|
|
|
|
|
| Aparecido,Lucas Eduardo de Oliveira; Batista,Rafael Madureira; Moraes,José Reinaldo da Silva Cabral de; Costa,Cícero Teixeira Silva; Moraes-Oliveira,Adriana Ferreira de. |
| Abstract: The objective of this work was to elaborate the agricultural zoning of climatic risk (ZARC) for Physalis peruviana, through the thermal and water requirements of the crop in Southeastern Brazil. Air temperature (TAIR) and precipitation (PYEAR) data from 1,530 meteorological stations covering the entire region were used. Regions were considered climatically favorable to Physalis peruviana when TAIR was between 13 and 18ºC and PYEAR between 1,000 and 2,000 mm per year. Regions where TAIR was above 30ºC or less than 13ºC were considered inapt. Maps were created with this information and used to identify climatic characteristics and to establish the agricultural aptitude classes, termed apt, inapt, and marginal for the cultivation of Physalis... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Climate risk; Agrometeorology; Modeling; Big data. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2019000100900 |
| |
|
|
| Moraes-Oliveira,Adriana Ferreira de; Aparecido,Lucas Eduardo de Oliveira; Figueira,Sérgio Rangel Fernandes. |
| Abstract: The objective of this work was to estimate the coffee supply by calibrating statistical models with economic and climatic variables for the main producing regions of the state of São Paulo, Brazil. The regions were Batatais, Caconde, Cássia dos Coqueiros, Cristais Paulista, Espírito Santo do Pinhal, Marília, Mococa, and Osvaldo Cruz. Data on coffee supply, economic variables (rural credit, rural agricultural credit, and production value), and climatic variables (air temperature, rainfall, potential evapotranspiration, water deficit, and water surplus) for each region, during the period from 2000-2014, were used. The models were calibrated using multiple linear regression, and all possible combinations were tested for selecting the variables.... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Coffea arabica; Climate; Econometrics; Modelling; Rural credit. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2017001201158 |
| |
|
|
|
