Results 101 to 110 of about 760,293 (222)

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

PODD: An ontology-driven data repository for collaborative phenomics research

open access: yes, 2010
Phenomics, the systematic study of phenotypes, is an emerging field of research in biology. It complements genomics, the study of genotypes, and is becoming an increasingly critical tool to understand phenomena such as plant morphology and human diseases.
Kennedy, Gavin   +7 more
core   +1 more source

Philosophy of phenomic prediction and its incompatibility with causal inference

open access: yesThe 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   +2 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

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

open access: yesAgriEngineering
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   +3 more
doaj   +1 more source

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

open access: yesThe 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   +9 more
wiley   +1 more source

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

open access: yesThe 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   +3 more
wiley   +1 more source

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

open access: yesFrontiers 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   +4 more
doaj   +1 more source

Zegami - Plant Phenomics Data Visualisation Tool

open access: yes
<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  

Phenomic prediction of club wheat milling yields

open access: yesThe 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   +4 more
wiley   +1 more source

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