This document is a novel qualitative dataset for coffee pest detection based on
the ancestral knowledge of coffee growers of the Department of Cauca, Colombia. Data has been
obtained from survey applied to coffee growers of the association of agricultural producers of
Cajibio – ASPROACA (Asociación de productores agropecuarios de Cajibio). The dataset contains
a total of 432 records and 41 variables collected weekly during September 2020 - August 2021.
The qualitative dataset consists of weather conditions (temperature and rainfall intensity),
productive activities (e.g., biopesticides control, polyculture, ancestral knowledge, crop phenology,
zoqueo, productive arrangement and intercropping), external conditions (animals close to the crop
and water sources) and coffee bioaggressors (e.g., brown-eye spot, coffee berry borer, etc.). This
dataset can provide to researchers the opportunity to find patterns for coffee crop protection from
ancestral knowledge not detected for real-time agricultural sensors (meteorological stations, crop
drone images, etc.). So far, there has not been found a set of data with similar characteristics of
qualitative value expresses the empirical knowledge of coffee growers used to see causal
behaviors of trigger pests and diseases in coffee crops. 

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license: cc-by-4.0
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region:us
{}
TAGS
#region-us 

This document is a novel qualitative dataset for coffee pest detection based on
the ancestral knowledge of coffee growers of the Department of Cauca, Colombia. Data has been
obtained from survey applied to coffee growers of the association of agricultural producers of
Cajibio – ASPROACA (Asociación de productores agropecuarios de Cajibio). The dataset contains
a total of 432 records and 41 variables collected weekly during September 2020 - August 2021.
The qualitative dataset consists of weather conditions (temperature and rainfall intensity),
productive activities (e.g., biopesticides control, polyculture, ancestral knowledge, crop phenology,
zoqueo, productive arrangement and intercropping), external conditions (animals close to the crop
and water sources) and coffee bioaggressors (e.g., brown-eye spot, coffee berry borer, etc.). This
dataset can provide to researchers the opportunity to find patterns for coffee crop protection from
ancestral knowledge not detected for real-time agricultural sensors (meteorological stations, crop
drone images, etc.). So far, there has not been found a set of data with similar characteristics of
qualitative value expresses the empirical knowledge of coffee growers used to see causal
behaviors of trigger pests and diseases in coffee crops. 

---
license: cc-by-4.0
---

TAGS
#region-us 

passage: TAGS
#region-us 
