1 to 3 of 3 Results
7 mai 2020
Bagny Beilhe Leïla; Roudine Sacha; Quintero Perez Jose Alcides; Allinne Clementine; Daout Djavan Daout; Mauxion Rémi; Carval Dominique, 2020, "Raw data: Bagny Beilhe et al 2020: "Pest-regulating networks of the coffee berry borer (Hypothenemus hampei) in agroforestry systems. Crop Protection, 131 : 10 p."", https://doi.org/10.18167/DVN1/QVTOBA, CIRAD Dataverse, V1, UNF:6:2df1/ylVi4QJtHRD+i5t6A== [fileUNF]
Données collectées à La Dalia, Nicaragua, de 2017 à 2018. Données issues de 3 systèmes agroforestiers à base de caféiers avec des niveaux de diversification végétale différents et trois types de pratiques (conventionnelles, durables et organiques). Dans chaque ferme 20 parcelles... |
5 nov. 2018
Jacques Avelino, 2018, "Raw data on coffee tree pests and diseases from surveys conducted in Costa Rica", https://doi.org/10.18167/DVN1/KUMGSQ, CIRAD Dataverse, V1
Dataset aiming at understanding the relationships between coffee pests and diseases, crop management, environment (including soil), and coffee tree characteristics from a two year survey conducted in Costa Rica at national level in 2002 and 2003 |
14 juin 2018
Babin, Régis, 2018, "Raw data for Azrag et al., 2018. PlosOne. Prediction of insect pest distribution as influenced by elevation: combining field observations and temperature-dependent development models for the coffee stink bug, Antestiopsis thunbergii (Gmelin).", https://doi.org/10.18167/DVN1/WQFFPV, CIRAD Dataverse, V1, UNF:6:3jkEQqVpgYCVboPZoccQSw== [fileUNF]
Raw data for Azrag et a., 2018. PlosOne. Prediction of insect pest distribution as influenced by elevation: combining field observations and temperature-dependent development models for the coffee stink bug, Antestiopsis thunbergii (Gmelin) |