Abstract
Remote sensing is an efficient method of monitoring experiments rapidly and by enabling the collection of significantly more detailed data, than using only field measurements, ensuring new possibilities in scientific research. A small plot field experiment was conducted in a randomized block design with winter oat (Avena sativa L.) varieties in Debrecen, Hungary in the 2020/2021 cropping year. Multiple field measurements and aerial surveys were carried out examining the response of oat on Silicon and Sulfur foliar fertilization treatments thereby monitoring their effects on the physiology, production and stress tolerance. Parallel application of in situ (elevation, soil pH, NDVI, SPAD, chlorophyll content) and aerial (NDVI, NDRE) surveys including unmanned aerial vehicles (UAVs) provided a diverse source of data for evaluation. Both the oat varieties (88.9%) and the foliar fertilization treatments (87.5%) were correctly classified and clearly separated with the discriminant analysis based on measured data. The Pearson correlation analysis showed a very strong positive connection (r = 0.895–1.00) between the NDVI values measured using a hand-held system and UAV-installed camera, except the third measurement time, where the correlation was weaker (r = 0.70). Our results indicate that field experiments can be effectively supported by UAVs.
Highlights
There has been an increase in concern about food security and sustainable agricultural development in the world recently, of which one of the main components is the actual estimation of supply and demand of crops such as oat (Avena sativa L.)
The Digital Elevation Model (DEM) generated from the measured elevation values shows a slight dipping towards the west, the general flow direction is from shows a slight dipping towards the west, the general flow direction is from east to west
We found no significant correlations among the soil pH, the chlorophyll content measured in the laboratory from leaf samples were taken on 24 June (BBCH 77) and the SPAD values from field measurements at different vegetation periods: 27 May (BBCH 52); 10 June (BBCH 65); 24 June (BBCH 77)
Summary
There has been an increase in concern about food security and sustainable agricultural development in the world recently, of which one of the main components is the actual estimation of supply and demand of crops such as oat (Avena sativa L.). Oat is the sixth most grown cereal globally [1] and the fifth most important in Europe [2]. The assessment of biomass and yield before actual production is crucial as it determines policies and decisions in the agricultural production system, due to the rising demand for food grain around the world [3]. Observations in agriculture require real-time data on the crops. The close connection between the canopy Leaf Area Index (LAI) and fAPAR (fraction of Absorbed Photosynthetically Active Radiation) [7,8] explains the viability of remote sensing-based biomass monitoring systems. NDVI can be used as an indirect measure of primary productivity
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