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Ítem 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,AlejandroCinchona 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.Ítem 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,AlejandroCinchona 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 2rea2cÍtem 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 EmilioHemileia 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 plantationÍtem Gis and fuzzy logic approach for forest fire risk modeling in the Cajamarca region, Peru(Growing Science, 2023-06-03) Ocaña Zúñiga,Candy LisbethForest fires are a potential threat to life, as they contribute to reducing forest areas, impact on the services we expect from ecosystems, the health of the inhabitants is affected by smoke and the economic costs for the recovery of affected areas is high. The objective of the study is to apply fuzzy logic to model the risk of forest fires in the Cajamarca-Peru region, incorporating variables that represent biological, topographic, socioeconomic, and meteorological factors. The analysis was based on the acquisition, editing and rasterization of the database, application of fuzzy membership functions and image fuzzification, fuzzy superposition and spatial reclassification of forest fire risk. The results obtained show that 71.68% of the area is under very low or medium forest fire risk. However, 28.32% of the study area has a high to very high fire risk, which makes the occurrence of fires susceptible to the lack of rain and water in the soil. It was found that biological, topographic, and socioeconomic factors with their respective variables are directly influenced by meteorological factor variables such as temperature, rainfall and water availability. Fuzzy logic offered flexibility in modeling wildfire risk in the region, proving to be a useful tool for predicting and mapping wildfire risk.Ítem 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 LisbethThe 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 %Ítem 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 IrvinThe 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.Ítem Determination of the Compressive Strength of Concrete Using Artificial Neural Network(Universidad Nacional de Jaén, 2024-03-31) Quiñones Huatangari, LeninThe 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.Ítem Implementing the Sustainable Development Goals in University Higher Education: A Systematic Review(Universidad Nacional de Jaén, 2024-03-31) Quiñones Huatangari,Lenin; Huaccha Castillo,Annick Estefany; Ocaña Zuñiga,CandyThe role of higher education institutions in promoting sustainability is realised through scientific research and academic activities. It is therefore essential to explore strategies to assess and monitor the implementation of sustainable practices in these institutions. This study set out to examine the mainstreaming of the Sustainable Development Goals (SDGs) in higher education institutions. The methodology used was a systematic review of research articles in the Scopus database, conducted between 6 and 20 January 2023. The inclusion criteria covered global university experiences in implementing the SDGs. The review revealed that 28.56% of the publications included were from European universities, 24% from the Americas, 13% from Asia and a smaller number from Oceania (5%) and Africa (2%). The analysis identified indicators to assess adherence to the SDGs, such as number of publications, institutional affiliation, number of reports, disciplinary field, type of course, number of essays, subject area, student/classroom ratio and age of participants. The data collection instruments used were questionnaires, interviews, published articles and field notes. This systematic review details the concern of higher education institutions to measure the impact of their activities in relation to the SDG guidelines, as well as a critical and decision-oriented summary for institutions wishing to initiate the procesÍtem Noise estimation using an artificial neural network in the urban area of Jaen, Cajamarca(Universidad Nacional de Jaén, 2024-03-31) Quiñones Huatangari,Lenin; Ocaña Zuñiga,CandyJaen is a city in constant urban growth which generates an increase in vehicular traffic and active noise pollution. The research presents the development of an artificial neural network (ANN) to estimate the noise produced by vehicular traffic in the urban area of the city. Consequently, information was collected from two investigations coded as T1 and T2, for which a matrix of 10 variables was elaborated with 210 and 273 data respectively. Random random sampling was performed to divide the data matrix into 80% (training) and 20% (validation). Weka software and the multi-layer perceptron (MLP) training algorithm were used to model the ANN. An ANN for T1 with 6-19-1 architecture and an ANN for T2 with 6-15-1 architecture were obtained. The performance of the ANNs was evaluated using the correlation coefficient (R), coefficient of determination (R2) and root mean square error (RMSE). The results show that the MLP networks are able to estimate the sound pressure level with values of R=0.9927, R2=0.9854 and RMSE=0.7313 for T1, R=0.9989, R2=0.9978, and RMSE=0.1515 for T2.Ítem Sound Pressure Level at Terminals through Data Mining(Universidad Nacional de Jaén, 2024-03-31) Quiñones Huatangari,LeninThe land transportation is a cause of noise in cities, thus breaking the natural balance and bringing with it physiological and mental illnesses, as well as occupational accidents. In this sense, the objective of the research was to estimate the sound pressure in land terminals in the city of Jaen, Peru, using data mining algorithms. The methodology consisted in environmentally monitoring six terminals in the city of Jaen, during 2019, using a class 1 sound level meter; the exploratory analysis of the collected variables that influence the noise of the terminals (minimum and maximum sound pressure level, number of light and heavy vehicles, and equivalent sound pressure level) was performed, which were grouped into three groups of variables for the purpose of using data mining algorithms. Three algorithms were used, namely, artificial neural network, linear regression, and M5Rules, using the free software Weka. Considering all variables, the M5Rules method performed the best, because the value of the mean absolute error (0.7462), the root mean square error (1.0575), and uncertainty analysis (0.09) was the smallest compared to the other two methods. However, for the two remaining groups of variables, the linear regression model showed the lowest mean absolute error and mean square root of the error; in addition to presenting coefficients of determination close to one. The algorithms show good behavior when estimating the sound pressure of the terminals in the city of Jaen.Ítem Non-destructive estimation of leaf area and leaf weight of Cinchona officinalis L. (Rubiaceae) based on linear models(Universidad Nacional de Jaén, 2024-03-31) Quiñones Huatangari, Lenin; Huaccha Castillo,Annick EstefanyNon-destructive methods that accurately estimate leaf area (LA) and leaf weight (LW) are simple and inexpensive, and represent powerful tools in the development of physiological and agronomic research. The objective of this research is to generate mathematical models for estimating the LA and LW of Cinchona officinalis leaves. A total of 220 leaves were collected from C. officinalis plants 10 months after transplantation. Each leaf was measured for length, width, weight, and leaf area. Data for 80% of leaves were used to form the training set, and data for the remaining 20% were used as the validation set. The training set was used for model fit and choice, whereas the validation set al.lowed assessment of the of the model’s predictive ability. The LA and LW were modeled using seven linear regression models based on the length (L) and width (Wi) of leaves. In addition, the models were assessed based on calculation of the following statistics: goodness of fit (R2), root mean squared error (RMSE), Akaike’s information criterion (AIC), and the deviation between the regression line of the observed versus expected values and the reference line, determined by the area between these lines (ABL). For LA estimation, the model LA = 11.521(Wi) − 21.422 (R2 = 0.96, RMSE = 28.16, AIC = 3.48, and ABL = 140.34) was chosen, while for LW determination, LW = 0.2419(Wi) − 0.4936 (R2 = 0.93, RMSE = 0.56, AIC = 37.36, and ABL = 0.03) was selected. Finally, the LA and LW of C. officinalis could be estimated through linear regression involving leaf width, proving to be a simple and accurate tool.Ítem Mapping density, diversity and species-richness of the Amazon tree flora(Universidad Nacional de Jaén, 2024-02-28) Marcelo Peña,José LuisUsing 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution.Ítem Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology(Universidad Nacional de Jaén, 2024-01-28) Marcelo Peña,José LuisIn a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics.Ítem Small and in-country herbaria are vital for accurate plant threat assessments: A case study from Peru(Universidad Nacional de Jaén, 2024-01-28) Marcelo Peña,José LuisHerbaria can be considered plant libraries, each holding collections of dried specimens documenting plant diversity in space and time. For many plant species, these are our only evidence of their existence and the only means of assessing their conservation status. Specimens in all herbaria, especially those in small and often under-resourced herbaria in megadiverse countries, are key to achieving accurate estimates of the conservation status of the world's plant species. They are also part of a country's shared heritage and critical contributions to knowledge of the world's diversity.Ítem More than 10,000 pre-Columbian earthworks are still hidden throughout Amazonia(Universidad Nacional de Jaén, 2024-02-28) Marcelo Peña,José LuisIndigenous societies are known to have occupied the Amazon basin for more than 12,000 years, but the scale of their influence on Amazonian forests remains uncertain. We report the discovery, using LIDAR (light detection and ranging) information from across the basin, of 24 previously undetected pre-Columbian earthworks beneath the forest canopy. Modeled distribution and abundance of large-scale archaeological sites across Amazonia suggest that between 10,272 and 23,648 sites remain to be discovered and that most will be found in the southwest. We also identified 53 domesticated tree species significantly associated with earthwork occurrence probability, likely suggesting past management practices. Closed-canopy forests across Amazonia are likely to contain thousands of undiscovered archaeological sites around which pre-Columbian societies actively modified forests, a discovery that opens opportunities for better understanding the magnitude of ancient human influence on Amazonia and its current state.Ítem 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 DarioThe 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.Ítem 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 DarioThis 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.Ítem Using pulsed magnetic fields to improve the quality of frozen blueberry: A bio-impedance approach(Universidad Nacional de Jaén, 2024-02-26) Arteaga Miñano,Hubert LuzdemioFreezing assisted by pulsed magnetic field (PMF) is an emerging technology that could be used in food preservation. This paper evaluates how PMF-assisted freezing affects the preservation of blueberry and its bioactive compounds. Blueberries were subjected to 8 PMF-assisted freezing treatments: T1 (36.8 mT/30 Hz), T2 (36.8 mT/60 Hz), T3 (36.8 mT/90 Hz), T4 (36.8 mT/20 Hz), T5 (44.7 mT/30 Hz), T6 (44.7 mT/60 Hz), T7 (44.7 mT/90 Hz), and T8 (44.7 mT/120 Hz). In treatment T9 (control), the blueberries were subjected to conventional freezing to −35 °C; T10 represents fresh blueberries. Compared to conventional freezing (T9), PMF-assisted freezing (T1 to T8) gave different parameters of temperature, nucleation time, degree of supercooling, and phase change time. The parameters achieved with T7 evidenced better behavior: smaller crystals were formed, allowing the cellular structure to be preserved, as confirmed by the electrical parameters (Re, Ri, and Cm) obtained from electrical impedance data. Moreover, T7 preserved anthocyanins and polyphenols, promoting the highest antioxidant capacity among the blueberries subjected to PMF-assisted freezing. Meanwhile, conventional freezing and PMF-assisted freezing reduced the polyphenol oxidase and peroxidase activities. In conclusion, at the laboratory level, PMF-assisted freezing preserves the blueberry cellular structures and bioactive compounds.Ítem Pijuayo (Bactris gasipaes) Pulp and Peel Flours as Partial Substitutes for Animal Fat in Burgers: Physicochemical Properties(Universidad Nacional de Jaén, 2024-02-26) Arteaga Miñano, Hubert Luzdemio; Rios Mera, Juan DarioThis study aimed to evaluate the incorporation of peach palm (PP) pulp and peel flours as substitutes for animal fat (25 and 50% substitution) in beef-based burgers. Incorporation of PP flours reduced hardness, springiness, cohesiveness, chewiness, fat, cooking losses, and diameter reduction. Burgers made with PP peel flour stood out for having low values of lipid oxidation in the two levels of fat substitution (0.14–0.23 malondialdehyde/kg) (p < 0.05). PP fruit has the potential to be utilized as a new ingredient in burgers, but future studies are needed regarding detailed sensory trials and consumer acceptance.Ítem Improving Behavior Monitoring of Free-Moving Dairy Cows Using Noninvasive Wireless EEG Approach and Digital Signal Processing Techniques(Universidad Nacional de Jaén, 2024-02-26) Arteaga Miñano, Hubert Luzdemio; -Electroencephalography (EEG) is the most common method to access brain information. Techniques to monitor and extract brain signal characteristics in farm animals are not as developed as those for humans and laboratory animals. The objective of this study was to develop a noninvasive method for monitoring brain signals in cattle, allowing the animals to move freely, and to characterize these signals. Brain signals from six Holstein heifers that could move freely in a paddock compartment were acquired. The control group consisted of the same number of bovines, contained in a climatic chamber (restrained group). In the second step, the signals were characterized by Power Spectral Density, Short-Time Fourier Transform, and Lempel–Ziv complexity. The preliminary results revealed an optimal electrode position, referred to as POS2, which is located at the center of the frontal region of the animal’s head. This positioning allowed for attaching the electrodes to the front of the bovine’s head, resulting in the acquisition of longer artifact-free signal sections. The signals showed typical EEG frequency bands, like the bands found in humans. The Lempel–Ziv complexity values indicated that the bovine brain signals contained random and chaotic components. As expected, the signals acquired from the retained bovine group displayed sections with a larger number of artifacts due to the hot 32 degree C temperature in the climatic chamber. We present a method that helps to monitor and extract brain signal features in unrestrained bovines. The method could be applied to investigate changes in brain electrical activity during animal farming, to monitor brain pathologies, and to other situations related to animal behavior.