Results 191 to 200 of about 52,638 (264)

Genome-Wide Identification and Expression Analysis of the <i>WSD</i> Gene Family in Wheat. [PDF]

Genes (Basel)
Liu C, Niu Z, Yu H, Gu B, Jia Y, Xie D, Wang R.   +6 more
europepmc   +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

Creation of the First Comparative Gluten Allergenicity Map Using a Mouse Model: A Preclinical Tool to Establish Substantial Equivalence of Novel Wheat Glutens. [PDF]

Int J Mol Sci
Jorgensen R, Gao H, Acharya HG, Srkalovic MB, Van Antwerp C, Ng PKW, Gangur V.   +6 more
europepmc   +1 more source

Predicting soybean aboveground biomass in the short‐season region of Canada: Integrating vegetative cover and canopy height

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Aboveground biomass (ABM) is a key determinant of soybean (Glycine max [L.] Merr.) yield and can be used to select for stress‐resilient cultivars. The objective of our study was to develop a predictive model describing ABM in short‐season soybean from vegetative cover (VC) and canopy height (CH).
Malcolm J. Morrison, Thomas L. Hotte, A. Claire Gahagan, Nathaniel W. W. Ort, Elroy R. Cober   +4 more
wiley   +1 more source

Plastome diversity and phylogenetic insights among modern Egyptian wheat cultivars: Genome-Wide and Gene-Level perspectives. [PDF]

BMC Plant Biol
Al-Andal A.
europepmc   +1 more source

Drone‐based phenotyping of maize for multiple disease resistance and yield in breeding field trials

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Improving selection for multiple disease resistance (MDR) and yield in maize (Zea mays L.) requires high‐throughput, objective phenotyping tools, particularly under field conditions where several foliar diseases co‐occur. We evaluated drone‐based multispectral vegetation indices (VIs) for predicting resistance to northern leaf blight (NLB ...
Danilo E. Moreta, Nina Blahut, Nicholas Kaczmar, Judith M. Kolkman, Gary Bergstrom, Margaret Smith, Michael A. Gore, Rebecca Nelson   +7 more
wiley   +1 more source

Wheat historical phenotypic data from European genebanks as an important resource for research and breeding. [PDF]

Sci Data
Le Floch E, Adam-Blondon AF, Alaux M, Bardet E, Bas N, Bassi FM, Boczkowska M, Bolc P, Brouwer M, Chalhoub B, De Blok R, Desheva G, Etukala JR, Flores R, Galit I, Groenink W, Hauptvogel R, Hoekstra R, Kehel Z, Kersey P, Kowalik R, Kumar S, Kyosev B, Lange M, Lazăr C, Marinciu C, Martín-Lammerding D, Motor A, Pachipala M, Pallero-Baena M, Petcu E, Pietrusińska-Radzio A, Podyma W, Pommier C, Puchta-Jasińska M, Puła S, Reiniers L, Ruff J, Ruiz M, Sansoni F, Schierscher B, Șerban G, Serex S, Vaccino P, Van Treuren R, Vasile M, Vasilescu L, Visioni A, Weise S, Wijnker E, Zaim M, Reif JC, Berkner MO.   +52 more
europepmc   +1 more source

Phenotype imputation using high‐throughput phenotyping produces a new secondary trait for further selection modeling

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Data from high‐throughput phenotyping (HTP) could be used for phenotype imputation to enhance genomic selection (GS) or gene discovery, but this has not been explored in crop species. Three machine learning models: multiple linear regression (MLR), missForest, and k‐nearest neighbors, were evaluated for grain yield (GY) phenotype imputation in
Raysa Gevartosky, Lucas Berger Munaro, Jessica E. Rutkoski   +2 more
wiley   +1 more source

VERNALIZATION2 alters early tiller development in a facultative spring hexaploid bread wheat. [PDF]

New Phytol
Hirsz D, Taylor H, Lacey I, Wu W, Gauley A, Dixon L.   +5 more
europepmc   +1 more source