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Registro Completo |
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Biblioteca(s): |
Embrapa Soja. |
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Data corrente: |
16/01/2009 |
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Data da última atualização: |
17/08/2009 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
YORINORI, J. T.; NUNES JUNIOR, J.; LAZZAROTTO, J. J. |
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Afiliação: |
José Tadashi Yorinori; José Nunes Junior, CTPA; Joelsio José Lazzarotto, CNPSo. |
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Título: |
Ferrugem-asiática-da-soja no Brasil: evolução econômica e controle. |
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Ano de publicação: |
2008 |
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Fonte/Imprenta: |
In: POLTRONIERI, L. S.; TRINDADE, D. R.; SANTOS, I. P. dos (Ed.). Pragas e doenças de cultivos amazônicos. 2. ed. rev. Belém, PA: Embrapa Amazônia Oriental; Brasília, DF: Embrapa Informação Tecnológica, 2008. |
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Páginas: |
p. 203-224. |
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Idioma: |
Português |
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Conteúdo: |
Ferrugem americana; Ferrugem-asiática; Evolução da ferrugem-asiática, safra 2000-2001, safra 2001-2002, safra 2002-2003; Plantas hospedeiras da ferrugem-asiática; Sintoma; Modo de disseminação; Efeitos da ferrugem; Condições predisponentes; Variabilidade patogênica; Estratégias de controle; Manejo da cultura; Resistência varietal; Controle químico; Pesquisas e assistência técnica desenvolvidas e em andamento; Perspectiva futura. |
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Categoria do assunto: |
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Marc: |
LEADER 01055naa a2200157 a 4500
001 1459863
005 2009-08-17
008 2008 bl uuuu u00u1 u #d
100 1 $aYORINORI, J. T.
245 $aFerrugem-asiática-da-soja no Brasil$bevolução econômica e controle.
260 $c2008
300 $ap. 203-224.
520 $aFerrugem americana; Ferrugem-asiática; Evolução da ferrugem-asiática, safra 2000-2001, safra 2001-2002, safra 2002-2003; Plantas hospedeiras da ferrugem-asiática; Sintoma; Modo de disseminação; Efeitos da ferrugem; Condições predisponentes; Variabilidade patogênica; Estratégias de controle; Manejo da cultura; Resistência varietal; Controle químico; Pesquisas e assistência técnica desenvolvidas e em andamento; Perspectiva futura.
700 1 $aNUNES JUNIOR, J.
700 1 $aLAZZAROTTO, J. J.
773 $tIn: POLTRONIERI, L. S.; TRINDADE, D. R.; SANTOS, I. P. dos (Ed.). Pragas e doenças de cultivos amazônicos. 2. ed. rev. Belém, PA: Embrapa Amazônia Oriental; Brasília, DF: Embrapa Informação Tecnológica, 2008.
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Registro original: |
Embrapa Soja (CNPSO) |
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Registro Completo
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
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Data corrente: |
05/10/2023 |
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Data da última atualização: |
09/10/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
CHANDNANI, R.; QIN, T.; YE, H.; HU, H.; PANJVANI, K.; TOKIZAWA, M.; MACIAS, J. M.; MEDINA, A. A.; BERNARDINO, K. C.; PRADIER, P.-L.; BANIK, P.; MOONEY, A.; MAGALHAES, J. V. de; NGUYEN, H. T.; KOCHIAN, L. V. |
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Afiliação: |
RAHUL CHANDNANI, UNIVERSITY OF SASKATCHEWAN; TONGFEI QIN, UNIVERSITY OF SASKATCHEWAN; HENG YE, UNIVERSITY OF MISSOURI; HAIFEI HU, UNIVERSITY OF WESTERN AUSTRALIA; KARIM PANJVANI, UNIVERSITY OF SASKATCHEWAN; MUTSUTOMO TOKIZAWA, UNIVERSITY OF SASKATCHEWAN; JAVIER MORA MACIAS, UNIVERSITY OF SASKATCHEWAN; ALMA ARMENTA MEDINA, UNIVERSITY OF SASKATCHEWAN; KARINE C. BERNARDINO; PIERRE-LUC PRADIER UNIVERSITY OF SASKATCHEWAN, UNIVERSITY OF SASKATCHEWAN; PANKAJ BANIK, UNIVERSITY OF SASKATCHEWAN; ASHLYN MOONEY, UNIVERSITY OF SASKATCHEWAN; JURANDIR VIEIRA DE MAGALHAES, CNPMS; HENRY T. NGUYEN, UNIVERSITY OF MISSOURI; LEON V. KOCHIAN, UNIVERSITY OF SASKATCHEWAN. |
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Título: |
Application of an improved 2-dimensional high-throughput soybean root phenotyping platform to identify novel genetic variants regulating root architecture traits. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Plant Phenomics, v. 5, article 97, 2023. |
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DOI: |
https://doi.org/10.34133/plantphenomics.0097 |
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Idioma: |
Inglês |
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Conteúdo: |
Nutrient-efficient root system architecture (RSA) is becoming an important breeding objective for generating crop varieties with improved nutrient and water acquisition efficiency. Genetic variants shaping soybean RSA is key in improving nutrient and water acquisition. Here, we report on the use of an improved 2-dimensional high-throughput root phenotyping platform that minimizes background noise by imaging pouch-grown root systems submerged in water. We also developed a background image cleaning Python pipeline that computationally removes images of small pieces of debris and filter paper fibers, which can be erroneously quantified as root tips. This platform was used to phenotype root traits in 286 soybean lines genotyped with 5.4 million single-nucleotide polymorphisms. There was a substantially higher correlation in manually counted number of root tips with computationally quantified root tips (95% correlation), when the background was cleaned of nonroot materials compared to root images without the background corrected (79%). Improvements in our RSA phenotyping pipeline significantly reduced overestimation of the root traits influenced by the number of root tips. Genome-wide association studies conducted on the root phenotypic data and quantitative gene expression analysis of candidate genes resulted in the identification of 3 putative positive regulators of root system depth, total root length and surface area, and root system volume and surface area of thicker roots (DOF1-like zinc finger transcription factor, protein of unknown function, and C2H2 zinc finger protein). We also identified a putative negative regulator (gibberellin 20 oxidase 3) of the total number of lateral roots. MenosNutrient-efficient root system architecture (RSA) is becoming an important breeding objective for generating crop varieties with improved nutrient and water acquisition efficiency. Genetic variants shaping soybean RSA is key in improving nutrient and water acquisition. Here, we report on the use of an improved 2-dimensional high-throughput root phenotyping platform that minimizes background noise by imaging pouch-grown root systems submerged in water. We also developed a background image cleaning Python pipeline that computationally removes images of small pieces of debris and filter paper fibers, which can be erroneously quantified as root tips. This platform was used to phenotype root traits in 286 soybean lines genotyped with 5.4 million single-nucleotide polymorphisms. There was a substantially higher correlation in manually counted number of root tips with computationally quantified root tips (95% correlation), when the background was cleaned of nonroot materials compared to root images without the background corrected (79%). Improvements in our RSA phenotyping pipeline significantly reduced overestimation of the root traits influenced by the number of root tips. Genome-wide association studies conducted on the root phenotypic data and quantitative gene expression analysis of candidate genes resulted in the identification of 3 putative positive regulators of root system depth, total root length and surface area, and root system volume and surface area of thicker roots (... Mostrar Tudo |
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Thesagro: |
Genética Vegetal; Raiz; Seleção Fenótipa; Soja. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1157100/1/Application-of-an-improved-2-dimensional-high-throughput-soybean-root.pdf
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Marc: |
LEADER 02746naa a2200349 a 4500
001 2157100
005 2023-10-09
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.34133/plantphenomics.0097$2DOI
100 1 $aCHANDNANI, R.
245 $aApplication of an improved 2-dimensional high-throughput soybean root phenotyping platform to identify novel genetic variants regulating root architecture traits.$h[electronic resource]
260 $c2023
520 $aNutrient-efficient root system architecture (RSA) is becoming an important breeding objective for generating crop varieties with improved nutrient and water acquisition efficiency. Genetic variants shaping soybean RSA is key in improving nutrient and water acquisition. Here, we report on the use of an improved 2-dimensional high-throughput root phenotyping platform that minimizes background noise by imaging pouch-grown root systems submerged in water. We also developed a background image cleaning Python pipeline that computationally removes images of small pieces of debris and filter paper fibers, which can be erroneously quantified as root tips. This platform was used to phenotype root traits in 286 soybean lines genotyped with 5.4 million single-nucleotide polymorphisms. There was a substantially higher correlation in manually counted number of root tips with computationally quantified root tips (95% correlation), when the background was cleaned of nonroot materials compared to root images without the background corrected (79%). Improvements in our RSA phenotyping pipeline significantly reduced overestimation of the root traits influenced by the number of root tips. Genome-wide association studies conducted on the root phenotypic data and quantitative gene expression analysis of candidate genes resulted in the identification of 3 putative positive regulators of root system depth, total root length and surface area, and root system volume and surface area of thicker roots (DOF1-like zinc finger transcription factor, protein of unknown function, and C2H2 zinc finger protein). We also identified a putative negative regulator (gibberellin 20 oxidase 3) of the total number of lateral roots.
650 $aGenética Vegetal
650 $aRaiz
650 $aSeleção Fenótipa
650 $aSoja
700 1 $aQIN, T.
700 1 $aYE, H.
700 1 $aHU, H.
700 1 $aPANJVANI, K.
700 1 $aTOKIZAWA, M.
700 1 $aMACIAS, J. M.
700 1 $aMEDINA, A. A.
700 1 $aBERNARDINO, K. C.
700 1 $aPRADIER, P.-L.
700 1 $aBANIK, P.
700 1 $aMOONEY, A.
700 1 $aMAGALHAES, J. V. de
700 1 $aNGUYEN, H. T.
700 1 $aKOCHIAN, L. V.
773 $tPlant Phenomics$gv. 5, article 97, 2023.
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Embrapa Milho e Sorgo (CNPMS) |
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