2011
DOI: 10.1590/s0103-90162011000500005
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Abstract: Upland rice (Oryza sativa L.) production is basically concentrated in four central Brazilian States, Mato Grosso, Goiás, Rondônia and Tocantins. To reduce the genotype and environment (G × E) interactions, the classification of environment groups was proposed. The goal of this study explores possibilities to adjust the upland rice regional breeding systems to optimally fit to the range of environments they are targeting, based on a historical yield data set of the Brazilian Geographic and Statistics Institute … Show more

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Cited by 22 publications
(7 citation statements)
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“…Actual yield were obtained from the Brazilian Geographical and Statistical Institute (IBGE) and Brazilian Food Supply Company (CONAB) for the period between 1980 and 2011. These data had their technological trend removed according to the procedure presented by Heinemann & Sentelhas (2011). The evaluated locations and their respective states were: Cruz Alta, Rio Grande do Sul; Campos Novos, Santa Catarina; Campo Mourão, Paraná; Assis, São Paulo; Dourados, Mato Grosso do Sul; Uberaba, Minas Gerais; Jataí, Goiás; Formosa, Goiás; Correntina, Bahia; Primavera do Leste, Mato Grosso; Tapurah, Mato Grosso; Peixe, Tocantins; Bom Jesus, Piauí; Santana do Araguaia, Pará; and Balsas, Maranhão (Fig.…”
Section: Methodsmentioning
confidence: 99%
“…Actual yield were obtained from the Brazilian Geographical and Statistical Institute (IBGE) and Brazilian Food Supply Company (CONAB) for the period between 1980 and 2011. These data had their technological trend removed according to the procedure presented by Heinemann & Sentelhas (2011). The evaluated locations and their respective states were: Cruz Alta, Rio Grande do Sul; Campos Novos, Santa Catarina; Campo Mourão, Paraná; Assis, São Paulo; Dourados, Mato Grosso do Sul; Uberaba, Minas Gerais; Jataí, Goiás; Formosa, Goiás; Correntina, Bahia; Primavera do Leste, Mato Grosso; Tapurah, Mato Grosso; Peixe, Tocantins; Bom Jesus, Piauí; Santana do Araguaia, Pará; and Balsas, Maranhão (Fig.…”
Section: Methodsmentioning
confidence: 99%
“…Second, UR is highly drought susceptible as compared with soybean or maize, which would increase the risks to growers. The latter is of particular importance in central Brazil since dry spells normally occur during the rainy season (Bernier et al , 2008; Crusciol et al , 2013), and because the subsoil acidity of the savannah soils leads to restricted root depth, which amplifies the negative effects of moderate droughts on crop growth (Heinemann and Sentelhas, 2011).…”
Section: Introductionmentioning
confidence: 99%
“…The standard deviation was used to quantify the uncertainties associated with soil texture, sowing date, maturity group and growing seasons in each site used for determining YG WD .The yield gap by sub-optimum crop management (YG CM ) was obtained from the difference between attainable and mean farmers' yield at the county. The mean farmers' yield at the county was obtained from IBGE (2017) database, which had the technological tendency, from 1989/90 to 2014/15 growing seasons, removed, considering the linear regression approach recommended byHeinemann and Sentelhas (2011). It was quantified the percentage of growing seasons with negative yield gap by sub-optimum crop management, identifying simulation management options from the aggregation of different sowing dates, maturity groups and soil types which lead to simulate attainable yield lower than mean farmers' yield at the county.…”
mentioning
confidence: 99%