Results 101 to 110 of about 21,140 (246)

High‐throughput phenotyping for the prediction and quantification of flower‐related traits in sugarcane

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Sugarcane (Saccharum spp.), a C4 plant, is a vital renewable biofuel and sugar source for industries worldwide. However, synchronizing flowering between parental lines often poses challenges for breeders, hindering effective crossbreeding efforts.
Paulo H. da Silva Santos, João R. Vieira Manechini, Carlos Augusto Dias Kanthack Jr., Mauro Alexandre Xavier, Samira Domingues Carlin, Dilermando Perecin, Thiago G. Marconi, Leandro G. Marconi, Elisson Antonio da Costa Romanel, Stephen Derek Jackson, Marcos. G. A. Landell, Luciana R. Pinto   +11 more
wiley   +1 more source

Oscilação genética em diferentes tamanhos de população sob seleção

Arquivo Brasileiro de Medicina Veterinária e Zootecnia, 2002
Com o objetivo de estudar alguns fatores que influenciam a seleção em longo prazo, foram utilizados dados simulados pelo programa GENESYS, considerando: duas herdabilidades, dois tamanhos de população, três níveis de repetição e 20 gerações, para ...
P.L.S. Carneiro, F.J.C. Corrêa, J.M. Carneiro Júnior, R.F. Euclydes, C.S. Pereira, R.A. Torres, M.G.M. Silva   +6 more
doaj   +1 more source

Insights into biomass accumulation and challenges in grain yield prediction of elite breeding materials using UAV‐based vegetation indices in soft red winter wheat

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract High‐throughput phenotyping (HTP) techniques have brought new opportunities to understand and evaluate key traits in plant breeding programs. Combining multiple measures through time and random regression models permits a more comprehensive understanding of the genetic and environmental effects on trait expression over time. This study aims to
Felipe Sabadin, Amelia Loeb, Francis Reith, Alexis Perry, Sunilda Frias, Demetrius Ragland, Limei Liu, Wynse Brooks, Ranjita Thapa, Julie Hansen, Christopher Pierce, Virginia M. Moore, Gina Brown‐Guedira, Ian Ray, Michael A. Gore, Kelly Robbins, Nicholas Santantonio   +16 more
wiley   +1 more source

Impact of Model Parameterisation and Variance Component Estimates on Genomic Predictions of Carcass Traits in Montana Composite Cattle. [PDF]

J Anim Breed Genet
ABSTRACT This study evaluated the influence of variance component (VC) estimates, obtained from different models and two relationship matrices, pedigree‐based (BLUP) and genomic information‐based (ssGBLUP), on genomic predictions of carcass traits in Montana composite cattle.
Almeida CA, de Carvalho FE, Bis FC, Carvalho RSB, de Mattos EC, Espigolan R, Eler JP, Gama LTD, Baldi F, Ferraz JBS.   +9 more
europepmc   +2 more sources

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

Advancing Canning Quality in Common Beans: An Integrated Farm‐to‐Can Framework Combining Breeding, Processing, and Artificial Intelligence

Legume Science, Volume 8, Issue 2, June 2026.
ABSTRACT Common beans (Phaseolus vulgaris L.) are essential raw material for the canning industry. This article reviews recent advances in assessing canning quality and the integration of artificial intelligence (AI) into breeding methodologies aimed at developing genotypes with superior yield and canning‐quality traits.
Arash Ghaitaranpour, Biniam Kebede, Mohsen Yoosefzadeh‐Najafabadi   +2 more
wiley   +1 more source

Perspectives from Agriculture: Advances in livestock breeding-Implications of aquaculture genetics [PDF]

In this paper we present livestock breeding developments that could be taken into consideration in the genetic improvement of farmed aquaculture species, especially in freshwater fish.
Nguyen, N.H., Ponzoni, R.W., WorldFish Center   +2 more
core  

Bayes factor for linear mixed model in genetic association studies

Quantitative Biology, Volume 14, Issue 2, June 2026.
Abstract Bayes factor has advantages over p‐value as test statistics for association, particularly when comparing multiple non‐nested alternative models. An efficient method to compute Bayes factor for linear mixed model (LMM) in the context of genetic association studies is lacking.
Yongtao Guan, Daniel Levy
wiley   +1 more source

Genetic determination of characteristics related to semi-mechanized coffee harvests

Crop Breeding and Applied Biotechnology, 2020
Brazilian coffee cultivation was boosted over the last few decades by the mechanization of various field operations. Considering the influence of genetic factors on coffee harvesting efficiency, we aimed to evaluate the use of mechanized harvesting ...
Rodrigo Elias Batista Almeida Dias, Rafael Antônio Almeida Dias, César Elias Botelho, Juliana Costa de Rezende Abrahão, Tiago Teruel Rezende, Gladyston Rodrigues Carvalho   +5 more
doaj