ArticleScientific reports2021
Bayesian ridge regression shows the best fit for SSR markers in Psidium guajava among Bayesian models.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 31 citations in OpenAlex.
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- Genomic selection for crop improvement in fruits and vegetables: a systematic scoping review.Molecular breeding : new strategies in plant improvement · 2024Article
- SABO-ILSTSVR: a genomic prediction method based on improved least squares twin support vector regression.Frontiers in genetics · 2024Article
- Evaluation of eight Bayesian genomic prediction models for three micronutrient traits in bread wheat (Triticum aestivum L.).The plant genome · 2023Article
- Article
- Comparison of artificial intelligence algorithms and their ranking for the prediction of genetic merit in sheep.Scientific reports · 2022Article
- Genomic selection in tropical perennial crops and plantation trees: a review.Molecular breeding : new strategies in plant improvement · 2022Review
- Prediction of East Asian Brain Age using Machine Learning Algorithms Trained With Community-based Healthy Brain MRI.Dementia and neurocognitive disorders · 2022Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Markers are an important tool in plant breeding, which can improve conventional phenotypic breeding, generating more accurate information outcoming better decision making. This study aimed to apply and compare the fit of different Bayesian models BRR, BayesA, BayesB, BayesB (setting the value from very low to [Formula: see text] = [Formula: see text]), BayesC and Bayesian Lasso (LASSO) for predictions of the genomic genetic values of productivity and quality traits of a guava population. The models were fitted for traits fruit mass, pulp mass, soluble solids content, fruit number, and production per plant in the genomic prediction with SSR markers, obtained through the CTAB extraction method with 200 primers. The Bayesian ridge regression model showed the best results for all traits and was chosen to predict the individual's genomic values according to the cross-validation data. A good stabilization of the Markov and Monte Carlo chains was observed with the mean values close to the observed phenotypic means. Heritabilities showed good predictive accuracy. The model showed strong correlations between some traits, allowing indirect selection.
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