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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Amazônia Oriental; Embrapa Gado de Corte; Embrapa Pecuária Sudeste. |
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Data corrente: |
29/12/2016 |
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Data da última atualização: |
30/03/2017 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
BIASE, A. G.; DIAS, C. T. dos S.; BARIONI, L. G.; ALBERTINI, T. Z.; MARTORANO, L. G.; OLTJEN, J. W.; LANNA, D. P. D.; OLIVEIRA, P. P. A.; MEDEIROS, S. R. de; TORRES JUNIOR, R. A. de A. |
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Afiliação: |
ADRIELE GIARETTA BIASE, Esalq/USP; CARLOS TADEU DOS SANTOS DIAS, Esalq/USP; LUIS GUSTAVO BARIONI, CNPTIA; TIAGO ZANETT ALBERTINI, Esalq/USP; LUCIETA GUERREIRO MARTORANO, CPATU; JAMES W. OLTJEN, University of California; DANTE PAZZANESE DUARTE LANNA, Esalq/USP; PATRICIA PERONDI ANCHAO OLIVEIRA, CPPSE; SERGIO RAPOSO DE MEDEIROS, CNPGC; ROBERTO AUGUSTO DE ALMEIDA TORRES JUNIOR, CNPGC. |
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Título: |
Parametrization of the Davis Growth Model using data of crossbred zebu cattle. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Scientia Agricola, v. 74, n. 1, p.8-17, Jan./Feb. 2017. |
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DOI: |
http://dx.doi.org/10.1590/1678-992X-2015-0284 |
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Idioma: |
Inglês |
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Conteúdo: |
The system of differential equations proposed by Oltjen et al. [1986, named Davis Growth Model (DGM)] to represent cattle growth has been parameterized with data from Bos taurus (British) and Bos indicus (Nellore) breeds. The DGM has been successfully used for simulation and decision support in the United States. However, the effect of about 30 years of genetic improvement and the use of different breeds may affect the model parameter values, which also may need to be re-estimated for crossbred animals. The aim of this study was to estimate parameter values and confidence intervals for the DGM with growth and body composition data from Zebu crossbred animals. Confidence intervals and asymptotic distribution were generated through nonparametric bootstrap with data from a field experiment conducted in Brazil. The parameters showed normal probability distribution for most scenarios. The rate constant for deoxyribonucleic acid (DNA) synthesis had a minimum increase of 156 % and the maximum of 389 %, compared to the original values and the maintenance requirement had a minimum increase of 126 % and maximum of 160 % compared to the original values. Lower limits of 95 % confidence intervals for the parameters related to maintenance and protein accretion rates were higher than the original estimates of the DGM, evidencing genetic differences of the Zebu crossbred animals in relation to the original DGM parameters. |
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Palavras-Chave: |
Asymptotic distribution; Calibração; Calibrating; Cattle growth; Crescimento do gado; Distribuição assintótica; Equações diferenciais ordinárias; Modelo de crescimento; Nonparametric bootstrap; Ordinary differential equations. |
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Thesagro: |
Ácido nucleico; Agricultura; DNA; Gado zebu; Modelo Matemático. |
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Thesaurus Nal: |
Beef cattle; Cattle; Mathematical models; Zebu. |
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Categoria do assunto: |
--
L Ciência Animal e Produtos de Origem Animal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/152540/1/AP-parametrization-Biase.pdf
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/165135/1/Parametrization-of-the-Davis-Growth-Model.pdf
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Marc: |
LEADER 02816naa a2200469 a 4500
001 2059601
005 2017-03-30
008 2017 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1590/1678-992X-2015-0284$2DOI
100 1 $aBIASE, A. G.
245 $aParametrization of the Davis Growth Model using data of crossbred zebu cattle.$h[electronic resource]
260 $c2017
520 $aThe system of differential equations proposed by Oltjen et al. [1986, named Davis Growth Model (DGM)] to represent cattle growth has been parameterized with data from Bos taurus (British) and Bos indicus (Nellore) breeds. The DGM has been successfully used for simulation and decision support in the United States. However, the effect of about 30 years of genetic improvement and the use of different breeds may affect the model parameter values, which also may need to be re-estimated for crossbred animals. The aim of this study was to estimate parameter values and confidence intervals for the DGM with growth and body composition data from Zebu crossbred animals. Confidence intervals and asymptotic distribution were generated through nonparametric bootstrap with data from a field experiment conducted in Brazil. The parameters showed normal probability distribution for most scenarios. The rate constant for deoxyribonucleic acid (DNA) synthesis had a minimum increase of 156 % and the maximum of 389 %, compared to the original values and the maintenance requirement had a minimum increase of 126 % and maximum of 160 % compared to the original values. Lower limits of 95 % confidence intervals for the parameters related to maintenance and protein accretion rates were higher than the original estimates of the DGM, evidencing genetic differences of the Zebu crossbred animals in relation to the original DGM parameters.
650 $aBeef cattle
650 $aCattle
650 $aMathematical models
650 $aZebu
650 $aÁcido nucleico
650 $aAgricultura
650 $aDNA
650 $aGado zebu
650 $aModelo Matemático
653 $aAsymptotic distribution
653 $aCalibração
653 $aCalibrating
653 $aCattle growth
653 $aCrescimento do gado
653 $aDistribuição assintótica
653 $aEquações diferenciais ordinárias
653 $aModelo de crescimento
653 $aNonparametric bootstrap
653 $aOrdinary differential equations
700 1 $aDIAS, C. T. dos S.
700 1 $aBARIONI, L. G.
700 1 $aALBERTINI, T. Z.
700 1 $aMARTORANO, L. G.
700 1 $aOLTJEN, J. W.
700 1 $aLANNA, D. P. D.
700 1 $aOLIVEIRA, P. P. A.
700 1 $aMEDEIROS, S. R. de
700 1 $aTORRES JUNIOR, R. A. de A.
773 $tScientia Agricola$gv. 74, n. 1, p.8-17, Jan./Feb. 2017.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Tipo/Formato |
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Cutter |
Registro |
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Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Ocidental. |
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Data corrente: |
15/10/2019 |
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Data da última atualização: |
16/10/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
SCHEPASCHENKO, D.; CHAVE, J.; PHILLIPS, O. L.; LEWIS, S. L.; DAVIES, S. J.; RÉJOU-MÉCHAIN, M.; SIST, P.; SCIPAL, K.; PERGER, C.; HERAULT, B.; LABRIÈRE, N.; HOFHANSL, F.; AFFUM-BAFFOE, K.; ALEINIKOV, A.; ALONSO, A.; AMANI, C.; ARAUJO-MURAKAMI, A.; ARMSTON, J.; ARROYO, L.; ASCARRUNZ, N.; AZEVEDO, C. P. de; BAKER, T.; BALAZY, R.; BEDEAU, C.; BERRY, N.; BILOUS, A. M.; BILOUS, S. Y.; BISSIENGOU, P.; BLANC, L.; BOBKOVA, K. S.; BRASLAVSKAYA, T.; BRIENEN, R.; BURSLEM, D. F. R. P.; CONDIT, R.; CUNI-SANCHEZ, A.; DANILINA, D.; TORRES, D. del C.; DERROIRE, G.; DESCROIX, L.; SOTTA, E. D.; OLIVEIRA, M. V. N. d'; DRESEL, C.; ERWIN, T.; EVDOKIMENKO, M. D.; FALCK, J.; FELDPAUSCH, T. R.; FOLI, E. G.; FOSTER, R.; FRITZ, S.; GARCIA-ABRIL, A. D.; GORNOV, A.; GORNOVA, M.; GOTHARD-BASSÉBÉ, E.; GOURLET-FLEURY, S.; GUEDES, M. C.; HAMER, K. C.; SUSANTY, F. H.; HIGUCHI, N.; CORONADO, E. N. H.; HUBAU, W.; HUBBELL, S.; ILSTEDT, U.; IVANOV, V. V.; KANASHIRO, M.; KARLSSON, A.; KARMINOV, V. N.; KILLEEN, T.; KOFFI, J. C. K.; KONOVALOVA, M.; KRAXNER, F.; KREJZA, J.; KRISNAWATI, H.; KRIVOBOKOV, L. V.; KUZNETSOV, M. A.; LAKYDA, I.; LAKYDA, P. I.; LICONA, J. C.; LUCAS, R. M.; LUKINA, N.; LUSSETTI, D.; MALHI, Y.; MANZANERA, J. A.; MARIMON, B.; MARIMON JUNIOR, B. H.; VASQUEZ MARTINEZ, R.; MARTYNENKO, O. V.; MATSALA, M.; MATYASHUK, R. K.; FREITAS, L. J. M. de; MEMIAGHE, H.; MENDOZA, C.; MONTEAGUDO MENDONZA, A.; MOROZIUK, O. V.; MUKHORTOVA, L.; MUSA, S.; NAZIMOVA, D. I.; OKUDA, T.; OLIVEIRA, L. C. de; ONTIKOV, P. V.; OSIPOV, A. F.; PIETSCH, S.; PLAYFAIR, M.; POULSEN, J.; RADCHENKO, V. G.; RODNEY, K.; ROZAK, A. H.; RUSCHEL, A. R.; RUTISHAUSER, E.; SEE, L.; SHCHEPASHCHENKO, M.; SHEVCHENKO, N.; SHVIDENKO, A.; SILVEIRA, M.; SINGH, J.; SONKÉ, B.; SOUZA, C. R. de; STERENCZAK, K.; STONOZHENKO, L.; SULLIVAN, M. J. P.; SZATNIEWSKA, J.; TAEDOUMG, H.; TER STEEGE, H.; TIKHONOVA, E.; TOLEDO, M.; TREFILOVA, O. V.; VALBUENA, R.; VALENZUELA GAMARRA, L.; VASILIEV, S.; VEDROVA, E. F.; VERHOVETS, S. V.; VIDAL, E.; VLADIMIROVA, N. A.; VLEMINCKX, J.; VOS, V. A.; VOZMITEL, F. K.; WANEK, W.; WEST, T. A. P.; WOELL, H.; WOODS, J. T.; WORTEL, V.; YAMADA, T.; HAJAR, Z. S. N.; ZO-BI, I. C. |
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Afiliação: |
DMITRY SCHEPASCHENKO; JÉRÔME CHAVE; OLIVER L. PHILLIPS; SIMON L. LEWIS; STUART J. DAVIES; MAXIME RÉJOU-MÉCHAIN; PLINIO SIST; KLAUS SCIPAL; CHRISTOPH PERGER; BRUNO HERAULT; NICOLAS LABRIÈRE; FLORIAN HOFHANSL; KOFI AFFUM-BAFFOE; ALEXEI ALEINIKOV; ALFONSO ALONSO; CHRISTIAN AMANI; ALEJANDRO ARAUJO-MURAKAMI; JOHN ARMSTON; LUZMILA ARROYO; NATALY ASCARRUNZ; CELSO PAULO DE AZEVEDO, CPAA; TIMOTHY BAKER; RADOMIR BALAZY; CAROLINE BEDEAU; NICHOLAS BERRY; ANDRII M. BILOUS; SVITLANA YU. BILOUS; PULCHÉRIE BISSIENGOU; LILIAN BLANC; KAPITOLINA S. BOBKOVA; TATYANA BRASLAVSKAYA; ROEL BRIENEN; DAVID F. R. P. BURSLEM; RICHARD CONDIT; AIDA CUNI-SANCHEZ; DILSHAD DANILINA; DENNIS DEL CASTILLO TORRES; GÉRALDINE DERROIRE; LAURENT DESCROIX; ELENEIDE DOFF SOTTA; MARCUS VINICIO NEVES D OLIVEIRA, CPAF-AC; CHRISTOPHER DRESEL; TERRY ERWIN; MIKHAIL D. EVDOKIMENKO; JAN FALCK; TED R. FELDPAUSCH; ERNEST G. FOLI; ROBIN FOSTER; STEFFEN FRITZ; ANTONIO DAMIAN GARCIA-ABRIL; ALEKSEY GORNOV; MARIA GORNOVA; ERNEST GOTHARD-BASSÉBÉ; SYLVIE GOURLET-FLEURY; MARCELINO CARNEIRO GUEDES, CPAF-AP; KEITH C. HAMER; FARIDA HERRY SUSANTY; NIRO HIGUCHI; EURÍDICE N. HONORIO CORONADO; WANNES HUBAU; STEPHEN HUBBELL; ULRIK ILSTEDT; VIKTOR V. IVANOV; MILTON KANASHIRO, CPATU; ANDERS KARLSSON; VIKTOR N. KARMINOV; TIMOTHY KILLEEN; JEAN-CLAUDE KONAN KOFFI; MARIA KONOVALOVA; FLORIAN KRAXNER; JAN KREJZA; HARUNI KRISNAWATI; LEONID V. KRIVOBOKOV; MIKHAIL A. KUZNETSOV; IVAN LAKYDA; PETRO I. LAKYDA; JUAN CARLOS LICONA; RICHARD M. LUCAS; NATALIA LUKINA; DANIEL LUSSETTI; YADVINDER MALHI; JOSÉ ANTONIO MANZANERA; BEATRIZ MARIMON; BEN HUR MARIMON JUNIOR; RODOLFO VASQUEZ MARTINEZ; OLGA V. MARTYNENKO; MAKSYM MATSALA; RAISA K. MATYASHUK; LUCAS JOSE MAZZEI DE FREITAS, CPATU; HERVÉ MEMIAGHE; CASIMIRO MENDOZA; ABEL MONTEAGUDO MENDOZA; OLGA V. MOROZIUK; LIUDMILA MUKHORTOVA; SAMSUDIN MUSA; DINA I. NAZIMOVA; TOSHINORI OKUDA; LUIS CLAUDIO DE OLIVEIRA, CPAF-AC; PETR V. ONTIKOV; ANDREY F. OSIPOV; STEPHAN PIETSCH; MAUREEN PLAYFAIR; JOHN POULSEN; VLADIMIR G. RADCHENKO; KENNETH RODNEY; ANDES H. ROZAK; ADEMIR ROBERTO RUSCHEL, CPATU; ERVAN RUTISHAUSER; LINDA SEE; MARIA SHCHEPASHCHENKO; NIKOLAY SHEVCHENKO; ANATOLY SHVIDENKO; MARCOS SILVEIRA; JAMES SINGH; BONAVENTURE SONKÉ; CINTIA RODRIGUES DE SOUZA, CPAA; KRZYSZTOF STERENCZAK; LEONID STONOZHENKO; MARTIN J. P. SULLIVAN; JUSTYNA SZATNIEWSKA; HERMANN TAEDOUMG; HANS TER STEEGE; ELENA TIKHONOVA; MARISOL TOLEDO; OLGA V. TREFILOVA; RUBEN VALBUENA; LUIS VALENZUELA GAMARRA; SERGEY VASILIEV; ESTELLA F. VEDROVA; SERGEY V. VERHOVETS; EDSON VIDAL; NADEZHDA A. VLADIMIROVA; JASON VLEMINCKX; VINCENT A. VOS; FOMA K. VOZMITEL; WOLFGANG WANEK; THALES A. P. WEST; HANNSJORG WOELL; JOHN T. WOODS; VERGINIA WORTEL; TOSHIHIRO YAMADA; ZAMAH SHARI NUR HAJAR; IRIÉ CASIMIR ZO-BI. |
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Título: |
The forest observation system, building a global reference dataset for remote sensing of forest biomass. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Scientific Data, v. 6, n. 198, p. 1-11, 2019. |
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DOI: |
https://doi.org/10.1038/s41597-019-0196-1 |
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Idioma: |
Inglês |
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Conteúdo: |
Forest biomass is an essential indicator for monitoring the Earth?s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. |
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Thesagro: |
Biomassa; Sensoriamento Remoto. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/202898/1/Nature-Schepaschenko-Biomassa.pdf
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Marc: |
LEADER 05124naa a2201861 a 4500
001 2113119
005 2019-10-16
008 2019 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1038/s41597-019-0196-1$2DOI
100 1 $aSCHEPASCHENKO, D.
245 $aThe forest observation system, building a global reference dataset for remote sensing of forest biomass.$h[electronic resource]
260 $c2019
520 $aForest biomass is an essential indicator for monitoring the Earth?s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others.
650 $aBiomassa
650 $aSensoriamento Remoto
700 1 $aCHAVE, J.
700 1 $aPHILLIPS, O. L.
700 1 $aLEWIS, S. L.
700 1 $aDAVIES, S. J.
700 1 $aRÉJOU-MÉCHAIN, M.
700 1 $aSIST, P.
700 1 $aSCIPAL, K.
700 1 $aPERGER, C.
700 1 $aHERAULT, B.
700 1 $aLABRIÈRE, N.
700 1 $aHOFHANSL, F.
700 1 $aAFFUM-BAFFOE, K.
700 1 $aALEINIKOV, A.
700 1 $aALONSO, A.
700 1 $aAMANI, C.
700 1 $aARAUJO-MURAKAMI, A.
700 1 $aARMSTON, J.
700 1 $aARROYO, L.
700 1 $aASCARRUNZ, N.
700 1 $aAZEVEDO, C. P. de
700 1 $aBAKER, T.
700 1 $aBALAZY, R.
700 1 $aBEDEAU, C.
700 1 $aBERRY, N.
700 1 $aBILOUS, A. M.
700 1 $aBILOUS, S. Y.
700 1 $aBISSIENGOU, P.
700 1 $aBLANC, L.
700 1 $aBOBKOVA, K. S.
700 1 $aBRASLAVSKAYA, T.
700 1 $aBRIENEN, R.
700 1 $aBURSLEM, D. F. R. P.
700 1 $aCONDIT, R.
700 1 $aCUNI-SANCHEZ, A.
700 1 $aDANILINA, D.
700 1 $aTORRES, D. del C.
700 1 $aDERROIRE, G.
700 1 $aDESCROIX, L.
700 1 $aSOTTA, E. D.
700 1 $aOLIVEIRA, M. V. N. d'
700 1 $aDRESEL, C.
700 1 $aERWIN, T.
700 1 $aEVDOKIMENKO, M. D.
700 1 $aFALCK, J.
700 1 $aFELDPAUSCH, T. R.
700 1 $aFOLI, E. G.
700 1 $aFOSTER, R.
700 1 $aFRITZ, S.
700 1 $aGARCIA-ABRIL, A. D.
700 1 $aGORNOV, A.
700 1 $aGORNOVA, M.
700 1 $aGOTHARD-BASSÉBÉ, E.
700 1 $aGOURLET-FLEURY, S.
700 1 $aGUEDES, M. C.
700 1 $aHAMER, K. C.
700 1 $aSUSANTY, F. H.
700 1 $aHIGUCHI, N.
700 1 $aCORONADO, E. N. H.
700 1 $aHUBAU, W.
700 1 $aHUBBELL, S.
700 1 $aILSTEDT, U.
700 1 $aIVANOV, V. V.
700 1 $aKANASHIRO, M.
700 1 $aKARLSSON, A.
700 1 $aKARMINOV, V. N.
700 1 $aKILLEEN, T.
700 1 $aKOFFI, J. C. K.
700 1 $aKONOVALOVA, M.
700 1 $aKRAXNER, F.
700 1 $aKREJZA, J.
700 1 $aKRISNAWATI, H.
700 1 $aKRIVOBOKOV, L. V.
700 1 $aKUZNETSOV, M. A.
700 1 $aLAKYDA, I.
700 1 $aLAKYDA, P. I.
700 1 $aLICONA, J. C.
700 1 $aLUCAS, R. M.
700 1 $aLUKINA, N.
700 1 $aLUSSETTI, D.
700 1 $aMALHI, Y.
700 1 $aMANZANERA, J. A.
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700 1 $aVASQUEZ MARTINEZ, R.
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700 1 $aMONTEAGUDO MENDONZA, A.
700 1 $aMOROZIUK, O. V.
700 1 $aMUKHORTOVA, L.
700 1 $aMUSA, S.
700 1 $aNAZIMOVA, D. I.
700 1 $aOKUDA, T.
700 1 $aOLIVEIRA, L. C. de
700 1 $aONTIKOV, P. V.
700 1 $aOSIPOV, A. F.
700 1 $aPIETSCH, S.
700 1 $aPLAYFAIR, M.
700 1 $aPOULSEN, J.
700 1 $aRADCHENKO, V. G.
700 1 $aRODNEY, K.
700 1 $aROZAK, A. H.
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700 1 $aVALENZUELA GAMARRA, L.
700 1 $aVASILIEV, S.
700 1 $aVEDROVA, E. F.
700 1 $aVERHOVETS, S. V.
700 1 $aVIDAL, E.
700 1 $aVLADIMIROVA, N. A.
700 1 $aVLEMINCKX, J.
700 1 $aVOS, V. A.
700 1 $aVOZMITEL, F. K.
700 1 $aWANEK, W.
700 1 $aWEST, T. A. P.
700 1 $aWOELL, H.
700 1 $aWOODS, J. T.
700 1 $aWORTEL, V.
700 1 $aYAMADA, T.
700 1 $aHAJAR, Z. S. N.
700 1 $aZO-BI, I. C.
773 $tScientific Data$gv. 6, n. 198, p. 1-11, 2019.
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