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

cg.contributor.crpClimate Change, Agriculture and Food Security
cg.coverage.countryBrazil
cg.coverage.iso3166-alpha2BR
cg.coverage.regionLatin America
cg.coverage.regionSouth America
cg.identifier.doihttps://doi.org/10.1590/s0100-204x2013000200002en
cg.issn0100-204Xen
cg.issue2en
cg.journalPesquisa Agropecuária Brasileiraen
cg.subject.ccafsCLIMATE-SMART TECHNOLOGIES AND PRACTICESen
cg.volume48en
dc.contributor.authorBergamaschi Hen
dc.contributor.authorCosta, S.M.S. daen
dc.contributor.authorWheeler TRen
dc.contributor.authorChallinor, Andrew J.en
dc.date.accessioned2014-12-16T06:37:30Zen
dc.date.available2014-12-16T06:37:30Zen
dc.identifier.urihttps://hdl.handle.net/10568/52070
dc.titleSimulating maize yield in sub-tropical conditions of southern Brazil using Glam modelen
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
dcterms.accessRightsOpen Access
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
dcterms.extentp. 132-140en
dcterms.issued2013-02
dcterms.languageen
dcterms.publisherFapUNIFESPen
dcterms.subjectclimateen
dcterms.subjectagricultureen
dcterms.subjectzea maysen
dcterms.subjectcrop modellingen
dcterms.typeJournal Article

Files