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Registro Completo |
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
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Data corrente: |
06/03/2025 |
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Data da última atualização: |
06/03/2025 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
CORBELLINI, M.; BOBEK, D. V.; TOLEDO, J. F. F. de; FERREIRA, L. U.; SANTANA, D. C.; GILIO, T. A. S.; TEODORO, L. P. R.; TEODORO, P. E.; TARDIN, F. D. |
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Afiliação: |
MARCOS CORBELLINI, SYNGENTA; DANIEL VICENTE BOBEK, SYNGENTA; JOSÉ FRANCISCO FERRAZ DE TOLEDO, THE CONTEXT NETWORK; LENIO URZEDA FERREIRA, SYNGENTA; DTHENIFER CORDEIRO SANTANA, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; THIAGO ALEXANDRE SANTANA GILIO, UNIVERSIDADE FEDERAL DE MATO GROSSO; LARISSA PEREIRA RIBEIRO TEODORO, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; PAULO EDUARDO TEODORO, UNIVERSIDADE FEDERAL DE MATO GROSSO DO SUL; FLAVIO DESSAUNE TARDIN, CNPMS. |
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Título: |
Geographical adaptability for optimizing the recommendation of soybean cultivars in the Brazilian Cerrado. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
Scientific Reports, v. 14, 13076, 2024. |
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Idioma: |
Inglês |
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Conteúdo: |
Yield multi-location trials associated to geostatistical techniques with environmental covariables can provide a better understanding of G x E interactions and, consequently, adaptation limits of soybean cultivars. Thus, the main objective of this study is understanding the environmental covariables efects on soybean adaptation, as well as predicting the adaptation of soybean under environmental variations and then recommend each soybean cultivar to favorable environments aiming maximize the average yield. The trials were carried out in randomized block design (RBD) with three replicates over three years, in 28 locations. Thirty-two genotypes (commercial and pre-commercial) representing diferent maturity groups (7.5–8.5) were evaluated in each trial were covering the Edaphoclimatic Region (REC) 401, 402 and 403. The covariables adopted as environmental descriptors were accumulated rainfall, minimum temperature, mean temperature, maximum temperature, photoperiod, relative humidity, soil clay content, soil water avaibility and altitude. After ftting means through Mixed Linear Model, the Regression-Kriging procedure was applied to spacialize the grain yield using environmental covariables as predictors. The covariables explained 32.54% of the GxE interaction, being the soil water avaibility the most important to the adaptation of soybean cultivars, contributing with 7.80%. Yield maps of each cultivar were obtained and, hence, the yield maximization map based on cultivar recommendation was elaborated. MenosYield multi-location trials associated to geostatistical techniques with environmental covariables can provide a better understanding of G x E interactions and, consequently, adaptation limits of soybean cultivars. Thus, the main objective of this study is understanding the environmental covariables efects on soybean adaptation, as well as predicting the adaptation of soybean under environmental variations and then recommend each soybean cultivar to favorable environments aiming maximize the average yield. The trials were carried out in randomized block design (RBD) with three replicates over three years, in 28 locations. Thirty-two genotypes (commercial and pre-commercial) representing diferent maturity groups (7.5–8.5) were evaluated in each trial were covering the Edaphoclimatic Region (REC) 401, 402 and 403. The covariables adopted as environmental descriptors were accumulated rainfall, minimum temperature, mean temperature, maximum temperature, photoperiod, relative humidity, soil clay content, soil water avaibility and altitude. After ftting means through Mixed Linear Model, the Regression-Kriging procedure was applied to spacialize the grain yield using environmental covariables as predictors. The covariables explained 32.54% of the GxE interaction, being the soil water avaibility the most important to the adaptation of soybean cultivars, contributing with 7.80%. Yield maps of each cultivar were obtained and, hence, the yield maximization map based on cultivar recomme... Mostrar Tudo |
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Palavras-Chave: |
Adaptação; Geoestatística; Variação ambiental. |
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Thesagro: |
Cerrado; Glycine Max; Produtividade; Rendimento; Soja. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02399naa a2200313 a 4500
001 2173619
005 2025-03-06
008 2024 bl uuuu u00u1 u #d
100 1 $aCORBELLINI, M.
245 $aGeographical adaptability for optimizing the recommendation of soybean cultivars in the Brazilian Cerrado.$h[electronic resource]
260 $c2024
520 $aYield multi-location trials associated to geostatistical techniques with environmental covariables can provide a better understanding of G x E interactions and, consequently, adaptation limits of soybean cultivars. Thus, the main objective of this study is understanding the environmental covariables efects on soybean adaptation, as well as predicting the adaptation of soybean under environmental variations and then recommend each soybean cultivar to favorable environments aiming maximize the average yield. The trials were carried out in randomized block design (RBD) with three replicates over three years, in 28 locations. Thirty-two genotypes (commercial and pre-commercial) representing diferent maturity groups (7.5–8.5) were evaluated in each trial were covering the Edaphoclimatic Region (REC) 401, 402 and 403. The covariables adopted as environmental descriptors were accumulated rainfall, minimum temperature, mean temperature, maximum temperature, photoperiod, relative humidity, soil clay content, soil water avaibility and altitude. After ftting means through Mixed Linear Model, the Regression-Kriging procedure was applied to spacialize the grain yield using environmental covariables as predictors. The covariables explained 32.54% of the GxE interaction, being the soil water avaibility the most important to the adaptation of soybean cultivars, contributing with 7.80%. Yield maps of each cultivar were obtained and, hence, the yield maximization map based on cultivar recommendation was elaborated.
650 $aCerrado
650 $aGlycine Max
650 $aProdutividade
650 $aRendimento
650 $aSoja
653 $aAdaptação
653 $aGeoestatística
653 $aVariação ambiental
700 1 $aBOBEK, D. V.
700 1 $aTOLEDO, J. F. F. de
700 1 $aFERREIRA, L. U.
700 1 $aSANTANA, D. C.
700 1 $aGILIO, T. A. S.
700 1 $aTEODORO, L. P. R.
700 1 $aTEODORO, P. E.
700 1 $aTARDIN, F. D.
773 $tScientific Reports$gv. 14, 13076, 2024.
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Embrapa Milho e Sorgo (CNPMS) |
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| 1. |  | TOMICH, T. P.; CATTANEO, A.; CHATER, S.; GEIST, H. J.; GOCKOWSKI, J.; KAIMOWITZ, D.; LAMBIN, E. F.; LEWIS, J.; NDOYE, O.; PALM, C. A.; STOLLE, F.; SUNDERLIN, W. D.; VALENTIM, J. F.; NOORDWIJK, M. van; VOSTI, S. A. Balancing agricultural development and environmental objectives: assessing tradeoffs in the humid tropics. In: PALM, C. A.; VOSTI, S. A.; SANCHEZ, P. A.; ERICKSEN, P. J. (ed.). Slash-and-burn agriculture: the search for alternatives. New York: Columbia University Press, 2005. cap. 18, p. 415-440.| Tipo: Capítulo em Livro Técnico-Científico |
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