A Qualitative Dataset for Coffee Bio-Aggressors Detection Based on the Ancestral Knowledge of the Cauca Coffee Farmers in Colombia Valencia Mosquera, Juan Felipe Griol Barres, David Solarte Montoya, Mayra Figueroa, Cristhian Corrales, Juan Carlos Corrales, David Camilo Ancestral knowledge Coffee crops Coffee pest 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. 2024-04-19T09:35:44Z 2024-04-19T09:35:44Z 2023-12-08 journal article 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 https://hdl.handle.net/10481/90924 10.3390/data8120186 eng http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional MDPI