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Precision Crop Protection - the Challenge and Use of Heterogeneity pp 135–149Cite as

Detection of Fungal Diseases Optically and Pathogen Inoculum by Air Sampling

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Abstract

Practical solutions to measure temporal and spatial differences in the epidemics of specific fungal plant diseases are described here. For diseases that develop from widespread airborne inoculum , timing of disease control methods are key. Air sampling , integrated with appropriate diagnostic methods can be used to identify and quantify the presence of pathogen inoculum in order to guide spray decisions. Where diseases are already established but with spatially variable severity (disease foci ), spatially selective spraying of crops is possible using different optical disease detection methods and knowledge of pathogen biology to estimate an area of latent (invisible but developing) infection around disease foci. Spatially-selective spraying mediated by optical sensors may also be beneficial when there are crop patches that have low yield potential due to other factors such as poor emergence, moisture or nutrient stress, or soil compaction. Precision agriculture methods to improve the efficiency of fungicide applications in terms of timing and selective spatial application can optimise the use of fungicides in integrated crop production systems to provide the lowest environmental impact per unit of produce while maintaining a high protection efficacy.

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Acknowledgements

We thank the EC Quality of Life Programme-Framework V, which funded the OPTIDIS project. Rothamsted Research receives funding from the BBSRC (UK).

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Authors and Affiliations

  1. Plant Pathology and Microbiology Department, Rothamsted Research, Harpenden, AL5 2JQ, UK

    Jonathan S. West & H. Alastair McCartney

  2. Division of Mechatronics Biostatistics and Sensors (MeBioS), Katholieke Universiteit Leuven, 3001, Leuven, Belgium

    Cedric Bravo & Herman Ramon

  3. Department of Agricultural Engineering, Università degli Studi di Milano, 20133, Milano, Italy

    Roberto Oberti

  4. Agricultural Engineering Laboratory, Faculty of Agriculture, Aristotle University of Thessaloniki, 275, Thessaloniki, Greece

    Dimitrios Moshou

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  1. Jonathan S. West
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  2. Cedric Bravo
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  3. Roberto Oberti
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  4. Dimitrios Moshou
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  5. Herman Ramon
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  6. H. Alastair McCartney
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Correspondence to Jonathan S. West .

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Editors and Affiliations

  1. , Institute of Crop Science and Resource C, University of Bonn, Nussallee 9, Bonn, 53115, Germany

    Erich-Christian Oerke

  2. , Department of Weed Sciences, University of Hohenheim, Otto-Sanderstrasse 5, Stuttgart, 70599, Germany

    Roland Gerhards

  3. , Department of Geography, Remote Sensing, University of Bonn, Meckenheimer Allee 166, Bonn, 53115, Germany

    Gunter Menz

  4. , Institute of Crop Science and Resource C, University of Bonn, Nussallee 9, Bonn, 53115, Germany

    Richard A. Sikora

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West, J.S., Bravo, C., Oberti, R., Moshou, D., Ramon, H., McCartney, H.A. (2010). Detection of Fungal Diseases Optically and Pathogen Inoculum by Air Sampling. In: Oerke, EC., Gerhards, R., Menz, G., Sikora, R. (eds) Precision Crop Protection - the Challenge and Use of Heterogeneity. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9277-9_9

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