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Registro Completo |
Biblioteca(s): |
Embrapa Meio-Norte. |
Data corrente: |
17/10/2022 |
Data da última atualização: |
17/10/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
SILVA, W. J. dos S.; ALCANTARA NETO, F. de; AL-QAHTANI, W. H.; OKLA, M. K.; AL-HASHIMI, A.; VIEIRA, P. F. de M. J.; GRAVINA, G. de A.; ZUFFO, A. M.; DUTRA, A. F.; CARVALHO, L. C. B.; SOUSA, R. S. de; PEREIRA, A. P. de A.; LEITE, W. de S.; SILVA JUNIOR, G. B. da; SILVA, A. C. da; LEITE, M. R. L.; LUSTOSA SOBRINHO, R.; ABDELGAWAD, H. |
Afiliação: |
WELDER JOSE DOS SANTOS SILVA, FEDERAL UNIVERSITY OF PIAUI; FRANCISCO DE ALCANTARA NETO, FEDERAL UNIVERSITY OF PIAUI; WAHIDAH H. AL-QAHTANI, COLLEGE OF FOOD AND AGRICULTURAL SCIENCES, KING SAUD UNIVERSITY, RIYADH, SAUDI ARABIA; MOHAMMAD K. OKLA, COLLEGE OF SCIENCE, KING SAUD UNIVERSITY, RIYADH, SAUDI ARABIA; ABDULRAHMAN AL-HASHIMI, COLLEGE OF SCIENCE, KING SAUD UNIVERSITY, RIYADH, SAUDI ARABIA; PAULO FERNANDO DE MELO JORGE VIEIRA, CPAMN; GERALDO DE AMARAL GRAVINA, STATE UNIVERSITY OF THE NORTH FLUMINENSE DARCY RIBEIRO, RIO DE JANEIRO, BRAZIL; ALAN MARIO ZUFFO, STATE UNIVERSITY OF MARANHÃO, BALSAS, MARANHÃO, BRAZIL; ALEXSON FILGUEIRAS DUTRA, FEDERAL UNIVERSITY OF PIAUI; LEONARDO CASTELO BRANCO CARVALHO, FEDERAL RURAL UNIVERSITY OF THE AMAZONIA; RICARDO SILVA DE SOUSA, FEDERAL UNIVERSITY OF PIAUI; ARTHUR PRUDÊNCIO DE ARAUJO PEREIRA, FEDERAL UNIVERSITY OF CEARA; WALLACE DE SOUSA LEITE, FEDERAL UNIVERSITY OF PIAUI; GABRIEL BARBOSA DA SILVA JUNIOR, FEDERAL UNIVERSITY OF PIAUI; ADRIANA CONCEIÇAO DA SILVA, FEDERAL UNIVERSITY OF PIAUI; MARCOS RENAN LIMA LEITE, FEDERAL UNIVERSITY OF PIAUI; RENATO LUSTOSA SOBRINHO, FEDERAL UNIVERSITY OF TECHNOLOGY, PATO BRANCO, PARANA, BRAZIL; HAMADA ABDELGAWAD, UNIVERSITY OF ANTWERP, ANTWERPEN, BELGIUM. |
Título: |
Yield of soybean genotypes identified through GGE biplot and path analysis. |
Ano de publicação: |
2022 |
Fonte/Imprenta: |
PLOS ONE, v. 17, n. 10, e0274726, 2022. |
DOI: |
https://doi.org/10.1371/journal. pone.0274726 |
Idioma: |
Inglês |
Conteúdo: |
Genotype x environment (GxE) interaction is an important source of variation in soybean yield, which can significantly influence selection in breeding programs. This study aimed to select superior soybean genotypes for performance and yield stability, from data from multienvironment trials (METs), through GGE biplot analysis that combines the main effects of the genotype (G) plus the genotype-by-environment (G×E) interaction. As well as, through path analysis, determine the direct and indirect influences of yield components on soybean grain yield, as a genotype selection strategy. |
Palavras-Chave: |
Interação genótipo x ambiente. |
Thesagro: |
Genótipo; Produtividade; Soja. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1147354/1/YieldSoybeanGenotypesGGEBiplotPlosOnev17n10e0274726.2022-1.pdf
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Marc: |
LEADER 01717naa a2200385 a 4500 001 2147354 005 2022-10-17 008 2022 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1371/journal. pone.0274726$2DOI 100 1 $aSILVA, W. J. dos S. 245 $aYield of soybean genotypes identified through GGE biplot and path analysis.$h[electronic resource] 260 $c2022 520 $aGenotype x environment (GxE) interaction is an important source of variation in soybean yield, which can significantly influence selection in breeding programs. This study aimed to select superior soybean genotypes for performance and yield stability, from data from multienvironment trials (METs), through GGE biplot analysis that combines the main effects of the genotype (G) plus the genotype-by-environment (G×E) interaction. As well as, through path analysis, determine the direct and indirect influences of yield components on soybean grain yield, as a genotype selection strategy. 650 $aGenótipo 650 $aProdutividade 650 $aSoja 653 $aInteração genótipo x ambiente 700 1 $aALCANTARA NETO, F. de 700 1 $aAL-QAHTANI, W. H. 700 1 $aOKLA, M. K. 700 1 $aAL-HASHIMI, A. 700 1 $aVIEIRA, P. F. de M. J. 700 1 $aGRAVINA, G. de A. 700 1 $aZUFFO, A. M. 700 1 $aDUTRA, A. F. 700 1 $aCARVALHO, L. C. B. 700 1 $aSOUSA, R. S. de 700 1 $aPEREIRA, A. P. de A. 700 1 $aLEITE, W. de S. 700 1 $aSILVA JUNIOR, G. B. da 700 1 $aSILVA, A. C. da 700 1 $aLEITE, M. R. L. 700 1 $aLUSTOSA SOBRINHO, R. 700 1 $aABDELGAWAD, H. 773 $tPLOS ONE$gv. 17, n. 10, e0274726, 2022.
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Registro original: |
Embrapa Meio-Norte (CPAMN) |
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Registro Completo
Biblioteca(s): |
Embrapa Instrumentação. |
Data corrente: |
07/06/2021 |
Data da última atualização: |
10/06/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
COLNAGO, L. A.; WIESMAN, Z.; PAGES, G.; MUSSE, M.; MONARETTO, T.; WINDT, C. W.; RONDEAU-MOURO, C. |
Afiliação: |
LUIZ ALBERTO COLNAGO, CNPDIA. |
Título: |
Low field, time domain NMR in the agriculture and agrifood sectors: An overview of applications in plants, foods and biofuels. |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Journal of Magnetic Resonance, v. 323, a. 106899, 2021. |
ISSN: |
1090-7807 |
DOI: |
https://doi.org/10.1016/j.jmr.2020.106899 |
Idioma: |
Inglês |
Conteúdo: |
In this contribution, a selective overview of low field, time-domain NMR (TD-NMR) applications in the agriculture and agrifood sectors is presented. The first applications of commercial TD-NMR instruments were in food and agriculture domains. Many of these earlier methods have now been recognized as standard methods by several international agencies. Since 2000, several new applications have been developed, using state of the art instruments, new pulse sequences and new signal processing methods. TDNMR is expected, in the coming years, to become even more important in quality control of fresh food and agricultural products, as well as for a wide range of food-processed products. TD-NMR systems provide excellent means to collect data relevant for use in the agricultural environment and the bioenergy industry. Data and information collected by TD-NMR systems thus may support decision makers in business and public organizations. |
Palavras-Chave: |
Food; Relaxation; TD-NMR. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01701naa a2200253 a 4500 001 2132202 005 2022-06-10 008 2021 bl uuuu u00u1 u #d 022 $a1090-7807 024 7 $ahttps://doi.org/10.1016/j.jmr.2020.106899$2DOI 100 1 $aCOLNAGO, L. A. 245 $aLow field, time domain NMR in the agriculture and agrifood sectors$bAn overview of applications in plants, foods and biofuels.$h[electronic resource] 260 $c2021 520 $aIn this contribution, a selective overview of low field, time-domain NMR (TD-NMR) applications in the agriculture and agrifood sectors is presented. The first applications of commercial TD-NMR instruments were in food and agriculture domains. Many of these earlier methods have now been recognized as standard methods by several international agencies. Since 2000, several new applications have been developed, using state of the art instruments, new pulse sequences and new signal processing methods. TDNMR is expected, in the coming years, to become even more important in quality control of fresh food and agricultural products, as well as for a wide range of food-processed products. TD-NMR systems provide excellent means to collect data relevant for use in the agricultural environment and the bioenergy industry. Data and information collected by TD-NMR systems thus may support decision makers in business and public organizations. 653 $aFood 653 $aRelaxation 653 $aTD-NMR 700 1 $aWIESMAN, Z. 700 1 $aPAGES, G. 700 1 $aMUSSE, M. 700 1 $aMONARETTO, T. 700 1 $aWINDT, C. W. 700 1 $aRONDEAU-MOURO, C. 773 $tJournal of Magnetic Resonance$gv. 323, a. 106899, 2021.
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