Results 141 to 150 of about 38,095 (258)

Genome-wide identification and expression analysis of salt-responsive bHLH transcription factors in the wheat (<i>Triticum aestivum</i>) genome. [PDF]

Front Plant Sci
Viitanen E, Hassan S, Vergara A, Aronsson H.   +3 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

Identification and validation of qPC-3A, a stable QTL for flour protein content in hard wheat (Triticum aestivum L.). [PDF]

Theor Appl Genet
Cha JK, Park H, Jang SG, Kwon Y, Lee SM, Kim KM, Kim WJ, Lee JH.   +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 mapping of QTLs for stripe rust resistance in bread wheat (Triticum aestivum L.). [PDF]

BMC Plant Biol
Sharma R, Kumar S, Prasad P, Kumar U, Yashveer S, Gangwar OP, Udupa S, Sharma I, Tiwari R, Sharma P.   +9 more
europepmc   +1 more source

Assessing double‐crop soybean management practices in central Illinois

Crop, Forage &Turfgrass Management, Volume 12, Issue 2, December 2026.
Giovani Preza Fontes, Dan Schaefer, Eric Miller, John Jones   +3 more
wiley   +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

Selection of Wheat (<i>Triticum aestivum</i> L.) Genotypes for Salinity Tolerance Based on Yield and Ionic Attributes Under Saline Soil Conditions. [PDF]

Life (Basel)
Alshamrani R, Al-Otayk SM, Elbasyoni IS, Motawei MI.   +3 more
europepmc   +1 more source

Assessing robustness and transferability of image‐based semantic segmentation models for major field crops

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Plant breeding is essential for crop improvement, yet progress is often hindered by slow, laborious, and subjective field phenotyping methods. High‐throughput phenotyping (HTP), particularly image‐based methodologies powered by machine learning, offers a pathway to overcome these limitations.
Gustavo N. Santiago, Pedro Cisdeli, German Mandrini, Mitchell Tuinstra, Ignacio A. Ciampitti   +4 more
wiley   +1 more source

Identification of resistance sources and genomic regions regulating spot blotch resistance in Asian bread wheat (Triticum aestivum L.) via genome-wide association study. [PDF]

Plant Genome
Aggarwal N, He X, Rathore M, Jan F, Gupta V, Mir RR, Singh PK.   +6 more
europepmc   +1 more source