Diagnosing Early Establishment of Hybrid Sorghum in Response to Seeding Rates Using UAV-Based Remote Sensing and Soil ECa Analysis

Abstract

Sorghum is a resilient crop important for sustainable intensification in semi-arid regions, yet the impact of variable seeding rates on its early development remains under-researched. This research investigated the early establishment of hybrid sorghum under three seeding strategies, "Uniformise" (medium density across all zones), "Optimise" (increased density in low-soil apparent Electrical Conductivity (ECa)), and "Maximise" (increased density in high-soil ECa), at the Herdade da Comenda (Innovation Center - Elvas, Portugal). Crop performance was monitored over 33 days, the established window for safe direct grazing, using Unmanned Aerial Vehicle (UAV) multispectral imagery to derive the Normalised Difference Vegetation Index (NDVI) and Canopy Cover (Cveg), alongside physical sampling of plant height and biomass. Statistical analysis revealed that both the seeding strategy and soil variability significantly affected early growth. The "Uniformise" strategy recorded the highest plant height, NDVI, and Cveg values, whereas the "Optimise" strategy performed the poorest. Additionally, an accumulation of 407.5 Growing Degree-Days (GDDs; ºC) accelerated the phenological cycle by five days relative to the climatological normal. Despite differences in vegetative vigour, no statistically significant variations were observed in final biomass across the strategies. These results indicate that while the "Uniformise" approach provided a more balanced environment for early establishment under these specific Mediterranean conditions, the lack of biomass differentiation highlights the potential for resource optimisation. The study demonstrates that UAV-based remote sensing is a useful diagnostic tool to identify these spatial limitations, providing the data to refine variable-rate seeding (VRS) algorithms and improve the economic efficiency of precision sowing.