Examinando por Autor "Carbajal Llosa, Carlos Miguel"

Mostrando 1 - 6 de 6

Atlas de las Estaciones Experimentales Agrarias del INIA
(Instituto Nacional de Innovación Agraria, 2025-04-29) Cruz Luis, Juancarlos Alejandro; Ortiz Morera, Narda Cecilia; Quispe Torres, Diego Rafael; Atalaya Lopez, José S.; Marcavilca Villar, Pedro Miguel; Ramírez Aparicio , Jorge A.; Salinas Rivera, Juan L.; Escobar Cuadros, Francisco; Carbajal Llosa, Carlos Miguel; Olivarez Rivera, Evelyn L.; Casaretto Castagnino, Duilio; Ganoza Roncal, Jorge Juan
El Instituto Nacional de Innovación Agraria (INIA) es un organismo técnico especializado adscrito al Ministerio de Desarrollo Agrario y Riego (MIDAGRI) que cumple funciones y desarrolla actividades de investigación, transferencia tecnológica y extensión en materia agraria. Es responsable de la generación de conocimientos y tecnologías, de la conservación y puesta en valor de los recursos genéticos de la agrobiodiversidad, así como de la producción de semillas, plantones y reproductores de alto valor genético. Asimismo, brinda servicios tecnológicos a través de una red de laboratorios a nivel nacional. Como ente rector del Sistema Nacional de Innovación Agraria (SNIA), articula y regula la investigación, desarrollo e innovación (I+D+i) con los actores del SNIA, orientadas a la competitividad, seguridad alimentaria y adaptación al cambio climático, a través de la política y el Plan Nacional de Innovación Agraria. Las funciones del INIA son desarrolladas de manera articulada y descentralizada desde sus veinticinco (25) Estaciones Experimentales Agrarias (EEA) a nivel nacional, las que están conformadas por Centros Experimentales (CE) ubicados a nivel regional. El presente atlas contiene información de los aspectos relevantes de las Estaciones Experimentales Agrarias, tales como: creación, Centros Experimentales, ubicación y ámbito de intervención. Asimismo, presenta una colección de mapas que contribuye al conocimiento geográfico de éstas, así como de las actividades de conservación y puesta en valor de recursos genéticos, investigación, desarrollo tecnológico, producción de material genético de calidad, transferencia de tecnología, extensión agropecuaria y servicios tecnológicos agrarios que se desarrollan a nivel nacional. Este documento es una colección cartográfica y un material de consulta que contribuye al conocimiento geográfico de las Estaciones Experimentales Agrarias y sus Centros Experimentales, el cual está dirigido no solo a los actores del SNIA, sino también a la sociedad civil en su conjunto; con el objeto de informar sobre el rol que desempeñan estos centros del INIA y su esencial aporte para enfrentar los desafíos del agro en condiciones de cambio climático.
Evaluation of the Flood Area in the Presence of Climate Change: Ravine La Ronda Case, Ricardo Palma, Peru
(Horizon Research Publishing, 2024-11-13) Perez Campomanes, Giovene; Perez Campomanes, Maria; Carbajal Llosa, Carlos Miguel
In the district of Ricardo Palma, human settlements are located near streams, which are seriously affected during the heavy flooding season (rainy season), which increases due to the presence of the El Niño Southern Oscillation (ENSO) and the global effect of climate change. To get to know the flood zone 09 de Octubre - La Ronda, Ricardo Palma, software was applied to obtain the area of influence to study, and to know 10.5 software was applied to obtain the area of influence to study, and to know the rainfall record of the National Water Service. Meteorology and Hydrology of Perú(SENAMHI) for a continuous period of 27 years of maximum daily rainfall, with the HEC HMS 4.9 software the maximum design flows for different return periods were obtained, and the HEC RAS 6.2 software to obtain the flooding area. To find out the support of the authorities in the presence of the Niño Southern Oscillation (ENSO), and the global effect of climate change, a survey was carried out among the population, obtaining that 14.43% had the appropriate conditions to mitigate the impacts of the flooding due to intense rains, 22.93% received help in the presence of the El Niño phenomenon, and for 20.75%, there was a response from their authorities to the needs of the population in the presence of an emergency, and no changes that benefit the population were distinguished. The maximum design flows were calculated for a return period of 10 and 100 years, which vary between 31.7 m³/s and 61.2 m³/s, and that for a design flow of 61.2 m³/s, the flooding area of 0.25 km² was obtained.
Implementing cloud computing for the digital mapping of agricultural soil properties from high resolution UAV multispectral imagery
(MDPI, 2023-06-20) Pizarro Carcausto, Samuel Edwin; Pricope, Narcisa G.; Figueroa Venegas, Deyanira Antonella; Carbajal Llosa, Carlos Miguel; Quispe Huincho, Miriam Rocío; Vera Vilchez, Jesús Emilio; Alejandro Méndez, Lidiana Rene; Achallma Mendoza, Lino; González Tovar, Izamar Estrella; Salazar Coronel, Wilian; Loayza, Hildo; Cruz Luis, Juancarlos Alejandro; Arbizu Berrocal, Carlos Irvin
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 indices with in situ measurements of physical-chemical soil properties in agricultural lands in the Peruvian Mantaro Valley. The prediction ability of several machine learning algorithms (CART, XGBoost, and Random Forest) was evaluated using R2, to select the best predicted maps (R2 > 0.80), for ten soil properties, including Lime, Clay, Sand, N, P, K, OM, Al, EC, and pH, using multispectral imagery and derived products such as spectral indices and a digital surface model (DSM). Our results indicate that the predictions based on spectral indices, most notably, SRI, GNDWI, NDWI, and ExG, in combination with CART and RF algorithms are superior to those based on individual spectral bands. Additionally, the DSM improves the model prediction accuracy, especially for K and Al. We demonstrate that high-resolution multispectral imagery processed in the GEE platform has the potential to develop soil properties prediction models essential in establishing adaptive soil monitoring programs for agricultural regions.
Soil management in Lepidium meyenii (maca) monoculture: trends and challenges for small farmers around Lake Chinchaycocha in the Andean highlands of Junin (Peru)
(Frontiers Media S.A., 2025-01-17) Solórzano Acosta, Richard; Chanco, Mirella; Seminario, Martín; Camel Paucar, Vladimir Fernando; Cabello Torres, Rita; Lastra Paucar, Sphyros Roomel Luciano; Arias Arredondo, Alberto Gilmer; Verástegui Martínez, Patricia; Quispe Matos, Kenyi Rolando; Carbajal Llosa, Carlos Miguel; Cuevas Gimenez, Juan Pablo; Cruz Luis, Juancarlos Alejandro; Turín Canchaya, Cecilia Claudia
Introduction: Monoculture is a significant concern due to its negative impact on soil quality, resource productivity, and agricultural sustainability, particularly in vulnerable communities. This research aims to evaluate high Andean soil management for maca monoculture. Materials and methods: To this end, interviews were conducted with maca farmers adjacent to Lake Chinchaycocha. The effect on soil quality was evaluated based on principal component analysis (PCA), weighted soil quality index (SQIw), and physico-chemical characteristics. Results: The results indicated differences between farmers in agronomic management, monoculture period (from 5 to 9 years), and fallow time (up to 10 years in the best cases). Regarding soil quality, the PCA highlighted boron andtotal nitrogen locations in the same quadrant, with the highest contribution to the analysis. Finally, the SQIw showed that soils without maca cultivation presented better quality. Conclusion: This research’s results indicate a need to optimize soil management practices, especially for small farmers, who are the most vulnerable group. In addition, further studies on boron and nitrogen availability in soils cultivated with maca are required, emphasizing areas that exceed 10 years of continuous use.
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 Andy
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 Variability of Soil Acidity and Lime Requirements for Potato Cultivation in the Huánuco Highlands
(MDPI, 2024-12-13) Quispe Matos, Kenyi Rolando; Mejía, Sharon; Carbajal Llosa, Carlos Miguel; Alejandro Mendez, Lidiana Rene; Verástegui Martinez, Patricia; Solórzano Acosta, Richard Andi
Soil acidity is a major limiting factor for potato production in Peru's high Andean region. This study aims to predict the spatial variability of soil acidity as a fundamental tool for recommending site-specific liming treatments and to identify the physical-chemical characteristics most closely related to soil acidity. The soil samples were collected from five locations in the province of Pachitea, Huánuco. Descriptive statistics, principal component analysis (PCA), and Pearson correlation analysis were used to identify the soil properties contributing most to total variance and those most strongly correlated with soil acidity. The ordinary geostatistical kriging method evaluated the predictive accuracy for 23 soil properties and liming requirements over a 28,463 ha area, at a spatial resolution of 10 m. Results showed that the Plaza Punta and Buenos Aires locations had more degraded acidic soils, with frequencies between 55% and 100% above the general mean (30.94 ± 24.87%) and the critical threshold (25%) for potato cultivation. Variables such as exchangeable calcium percentage (ECP), Ca2+, Mg2+, sand content, and organic matter strongly correlated with soil acidity, while exchangeable H+ and ECP were the main contributors to the total variance. Geostatistical analysis revealed that Mg2+ and Ca2+ had the highest R² values (0.87 and 0.76, respectively), indicating a strong fit between observed and predicted values in the spatial analysis of soil acidity. It is concluded that the agricultural dolomite requirements in the localities of Plaza Punta and Buenos Aires exhibit high spatial predictability. Additionally, the analysis of diverse soil physicochemical properties is emphasized as critical for determining precise application rates.