Quality and safety of the soil are essential to ensure social and economic development and provides the supply of contaminant free food. With agriculture intensification, expansion of urban zones, construction of roads, and mining, some agricultural soils sites become polluted increasing environmental risks to ecosystems functions and human health. Hence the need know the spatial distribution of elements in soils, we mapped 25 elements, namely Ca, Mg, Sr, Ba, Be, K, Na, As, Sb, Se, Tl, Cd, Zn, Al, Pb, Hg, Cr, Ni, Cu, Mo, Ag, Fe, Co, Mn and V, using various geospatial datasets, such as remote sensing, climate, topography, soil data, and distance, to establish the spatial estimation models of spatial distribution trained trough machine learning model with a supervised dataset of 109 topsoil samples, into Google earth engine platform. Using R2, RMSE and MAE to assess the prediction accuracy...

Quality and safety of the soil are essential to ensure social and economic development and provides the supply of contaminant free food. With agriculture intensification, expansion of urban zones, construction of roads, and mining, some agricultural soils sites become polluted increasing environmental risks to ecosystems functions and human health. Hence the need know the spatial distribution of elements in soils, we mapped 25 elements, namely Ca, Mg, Sr, Ba, Be, K, Na, As, Sb, Se, Tl, Cd, Zn, Al, Pb, Hg, Cr, Ni, Cu, Mo, Ag, Fe, Co, Mn and V, using various geospatial datasets, such as remote sensing, climate, topography, soil data, and distance, to establish the spatial estimation models of spatial distribution trained trough machine learning model with a supervised dataset of 109 topsoil samples, into Google earth engine platform. Using R2, RMSE and MAE to assess the prediction accuracy...

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...

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...

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.

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), ...

Universidad Nacional Agraria La Molina. Escuela de Posgrado. Maestría en Producción Animal

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 ...

Moderate resolution imagery (MODIS) data from the Normalized Difference Vegetation Index (NDVI) can be used to estimate aboveground biomass at large spatial scales; however, validation of the information with fieldwork is required to make more accurate grassland vegetation predictions. The study was conducted in three districts of the central highlands of Peru. In total, 153 grass samples (high grassland and low grassland) were collected after reading NDVI in situ within a pixel of 250x250 m, with a frequency of three months during a three year period. Satellite images were downloaded from the MODIS sensor to obtain the NDVI. The NDVI-MODIS values were calibrated with the NDVI registered in situ, using regression models. The calibrated equations modelled the dynamic trends of vegetation between 2000 and 2018 for the central highlands. The NDVI in situ of the low grassland ranged between ...

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...

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...

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 ...

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 ...

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...

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...

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...

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...

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...

Accurate and timely estimation of oat biomass is crucial for the development of sustainable and efficient agricultural practices. This research focused on estimating and predicting forage oat biomass using UAV and agronomic variables. A Matrice 300 equipped with a multispectral camera was used for 14 flights, capturing 21 spectral indices per flight. Concurrently, agronomic data were collected at six stages synchronized with UAV flights. Data analysis involved correlations and Principal Component Analysis (PCA) to identify significant variables. Predictive models for forage biomass were developed using various machine learning techniques: linear regression, Random Forests (RFs), Support Vector Machines (SVMs), and Neural Networks (NNs). The Random Forest model showed the best performance, with a coefficient of determination R2 of 0.52 on the test set, followed by Support Vector Machines ...