Skip to main content
Log in

Thermographic medium-far ground-based proximal sensing for in-field wheat Stagonospora nodorum blotch detection

  • Short Communication
  • Published:
Journal of Plant Diseases and Protection Aims and scope Submit manuscript

Abstract

Thermal imaging is a potential remote sensing tool for estimating fungal wheat diseases. This study for the first time investigated the suitability of infrared thermography as rapid non-destructive technique to detect Stagonospora nodorum blotch wheat infection observing differences in temperatures due to loss of water content in infected wheat. Analyses were conducted in-field using medium-far ground-based proximal sensing technique. The study demonstrated statistically significant differences between images relative to different plots planted with two cultivars treated with three different conditions: artificially inoculated with Stagonospora nodorum (IN), treated with fungicide (TT) and not inoculated nor treated (NT). This study is oriented on medium-far ground-based proximal sensing in order to frame an area of medium extension (~10–20 m2), placing the acquisition system at the bottom of each plot with a height of 4 m. Fifty-three thermal images of durum wheat plants have been acquired at growth stage 83, with a FLIR (S40) thermo-camera. A randomized split-plot design with three replicates has been utilized. Regions of interest were extracted from each plot image and thus, mean temperature and relative · standard deviation were calculated. The two-tailed (Wilcoxon) Mann-Whitney U test has been used to evidence whether the medians of couples of diverse treatments were different. Considering the whole samples significant differences (p < 0.05) have been observed between IN and TT.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  • Adamchuk VI, Hummel JW, Morgan MT & Upadhyaya SK, 2004. On-the-go soil sensors for precision agriculture. Comput Electron Agr 44, 71–91.

    Article  Google Scholar 

  • Antonucci F, Pallottino F, Costa C, Rimatori V, Giorgi S, Papetti P & Menesatti P, 2011. Development of a rapid soil water content detection technique using active infrared thermal methods for in-field applications. Sensors 11, 10114–10128.

    Article  PubMed  PubMed Central  Google Scholar 

  • Chaerle L, Van Caeneghem W, Messens E, Lambers H, Van Montagu M & Van Der Straeten D, 1999. Presymptomatic visualization of plant-virus interactions by thermography. Nat Biotechnol 17, 813–816.

    Article  CAS  PubMed  Google Scholar 

  • Chaerle L, De Boever F, Van Montagu M & Van Der Straeten D, 2001. Thermographic visualization of cell death in tobacco and Arabidopsis. Plant Cell Environ 24, 15–25.

    Article  Google Scholar 

  • Gebbers R & Adamchuk VI, 2010. Precision Agriculture and Food Security. Science 327, 828–831.

    Article  CAS  PubMed  Google Scholar 

  • Hellebrand HJ, Dammer KH, Beuche H, Herppich WB & Flath K, 2005. Infrared imaging for plant protection. J Agr Eng Res 11, 35–42.

    Google Scholar 

  • Hellebrand HJ, Herppich WB, Beuche H, Dammer K, Linke M & Flath K, 2006. Investigations of plant infections by thermal vision and NIR imaging. Int Agrophys 20, 1.

    Google Scholar 

  • Jones HG & Schofield P, 2008. Thermal and other remote sensing of plant stress. Gen Appl Plant Physiol, Special Issue 34, 19–32.

    Google Scholar 

  • Leinonen I & Jones HG, 2004. Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress. J Exp Bot 55, 1423–1431.

    Article  CAS  PubMed  Google Scholar 

  • López MM, Bertolini E, Olmos A, Caruso P, Gorris MT, Llop P, Penyalver R & Cambra M, 2003. Innovative tools for detection of plant pathogenic viruses and bacteria. Int Microbiol 6, 233–243.

    Article  PubMed  Google Scholar 

  • Menesatti P, Antonucci F, Pallottino F, Giorgi S, Matere A, Nocente F, Pasquini M, D’Egidio MG & Costa C, 2013. Laboratory vs. in-field spectral proximal sensing for early detection of Fusarium head blight infection in durum wheat. Biosyst Eng 114, 289–293.

    Article  Google Scholar 

  • Moshou D, Bravo C, Oberti R, West J, Bodria L, McCartney A & Ramon H, 2005. Plant disease detection based on data fusion of hyper-spectral and multi-spectral fluorescence imaging using Kohonen maps. Real-Time Imaging 11, 75–83.

    Article  Google Scholar 

  • Moshou D, Bravo C, Oberti R, West JS, Ramon H, Vougioukas S & Bochtis D, 2011. Intelligent multi-sensor system for the detection and treatment of fungal diseases in arable crops. Biosyst Eng 108, 311–321.

    Article  Google Scholar 

  • Nilsson HE, 1995. Remote sensing and image analysis in plant pathology. Can J Plant Pathol 17, 154–166.

    Article  Google Scholar 

  • Oerke EC, Steiner U, Dehne HW & Lindenthal M, 2006. Thermal imaging of cucumber leaves affected by downy mildew and environmental conditions. J Exp Bot 57, 2121–2132.

    Article  CAS  PubMed  Google Scholar 

  • Oerke EC & Steiner U, 2010. Potential of digital thermography for disease control. In: Oerke EC, Gerhards R, Menz G, Sikora RA (Eds.) 2010: Precision Crop Protection–The Challenge and Use of Heterogeneity. Springer, Dordrecht, Heidelberg, London, New York. 167–182.

    Chapter  Google Scholar 

  • Sankaran S, Mishra A, Ehsani R & Davis C, 2010. A review of advanced techniques for detecting plant diseases. Comp Electron Agr 72, 1–13.

    Article  Google Scholar 

  • West JS, Bravo C, Oberti R, Moshou D, Ramon H & McCartney HA, 2010. Detection of fungal diseases optically and pathogen inoculum by air sampling. In: Oerke EC, Gerhards R, Menz G, Sikora RA (Eds.) 2010: Precision Crop Protection–the Challenge and Use of Heterogeneity. Springer, Dordrecht, Heidelberg, London, New York. 135–149.

    Chapter  Google Scholar 

  • Zadoks JC, Chang TT & Konzak CF, 1974. A decimal code for the growth stages of cereals. Weed Res 14, 415–421.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Paolo Menesatti.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Antonucci, F., Menesatti, P., Iori, A. et al. Thermographic medium-far ground-based proximal sensing for in-field wheat Stagonospora nodorum blotch detection. J Plant Dis Prot 120, 205–208 (2013). https://doi.org/10.1007/BF03356476

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF03356476

Key words

Navigation