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Registro Completo |
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Biblioteca(s): |
Embrapa Recursos Genéticos e Biotecnologia; Embrapa Semiárido. |
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Data corrente: |
18/09/2020 |
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Data da última atualização: |
17/11/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MELO, B. P. de; LOURENCO-TESSUTTI, I. T.; MORGANTE, C. V.; SANTOS, N. C.; PINHEIRO, L. B.; LINS, C. B. de J.; SILVA, M. C. M.; MACEDO, L. L. P.; FONTES, E. P. B.; GROSSI-DE-SA, M. F. |
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Afiliação: |
BRUNO PAES DE MELO, UFV; ISABELA TRISTAN LOURENCO TESSUTTI, Cenargen; CAROLINA VIANNA MORGANTE, CPATSA; NAIARA CORDEIRO SANTOS; LUANNA BEZERRA PINHEIRO, UCB; CAMILA BARROZO DE JESUS LINS; MARIA CRISTINA MATTAR DA SILVA, Cenargen; LEONARDO LIMA PEPINO DE MACEDO, Cenargen; ELIZABETH PACHECO BATISTA FONTES, UFV; MARIA FATIMA GROSSI DE SA, Cenargen. |
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Título: |
Soybean embryonic axis transformation: combining biolistic and Agrobacterium-Mediated Protocols to overcome typical complications of in vitro plant regeneration. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Frontiers in Plant Science, v. 11, article 1228, 2020. |
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DOI: |
https://doi.org/10.3389/fpls.2020.01228 |
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Idioma: |
Inglês |
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Conteúdo: |
The first successful attempt to generate genetically modified plants expressing a transgene was preformed via T-DNA-based gene transfer employing Agrobacterium tumefaciens-mediated genetic transformation. Limitations over infectivity and in vitro tissue culture led to the development of other DNA delivery systems, such as the biolistic method. Herein, we developed a new one-step protocol for transgenic soybean recovery by combining the two different transformation methods. This protocol comprises the following steps: agrobacterial preparation, seed sterilization, soybean embryo excision, shoot-cell injury by tungsten-microparticle bombardment, A. tumefaciens-mediated transformation, embryo co-cultivation in vitro, and selection of transgenic plants. This protocol can be completed in approximately 30?40 weeks. The average efficiency of producing transgenic soybean germlines using this protocol was 9.84%, similar to other previously described protocols. However, we introduced a more cost-effective, more straightforward and shorter methodology for transgenic plant recovery, which allows co-cultivation and plant regeneration in a single step, decreasing the chances of contamination and making the manipulation easier. Finally, as a hallmark, our protocol does not generate plant chimeras, in contrast to traditional plant regeneration protocols applied in other Agrobacterium-mediated transformation methods. Therefore, this new approach of plant transformation is applicable for studies of gene function and the production of transgenic cultivars carrying different traits for precision-breeding programs. MenosThe first successful attempt to generate genetically modified plants expressing a transgene was preformed via T-DNA-based gene transfer employing Agrobacterium tumefaciens-mediated genetic transformation. Limitations over infectivity and in vitro tissue culture led to the development of other DNA delivery systems, such as the biolistic method. Herein, we developed a new one-step protocol for transgenic soybean recovery by combining the two different transformation methods. This protocol comprises the following steps: agrobacterial preparation, seed sterilization, soybean embryo excision, shoot-cell injury by tungsten-microparticle bombardment, A. tumefaciens-mediated transformation, embryo co-cultivation in vitro, and selection of transgenic plants. This protocol can be completed in approximately 30?40 weeks. The average efficiency of producing transgenic soybean germlines using this protocol was 9.84%, similar to other previously described protocols. However, we introduced a more cost-effective, more straightforward and shorter methodology for transgenic plant recovery, which allows co-cultivation and plant regeneration in a single step, decreasing the chances of contamination and making the manipulation easier. Finally, as a hallmark, our protocol does not generate plant chimeras, in contrast to traditional plant regeneration protocols applied in other Agrobacterium-mediated transformation methods. Therefore, this new approach of plant transformation is applicable for stud... Mostrar Tudo |
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Palavras-Chave: |
Agrobacterium-mediated transformation; Embryonic axis; High-efficiency plant transformation; Particle bombardment; Planta geneticamente modificada; Recuperação trangênica de soja. |
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Thesagro: |
Cultura de Tecido; Glycine Max; Soja. |
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Thesaurus Nal: |
Agrobacterium; Embryonic structures; Genetic transformation; Plant genetics. |
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Categoria do assunto: |
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G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/216085/1/fpls-11-01228.pdf
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Marc: |
LEADER 02941naa a2200397 a 4500
001 2125013
005 2020-11-17
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3389/fpls.2020.01228$2DOI
100 1 $aMELO, B. P. de
245 $aSoybean embryonic axis transformation$bcombining biolistic and Agrobacterium-Mediated Protocols to overcome typical complications of in vitro plant regeneration.$h[electronic resource]
260 $c2020
520 $aThe first successful attempt to generate genetically modified plants expressing a transgene was preformed via T-DNA-based gene transfer employing Agrobacterium tumefaciens-mediated genetic transformation. Limitations over infectivity and in vitro tissue culture led to the development of other DNA delivery systems, such as the biolistic method. Herein, we developed a new one-step protocol for transgenic soybean recovery by combining the two different transformation methods. This protocol comprises the following steps: agrobacterial preparation, seed sterilization, soybean embryo excision, shoot-cell injury by tungsten-microparticle bombardment, A. tumefaciens-mediated transformation, embryo co-cultivation in vitro, and selection of transgenic plants. This protocol can be completed in approximately 30?40 weeks. The average efficiency of producing transgenic soybean germlines using this protocol was 9.84%, similar to other previously described protocols. However, we introduced a more cost-effective, more straightforward and shorter methodology for transgenic plant recovery, which allows co-cultivation and plant regeneration in a single step, decreasing the chances of contamination and making the manipulation easier. Finally, as a hallmark, our protocol does not generate plant chimeras, in contrast to traditional plant regeneration protocols applied in other Agrobacterium-mediated transformation methods. Therefore, this new approach of plant transformation is applicable for studies of gene function and the production of transgenic cultivars carrying different traits for precision-breeding programs.
650 $aAgrobacterium
650 $aEmbryonic structures
650 $aGenetic transformation
650 $aPlant genetics
650 $aCultura de Tecido
650 $aGlycine Max
650 $aSoja
653 $aAgrobacterium-mediated transformation
653 $aEmbryonic axis
653 $aHigh-efficiency plant transformation
653 $aParticle bombardment
653 $aPlanta geneticamente modificada
653 $aRecuperação trangênica de soja
700 1 $aLOURENCO-TESSUTTI, I. T.
700 1 $aMORGANTE, C. V.
700 1 $aSANTOS, N. C.
700 1 $aPINHEIRO, L. B.
700 1 $aLINS, C. B. de J.
700 1 $aSILVA, M. C. M.
700 1 $aMACEDO, L. L. P.
700 1 $aFONTES, E. P. B.
700 1 $aGROSSI-DE-SA, M. F.
773 $tFrontiers in Plant Science$gv. 11, article 1228, 2020.
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Registro original: |
Embrapa Recursos Genéticos e Biotecnologia (CENARGEN) |
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
26/07/2023 |
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Data da última atualização: |
26/07/2023 |
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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: |
BASTOS, B. P.; PINHEIRO, H. S. K.; FERREIRA, F. J. F.; CARVALHO JUNIOR, W. de; ANJOS, L. H. C. dos. |
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Afiliação: |
BLENDA PEREIRA BASTOS, UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO; HELENA SARAIVA KOENOW PINHEIRO, UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO; FRANCISCO JOSÉ FONSECA FERREIRA, UNIVERSIDADE FEDERAL DO PARANÁ; WALDIR DE CARVALHO JUNIOR, CNPS; LÚCIA HELENA CUNHA DOS ANJOS, UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO. |
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Título: |
Could airborne geophysical data be used to improve predictive modeling of agronomic soil properties in tropical hillslope area? |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Remote Sensing, v. 15, n. 15, 3719, 2023. |
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DOI: |
https://doi.org/10.3390/rs15153719 |
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Idioma: |
Inglês |
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Conteúdo: |
Airborne geophysical data (AGD) have great potential to represent soil-forming factors. Because of that, the objective of this study was to evaluate the importance of AGD in predicting soil attributes such as aluminum saturation (ASat), base saturation (BS), cation exchange capacity (CEC), clay, and organic carbon (OC). The AGD predictor variables include total count (uR/h), K (potassium), eU (uranium equivalent), and eTh (thorium equivalent), ratios between these elements (eTh/K, eU/K, and eU/eTh), factor F or F-parameter, anomalous potassium (Kd), anomalous uranium (Ud), anomalous magnetic field (AMF), vertical derivative (GZ), horizontal derivatives (GX and GY), and mafic index (MI). The approach was based on applying predictive modeling techniques using (1) digital elevation model (DEM) covariates and Sentinel-2 images with AGD; and (2) DEM covariates and Sentinel-2 images without the AGD. The study was conducted in Bom Jardim, a county in Rio de Janeiro-Brazil with an area of 382,430 km², with a database of 208 soil samples to a predefined depth (0-30 cm). Non-explanatory covariates for the selected soil attributes were excluded. Through the selected covariables, the random forest (RF) and support vector machine (SVM) models were applied with separate samples for training (75%) and validation (25%). The model's performance was evaluated through the R-squared (R2), root mean square error (RMSE), and mean absolute error (MAE), as well as null model values and coefficient of variation (CV%). The RF algorithm showed better performance with AGD (R2 values ranging from 0.15 to 0.23), as well as the SVM model (R2 values ranging from 0.08 to 0.23) when compared to RF (R2 values ranging from 0.10 to 0.20) and SVM (R2 values ranging from 0.04 to 0.10) models without AGD. Overall, the results suggest that AGD can be helpful for soil mapping. Nevertheless, it is crucial to acknowledge that the accuracy of AGD in predicting soil properties could vary depending on various common factors in DSM, such as the quality and resolution of the covariates and available soil data. Further research is needed to determine the optimal approach for using AGD in soil mapping. MenosAirborne geophysical data (AGD) have great potential to represent soil-forming factors. Because of that, the objective of this study was to evaluate the importance of AGD in predicting soil attributes such as aluminum saturation (ASat), base saturation (BS), cation exchange capacity (CEC), clay, and organic carbon (OC). The AGD predictor variables include total count (uR/h), K (potassium), eU (uranium equivalent), and eTh (thorium equivalent), ratios between these elements (eTh/K, eU/K, and eU/eTh), factor F or F-parameter, anomalous potassium (Kd), anomalous uranium (Ud), anomalous magnetic field (AMF), vertical derivative (GZ), horizontal derivatives (GX and GY), and mafic index (MI). The approach was based on applying predictive modeling techniques using (1) digital elevation model (DEM) covariates and Sentinel-2 images with AGD; and (2) DEM covariates and Sentinel-2 images without the AGD. The study was conducted in Bom Jardim, a county in Rio de Janeiro-Brazil with an area of 382,430 km², with a database of 208 soil samples to a predefined depth (0-30 cm). Non-explanatory covariates for the selected soil attributes were excluded. Through the selected covariables, the random forest (RF) and support vector machine (SVM) models were applied with separate samples for training (75%) and validation (25%). The model's performance was evaluated through the R-squared (R2), root mean square error (RMSE), and mean absolute error (MAE), as well as null model values and coefficient ... Mostrar Tudo |
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Palavras-Chave: |
Digital soil mapping; Gamma-ray spectrometry data; Hillslope areas; Machine learning; Magnetic data; Mapeamento digital do solo; Parent material. |
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Thesagro: |
Sensoriamento Remoto. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1155276/1/Could-airborne-geophysical-data-be-used-to-improve-predictive-modeling-2023.pdf
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Marc: |
LEADER 03095naa a2200277 a 4500
001 2155276
005 2023-07-26
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/rs15153719$2DOI
100 1 $aBASTOS, B. P.
245 $aCould airborne geophysical data be used to improve predictive modeling of agronomic soil properties in tropical hillslope area?$h[electronic resource]
260 $c2023
520 $aAirborne geophysical data (AGD) have great potential to represent soil-forming factors. Because of that, the objective of this study was to evaluate the importance of AGD in predicting soil attributes such as aluminum saturation (ASat), base saturation (BS), cation exchange capacity (CEC), clay, and organic carbon (OC). The AGD predictor variables include total count (uR/h), K (potassium), eU (uranium equivalent), and eTh (thorium equivalent), ratios between these elements (eTh/K, eU/K, and eU/eTh), factor F or F-parameter, anomalous potassium (Kd), anomalous uranium (Ud), anomalous magnetic field (AMF), vertical derivative (GZ), horizontal derivatives (GX and GY), and mafic index (MI). The approach was based on applying predictive modeling techniques using (1) digital elevation model (DEM) covariates and Sentinel-2 images with AGD; and (2) DEM covariates and Sentinel-2 images without the AGD. The study was conducted in Bom Jardim, a county in Rio de Janeiro-Brazil with an area of 382,430 km², with a database of 208 soil samples to a predefined depth (0-30 cm). Non-explanatory covariates for the selected soil attributes were excluded. Through the selected covariables, the random forest (RF) and support vector machine (SVM) models were applied with separate samples for training (75%) and validation (25%). The model's performance was evaluated through the R-squared (R2), root mean square error (RMSE), and mean absolute error (MAE), as well as null model values and coefficient of variation (CV%). The RF algorithm showed better performance with AGD (R2 values ranging from 0.15 to 0.23), as well as the SVM model (R2 values ranging from 0.08 to 0.23) when compared to RF (R2 values ranging from 0.10 to 0.20) and SVM (R2 values ranging from 0.04 to 0.10) models without AGD. Overall, the results suggest that AGD can be helpful for soil mapping. Nevertheless, it is crucial to acknowledge that the accuracy of AGD in predicting soil properties could vary depending on various common factors in DSM, such as the quality and resolution of the covariates and available soil data. Further research is needed to determine the optimal approach for using AGD in soil mapping.
650 $aSensoriamento Remoto
653 $aDigital soil mapping
653 $aGamma-ray spectrometry data
653 $aHillslope areas
653 $aMachine learning
653 $aMagnetic data
653 $aMapeamento digital do solo
653 $aParent material
700 1 $aPINHEIRO, H. S. K.
700 1 $aFERREIRA, F. J. F.
700 1 $aCARVALHO JUNIOR, W. de
700 1 $aANJOS, L. H. C. dos
773 $tRemote Sensing$gv. 15, n. 15, 3719, 2023.
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Embrapa Solos (CNPS) |
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