Repositorio Nacional

The milpa agroecosystem is an intercropping of maize, beans, squash and other crops, developed in Mesoamerica, and its adoption is widely variable across climates and regions. An example of particular interest is the Yucatan Peninsula in Mexico, which holds highly diverse milpas, drawing on ancestral Mayan knowledge. Traditional milpas have been described as sustainable resource management models, based on long rotations within a slash-and-burn cycle in forest areas. Nevertheless, due to modernization and intensification processes, new variants of the approach have appeared. The objective of this study was to evaluate the sustainability of three milpa systems (traditional, continuous, and mechanized) in four case studies across the Peninsula, with emphasis on food self-sufficiency, social inclusion and adoption of innovations promoted by a development project. The Framework for the Evaluation of Agroecosystems using Indicators (MESMIS, for its Spanish acronym) was used for its flexible, participatory approach. A common group of indicators was developed despite regional differences between study cases, with a high level of farmer participation throughout the iterative process. The results show lower crop yields in traditional systems, but with lower inputs costs and pesticide use. In contrast, continuous milpas had higher value in terms of crop diversity, food security, social inclusion, and innovation adoption. Mechanized milpas had lower weed control costs. Profitability of cash crops and the proportion of forest were high in all systems. Highly adopted innovations across milpa types and study cases included spatial crop arrangement and the use of residues as mulches. However, most innovations are not adapted to local conditions, and do not address climate change. Further, women and youth participation is low, especially in traditional systems.

Milpa Intensification Processes Women and Youth Participation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SUSTAINABILITY INTERCROPPING FOOD SECURITY INNOVATION SOCIAL INCLUSION AGROECOSYSTEMS CASE STUDIES

Colaboración y co-creación de conocimiento para una agricultura sostenible

Jelle Van Loon (2021, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SUSTAINABLE AGRICULTURE AGRIFOOD SYSTEMS FOOD SECURITY CLIMATE CHANGE ADAPTATION

Climate change and agriculture: Adaptation strategies and mitigation opportunities for smallholder farmers in South Asia

Tek Sapkota (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE STRATEGIES CLIMATE CHANGE IMPACT FOOD SECURITY FOOD SYSTEMS CLIMATE-SMART AGRICULTURE SUSTAINABLE INTENSIFICATION CONSERVATION AGRICULTURE SMALLHOLDERS

Near-real-time welfare and livelihood impacts of an active war: Evidence from Ethiopia

Kibrom Abay Guush Berhane Jordan Chamberlin Mehari Hiluf Abay (2023, [Artículo])

Ethiopia recently experienced a large-scale war that lasted for more than two years. Using unique High-Frequency Phone Survey (HFPS) data, which span several months before and after the outbreak of the war, this paper provides evidence on the immediate impacts of the conflict on households’ food security. We also assess potential mechanisms and evaluate impacts on proximate outcomes, including on livelihood activities and access to food markets. We use difference-in-differences and two-way fixed effects estimation to compare trends across affected and unaffected regions (households) and before and after the outbreak of the war. Seven months into the conflict, we find that the war was associated with a 37 percentage points increase in the probability of moderate to severe food insecurity. Using the Armed Conflict Location and Event Data (ACLED), we show that exposure to an additional battle leads to a 1 percentage point increase in the probability of moderate or severe food insecurity. The conflict was associated with significant reduction in access to food through supply chain disruptions and by curtailing non-farm livelihood activities. Non-farm and wage related activities were affected the most, whereas farming activities were relatively more resilient. Our estimates, which likely underestimate the true average effects on the population, constitute novel evidence on the near-real-time impacts of large-scale conflict. Our work highlights the potential of HFPS to monitor active and large-scale conflicts, especially in contexts where conventional data sources are not immediately available.

Phone Surveys CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WAR CONFLICTS FOOD SECURITY LIVELIHOODS

Gender analysis of household seed security : A case of maize and wheat seed systems in Nepal

Hom Nath Gartaula (2022, [Libro])

Seed Security Mountains CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SEED SYSTEMS MAIZE WHEAT ROLE OF WOMEN WOMEN'S PARTICIPATION

Chapter 11. Genomic insights on global journeys of adaptive wheat genes that brought us to modern wheat

deepmala sehgal Laura Dixon Diego Pequeno Jose Crossa Alison Bentley Susanne Dreisigacker (2024, [Capítulo de libro])

Hexaploid Wheat Adaptive Genes Novel Genomic Regions Gene-Based Modeling Process-Based Modeling Global Food Security CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA HEXAPLOIDY WHEAT QUANTITATIVE TRAIT LOCI MODELLING FOOD SECURITY

Monitoreo e Instalación visual de señales a un motor eléctrico de inducción de instalación trifásica de forma jaula de ardilla, mediante la implementación de tecnología industria 4.0

Luis Ricardo Uribe Dávila (2023, [Tesis de maestría])

Vivimos la industria 4.0, misma que no es nueva, ya que sus orígenes se remontan a finales de la década de los 2000, en Alemania. Un pilar de la industria 4.0 es el análisis de datos, conocido como Big Data. El conocer los datos de un proceso, de un estudio, ayuda en gran medida a predecir el comportamiento que tendrá el proceso o la máquina a estudiar en un periodo a corto o mediano plazo. En el presente proyecto se analizan los datos arrojados por un motor eléctrico de corriente alterna, del tipo inducción, jaula de ardilla. El motor está diseñado para trabajar de manera continua, sin embargo, el uso que se le da, es meramente educativo; es decir, no sobre pasa las 15 horas por semana de uso. Mediante la toma de datos de las tres fases de corriente RMS o corriente de valor eficaz que posee el motor eléctrico que se realizará con el microcontrolador Arduino UNO, se analizarán los mismos mediante el software de cómputo numérico MATLAB, ordenando los datos, descartando valores que no aporten información relevante para lograr la predicción de datos. Por último, se llevará a conocer este proyecto a la carrera mecatrónica, área sistemas de manufactura flexible y área automatización, con el fin de que puedan observar de una mejor manera la aplicación y funcionamiento de uno de los pilares de la actual industria 4.0.

We live in industry 4.0, which is not new, since its origins date back to the late 2000s, in Germany. One pillar of industry 4.0 is data analysis, known as Big Data. Knowing the data of a process, of a study, helps greatly to predict the behavior that the process or machine will have to study in a short- or medium-term period. This project analyzes the data released by an electric motor of alternating current, of the type induction, squirrel cage. The engine is designed to work continuously, however, the use given to it is merely educational, that is; only not over spends 15 hours per week of use. By taking data from the three phases of RMS current or effective value current of the electric motor that will be made with the Arduino UNO micro controller, they will be analyzed using MATLAB numerical computing software, ordering the data, discarding values that do not provide relevant information to achieve data prediction. Finally, this project will be presented to the mechatronics career, flexible manufacturing systems area and automation area, so that they can observe in a better way the application and operation of one of the pillars of the current industry 4.0.

Mantenimiento predictivo Regresión lineal Industria 4.0 Big data Corriente RMS Predictive maintenance Linear regression Industry 4.0 Big data RMS Current INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS