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| Registros recuperados : 105 | |
| 84. |  | LINK, H. M.; LINK, F. M.; LINK, D. Controle da formiga-preta-pastadeira, Acromyrmex crassipinus, com formicidas em po. Ciencia Florestal, Santa Maria, v.10, n.1, p.45-56, 2000.| Biblioteca(s): Embrapa Florestas. |
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| 87. | | LINK, D.; ESTEFANEL, V.; SANTOS, O. S. dos; MEZZOMO, M. C.; ABREU, L. E. V. Influência do ataque de pentatomideos nas características agronômicas do grão da soja Glycine max (L.) Mer. Anais da Sociedade Entomológica do Brasil, Itabuna, v. 2, n. 1, p. 59-65, 1973.| Biblioteca(s): Embrapa Soja. |
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| 88. | | BRONDANI, D.; DORNELLES, S. H. B.; LINK, D.; HATSCHBACH, M.; DEBORTOLI, M.; SANCHOTENE, D. Manejo de plantas daninhas, através do uso de herbicidas dessecantes aplicados em jato dirijido na cultura de eucalipto (Eucalyptus saligna). In: CONGRESSO FLORESTAL ESTADUAL DO RIO GRANDE DO SUL, 9., 2003, Nova Prata, RS. Floresta: função social: anais. Nova Prata: Prefeitura Municipal, 2003. 1 CD-ROM.| Biblioteca(s): Embrapa Florestas. |
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| 89. | | BRONDANI, D.; DORNELLES, S. H. B.; LINK, D.; HATSCHBACH, M.; DEBORTOLI, M.; SANCHOTENE, D. Manejo de plantas daninhas, através do uso de herbicidas dessecantes associados a herbicidas residuais, aplicados em jato dirijido na cultura de pínus (Pinus taeda). In: CONGRESSO FLORESTAL ESTADUAL DO RIO GRANDE DO SUL, 9., 2003, Nova Prata, RS. Floresta: função social: anais. Nova Prata: Prefeitura Municipal, 2003. 1 CD-ROM.| Biblioteca(s): Embrapa Florestas. |
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| 92. | | LINK, D.; COSTA, E. C.; ALVAREZ FILHO, A.; CARVALHO, S.; TARRAGO, M. F. S. Serrador: levantamento das espécies, épocas de ocorrência e especificação hospedeira (Coleoptera: Cerambycidae) Nota prévia. Silvicultura em São Paulo, São Paulo, v. 16-A, pt. 2, p. 1201-1203, 1982. Edição dos Anais do Congresso Nacional sobre Essências Nativas, 1982, Campos do Jordão.| Biblioteca(s): Embrapa Florestas. |
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| 93. | | LINK, D.; STORCK, L.; CERVI, J. A.; PADOIN, A. J.; GIULIANI, D. Ocorrência da mosca Euxesta SP. em milho doce na região de Santa Maria Revista do Centro de Ciencias Rurais, Santa Maria, RS, v. 14, n. 2, p. 93-99, abril/jun. 1984.| Biblioteca(s): Embrapa Hortaliças. |
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| 94. | | BELARMINO, L. C.; SILVA, M. T. B. da; CORSO, I. C.; LINK, D.; TONET, G. L.; GOMEZ, S. A.; SANTOS, B. Efecto de insecticidas en los predatores de las plagas de la soja en Brasil. In: CONFERENCIA MUNDIAL DE INVESTIGACION EN SOJA, 4., 1989, Buenos Aires. Actas... Buenos Aires: AASOJA, 1989. t.3 p.1572-1577.| Biblioteca(s): Embrapa Soja. |
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| 95. | | BELARMINO, L. C.; SILVA, M. T. B. da; CORSO, I. C.; LINK, D.; TONET, G. L.; GOMES, S. A.; SANTOS, B. Efectos de insecticidas en los predadores de las plagas de la soja en Brasil. In: CONFERENCIA MUNDIAL DE INVESTIGACION EN SOJA, 4., 1989, Buenos Aires. Buenos Aires: AASOJA, 1989. 75.| Biblioteca(s): Embrapa Soja. |
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| 96. | | PEREIRA, P. R. V. da S.; SALVADORI, J. R.; SILVA, M. B.; PAGLIARINI, L.; SCHNEIDER, S.; ROSA, A. C.; CASTRO, R. L.; LINK, D.; CAETANO, W. Resposta de cultivares de trigo ao controle do complexo pulgões/VNAC com inseticidas, via tratamento de sementes1. In: REUNIÃO DA COMISSÃO SUL-BRASILEIRA DE PESQUISA DE TRIGO E DE TRITICALE, 38.; REUNIÃO DA COMISSÃO CENTRO-SUL BRASILEIRA DE PESQUISA DE TRIGO E DE TRITICALE, 21., 2006. Passo Fundo. Atas e resumos... Passo Fundo: Embrapa Trigo: Comissão Sul-brasileira de Pesquisa de Trigo e Triticale: Comissão Centro-Sul Brasileira de Pesquisa de Trigo e Triticale, 2006. ento3. 1 CD-ROM.| Biblioteca(s): Embrapa Trigo. |
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| 97. | | SILVA, M. T. B. da; CORSO, I. C.; BELARMINO, L. C.; LINK, D.; TONET, G. L.; GOMES, S. A.; SANTOS, B. Avaliacao de inseticidas sobre predadores das pragas da soja, em dez anos agricolas, no Brasil. Trigo e Soja, Porto Alegre, n.9, p.3-16, mar/abr. 1988.| Biblioteca(s): Embrapa Soja. |
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| 98. | | ROSETTO, C. J.; SILVEIRA NETO, S.; AMANTE, E.; LINK, D.; SOUZA, D. M. de; BANZATO, N. V.; OLIVEIRA, A. M. de. Rice pests in Brazil. Pelotas: FAO, 1971. 22 p. Brazil Delegation to the Second Session of the Rice Committee for the Americas. FAO - International Rice Commission, December 6-11, 1971. Pelotas, RGS.| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 99. | | BELARMINO, L. C.; SILVA, M. T. B. da; CORSO, I. C.; LORINI, I.; LINK, D.; COSTA, E. C.; FONTES, L. F.; SILVA, R. F. P. da; BERTOLDO, N. G. Efficiency of insecticides in soybean in Brazil: III - Nezara viridula Linnaeus, 1763 (Hemiptera, Pentatomidae, Pentatominae). In: INTERNATIONAL PLANT PROTECTION CONGRESS, 12., 1991, Rio de Janeiro. Oral and poster sessions: programs and abstracts. Rio de Janeiro: [s.n.], 1991. nao paginado.| Biblioteca(s): Embrapa Soja; Embrapa Trigo. |
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| 100. | | BELARMINO, L. C.; COSTA, E. C.; LINK, D.; CORSO, I. C.; SILVA, M. T. B. da; FONTES, L. F.; LORINI, I.; SILVA, R. F. P. da; BERTOLDO, N. G. Efficiency of insecticides soybean Brazil: II - Pseudoplusia includens (Walker, 1857) and Rachiplusia nu Guenee, 1852 (Lepidoptera, Noctuidae, Plusiinae). In: INTERNATIONAL PLANT PROTECTION CONGRESS, 12., 1991, Rio de Janeiro. Oral and poster sessions: programs and abstracts. Rio de Janeiro: [s.n.], 1991. nao paginado.| Biblioteca(s): Embrapa Soja; Embrapa Trigo. |
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| Registros recuperados : 105 | |
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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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Circulação/Nível: |
A - 1 |
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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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