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Zoning of agroclimatic and productive areas for quinoa (Chenopodium quinoa Willd.) in Peru; an integration of F-AHP, TOPSIS, and GIS

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Abstract

Quinoa (Chenopodium quinoa Willd.) is an Andean crop of high nutritional value that is resistant to adverse climatic conditions. However, its sustainable expansion in Peru faces limitations due to the lack of detailed spatial information on areas suitable for cultivation, especially under climate change scenarios. The objective of this study was to define the agroclimatic and productive zones suitable for quinoa cultivation in Peru, taking into account current conditions (1970–2000) and projected climate change scenarios (2041–2060 and 2081–2100). Multicriteria evaluation techniques were integrated using the Fuzzy analytic hierarchy process (F-AHP) method to weight the criteria and the technique of Order of Preference by Similarity to the ideal Solution (TOPSIS) to classify the alternatives in a Geographic Information System (GIS) environment. Future projections were assessed under Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5). The results indicated that 45.71% of the national territory is marginally suitable and 10.95% is moderately suitable. Under future scenarios (SSP2-4.5 and SSP5-8.5), a slight reduction in marginal areas and an increase in moderately suitable and highly suitable areas are projected, especially towards the end of the period 2081–2100. For the SSP5-8.5 scenario, highly suitable areas could increase to 1.09% of the territory and moderately suitable areas to 14.08%. These results show a spatial redistribution of suitability, highlighting the need for adaptive agricultural policies, climate resilient planning strategies, and targeted territorial management to support sustainable quinoa expansion in Peru.

Data availability

The datasets generated and analysed during this study are not currently in a public repository due to institutional restrictions, but are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors would like to thank the anonymous reviewers and the editor for their invaluable comments for improving the quality of the manuscript. We are grateful to USGS for providing free-of-cost satellite imagery.

Funding

This research was funded by the Public Investment Project “Creation of a Geomatics and Remote Sensing Laboratory of the National University Toribio Rodríguez of Mendoza of Amazonas” GEOMATICA, (CUI N° 2255626). The APC was funded by the Vice-Rectorate for Research of the Universidad Nacional del Amazonas Toribio Rodríguez de Mendoza de Amazonas.

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  1. Instituto de Investigación Para El Desarrollo Sustentable de Ceja de Selva (INDES-CES), Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas, Chachapoyas, 01001, Perú

    Katerin M. Tuesta-Trauco, Angel J. Medina-Medina, Jhon A. Zabaleta-Santisteban, Abner S. Rivera-Fernandez, José A. Sánchez-Vega, Teodoro B. Silva-Melendez, Marlen A. Grandez-Alberca, Cecibel Portocarrero, Rolando Salas López, Lily Juarez-Contreras, Samuel Pizarro, Manuel Oliva Cruz & Elgar Barboza

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  1. Katerin M. Tuesta-Trauco
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Contributions

KMT-T., J.A.Z-S. y E.B. Concepción y diseño de trabajo; KMT-T., J.A.Z-S. y RSL Recolección de datos; E.B. Adquisición de financiación; KMT-T., AJM-M., JAZ-S., ASR-F., JAS-V., T.B.S-M., M.A.G-A., L.J., RSL. y SP. Investigación; KMT-T., E.B., JAZ-S., AJM-M. y M.O-C; Metodología; E.B., C.P. y L.J-C.; Administración de proyectos; KMT-T., E.B. y M.O-C; Manejo de Recursos; KMT-T., JAZ-S., AJM-M., ASR-F., JAS-V., T.B.S-M. y M.A.G-A. Desarrollo de Software, E.B y S.C. Supervisión de datos; KMT-T., JAZ-S., ASR-F. y JAS-V. Validación; E. B, AJM-M., ASR-F., JAS-V., T.B.S-M. y M.A.G-A. Visualización; KMT-T., EB y AJM-M. Redacción del borrador original; EB, JAZ-S., AJM-M., ASR-F., JAS-V., T.B.S-M. y M.A.G-A. Redacción de la revisión y edición. Todos los autores revisaron el manuscrito.

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Tuesta-Trauco, K.M., Medina-Medina, A.J., Zabaleta-Santisteban, J.A. et al. Zoning of agroclimatic and productive areas for quinoa (Chenopodium quinoa Willd.) in Peru; an integration of F-AHP, TOPSIS, and GIS.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-46995-9

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Keywords

  • Sustainable agriculture
  • Agroclimatic adaptability
  • Crop suitability
  • Multi-criteria assessment
  • Peruvian andes
  • Spatial modeling

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