Pengcheng Hu

Latest

• Climate change enhances stability of wheat-flowering-date
• Quantification of the Cumulative Shading Capacity in a Maize–Soybean Intercropping System Using an Unmanned Aerial Vehicle
• Unsupervised Plot-Scale LAI Phenotyping via UAV-Based Imaging, Modelling, and Machine Learning
• Phenological optimization of late reproductive phase for raising wheat yield potential in irrigated mega-environments
• Comparison of Modelling Strategies to Estimate Phenotypic Values from an Unmanned Aerial Vehicle with Spectral and Temporal Vegetation Indexes
• Using a gene-based phenology model to identify optimal flowering periods of spring wheat in irrigated mega-environments
• Coupling of machine learning methods to improve estimation of ground coverage from unmanned aerial vehicle (UAV) imagery for high-throughput phenotyping of crops
• Extraction of phenotypic traits using unmanned aerial vehicle for field experiments in the agronomy and crop breeding
• Estimation of plot variability using unmanned aerial vehicle (UAV) for the wheat breeding trials
• Pixel size of aerial imagery constrains the applications of unmanned aerial vehicle in crop breeding
• Estimation of aboveground biomass and leaf area for a wheat trial index using unmanned aerial vehicle
• PhenoCopter: An cloud based solution for image processing captured by unmanned aerial vehicle in high throughput phenotyping
• Estimation of plant height using a high throughput phenotyping platform based on unmanned aerial vehicle and self-calibration: Example for sorghum breeding
• PhenoCopter: An cloud based platform to manage, process and visualize images captured by unmanned aerial vehicle for high throughput phenotyping
• The big impacts of image resolution on the estimation of ground coverage for wheat in UAV survey
• Estimation of canopy height using an unmanned aerial vehicle in the field during wheat growth season
• A field-based high-throughput method for acquiring canopy architecture using unmanned aerial vehicle images