A Qualitative Dataset for Coffee Bio-Aggressors Detection Based on the Ancestral Knowledge of the Cauca Coffee Farmers in Colombia
Metadatos
Afficher la notice complèteAuteur
Valencia Mosquera, Juan Felipe; Griol Barres, David; Solarte Montoya, Mayra; Figueroa, Cristhian; Corrales, Juan Carlos; Corrales, David CamiloEditorial
MDPI
Materia
Ancestral knowledge Coffee crops Coffee pest
Date
2023-12-08Referencia bibliográfica
Valencia-Mosquera, J.F.; Griol, D.; Solarte-Montoya, M.; Figueroa, C.; Corrales, J.C.; Corrales, D.C. A Qualitative Dataset for Coffee Bio-Aggressors Detection Based on the Ancestral Knowledge of the Cauca Coffee Farmers in Colombia. Data 2023, 8, 186. https://doi.org/10.3390/data8120186
Patrocinador
Call 823—High-level training human capital for the regions of Cauca; Ministry of Science, Technology and Innovation (MinCiencias); General Royalties System (SGR), code BPIN 2020000100098Résumé
This paper describes a novel qualitative dataset regarding coffee pests based on the
ancestral knowledge of coffee farmers in the Department of Cauca, Colombia. The dataset has
been obtained from a survey applied to coffee growers with 432 records and 41 variables collected
weekly from September 2020 to August 2021. The qualitative dataset includes climatic conditions,
productive activities, external conditions, and coffee bio-aggressors. This dataset allows researchers
to find patterns for coffee crop protection through the ancestral knowledge not detected by real-time
agricultural sensors. As far as we are concerned, there are no datasets like the one presented in this
paper with similar characteristics of qualitative value that express the empirical knowledge of coffee
farmers used to detect triggers of causal behaviors of pests and diseases in coffee crops.