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Crop biomass and humidity related factors reflect the spatial distribution of phytopathogenic Fusarium fungi and their mycotoxins in heterogeneous fields and landscapes

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Abstract

Fusarium head blight (FHB) is a global problem in small-grains agriculture that results in yield losses and, more seriously, produces harmful toxins that enter the food chain. This study builds on previous research identifying within-field humidity as an important factor in infection processes by Fusarium species and its mycotoxin production. Environmental variables describing topographic control of humidity (TWI), soil texture and related moisture by electrical conductivity (ECa), and canopy humidity by density (NDVI) were explored in their relationship to the fungal infection rates, the abundance of trichothecene-producing Fusarium spp. as determined by TRI 6 gene copies and mycotoxin accumulation. Field studies were performed at four field sites in northeastern Germany in 2009 and 2011. In the wet year 2011, a high Fusarium infection rate resulted in a high abundance of trichothecene-producing fungi as well as high concentrations of mycotoxins. Simultaneously, Fusarium spp. inhibited the development of other filamentous fungi. Overall, a very heterogeneous distribution of pathogen infections and mycotoxin concentrations were displayed in each field in each landscape. The NDVI serves as an important predictor of the occurrence of phytopathogenic Fusarium fungi and their mycotoxins in a field and landscape scale. In addition, the ECa reflects the distribution of the most frequently occurring mycotoxin deoxynivalenol within the fields and landscapes. In all cases, TWI was not found to be a significant variable in the models. All in all, the results extend our knowledge about suitable indicators of FHB infection and mycotoxin production within the field.

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References

  • Bateman, G. L., Gutteridge, R. J., Gherbawy, Y., Thomsett, M. A., & Nicholson, P. (2007). Infection of stem bases and grains of winter wheat by Fusarium culmorum and F. graminearum and effects of tillage method and maize-stalk residues. Plant Pathology, 56, 604–615.

    Article  Google Scholar 

  • Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, 57, 289–300.

    Google Scholar 

  • Berntoft, A., Torp, M., Clasen, P. E., Löes, A. K., & Kristoffersen, A. B. (2012). Influence of agronomic and climatic factors on Fusarium infestation and mycotoxin contamination in cereals in Norway. Food Additives & Contaminants, 29, 1129–1140.

    Article  Google Scholar 

  • Bottalico, A., & Perrone, G. (2002). Toxigenic Fusarium species and mycotoxins associated with head blight in small-grain cereals in Europe. European Journal of Plant Pathology, 108, 611–624.

    Article  CAS  Google Scholar 

  • Buchanan, B. P., Fleming, M., Schneider, R. L., Richards, B. K., Archibald, J., Qui, Z., et al. (2014). Evaluating topographic wetness indices across central New York agricultural landscapes. Hydrology and Earth System Sciences, 18, 3279–3299.

    Article  Google Scholar 

  • Byamukama, E., Robertson, A. E., & Nutter, F. W, Jr. (2010). Quantification of temporal and spatial dynamics of Bean pod mottle virus at different spatial scales. Plant Health Progress. doi:10.109.1094/PHP-2010-0526-03-SY.

    Google Scholar 

  • Champeil, A., Doré, T., & Fourbet, J. F. (2004a). Fusarium head blight: epidemiological origin of the effects of cultural practices on head blight attacks and the production of mycotoxins by Fusarium in wheat grains. Plant Science, 166, 1389–1415.

    Article  CAS  Google Scholar 

  • Champeil, A., Fourbet, J. F., Doré, T., & Rossignol, L. (2004b). Influence of cropping system on Fusarium head blight and mycotoxin levels in winter wheat. Crop Protection, 23, 531–537.

    Article  CAS  Google Scholar 

  • Corwin, D. L., & Lesch, S. M. (2005). Apparent soil electrical conductivity measurements in agriculture. Computers and Electronics in Agriculture, 46, 11–43.

    Article  Google Scholar 

  • Dänicke, S., Goyarts, T., Valenta, H., Razzari, E., & Böhm, J. (2004). On the effects of deoxynivalenol (DON) in pig feed on growth performance, nutrients utilization and DON metabolism. Journal of Animal Feed Science, 13, 539–556.

    Google Scholar 

  • Delin, S. (2004). Within-field variations in grain protein content—Relationships to yield and soil nitrogen and consistency in maps between years. Precision Agriculture, 5, 565–577.

    Article  Google Scholar 

  • Durlesser, H. (1999). Bestimmung der Variation bodenphysikalischer Parameter in Raum und Zeit mit elektromagnetischen Induktionsverfahren. Dissertation, TU München. FAM-Bericht 35. Aachen: Shaker. ISBN: 3-8265-6180-5.

  • EC 2006. European Commission Regulation No 1881/2006: setting maximum levels for certain contaminants in foodstuffs. Official Journal of the European Union.

  • Helsel, D. R. (2005). Nondetects and data analysis: statistics for censored environmental data. New York: Wiley.

    Google Scholar 

  • Hengl, T., & Reuter, R. I. (2009). Geomorphometry: Concepts, Software, Applications. Developments in Soil Science (Vol. 33). Amsterdam: Elsevier.

    Google Scholar 

  • Holah, N. S., Marois, J., Wright, D., & 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.

    Google Scholar 

  • King, R., Urban, M., Hammond-Kosack, M. C. U., Hassani-Pak, K., & Hammond-Kosack, K. E. (2015). The completed genome sequence of the pathogenic ascomycete fungus Fusarium graminearum. BMC Genomics, 16, 544.

    Article  PubMed  PubMed Central  Google Scholar 

  • Koch, H. J., Pringas, C., & Maerlaender, B. (2006). Evaluation of environmental and management effects on Fusarium head blight infection and deoxynivalenol concentration in the grain of winter wheat. European Journal of Agronomy, 24, 357–366.

    Article  CAS  Google Scholar 

  • Korn, U., Müller, T., Ulrich, A., & Müller, M. E. H. (2011). Impact of aggressiveness of Fusarium graminearum and F. culmorum isolates on yield parameters and mycotoxin production in wheat. Mycotoxin Research, 27, 195–206.

    Article  CAS  PubMed  Google Scholar 

  • Koszinski, S., Gerke, H. H., Hierold, W., & Sommer, M. (2013). Geophysical-based modeling of a kettle hole catchment of the morainic soil landscape. Vadose Zone Journal. doi:10.2136/vzj2013.02.0044.

    Google Scholar 

  • Lacey, J., Bateman, G. L., & Mirocha, C. J. (1999). Effects of infection time and moisture on development of ear blight and deoxynivalenol production by Fusarium spp. in wheat. Annals of Applied Biology, 134, 277–283.

    Article  CAS  Google Scholar 

  • Lee, L. (2013). Nondetects and data analysis for environmental data. R-package version 1.5–6. Retrieved http://cran.r-project.org/web/packages/NADA/NADA.pdf.

  • McBratney, A. B., Minasny, B., & Whelan, B. M. (2005). Obtaining “useful” high-resolution soil data from proximally-sensed electrical conductivity/resistivity (PSEC/R) surveys. In J. V. Stafford (Ed.), Precision Agriculture, Proceedings of the 5th European Conference on Precision Agriculture (pp. 503–510). Wageningen: Wageningen Academic Publishers.

    Google Scholar 

  • Mirocha, C. J., Xie, W. P., Wilcoxson, R. D., Woodward, R. P., Etebarian, R. H., & Behele, G. (1995). Production of trichothecene mycotoxins by Fusarium graminearum and Fusarium culmorum on barley and wheat. Mycopathologia, 128, 19–23.

    Article  Google Scholar 

  • Müller, M. E. H., Brenning, A., Verch, G., Koszinski, S., & Sommer, M. (2010). Multifactorial spatial analysis of mycotoxin contamination of winter wheat at the field and landscape scale. Agriculture, Ecosystems & Environment, 139, 245–254.

    Article  Google Scholar 

  • Müller, M. E. H., Koszinski, S., Brenning, A., Verch, G., Korn, U., & Sommer, M. (2011). Within-field variation of mycotoxin contamination of winter wheat is related to indicators of soil moisture. Plant and Soil, 342, 289–300.

    Article  Google Scholar 

  • Nelson, P. E., Toussoun, T. A., & Mararas, W. F. O. (1983). Fusarium species. An illustrated manual for identification. London: Pennsylvania State University Press.

    Google Scholar 

  • Nirenberg, H. I. (1976). Untersuchungen über die morphologische und biologische Differenzierung in der Fusarium Sektion Liseola. Mitteilungen der Biologischen Bundes- Anstalt für Land- und Forstwirtschaft, 169, 1–117.

    Google Scholar 

  • Nirenberg, H. I. (1990). Recent advances in the taxonomy of Fusarium. Studies in Mycology, 32, 91–101.

    Google Scholar 

  • Norng, S., Pettitt, A. N., Kelly, R. M., Butler, D. G., & Strong, W. M. (2005). Investigating the relationship between site-specific yield and protein of cereal crops. Precision Agriculture, 6, 41–51.

    Article  Google Scholar 

  • Nutter, F. W, Jr. (2009). Role of imagery, spatial pattern analysis, and sampling in plant pathogen forensics. Phytopathology, 99, S160.

    Article  Google Scholar 

  • Nutter, F. W, Jr, Van Rij, N., Eggenberger, S. K., & Holah, N. (2010). Spatial and temporal dynamics of plant pathogens. In E.-C. Oerke, G. Gerhards, G. Menz, & R. A. Sikora (Eds.), Precision crop protection—the challenge and use of heterogeneity (pp. 27–50). New York: Springer.

    Chapter  Google Scholar 

  • Oerke, E.-C., Meier, A., Dehne, H. W., Sulyok, M., Krska, R., & Steiner, U. (2010). Spatial variability of Fusarium head blight pathogens and associated mycotoxins in wheat crops. Plant Pathology, 59, 671–682.

    Article  CAS  Google Scholar 

  • Oerke, E.-C., & Steiner, U. (2010). Potential of digital thermography for disease control. In E.-C. Oerke, G. Gerhards, G. Menz, & R. A. Sikora (Eds.), Precision crop protection—the challenge and use of heterogeneity (pp. 167–182). New York: Springer.

    Chapter  Google Scholar 

  • Oldenburg, E., Brunotte, J., & Weinert, J. (2007). Strategies to reduce DON contamination of wheat with different soil tillage and variety systems. Mycotoxin Research, 23, 73–77.

    Article  CAS  PubMed  Google Scholar 

  • Pebesma, E. J. (2004). Multivariable geostatistics in S: the gstat package. Computers & Geosciences, 30, 683–699.

    Article  Google Scholar 

  • Pinheiro, J., Bates, D., DebRoy, S., & Sarkar, D. (2013). nlme: Linear and Nonlinear Mixed Effects Models. R-package version 3.1–110.

  • Placinta, C. M., D’Mello, J. P. F., & Macdonald, A. M. C. (1999). A review of worldwide contamination of cereal grains and animal feed with Fusarium mycotoxins. Animal Feed Science and Technology, 78, 21–37.

    Article  CAS  Google Scholar 

  • Pringle, M. J., Bishop, T. F. A., Lark, R. M., Whelan, B. M., & McBratney, A. B. (2010). Geostatistical applications for precision agriculture. In M. A. Oliver (Ed.), The analysis of spatial experiments. Dordrecht: Springer.

    Chapter  Google Scholar 

  • Ricotta, C., Avena, G., & De Palma, A. (1999). Mapping and monitoring net primary productivity with AVHRR NDVI time-series: Statistical equivalence of cumulative vegetation indices. ISPRS Journal of Photogrammetry and Remote Sensing, 54, 325–331.

    Article  Google Scholar 

  • Rotter, B., Prelusky, D. B., & Pestka, J. J. (1996). Toxicology of deoxynivalenol (vomitoxin). Journal of Toxicology and Environmental Health, 48, 1–34.

    Article  CAS  PubMed  Google Scholar 

  • Rouse, J.W., Haas, R.H., Schell, J.A., & Deering, D.W. (1974). Monitoring vegetation systems in the great plains with ERTS. In Proceedings, Third Eastern Resources Technology Satellite-1 Symposium, Greenbelt: NASA SP-351, pp. 3010–3017.

  • Samson, R. A., Hoekstra, E. S., Frisvad, J. C., & Filtenborg, O. (2002). Introduction to Food- and Airborne Fungi (6th ed.). Utrecht: Centraalbureau Voor Schimmelcultures.

    Google Scholar 

  • Sobrova, P., Adam, V., Vasatkova, A., Beklova, M., Zeman, L., & Kizek, R. (2010). Deoxynivalenol and its toxicity. Interdisciplinary Toxicology, 3, 94–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Söderström, M., Börjesson, T., Roland, B., & Stadig, H. (2015). Modelling within-field variations in deoxynivalenol (DON) content in oats using proximal and remote sensing. Precision Agriculture, 16, 1–14.

    Article  Google Scholar 

  • Sørensen, R., Zinko, U., & Seibert, J. (2006). On the calculation of the topographic wetness index: evaluation of different methods based on field observations. Hydrology and Earth System Sciences, 10, 101–112.

    Article  Google Scholar 

  • R Core Team (2013). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. http://www.R-project.org.

  • Tucker, C. J., Vanpraet, C., Sharman, M., & Vanittersum, G. (1985). Satellite remote sensing of total herbaceous biomass production in the Senegalese Sahel 1980–1984. Remote Sensing of Environment, 17, 233–249.

    Article  Google Scholar 

  • Urban, M., & Hammond-Kosack, K. E. (2013). Molecular genetics and genomic approaches to explore Fusarium infection of wheat floral tissu. In D. W. Brown & R. H. Proctor (Eds.), Fusarium Genomics, Molecular and Cellular Biology (pp. 43–79). Norfolk: Caister Academic Press.

    Google Scholar 

  • Ver Hoef, J. M., Cressie, N., Fisher, R. N., & Case, T. J. (2001). Uncertainty in spatial linear models for ecological data. In C. T. Hunsacker, M. F. Goodchild, M. A. Friedl, & T. J. Case (Eds.), Spatial Uncertainty in Ecology: Implications for Remote Sensing and GIS Applications (pp. 214–237). New York: Springer.

    Chapter  Google Scholar 

  • Visconti, A., Minervini, F., Solfrizzo, M., Bottalico, C., & Lucivero, G. (1992). Toxicity of some Fusarium section Sporotrichiella strains in relation to mycotoxin production. Applied and Environmental Microbiology, 58, 769–772.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Webster, R., & Oliver, M. A. (2001). Geostatistics for Environmental Scientists (p. 271). Chichester: Wiley.

    Google Scholar 

  • Wessolek, G., & Asseng, S. (2006). Trade-off between wheat yield and drainage under current and climate change conditions in northeast Germany. European Journal of Agronomy, 24, 333–342.

    Article  Google Scholar 

  • Wiegand, C. L., Maas, S. J., Aase, J. K., Hatfield, J. L., Pinter, P. J, Jr, Jackson, R. D., et al. (1992). Multisite analyses of spectral-biophysical data for wheat. Remote Sensing of Environment, 42, 1–21.

    Article  Google Scholar 

  • Windels, C. E. (2000). Economic and social impacts of Fusarium head blight: changing farms and rural communities in the Northern Great Plains. Phytopathology, 90, 17–21.

    Article  CAS  PubMed  Google Scholar 

  • Wong, M. T. F., Wittwer, K., Oliver, Y. M., & Robertson, M. J. (2010). Use of EM38 and Gamma Ray Spectrometry as complementary sensors for high-resolution soil property mapping. In R. A. Viscarra Rossel, A. B. McBratney, B. Minasny, & B. Minasny (Eds.), Proximal Soil Sensing. Progress in Soil Science I (pp. 343–349). New York: Springer. doi:10.1007/987-90-481-8859-8_1.

    Chapter  Google Scholar 

  • WRB IUSS Working Group (2006). World Reference Base for Soil Resources. World Soil Resources Report No. 103. Rome: FAO, ISBN: 92-5-105511-4.

  • Xu, X. M., Monger, W., Ritieni, A., & Nicholson, P. (2007). Effect of temperature and duration of wetness during initial infection periods on disease development, fungal biomass and mycotoxin concentrations on wheat inoculated with single, or combination of, Fusarium species. Plant Pathology, 56, 943–956.

    Article  CAS  Google Scholar 

  • Xu, X. M., Parry, D. W., Nicholson, P., Thomsett, M. A., Simpson, D., Edwards, S. G., et al. (2008). Within-field variability of Fusarium head blight pathogens and their associated mycotoxins. European Journal of Plant Pathology, 120, 21–34.

    Article  CAS  Google Scholar 

  • Zadoks, J. C., Chang, T. T., & Konzak, C. F. (1974). A decimal code for the growth stages of cereals. Weed Research, 14, 415–421.

    Article  Google Scholar 

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Acknowledgments

RapidEye data obtained from the RapidEye Science Archive (RESA) were provided by the German Aerospace Center (DLR) with funds from the German Federal Ministry of Economics and Energy (original proposals 278 and 457). The authors are grateful to Kathrin Jürgens (Department of Landscape Information Systems ZALF) for constructing the precipitation map and to Lidia Völker (Institute of Soil Landscape Research ZALF) for deriving the TWI values. We thank Martina Peters, Grit von der Waydbrink and Sigune Weinert for their excellent technical assistance. The farmer’s support at Dedelow, Falkenhagen, Pasenow and Gross Miltzow is highly appreciated.

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Müller, M.E.H., Koszinski, S., Bangs, D.E. et al. Crop biomass and humidity related factors reflect the spatial distribution of phytopathogenic Fusarium fungi and their mycotoxins in heterogeneous fields and landscapes. Precision Agric 17, 698–720 (2016). https://doi.org/10.1007/s11119-016-9444-y

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