ArticlePlants (Basel, Switzerland)2026
Estimation of Grain Yield and Quality in Awned and Awnless Wheat Genotypes Using UAV and Proximal Multispectral Sensors.
Article in Plants (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study aimed to evaluate the complementary potential of UAV-based and proximal multispectral sensing using the Plant-O-Meter (POM) sensor for the assessment of wheat grain yield and quality across different phenological stages and two growing seasons. The analysis was based on three vegetation indices, the Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), and Normalized Difference Red Edge Index (NDRE), and included two morphologically distinct genotype groups, awned and awnless. The study included nine awned and nine awnless genotypes. Vegetation indices showed pronounced seasonal dynamics, with higher values during intensive vegetative development and a decline during later growth stages. The strongest relationship with grain yield was observed for GNDVI-A during the heading to beginning of flowering stage (BBCH 51-61) in Season I (r = 0.85), whereas in Season II, the strongest relationship was observed for NDRE-A during the flag leaf stage (BBCH 37-39) (r = 0.80). Awned genotypes generally showed stronger VI-yield relationships, while associations with grain quality parameters varied among genotype groups and seasons. Linear mixed-effects models showed that both VI-related effects and genotype variability contributed to the variation in grain yield and quality. For yield, marginal R
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