The Junín Lake basin, a critical high-altitude ecosystem in the central Peruvian Andes, faces severe contamination from potentially toxic elements (PTEs) driven by mining activities, agriculture, and urbanization. This study evaluates the spatial distribution, ecological risk, and human health implications of 14 heavy metals, metalloids, and trace elements in surface soils surrounding the lake. Using 211 soil samples, we integrated remote sensing, land cover classification, and Random Forest machine learning models with spectral, edaphic, topographic, and proximity-based environmental covariates to predict contamination patterns and assess risk. Results reveal extreme contamination, with arsenic (As), lead (Pb), cadmium (Cd), and zinc (Zn) concentrations exceeding ecological thresholds by over 100-fold in agricultural zones. Ecological risk assessments using contamination degree (mCD), ...

Most Andean lakes and lagoons are used as reservoirs to manage hydropower generation and cropland irrigation, which, in turn, alters river flow patterns through processes of storage and discharge. The Carhuacocha and Vichecocha lagoons, fed by glaciers, are important aquatic ecosystems regulated by dams. These dams increase the flow of the Mantaro River during the dry season, supporting both energy production and irrigation for croplands. Water quality in the Carhuacocha and Vichecocha lagoons was assessed between storage and discharge events by using the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) and multivariate statistical methods. The quality of both lagoons is excellent during the storage period; however, it decreases when they are discharged during the dry season. The most sensitive parameters are pH, dissolved oxygen (DO), and biochemical oxyge...

The spatial heterogeneity of soil properties has a significant impact on crop growth, making it difficult to adopt site-specific crop management practices. Traditional laboratory-based analyses are costly, and data extrapolation for mapping soil properties using high-resolution imagery becomes a computationally expensive procedure, taking days or weeks to obtain accurate results using a desktop workstation. To overcome these challenges, cloud-based solutions such as Google Earth Engine (GEE) have been used to analyze complex data with machine learning algorithms. In this study, we explored the feasibility of designing and implementing a digital soil mapping approach in the GEE platform using high-resolution reflectance imagery derived from a thermal infrared and multispectral camera Altum (MicaSense, Seattle, WA, USA). We compared a suite of multispectral-derived soil and vegetation indi...

This study evaluated the use of visible and near-infrared (Vis-NIR) spectroscopy combined with machine learning (ML) algorithms to predict soil fertility-related properties in two contrasting agroecological regions of Peru: the Highlands and the Rainforest. A total of 297 soil samples were analyzed using portable spectroradiometers covering a spectral range of 350–2500 nm, applying transformations such as Savitzky–Golay smoothing, first derivative, and band depth. Predictive models were developed using PLSR, Random Forest, Support Vector Machines, and neural networks. Results show variable predictive performance across soil properties and ecosystems. Organic matter in Highland soils and calcium in Rainforest soils achieved the strongest test-set accuracy (R2 > 0.70), while pH and texture fractions showed moderate performance (R2 = 0.42–0.67), and mobile nutrients including phosphor...

En primer lugar, este trabajo no hubiera sido posible sin la confianza depositada por el Dr. Javier Ñaupari y, director de la tesis que ha dado lugar a este estudio, para que participara en el proyecto financiado por el CONCYTEC y FINCyT, el cual ha proporcionado el contexto y los materiales necesarios.

El estudio se efectuó en la Granja Agropecuaria de Yauris de la Universidad Nacional del Centro del Perú. Teniendo como objetivo determinar la viabilidad económica, social y ambiental para el sistema de la Granja Agropecuaria de Yauris, como centro de producción experimental, investigación, desarrollo y recreación en el formato del Sistema Nacional de Inversión Pública. Se realizó el levantamiento topográfico de toda la área de la Granja Agropecuaria de Yauris, para luego realizar los trabajos de gabinete, como es la realización de presupuesto, planos y el estudio bajo el anexo SNIP 05, que son los contenidos mínimos para elaborar proyecto de Pre inversión. Los resultados obtenidos muestran, que la inversión total del proyecto asciende a s/. 24 446 464,52 nuevos soles, en la cual 3,7 % representa para gastos generales, 3,07% como gastos de supervisión y 0,88% para gastos ...

In agricultural systems, soil pH and electrical conductivity (EC) are crucial chemical properties that directly affect nutrient availability and microbial activity, but the challenging environment of the Peruvian Andes has limited research on their estimation. This study aimed to develop an ensemble learning method to predict soil pH and EC in Andean agroecosystems using environmental predictors. By using simple and weighted averaging, we developed a heterogeneous ensemble learning approach that integrates machine learning (ML) algorithms, including Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The weighted ensemble assigns weights to models based on their predictive accuracy, measured by R² from spatial cross-validation. Spatial patterns are noticeable, and pH displays greater spatial clustering than EC. Elev...

Soil organic carbon (SOC) sequestration in croplands represents a significant opportunity to mitigate climate change by removing carbon dioxide from the atmosphere. Simulation tools are increasingly used to assess the impact of climate change and soil management on soil organic carbon stock dynamics. Although Andean soils typically store large amounts of organic carbon, agricultural practices, especially plowing, may deplete these stocks, creating a need to understand these dynamics better. Here, we show the soil organic carbon sequestration potential in croplands in the Peruvian Andean region over 50 years. Soil organic carbon content and bulk density were spatially predicted across the study area using 100 georeferenced soil samples to quantify organic carbon stocks. Spatial interpolation was performed using Ordinary Kriging with exponential and spherical variogram models, which provid...

The concept of ecosystem services has gained popularity among academics, researchers and policymakers to support environmental management and biodiversity conservation, so that many development projects in rural areas have merited investment for restoration and improvement of grassland ecosystems accompanied by training programs for the beneficiaries, With this criterion in mind, the study investigated the perception of puna pastoralists in Acopalca, Peru, regarding the degree of knowledge about the significance of the ecosystem services provided by soil-water-grasslands, with the objective of characterizing the environmental, social and economic dimensions of this local perception, through the application of a survey to the representative of the livestock family affiliated to two producers' associations. It was evidenced that cattle-raising families have a limited understanding of the r...

Aims: determine the composition and floristic diversity, the similarity between sites based on the distribution of species in the altitudinal gradient, and determine the value of ecological importance, in Andean grassland ecosystems. Study Design: Original research. Place and Duration of Study: This study took place in the Huacracocha micro-watershed in the Central Highlands of Peru, during the rainy season (January - March 2022). Methodology: The agrostological evaluation points were determined taking into account twelve sites of interest were determined, located from the lowest part of the micro-watershed (4091.8 masl) to the part with the highest vegetation cover (4512.27 masl), the agrostological reading process at each evaluation site was carried out using the radial transect method with the line and intercept point technique. Results: We observed the presence of the presence of 78 ...

Heavy metal contamination in rivers is a serious environmental and public health concern, especially in areas affected by mining. This study evaluated the levels of contamination and the associated ecological and carcinogenic risks in the sediments of the Cunas River, located in the central highlands of Peru. Sediment samples were collected from upstream and downstream sections. Several metals and metalloids were analyzed, including copper (Cu), chromium (Cr), iron (Fe), manganese (Mn), molybdenum (Mo), nickel (Ni), lead (Pb), vanadium (V), zinc (Zn), antimony (Sb), arsenic (As), and cadmium (Cd). The ecological risk assessment focused on ten of these elements, while carcinogenic and non-carcinogenic risks were assessed for seven metals selected based on their toxicological importance. The results showed that Cd and Pb concentrations were higher in the downstream section. Cd and As excee...

Soil elemental composition in heterogeneous agroecosystems is shaped by interacting environmental and anthropogenic controls. This study evaluated the spatial variability of potentially toxic elements (PTEs: Cu, Cr, Fe, Mn, Mo, Ni, Pb, V, Zn, As, and Cd) across coastal (Chancay and Pativilca) and highland (Mantaro and Tarma) agricultural valleys of Peru. A stratified sampling design was combined with multivariate analyses (PCA, PERMANOVA, PERMDISP, and variance partitioning) and ecological risk assessment using integrated indices (PLI, mCd, SRI, and Nemerow index). The first two principal components explained 50.2% of total variance (PC1 = 36.8%; PC2 = 13.4%), reflecting distinct soil–geochemical and climatic–spatial gradients. The Valley × Zone interaction significantly structured elemental composition (R² = 0.049, p = 0.011), whereas crop type showed no significant effect (p = 0....

The high-Andean vegetation ecosystems of the Bombón Plateau in Peru face increasing degradation due to aggressive anthropogenic land use and the climate change scenario. The lack of historical degradation evolution information makes implementing adaptive monitoring plans in these vulnerable ecosystems difficult. Remote sensor technology emerges as a fundamental resource to fill this gap. The objective of this article was to analyze the degradation of vegetation in the Bombón Plateau over almost four decades (1985–2022), using high spatiotemporal resolution data from the Landsat 5, 7, and 8 sensors. The methodology considers: (i) the use of the atmosphere resistant vegetation index (ARVI), (ii) the implementation of non-parametric Mann–Kendall trend analysis per pixel, and (iii) the affected vegetation covers were determined by supervised classification. This article’s results sho...

The rising global demand for food, including potatoes, necessitates increased crop production. To achieve higher yields, farmers frequently depend on regular applications of nitrogen and phosphate fertilizers. As people seek more environmentally friendly alternatives, biofertilizers are gaining popularity as a potential replacement for synthetic fertilizers. This study aimed to determine how Glomus iranicum affects the growth of potatoes (Solanum tuberosum L.) and the nutritional value of potato tubers when grown alongside broad beans (Vicia faba L.). An experiment was conducted using potatoes tested at five dosage levels of G. iranicum, ranging from 0 to 4 g, to see its impact on the plants and soil. Inoculation with G. iranicum produced variable results in associated potato and bean crops, with significant effects on some variables. In particular, inoculation with 3 g of G. iranicum pr...

High-altitude Andean lagoons are ecologically sensitive systems whose water quality is under increasing pressure from the expansion of aquaculture and other human activities. An integrated assessment of water quality and trophic status was carried out in three lagoons located in the highlands of central Peru, using a multi-index and multivariate approach that combined physicochemical parameters, trophic indices (TRIX, TSI, molar N:P ratio), and heavy-metal indices, evaluated against Peruvian EQS, USEPA, and CCME water-quality standards. Principal component analysis explained 60.1% of the total variability, with the first axis (40.4%) structured by an organic loading and nutrient gradient that consistently separated Tipicocha from the other lagoons. Total phosphorus in Tipicocha reached concentrations well above the Peruvian EQS threshold, and TRIX values classified all lagoons as eutroph...

Biochar, a carbon-rich material produced through oxygen-limited pyrolysis of organic biomass, demonstrates exceptional potential as a soil amendment due to its porous structure and stability. This research investigated the impact of guinea pig manure biochar on three vegetable species cultivated in high Andean conditions: spinach (Spinacia oleracea L.), cabbage (Brassica oleracea var.), and chard (Beta vulgaris var.). The study implemented four biochar application rates (0, 10, 20, and 30 t/ha) and measured comprehensive agronomic parameters including leaf count, leaf length, and fresh/dry biomass of both leaves and roots. Simultaneously, UAV-captured multispectral imagery provided spectral indices that were integrated with agronomic data into machine learning models: linear regression, support vector machines (SVM), and regression trees (CART). Results demonstrated significant vegetativ...

Heavy metal contamination in Andean agricultural systems is a growing concern for food safety and environmental health. This study assessed the concentrations and bioaccumulation patterns of eleven metals (Cd, Pb, As, Cr, Ni, Cu, Zn, Mn, Fe, Hg, Mo) in seven representative crops cultivated under irrigated and rainfed conditions in the Mantaro Valley, central Peruvian Andes. Soil and foliar samples were collected from paired plots, and bioaccumulation factors (BAF) were calculated to evaluate metal transfer to plant tissues. Irrigated soils showed higher and more homogeneous concentrations of Cd, Pb, and As, reflecting long-term accumulation from historical mining activities and irrigation with contaminated water from the Mantaro River. Foliar concentrations exceeded Codex Alimentarius limits for Cd, Pb, and As in several crops, especially potato and broad bean. BAF analyses revealed dist...

This study evaluated nutrient extraction and uptake in native forage grasses (Festuca dolichophylla and Calamagrostis chrysantha) and improved species (Lolium perenne and Dactylis glomerata) at 4,100 m a.s.l. in the Peruvian Andes using a completely randomized design. Results revealed significant interspecific variability in nutrient accumulation. Dactylis glomerata showed superior macronutrient accumulation, particularly Mg, while Lolium perenne achieved highest K extraction (0.07 t ha⁻¹) and biomass production. Native species demonstrated lower nutritional demands: Festuca dolichophylla reached maximum dry matter production (6 t ha⁻¹), while Calamagrostis chrysantha showed elevated Ca and P concentrations. Correlation analysis revealed strong positive associations among Ca, Mg, Cu, Fe, Mn, and Zn (r = 0.7-1.0), indicating coordinated uptake mechanisms. Nickel exhibited negative c...

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...

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 ...