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

International Potato Center Dataverse OAI Archive

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Title Dataset for: Data mining to predict late blight resistance (susceptible, moderately resistant, resistant) using learning methods and climatic layers
 
Identifier https://doi.org/10.21223/HOUFZD
 
Creator Juarez, Henry
Perez, Willmer
Andrade-Piedra, Jorge
 
Publisher International Potato Center
 
Description 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 (https://doi.org/10.21223/P3/NGX3BJ, https://doi.org/10.21223/P3/HKABUV, https://doi.org/10.21223/2NYJIT, https://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.
 
Subject Agricultural Sciences
Computer and Information Science
Late blight
Data mining
Bioclimatology
 
Language English
 
Contributor Administrator, CIP
International Potato Center
CGIAR Research Program on Roots, Tubers and Bananas (RTB)