Tsoulias Nikos, Khosravi Arash, Herppich Werner B, Zude-Sasse Manuela
Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Department Agromechatronic, WG Precision Horticulture, Potsdam, Germany.
Department of Agricultural, Food and Environmental Science, Marche Polytechnic University, 60131 Ancona, Italy.
Plant Phenomics. 2024 Sep 18;6:0252. doi: 10.34133/plantphenomics.0252. eCollection 2024.
In applied ecophysiological studies related to global warming and water scarcity, the water status of fruit is of increasing importance in the context of fresh food production. In the present work, a fruit water stress index () is introduced for close analysis of the relationship between fruit and air temperatures. A sensor system consisting of light detection and ranging (LiDAR) sensor and thermal camera was employed to remotely analyze apple trees ( x Borkh. "Gala") by means of 3D point clouds. After geometric calibration of the sensor system, the temperature values were assigned in the corresponding 3D point cloud to reconstruct a thermal point cloud of the entire canopy. The annotated points belonging to the fruit were segmented, providing annotated fruit point clouds. Such estimated 3D distribution of fruit surface temperature ( ) was highly correlated to manually recorded reference temperature ( = 0.93). As methodological innovation, based on , the fruit water stress index ( ) was introduced, potentially providing more detailed information on the fruit compared to the crop water stress index of whole canopy obtained from established 2D thermal imaging. showed low error when compared to manual reference data. Considering in total 302 apples, increased during the season. Additional diel measurements on 50 apples, each at 6 measurements per day (in total 600 apples), were performed in the commercial harvest window. calculated with air temperature plus 5 °C appeared as diel hysteresis. Such diurnal changes of and those throughout fruit development provide a new ecophysiological tool aimed at 3D spatiotemporal fruit analysis and particularly more efficient, capturing more samples, insight in the specific requests of crop management.
在与全球变暖和水资源短缺相关的应用生态生理学研究中，在新鲜食品生产背景下，果实的水分状况变得越来越重要。在本研究中，引入了果实水分胁迫指数（），以密切分析果实温度与气温之间的关系。采用由光探测与测距（LiDAR）传感器和热成像相机组成的传感器系统，通过三维点云对苹果树（×Borkh.“Gala”）进行远程分析。在对传感器系统进行几何校准后，将温度值分配到相应的三维点云中，以重建整个树冠的热学点云。对属于果实的标注点进行分割，得到标注的果实点云。这种估计的果实表面温度（）的三维分布与人工记录的参考温度高度相关（=0.93）。作为方法创新，基于，引入了果实水分胁迫指数（），与从已建立的二维热成像获得的整个树冠的作物水分胁迫指数相比，它可能提供关于果实的更详细信息。与人工参考数据相比，显示出较低的误差。在总共302个苹果中，在季节期间有所增加。在商业收获期，对50个苹果进行了额外的日变化测量，每个苹果每天测量6次（总共600个苹果）。用气温加5°C计算得出的呈现出日滞后现象。这种的日变化以及整个果实发育过程中的变化提供了一种新的生态生理学工具，旨在进行三维时空果实分析，特别是更高效地获取更多样本，洞察作物管理的具体要求。
