Results 111 to 120 of about 722,503 (205)

Philosophy of phenomic prediction and its incompatibility with causal inference

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Breeding programs need to make decisions frequently to improve populations and develop varieties efficiently. These needs led to the development of genomic prediction in the early 2000s and phenomic prediction in the mid‐2010s. In practice, phenomic prediction techniques rely on the same statistical tools and computational frameworks as other ...
Mitchell J. Feldmann, Fangyi Wang, Daniel E. Runcie   +2 more
wiley   +1 more source

Root-TransUNet enables high-throughput phenotyping of Arabidopsis thaliana roots as a parameter in Heterodera schachtii parasitism

Frontiers in Plant Science
IntroductionPlant parasitism by sedentary plant-parasitic nematodes is a dynamic and continuously evolving process, accompanied by profound remodelling of host root system architecture across distinct infection stages.
Jie Zhou, Victor Hugo Moura de Souza, Lei Ju, Sebastian Eves-van den Akker, Ji Zhou, Ji Zhou, Olaf Prosper Kranse   +6 more
doaj   +1 more source

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

The 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, Benjamin Wittkop, Andreas Stahl, Olaf Sass, Gregor Welna, Hanna Tietgen, Rod J. Snowdon   +6 more
wiley   +1 more source

Time course sensor‐based phenotyping can predict Ascochyta blight disease severity in Cicer species

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Ascochyta blight is a widely occurring chickpea fungal disease that can cause severe yield loss. Breeding for crop resistance benefits from high‐throughput evaluation of plant–pathogen interactions in genotypes which can serve as sources of resistance.
Florian Tanner, Judith Atieno, Sara Blake, Marzena Krysinska‐Kaczmarek, Chris Brien, Mohsen Khani, Kenneth Clarke, Darren Plett, Jennifer Davidson, Bettina Berger   +9 more
wiley   +1 more source

Root and shoot phenotyping elucidate plant growth‐promoting microorganisms effects on wheat under water deficit

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Water scarcity represents a major constraint to crop productivity, increasing interest in sustainable strategies such as plant growth‐promoting microorganisms (PGPM). This study investigated the effects of a commercial PGPM consortium, composed of four Bacillus spp.
Christian Lorenz, Lamis Abdelhakim, Carmen Arena, Klára Panzarová   +3 more
wiley   +1 more source

Use of Phenomics in the Selection of UAV-Based Vegetation Indices and Prediction of Agronomic Traits in Soybean Subjected to Flooding

AgriEngineering
Flooding is a frequent environmental stress that reduces soybean growth and grain yield in many producing areas in the world, such as the United States, Southeast Asia, and Southern Brazil.
Charleston dos Santos Lima, Darci Francisco Uhry Junior, Ivan Ricardo Carvalho, Christian Bredemeier   +3 more
doaj   +1 more source

Phenomic prediction of club wheat milling yields

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Near‐infrared reflectance spectroscopy (NIRS) provides a nondestructive method for estimating physical and chemical grain properties and is widely used in breeding programs to phenotype traits such as texture, color, moisture, protein, and oil content. Club wheat (Triticum aestivum subsp.
Peter Schmuker, Alecia Kiszonas, Sheri Rynearson, Kim Garland‐Campbell, Michael Pumphrey   +4 more
wiley   +1 more source

Zegami - Plant Phenomics Data Visualisation Tool

<p>The Adelaide node of the Australian Plant Phenomics Facility, The Plant Accelerator, measures the growth and performance of hundreds of plants using automation and digital imaging, referred to as plant phenomics. To facilitate the exploration of

core  

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

The 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, Sarah Anderson, Guilherme Simiqueli, Adam Barbeau, Sara Tirado Tolosa, Julien Linares, Nathan Coles   +6 more
wiley   +1 more source

Bridging affordable phenomics with high-efficiency controlled environment agriculture for data-driven agriculture

Frontiers in Agronomy
Controlled environment agriculture (CEA) is essential for resilient crop production but faces high energy demands and operational costs. While high-throughput phenotyping (HTP) provides critical biological feedback to optimize these systems, conventional
Hsing-Ying Chung, Yuan-Kai Tu, Han-Wei Chen, Ching-Shan Tseng, Daisuke Sugiura   +4 more
doaj   +1 more source