Dataset for: Data mining to predict late blight resistance (susceptible, moderately resistant, resistant) using learning methods and climatic layers
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. 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' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Bioclimatology","Data mining","Late blight"]} <|eot_id|>
 Here is the Description of a dataset. 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' . Please return only a json list of at most 3 Keywords corresponding to the 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
Bioclimatology; Data mining; Late blight