Results 111 to 120 of about 760,293 (222)

LabEmbryoCam: An opensource phenotyping system for developing aquatic animals

HardwareX
Phenomics is the acquisition of high-dimensional data on an individual-wide scale and is proving transformational in areas of biological research related to human health including medicine and the crop sciences.
Ziad Ibbini, Maria Bruning, Sakina Allili, Luke A Holmes, Ellen Tully, Jamie McCoy, Benjamin Larsen, Tony Wilson, Guy Ludford, Jack Barrett-Kelly, John I. Spicer, Oliver Tills   +11 more
doaj   +1 more source

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

Phenomics Data Platforms: Introduction and user training Workshop: Included Topics:Plant Phenomics PlatformFAIR-Data ManagementPHIS-phenomics information systemEuropean EGI data servicesDeep-Learning methods and tools

, 2023
DoctoralIn March 6-7 2023, The EGI-ACE use case project “PHIS deployment on EGI cloud” is organizing a workshop on plant “Phenomics data platforms – introduction and user training workshop”.The aim of the workshop is to support image-data users to adopt ...
Himanen, Kristiina, Pascal, Neveu, Manzi, Andrea, Rousseau, David, Poque, Sylvain, Nègre, Vincent, Metuarea, Herearii, Alic, Isabelle   +7 more
core   +1 more source

MaizeEar‐SAM: Zero‐shot maize ear phenotyping

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Quantifying the variation in yield component traits of maize (Zea mays L.), which collectively determine the overall productivity of this globally significant crop, is critical to plant genetics research, plant breeding, and the development of improved agronomic practices.
Hossein Zaremehrjerdi, Lisa Coffey, Talukder Jubery, Huyu Liu, Jon Turkus, Kyle Linders, James C. Schnable, Patrick S. Schnable, Baskar Ganapathysubramanian   +8 more
wiley   +1 more source

Optimization of γ-Aminobutyric Acid Production in Brown Rice via Prolonged Seed Priming

Plants
Germinated whole seeds possess elevated levels of bioactive nutrients; however, their application is hindered by several constraints. The germination process is typically time-consuming, and germinated seeds present challenges in terms of storage and ...
Lingxiang Xu, Xiaoan Wang, Qixiang Li, Yuqing Niu, Guohui Ding, Jiawei He, Weiping Chen, Dagang Tian   +7 more
doaj   +1 more source

High‐throughput unmanned aerial vehicle phenomics and machine learning enables accurate early single‐plant biomass prediction in lettuce

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Lettuce (Lactuca sativa L.) exhibits pronounced genotype and environment‐dependent growth variation, making early, non‐destructive single‐plant biomass prediction critical for breeding. However, harvest‐based measurements fail to capture growth dynamics.
Görkem Eren Özdemir, Ahmet Rıza Ağır, Burak Aktürk, Nida Selen Baysal, Adem Dogan, Aaron J. DeSalvio, Mustafa A. Arik, Yasin Topcu, Alper Adak   +8 more
wiley   +1 more source

Next-Generation Crop Breeding: Harnessing Genomics, Phenomics and Machine Learning: A Review

International audienceGlobal food security requires crop improvement strategies that can respond to population growth, climate variability and increasing constraints on agricultural resources.
Mahiboobsa, ., Patel, Divya, Patidar, Dilip, Singh, Namita, Gautam, Budhayash, Nayak, Anup Aurojyoti, Maru, Harsh Harilal, Singh, Vikram   +7 more
core  

Evaluation of uncrewed aerial system‐derived vegetation indices for forage trait phenomic prediction in oat–pea intercrop breeding trials

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accelerating genetic gain in intercrop forage breeding requires scalable phenotyping approaches that can capture both yield and quality variation across complex genotype combinations. This study evaluated the use of uncrewed aerial system (UAS)‐derived multispectral vegetation indices (VIs) for predicting forage yield and nutritive quality in ...
Milcah Kigoni, Raysa Gevartosky, Lucas B. Munaro, Tim Mies, Luis Gehrke, Jessica Rutkoski, Juan David Arbelaez   +6 more
wiley   +1 more source

Evaluation of LiDAR‐based canopy trait estimation in Midwestern row crops

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Stand count, the number of plants per unit ground area, and leaf area index (LAI), the ratio of leaf area to ground area, are critical traits for crop research but are traditionally measured using labor‐intensive methods. While new sensing technologies are being developed, quantifying improvement in measurement efficiency and data quality ...
Matthew H. Siebers, Peng Fu, Stephen P. Long, Justin M. McGrath, Carl J. Bernacchi   +4 more
wiley   +1 more source

Genomic and phenomic prediction models improve selection accuracy for complex traits in alfalfa

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Predictive breeding has been proposed as an effective approach to accelerate genetic gain for complex traits. Genomic prediction (GP) models have been developed in alfalfa (Medicago sativa L.) for key traits in the last decade. More recently, phenomic prediction (PP) models have been proposed as a low‐cost, high‐throughput alternative to GP in
Pablo Sipowicz, Ayush K. Sharma, Mario H. Andrade, Claudio C. Fernandes Filho, L. Felipe V. Ferrão, Aditya Singh, Anju Biswas, Charlie Messina, Esteban Rios   +8 more
wiley   +1 more source