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

• Optimal tree species improve coffee yields and soil fertility in these systems. • Shade cover (21–56% canopy) helps buffer climate and reduce pest incidence. • Random Forest and TOPSIS identified key species for each altitude. • Inga and Cedrela species boost coffee quality and ecosystem resilience. • Agroforestry systems support sustainable coffee production in the Amazon. 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/100g 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.

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Journal
Trees Forests and People
Published
2025-05-06
DOI
https://doi.org/10.1016/j.tfp.2025.100878
Citations
1
Primary Topic
Cocoa and Sweet Potato Agronomy
Type
article
Field-Weighted Citation Impact
2.74
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article

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

Gerson Meza-Mori, Elí Pariente, Lily Juarez-Contreras, Manuel Oliva et al.
1 citations
Trees Forests and People
Cocoa and Sweet Potato Agronomy
2.74
article

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

Gerson Meza-Mori, Elí Pariente, Lily Juarez-Contreras, Manuel Oliva, Helena Cruz, Elver Coronel-Castro, Nixon Haro, Jorge López, R. J. Garcı́a López
article en
1 citations

Abstract

• Optimal tree species improve coffee yields and soil fertility in these systems. • Shade cover (21–56% canopy) helps buffer climate and reduce pest incidence. • Random Forest and TOPSIS identified key species for each altitude. • Inga and Cedrela species boost coffee quality and ecosystem resilience. • Agroforestry systems support sustainable coffee production in the Amazon. 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/100g 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.

Trees Forests and PeopleVol. 20
National University Toribio Rodríguez de Mendoza (PE)
Zero hunger, Life in Land
Openalex Percentile: Top 13%
Cocoa and Sweet Potato Agronomy
2.74
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