Examinando por Materia "Soil quality index"

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Soil quality in olive orchards of southern Peru using a weighted soil quality index (SQIw): constraints by salinity, organic matter and sustainable management approach
(Frontiers Media S.A., 2026-02-09) Poma Chamana, Russell Hilario; Vilca Gamarra, César; Linares Escapa, Solmayra; Puma Huacani, Katherine; Carrillo, Alex; Villalta Soto, Martín J.C.; Quispe Matos, Kenyi Rolando
Introduction: Soil salinization and alkalinization in the arid zones of southern Peru pose major challenges to agricultural sustainability, particularly in the olive orchards of Bella Unión, where irrigation relies on surface and groundwater of variable quality. This study aimed to assess soil quality and its spatial variability to support site-specific management in olive (Olea europaea L.) orchards. Methods: A total of 160 composite soil samples (0–30 cm) were collected from representative olive orchards and analyzed for pH, electrical conductivity (ECe), organic matter (OM), available phosphorus (Pav), available potassium (Kav), texture, and calcium carbonate equivalent (CCE). The Soil Quality Index (SQIw) was calculated and combined with multivariate and geostatistical analyses to identify key soil quality indicators and characterize their spatial variability. Results: Soils showed high variability in salinity (ECe = 1.30–24.61 dS m⁻¹) and organic matter content (0.50–3.10%), while pH was relatively homogeneous (6.90–8.40). According to the SQIw, 1.26% of soils were classified as Very Poor, 44.96% as Poor, 51.49% as Acceptable, 2.28% as Good, and 0.01% as Optimal. Electrical conductivity was the main factor controlling the SQIw. Discussion: These results indicate that salinity represents a major constraint for olive growth and productivity in the study area. Despite its lower weight in the SQIw, the generally low organic matter levels suggest limitations for soil fertility, water retention, and nutrient cycling, highlighting the need for organic amendments with low electrical conductivity. Nutrient management should also account for reduced nutrient availability under alkaline–saline conditions and the widespread organic matter deficiency. This study represents the first application of SQIw in Peruvian olive orchards and demonstrates its usefulness for delineating low-quality zones, guiding fertilization and soil recovery strategies, and promoting sustainable soil management in arid agroecosystems.
Soil quality variation associated with land cover in the Peruvian jungle of the Junín region
(Elsevier, 2025-05-03) Carbajal Llosa, Carlos Miguel; Moya Ambrosio, Fernanda; Barja Ingaruca, Antony Marcos; Ottos Diaz, Elvis; Aguilar Tito, Cinthya; Advíncula Zeballos, Orlando; Cruz Luis, Juancarlos Alejandro; Solórzano Acosta, Richard Andi
In the Junín jungle, inappropriate agricultural management practices for a long time can adversely affect soil quality. This has driven the development of multiple soil quality evaluation methods that are highly demanding in terms of economic and human resources. This study aimed to evaluate the effect of land-use change from natural ecosystems to agricultural systems by determining soil quality in the jungle of the Junin Region. Soil samples were collected between December 2021 and July 2022 in the Chanchamayo and Satipo provinces in the Junín region. Seventy-four samples were determined using stratified sampling, along with the support provided by the stacking of five spatial layers. Physical, chemical, and biological indicators, along with land cover type data from the European Space Agency (ESA) WorldCover product, were determined. A minimum data set (MDS) was established through correlation analysis, from which principal component analysis (PCA) was performed. Finally, the weighted soil quality index (SQIw) was calculated by integrating the most essential variables identified through PCA. It was found that forest cover soils had a higher SQIw than soils with crops and grassland cover. According to PCA, the soil quality variables that contributed the most are potassium (K) content and pH. It was concluded that the jungle soil quality in the Junín region is moderate to low, depending on the coverage. In addition, more significant degradation was observed in grassland-covered areas, particularly in the Chanchamayo province than in the Satipo province.
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.