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		<doi>10.1590/S0100-204X2013000200002</doi>
		<issn>0100-204X</issn>
		<label>lattes: 2921337850760630 2 BergamaschiCostWheeChal:2013:SiMaYi</label>
		<citationkey>BergamaschiCostWheeChal:2013:SiMaYi</citationkey>
		<title>Simulating maize yield in sub&#8209;tropical conditions of southern Brazil using Glam model / Simulação do rendimento de milho em condições subtropicais do Sul do Brasil por meio do modelo Glam</title>
		<year>2013</year>
		<month>Feb.</month>
		<typeofwork>journal article</typeofwork>
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		<author>Bergamaschi, Homero,</author>
		<author>Costa, Simone Marilene Sievert da,</author>
		<author>Wheeler, Timothy Robert,</author>
		<author>Challinor, Andrew Juan,</author>
		<group></group>
		<group>DSA-CPT-INPE-MCTI-GOV-BR</group>
		<affiliation>Universidade Federal do Rio Grande do Sul</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>University of Reading, PO Box 217, Reading RG6 6AH, UK.</affiliation>
		<affiliation>University of Leeds, Leeds LS2 9JT, UK.</affiliation>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress>simone.sievert@cptec.inpe.br</electronicmailaddress>
		<e-mailaddress>simone.sievert@cptec.inpe.br</e-mailaddress>
		<journal>Pesquisa Agropecuária Brasileira</journal>
		<volume>48</volume>
		<number>2</number>
		<pages>132-140</pages>
		<secondarymark>A2 A2 B1 B1 B1 B1 B1 B1 B1 B1 B1 B1 B2 B2 B2 B2 B2 B2 B3 B3 B3 B4 B4 B4 B5</secondarymark>
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		<keywords>Zea mays , crop modeling, crop parameters, crop, weather relationships., Zea mays , modelagem, parâmetros de cultivo, relações clima&#8209,,cultivo.</keywords>
		<abstract>The objective of this work was to evaluate the feasibility of simulating maize yield in a sub&#8209;tropical region of southern Brazil using the general large area model (Glam). A 16&#8209;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 km 2 ), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small spatial scales (lower than 10,000 km 2 ). 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&#8209;Maize is one of the alternatives. RESUMO: O objetivo deste trabalho foi avaliar a viabilidade de se estimar a produção de milho numa região subtropical do Sul do Brasil por meio do general large area model (Glam). Foi utilizada uma série de 16 anos de dados meteorológicos diários. O modelo foi ajustado e testado como alternativa para simular rendimentos de milho em pequena e grande escala espacial. Os rendimentos de milho simulados e observados estiveram altamente correlacionados (R acima de 0,8; p<0,01) em grande escala (mais de 100.000 km 2 ), e apresentaram correlações variáveis e geralmente inferiores (R de 0,65 a 0,87; p<0,1) em pequena escala (menos de 10.000 km 2 ). Modelos de grande escala podem contribuir para monitorar ou predizer padrões de variabilidade na produção de milho na região, o que fornece uma base para tomadas de decisão, e o Glam&#8209;Maize é uma alternativa.</abstract>
		<area>MET</area>
		<language>en</language>
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