Application of Infrared Imaging for Early Detection of Downy Mildew ( Plasmopara viticola ) in Grapevine

Shamaila Zia-Khan, Melissa Kleb, Nikolaus Merkt, Steffen Schock and Joachim Müller
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Shamaila Zia-Khan: Institute of Agricultural Engineering, Tropics and Subtropics Group (440e), University of Hohenheim, Garbenstrasse 9, 70599 Stuttgart, Germany
Melissa Kleb: Institute of Crop Science, Department of Quality of Plant Products, Viticulture (340e), University of Hohenheim, Emil-Wolff-Strasse 35, 70599 Stuttgart, Germany
Nikolaus Merkt: Institute of Crop Science, Department of Quality of Plant Products, Viticulture (340e), University of Hohenheim, Emil-Wolff-Strasse 35, 70599 Stuttgart, Germany
Steffen Schock: Institute of Agricultural Engineering, Tropics and Subtropics Group (440e), University of Hohenheim, Garbenstrasse 9, 70599 Stuttgart, Germany
Joachim Müller: Institute of Agricultural Engineering, Tropics and Subtropics Group (440e), University of Hohenheim, Garbenstrasse 9, 70599 Stuttgart, Germany

Agriculture, 2022, vol. 12, issue 5, 1-12

Abstract: Late detection of fungal infection is the main cause of inadequate disease control, affecting fruit quality and reducing yield of grapevine. Therefore, infrared imagery as a remote sensing technique was investigated in this study as a potential tool for early disease detection. Experiments were conducted under field conditions, and the effects of temporal and spatial variability in the leaf temperature of grapevine infected by Plasmopara viticola were studied. Evidence of the grapevine’s thermal response is a 3.2 °C increase in leaf temperature that occurred long before visible symptoms appeared. In our study, a correlation of R 2 = 0.76 at high significance level ( p ≤ 0.001) was found between disease severity and MTD. Since the pathogen attack alters plant metabolic activities and stomatal conductance, the sensitivity of leaf temperature to leaf transpiration is high and can be used to monitor irregularities in temperature at an early stage of pathogen development.

Keywords: thermography; canopy temperature; fungal infection; maximum temperature difference; remote sensing; leaf wetness duration (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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