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7 datasets found
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Replication Data for: Optimizing Genomic-Enabled Prediction: A Feature Weight... N3 | TTL | RDF/XML | JSON-LD
CIMMYT EthiopiaThis study provides supplemental data to support the study on Optimizing Genomic-Enabled Prediction: A Feature Weighting Approach for Enhancing within Family Accuracy.Created January 20, 2025 • Updated January 20, 2025 -
Replication Data for: Genome-based genotype × environment prediction enhances... N3 | TTL | RDF/XML | JSON-LD
CIMMYT EthiopiaPotato 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...Created January 20, 2025 • Updated January 20, 2025 -
Replication Data for: Multi-generation genomic prediction of maize yield usin... N3 | TTL | RDF/XML | JSON-LD
CIMMYT EthiopiaGenomic prediction models may be used in plant breeding pipelines. They are often calibrated using multi-generation data and there is an open question of whether all available data or a subset of it should be used to calibrate genomic prediction models. Therefore, a study was undertaken to determine whether combining sparse selection indexes (SSIs) and...Created January 20, 2025 • Updated January 20, 2025 -
Multi-trait multi-environment genomic prediction of durum wheat N3 | TTL | RDF/XML | JSON-LD
CIMMYT EthiopiaIn this paper we cover multi-trait prediction of grain yield (GY), days to heading (DH) and plant height (PH) of 270 durum wheat lines that were evaluated in 43 environments (location-year combinations) in Bologna, Italy. The results of the multi-trait deep learning method also were compared with univariate predictions of the genomic best linear unbiased...Created January 20, 2025 • Updated January 20, 2025 -
Deep kernel of genomic and near infrared predictions in multi-environment bre... N3 | TTL | RDF/XML | JSON-LD
CIMMYT EthiopiaIn genomic prediction deep learning artificial neural network are part of machine learning methods that incorporate parametric, non-parametric and semi-parametric statistical models. Kernel methods are seeing more flexible, and easier to interpret than neural networks. Kernel methods used in genomic predictions comprise the linear genomic best linear...Created January 20, 2025 • Updated January 20, 2025 -
A Bayesian genomic multi-output regressor stacking model for predicting multi... N3 | TTL | RDF/XML | JSON-LD
CIMMYT EthiopiaA new statistical model is presented for genomic prediction on maize and wheat data comprising multi-trait, multi-environment data.Created January 20, 2025 • Updated January 20, 2025 -
Deep learning genomic-enabled prediction of plant traits N3 | TTL | RDF/XML | JSON-LD
CIMMYT EthiopiaMachine learning (ML) is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" (i.e., progressively improve performance on a specific task) from data, without being explicitly programmed to do this. ML is closely related to (and often overlaps with) computational statistics, which also focuses on...Created January 20, 2025 • Updated January 20, 2025
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