Standardization of tree species in agroforestry systems of Coffea arabica L. at different altitudes in Amazonas, Peru

Abstract

Coffee is a key crop for the Peruvian economy, and agroforestry systems (AFS) have been promoted as a sustainable strategy for its production. However, the selection of optimal tree species remains a challenge. This study evaluated the impact of different tree species on coffee productivity, sensory quality and edaphic properties in AFS with Coffea arabica L. in the Amazon region, Peru. The research was carried out in three altitudinal levels: low (1200–1500 masl), intermedium (1500–1800 masl) and high (>1800 masl), in plots located in Lonya Grande, Rodriguez de Mendoza, Camporredondo and Pisuquia. Thirty-one species were analyzed in terms of canopy cover provided, pest incidence (Hemileia vastatrix and Hypothenemus hampei), soil characteristics (pH, N, P, K, C) organic matter (O.M), cation exchange capacity (C. E. C), electrical conductivity (E. C) and coffee yield. For the analysis, Random Forest was used to determine the importance of the variables, followed by the TOPSIS method to prioritize the most suitable species at each altitude. At low altitudes, Mespilodaphne quixos and Psidium guajava presented canopy cover of 21 % and 35 %, pH of 6.04 and 5.56, and yields above 80 %. At intermedium altitude, Inga densiflora stood out with 52 % canopy cover, C.E.C of 32 meq/100 g and a yield of 83.25 %. At high altitudes, Inga edulis and Cedrela fissilis provided average canopy cover of 40 % and 56 %, respectively. These species were also associated with soil carbon content above 3 % and cup scores above 82 points. The results ort the identification of key tree species for the implementation of sustainable coffee agroforestry systems, contributing to improve productivity and ecosystem conservation in the Amazon region.