Examinando por Autor "Fernandez Jibaja, Jorge Antonio"

Mostrando 1 - 4 de 4

Integration of agronomic information, vegetation indices (VIs), and meteorological data for phenological monitoring and yield estimation of rice (Oryza sativa L.)
(Elsevier, 2025-07-15) Fernandez Jibaja, Jorge Antonio; Atalaya Marin, Nilton; Álvarez Robledo, Yeltsin Abel; Taboada Mitma, Víctor Hugo; Cruz Luis, Juancarlos Alejandro; Tineo Flores, Daniel; Goñas Goñas, Malluri; Gómez Fernández, Darwin
Rice (Oryza sativa L.) is a staple crop for sustaining global food security and is particularly important in tropical and subtropical regions. In this context, precision agriculture enables more efficient crop management to increase productivity and sustainability. This study proposes an integrated framework for monitoring the phenological development and estimating the yield of O. sativa by combining agronomic variables, vegetation indices (VIs), and meteorological data. Six rice varieties (Victoria, Esperanza, Bellavista, Puntilla, Capoteña, and Valor) were evaluated across six phenological stages using field data, 20 VIs and meteorological parameters. Field data revealed greater tillering of the Puntilla and Valor varieties (9–28 tillers), with Esperanza having the most stable chlorophyll values (21.5–38.7, σ = 10.46) during ripening. The temporal dynamics of the VIs consistently increased from the seedling to inflorescence emergence stage, followed by a decrease during flowering and ripening, which aligns with known physiological transitions in rice; however, significant differences in the NDVI index were detected during ripening (p > 0.05). For yield estimation, feature selection was performed using principal component analysis (PCA) and the least absolute shrinkage and selection operator (LASSO) to increase model efficiency and interpretability. Among the regression algorithms tested, support vector regression (SVR) demonstrated the highest predictive accuracy (R² = 0.81) for the Bellavista variety at the maximum tillering stage. Furthermore, the Valor variety presented the highest grain yield (13.70 t/ha). These results underscore the potential of integrating multisource data with machine learning techniques for high-resolution phenological monitoring and varietal performance assessment.
Occurrence, sources, and ecological risk of polycyclic aromatic hydrocarbons (PAHs) in rice field soils of northwestern Peru
(Elsevier B.V., 2026-02-04) Culqui Gaslac, Cristian; Tineo Flores, Daniel; Fernandez Jibaja, Jorge Antonio; Alvarez Robledo, Yeltsin Abel; Garcia Frias, Larry Dustin; Mendoza Merino, Jani Elisabet; Taboada Mitma, Víctor Hugo; Cruz Luis, Juancarlos Alejandro; Rojas Briceño, Nilton B.; García, Ligia; Zirena Vilca, Franz; Goñas Goñas, Malluri
Polycyclic aromatic hydrocarbons (PAHs) are organic contaminants that pose significant risks to human health and ecosystems. This study investigated the occurrence, sources, and ecological risks of PAHs in rice paddy soils from northwestern Peru. Ninety-seven soil samples were collected at a depth of 30 cm across three altitudinal zones, four phenological stages, and two agronomic management practices. Quantification was performed using ultra-high-performance liquid chromatography coupled with fluorescence detection (UHPLC-FLD). Source apportionment was conducted through rotated principal component analysis combined with multiple linear regression. Ecological risk was assessed using organic carbon normalization and the mean effects range-median quotient (M-ERM-Q) method, while carcinogenic potential was estimated using the toxic equivalent factor (TEQCARC). Total PAHs ranged from 22.02 to 130.55 ng g⁻¹ (mean: 55.26 ng g⁻¹); LMW PAHs averaged 37.38 ng g⁻¹, exceeding HMW PAHs (17.88 ng g⁻¹). No significant differences were observed among altitudinal zones, phenological stages or agronomic practices (p > 0.05). The predominant sources of PAHs were attributed to vehicular emissions (52.3%), petroleum and biomass combustion (42.1%), and coal combustion (5.4%). Ecological risk assessment revealed low contamination levels below established safety thresholds (CEC <290 μg g⁻¹), consistent with the carcinogenic risk estimated through TEQCARC (0.0083 to 18.7483 ng BaPeq g⁻¹). This study provides the first comprehensive evaluation of PAHs contamination in rice paddy soils in Peru and underscores the influence of altitude and agricultural practices, emphasizing the need for further research on pollution sources, impacts on crop productivity, and potential risks to human health.
Sustainability of coffee farms: Case study of the cooperativa agraria cafetalera La Prosperidad de Chirinos
(Universe Scientific Publishing, 2025-12-29) Fernández Zarate, Franklin Hitler; Goñas Goñas, Malluri; Oblitas Juarez, Jhon; Fernandez Jibaja, Jorge Antonio; Gomez Fernandez, Darwin; García Chimbo, Nilter; Montalvan, Michael; Quiñonez Huatangari, Lenin; Acosta Jacinto, Rubén Eusebio; Ríos Julcapoma, Milton; Guardia, Guillermo; Sanz Cobeña, Alberto
Ignorance of the sustainability of coffee systems compromises the continuity of productive activities by weakening their economic viability, environmental integrity and social cohesion over time, which is why it is essential to carry out diagnoses. This study aimed to assess the sustainability level of coffee farms associated with the Cooperativa Agraria Cafetalera La Prosperidad de Chirinos. From January to March 2024, data were collected from 60 farms out of a population of 788. The analysis was based on nine criteria: six environmental (soil quality, crop health, solid waste and effluent management, integrated pest and disease management, ecological knowledge, and agricultural system), two economic (agricultural economy and food sovereignty), and one social (social aspects). To identify groups of farmers with homogeneous characteristics, a cluster analysis was performed and the level of sustainability of each group was determined by calculating overall averages, represented through Amoeba charts. Results identified two farm types farms in group 1 showed less sustainability than group 2, mainly due to unfavorable conditions related to soil quality. Consequently, it is recommended to implement cover crops, live barriers, infiltration ditches, contour planting, and productive diversification for food security are recommended. This study provides a scientific diagnosis of sustainability levels on coffee farms and offers practical options for improving sustainability.
Territorial zoning as a strategy for sustainable natural resource management in Cajamarca, Northwestern Peru
(Elsevier B.V., 2025-09-25) Gómez Fernández, Darwin; Atalaya Marin, Nilton; Arce Inga, Marielita; Tineo Flores, Daniel; Fernandez Jibaja, Jorge Antonio; Taboada Mitma, Víctor Hugo; Cabrera Hoyos, Héctor Antonio; Cruz Luis, Juancarlos Alejandro; Goñas Goñas, Malluri
Generating agricultural suitability analyses that are objective, consistent, and accessible through digital platforms remains a technical and methodological challenge, creating an information gap for certain stakeholders. To address this issue, we assessed the territorial suitability of the Cajamarca region for coffee and cocoa cultivation using 18 subcriteria grouped into climatic, edaphological, topographic, and socioeconomic categories. To reduce subjectivity and improve consistency in variable comparisons, we applied multicriteria evaluation techniques, including the analytical hierarchy process (AHP) and Shannon entropy method. On the basis of the resulting weights, suitability models were generated using two approaches: one based on threshold reclassification and another using continuous suitability functions. Both approaches were validated using 3886 presence points for coffee and 671 for cocoa. The continuous approach demonstrated a greater ability to capture internal variability and spatial transitions, with greater dispersion and significant differences between classes. The most influential subcriteria for coffee were annual mean temperature, soil texture, elevation, and land use/land cover (LULC); for cocoa, they were annual mean temperature, soil pH, elevation, and LULC. In key districts, up to 59.8 % of the territory was classified as highly suitable, highlighting localized production potential. Finally, the results were integrated into the Suitability Watch Cajamarca application, developed in the Google Earth Engine, enabling interactive inspection of spatial suitability. This tool aims to support evidence-based agricultural planning and is intended for national scaling to other strategic crops.