Results 201 to 210 of about 2,082,703 (256)

Phenotypic Differentiation Between Highland and Coastal Quinoa Under Cold Stress Conditions. [PDF]

Plant Cell Environ
Rakasi N, Kienbaum L, Böndel KB, Wiederstein JD, Raju NKG, Schmöckel SM, Schmid KJ.   +6 more
europepmc   +1 more source

Advances in the Integration of Genomic and Phenomic Tools in Cowpea Breeding for Improving Stress Resilience and Grain Yield and Quality

Legume Science, Volume 8, Issue 4, December 2026.
ABSTRACT Cowpea (Vigna unguiculata L. Walp) is a multi‐use crop highly valued as a food crop, high‐protein fodder, and sustainable cover crop. Yet, it remains underused, and yields in most growing regions are below the crop's potential due to multiple biotic and abiotic stresses.
Habib Akinmade, Luis Getino, María Muñoz‐Amatriaín, Esteban Rios   +3 more
wiley   +1 more source

SMART: Speedy Measurement of Arabidopsis Rosette Traits

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Most computer vision‐ and machine learning‐based plant phenotyping systems compute traits such as shape and size rather than the color distribution of the plant surface, even though color can provide important insights into plant physiology. Therefore, we developed Speedy Measurement of Arabidopsis Rosette Traits (SMART), an open‐source plant ...
Suxing Liu, Allison E. Harris, Jiamei Li, Fiona L. Goggin, David G. Mendoza‐Cozatl, Alexander Bucksch   +5 more
wiley   +1 more source

PlantCV v4: Image analysis software for high‐throughput plant phenotyping

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
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, Keely E. Brown, Hudanyun Sheng, Parag K. Bhatt, Jorge Gutierrez, Dominik Schneider, Anna L. Casto, Lucia Acosta‐Gamboa, Joe G. Ballenger, Fabio Barbero, Jackson Braley, Autumn M. Brown, Leonardo Chavez, Shannon Cunningham, Malinda Dilhara, Adam M. Dimech, Joseph G. Duenwald, Annika Fischer, Jared M. Gordon, Chloe Hendrikse, Gabriela L. Hernandez, John G. Hodge, Martina Huber, Brandon M. Hurr, Sanaz Jarolmasjed, Karina Medina Jimenez, Samuel Kenney, Grant Konkel, Alexander Kutschera, Sunita Lama, Matthew Lohbihler, Argelia Lorence, Collin Luebbert, Nathaniel Ly, Heather K. Manching, Annarita Marrano, Susan Meerdink, Nicholas M. Miklave, Pavan Mudrageda, Katherine M. Murphy, J. David Peery, Ronald Pierik, Seth Polydore, Caleb Robey, Tess Rogers, Tyler J. Schultz, Eliza Seigel, Dhiraj Srivastava, Stephan Summerer, Josh Sumner, Chong Teng, Adriane E. Thompson, Jose C. Tovar, Tim van Daalen, Mark Watson, John J. Wheeler, Mark C. Wilson, Kaitlyn R. Ying, Alina Zare, Yutai Zhou, Malia A. Gehan, Noah Fahlgren   +61 more
wiley   +1 more source

OzBarley: A genetic and phenotypic data resource capturing the Australian barley breeding history. [PDF]

Sci Data
Baumann U, Kalashyan E, Schwerdt J, Box A, Brien C, Chalmers K, Coventry S, Ganesalingam A, Hyles J, Lobsey B, Lou H, Raubach S, Richmond S, Sainsbury G, Shaw PD, Sherman B, Stephen JR, Trevaskis B, Waugh R, Tucker MR, Berger B.   +20 more
europepmc   +1 more source

A systematic color correction pipeline for controlled‐environment imaging

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
ABSTRACT We present a stepwise color correction (CC) pipeline for controlled imaging environments. The workflow integrates flat‐field correction (FFC), gamma correction, and white‐balance correction, followed by a color‐mapping (CM) stage using machine‐learning regression—linear, partial least squares, and neural networks (NNs)—to deliver reliable CC ...
Collins Wakholi, Michael A. Hardigan, Jungmin Lee, Scott B. Lukas, Max J. Feldman, Kayla R. Altendorf, Jeffrey L. Neyhart, Devin A. Rippner   +7 more
wiley   +1 more source

Hemp seed counting and morphometric analysis method comparison

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract The USDA ARS Hemp Germplasm Laboratory recently acquired over 800 hemp accessions (Cannabis sativa L.). Variation in hemp seed size characteristics is needed to develop quantitative standards to support the transition of hemp grain into a commodity.
Tyler Gordon, Zachary Stansell
wiley   +1 more source

New biologically relevant resistance to bacterial wilt in heat-stressed tomato revealed by two-reference Genome Wide Association. [PDF]

PLoS Genet
Belny A, Desaint H, Rigal M, Carrère S, Gouzy J, Bonnet G, Labourey C, Albert E, Grivet L, Roux F, Vailleau F, Mary-Huard T, Berthomé R.   +12 more
europepmc   +1 more source

A systematic review of interventions targeting physical literacy outcomes for children and adolescents with ADHD: Effects on affective, cognitive, behavioural and physical domains

Review of Education, Volume 14, Issue 3, December 2026.
Abstract Attention‐deficit/hyperactivity disorder (ADHD) affects children and adolescents' educational, social and emotional aspects and can persist in adulthood. In this context, physical activity (PA) plays a crucial role in enhancing their physical and psychological well‐being and potentially increasing their health‐related quality of life (HRQoL ...
José Ignacio Calzada‐Rodríguez, María Mendoza‐Muñoz, Jorge Carlos‐Vivas, Laura Muñoz‐Bermejo   +3 more
wiley   +1 more source

Low-cost generation of clinical-grade, layperson-friendly pharmacogenetic passports using oligonucleotide arrays. [PDF]

Am J Hum Genet
Lanting P, Warmerdam R, Slager J, Brugge H, Ochi T, Benjamins M, Lopera-Maya E, Jankipersadsing S, Gelderloos-Arends J, Teuben D, Hendriksen D, Charbon B, Johansson L, Munnink TO, de Boer-Veger N, Lifelines NEXT Cohort Study, Lifelines Cohort Study, Wilffert B, Swertz M, Touw D, Deelen P, Knoers N, Dekens J, Franke L.   +23 more
europepmc   +1 more source