Results 151 to 160 of about 39,669 (258)

Identification of KASP markers and putative genes for herbicide (metribuzin) tolerance in common wheat (Triticum aestivum L.). [PDF]

BMC Plant Biol
Liu G, Mullan D, Liu D, Zhang A, Xu L, Liu H, Yan G.   +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

Integrative evolutionary and structural modeling of leaf rust resistance genes in wheat (<i>Triticum aestivum</i> subsp. and <i>T. monococcum</i>). [PDF]

Front Plant Sci
Almutairi MMR.
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

Alleviation of lead toxicity and enhancement of wheat (<i>Triticum aestivum</i> L.) yield and antioxidant capacity using silicon and humic acid amendments in contaminated soil. [PDF]

RSC Adv
Sohail MK, Ghafoor A, Tahir MA, Munir M, Waheed H, Abdel-Banat BMA.   +5 more
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

Functional analyses of homoeologous pericentromeric cohesion protective genes TaSGO1s during meiosis in Triticum aestivum. [PDF]

BMC Plant Biol
Hu K, Li X, Liu J, Zhuang T, Kong X, Wang M, Liao H, Lu P.   +7 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

Molecular regulators of regeneration and strategies for overcoming genotype-dependent recalcitrance in wheat (Triticum aestivum). [PDF]

Commun Biol
Wang YK, Wang YP, Zhou LZ.
europepmc   +1 more source

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate prediction of grain yield (GY) remains a major challenge in plant breeding due to complex interactions between genotype, environment, and management (G × E × M) factors. Remote sensing data from unmanned aerial vehicles (UAVs) equipped with multispectral sensors have emerged as a pivotal resource for high‐throughput phenotyping.
Swas Kaushal, Mohammad Maruf Billah, Mandeep Singh, Dante Koupal, Pradeep Raj Sitaula, Jyotirmoy Halder, Jagdeep Sidhu, Maitiniyazi Maimaitijiang, Sunish K. Sehgal   +8 more
wiley   +1 more source