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Autor: Jose Crossa
14th Semi-Arid Wheat Yield Trial Genotyping-by-sequencing Data
Susanne Dreisigacker Jose Crossa Jesse Poland (2015)
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Dataset
17th Semi-Arid Wheat Yield Trial Genotyping-by-sequencing Data
Susanne Dreisigacker Jose Crossa Jesse Poland (2015)
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Dataset
Multi-environment genomic prediction of plant traits using deep learners with dense architecture
Osval Antonio Montesinos-Lopez Jose Crossa (2018)
Artículo
Shared Data Resources Deep Learning Genomic Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ACCURACY GENOMICS NEURAL NETWORKS FORECASTING DATA MARKER-ASSISTED SELECTION
Osval Antonio Montesinos-Lopez Pawan Singh Jose Crossa (2020)
Genomic selection (GS) is an important method used in plant and animal breeding. The experimental data provided in this study contain counting data. These datasets were used to support research on efficient methodologies for multivariate count data outcomes including a multivariate Poisson deep neural network (MPDN) model, a conventional multivariate generalized Poisson regression model, and a univariate Poisson deep learning models. The results of the analyses are presented in a corresponding publication.
Dataset
Guillermo Gerard Paolo Vitale Susanne Dreisigacker Morten Lillemo Jose Crossa (2023)
This study provides supplemental data to support the study on Optimizing Genomic-Enabled Prediction: A Feature Weighting Approach for Enhancing within Family Accuracy.
Dataset
Rodomiro Ortiz Jose Crossa Paulino Pérez-Rodríguez Jaime Cuevas (2021)
Potato breeding efficiency can be improved by increasing the reliability of selection and identifying promising germplasm for crossing. The data provided in these datasets were used to compare the prediction accuracy of genomic-estimated breeding values for several potato (Solanum tuberosum L.) breeding clones and released cultivars evaluated in three locations in northern and southern Sweden. The analysis included several traits such as tuber starch percentage and total tuber weight. Results of the analyses are reported in an accompanying journal article.
Dataset
J. Jesús Cerón Rojas Sergio Pérez-Elizalde Jose Crossa (2020)
In breeding, the net genetic merit of candidates for selection is a linear combination of the breeding values of the traits of interest weighted by their respective economic values. This dataset contains the R code that accompanies a publication that describes an evaluation of linear phenotypic selection indices (LPSI) and Bayesian linear phenotypic selection indices (BLPSI).
Dataset
A novel method for genomic-enabled prediction of cultivars in new environments
Osval Antonio Montesinos-Lopez Brandon Alejandro Mosqueda González Jose Crossa (2023)
Artículo
Genomic Best Linear Unbiased Prediction Gains in Accuracy Genomic Prediction Novel Methods CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPE ENVIRONMENT INTERACTION METHODS ENVIRONMENT
Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.)
Filippo Maria Bassi Alison Bentley Rodomiro Ortiz Jose Crossa (2016)
Artículo
Marker-Aided Breeding CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING VALUE GENETIC GAIN GENOTYPE ENVIRONMENT INTERACTION QUANTITATIVE TRAIT LOCI
Sivakumar Sukumaran Jose Crossa DIEGO JARQUIN Matthew Paul Reynolds (2016)
This study contains spring wheat yield data (1st, 2nd, and 3rd WYCYTs and 1st, 2nd, 3rd and 4th SATYNs) from 136 international environments that were used to evaluate the predictive ability of different models in diverse environments by modeling G×E using the pedigree-derived additive relationship matrix (A matrix).
Dataset