Results 201 to 210 of about 129,505 (245)

AGIcam: An open‐source Internet of Things–based camera system for automated in‐field phenotyping and yield prediction

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Continuous, high‐frequency monitoring is essential to capture rapid phenological transitions and dynamic crop responses to the environment. However, most phenotyping platforms lack the temporal resolution and automation required for consistent, season‐long trait assessment.
Worasit Sangjan   +5 more
wiley   +1 more source

Automatic measurement of rice tiller angle from unmanned aerial vehicle images

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Rice (Oryza sativa L.) tiller angle is an important trait that influences plant architecture, canopy light interception, and yield potential. In this study, we proposed a deep learning‐based pipeline for automated measurement of rice tiller angle and plant base width using unmanned aerial vehicle (UAV) imagery.
Tan‐Hanh Pham   +10 more
wiley   +1 more source

Bayesian optimized color filter: A fast method for segmentation of plant phenotypes from 3D point cloud images

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Multispectral three‐dimensional (3D) imaging offers substantial potential for plant phenotyping, yet manual segmentation of plant organs remains a bottleneck in breeding programs. We developed a color‐based filtering workflow for faba bean (Vicia faba L.) point clouds that optimizes lower and upper thresholds of spectral indices and broadband ...
Lennart Scheer   +6 more
wiley   +1 more source

Scaling up soybean breeding: Satellite imagery delivers accurate maturity estimation across plot sizes

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate and scalable phenotyping is essential for accelerating genetic gain in soybean (Glycine max (L.) Merr.) breeding programs. Traditional methods for estimating physiological maturity are labor‐intensive and prone to subjectivity, limiting throughput and consistency. This study evaluates the potential of high‐resolution satellite imagery
Anastasios Mazis   +6 more
wiley   +1 more source

Canola yield prediction and genotype selection using uncrewed aerial system multispectral imagery and machine learning models

open access: yesThe Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Evaluation and selection of canola breeding lines across multiple years and locations are vital for variety development. However, accurately measuring canola (Brassica napus L.) yield under field conditions is challenging due to end‐of‐season events such as rain, windstorms, and hail, as well as variability in plant maturity and pod shattering.
Mohammad Jony   +4 more
wiley   +1 more source

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