Simulating maize yield in sub-tropical conditions of southern Brazil using Glam model

cg.contributor.crpClimate Change, Agriculture and Food Securityen_US
cg.coverage.countryBrazilen_US
cg.coverage.iso3166-alpha2BRen_US
cg.coverage.regionLatin Americaen_US
cg.coverage.regionSouth Americaen_US
cg.identifier.doihttps://doi.org/10.1590/s0100-204x2013000200002en_US
cg.issn0100-204Xen_US
cg.issue2en_US
cg.journalPesquisa Agropecuária Brasileiraen_US
cg.subject.ccafsCLIMATE-SMART TECHNOLOGIES AND PRACTICESen_US
cg.volume48en_US
dc.contributor.authorBergamaschi Hen_US
dc.contributor.authorCosta, S.M.S. daen_US
dc.contributor.authorWheeler TRen_US
dc.contributor.authorChallinor, Andrew J.en_US
dc.date.accessioned2014-12-16T06:37:30Zen_US
dc.date.available2014-12-16T06:37:30Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/52070en_US
dc.titleSimulating maize yield in sub-tropical conditions of southern Brazil using Glam modelen_US
dcterms.abstractThe objective of this work was to evaluate the feasibility of simulating maize yield in a sub‑tropical region of southern Brazil using the general large area model (Glam). A 16‑year time series of daily weather data were used. The model was adjusted and tested as an alternative for simulating maize yield at small and large spatial scales. Simulated and observed grain yields were highly correlated (r above 0.8; p<0.01) at large scales (greater than 100,000 km2), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small spatial scales (lower than 10,000 km2). Large area models can contribute to monitoring or forecasting regional patterns of variability in maize production in the region, providing a basis for agricultural decision making, and Glam‑Maize is one of the alternatives.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.bibliographicCitationBergamaschi H, da Costa SMS, Wheeler TR, Challinor AJ. 2013. Simulating maize yield in sub-tropical conditions of southern Brazil using Glam model. Pesquisa Agropecuaria Brasileira: 48(2):132-140.en_US
dcterms.extentp. 132-140en_US
dcterms.issued2013-02en_US
dcterms.languageenen_US
dcterms.publisherFapUNIFESP (SciELO)en_US
dcterms.subjectclimateen_US
dcterms.subjectagricultureen_US
dcterms.subjectzea maysen_US
dcterms.subjectcrop modellingen_US
dcterms.typeJournal Articleen_US

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