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...

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), ...

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...

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...

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...

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...

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 ...

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 ...

Remote sensing is essential in precision agriculture as this approach provides high-resolution information on the soil's physical and chemical parameters for detailed decision making. Globally, technologies such as remote sensing and machine learning are increasingly being used to infer these parameters. This study evaluates soil fertility changes and compares them with previous fertilization inputs using high-resolution multispectral imagery and in situ measurements. A UAV-captured image was used to predict the spatial distribution of soil parameters, generating fourteen spectral indices and a digital surface model (DSM) from 103 soil plots across 49.83 hectares. Machine learning algorithms, including classification and regression trees (CART) and random forest (RF), modeled the soil parameters (N-ppm, P-ppm, K-ppm, OM%, and EC-mS/m). The RF model outperformed others, with R² values of...

The lack of precise methods for estimating forest biomass results in both economic losses and incorrect decisions in the management of forest plantations. In response to this issue, this study evaluated the effectiveness of using the DJI Zenmuse L1 LiDAR, mounted on a DJI Matrice 300 RTK UAV, to provide three-dimensional measurements of canopy structure and estimate the aboveground biomass of Eucalyptus globulus. Various LiDAR metrics were employed alongside field measurements to calibrate predictive models using multiple regression and machine learning algorithms. The results at the individual tree level show that RF is the most accurate model, with a coefficient of determination (R²) of 0.76 in the training set and 0.66 in the test set, outperforming Elastic Net (R² of 0.58 and 0.57, respectively). At the plot level, a multiple regression model achieved an R² of 0.647, highlighting ...