Results 201 to 210 of about 94,061 (308)

Multiple ortho‐mosaicking software pipelines produce comparable imagery‐derived wheat phenotypes

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Unmanned aerial systems (UAS) equipped with multispectral and RGB sensors offer valuable data for monitoring crop health and assessing disease severity. However, the wide range of available photogrammetric software complicates software selection for high‐throughput plant phenotyping.
Sanju Shrestha, Phillip D. Alderman, Grishma Ojha, Brett F. Carver   +3 more
wiley   +1 more source

Genome-Wide Comparative Analysis of WRKY Gene Family Explores Insight Into the Evolution and Expression Divergence in the Genus <i>Triticum</i>. [PDF]

Food Sci Nutr
Li X, Gao X, Wang Z, Shi J, Zhang H, Wang L, Xia J, Wang C, Zhao Z, Zhang Y, Li J.   +10 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

Electrospun Fibers Encapsulating <i>Triticum vulgare</i> Extract as a Potential Scaffold for the Regeneration of Subepithelial Connective Tissue. [PDF]

Molecules
Figueroa-Ariza LT, Cely-Veloza W, Coccaro M, Gualtero DF, Jiménez RA, Coy-Barrera E, Pinzón-García AD, Lesmes Y, Chambrone L, Lafaurie GI.   +9 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

Pan-genomic diversity of the EPF/EPFL gene family across wild and modern wheat species. [PDF]

BMC Plant Biol
Javed J, Wang G, Sun S, Saleem H, Baloch FS, Xue X, Gou JY.   +6 more
europepmc   +1 more source

Knockout of TaCKX2.2 in Wheat Improved Grain Yield by Increasing Grain Number Per Spike and Grain Size Under Field Production Conditions

Plant, Cell &Environment, EarlyView.
Zhenzhen Zhu, Fangyao Sun, Guihua Bai, Yanpeng Ding, Fuping Zhang, Xi He, Zhongfu Ni, Qixin Sun, Zhenqi Su   +8 more
wiley   +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

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

Triticum aestivum Färbreaktion

Aus der LV UE Einführung in die Laborpraxis 330051 Mikroskopie: Triticum aestivum Färbreaktion Inhalt:Prof. Mag. Dr.
Karpe, Dennis, Till, Susanne
core