The modern plant breeding triangle: optimizing the use of genomics, phenomics, and enviromics data
J Crossa, R Fritsche-Neto… - Frontiers in plant …, 2021 - frontiersin.org
Continued increases in genetic gain demonstrate the success of established public and
private plant breeding programs. Nevertheless, in the last two decades, a growing body of …
private plant breeding programs. Nevertheless, in the last two decades, a growing body of …
Phenomic selection: A new and efficient alternative to genomic selection
Recently, it has been proposed to switch molecular markers to near-infrared (NIR) spectra
for inferring relationships between individuals and further performing phenomic selection …
for inferring relationships between individuals and further performing phenomic selection …
[HTML][HTML] Re-imagining crop domestication in the era of high throughput phenomics
De novo domestication is an exciting option for increasing species diversity and ecosystem
service functionality of agricultural landscapes. Genomic selection (GS), the application of …
service functionality of agricultural landscapes. Genomic selection (GS), the application of …
Deep learning for predicting complex traits in spring wheat breeding program
Genomic selection (GS) is transforming the field of plant breeding and implementing models
that improve prediction accuracy for complex traits is needed. Analytical methods for …
that improve prediction accuracy for complex traits is needed. Analytical methods for …
Nonlinear kernels, dominance, and envirotyping data increase the accuracy of genome-based prediction in multi-environment trials
Modern whole-genome prediction (WGP) frameworks that focus on multi-environment trials
(MET) integrate large-scale genomics, phenomics, and envirotyping data. However, the …
(MET) integrate large-scale genomics, phenomics, and envirotyping data. However, the …
EnvRtype: a software to interplay enviromics and quantitative genomics in agriculture
Envirotyping is an essential technique used to unfold the nongenetic drivers associated with
the phenotypic adaptation of living organisms. Here, we introduce the EnvRtype R package …
the phenotypic adaptation of living organisms. Here, we introduce the EnvRtype R package …
Deep kernel and deep learning for genome-based prediction of single traits in multienvironment breeding trials
Deep learning (DL) is a promising method for genomic-enabled prediction. However, the
implementation of DL is difficult because many hyperparameters (number of hidden layers …
implementation of DL is difficult because many hyperparameters (number of hidden layers …
Genomic selection for end-use quality and processing traits in soft white winter wheat breeding program with machine and deep learning models
Simple Summary Wheat (Triticum aestivum L.) breeding programs mainly focus on
improving grain yield, biotic and abiotic stress tolerance, and end-use quality traits. End-use …
improving grain yield, biotic and abiotic stress tolerance, and end-use quality traits. End-use …
Enviromic assembly increases accuracy and reduces costs of the genomic prediction for yield plasticity in maize
Quantitative genetics states that phenotypic variation is a consequence of the interaction
between genetic and environmental factors. Predictive breeding is based on this statement …
between genetic and environmental factors. Predictive breeding is based on this statement …
MegaLMM: mega-scale linear mixed models for genomic predictions with thousands of traits
Large-scale phenotype data can enhance the power of genomic prediction in plant and
animal breeding, as well as human genetics. However, the statistical foundation of multi-trait …
animal breeding, as well as human genetics. However, the statistical foundation of multi-trait …