Examinando por Autor "Garcia Seguil, Erika Janina"

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Assessment of soil fertility variability for maize production in highland agroecosystems of Peru
(Polish Society of Ecological Engineering (PTIE), 2026-04-01) 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
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.
Moderate deficit irrigation improves agronomic performance of quinoa (Chenopodium quinoa Willd.) compared to full irrigation in the central highlands of Peru
(Learning Gate, 2026-03-19) Gavino Lulo, Esthefany Irene; Ccopi Trucios, Dennis; Garcia Seguil, Erika Janina; Requena Rojas, Edilson Jimmy; Contreras, Jose; Solórzano Acosta, Richard Andi; Betega, S.D.; Yaranga, Raúl M.; Pizarro Carcausto, Samuel Edwin
This study evaluated the agronomic performance and water productivity of quinoa (Chenopodium quinoa Willd. cv. INIA 433) under three irrigation regimes in the central highlands of Peru: optimal irrigation (Ks = 1.00), moderate deficit (Ks = 0.66), and severe deficit (Ks = 0.49). The experiment combined constant water table lysimeters and field plots, integrating crop coefficient estimation, water balance analysis, and multispectral monitoring (NDVI, NDRE, SRWI) using UAV imagery and ground spectroradiometry. Moderate water stress (Ks = 0.66) significantly improved reproductive performance, producing approximately 8,000 grains per plant compared with ~3,900 grains per plant under optimal irrigation. Grain protein content increased from 4.8% to 6.0%, while evapotranspiration decreased by 37% (from 374.5 to 234.4 mm), markedly improving water use efficiency. In contrast, optimal irrigation promoted maximum vegetative growth (plant height ~110 cm; NDVI 0.7–0.8) but lower reproductive output, whereas severe stress (Ks = 0.49) reduced yield to 4,400 grains per plant and accelerated senescence. Multispectral indices effectively distinguished water stress levels: NDVI reflected canopy vigor, NDRE detected chlorophyll variation, and SRWI captured plant water status. The results demonstrate that regulated deficit irrigation enhances water productivity and grain quality in quinoa. Maintaining Ks values around 0.65–0.70 appears to optimize yield and resource use efficiency in water-limited Andean agroecosystems.