South America, Set of agroclimatic indicators for the identification of abiotic stresses (Base of the subsetting tool)
South America, Set of agroclimatic indicators for the identification of abiotic stresses (Base of the subsetting tool)
Methodology: To carry out the calculation of these agroclimatic indicators, daily data of the following climatic variables were used at a resolution of 5 km: Maximum and minimum temperatures (source: CHIRTS), precipitation (source: CHIRPS), solar radiation (AGMERRA), data of soil (SoilGrids). The indicators were calculated for each month during a period of 33 years (1983 - 2016). With the above, the indicators were calculated per month during 1983 -2016 and finally, in order to summarize the calculated indicators, an aggregation of data was carried out, calculating the average in the following time periods: 1983 - 2016, 1990 - 2016, 1995 - 2016, 2000 – 2016, 2005 – 2016, 2010 – 2016
The purpose for which these indicators were created is to group or characterize the different accessions available in the Genesys database, considering climatic data from where they were collected. For the above, it is necessary to carry out a characterization of zones based on agroclimatic indicators, which are framed in evaluating the following stresses: Heat, Drought and Flooding, in addition to including indicators that capture the behavior of the photoperiod.
- CGIAR France
- CGIAR France
- CGIAR Consortium France
- CGIAR Consortium France
abiotic stress, Agricultural Sciences, solar radiation, evapotranspiration, temperature, drought, raster, precipitation, South America, agroclimatic indicators, Latin America and the Caribbean, soil, waterlogging, Climate Action, maximum temperature, climate change, flooding, climatic data, Cross Cutting - Data Science for Climate Action, Earth and Environmental Sciences, spatial data, heat, soils, minimum temperature
abiotic stress, Agricultural Sciences, solar radiation, evapotranspiration, temperature, drought, raster, precipitation, South America, agroclimatic indicators, Latin America and the Caribbean, soil, waterlogging, Climate Action, maximum temperature, climate change, flooding, climatic data, Cross Cutting - Data Science for Climate Action, Earth and Environmental Sciences, spatial data, heat, soils, minimum temperature
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