Examinando por Autor "Manrique Gonzales, Luis Fernando"

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Critical edaphic and altitudinal factors influencing cation exchange capacity in coffee-growing soils of northeastern Peru: implications for sustainable fertility management
(Frontiers Media SA, 2026-05-05) Díaz Chuquizuta, Henry; Manrique Gonzales, Luis Fernando; Sánchez Ojanasta, Martín; Cuevas Giménez, Juan Pablo; Carbajal Llosa, Carlos Miguel; Cuellar Condori, Néstor Edwin; Martínez Zapata, Boris Guillermo; Vallejos Torres, Geomar
Introduction: Effective cation exchange capacity (ECEC) is a key indicator of soil fertility and sustainable soil management assessment in coffee-growing systems. Methods: This study aimed to identify the principal edaphic and altitudinal factors explaining ECEC variability in 69 soil samples collected from coffee farms in northeastern Peru. Results: ECEC results exhibited substantial variation, ranging from 0.14 to 55.49 cmol(+)·kg⁻¹ (mean = 15.21; SD = 12.47), and were significantly correlated with organic matter (r = 0.71), clay content (r = 0.62), exchangeable acidity (r = -0.63), and altitude (r = 0.33). Principal component analysis accounted for 64.3% of the edaphic variability, identifying Ca²⁺, pH, Mg²⁺, and exchangeable acidity as the most influential variables. The Random Forest model demonstrated high predictive accuracy (R² = 0.93; root mean square error (RMSE) = 2.1 cmol(+)·kg⁻¹), outperforming the generalized additive model (GAM) and identifying Ca²⁺ as the most important predictor (IncMSE% = 3177.37). A functional altitudinal gradient was also evident: areas above 1150 m.a.s.l. showed higher acidity and aluminium content, whereas areas below 900 m.a.s.l. exhibited greater base saturation and higher ECEC. Discussion: These findings support the development of site-specific fertilization strategies and soil–climate zoning, emphasizing the value of integrating multivariate analyses with machine-learning models as key tools for optimizing fertility management and coffee crop productivity in tropical mountain ecosystems; where soil texture represents a key factor influencing coffee sustainability, as greater nutrient retention capacity and improved nutritional balance are associated with enhanced potential for sustainable production and reduced environmental impact.
Integrated multivariate analysis of morphological and yield traits in native Capsicum chinense ecotypes grown in acidic soils of the Peruvian Amazon
(Frontiers Media S.A., 2026-04-15) Díaz Chuquizuta, Henry; Manrique Gonzales, Luis Fernando; Sánchez Ojanasta, Martín; Cuevas Gimenez, Juan Pablo; Martínez Zapata, Boris Guillermo; Flores Sinti, Geiner; Kerry Tanchiva, Juan Jose; Vallejos Torres, Geomar
Introduction: The comprehensive characterization of native Capsicum chinense ecotypes represents a strategic priority for genetic improvement, germplasm conservation, and the sustainable use of Amazonian crops. The objective of this study was to evaluate morphological, phenological, and productive variability among 12 ecotypes from the Peruvian Amazon by integrating multivariate análisis and machine learning with soil physicochemical characterization. Methods: The research was conducted on acidic tropical soils with low organic matter content and limited availability of exchangeable bases, conditions representative of degraded Amazonian agroecosystems, which enabled the assessment of soil–plant interactions and their influence on phenotypic expression and crop yield. Results: The results revealed a broad, well-structured range of phenotypic variability, with fruit diameter, fruit length, fruit weight, and seed weight identified as the primary morphological determinants of yield and adaptive capacity under low-fertility soil conditions. Principal component analysis indicated that four components explained more than 70% of the total variance, primarily associated with productivity, fruit morphometry, and phenological traits. Cluster análisis identified groups with high internal consistency, while linear discriminant analysis validated the phenotypic structure, achieving a classification accuracy of 91.8%. The ecotypes JEB-028 and LAG-022 exhibited superior productive performance, whereas BAL-012 and YUR-001 demonstrated greater phenotypic stability under restrictive soil conditions. Discussion: Overall, these findings confirm the strategic value of native Amazonian germplasm and underscore the importance of integrating edaphic diagnostics into genetic selection programs and into strategies for the sustainable management and restoration of degraded agricultural soils in the Amazon.
Spatial Modelling of Soil Quality and Lime Requirement for Precision Management in Humid Tropical Coffee Systems
(MDPI, 2026-02-25) Díaz Chuquizuta, Henry; Mejia Maita, Sharon Yahaira; Mercado Chinchay, Ruth Lizbeth; Arroyo Julca, Michell Karolay; Ore Valeriano, Ruddy Adely; Díaz Chuquizuta, Percy; Manrique Gonzales, Luis Fernando; Sánchez Ojanasta, Martín; Quispe Matos, Kenyi Rolando
Soil heterogeneity and acidity are major constraints to Coffea arabica production in the Amazonian soils of Peru. This study developed a spatial predictive framework that integrates a weighted Soil Quality Index (SQIw) and geostatistical modelling (Regression–Kriging and Ordinary Kriging) to estimate lime requirements (LRs) and delineate management zones. A total of 69 coffee-cultivated soil samples were analysed, and spectral information (NDVI) was incorporated to estimate relative yield (RR). Multivariate analysis defined a Minimum Data Set (MDS) composed of exchangeable Na, available P, pH and silt percentage; the highest weights were assigned to P (Wi = 0.292) and pH (Wi = 0.276). SQIw exhibited wide variability (0.01–0.87; CV = 51.8%) and was grouped into five classes, with low (43.5%)- and very low (21.7%)-quality classes predominating. SQIw showed a strong relationship with RR (r = 0.64). Geostatistical models performed differently between localities: in Nuevo Huancabamba, Regression–Kriging improved prediction accuracy (SQIw: R² = 0.58; LR: R² = 0.396), whereas in San José de Sisa, Ordinary Kriging provided better fits only for LRs (R² = 0.32). Nuevo Huancabamba is dominated by moderate-to-high-quality soils (87.29%; SQIw > 0.6) and low lime requirements (74.94%; <0.84 t ha⁻¹), in contrast with San José de Sisa, where low-quality soils prevail (89.45%; SQIw < 0.4) alongside high LRs (75.26%; 2.54–7.13 t ha⁻¹). The resulting maps enable targeted interventions—precision liming and focused P fertilisation—to correct acidity and phosphorus deficiency, thereby improving input-use efficiency and enhancing the sustainability of Amazonian coffee systems.