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| Seffrin, Rodolfo; Araújo, Everton Coimbra De; Bazzi, Claudio Leones. |
| This study aimed to identify areas that showed spatial autocorrelation for corn yield and its predictive variables (i.e., average air temperature, rainfall, solar radiation, soil agricultural potential and altitude) and to determine the most appropriate spatial regression model to explain this culture. The study was conducted using data from the municipalities of the state of Paraná relating to the summer harvests in 2011/2012, 2012/2013, and 2013/2014. The statistical diagnostic of the OLS (Ordinary Least Square regression model) was employed to determine the most suitable regression model to predict corn yield. The SAR (Spatial Lag Model) was recommended for all crop years; however, the Spatial Error Model (CAR) was recommended only for the 2013/2014... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Autoregressive spatial model; Moran’s index; Spatial autocorrelation; Spatial error model; Spatial regression.; Produção de Cultura; Geomática. |
| Ano: 2018 |
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/36494 |
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| Seffrin, Rodolfo; Araújo, Everton Coimbra De; Bazzi, Claudio Leones. |
| This study aimed to identify areas that showed spatial autocorrelation for corn yield and its predictive variables (i.e., average air temperature, rainfall, solar radiation, soil agricultural potential and altitude) and to determine the most appropriate spatial regression model to explain this culture. The study was conducted using data from the municipalities of the state of Paraná relating to the summer harvests in 2011/2012, 2012/2013, and 2013/2014. The statistical diagnostic of the OLS (Ordinary Least Square regression model) was employed to determine the most suitable regression model to predict corn yield. The SAR (Spatial Lag Model) was recommended for all crop years; however, the Spatial Error Model (CAR) was recommended only for the 2013/2014... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Produção de Cultura; Geomática autoregressive spatial model; Moran’s index; Spatial autocorrelation; Spatial error model; Spatial regression. Produção de Cultura; Geomática. |
| Ano: 2018 |
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/36494 |
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| Michelon, Gabriela Karoline; de Menezes, Paulo Lopes; Júnior, Arnaldo Cândido; Bazzi, Claudio Leones; Barbosa, Marcela Marques. |
| Soybean is one of the major oleaginous, used for food and feed to processed products and also as an alternative source of biofuel. Due to its great uses that is highly valued and cultivated in the world. Therefore, this study sought to apply an artificial intelligence technique to predict soybean yield and therefore maximize production from farmlands, increase the profit of the producer and reduce environmental impacts. There were then used the support vector machine technique, to find a prediction model of soybean yield from the leaf nutrients, allowing therefore that fertilization is carried out only in necessary locations predicted as low productivity points for best support vector machine model obtained. Among all created models, the best prediction of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Agricultura de Precisão Inteligência Artificial; Nutrientes Foliares; Regressão. |
| Ano: 2017 |
URL: http://www.seer.ufv.br/seer/index.php/reveng/article/view/745 |
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