virus in Iowa. Phytopathology 97:S110 (Jana Stedman was awarded the American Phytopathological Society Frank Howard Undergraduate Research Award for this project).
- Thomas, C., Cresswell, T., Luke, E., Nutter, F.W., Jr., Lanier, W., Durgy, R., Bryne, J., Tidwell, T., and Draper, M. 2007. Expansion of data collection capabilities for the National NPDN database. Page 26 in: National Plant Diagnostic Network National Meeting, Orlando, Florida. 33 p.
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Progress 02/01/06 to 01/31/07
Outputs
In year two of this project, we have made tremendous strides for Objectives 1-3. These were to establish Real-Time, Web-Based, GIS Mapping Tools (Objective 1), to Develop Pest Sampling and Assessment Protocols for Use by First Responders (Objective 2), and to Develop Remote Sensing Technologies That Utilize Temporal and Spatial Pattern Analyses to Detect and Correctly Diagnose Emerging Threats from Plant Pathogens/Pests (Objective 3). After obtaining, processing, and analyzing satellite imagery of soybean fields in South Africa (April 2006), we successfully detected and quantified disease gradients of Asian Soybean Rust, as well as the temporal and spatial changes in green leaf area index as affected by this disease. Moreover, we have detected disease foci of Asian soybean rust and have quantified the temporal and spatial expansion of rust foci. More importantly, we were able to differentiate rust foci from foci caused by Cercospora blight of soybean. We are currently
working on adding GIS atmospheric transport and weather GPS mapping tools to support the USDA-CREES National Plant Diagnostic Network (Objectives 4 and 5).
Impacts
For more than 40 years, the single factor that has most limited the application of remote sensing for improved disease and pest management has been the inability to correctly diagnose (identify) the specific diseases and pests responsible for causing crop injury and lowering crop yields. By detecting and quantifying the temporal and spatial changes of sunlight reflected from crop canopies (as opposed to searching for unique spectral signatures), we have made a tremendous science breakthrough by successfully detecting and quantifying the expansion rate and shape of disease foci caused by Asian soybean rust. Most important is that we now have the capability to differentiate one plant disease from all others that infect soybeans using satellite imagery.
Publications
- Nutter, F.W. 2006. Applications of GIS and geostatistics to epidemics in natural systems. Phytopathology 96:S144.
- Nutter, F.W., Jr., Robertson, A.E., Khalil, A., and Esker, P.D. 2006. Development of mapping tools to generate disease risk contour maps depicting prevalence, incidence, and severity of soybean diseases in Iowa in 2005. Phytopathology 96:S86.
- Nutter, F. W., Jr., and L. V. Madden. 2006. Plant pathogens as biological weapons against agriculture. Pages xx-xx in: Bioterror: The Weaponization of Infectious Disease. L. I. Lutwick and S. M. Lutwick, eds. The Human Press Inc., Totowa, NJ. (In press).
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Progress 02/01/05 to 01/31/06
Outputs
The first Project Objective "Establish a Real-Time, Web-Based GIS Reporting System for New, Emerging and Endemic Diseases" has been accomplished. Diagnostic records originating from Plant Disease Clinics can be shared, communicated and mapped via the USDA- National Plant Diagnostic Network (NPDN). We are currently training project staff and graduate students to further enhance NPDN-GIS capabilities. We are working to develop and incorporate atmospheric transport models to map past, present, and future spatial dissemination of plant pathogens/pests (Objective 4), and to develop weather-based disease prediction/pest establishment risk maps (Objective 5). Satellite imagery of soybean fields/sentinel plots infected with Asian soybean rust were obtained in 2005 from soybean fields in Georgia, Alabama, and Florida. We are currently analyzing these images to develop algorithms to detect and monitor the geospatial and temporal spread of soybean rust, and to develop
disease/pest injury models to estimate economic impacts of soybean rust epidemics on soybean (Objectives 2 & 3).
Impacts
A vital prerequisite for the effective mitigation and management of introduced plant pathogens and pests is the availability of reliable, real-time knowledge concerning the location and geographic distribution of threatening plant pathogens/pests. The successful development of a real-time, web-based capability to map disease/pest occurrence from plant disease/pest diagnostic records (via the NPDN), is a critical first step towards enhancing the biosecurity of US agriculture. Moreover, the capability to detect and diagnose threatening plant pathogens and pests that are presently affecting agricultural crops in other countries before such threatening agents are introduced into the US (accidentally, deliberately, or by natural events) would further enhance US agricultural biosecurity by providing early warnings/indications of potential threats.
Publications
- Guan, J., Kaiser, M. S., Caragea, P. C., Tylka, G. L., and Nutter, F. W., Jr. 2005 Improving the relationship between IKONOS satellite image intensity and soybean yield as affected by SCN using geostatistics. Phytopathology 95:S162.
- Moreira, A. J. A., Guan, J., Tylka, G. L., and Nutter, F. W., Jr. 2005. Use of remote sensing, geographic information systems, and spatial statistics to assess soybean yield and soybean cyst nematode (SCN) populations in soybean fields. Phytopathology 95:S164.
- Nutter, F.W., Jr. 2005. Post-introduction mapping of plant virus spread using GPS and real-time GIS technologies. Page 62 in: IX International Plant Virus Epidemiology Symposium: Applying Epidemiological Research to Improve Virus Disease Management. 4-7 April, International Potato Center, Lima, Peru.
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