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dc.creatorSarmiento, Christiany Mattioli-
dc.creatorColtri, Priscila Pereira-
dc.creatorAlves, Marcelo de Carvalho-
dc.creatorCarvalho, Luiz Gonsaga de-
dc.identifier.citationSARMIENTO, C. M. et al. A spectral agrometeorological model for estimating soybean grain productivity in Mato Grosso, Brazil. Engenharia Agrícola, Jaboticabal, v. 40, n. 3, p. 405-412, mai./jun. 2020. DOI:
dc.description.abstractThis study used spectral data integrated with the agrometeorological model by Doorenbos and Kassam to estimate soybean grain productivity in the state of Mato Grosso, Brazil. In the developed model, spectral data were used instead of meteorological data and biophysical parameters of the crop. For this purpose, the products of real and potential evapotranspiration (MOD16), normalized difference vegetation index – NDVI (MOD13Q1), and leaf area index (MOD15A2H) from the MODIS satellite were used, in addition to sunstroke data obtained by using the visible channel from the satellite GOES IMAGER. The results obtained showed that, with the proposed methodology, it was possible to follow the development of soybean cultivation throughout the cycle and to estimate production and productivity in the study area. Willmott's agreement index was 0.99 and 0.96 and Pearson's correlation coefficient was 0.99 and 0.84 for production and productivity, respectively.pt_BR
dc.publisherAssociação Brasileira de Engenharia Agrícolapt_BR
dc.rightsacesso abertopt_BR
dc.sourceEngenharia Agrícolapt_BR
dc.subjectGeographic information systempt_BR
dc.subjectMathematical modelingpt_BR
dc.subjectRemote sensingpt_BR
dc.subjectCrop monitoringpt_BR
dc.subjectSistema de informação geográficapt_BR
dc.subjectModelagem matemáticapt_BR
dc.subjectSensoriamento remotopt_BR
dc.subjectMonitoramento de safrapt_BR
dc.subjectSoja - Produtividadept_BR
dc.titleA spectral agrometeorological model for estimating soybean grain productivity in Mato Grosso, Brazilpt_BR
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