Digital infrared thermography for the assessment of leaf pathogens

Precision Agriculture 2005, ECPA 2005

Volumn , Issue , 2005, Pages 91-98

  Oerke, E C ^a   Lindenthal, M ^a   Frohling P ^a   Steiner, U ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

IR thermography; Plant diseases; Sensor

Indexed keywords

ABIOTIC FACTORS; CONTROLLED CONDITIONS; DISEASE DETECTION; FIELD EXPERIMENT; IR THERMOGRAPHY; PLANT DISEASE; SITE-SPECIFIC; VENTURIA INAEQUALIS;

AGRICULTURE; FRUITS; SENSORS; THERMOGRAPHY (IMAGING);

FUNGI;

EID: 84893423827     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Accetta, J.S., Shumaker, D.L. 1993. The Infrared and Electro-Optical Systems Handbook. SPIE Optical Engineering Press, Washington, USA.
2. Bongiovanni, R., Lowenberg-Deboer, J. 2004. Precision agriculture and sustainability. Precision Agriculture 5 359-387.
3. Chaerle, L., Hagenbeek, D., De Bruyne, E., Valcke, R., Van der Straeten, D. 2004. Thermal and chlorophyllfluorescence imaging distinguish plant-pathogen interactions at an early stage. Plant & Cell Physiology 45 887-896.
4. Chaerle, L., Van der Straeten, D. 2001. Seeing is believing: imaging techniques to monitor plant health. Biochimica et Biophysica Acta 1519 153-166.
5. Gebhardt, A. 1990. Differenzierte Einschätzung des Wasserversorgungszustandes landwirtschaftlicher Kulturen mittels thermografischer Luftaufnahmen. Archiv für Acker- und Pflanzenbau und Bodenkunde 34 741-748.
6. Gerhards, R., Christensen, S. 2003. Real-time weed detection, decision making and patch spraying in maize (Zea mays L.), sugar beet (Beta vulgaris L.), winter wheat (Triticum aestivum L.) and winter barley (Hordeum vulgare L.). Weed Research 43 1-8.
7. Lindenthal, M., Steiner, U., Dehne, H.-W., Oerke, E.-C. 2005. Effect of downy mildew development on transpiration of cucumber leaves visualized by digital infrared thermography. Phytopathology 95 233-240.
8. Lorenzen, B., Jensen, A. 1989. Changes in spectral properties induced in barley by cereal powdery mildew. Remote Sensing and Environment 27 201-209.
9. MacHardy, W.E., Gadoury, D.M., Gessler, C. 2001. Parasitic and biological fitness of Venturia inaequalis: relationship to disease management strategies. Plant Disease 85 1036-105.
10. Moshou, D., Bravo, C., West, J., Wahlen, S., McCartney, A., Ramon, H. 2004. Automatic detection of ?yellow rust? in wheat using reflectance measurements and neural networks. Computers and Electronics in Agriculture 44 173-188.
11. Oerke, E.-C., Dehne, H.-W., Schönbeck, F., Weber, A. 1994. Crop production and crop protection - estimated losses in major food and cash crops. Elsevier Science, Amsterdam. 808 pp.
12. Oliver, M.A., Heming, S.D., Gibson, G., Adams, N. 2003. Exploring the spatial variation of take-all (Gaeumannomyces graminis var. tritici) for site-specific management. In: Precision Agriculture, Proceedings of the 4th European Conference on Precision Agriculture. J. Stafford, A. Werner (eds.) Wageningen Academic Publishers, Wageningen, The Netherlands, 481-486.
13. Sasaki, Y., Okamoto, T., Imou, K., Torii, T. 1998. Automatic diagnosis of plant disease: spectral reflectance of healthy and diseases leaves. Proceedings AgEng?98 Conference, Oslo, 6 pp.
14. West, J.S., Bravo, C., Oberti, R., Lemaire, D., Moshou, D., McCartney, H.A. 2003. The potential of optical canopy measurement for targeted control of field crop diseases. Annual Review of Phytopathology 41 593-614.
15. Wisniewski, M., Lindow, S.E., Ashworth, E.N. 1997. Observations of ice nucleation and propagation in plants using infrared video thermography. Plant Physiology 113 327-334.