Neural networks in climate spatialization and their application in the agricultural zoning of climate risk for sunflower in different sowing dates

2019 ◽  
Vol 65 (11) ◽  
pp. 1477-1492
Author(s):  
Lucas Eduardo de Oliveira Aparecido ◽  
José Reinaldo da Silva Cabral de Moraes ◽  
Glauco de Souza Rolim ◽  
Lucieta Guerreiro Martorano ◽  
Kamila Cunha de Meneses ◽  
...  
2018 ◽  
Vol 62 (11) ◽  
pp. 1955-1962
Author(s):  
Lucas Eduardo de Oliveira Aparecido ◽  
José Reinaldo da Silva Cabral de Moraes ◽  
Glauco de Souza Rolim ◽  
Lucieta Guerreiro Martorano ◽  
Sabrina dos Santos Soares ◽  
...  

Author(s):  
Lucas Eduardo de Oliveira Aparecido ◽  
Rafael Madureira Batista ◽  
José Reinaldo da Silva Cabral de Moraes ◽  
Cícero Teixeira Silva Costa ◽  
Adriana Ferreira de Moraes-Oliveira

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 peruviana. The Southeastern region of Brazil showed a thermal variation from 16.5 to 22.6°C and water amplitude from 800 to 2,800 mm. ZARC shows that 10% of Southeastern Brazil is climatically apt for the cultivation of Physalis peruviana, corresponding to the following regions of Brazilian states: central and southern Minas Gerais, western Rio de Janeiro and Espírito Santo, and eastern and southern São Paulo.


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