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Updated: Aug 26, 2025

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes
Published on: March 28, 2025
Daytime and seasonal reflectance of maize grown in varying compass directions
Claudia Buchhart1,2, Urs Schmidhalter2
1Chair of Restoration Ecology, Department of Life Science Systems, Technical University of Munich, Freising, Germany.
Abstract:
High temporal and spatial resolution is required to meet the challenges of changing plant characteristics over time. Solar radiation and reflectance of vegetation canopies vary with the time of day and growing season. Little is known regarding the interactions between daily and seasonally varying irradiation and reflectance of row-planted crops that can be grown in any compass direction. The spectral reflectance of maize grown in four compass directions was recorded across the entire life cycle through highly frequent drone-based multispectral sensing to determine biomass changes over time and make early yield predictions. Comparison of information from spectral bands and indices indicated no differences among the four compass directions at the reproductive stage and only a few differences at the earlier vegetative growth stages. There was no systematic influence of row orientation on the relationships between spectral data, biomass, and grain yield, except at the early growth stages. Spectral relationships to biomass at the reproductive stage varied in row directions with R2-values close to 0.9, already observed at early growth stages for the indices NDVI, SR, GCI, and GNDVI. The spectral relationships to yield were closer in individual compass directions, with R2-values varying between 0.8-0.9 for the best indices GCI and GNDV after BBCH 61. A closer inspection of daytime changes indicated a diurnal trend with 15 and 20% decreased spectral values observed after midday at the growth stages BBCH 81 and 61, respectively, thus requiring standardization of flight timing during the day. Drone-assisted nadir-oriented spectral sensing could be a reference for terrestrial and satellite-based reflectance sensing to relate canopy reflectance to crop characteristics quantitatively.
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