The transition toward Agriculture 4.0 requires soil sampling strategies that really characterize spatial heterogeneity. This study compared conventional five-point composite (5P) and zigzag (ZZ) sampling methods with multispectral image-guided sampling (MI) using a DJI Mavic 3 unmanned aerial vehicle (UAV) (SZ DJI Technology Co., Ltd.), Shenzhen, Guangdong, China) in a semi-arid agroecosystem of northeastern Mexico. In situ measurements included penetration resistance (PR), volumetric water content (VWC), and apparent electrical conductivity (ECa), while laboratory analyses included bulk density (ρ_b) and soil pH (H₂O). Statistical analyses revealed significant differences among sampling strategies for penetration resistance and volumetric water content (p < 0.05). The MI approach captured greater spatial contrasts in penetration resistance within the 10–20 cm depth interval, with PR values reaching up to 5076 kPa, whereas conventional methods recorded substantially lower PR values. UAV-guided sampling identified sampling locations associated with contrasting VWC and PR measurements relative to conventional composite sampling strategies. Soil pH (H₂O) and ECa remained stable among sampling methods; however, highlighting the need for methodological standardization and local calibration. Multispectral image-guided sampling facilitates spatial stratification and the characterization of within-field variability in dynamic soil physical properties, supporting stratified soil management and more efficient resource use in semi-arid agricultural systems.

The objective of this study was to evaluate the regrowth capacity of Amelichloa clandestina at different regrowth intervals after non-selective grazing in different seasons of the year. The study was carried out on a 2.23 ha⁻¹ site in northeastern Mexico. Plots of 600 m² were used, with three replications, and were subjected to grazing at 333 LU ha⁻¹ at the beginning of every season, with biweekly evaluations. Dry matter yield (DMY) was determined by harvesting 1 m² per plot and extrapolating it to kg ha⁻¹. Morphological composition was evaluated from a 10% subsample of the total biomass. The height of 12 plants and light interception were measured with a ruler and a Quantum meter, respectively. The data were analysed using a randomized complete block design (RCBD) with a split-plot in time structure, evaluating Season (S), Days After Regrowth (DAR), and their interaction (S × DAR). Means were compared using the Tukey test in JMP 14 Pro. In autumn, DMY peaked at 535.0 kg ha⁻¹ at 90 DAR (p ≤ 0.05), accompanied by a maximum canopy height of 28.7 cm and a light interception of 30.3% at the same interval. Leaf biomass was highest in autumn, with a seasonal mean of 220.8 kg ha⁻¹ across all regrowth intervals. A significant correlation was found between plant height and light interception (r = 0.67, p ≤ 0.001). Autumn favoured A. clandestina productivity under a high stocking rate.

A variable seed rate system was integrated and evaluated using Trimble technology. Laboratory tests were conducted to assess system performance on a seeder test bench, with seed delivery rates ranging from 180 to 800 seeds per minute. The system was tested using two corn seed plates: a 30-cell Precision Planting plate (PP) and a 40-cell John Deere (JD) plate. The laboratory results showed a cell fill rate of 98.6% for the PP plate and 104.5% for the JD plate. Field performance was evaluated at four sowing densities (100,000; 80,000; 60,000; and 40,000 seeds·ha ⁻¹ ) and three travel speeds (6, 8, and 10 km·h ⁻¹ ). Results showed no significant differences in dosing uniformity due to sowing density otr speed. The system achieved 100% dose uniformity with a coefficient of variation (CV) of just 1.36%, demonstrating high operational reliability. Regarding seed delivery uniformity, an analysis of variance of seed fall timing revealed a significant difference between the plates. The PP plate outperformed the JD plate, with a CV of 10.82% compared to 14.387%, respectively. The system‘s response time to changes in seeding density ranged from 43 milliseconds (from 100,000 to 80,000 seeds·ha ⁻¹ at 10 km·h ⁻¹ ) to 232 milliseconds (from 40,000 to 100,000 seeds·ha ⁻¹ at 6 km·h ⁻¹ ). In conclusion, the integrated variable seed rate system demonstrated high operational reliability. However, an average variability of 12.5% in planter performance was observed, highlighting an opportunity for further optimisation and system improvement.