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Registro Completo |
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
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Data corrente: |
30/03/2026 |
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Data da última atualização: |
30/03/2026 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
PIMENTEL, M. P. C.; PASSOS, A. M. A. dos; PRIGENT, S.; CASSAN, C.; TARDIN, F. D.; FERREIRA, M. S. L.; PÉTRIACQ, P.; SANTOS, M. C. B. |
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Afiliação: |
MARIANA PINHEIRO COSTA PIMENTEL, UNIVERSIDADE FEDERAL DO ESTADO DO RIO DE JANEIRO; ALEXANDRE MARTINS ABDAO DOS PASSOS, CNPMS; SYLVAIN PRIGENT, UNIVERSITY OF BORDEAUX; CÉDRIC CASSAN, UNIVERSITY OF BORDEAUX; FLAVIO DESSAUNE TARDIN, CNPMS; MARIANA SIMÕES LARRAZ FERREIRA, UNIVERSIDADE FEDERAL DO ESTADO DO RIO DE JANEIRO; PIERRE PÉTRIACQ, UNIVERSITY OF BORDEAUX; MILLENA C. BARROS SANTOS, UNIVERSITY OF BORDEAUX. |
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Título: |
Exploiting predictive metabolomics of pearl millet phenotypic traits using untargeted profiling across a Brazilian germplasm panel. |
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Ano de publicação: |
2026 |
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Fonte/Imprenta: |
Metabolomics, v. 22, article 46, 2026. |
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DOI: |
https://doi.org/10.1007/s11306-026-02407-7 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract Introduction Pearl millet is a high nutritional cereal recognised for its agro-climatic resilience, making it relevant for food security under climate change scenarios. Phenotypic traits are indicative of crop performance, stability and adaptability, yet the potential of metabolomics to predict these traits has not been explored. Objectives This study aimed to identify metabolite–trait associations in the Brazilian germplasm core collection, comprising 203 pearl millet genotypes, by combining untargeted metabolomics with machine-learning models. Methods Grains metabolic profiles were obtained using untargeted UHPLC-LTQ-Orbitrap-HRMS. Phenotypic data were sourced from standardised evaluations conducted by Embrapa across different years and field trials within the Sete Lagoas experimental station (Minas Gerais, Brazil). Generalised linear modelling with penalisation (GLM) and Random Forest was applied to explore the correlation between metabolism and 21 phenotypic traits. Results GLM successfully predicted eight qualitative and seven quantitative traits. Prediction accuracy was higher for qualitative traits, reflecting their comparatively simpler genetic architecture, whereas quantitative traits also achieved satisfactory performance (R² ≥ 0.6). Key predictors included phenolic compounds, amino acids, fatty acids, and carbohydrates. Notably, several associations corresponded to metabolites involved in nitrogen metabolism and vegetative growth, underscoring biologically meaningful links between metabolic profiles and trait variation. Conclusions This exploratory study presents the first metabolome characterisation of a pearl millet germplasm bank, coupled with predictive modelling of phenotypic traits. However, our findings are constrained by the single-environment design and the absence of population-structure assessment. To establish the stability and biological relevance of these results, future work should incorporate multi-environment trials and pathway-level analyses accounting for population structure. MenosAbstract Introduction Pearl millet is a high nutritional cereal recognised for its agro-climatic resilience, making it relevant for food security under climate change scenarios. Phenotypic traits are indicative of crop performance, stability and adaptability, yet the potential of metabolomics to predict these traits has not been explored. Objectives This study aimed to identify metabolite–trait associations in the Brazilian germplasm core collection, comprising 203 pearl millet genotypes, by combining untargeted metabolomics with machine-learning models. Methods Grains metabolic profiles were obtained using untargeted UHPLC-LTQ-Orbitrap-HRMS. Phenotypic data were sourced from standardised evaluations conducted by Embrapa across different years and field trials within the Sete Lagoas experimental station (Minas Gerais, Brazil). Generalised linear modelling with penalisation (GLM) and Random Forest was applied to explore the correlation between metabolism and 21 phenotypic traits. Results GLM successfully predicted eight qualitative and seven quantitative traits. Prediction accuracy was higher for qualitative traits, reflecting their comparatively simpler genetic architecture, whereas quantitative traits also achieved satisfactory performance (R² ≥ 0.6). Key predictors included phenolic compounds, amino acids, fatty acids, and carbohydrates. Notably, several associations corresponded to metabolites involved in nitrogen metabolism and vegetative growth, underscoring biologicall... Mostrar Tudo |
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Palavras-Chave: |
Perfilamento. |
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Thesagro: |
Germoplasma; Milheto; Pennisetum Glaucum. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02876naa a2200265 a 4500
001 2185907
005 2026-03-30
008 2026 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s11306-026-02407-7$2DOI
100 1 $aPIMENTEL, M. P. C.
245 $aExploiting predictive metabolomics of pearl millet phenotypic traits using untargeted profiling across a Brazilian germplasm panel.$h[electronic resource]
260 $c2026
520 $aAbstract Introduction Pearl millet is a high nutritional cereal recognised for its agro-climatic resilience, making it relevant for food security under climate change scenarios. Phenotypic traits are indicative of crop performance, stability and adaptability, yet the potential of metabolomics to predict these traits has not been explored. Objectives This study aimed to identify metabolite–trait associations in the Brazilian germplasm core collection, comprising 203 pearl millet genotypes, by combining untargeted metabolomics with machine-learning models. Methods Grains metabolic profiles were obtained using untargeted UHPLC-LTQ-Orbitrap-HRMS. Phenotypic data were sourced from standardised evaluations conducted by Embrapa across different years and field trials within the Sete Lagoas experimental station (Minas Gerais, Brazil). Generalised linear modelling with penalisation (GLM) and Random Forest was applied to explore the correlation between metabolism and 21 phenotypic traits. Results GLM successfully predicted eight qualitative and seven quantitative traits. Prediction accuracy was higher for qualitative traits, reflecting their comparatively simpler genetic architecture, whereas quantitative traits also achieved satisfactory performance (R² ≥ 0.6). Key predictors included phenolic compounds, amino acids, fatty acids, and carbohydrates. Notably, several associations corresponded to metabolites involved in nitrogen metabolism and vegetative growth, underscoring biologically meaningful links between metabolic profiles and trait variation. Conclusions This exploratory study presents the first metabolome characterisation of a pearl millet germplasm bank, coupled with predictive modelling of phenotypic traits. However, our findings are constrained by the single-environment design and the absence of population-structure assessment. To establish the stability and biological relevance of these results, future work should incorporate multi-environment trials and pathway-level analyses accounting for population structure.
650 $aGermoplasma
650 $aMilheto
650 $aPennisetum Glaucum
653 $aPerfilamento
700 1 $aPASSOS, A. M. A. dos
700 1 $aPRIGENT, S.
700 1 $aCASSAN, C.
700 1 $aTARDIN, F. D.
700 1 $aFERREIRA, M. S. L.
700 1 $aPÉTRIACQ, P.
700 1 $aSANTOS, M. C. B.
773 $tMetabolomics$gv. 22, article 46, 2026.
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Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
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| 3. |  | TORRES, G. A. M. Prospectar genes. Cultivar, 19-11-2008 e Diário da Manhã, Passo Fundo, p. 7, 25-11-2008 e AgroLink, 20-7-2009. 1 p.| Tipo: Artigo de Divulgação na Mídia |
| Biblioteca(s): Embrapa Trigo. |
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| 7. | | CASASSOLA, A.; TURCHETTO, C.; TORRES, G. A. M.; CONSOLI, L. Variabilidade de virulência de diferentes isolados de Pyricularia oryzae em plantas jovens de trigo. In: MOSTRA DE INICIAÇÃO CIENTÍFICA, 10., MOSTRA DE PÓS-GRADUAÇÃO DA EMBRAPA TRIGO, 7., 2015, Passo Fundo. Resumos... Brasília, DF: Embrapa, 2015. Graduação. p. 38.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Trigo. |
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| 8. | | CASASSOLA, A.; TORRES, G. A. M.; TURCHETTO, C.; CONSOLI, L. Variação de agressividade entre isolados de Magnaporthe oryzae de trigo no Brasil. In: REUNIÃO DA COMISSÃO BRASILEIRA DE PESQUISA DE TRIGO E TRITICALE, 8.; SEMINÁRIO TÉCNICO DO TRIGO, 9., 2014, Canela; REUNIÃO DA COMISSÃO BRASILEIRA DE PESQUISA DE TRIGO E TRITICALE, 9.; SEMINÁRIO TÉCNICO DO TRIGO, 10., 2015, Passo Fundo. Anais... Passo Fundo: Biotrigo Genética: Embrapa Trigo, 2015. 2015-Fitopatologia-Trabalho 137. 1 CD-ROM.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Trigo. |
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| 9. | | CASASSOLA, A.; TORRES, G. A. M.; TURCHETTO, C.; CONSOLI, L. Caracterização de isolados de Magnaporthe oryzae de trigo. In: SEMANA DO CONHECIMENTO, 2.; MOSTRA DE INICIAÇÃO CIENTÍFICA, 25., 2015, Passo Fundo. Integrando práticas e transversalizando saberes: [anaIs]. Passo Fundo: Universidade de Passo Fundo, 2015. Ciências agrárias, 4 p.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Trigo. |
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| 10. | | FERREIRA, J. R.; CONSOLI, L.; TORRES, G. A. M. Construção de mapa genético para estudos de QTL de resistência de trigo a Magnaporthe oryzae. In: MOSTRA DE INICIAÇÃO CIENTÍFICA, 15.; MOSTRA DE PÓS-GRADUAÇÃO DA EMBRAPA TRIGO, 12., 2020, Passo Fundo. Resumos... Brasília, DF: Embrapa, p. 51, 2021.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Trigo. |
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| 15. | | FERREIRA, K.; TORRES, G. A.; CARVALHO, I. V. de; DAVIDE, L. C. Abnormal meiotic behavior in three species of Crotalaria. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 44, n. 12, p. 1641-1646, dez. 2009 Título em português: Comportamento meiótico anormal em três espécies de Crotalaria.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 17. | | TORRES, G. A. M.; SIMIONI, A.; CONSOLI, L.; TONON, V. D.; GUARIENTI, E. M. Aplicações de marcadores protéicos de gluteninas no melhoramento de trigo. In: REUNIÃO DA COMISSÃO BRASILEIRA DE PESQUISA DE TRIGO E TRITICALE, 3., 2009, Veranópolis. Ata e resumos... Veranópolis: Comissão Brasileira de Pesquisa de Trigo e Triticale: Fepagro: Asav; Passo Fundo: Embrapa Trigo, 2009. Melhoramento, trabalho 82. 1 p.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Trigo. |
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| 18. | | VENANCIO, J. F.; SEIXAS, C. D. S.; TORRES, G. A. M.; CONSOLI, L. Avaliação de genótipos de trigo quanto à reação a Pyricularia oryzae em campo. In: CONGRESSO BRASILEIRO DE FITOPATOLOGIA, 48.; CONGRESSO BRASILEIRO DE PATOLOGIA PÓS COLHEITA, 2., 2015, São Pedro, SP. Fitopatologia de precisão - fronteiras da ciência: anais. [Brasilia, DF]: Sociedade Brasileira de Fitopatologia, 2015. 1 CD-ROM.| Tipo: Resumo em Anais de Congresso |
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| 19. | | VANCINI, C.; GRANDO, M. F.; TORRES, G. A. M.; MIRANDA, M. Z. de; CONSOLI, L. Associação de gluteninas de alto peso molecular com a qualidade tecnológica de trigo no Brasil. In: MOSTRA DE INICIAÇÃO CIENTÍFICA, 11.; MOSTRA DE PÓS-GRADUAÇÃO DA EMBRAPA TRIGO, 8., 2016, Passo Fundo. Resumos... Brasília, DF: Embrapa, 2016. p. 49.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Trigo. |
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| Registros recuperados : 158 | |
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