Dataset for: Data mining to predict late blight resistance (susceptible, moderately resistant, resistant) using learning methods and climatic layers

This dataset includes information of late blight severity readings under greenhouse conditions (experiments carried out in CIP-Lima during 2019-2021) from the following datasets (doi.org/10.21223/P3/NGX3BJ, doi.org/10.21223/P3/HKABUV, doi.org/10.21223/2NYJIT, doi.org/10.21223/66XOT9). A total of 384 records (76% of total records) with correct geographic coordinates were used for mapping and data mining.

Records were annotated using global grids at 2.5 min resolution from the world climate database (Fick and Hijmans, 2017). We assessed 19 bioclimatic variables (annual temperature, monthly temperature range, isothermality, temperature seasonality, maximum temperature of warmest month, minimum temperature of coldest month, temperature annual range, temperature of wettest quarter, temperature of driest quarter, temperature of warmest quarter, temperature of coldest quarter, annual precipitation, precipitation of wettest month, precipitation of driest month, precipitation seasonality, precipitation of wettest quarter, precipitation of driest quarter, precipitation of warmest quarter, precipitation of coldest quarter) and also assessed altitude as a 20th variable.