Abstract

Five winter oat (Avena sativa L.) varieties were set in a small-plot field experiment to examine the abiotic stress considering silicone and sulphur foliar fertilization treatments under temperate and dry climatic conditions in Hungary. Numerous in situ and laboratory measurements were performed to describe the crop's condition at various phenological stages. Drones with multispectral, thermal and LiDAR payloads monitored the field both with high temporal and spatial resolution. A high level of GIS data assimilation was performed in order to handle the different spatial-related parameters in one interface. It is a multi-purpose experiment, and for all of them it is an important criterion whether the study was carried out in a truly homogeneous area. Practically, it means that we ignore the patterns of the crop or the soil. If this is not the case, the various parameters measured should be evaluated accordingly. Hence, our study's main goal here is to reveal the soil and crop heterogeneity level. For this, all the measured parameters are involved in the multi-parameter analysis by which the heterogeneity level of the site can be assessed.Practically, by this, we can answer the main question: is the field suitable to carry out analysis such as abiotic stress studies or yield prediction modelling on it or shall we handle certain parts differently?Based on the example of our experiment we design a workflow by which the heterogeneity level of a small-plot field can be assessed and provide a solution for how to handle it in order not to involve data which may mislead analysis.

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