Found: 8
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Genome‐enabled prediction through machine learning methods considering different levels of trait complexity.
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- Crop Science, 2021, v. 61, n. 3, p. 1890, doi. 10.1002/csc2.20488
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- Article
Prediction of the importance of auxiliary traits using computational intelligence and machine learning: A simulation study.
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- PLoS ONE, 2021, v. 16, n. 11, p. 1, doi. 10.1371/journal.pone.0257213
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- Article
Genetic diversity and heterotic grouping of sorghum lines using SNP markers.
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- Scientia Agricola, 2021, v. 78, n. 6, p. 1, doi. 10.1590/1678-992X-2020-0039
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- Article
Identification of mega‐environments for grain sorghum in Brazil using GGE biplot methodology.
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- Agronomy Journal, 2021, v. 113, n. 4, p. 3019, doi. 10.1002/agj2.20707
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- Article
Combining ability of biomass sorghum in different crop years and sites for bioenergy generation.
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- Agronomy Journal, 2020, v. 112, n. 3, p. 1549, doi. 10.1002/agj2.20123
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- Article
Introgression of the bmr6 allele in biomass sorghum lines for bioenergy production.
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- Euphytica, 2020, v. 216, n. 6, p. 1, doi. 10.1007/s10681-020-02635-5
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- Article
Application of fuzzy logic for adaptability and stability studies in flood‐irrigated rice (Oryza sativa).
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- Plant Breeding, 2021, v. 140, n. 6, p. 1002, doi. 10.1111/pbr.12973
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- Article
Phenotypic and molecular characterization of sweet sorghum accessions for bioenergy production.
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- PLoS ONE, 2017, v. 12, n. 8, p. 1, doi. 10.1371/journal.pone.0183504
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- Article