Assessment of soil fertility variability for maize production in highland agroecosystems of Peru

• Autores: Garcia Seguil, Erika Janina, Ccopi Trucios, Dennis, Requena Rojas, Edilson Jimmy, Sanabria Quispe, Samuel, Arias Arredondo, Alberto Gilmer, Gavino Lulo, Esthefany Irene, Azabache, Andres, Pizarro Carcausto, Samuel Edwin
• Formato: artículo
• Fecha de Publicación: 2026
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.inia.gob.pe:20.500.12955/3167
• Enlace del recurso: http://hdl.handle.net/20.500.12955/3167; https://doi.org/10.12911/22998993/216243
• Nivel de acceso: acceso abierto
• Materia: Spatial variability; Variabilidad espacial; Random forest; Site-specific management; Manejo sitio-específico; Maize (Zea mays L.); Maíz (Zea mays L.); Soil fertility mapping; Mapeo de fertilidad del suelo; https://purl.org/pe-repo/ocde/ford#4.01.04; Soil fertility, Fertilidad del suelo; Phosphorus, Fósforo; Potassium, Potasio; Organic matter, Materia orgánica; Nitrogen, Nitrógeno; Geographical information systems, Sistemas de información geográfica.

Maize (Zea mays L.) is central to food, feed, and rural livelihoods, yet the yields in Peru’s highlands remain modest, underscoring the need for spatially explicit soil diagnostics. This study aimed to characterize the spatial variability of soil fertility in a highland maize production area of the southern Mantaro Valley and translate those patterns into site-specific management zones. The authors sampled the arable layer (0–30 cm) at 100 plots and analyzed pH, electrical conductivity, exchangeable acidity, texture, organic matter (OM), total nitrogen (N), available phosphorus (P), available potassium (K), exchangeable cations (Ca, Mg, Na, K), and calcium carbonate (CaCO₃). Laboratory data were integrated with environmental covariates using geostatistics, Random Forest, and GIS to generate high-resolution maps. Results showed uneven distributions in key attributes about 25% of the area with P deficiency, 15% with localized K shortages, and ~20% with OM < 2% while pH and CEC were comparatively stable. Random Forest achieved strong predictive performance for relatively stable properties (e.g., OM, pH, exchangeable cations), whereas mobile nutrients (available P, exchangeable K) were less predictable. The resulting products constitute the first high-resolution soil-fertility baseline for maize in the southern Mantaro Valley. The maps delineate fertilization management zones and provide a practical basis for preliminary rate recommendations that target constraints while avoiding surpluses. Future work will refine these zoned recommendations through yield-response trials, seasonal monitoring of mobile nutrients, and farmercentered decision-support tools, with the goal of improving nutrient-use efficiency, sustaining maize productivity, and reducing environmental risks across the valley.