Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/217363
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dc.contributor.authorHEINEMANN, A. B.
dc.contributor.authorSTONE, L. F.
dc.date.accessioned2024-02-05T14:32:32Z-
dc.date.available2024-02-05T14:32:32Z-
dc.date.created2008-09-10
dc.date.issued2008
dc.identifier.citationIn: INTERNATIONAL CONFERENCE OF AGRICULTURAL ENGINEERING; BRAZILIAN CONGRESS OF AGRICULTURAL ENGINEERING, 37.; INTERNATIONAL LIVESTOCK ENVIRONMENT SYMPOSIUM - ILES, 8., 2008, Foz do Iguaçu. Technology for all: sharing the knowledge for development: proceedings... Foz do Iguaçu: SBEA, 2008.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/217363-
dc.descriptionThe objective of this study was to determine the optimum sowing date for early upland rice cultivar at Santo Antonio de Goiás, GO, Brazil. To optimize solar radiation and precipitation during the upland rice sowing period (from November to December) it was used the crop model RICE06 from Ecotrop plataform. To mimic the conditions of region, two scenarios were created: a) no restriction to root development (0.8 m effective root depth) and b) restrictions to root development (Al toxic in the subsoil ? 0.4 m effective root depth). The crop model was run based on the climate historical date (22 years of daily data for precipitation, solar radiation, maximum and minimum temperature, maximum and minimum relative humidity, and wind speed) collected at Embrapa Rice & Beans weather station. Five different sowing dates (01/11, 15/11, 1/12, 15/12, and 31/12) were taken into account. The decision criterions used to determine the optimum sowing date were the variability, comparison of exceedance probability and mean variation for yield and the averaged index stress factor. The results obtained showed that the optimum sowing date for both scenarios was 15-Nov.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectCrop model
dc.subjectRoot depth
dc.titleDetermining optimum sowing date for early upland rice cultivar using modelling approach.
dc.typeArtigo em anais e proceedings
dc.subject.thesagroArroz
dc.subject.thesagroOryza Sativa
dc.subject.thesagroModelo de Simulação
dc.subject.nalthesaurusrice
riaa.ainfo.id217363
riaa.ainfo.lastupdate2024-02-05
dc.contributor.institutionALEXANDRE BRYAN HEINEMANN, CNPAF; LUIS FERNANDO STONE, CNPAF.
Appears in Collections:Artigo em anais de congresso (CNPAF)

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