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ORIGINAL RESEARCH article

Front. Soil Sci.

Sec. Soil Management

Soil spatial variability in high-yield Peruvian Amazon coffee: a geostatistical approach for precision fertilization

Provisionally accepted
Sharon  Mejia MaitaSharon Mejia Maita1Kenyi  QuispeKenyi Quispe2Henry  Díaz ChuquizutaHenry Díaz Chuquizuta2Raihil  Rengifo SanchézRaihil Rengifo Sanchéz2Ruth  Mercado ChinchayRuth Mercado Chinchay2Juan Pablo  Cuevas GimenezJuan Pablo Cuevas Gimenez2RICHARD  SOLÓRZANORICHARD SOLÓRZANO2*
  • 1Dirección de Desarrollo Tecnológico Agrario, Instituto Nacional de Innovación Agraria (INIA), Lima, Peru
  • 2Instituto Nacional de Innovacion Agraria, La Molina, Peru

The final, formatted version of the article will be published soon.

Fertilization practices in coffee plantations often overlook the spatial variability of soils, particularly in mountainous regions with acidic conditions. Although geostatistics has been used to map nutrient distributions, its integration with multivariate analysis to identify differentiated fertilization zones in coffee systems remains limited. This study evaluated the influence of soil properties, altitude, and crop age on coffee yield by combining principal component analysis (PCA) and ordinary kriging to design site-specific fertilization strategies. A total of 70 soil samples were collected from three districts of the Peruvian high jungle (San Martín and Amazonas), measuring physical and chemical properties, altitude, and crop age. The following analyses were applied: (1) Spearman correlations to assess associations with yield, (2) PCA to identify fertility gradients, and (3) geostatistical models with cross-validation. The PCA identified two main gradients: PC1 (32.41% of variance) associated with cation exchange capacity (CEC) and organic matter, and PC2 (17.88%) associated with the availability of K and P and crop age. Cross-validation confirmed high accuracy in the spatial prediction of available P and K across the three study areas. Kriging maps revealed zones with high available K (>150 mg kg⁻¹) and P (>20 mg kg⁻¹) associated with yields >1.5 t ha⁻¹. The integration of PCA and geostatistics enabled the delineation of management zones with differentiated nutrient requirements, reducing fertilization needs by up to 30% in areas with high fertility potential (e.g., Alto Saposoa). Overall, the results provide a solid methodological basis for implementing precision fertilization strategies in tropical coffee systems, promoting more efficient nutrient use and greater production sustainability.

Keywords: precision agriculture, Soil zoning, Coffee yield, applied geostatistics, soil fertility

Received: 09 Sep 2025; Accepted: 26 Nov 2025.

Copyright: © 2025 Mejia Maita, Quispe, Díaz Chuquizuta, Rengifo Sanchéz, Mercado Chinchay, Cuevas Gimenez and SOLÓRZANO. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: RICHARD SOLÓRZANO

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