Genome-wide detection of genotype environment interactions for flowering time in Brassica napus

X Han, Q Tang, L Xu, Z Guan, J Tu, B Yi, K Liu… - Frontiers in Plant …, 2022 - frontiersin.org
Flowering time is strongly related to the environment, while the genotype-by-environment
interaction study for flowering time is lacking in Brassica napus. Here, a total of 11,700,689 …

Combining GWAS and comparative genomics to fine map candidate genes for days to flowering in mung bean

KO Chiteri, A Rairdin, K Sandhu, S Redsun, A Farmer… - BMC genomics, 2024 - Springer
Abstract Background Mung bean (Vigna radiata (L.) Wilczek), is an important pulse crop in
the global south. Early flowering and maturation are advantageous traits for adaptation to …

Application of genomic selection at the early stage of breeding pipeline in tropical maize

Y Beyene, M Gowda, P Pérez-Rodríguez… - Frontiers in Plant …, 2021 - frontiersin.org
In maize, doubled haploid (DH) line production capacity of large-sized maize breeding
programs often exceeds the capacity to phenotypically evaluate the complete set of testcross …

Artificial neural networks in the prediction of genetic merit to flowering traits in bean cultivars

RDS Rosado, CD Cruz, LD Barili… - Agriculture, 2020 - mdpi.com
Flowering is an important agronomic trait that presents non-additive gene action. Genome-
enabled prediction allow incorporating molecular information into the prediction of individual …

Boosting predictive ability of tropical maize hybrids via genotype‐by‐environment interaction under multivariate GBLUP models

M Dalsente Krause, KOG Dias… - Crop …, 2020 - Wiley Online Library
Genomic selection has been implemented in several plant and animal breeding programs
and it has proven to improve efficiency and maximize genetic gains. Phenotypic data of …

Prediction of maize phenotypic traits with genomic and environmental predictors using gradient boosting frameworks

CC Westhues, GS Mahone, S da Silva… - Frontiers in plant …, 2021 - frontiersin.org
The development of crop varieties with stable performance in future environmental
conditions represents a critical challenge in the context of climate change. Environmental …

Climate and genetic data enhancement using deep learning analytics to improve maize yield predictability

P Sarzaeim, F Muñoz-Arriola… - Journal of experimental …, 2022 - academic.oup.com
Despite efforts to collect genomics and phenomics ('omics') and environmental data,
spatiotemporal availability and access to digital resources still limit our ability to predict …

Focusing the GWAS Lens on days to flower using latent variable phenotypes derived from global multienvironment trials

S Neupane, DM Wright, RO Martinez, J Butler… - The Plant …, 2023 - Wiley Online Library
Adaptation constraints within crop species have resulted in limited genetic diversity in some
breeding programs and areas where new crops have been introduced, for example, for lentil …

Quantile regression for genome-wide association study of flowering time-related traits in common bean

M Nascimento, ACC Nascimento, FF Silva, LD Barili… - PLoS …, 2018 - journals.plos.org
Flowering is an important agronomic trait. Quantile regression (QR) can be used to fit
models for all portions of a probability distribution. In Genome-wide association studies …

Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids

F Bonnafous, G Fievet, N Blanchet… - Theoretical and applied …, 2018 - Springer
Key message This study compares five models of GWAS, to show the added value of non-
additive modeling of allelic effects to identify genomic regions controlling flowering time of …