首页|Reports Summarize Machine Learning Findings from Federal University of Mato Gros so do Sul (UFMS) (Classification of Soybean Groups for Grain Yield and Industria l Traits Using Vnir-swir Spectroscopy)
Reports Summarize Machine Learning Findings from Federal University of Mato Gros so do Sul (UFMS) (Classification of Soybean Groups for Grain Yield and Industria l Traits Using Vnir-swir Spectroscopy)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Machine Learning have been presented. According to news reporting originating in Chapadao do Sul, Bra zil, by NewsRx journalists, research stated, "This research aimed to evaluate th e accuracy of machine learning techniques in distinguishing groups soybean genot ypes according to grain industrial traits using hyperspectral reflectance of the leaves. A total of 32 soybean genotypes were evaluated and allocated in randomi zed blocks with four replications." Financial supporters for this research include Universidade Federal de Mato Gros so do Sul (UFMS), Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ), Fundacao de Apoio ao Desenvolvimento do Ensino Ciencia e Tecnologia do E stado de Mato Grosso do Sul (FUNDECT MS), Coordenacao de Aperfeicoamento de Pess oal de Nivel Superior (CAPES).
Chapadao do SulBrazilSouth AmericaCyborgsEmerging TechnologiesGeneticsMachine LearningFederal University o f Mato Grosso do Sul (UFMS)
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