Light Detection and Ranging (LiDAR) technology can be used to assess canopy height in cotton (Gossypium hirsutum L.), but standardized data acquisition and processing guidelines are lacking. Accurate canopy height estimation is crucial in cotton for optimizing growth regulator application and maximizing yield. The main goal of this study was to determine the optimal unmanned aerial vehicle flight settings—altitude and speed—and assess specific processing parameters’ impact on data accuracy, processing time, and file size. Nine flight settings comprising three altitudes (12.2 m, 24.4 m, and 48.8 m) and three speeds (4.8 km/h, 9.6 km/h, and 14.4 km/h) were tested. LiDAR data were processed using DJI Terra software (v. 4.1.0), where two user-defined processing steps were examined: point-cloud thinning via grid size sub-sampling (0, 10, 20, 30, 40, and 50 cm) and slope classification (flat, gentle, and steep). The optimal flight altitude was 24.4 m, with no effect of flight speed. Grid sub-sampling up to 20 cm produced balanced accuracy, processing time, and file size. The choice of slope category had no significant effect on LiDAR-derived canopy height. These findings contribute to the development of standardized LiDAR data acquisition and processing guidelines for cotton to support crop management decision.

Light Detection and Ranging (LiDAR) technology can be used to assess canopy height in cotton (Gossypium hirsutum L.), but standardized data acquisition and processing guidelines are lacking. Accurate canopy height estimation is crucial in cotton for optimizing growth regulator application and maximizing yield. The main goal of this study was to determine the optimal unmanned aerial vehicle flight settings—altitude and speed—and to assess specific processing parameters impact on data accuracy, processing time, and file size. Nine flight settings comprising three altitudes (12.2 m, 24.4 m, and 48.8 m) and three speeds (4.8 km/h, 9.6 km/h, and 14.8 km/h) were tested. LiDAR data were processed using DJI Terra software, where two user-defined processing steps were examined: point-cloud thinning via grid size sub-sampling (0, 10, 20, 30, 40, and 50 cm) and slope classification (flat, gentle, and steep). The optimal flight altitude was 24.4 m, with no effect of flight speed. Grid sub-sampling up to 20 cm produced balanced accuracy, processing time, and file size. The choice of slope category had no significant effect on LiDAR-derived canopy height. These findings contribute to the development of standardized LiDAR data acquisition and processing guidelines for cotton to support crop management decision.

Alternaria leaf spot of cotton is a widespread foliar disease worldwide; however, information regarding disease progress and cultivar response under field conditions in northern Argentina is limited. This study aimed to evaluate disease progress, commercial cultivar performance, and the effects of fungicide application on plant growth, yield, and fiber quality. Field experiments were conducted during two growing seasons (2021–22 and 2022–23) in Reconquista, Santa Fe, Argentina, using three commercial upland cotton cultivars grown under fungicide-treated and untreated conditions, under high plant density and narrow row system. A commercial mixture of pyraclostrobin and epoxiconazole was applied at 50, 70, and 100 days after sowing. Disease incidence and severity were assessed over time, and plant growth, yield, and fiber quality traits were evaluated. Disease showed clear temporal progression in both growing seasons, reaching 100% incidence at 110 days after sowing, however, mean severity values remained moderate (<10%). The fungicide neither reduced incidence or severity nor improved yield or fiber quality. However, fungicide-treated plots showed significantly higher aboveground biomass, nearly 20% over control, suggesting a physiological effect unrelated to disease suppression, which warrant further research. Despite low disease pressure, cultivars differed in their response to infection, with NuOpal showing the highest susceptibility and Guazuncho 4 the lowest disease accumulation. Alternaria leaf spot of cotton progresses in northern Argentina even under unfavorable environmental conditions for fungal epidemics. Significant and consistent differences among cultivars were detected across seasons. Under low disease pressure observed in both seasons evaluated, fungicide applications did not significantly affect disease severity, yield or fiber quality.