Repositorio Institucional Universidad EAFIT ::Examinando por Materia "PRODUCTIVIDAD AGRÍCOLA"

Examinando por Materia "PRODUCTIVIDAD AGRÍCOLA"

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Análisis de los factores que limitan la mejora económica de los productores rurales organizados en el distrito de Yarabamba, Provincia de Arequipa – Perú - 2015
(Universidad EAFIT, 2018) Rocha Miranda, Andreé José; Vargas Sáenz, Mario Enrique
Análisis departamental de los factores productivos y su influencia en los cultivos transitorios en Colombia para el 2022
(Universidad EAFIT, 2024) García Guette, David Mauricio; Chacón Indaburo, María Fernanda; Zuluaga Orrego, Juan Fernando
This research determines the main productive factors that influenced the production of transitional crops in the departments of Colombia for 2022. We establish the importance of these to improve the conditions of Colombian agriculture through the prioritization of the most important productive factors in this type of crops, contributing to analytical mechanisms that allow a better articulation of the actors in the territories where transitional crops predominate. The analytical development made it possible to establish through a mixed methodology within which the sequential use of statistical techniques such as the Lasso regression model, Stepwise Regression and Random Forest stands out that access to land and financing were the most significant elements in the production of transitional crops for 2022 with 75.2% 15.4% respectively. The study suggests that these factors be prioritized for the articulation of actors and the prioritization of public goods for productivity and territorial development in the departments of Colombia.
Análisis marginal del uso de aminoácidos para potencializar fertilizantes en bananera de Ecuador-Los Ríos
(Escuela Agrícola Panamericana Zamorano, 2023) Grandes Navarro, Franz Richelieu; Reconco, Rommel
Characterization of Phytosanitary Risks in Agricultural Crops using Multispectral Images
(Universidad EAFIT, 2025) García Montenegro, Michell; Peña Palacio, Juan Alejandro; Martínez Vargas, Juan David
Desarrollo de un plan de negocios para exportación directa de fruta fresca de banano
(Universidad EAFIT, 2024) Cabuya Gómez, Laura Daniela; Godoy, Álex Jharjeny
Determinantes de la volatilidad del precio interno del café en el mercado colombiano entre los años 2015 y 2022
(Universidad EAFIT, 2024) Chávez Pinzón , Laura María; Pardo Calderón, Lina María; Cruz Castañeda, Vivian
Colombia is a country recognized worldwide for its agricultural products, especially for its coffee. Ninety-six percent of the coffee producers are small farmers that are exposed daily to the fluctuation of prices in the international market and, in many occasions, this dependence does not cover their production costs, encouraging the exit or little participation of the producers in the coffee industry. The main variables that influence the behavior of internal coffee prices are: the price of the C contract, the quality premium and the exchange rate. In this study a quantile regression of the returns of internal coffee prices as a function of the conditional volatility of the returns of the C Contract and the TRM, between the years 2015 and 2022, using ARMA-GARCH models, was carried out. The most impactful results show that a unit increase in the conditional volatility of the TRM returns at the 0.95 quantile generates an increase in domestic coffee returns by 0.97% and that a unit increase in the conditional volatility of C contracts generates an increase of 0.31% in the returns of domestic coffee prices. This study offers valuable insights that can contribute to improve the resilience and sustainability of the Colombian coffee industry. Furthermore, by identifying the factors that influence domestic coffee prices, this study lays the foundation for future research and policies aimed at mitigating volatility and promoting more equitable and stable conditions for coffee producers in the country.
Efecto antimicrobiano de extractos obtenidos de residuos agroindustriales en un microorganismo aislado del tomate de árbol
(Universidad EAFIT, 2020) Mesa González, Alejandra; Orozco del Corral, Marcela; Lopera Pérez, Yasmin Eliana; Marín Palacio, Luz Deisy
The tamarillo is a fruit native to South America, of great production in Colombia, especially in the department of Antioquia. Its production, like that of most agricultural products, is affected by the emergence of diseases caused by microorganisms, generating significant losses in production. Natural extracts with antimicrobial activity are considered an alternative to control the emergence of these diseases. The purpose of this work was the identification of a microorganism isolated from the diseased tamarillo and the evaluation of the antimicrobial activity on this of extracts obtained from mint, oregano, papaya seeds and orange peel. The extracts were obtained; using hydrodistillation and the Soxhlet extraction method. By the first method, only the oily phase could be extracted from the orange peel; for the rest of the materials, aqueous extracts were obtained. While by Soxhlet the oily phase of mint, oregano and papaya seeds was recovered. The microorganism that was isolated was identified in the company AOXLAB as Colletotrichum acutatum and the minimum inhibitory capacity of the extracts obtained on it was evaluated. This allowed determining that the oily extract of the papaya seeds was the only one capable of inhibiting the fungus with a concentration of 1250 mg/L. The oily papaya extract was subsequently nanoencapsulated in niosomes in order to compare its encapsulated and unencapsulated antimicrobial potential. This test allowed finding that the encapsulation process reduces the required minimum inhibition concentration to 78.13 mg/L.
Estimación del crecimiento poblacional de Leptopharsa Gibbicarina en palma de aceite (caso de estudio)
(Universidad EAFIT, 2025) Salazar Hoyos, Alejandro; Restrepo Arias, Juan Felipe
Estimación del efecto de las variables ambientales en la producción agrícola exportable en Antioquia usando modelos de ML
(Universidad EAFIT, 2025) Páez Bermúdez, Johan Stiven; García Vargas, Johan Felipe
Estudio de prefactibilidad para evaluar la viabilidad de transferir prototipos derivados de la producción de aguacate y cacao en el Centro de Desarrollo Tecnológico Agroindustrial de la Universidad Tecnológica de Pereira
(Universidad EAFIT, 2023) García Tobar, Andrés Felipe; Carrillo Caballero, Dairo Rafael; Zartha Sossa, Jhon Wilder; Díez Benjumea, Jhon Miguel
Evaluación del potencial adsorbente de la semilla de aguacate para la remoción de un colorante
(Universidad EAFIT, 2023) Salgado Durango, María Fernanda; Ospino Mulett, Gabriela María; Estrada Giraldo, Catalina
Heterogeneous effects of agricultural technical assistance in Colombia
(Universidad EAFIT, 2019) Torres Franco, Nicolas Arturo; Dávalos Álvarez, Eleonora; Morales Zurita, Leonardo Fabio
La aplicación de la agricultura de precisión en el proceso de fertilización: Un caso de estudio para el sector bananero del Urabá-Antioqueño
(Universidad EAFIT, 2018) Alcaraz Restrepo, John James; Jiménez Trespalacios, Juan Gonzalo; Gómez Cifuentes, Alfonso de Jesús
This paper has as main objective to analyze the effect of applying precision agriculture in the nutrition program of a banana farm, and compare its results with traditional agriculture, in terms of financial benefits from cost reductions in the use of chemical fertilizing supplies -- To evaluate this effect, the net present value methodology was used, comparing two cash flows: a negative one, that is the initial investment (cost of soil analysis using direct and remote sensors), and a positive one, that is the result of the investment (cost savings of the fertilization program) -- These values were sensitized with the value of money over time, to be equivalent and comparable -- Applying precision agriculture, the result obtained in the farm was a 5% saving in the fertilization program, compared to conventional ones -- The decrease in the use of fertilizers resulted in economic benefits and positive environmental effects, allowing the return on the made investment by adopting the new technology -- The present paper is an important starting point for future research -- In the literature review, little information was found regarding precision agriculture in the banana production in Colombia
Lenguaje de modelado de arquitectura para sistemas ciber-físicos adaptativos
(Universidad EAFIT, 2020) Londoño Londoño, Luis Fernando; Mazo Peña, Raul
It is becoming increasingly common for systems to be dynamically adapted to changing contexts at run time. Such systems exhibit degrees of variability that depend on the fluctuations of the runtime in their contexts. Although dynamic variability has been addressed by long-established concepts in the field of system families, this approach is considered insufficient to meet the needs of distributed and dynamically adaptive systems such as IoT (Internet of Things)-based intelligent agriculture systems considered cyber-physical systems. These systems are required to improve the productivity and competitiveness of Colombian agricultural production. For dynamically adapted systems, approaches to support the variability of cyber-physical systems may not be just component specializations or restrictions on system variables since often the operating conditions of these systems are not predictable. In this study that seeks to establish the most appropriate techniques for managing dynamic variability in self-adapting systems, it has been necessary to address architecture modeling as a key practice in software engineering. It is considered that a modeling language that allows to represent such systems will be definitive for the production of systems with the level of quality and reliability that is required. All the results of this research are focused on enabling development companies, the tools that allow them to increase the productivity, flexibility and quality that cyber-physical systems require for agriculture. For the study it will be necessary to analyze the literature to create a language that improves the state of the art and to evaluate and perform at least one test case of a real system, this will allow to validate the proposed language. This work starts from the premise that that language should allow you to specify software, hardware, monitoring, and action components on the physical environment of each system and represent physical objects that are part of the system to be deployed. In order to test the novel nature of the proposed language, this study includes a comparison with other modeling languages proposed by the world's academic and industrial community. Finally, the study will result in a language of modeling the architecture of self-adapting systems, seen as a family or individually. The language is implemented in the VariaMos platform (http://variamos.dis.eafit.edu.co/#/) seeking to show that it can be used to represent, at the same time, reference architectures and individual system architectures, thanks to the mechanisms offered by the tool to represent and manipulate variability. The justification for the validity of the use of the proposed language is made from the presentation of a real case of a smart greenhouse. It is intended to be able to demonstrate that: (i) The modeling language has characteristics that give the possibility to represent elements such as physical and environment objects that other languages do not allow and extends the possibilities of designing cyber-physical systems (ii) The language has elements that expand the possibility of specifying in models, the components of variability that an architecture for a self-adapting cyber-physical system requires in its representation. (iii) The architecture modeling language for self-adapting cyber-physical systems while designed with IoT system design as a benchmark in a software product line domain, this language can be extended to design other cyber-physical systems.
Piloto Centro de Transferencia Tecnológica para el sector del Agro
(Universidad EAFIT, 2016) Álvarez Sánchez, Camilo; Bedoya Bayer, Andrés Felipe; Vargas Sáenz, Mario Enrique
Precision agriculture for grazing and animal health management : a case study in Colombia
(Universidad EAFIT, 2023) García Hoyos, Rodrigo Junior; Aguilar Castro, José Lisandro
In this research, we address the problem of fattening management and animal health in rotational grazing. For the study of this problem, we have positioned ourselves in the framework of the paradigm of precision farming, a technological approach that uses advanced information and communication tools and techniques to optimize agricultural and livestock production processes. In this context, precision livestock farming focuses on the use of technologies to improve grazing management and animal health on cattle farms. Some objectives of precision livestock farming are to increase farm efficiency and productivity, improve product quality and reduce production costs. In addition, it also contributes to environmental sustainability by enabling more efficient management of natural resources and reducing negative impacts on the environment. Although precision livestock farming offers many opportunities to improve efficiency and sustainability in livestock production, it also presents challenges that must be addressed for successful implementation. To address this problem, our objective was to develop methodologies, models, and approaches to support decision-making related to productivity management and animal health. To achieve this objective, several sub-objectives were raised, the first one was to develop a precision livestock farming architecture based on emerging technologies (Industry 4.0, artificial intelligence, etc.), the second on developing generic knowledge models of precision livestock farming for animal health and herding management and finally, in the third to develop meta-intelligent models for precision livestock farming in the context of autonomous grazing and animal health management. In general, several research articles were developed to meet the objectives proposed in this thesis. Initially, a review article on the latest trends in precision livestock farming using machine learning techniques was carried out. On the other hand, for the first specific objective, an article was conducted where three autonomous cycles of data analysis tasks based on autonomous computing were proposed for a beef production process for precision livestock farming. To meet the second specific objective, three articles were proposed. The first is a beef cattle weight identification model using machine learning techniques for anomaly detection, the second presented a system for monitoring the cattle fattening process in rotational grazing using fuzzy classification, in the third, a multi-objective optimization model was developed to maximize weight gain of cattle in rotational grazing. Regarding the third objective, three articles were developed, the first one proposed an autonomous cycle of data analysis tasks for the self-supervision of animal fattening in the context of precision livestock farming, and the second article presents a management system for the cattle fattening process in rotational grazing by means of diagnostic and recommendation systems. Finally, the last article proposed the use of the meta-learning paradigm in a cattle weight identification system for anomaly detection. In each article, we evaluated the strategies/models using various datasets. The results showed the capacity of the developed methodologies and models for decision-making in the management of the livestock production process. Specifically, our proposals allow the management of fattening and animal health in rotational grazing, considering, among other things, monitoring, diagnosis, and optimization of the productive process, with good results in performance metrics.
Predicción del rendimiento de cultivos agrícolas en los cinco corregimientos de la ciudad de Medellín, utilizando modelos de Machine Learning
(Universidad EAFIT, 2024) Gómez Arango, Alba Miriam; Valencia Diaz, Edison; Zuluaga Orrego, Juan Fernando
In a global context where agriculture and food production play a crucial role in food security, employment, and sustainability, this study focuses on predicting the yield of agricultural crops in the five districts of Medellín. The main objective is to design a prediction model for nine local crops using machine learning techniques. Medellín is distinguished by its diversity of crops, including peri-urban agriculture characterized by productive small plots distributed across various chagra-type crops. These traditional agricultural practices are carried out by an aging population of farmers. Accuracy in yield prediction becomes essential, as a significant portion of the production is dedicated to self-consumption, with a subsistence focus. However, surpluses are also traded, directly impacting the food security of the local community. The results highlight the effectiveness of machine learning models, particularly Boosting models such as PCA Random Forest and PCA XGB Boosting, in predicting the crops under study. These models demonstrate the ability to capture relationships between variables and the heterogeneity present in territorial production. However, opportunities for improvement related to reducing model errors have been identified, which can be addressed through continuous data collection and technical support provided to farmers. This will not only increase data availability but also contribute to refining the model and understanding performance behavior in the analyzed crops, facilitating decision-making in the agricultural sector of the municipality of Medellín. This project represents a valuable tool for professionals in the agricultural sector and institutions responsible for planning and agricultural development. It offers an innovative approach to sector data analysis, leveraging the advantages of data science. Through these techniques, opportunities are opened to establish strategies, plans, and projects that contribute to crop planning, the management of productive areas in the municipality, and the strengthening of local food security.
TERRA SABIA: caso de bioinnovación en la medición del estado de la red alimenticia del suelo como tecnología para la producción agrícola
(Universidad Eafit, 2020) Montoya Rojas, Nicolás; Sierra Zapata, Laura

Examinando por Materia "PRODUCTIVIDAD AGRÍCOLA"

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