Towards remote estimation of radiation use efficiency in maize using UAV-based low-cost camera imagery

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Abstract

Radiation Use Efficiency (RUE) defines the productivity with which absorbed photosynthetically active radiation (APAR) is converted to plant biomass. Readily used in crop growth models to predict dry matter accumulation, RUE is commonly determined by elaborate static sensor measurements in the field. Different definitions are used, based on total absorbed PAR (RUEtotal) or PAR absorbed by the photosynthetically active leaf tissue only (RUEgreen). Previous studies have shown that the fraction of PAR absorbed (fAPAR), which supports the assessment of RUE, can be reliably estimated via remote sensing (RS), but unfortunately at spatial resolutions too coarse for experimental agriculture. UAV-based RS offers the possibility to cover plant reflectance at very high spatial and temporal resolution, possibly covering several experimental plots in little time. We investigated if (a) UAV-based low-cost camera imagery allowed estimating RUEs in different experimental plots where maize was cultivated in the growing season of 2016, (b) those values were different from the ones previously reported in literature and (c) there was a difference between RUEtotal and RUEgreen. We determined fractional cover and canopy reflectance based on the RS imagery. Our study found that RUEtotal ranges between 4.05 and 4.59, and RUEgreen between 4.11 and 4.65. These values are higher than those published in other research articles, but not outside the range of plausibility. The difference between RUEtotal and RUEgreen was minimal, possibly due to prolonged canopy greenness induced by the stay-green trait of the cultivar grown. The procedure presented here makes time-consuming APAR measurements for determining RUE especially in large experiments superfluous.

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Tewes, A., & Schellberg, J. rgen. (2018). Towards remote estimation of radiation use efficiency in maize using UAV-based low-cost camera imagery. Agronomy, 8(2). https://doi.org/10.3390/agronomy8020016

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