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    Evaluating spatially resolved influence of soil and tree water status on quality of European plum grown in semi-humid climate
    (Lausanne : Frontiers Media, 2017) Käthner, Jana; Ben-Gal, Alon; Gebbers, Robin; Peeters, Aviva; Herppich, Werner B.; Zude-Sasse, Manuela
    In orchards, the variations of fruit quality and its determinants are crucial for resource effective measures. In the present study, a drip-irrigated plum production (Prunus domestica L. “Tophit plus”/Wavit) located in a semi-humid climate was studied. Analysis of the apparent electrical conductivity (ECa) of soil showed spatial patterns of sand lenses in the orchard. Water status of sample trees was measured instantaneously by means of leaf water potential, Ψleaf [MPa], and for all trees by thermal imaging of canopies and calculation of the crop water stress index (CWSI). Methods for determining CWSI were evaluated. A CWSI approach calculating canopy and reference temperatures from the histogram of pixels from each image itself was found to suit the experimental conditions. Soil ECa showed no correlation with specific leaf area ratio and cumulative water use efficiency (WUEc) derived from the crop load. The fruit quality, however, was influenced by physiological drought stress in trees with high crop load and, resulting (too) high WUEc, when fruit driven water demand was not met. As indicated by analysis of variance, neither ECa nor the instantaneous CWSI could be used as predictors of fruit quality, while the interaction of CWSI and WUEc did succeed in indicating significant differences. Consequently, both WUEc and CWSI should be integrated in irrigation scheduling for positive impact on fruit quality.
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    Tree Water Status in Apple Orchards Measured by Means of Land Surface Temperature and Vegetation Index (LST–NDVI) Trapezoidal Space Derived from Landsat 8 Satellite Images
    (Basel : MDPI AG, 2020) Zare, Mohammad; Drastig, Katrin; Zude-Sasse, Manuela
    In this study, the split window (SW) method was applied for land surface temperature (LST) retrieval using Landsat 8 in two apple orchards (Glindow, Altlandsberg). Four images were acquired during high demand of irrigation water from July to August 2018. After pre-processing images, the normalized difference vegetation index (NDVI) and LST were calculated by red, NIR, and thermal bands. The results were validated by interpolated infrared thermometer (IRT) measurements using the inverse distance weighting (IDW) method. In the next step, the temperature vegetation index (TVDI) was calculated based on the trapezoidal NDVI/LST space to determine the water status of apple trees in the case studies. Results show good agreement between interpolated LST using IRT measurements and remotely sensed LST calculation using SW in all satellite overpasses, where the absolute mean error was between 0.08 to 4.00 K and root mean square error (RMSE) values ranged between 0.71 and 4.23 K. The TVDI spatial distribution indicated that the trees suffered from water stress on 7 and 23 July and 8 August 2018 in Glindow apple orchard with the mean value of 0.69, 0.57, and 0.73, whereas in the Altlandsberg orchard on 17 August, the irrigation system compensated the water deficit as indicated by the TVDI value of 0.34. Moreover, a negative correlation between TVDI and vegetation water content (VWC) with correlation coefficient (r) of −0.81 was observed. The corresponding r for LST and VWC was equal to −0.89, which shows the inverse relation between water status and temperature-based indices. The results indicate that the LST and/or TVDI calculation using the proposed methods can be effectively applied for monitoring tree water status and support irrigation management in orchards using Landsat 8 satellite images without requiring ground measurements.