Artículos Científicos UNJ

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A Comparative Study of Freshwater Fish Burgers Made from Three Amazonian Species: Omega 3 Fortification and Sodium Reduction
(Universidad Nacional de Jaén, 2024-02-26) Rios Mera, Juan Dario
This study aimed to formulate burgers made from three Amazonian fish species: pacu (Pyaractus brachypomus), boquichico (Prochilodus nigricans), and bujurqui (Chaetobranchus flavescens), focusing on sodium reduction and fortification with fish oil microparticles (FOM) rich in eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). The proximal composition, sodium and calcium content, instrumental texture profile, fatty acid profile, sensory profile, and overall liking were evaluated. Differences in proximal composition and fatty acid profiles between the fillets were reflected in the burgers. Fortification with FOM increased EPA and DHA in the burgers; thus, they can be considered “high in omega-3 fatty acids” and reduced the n-6/n-3 ratio below 4. There were sensory attributes that could be related to lipid oxidation but reduced overall liking for less than 10% of consumers. Nevertheless, certain sensory attributes (grilled, characteristic, aromatic, tasty, tender, and juicy) had a positive impact on the overall liking of more than 20% of consumers, yielding adequate scores (between 5.60 and 5.71) on the 9-point hedonic scale. The production process must be optimized by knowing the fish fillet quality in depth, improving the FOM and burgers’ oxidative stability, and achieving an adequate sensory and hedonic profile by employing consumers’ vocabulary to characterize new products.
A sequential approach to reduce sodium chloride in freshwater fish burgers considering chemical, texture, and consumer sensory responses
(Universidad Nacional de Jaén, 2024-02-26) Rios Mera, Juan Dario
The objective of this work was to determine the effect of the reduction and substitution of salt (NaCl) in pacu (Piaractus brachypomus) burgers, an Amazonian freshwater fish. In the first stage, five treatments with NaCl concentrations from 0.5 to 1.5 g/100 g were evaluated for proximal composition, instrumental texture, cooking losses, sensory profile, overall liking, and lipid oxidation for eight weeks. The results suggest a 50% reduction in NaCl content without affecting the parameters of burgers. In the second stage, NaCl was replaced up to 50% by potassium chloride (KCl) or calcium chloride (CaCl2), observing that CaCl2 at 50% substitution of NaCl presents better compatibility with the product in the chemical aspect, instrumental texture, sensory profile and overall liking, with the improvement in the decrease of the lipid oxidation compared to the product with only NaCl. The NaCl reductions in the two stages reached up to 75% NaCl reduction in the burger, showing the salience of studying first the NaCl reduction and then the incorporation of NaCl substitutes.
Amazon Fruits as Healthy Ingredients in Muscle Food Products: A Review
(Foods, 2024-07-01) Rios Mera,Juan Dario; Arteaga Miñano,Hubert Luzdemio
When looking for new ingredients to process red meat, poultry, and fish products, it is essential to consider using vegetable resources that can replace traditional ingredients such as animal fat and synthetic antioxidants that may harm health. The Amazon, home to hundreds of edible fruit species, can be a viable alternative for new ingredients in processing muscle food products. These fruits have gained interest for their use as natural antioxidants, fat replacers, colorants, and extenders. Some of the fruits that have been tested include açai, guarana, annatto, cocoa bean shell, sacha inchi oil, and peach palm. Studies have shown that these fruits can be used as dehydrated products or as liquid or powder extracts in doses between 250 and 500 mg/kg as antioxidants. Fat replacers can be added directly as flour or used to prepare emulsion gels, reducing up to 50% of animal fat without any detrimental effects. However, oxidation problems of the gels suggest that further investigation is needed by incorporating adequate antioxidant levels. In low doses, Amazon fruit byproducts such as colorants and extenders have been shown to have positive technological and sensory effects on muscle food products. While evidence suggests that these fruits have beneficial health effects, their in vitro and in vivo nutritional effects should be evaluated in muscle food products containing these fruits. This evaluation needs to be intended to identify safe doses, delay the formation of key oxidation compounds that directly affect health, and investigate other factors related to health.
An Overview of 20 Years of Pisco Spirit Research: Trends and Gaps Revealed by a Systematic Review
(Beverages, 2025-05-26) Rios Mera,Juan Dario
Pisco is an emblematic spirit in Peru and Chile, made from fermented grapes, gaining growing scientific interest over the last two decades. This study aimed to map 20 years of research on Pisco through a systematic bibliometric review. A search was conducted in the Scopus database covering the period from 2004 to 2024, applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology for the transparent selection of scientific articles. The search strategy considered titles, abstracts, and keywords, using the terms “Pisco” and “schnapps”, excluding unrelated fields such as geology (basin, seismic, fossil). The initial search yielded 360 records. After removing non-original articles (books, book chapters, conference papers, and reviews), 101 articles remained. A further screening excluded irrelevant studies (e.g., those referring to the city of Pisco rather than the beverage), resulting in 78 articles included for final analysis. It was observed that 19% of the studies focus on the history, culture, and appellation of origin; 14% on environmental sustainability; 10% on innovation and quality; and 9% on the bioactive properties of by-products. Other areas include extraction technologies (9%), distillation process modeling (8%), and marketing and economics (8%), among others. Recent trends are related to clean production practices. Thus, Pisco by-products and their components can be exploited by applying technologies such as supercritical fluids, drying, and biofilms, while, for waste management, the processes of composting, solar photo-Fenton, and ozonation can be applied. Moreover, it is important to highlight that the valorization of Pisco by-products opens opportunities for translation into the market, particularly in developing cosmetics, nutritional supplements, and bio-packaging materials, contributing to sustainability and innovation in new industries. However, a more holistic view is still needed in Pisco research. These findings suggest that future research should prioritize the integration of consumer-based sensory evaluations and sustainable production innovations to optimize Pisco’s quality, enhance market acceptance, and promote environmentally responsible industry practices
Application of the Greenhouse Gas Protocol (GHG Protocol) and the ISO 14064-1: 2006 standard for the estimation of the carbon footprint at the National University of Jaen in 2021
(Universidad Nacional de Colombia||DYNA, 2023-05-31) Ocaña Zúñiga,Candy Lisbeth
The objective of the study is to estimate the Carbon Footprint of the National University of Jaen (UNJ), for the period 2021. The direct Scope 1 (fuel consumption) and indirect Scope 2 (electricity consumption) greenhouse gas (GHG) emissions were calculated from CO2, CH4 and N2O produced in 29 administrative offices of the university campus. The methodology used was proposed by the GHG Protocol and ISO 14064-1:2006. For fuel emission factors, the indicators established by the Intergovernmental Panel on Climate Change (IPCC) were used, and for electrical energy: 1.56E-01 tCO2/MWh, 9.70E-06 tCH4/MWh, 1.20E-06 tN2O/MWh, and specific conversion factors established by the Ministry of the Environment (MINAM) were used. The results show that a total of 29.3937 tCO2eq were emitted, being CO2 the predominant GHG (23.1364 t). Scope 1 contributed 15,6827 tCO2eq, occupying the highest participation with 53.35 %
Assembly Algorithms for Seismic Vulnerability Estimation in Confined Masonry Dwellings
(IIETA, 2024-06-24) Arce Fernández,Nilthon
In Peru, confined masonry houses are self-built, which makes it crucial to determine their seismic vulnerability. The objective of the research was to estimate the seismic vulnerability of confined masonry dwellings in the Pueblo Libre-Jaén sector using assembly algorithms. A database was constructed with data obtained from the National Institute of Civil Defense (INDECI), scientific articles, and theses. Subsequently, the data set was divided into a training set (80%) and a validation set (20%), employing the stacking method with five combinations CB_1, CB_2, CB_3, CB_4, and CB_5. The basic algorithms Gradient-Boosting, Random-Forest, Extra-Tree, and Decision-Tree were utilized as the base algorithms, with the final estimator being the Random Forest Meta-Learner. The models were trained and validated in Python, achieving accuracies of 94.95, 95.48, 95.39, and 95.66 for the base models and 95.62, 95.23, 95.76, 95.90, and 94.80% for the ensemble models. The most accurate models were the simple Gradient Boosting (95.66%) and the assembled models CB_3 (95.76%) and CB_4 (95.90%). The CB_4 model, which is composed of the Decision Tree and Gradient Boosting algorithms, was applied to the Pueblo Libre sector and yielded a reliability estimate of greater than 95% for the seismic vulnerability of confined masonry. This estimate was classified as high (1.48%), moderate (32.85%), and low (65.67%). It is anticipated that the model implemented will enable engineers and authorities to implement mitigation measures to reinforce housing in the event of a seismic event.
Climatic Aggressiveness and Precipitation Concentration in a Peruvian Amazon Basin: Alto Huallaga Interbasin
(Revista Politecnica, 2025-05-31) Piedra Tineo,José Luis; Cayatopa Calderon,Billy Alexis
Precipitation in the central Peruvian Amazon is characterized by being seasonal and with strong intensities during the first months of the year, leading to flooding and the subsequent collapse of the local infrastructure in provinces of San Martin, Huanuco, Pasco and La Libertad Regions of Peru, which are located within the delimitation of the Alto Huallaga Interbasin. Therefore, the objective of this research was to evaluate the climatic aggressiveness and concentration precipitation in the Amazon basin, applying three indices of aggressiveness and a precipitation concentration index (ICP), estimated from the precipitation record of the climatic stations in the study area. The results show a very high correlation between mean precipitation and altitude (R2 = 0.72) and with respect to the aggressiveness, the modified Fournier-Maule index (IFMM) was the one with the best correspondence with respect to altitude (R2 = 0.72) and mean precipitation (R2 = 0.98), however, the ICP shows moderate correlations with altitude (R2 = 0.21) and mean precipitation (R2 = 0.16). Likewise, the extreme values of the different indices were estimated for different return periods and a multiple linear regression model was developed to relate climatic aggressiveness and the ICP to estimate the mean precipitation (R2 = 0.99). Finally, it is concluded that, the Alto Huallaga Interbasin presents a very low climatic aggressiveness and the concentration of rain is moderately seasonal.
Coffee Rust Severity Analysis in Agroforestry Systems Using Deep Learning in Peruvian Tropical Ecosystems
(Agriculture, 2024-12-27) Ocaña Zúñiga,Candy Lisbeth
Agroforestry systems can influence the occurrence and abundance of pests and diseases because integrating crops with trees or other vegetation can create diverse microclimates that may either enhance or inhibit their development. This study analyzes the severity of coffee rust in two agroforestry systems in the provinces of Jaén and San Ignacio in the department of Cajamarca (Peru). This research used a quantitative descriptive approach, and 319 photographs were collected with a professional camera during field trips. The photographs were segmented, classified and analyzed using the deep learning MobileNet and VGG16 transfer learning models with two methods for measuring rust severity from SENASA Peru and SENASICA Mexico. The results reported that grade 1 is the most prevalent rust severity according to the SENASA methodology (1 to 5% of the leaf affected) and SENASICA Mexico (0 to 2% of the leaf affected). Moreover, the proposed MobileNet model presented the best classification accuracy rate of 94% over 50 epochs. This research demonstrates the capacity of machine learning algorithms in disease diagnosis, which could be an alternative to help experts quantify the severity of coffee rust in coffee trees and broadens the field of research for future low-cost computational tools for disease recognition and classification
Comparison of Collinearity Indices for Linear Models in Agricultural Trials
(Journal of Biological Sciences, 2023-12-28) Garrido Campaña,Zadith Nancy
The deleterious consequences of collinearity in linear regression on the precision of estimators of regression coefficients and the interpretability of the fitted model are widely recognized. In this study, we compare several methodologies for assessing collinearity in linear models and explore the effect of outliers on collinearity. The robustness of collinearity measures (individual and overall) is validated through two detailed Monte Carlo simulation study which also considers the effect of outliers on collinearity indices. The methods are illustrated with two real-world agricultural and fish morphology l data sets to show potential applications. The results do not provide any evidence for an effect from outliers on collinearity identification using the collinearity indices (individual and overall). The FG and Fj collinearity indices more robust as both sample size and collinearity degree increase. The VIF (individual measure) had a better performance on the fitted model with a greater number of parameters.
Comparison of non-destructive methods for estimating the leaf area of Cinchona officinalis L. using digital image processing
(Revista Cubana de Ciencias Forestales, 2025-09-11) Huaccha Castillo,Annick Estefany
Cinchona officinalis it is an important plant species and was the only treatment for malaria for over three centuries. The aim of this study was to compare the accuracy of four non-destructive digital image processing methods (LeafArea and three ImageJ algorithms)for estimating the leaf area of young C. officinalis plantations under two establishment conditions: forest stands and enrichment strips. Leaves were photographed at a distance of 8 cm using a 24 MP smartphone and processed with the evaluated methods. Statistical analysis included box and whisker plots, Pearson correlation, and Friedman test. The results showed that ImageJ methods M3 and M4 had the highest accuracy (r = 0.99), with no significant differences between them, and overestimations detected in M1 and M2. It is concluded that M3 and M4 are fast, low-cost, and highly accurate options for foliar monitoring of C. officinalis in the field.
Current and Future Spatial Distribution of the Aedes aegypti in Peru Based on Topoclimatic Analysis and Climate Change Scenarios
(Insects, 2025-05-02) Ocaña Zúñiga,Candy Lisbeth
Dengue, a febrile disease that has caused epidemics and deaths in South America, especially Peru, is vectored by the Aedes aegypti mosquito. Despite the seriousness of dengue fever, and the expanding range of Ae. aegypti, future distributions of the vector and disease in the context of climate change have not yet been clearly determined. Expanding on previous findings, our study employed bioclimatic and topographic variables to model both the present and future distribution of the Ae. aegypti mosquito using the Maximum Entropy algorithm (MaxEnt). The results indicate that 10.23% (132,053.96 km2) and 23.65% (305,253.82 km2) of Peru’s surface area possess regions with high and moderate distribution probabilities, respectively, predominantly located in the departments of San Martín, Piura, Loreto, Lambayeque, Cajamarca, Amazonas, and Cusco. Moreover, based on projected future climate scenarios, it is anticipated that areas with a high probability of Ae. aegypti distribution will undergo expansion; specifically, the extent of these areas is estimated to increase by 4.47% and 2.99% by the years 2070 and 2100, respectively, under SSP2-4.5 in the HadGEM-GC31-LL model. Given the increasing dengue epidemic in Peru in recent years, our study seeks to identify tools for effectively addressing this pressing public health concern. Consequently, this research serves as a foundational framework for assessing areas with the highest likelihood of Ae. aegypti distribution in response to projected climate change in the second half of the 21st century.
Current and Future Spatial Distribution of the Genus Cinchona in Peru: Opportunities for Conservation in the Face of Climate Change
(Sustainability- MDPI, 2023-09-23) Ocaña Zúñiga,Candy Lisbeth; Vergara Anticona,Alex Joel; Cieza Tarrillo,Dennis Alvarino; Quiñones Huatangari,Lenin; Idrogo Vasquez,Guillermo; Muñoz Astecker,Lucas Dalvil; Auquiñivin Silva,Erick Aldo; Cruzalegui Fernandez,Robert Javier; Arbizu Berrocal,Carlos Irvin
The genus Cinchona belongs to the Rubiaceae family and comprises native Peruvian tree species distributed in tropical areas. It is currently endangered due to human disturbance and overexploitation for medicinal, forestry and food uses. To date, the current and future distribution of Cinchona spp. under the climate change scenario is unknown. Here, we modeled the present and future spatial distribution of the genus Cinchona using bioclimatic, edaphic and topographic variables using the maximum entropy algorithm (MaxEnt). The results indicate that 8.08% (103,547.89 km2) and 6.02% (77,163.81 km2) of the surface of Peru possesses areas with high and moderate distribution probabilities, respectively, to host the genus Cinchona, distributed mainly in the departments of Cusco, Amazonas, San Martín and Cajamarca. Furthermore, according to future climate scenarios, the areas of high suitability will increase their extension for the years 2050 and 2070 by 3.65% and 3.9%, respectively. Since Peru seeks to promote the forest sector to be the other force for its development, this study can be considered as a basis for the establishment of priority zones for the conservation, restoration, reforestation and sustainable management of Cinchona spp. species in Peru.
Detection of Rust Emergence in Coffee Plantations using Data Mining: A Systematic Review
(OnLine Journal of Biological Sciences, 2022-09-03) Ocaña Zúñiga,Candy Lisbeth; Quiñones Huatangari,Lenin; Huaccha Castillo,Annick Estefany; Milla Pino,Manuel Emilio
Hemileia vastatrix is a fungus that causes coffee rust disease and, depending on the level of severity, reduces the photosynthetic capacity of the plant and of new shoots, leading to low coffee yields and even death; its symptoms are visible on the leaf. Systems based on computer algorithms have been developed to predict diseases and pests in coffee. The objective of the manuscript was to analyse the detection of rust occurrence in coffee plantations, through field determinations of climatological, agronomic and crop management variables using data mining algorithms. A systematic review of studies published from 2001 to 2021 was carried out in the Scopus, Ebsco Host and Scielo databases, considering as an inclusion criterion the works that used experimental design in data collection. The studies included in this review were 22, 64% of which came from the top two coffee-roducing countries in Latin America (Brazil and Colombia); the analysis of these studies revealed that the input variables were climatic, soil fertility properties, management and physical properties of the crops. In addition, they used supervised (decision tree, artificial neural networks, multiple linear regression, among others) and unsupervised (clustering) algorithms, with the support of experts in the study of the fungus and used statistics such as coefficient of determination, root mean square error, among others, to validate the proposals. Overall, this systematic review provides evidence of the effectiveness of data mining algorithms implemented to detect the occurrence of rust in coffee plantation
Determination of hydration kinetic of pinto beans: A hyperspectral images application
(Measurement: Food, 2024-03-30) Arteaga Miñano,Hubert Luzdemio
Hydration is a typical operation applied to legumes before cooking, reducing time and the associated energy cost. To monitor the process, mass balance method is the most used methodology, despite this method is destructive, repetitive, and time-consuming. For that reason. hyperspectral techniques are presented as an alternative for assessing the hydration process since it is a noninvasive method. Therefore, the objective of this work was to evaluate the technique of hyperspectral imaging for studying the hydration kinetics of pinto beans. For this purpose, a sample of pinto beans was hydrated in distilled water, determining moisture content during the process and taking hyperspectral images by reflectance mode, in the range 400 to 800 nm until constant mass. The moisture content was modelled using Peleg and a sigmoidal model. Next, the images were pre-treated and the median spectral profile for each bean was obtained. Then, a regression model was fitted, using the wavelength that maximized the coefficient of determination (R2) and minimized the root mean square error (RMSE). The results show that Peleg model fit experimental data with R2 in the range of 0.974 to 0.989 while sigmoidal model of 0.997 to 0.999. On other hand, mean spectral profiles at 632 nm and sigmoidal model give the higher metrics 0.997 and 38.3 for R2 and RMSE respectively. The results showed that hyperspectral imaging in reflectance mode is a tool
Determination of the Compressive Strength of Concrete Using Artificial Neural Network
(Universidad Nacional de Jaén, 2024-03-31) Quiñones Huatangari, Lenin
The objective of the work is to estimate the compressive strength of concrete by means of the application of Artificial Neural Networks (ANNs). A database is created with design variables of mixtures of 175, 210, and 280 kgf/cm², which are collected from certified laboratories of soil mechanics and concrete of the city of Jaen. In addition, Weka software is used for the selection of the variables and Matlab software is used for the learning, training, and validation stages of ANNs. Five ANNs are proposed to estimate the compressive strength of concrete at 7th, 14th, and 28th day. The results show that the networks obtain the average error of 4.69% and are composed of an input layer with eleven neurons, two hidden layers with nine neurons each, and the compressive strength of concrete as the output. This method is effective and valid for estimating the compressive strength of concrete as a non-destructive alternative for quality control in the construction industry.
Dielectric spectroscopy for the prediction of pork quality during the post-mortem time
(Journal of Food Composition and Analysis, 2025-08-05) Arteaga Miñano,Hubert Luzdemio
Dielectric spectroscopy was used in this study to predict and classify pork quality during the post-mortem time. Eighty ∼1 kg- longissimus dorsi muscles were collected and stored at 4 ± 1 °C and pH, instrumental color, and dielectric properties (ɛ' and ɛ'') were subsequently determined in the microwave range (0.5–9 GHz) at 3, 4, 5, 6, 7, 8, 9, 10 and 24 h post-mortem (hpm), as well as moisture at 8 hpm and drip weight loss at 24 hpm. Of the 80 pork samples, two types of meat were found. RFN (33) and DFD (47) between males and females. Quality parameters: RFN (pH=5.708–5.714; L*=43.341–43.692; moisture (%) = 68.857–69.604; drip loss = 1.655–1.833) and DFD (pH=6.154–6.177; L*=40.152–41.91; moisture (%) = 69.032–69.9; drip loss = 1.129–1.693). Quality parameter predictions during muscle-to-meat transformation showed R² of 0.743 (pH), 0.811 (L*) and 0.603 (C*) for DFD meats with PLSR (full) and R2 of 0.359 (pH), 0.558 (L*) and 0.284 (C*) for RNF meats with PLSR (optimized) from male pigs. of 0.412–0.637 for pH, L* and c* for RFN and DFD meats from female pigs with PLSR (optimized). Dielectric spectroscopy predicts pork quality moderately well, but models that are more robust are needed to improve predictions of internal pork quality
Effect of arbuscular mycorrhizae on the growth of cinchona officinalis L. (rubiaceae) in nursery
(Universidad Nacional de Jaén, 2024-04-27) Fernandez Zarate,Franklin Hitler; Huaccha Castillo,Annick Estefany; Quiñones Huatangari,Lenin; Vaca Marquina,Segundo Primitivo; Sanchez Santillan,Tito; Guelac Santillan,Marly; Seminario Cunya,Alejandro
Cinchona officinalis, commonly called cascarilla or quina, has medicinal value; and rea Peru’s national coat of arms representing its plant wealth (flora), however, it is threatened by anthropogenic activities. This study aimed to determine the effect of the rea ctorea cto Myco Grow® on the growth of C. officinalis in nursery. A randomized design was used with two treatments, one with Myco Grow® application (WM) and the other without incorporating this rea cto rea cto (NM). Each treatment had three replicates consisting of 30 plants each. Monthly evaluations were performed, during which the number of dead plants, plant height, and plant diameter were recorded. Additionally, at the end of the study, the anhydrous weight of leaves, stems, and roots; leaf rea; mycorrhizal frequency; mycorrhizal colonization index; and the length of extra-radicular mycelia were determined. The WM treatment achieved 36.6% lower mortality, 38.01% greater height, and 48.52% greater diameter re the NM treatment. Additionally, inoculation with arbuscular mycorrhizae (AM) improved the anhydrous weights of the leaves, stems, roots, and leaf rea by 84.31%, 84.28%, 70.85%, and 76.91%, respectively. Regarding the three fungal variables analyzed for the WM treatment; mycorrhizal frequency was 87%, AM application led to a mycorrhizal intensity of 7.7% and an extra-radicular mycelium length of 90.3 cm. This study confirmed that AM positively influences the growth of C. officinalis in the nursery and can be used to sustainably produce this species on a large scale.
Effect of salt reduction, mixture of salt with animal fat, and salt particle sizes on instrumental texture, yield properties and sensory characteristics of burgers
(Springer Nature Link, 2024-10-01) Rios Mera,Juan Dario
This study aimed to investigate the impact of reduction of salt content (from 1.5 to 0.75%), the technique of mixing half of the salt content with animal fat, and the salt particle size on the instrumental texture, cooking losses, diameter reduction, overall liking, and sensory characteristics of burgers. The results showed that regardless of the types of micronized salt (MS < 250 µm) incorporation (directly into the meat or the mixture of half of the MS with the meat and the other half with the fat), salt reduction decreased the salty perception and the instrumental hardness and chewiness. Thus, the mixture of MS with fat does not present sensory improvements nor overcome the texture effects of salt reduction. In a second experiment, the effect of different particle sizes (from <177 µm to 1 mm) was evaluated, where it was observed that salt with particle size <177 µm decreased the burgers’ hardness, cooking losses, and diameter reduction. The salt particle sizes did not cause sensory changes in the burgers, and in both experiments, the overall liking was greater than 7 points on the 9-point hedonic scale. Salt < 177 µm could be a good option for reducing salt in burgers and possibly in other meat products.
Effect of synthetic fertilization 1rea on the diameter increase, height and mortality of Cinchona officinalis L. (Rubiaceae)
(Universidad Nacional de Jaén, 2024-04-18) Fernandez Zarate,Franklin Hitler; Huaccha Castillo,Annick Estefany; Quiñones Huatangari,Lenin; Vaca Marquina,Segundo Primitivo; Goñas Goñas,Malluri; Milla Pino,Manuel Emilio; Seminario Cunya,Alejandro
Cinchona officinalis, is a South American tree species, commonly used for medicine, and is currently threatened by agricultural 1rea1cto1 and cattle ranching. The objective was to determine the effect of chemical fertilization on the nursery growth to increase growth potential and survival of C. officinalis. A completely randomized design with six treatments and three replicates was used; 20 C. officinalis plants were used per replicate. Two months after transplanting the C. officinalis seedlings to the polyethylene bags, inorganic fertilizer (YaraMila® HYDRAN) was applied. Monthly evaluations were carried out and the number of dead plants, plant height, diameter and number of leaves were recorded. The highest mortality rate was recorded when fertilizer was applied (73%) while in the non-fertilized treatment mortality reached 36%. Regarding the increase in height, diameter and number of leaves in all cases, the best results were obtained in the fertilized treatments, exceeding by 85, 70 and 17% (respectively) those obtained in the treatment to which fertilization was not applied. This study shows the effects that the application of fertilizers to C. officinalis plants at the nursery level can have on growth and mortality variables, the results suggest the use of this 2rea2cto for a sustainable and large-scale production of this species taking into consideration the appropriate 2rea2c
Electric Motor Simulator for Didactic Support by Means of an Electromechanical Mathematical Model
(IIETA, 2024-10-31) Arce Fernández,Nilthon
El objetivo de esta investigación es desarrollar un simulador de motor eléctrico basado en un modelo matemático electromecánico, que pueda utilizarse como herramienta didáctica para la enseñanza de cursos en laboratorios de ingeniería mecánica, eléctrica y electromecánica. Se empleó un método analítico para estudiar los principios y elementos de todas las partes de un motor de CC y una técnica experimental para la recopilación de datos; se empleó el lenguaje de programación Python para realizar el análisis de datos. En la validación del modelo, se encontró una correlación de 0,775 para la corriente; es decir, la fuerza de asociación es alta, y una correlación de 0,94 para la velocidad, lo que explica una fuerza de asociación muy alta. Además, el error cuadrático medio en la corriente es de 0,002, mientras que el error cuadrático medio en la velocidad es de 1,189. Los resultados numéricos ilustran la robustez y estabilidad del modelo matemático. La investigación tiene contribuciones tanto académicas como sociales, y sirve de base para futuras investigaciones relacionadas con el modelado matemático en el campo de la ingeniería mecánica, eléctrica, electromecánica y de control. En futuras investigaciones, el objetivo es modelar varios tipos de motores y posteriormente desarrollar un multisimulador de motores eléctricos con fines educativos y económicos

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