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Registro Completo |
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Biblioteca(s): |
Embrapa Acre. |
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Data corrente: |
04/02/2022 |
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Data da última atualização: |
07/02/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
BISWAS, A.; ANDRADE, M. H. M. L.; ACHARYA, J. P.; SOUZA, C. L. de; LOPEZ, Y.; ASSIS, G. M. L. de; SHIRBHATE, S.; SINGH, A.; MUNOZ, P.; RIOS, E. F. |
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Afiliação: |
ANJU BISWAS, Department of Agronomy, University of Florida, Gainesville, FL, United States; MARIO HENRIQUE MURAD LEITE ANDRADE, Department of Agronomy, University of Florida, Gainesville, FL, United States; JANAM P. ACHARYA, Department of Agronomy, University of Florida, Gainesville, FL, United States; CLEBER LOPES DE SOUZA, Department of Agronomy, University of Florida, Gainesville, FL, United States; YOLANDA LOPEZ, Department of Agronomy, University of Florida, Gainesville, FL, United States; GISELLE MARIANO LESSA DE ASSIS, CPAF-AC; SHUBHAM SHIRBHATE, Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, United States; ADITYA SINGH, Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, United States; PATRICIO MUNOZ, Department of Horticultural Sciences, University of Florida, Gainesville, FL, United States; ESTEBAN F. RIOS, Department of Agronomy, University of Florida, Gainesville, FL, United States. |
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Título: |
Phenomics-assisted selection for herbage accumulation in alfalfa (Medicago sativa L.). |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Frontiers in Plant Science, v. 12, 756768, Dec. 2021. |
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DOI: |
https://doi.org/10.3389/fpls.2021.756768 |
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Idioma: |
Inglês |
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Conteúdo: |
The application of remote sensing in plant breeding is becoming a routine method for fast and non-destructive high-throughput phenotyping (HTP) using unmanned aerial vehicles (UAVs) equipped with sensors. Alfalfa (Medicago sativa L.) is a perennial forage legume grown in more than 30 million hectares worldwide. Breeding alfalfa for herbage accumulation (HA) requires frequent and multiple phenotyping efforts, which is laborious and costly. The objective of this study was to assess the efficiency of UAV-based imagery and spatial analysis in the selection of alfalfa for HA. The alfalfa breeding population was composed of 145 full-sib and 34 half-sib families, and the experimental design was a row-column with augmented representation of controls. The experiment was established in November 2017, and HA was harvested four times between August 2018 and January 2019. A UAV equipped with a multispectral camera was used for HTP before each harvest. Four vegetation indices (VIs) were calculated from the UAVbased images: NDVI, NDRE, GNDVI, and GRVI. All VIs showed a high correlation with HA, and VIs predicted HA with moderate accuracy. HA and NDVI were used for further analyses to calculate the genetic parameters using linear mixed models. The spatial analysis had a significant effect in both dimensions (rows and columns) for HA and NDVI, resulting in improvements in the estimation of genetic parameters. Univariate models for NDVI and HA, and bivariate models, were fit to predict family performance for scenarios with various levels of HA data (simulated in silico by assigning missing values to full dataset). The bivariate models provided higher correlation among predicted values, higher coincidence for selection, and higher genetic gain even for scenarios with only 30% of HA data. Hence, HTP is a reliable and efficient method to aid alfalfa phenotyping to improve HA. Additionally, the use of spatial analysis can also improve the accuracy of selection in breeding trials. MenosThe application of remote sensing in plant breeding is becoming a routine method for fast and non-destructive high-throughput phenotyping (HTP) using unmanned aerial vehicles (UAVs) equipped with sensors. Alfalfa (Medicago sativa L.) is a perennial forage legume grown in more than 30 million hectares worldwide. Breeding alfalfa for herbage accumulation (HA) requires frequent and multiple phenotyping efforts, which is laborious and costly. The objective of this study was to assess the efficiency of UAV-based imagery and spatial analysis in the selection of alfalfa for HA. The alfalfa breeding population was composed of 145 full-sib and 34 half-sib families, and the experimental design was a row-column with augmented representation of controls. The experiment was established in November 2017, and HA was harvested four times between August 2018 and January 2019. A UAV equipped with a multispectral camera was used for HTP before each harvest. Four vegetation indices (VIs) were calculated from the UAVbased images: NDVI, NDRE, GNDVI, and GRVI. All VIs showed a high correlation with HA, and VIs predicted HA with moderate accuracy. HA and NDVI were used for further analyses to calculate the genetic parameters using linear mixed models. The spatial analysis had a significant effect in both dimensions (rows and columns) for HA and NDVI, resulting in improvements in the estimation of genetic parameters. Univariate models for NDVI and HA, and bivariate models, were fit to predict family... Mostrar Tudo |
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Palavras-Chave: |
Fitomejoramiento; Genetic gain; High-throughput phenotyping (HTP); Leguminosas forrajeras; Normalized difference vegetation index (NDVI); Teledetección; Variación espacial. |
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Thesagro: |
Alfafa; Leguminosa Forrageira; Medicago Sativa; Melhoramento Genético Vegetal; Sensoriamento Remoto. |
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Thesaurus Nal: |
Forage legumes; Phenotype; Plant breeding; Remote sensing; Spatial variation. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/230884/1/27295.pdf
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Marc: |
LEADER 03318naa a2200445 a 4500
001 2139673
005 2022-02-07
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3389/fpls.2021.756768$2DOI
100 1 $aBISWAS, A.
245 $aPhenomics-assisted selection for herbage accumulation in alfalfa (Medicago sativa L.).$h[electronic resource]
260 $c2021
520 $aThe application of remote sensing in plant breeding is becoming a routine method for fast and non-destructive high-throughput phenotyping (HTP) using unmanned aerial vehicles (UAVs) equipped with sensors. Alfalfa (Medicago sativa L.) is a perennial forage legume grown in more than 30 million hectares worldwide. Breeding alfalfa for herbage accumulation (HA) requires frequent and multiple phenotyping efforts, which is laborious and costly. The objective of this study was to assess the efficiency of UAV-based imagery and spatial analysis in the selection of alfalfa for HA. The alfalfa breeding population was composed of 145 full-sib and 34 half-sib families, and the experimental design was a row-column with augmented representation of controls. The experiment was established in November 2017, and HA was harvested four times between August 2018 and January 2019. A UAV equipped with a multispectral camera was used for HTP before each harvest. Four vegetation indices (VIs) were calculated from the UAVbased images: NDVI, NDRE, GNDVI, and GRVI. All VIs showed a high correlation with HA, and VIs predicted HA with moderate accuracy. HA and NDVI were used for further analyses to calculate the genetic parameters using linear mixed models. The spatial analysis had a significant effect in both dimensions (rows and columns) for HA and NDVI, resulting in improvements in the estimation of genetic parameters. Univariate models for NDVI and HA, and bivariate models, were fit to predict family performance for scenarios with various levels of HA data (simulated in silico by assigning missing values to full dataset). The bivariate models provided higher correlation among predicted values, higher coincidence for selection, and higher genetic gain even for scenarios with only 30% of HA data. Hence, HTP is a reliable and efficient method to aid alfalfa phenotyping to improve HA. Additionally, the use of spatial analysis can also improve the accuracy of selection in breeding trials.
650 $aForage legumes
650 $aPhenotype
650 $aPlant breeding
650 $aRemote sensing
650 $aSpatial variation
650 $aAlfafa
650 $aLeguminosa Forrageira
650 $aMedicago Sativa
650 $aMelhoramento Genético Vegetal
650 $aSensoriamento Remoto
653 $aFitomejoramiento
653 $aGenetic gain
653 $aHigh-throughput phenotyping (HTP)
653 $aLeguminosas forrajeras
653 $aNormalized difference vegetation index (NDVI)
653 $aTeledetección
653 $aVariación espacial
700 1 $aANDRADE, M. H. M. L.
700 1 $aACHARYA, J. P.
700 1 $aSOUZA, C. L. de
700 1 $aLOPEZ, Y.
700 1 $aASSIS, G. M. L. de
700 1 $aSHIRBHATE, S.
700 1 $aSINGH, A.
700 1 $aMUNOZ, P.
700 1 $aRIOS, E. F.
773 $tFrontiers in Plant Science$gv. 12, 756768, Dec. 2021.
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Registro original: |
Embrapa Acre (CPAF-AC) |
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| Registros recuperados : 83 | |
| 8. |  | IKUMA, E. S.; AOKI, R. T.; SOUZA, E. B. de; KOMEGAWA, E. O.; SONEGO, O. R. Avaliação do controle químico das doenças foliares na cultura do trigo. In: REUNIÃO DA COMISSÃO CENTRO-SUL-BRASILEIRA DE PESQUISA DE TRIGO, 3., 1987, Cascavel. Resultados de pesquisa com trigo - 1986. Dourados: EMBRAPA-UEPAE Dourados, 1987. p. 116-118. (EMBRAPA-UEPAE Dourados. Documentos, 28). Projeto 004.82.034-6 - Avaliação de fungicidas no controle das ferrugens do trigo.| Biblioteca(s): Embrapa Agropecuária Oeste. |
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| 11. | | SOUSA, P. G.; SOARES SOBRINHO, J.; LUIZ, A. J. B.; RUMIATTO, M.; SOUZA, E. B. de. Cultivares de trigo em nível estadual de experimentação. In: REUNIÃO DA COMISSÃO CENTRO-SUL-BRASILEIRA DE PESQUISA DE TRIGO, 5., 1989, Cornélio Procópio. Resultados de pesquisa com trigo - 1988. Dourados: EMBRAPA-UEPAE Dourados, 1989. p. 31-34. (EMBRAPA-UEPAE Dourados. Documentos, 39). Projeto 004.87.0116-8 - Competição de cultivares de trigo na Região Sul de Mato Grosso do Sul.| Biblioteca(s): Embrapa Agropecuária Oeste. |
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| 12. | | NICKEL, O.; SOUZA, E. B. de; FAJARDO, T. V. M.; BARROS, D. R. de. Comparison of the nucleotide sequences of two isolates of apple stem grooving virus from apple plants. Virus Reviews and Research, Belo Horizonte, v. 20, p. 201, 2015. Suplemento. Abstract PIV 48. Edição dos Resumos do XXVI Brazilian Congress of Virology, X Mercour Meeting of Virology, 2015, Florianópolis.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Uva e Vinho. |
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| 13. | | SOUSA, P. G.; SOARES SOBRINHO, J.; LUIZ, A. J. B.; RUMIATTO, M.; SOUZA, E. B. de. Linhagens e cultivares de trigo em nível final de experimentação. In: REUNIÃO DA COMISSÃO CENTRO-SUL-BRASILEIRA DE PESQUISA DE TRIGO, 5., 1989, Cornélio Procópio. Resultados de pesquisa com trigo - 1988. Dourados: EMBRAPA-UEPAE Dourados, 1989. p. 35-43. (EMBRAPA-UEPAE Dourados. Documentos, 39). Projeto 004.87.016-8 - Competição de cultivares de trigo na Região Sul de Mato Grosso do Sul.| Biblioteca(s): Embrapa Agropecuária Oeste. |
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| 14. | | SOUSA, P. G.; SOARES SOBRINHO, J.; LUIZ, A. J. B.; RUMIATTO, M.; SOUZA, E. B. de. Linhagens de trigo em nível intermediário de experimentação. In: REUNIÃO DA COMISSÃO CENTRO-SUL-BRASILEIRA DE PESQUISA DE TRIGO, 5., 1989, Cornélio Procópio. Resultados de pesquisa com trigo - 1988. Dourados: EMBRAPA-UEPAE Dourados, 1989. p. 44-54. (EMBRAPA-UEPAE Dourados. Documentos, 39). Projeto 004.87.016-8 - Competição de cultivares de trigo na Região Sul de Mato Grosso do Sul.| Biblioteca(s): Embrapa Agropecuária Oeste. |
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| 18. | | ALBUQUERQUE, G. M. R.; FONSECA, M. E. N.; BOITEUX, L. S.; LOPES, C. A.; SOUZA, E. B. Análise do perfil de DEGS obtidos via RNASeq associados à suplantação da resistência de 'Hawaii 7996' por isolado brasileiro de Ralstonia pseudosolanacearum. In: CONGRESSO BRASILEIRO DE FITOPATOLOGIA, 51., 2019, Recife. Anais... Brasília, DF: Sociedade Brasileira de Fitopatologia, 2019. p. 742. Resumo.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Hortaliças. |
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| 19. | | OLIVEIRA, J. C.; ALBUQUERQUE, G. M. R.; XAVIER, A. S.; MARIANO, R. L. R.; SUASSUNA, N. D.; SOUZA, E. B. Characterization of xanthomonas citri subsp. malvacearum causing cotton angular leaf spot in Brazil. Journal of Plant Pathology, v. 93, n. 3, p. 707-712, 2011.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Algodão. |
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| Registros recuperados : 83 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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