Data for: "The Dark side of shade: How microclimates drive the epidemiological mechanisms of coffee berry disease"
Data of coffee berry disease (CBD) dynamics and of microclimates, collected over two consecutive years (2012-2013) on a smallholding coffee farm in Bamendjou in West Cameroon (5°24′0″N; 10°19′0″E, alt. 1600m), were used to assess the effect of shade and full sun on CBD epidemiological processes. For this purpose we developed a mechanistic SEIR model, and we inferred, within a Bayesian framework, the epidemiological parameters against microclimatic covariates. We computed the Bayesian joint posterior distribution for inference of parameters via a Markov chain Monte Carlo (MCMC) algorithm using JAGS software (Plummer, 2017) and the package MecaStat (Rey et al., 2018).
Saved in:
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Dataset biblioteca |
| Language: | French |
| Published: |
CIRAD Dataverse
|
| Subjects: | Agricultural Sciences, Earth and Environmental Sciences, Mathematical Sciences, Coffea arabica, Colletotrichum kahawae, agroforestry systems, Susceptible - Exposed - Infectious - Removed (SEIR) model, mechanistic-statistical approach, Bayesian inference, |
| Online Access: | https://doi.org/10.18167/DVN1/KP76RE |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|