Multi-trait, multi-environment genomic prediction of durum wheat with genomic best linear unbiased predictor and deep learning methods

OA Montesinos-López, A Montesinos-López… - Frontiers in Plant …, 2019 - frontiersin.org
Although durum wheat (Triticum turgidum var. durum Desf.) is a minor cereal crop
representing just 5–7% of the world's total wheat crop, it is a staple food in Mediterranean …

Association mapping of flowering time QTLs and insight into their contributions to rapeseed growth habits

N Wang, B Chen, K Xu, G Gao, F Li, J Qiao… - Frontiers in plant …, 2016 - frontiersin.org
Plants have developed sophisticated systems to adapt to local conditions during evolution,
domestication and natural or artificial selection. The selective pressures of these different …

Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize

R Gevartosky, HF Carvalho, G Costa-Neto… - BMC Plant …, 2023 - Springer
Background Success in any genomic prediction platform is directly dependent on
establishing a representative training set. This is a complex task, even in single-trait single …

Quantile regression applied to genome-enabled prediction of traits related to flowering time in the common bean

AC Nascimento, M Nascimento, C Azevedo, F Silva… - Agronomy, 2019 - mdpi.com
Genomic selection (GS) aims to incorporate molecular information directly into the prediction
of individual genetic merit. Regularized quantile regression (RQR) can be used to fit models …

Identification of a genomic region controlling thermotolerance at flowering in maize using a combination of whole genomic re-sequencing and bulked segregant …

W Zeng, J Shi, C Qiu, Y Wang, S Rehman, S Yu… - Theoretical and Applied …, 2020 - Springer
Key message A novel genomic region controlling thermotolerance at flowering was
identified by the combination of whole genomic re-sequencing and bulked segregant …

Predictive breeding for maize: Making use of molecular phenotypes, machine learning, and physiological crop models

JD Washburn, MB Burch, JAV Franco - Crop Science, 2020 - Wiley Online Library
Maize (Zea mays L.) has been a focus of scientific research and breeding for over a century.
It is also one of the most economically important crops in the world, with a value of …

Using Genome-Wide Predictions to Assess the Phenotypic Variation of a Barley (Hordeum sp.) Gene Bank Collection for Important Agronomic Traits and Passport …

Y Jiang, S Weise, A Graner, JC Reif - Frontiers in Plant Science, 2021 - frontiersin.org
Genome-wide predictions are a powerful tool for predicting trait performance. Against this
backdrop we aimed to evaluate the potential and limitations of genome-wide predictions to …

[HTML][HTML] Genome-wide haplotype analysis improves trait predictions in Brassica napus hybrids

HU Jan, M Guan, M Yao, W Liu, D Wei, A Abbadi… - Plant science, 2019 - Elsevier
Combining ability is crucial for parent selection in crop hybrid breeding. Many studies have
attempted to provide reliable and quick methods to identify genome regions in parental lines …

Partial least squares enhances genomic prediction of new environments

OA Montesinos-López, A Montesinos-López… - Frontiers in …, 2022 - frontiersin.org
In plant breeding, the need to improve the prediction of future seasons or new locations
and/or environments, also denoted as “leave one environment out,” is of paramount …

Field-based high-throughput phenotyping enhances phenomic and genomic predictions for grain yield and plant height across years in maize

A Adak, AJ DeSalvio, MA Arik… - G3: Genes, Genomes …, 2024 - academic.oup.com
Field-based phenomic prediction employs novel features, like vegetation indices (VIs) from
drone images, to predict key agronomic traits in maize, despite challenges in matching …