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Registro Completo |
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
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Data corrente: |
16/11/2021 |
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Data da última atualização: |
16/11/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
CHABI-JESUS, C.; RAMOS-GONZÁLEZ, P. L.; POSTCLAM-BARRO, M.; FONTENELE, RA. S.; HARAKAVA, R.; BASSANEZI, R. B.; MOREIRA, A. S.; KITAJIMA, E. W.; VARSANI, A.; ASTUA, J. de F. |
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Afiliação: |
CAMILA CHABI-JESUS, ESALQ; PEDRO L. RAMOS-GONZÁLEZ, Instituto Biológico/IB; MATHEUS POSTCLAM-BARRO, Instituto Biológico/IB; RAFAELA SALGADO FONTENELE, Arizona State University; RICARDO HARAKAVA, Instituto Biológico/IB; RENATO B. BASSANEZI, Fundo de Defesa da Citricultura; ALECIO SOUZA MOREIRA, CNPMF; ELLIOT W. KITAJIMA, Instituto Biológico/IB; ARVIND VARSANI, Arizona State University; JULIANA DE FREITAS ASTUA, CNPMF. |
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Título: |
Molecular epidemiology of Citrus Leprosis Virus C: a new viral lineage and phylodynamic of the main viral subpopulations in the Americas. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Frontiers in Microbiology, V. 12, 2021. |
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Idioma: |
Inglês |
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Conteúdo: |
Despite the importance of viral strains/variants as agents of emerging diseases, genetic and evolutionary processes affecting their ecology are not fully understood. To get insight into this topic, we assessed the population and spatial dynamic parameters of citrus leprosis virus C (CiLV-C, genus Cilevirus, family Kitaviridae). CiLV-C is the etiological agent of citrus leprosis disease, a non-systemic infection considered the main viral disorder affecting citrus orchards in Brazil. Overall, we obtained 18 complete or near-complete viral genomes, 123 complete nucleotide sequences of the open reading frame (ORF) encoding the putative coat protein, and 204 partial nucleotide sequences of the ORF encoding the movement protein, from 430 infected Citrus spp. samples collected between 1932 and 2020. A thorough examination of the collected dataset suggested that the CiLV-C population consists of the major lineages CRD and SJP, unevenly distributed, plus a third one called ASU identified in this work, which is represented by a single isolate found in an herbarium sample collected in Asuncion, Paraguay, in 1937. Viruses from the three lineages share about 85% nucleotide sequence identity and show signs of inter-clade recombination events. Members of the lineage CRD were identified both in commercial and non-commercial citrus orchards. However, those of the lineages SJP were exclusively detected in samples collected in the citrus belt of São Paulo and Minas Gerais, the leading Brazilian citrus production region, after 2015. The most recent common ancestor of viruses of the three lineages dates back to, at least, ?1500 years ago. Since citrus plants were introduced in the Americas by the Portuguese around the 1520s, the Bayesian phylodynamic analysis suggested that the ancestors of the main CiLV-C lineages likely originated in contact with native vegetation of South America. The intensive expansion of CRD and SJP lineages in Brazil started probably linked to the beginning of the local citrus industry. The high prevalence of CiLV-C in the citrus belt of Brazil likely ensues from the intensive connectivity between orchards, which represents a potential risk toward pathogen saturation across the region. MenosDespite the importance of viral strains/variants as agents of emerging diseases, genetic and evolutionary processes affecting their ecology are not fully understood. To get insight into this topic, we assessed the population and spatial dynamic parameters of citrus leprosis virus C (CiLV-C, genus Cilevirus, family Kitaviridae). CiLV-C is the etiological agent of citrus leprosis disease, a non-systemic infection considered the main viral disorder affecting citrus orchards in Brazil. Overall, we obtained 18 complete or near-complete viral genomes, 123 complete nucleotide sequences of the open reading frame (ORF) encoding the putative coat protein, and 204 partial nucleotide sequences of the ORF encoding the movement protein, from 430 infected Citrus spp. samples collected between 1932 and 2020. A thorough examination of the collected dataset suggested that the CiLV-C population consists of the major lineages CRD and SJP, unevenly distributed, plus a third one called ASU identified in this work, which is represented by a single isolate found in an herbarium sample collected in Asuncion, Paraguay, in 1937. Viruses from the three lineages share about 85% nucleotide sequence identity and show signs of inter-clade recombination events. Members of the lineage CRD were identified both in commercial and non-commercial citrus orchards. However, those of the lineages SJP were exclusively detected in samples collected in the citrus belt of São Paulo and Minas Gerais, the leading Brazilia... Mostrar Tudo |
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Thesaurus Nal: |
Cilevirus; Citrus leprosis virus C; Plant diseases and disorders. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/227810/1/fmicb-12-641252.pdf
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Marc: |
LEADER 03057naa a2200265 a 4500
001 2136190
005 2021-11-16
008 2021 bl uuuu u00u1 u #d
100 1 $aCHABI-JESUS, C.
245 $aMolecular epidemiology of Citrus Leprosis Virus C$ba new viral lineage and phylodynamic of the main viral subpopulations in the Americas.$h[electronic resource]
260 $c2021
520 $aDespite the importance of viral strains/variants as agents of emerging diseases, genetic and evolutionary processes affecting their ecology are not fully understood. To get insight into this topic, we assessed the population and spatial dynamic parameters of citrus leprosis virus C (CiLV-C, genus Cilevirus, family Kitaviridae). CiLV-C is the etiological agent of citrus leprosis disease, a non-systemic infection considered the main viral disorder affecting citrus orchards in Brazil. Overall, we obtained 18 complete or near-complete viral genomes, 123 complete nucleotide sequences of the open reading frame (ORF) encoding the putative coat protein, and 204 partial nucleotide sequences of the ORF encoding the movement protein, from 430 infected Citrus spp. samples collected between 1932 and 2020. A thorough examination of the collected dataset suggested that the CiLV-C population consists of the major lineages CRD and SJP, unevenly distributed, plus a third one called ASU identified in this work, which is represented by a single isolate found in an herbarium sample collected in Asuncion, Paraguay, in 1937. Viruses from the three lineages share about 85% nucleotide sequence identity and show signs of inter-clade recombination events. Members of the lineage CRD were identified both in commercial and non-commercial citrus orchards. However, those of the lineages SJP were exclusively detected in samples collected in the citrus belt of São Paulo and Minas Gerais, the leading Brazilian citrus production region, after 2015. The most recent common ancestor of viruses of the three lineages dates back to, at least, ?1500 years ago. Since citrus plants were introduced in the Americas by the Portuguese around the 1520s, the Bayesian phylodynamic analysis suggested that the ancestors of the main CiLV-C lineages likely originated in contact with native vegetation of South America. The intensive expansion of CRD and SJP lineages in Brazil started probably linked to the beginning of the local citrus industry. The high prevalence of CiLV-C in the citrus belt of Brazil likely ensues from the intensive connectivity between orchards, which represents a potential risk toward pathogen saturation across the region.
650 $aCilevirus
650 $aCitrus leprosis virus C
650 $aPlant diseases and disorders
700 1 $aRAMOS-GONZÁLEZ, P. L.
700 1 $aPOSTCLAM-BARRO, M.
700 1 $aFONTENELE, RA. S.
700 1 $aHARAKAVA, R.
700 1 $aBASSANEZI, R. B.
700 1 $aMOREIRA, A. S.
700 1 $aKITAJIMA, E. W.
700 1 $aVARSANI, A.
700 1 $aASTUA, J. de F.
773 $tFrontiers in Microbiology, V. 12, 2021.
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Registro original: |
Embrapa Mandioca e Fruticultura (CNPMF) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Acre; Embrapa Amazônia Oriental. |
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Data corrente: |
31/10/2018 |
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Data da última atualização: |
10/01/2019 |
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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: |
APARECIDO, L. E. de O.; MORAES, J. R. da S. C. de; ROLIM, G. de S.; MARTORANO, L. G.; SOARES, S. dos S.; MENESES, K. C. de; COSTA, C. T. S.; MESQUITA, D. Z.; BARBOSA, A. M. da S.; AMARAL, E. F. do; BARDALES, N. G. |
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Afiliação: |
Lucas Eduardo de Oliveira Aparecido, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; José Reinaldo da Silva Cabral de Moraes, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; Glauco de Souza Rolim, São Paulo State University; LUCIETA GUERREIRO MARTORANO, CPATU; Sabrina dos Santos Soares, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; Kamila Cunha de Meneses, São Paulo State University; Cicero Teixeira Silva Costa, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; Daniel Zimmermann Mesquita, Federal Institute of Education, Science and Technology of Mato Grosso do Sul; Aline Michelle da Silva Barbosa, São Paulo State University; EUFRAN FERREIRA DO AMARAL, CPAF-AC; Nilson Gomes Bardales, EMBRAPA. |
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Título: |
Neural networks in spatialization of meteorological elements and their application in the climatic agricultural zoning of bamboo. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
International Journal of Biometeorology, v. 62, n. 11, p. 1955-1962, Nov. 2018. |
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DOI: |
10.1007/s00484-018-1596-1 |
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Idioma: |
Inglês |
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Conteúdo: |
Bamboo has an important role in international commerce due to its diverse uses, but fewstudies have been conducted to evaluate its climatic adaptability. Thus, the objective of this study was to construct an agricultural zoning for climate risk (ZARC) for bamboo usingmeteorological elements spatialized byneural networks.Climatedata includedair temperature (TAIR, °C) and rainfall (P) from 4947 meteorological stations in Brazil from the years 1950 to 2016. Regions were considered climatically apt for bamboo cultivation when TAIR varied between 18 and 35 °C, and P was between 500 and 2800 mm year−1, or PWINTER was between 90 and 180 mm year−1. The remainder of the areas was considered marginal or inapt for bamboo cultivation. A multilayer perceptron (MLP) neural network with amultilayered Bbackpropagation^ training algorithmwas used to spatialize the territorial variability of eachclimatic element for thewhole area ofBrazil.Usingtheoverlappingof theTAIR,P, andPWINTERmaps preparedbyMLP, and the established climatic criteria of bamboo, we established the agricultural zoning for bamboo. Brazil demonstrates high seasonal climatic variabilitywith TAIR varying between 14 and 30°C, andPvarying between< 400 and 4000mmyear−1.TheZARCshowed that 87%of Brazil is climatically apt for bamboo cultivation. The states that were classified as apt in 100% of their territories were Mato Grosso do Sul, Goiás, Tocantins, Rio de Janeiro, Espírito Santo, Sergipe, Alagoas, Ceará, Piauí, Maranhão, Rondônia, and Acre. The regions that have restrictions due to lowTAIR represent just 11% of Brazilian territory. This agroclimatic zoning allowed for the classification of regions based on aptitude of climate for bamboo cultivation and showed that 71% of the total national territory is considered to be apt for bamboo cultivation. The regions that have restrictions are part of southern Brazil due to low values of TAIR and portions of the northern region that have high levels of P which is favorable for the development of diseases. MenosBamboo has an important role in international commerce due to its diverse uses, but fewstudies have been conducted to evaluate its climatic adaptability. Thus, the objective of this study was to construct an agricultural zoning for climate risk (ZARC) for bamboo usingmeteorological elements spatialized byneural networks.Climatedata includedair temperature (TAIR, °C) and rainfall (P) from 4947 meteorological stations in Brazil from the years 1950 to 2016. Regions were considered climatically apt for bamboo cultivation when TAIR varied between 18 and 35 °C, and P was between 500 and 2800 mm year−1, or PWINTER was between 90 and 180 mm year−1. The remainder of the areas was considered marginal or inapt for bamboo cultivation. A multilayer perceptron (MLP) neural network with amultilayered Bbackpropagation^ training algorithmwas used to spatialize the territorial variability of eachclimatic element for thewhole area ofBrazil.Usingtheoverlappingof theTAIR,P, andPWINTERmaps preparedbyMLP, and the established climatic criteria of bamboo, we established the agricultural zoning for bamboo. Brazil demonstrates high seasonal climatic variabilitywith TAIR varying between 14 and 30°C, andPvarying between< 400 and 4000mmyear−1.TheZARCshowed that 87%of Brazil is climatically apt for bamboo cultivation. The states that were classified as apt in 100% of their territories were Mato Grosso do Sul, Goiás, Tocantins, Rio de Janeiro, Espírito Santo, Sergipe, Alagoas, Ceará, Piau... Mostrar Tudo |
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Palavras-Chave: |
Aclimatación; Climate risk; Crop zoning; Modeling; Multilayer perceptron; Redes neuronales; Training algorithm; Zonificación agrícola. |
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Thesagro: |
Aclimatação; Bambu; Bambusa Vulgaris; Climatologia; Modelo Matemático; Risco Climático; Zoneamento Agrícola. |
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Thesaurus NAL: |
Acclimation; Agricultural zoning; Bamboos; Climatology; Mathematical models; Neural networks. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 03571naa a2200505 a 4500
001 2098629
005 2019-01-10
008 2018 bl uuuu u00u1 u #d
024 7 $a10.1007/s00484-018-1596-1$2DOI
100 1 $aAPARECIDO, L. E. de O.
245 $aNeural networks in spatialization of meteorological elements and their application in the climatic agricultural zoning of bamboo.$h[electronic resource]
260 $c2018
520 $aBamboo has an important role in international commerce due to its diverse uses, but fewstudies have been conducted to evaluate its climatic adaptability. Thus, the objective of this study was to construct an agricultural zoning for climate risk (ZARC) for bamboo usingmeteorological elements spatialized byneural networks.Climatedata includedair temperature (TAIR, °C) and rainfall (P) from 4947 meteorological stations in Brazil from the years 1950 to 2016. Regions were considered climatically apt for bamboo cultivation when TAIR varied between 18 and 35 °C, and P was between 500 and 2800 mm year−1, or PWINTER was between 90 and 180 mm year−1. The remainder of the areas was considered marginal or inapt for bamboo cultivation. A multilayer perceptron (MLP) neural network with amultilayered Bbackpropagation^ training algorithmwas used to spatialize the territorial variability of eachclimatic element for thewhole area ofBrazil.Usingtheoverlappingof theTAIR,P, andPWINTERmaps preparedbyMLP, and the established climatic criteria of bamboo, we established the agricultural zoning for bamboo. Brazil demonstrates high seasonal climatic variabilitywith TAIR varying between 14 and 30°C, andPvarying between< 400 and 4000mmyear−1.TheZARCshowed that 87%of Brazil is climatically apt for bamboo cultivation. The states that were classified as apt in 100% of their territories were Mato Grosso do Sul, Goiás, Tocantins, Rio de Janeiro, Espírito Santo, Sergipe, Alagoas, Ceará, Piauí, Maranhão, Rondônia, and Acre. The regions that have restrictions due to lowTAIR represent just 11% of Brazilian territory. This agroclimatic zoning allowed for the classification of regions based on aptitude of climate for bamboo cultivation and showed that 71% of the total national territory is considered to be apt for bamboo cultivation. The regions that have restrictions are part of southern Brazil due to low values of TAIR and portions of the northern region that have high levels of P which is favorable for the development of diseases.
650 $aAcclimation
650 $aAgricultural zoning
650 $aBamboos
650 $aClimatology
650 $aMathematical models
650 $aNeural networks
650 $aAclimatação
650 $aBambu
650 $aBambusa Vulgaris
650 $aClimatologia
650 $aModelo Matemático
650 $aRisco Climático
650 $aZoneamento Agrícola
653 $aAclimatación
653 $aClimate risk
653 $aCrop zoning
653 $aModeling
653 $aMultilayer perceptron
653 $aRedes neuronales
653 $aTraining algorithm
653 $aZonificación agrícola
700 1 $aMORAES, J. R. da S. C. de
700 1 $aROLIM, G. de S.
700 1 $aMARTORANO, L. G.
700 1 $aSOARES, S. dos S.
700 1 $aMENESES, K. C. de
700 1 $aCOSTA, C. T. S.
700 1 $aMESQUITA, D. Z.
700 1 $aBARBOSA, A. M. da S.
700 1 $aAMARAL, E. F. do
700 1 $aBARDALES, N. G.
773 $tInternational Journal of Biometeorology$gv. 62, n. 11, p. 1955-1962, Nov. 2018.
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