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		<isbn>85-17-00017-X</isbn>
		<citationkey>MeloFontBerl:2003:MoAgEs</citationkey>
		<title>Modelo agrometeorológico-espectral de estimativa de rendimento da soja para o Estado do Rio Grande do Sul</title>
		<format>CD-ROM, Online.</format>
		<year>2003</year>
		<secondarytype>CN</secondarytype>
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		<author>Melo, Ricardo Wanke de,</author>
		<author>Fontana, Denise Cybis,</author>
		<author>Berlato, Moacir Antonio,</author>
		<affiliation>Universidade Federal do Rio Grande do Sul (UFRGS). Faculdade de Agronomia.</affiliation>
		<affiliation>Universidade Federal do Rio Grande do Sul (UFRGS). Faculdade de Agronomia.</affiliation>
		<affiliation>Universidade Federal do Rio Grande do Sul (UFRGS). Faculdade de Agronomia.</affiliation>
		<editor>Epiphanio, José Carlos Neves,</editor>
		<editor>Fonseca, Leila Maria Garcia,</editor>
		<e-mailaddress>wanke@zipmail.com.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 11 (SBSR).</conferencename>
		<conferencelocation>Belo Horizonte</conferencelocation>
		<date>5-10 abr. 2003</date>
		<publisher>INPE</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>173-179</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais</organization>
		<transferableflag>1</transferableflag>
		<keywords>soybeans, crop yield estimation, NDVI, Rio Grande do Sul.</keywords>
		<abstract>The objective of this study was to fit and validate an agrometeorological-spectral model to estimate soybean yield in the State of Rio Grande do Sul, Brazil. The fitness was done using agrometeorological model (meteorological data from 1975 to 2000 of the seven weather stations located in the major soybean production region), spectral data (NDVI/NOAA images from 1982 to 2000) and soybean yield averaged over the State (official governmental statistics from 1975 to 2000). The parameters of the agrometeorological-spectral model were obtained through a linear multiple regression of the addition of agrometeorological term and spectral term. The model showed a good fit, with determination coefficient of 0,91. The model validation, done with independent data, had also a good performance, with determination coefficient of 0,88. The agrometeorological-spectral model produces the yield estimations before the end of the harvest with objectivity, swiftness and low cost, and could be incorporated into crop forecasting programs.</abstract>
		<area>SRE</area>
		<type>Agronomia / Agriculture</type>
		<language>pt</language>
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		<url>http://marte.sid.inpe.br/rep-/ltid.inpe.br/sbsr/2002/11.13.11.52</url>
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