Browsing by Subject "Thermography"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Publication
    Application of infrared imaging for early detection of downy mildew (Plasmopara viticola) in grapevine
    (2022) Zia-Khan, Shamaila; Kleb, Melissa; Merkt, Nikolaus; Schock, Steffen; Müller, Joachim
    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 R2 = 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.
  • Thumbnail Image
    Publication
    Suitability of the stress severity index combined with remote‐sensing data as a tool to evaluate drought resistance traits in potato
    (2023) Hoelle, Julia; Asch, Folkard; Khan, Awais; Bonierbale, Merideth
    Potato is a drought susceptible crop and even short drought spells reduce tuber yields notably. In an earlier study we developed a stress severity index (SSI) based on the development stage of a genotype at the onset of drought and the soil water deficit based on soil water tension. Here, we test the suitability of the SSI combined with remotely sensed data as a screening tool to select drought‐tolerant potato genotypes. Normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) were obtained from reflectance measurements and thermography. Temperature data from the thermography allow using the difference between leaf and air temperature (∆T) to estimate the transpirational cooling of the leaves. Via cluster analysis including SSI, tuber yield reduction under drought, NDVI, PRI and thermography, three groups were distinguished: 1. SSI < 1000 with fast decreasing NDVI, PRI and ∆T, 2. SSI 1000–2000 with almost constant NDVI and ∆T and 3. SSI > 2000 described by small changes of NDVI, PRI and temperature deficit. For SSI < 1000, ∆T, PRI and NDVI showed to be good indicators of genotypic performance under drought. Potential strategies for drought resistance in potato detectable through remote sensing are discussed.