PlantCV v4: Image analysis software for high‐throughput plant phenotyping
Abstract PlantCV is an open‐source Python project aimed at developing tools to address a range of image‐based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data, and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding ...
Haley Schuhl +61 more
wiley +1 more source
Hyperspectral Imaging for Agricultural and Food Sensing: Applications, Data Analytics, and Deployment Challenges. [PDF]
Wen D, Dong Y, Hu L, Cao D, Li J.
europepmc +1 more source
Affordable Phenomics special topic—Foreword for The Plant Phenome Journal
Abstract The Affordable Phenomics special topic in The Plant Phenome Journal showcased recent advances that expand the accessibility, cost‐effectiveness, and scalability of plant phenotyping technologies. This collection of 15 articles presented innovative approaches, ranging from low‐cost sensors and open‐source analytical pipelines to artificial ...
Valerio Hoyos‐Villegas +1 more
wiley +1 more source
Early Detection of Postharvest Potato Tuber Dry Rot Based on Hyperspectral Imaging and a Dual-Branch ResNet12-SE Spatial-Spectral Fusion Network. [PDF]
Cao H +5 more
europepmc +1 more source
Spatial and temporal scales in plant phenotyping for crop water stress assessment: A review
Abstract Water stress is a major limiting factor for crop productivity worldwide, and its impacts are intensifying due to climate variability and increasing water scarcity. This review focuses on the spatial and temporal scales in plant phenotyping as a critical approach to improving crop water‐stress assessment and supporting precision water ...
Daniel Kingsley Cudjoe +3 more
wiley +1 more source
A multi-layer active intellectual property protection framework for hyperspectral image classification models. [PDF]
Xiao S +5 more
europepmc +1 more source
Abstract High‐throughput phenotyping (HTP) techniques have brought new opportunities to understand and evaluate key traits in plant breeding programs. Combining multiple measures through time and random regression models permits a more comprehensive understanding of the genetic and environmental effects on trait expression over time. This study aims to
Felipe Sabadin +16 more
wiley +1 more source
Non-destructive yield estimation of onion and garlic using UAV-based hyperspectral imaging and hybrid machine learning models. [PDF]
Su Y +6 more
europepmc +1 more source
Combining phenomic and genomic selection for pea breeding improvement
Abstract Pea (Pisum sativum L.) is a strategic crop in the development of sustainable agriculture. However, the genetic gain remains limited despite advances in breeding. Genomic selection holds promise to accelerate varietal improvement, but its high implementation cost restricts its use in crops.
Anthony Klein +15 more
wiley +1 more source
Abstract Traditionally, turfgrass color has been assessed through visual ratings or light box‐based digital image analysis, methods that are either subjective or labor‐intensive. In this study, we evaluated the potential of unmanned aerial vehicle (UAV)‐based multispectral and red‐green‐blue (RGB) imagery as a high‐throughput alternative for capturing ...
Ved Parkash +9 more
wiley +1 more source

