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Estimation of general and specific combining ability effects for quality protein maize inbred lines
Adefris Teklewold Dagne Wegary Gissa (2022, [Artículo])
General Combining Ability Specific Combining Ability CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA COMBINING ABILITY MAIZE PROTEIN QUALITY INBRED LINES DATA ANALYSIS
Simon Fonteyne Nele Verhulst (2022, [Libro])
Esta edición presenta los resultados de la red de plataformas en el Hub Pacífico Norte, misma que resulta de la colaboración entre el CIMMYT; el Patronato para la Investigación y Experimentación Agrícola del Estado de Sonora A.C. (PIEAES); el Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP); la Asociación de Agricultores del Río Sinaloa Poniente (AARSP); la Asociación de Agricultores del Río Fuerte Sur (AARFS); la Asociación de Agricultores del Río Culiacán (AARC); la Universidad Autónoma de Sinaloa (UAS); Servicios Agrofinancieros del Norte S.A. de C.V. (SAFINSA); el Club de Labranza de Conservación del Valle del Évora; Granera del Noroeste S.A. de C.V; y el Instituto de Ciencias Agrícolas de la Universidad Autónoma de Baja California (ICA-UABC). Los lectores podrán encontrar en este libro los resultados de las plataformas con más tiempo de operación, en donde ya se han podido generar suficientes datos para sacar conclusiones basadas en evidencias sólidas. Esperamos que el libro pueda servir de inspiración a los productores para que busquen que sus actividades en el campo sean más productivas, rentables y sustentables.
Plataformas de Investigación Maíz Amarillo Pulgón Áreas de extensión Módulos demostrativos Autosuficiencia Alimentaria Uso de Insumos Ganancias para el Productor Nodos de Innovación CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURA DE CONSERVACIÓN COSTOS DE PRODUCCIÓN EUTROFIZACIÓN MONOCULTIVO DEGRADACIÓN DEL SUELO CONTAMINACIÓN PLAGUICIDAS CAMBIO CLIMÁTICO PLATAFORMAS DE INNOVACIÓN EXTENSIÓN AGRÍCOLA AUTOSUFICIENCIA INSUMOS AGRÍCOLAS CONSERVATION AGRICULTURE PRODUCTION COSTS EUTROPHICATION MONOCULTURE SOIL DEGRADATION CONTAMINATION PESTICIDES CLIMATE CHANGE INNOVATION PLATFORMS AGRICULTURAL EXTENSION SELF-SUFFICIENCY FARM INPUTS
Sistemas de producción sostenibles y redes de innovación
Jelle Van Loon (2022, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PRODUCTION SYSTEMS INNOVATION PRODUCTION SYSTEMS AGRIFOOD SYSTEMS
Brendan Brown Pragya Timsina Emma Karki (2023, [Artículo])
While crop diversification has many benefits and is a stated government objective across the Eastern Gangetic Plains (EGP) of South Asia, the complexity of assessment has led to a rather limited understanding on the progress towards, and status of, smallholder crop diversification. Most studies focus on specific commodities or report as part of a singular index, use outdated secondary data, or implement highly localized studies, leading to broad generalisations and a lack of regional comparison. We collected representative primary data with more than 5000 households in 55 communities in Eastern Nepal, West Bengal (India) and Northwest Bangladesh to explore seasonally based diversification experiences and applied novel metrics to understand the nuanced status of farm diversification. While 66 crops were commercially grown across the region, only five crops and three crop families were widely grown (Poaceae, Malvaceae, and Brassicaceae). Non-cereal diversification across the region was limited (1.5 crops per household), though regional differentiation were evident particularly relating to livestock and off-farm activities, highlighting the importance of cross border studies. In terms of farmer's largest commercial plots, 20% of systems contained only rice, and 57% contained only rice/wheat/maize, with substantial regional diversity present. This raises concerns regarding the extent of commercially oriented high value and non-cereal diversification, alongside opportunities for diversification in the under-diversified pre-monsoon and monsoon seasons. Future promotional efforts may need to focus particularly on legumes to ensure the future sustainability and viability of farming systems.
Agricultural Production Systems Farming Systems Change CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL PRODUCTION CROPPING SYSTEMS DIVERSIFICATION FARMING SYSTEMS SUSTAINABLE INTENSIFICATION
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
Visualising the pattern of long-term genotype performance by leveraging a genomic prediction model
Vivi Arief Ian Delacy Thomas Payne Kaye Basford (2022, [Artículo])
Factor Analytic Genotype-By-Year Historical Data Relationship Matrix CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPES PLANT BREEDING SPRING WHEAT RESEARCH
Jelle Van Loon (2022, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA INNOVATION SYSTEMS FOOD SYSTEMS AGRIFOOD SYSTEMS DATA PROCESSING
Review of Nationally Determined Contributions (NCD) of China from the perspective of food systems
Tek Sapkota (2023, [Documento de trabajo])
China is the largest emitter of greenhouse gases (GHG) and one of the countries most affected by climate change. China's food systems are a major contributor to climate change: in 2018, China's food systems emitted 1.09 billion tons of carbondioxide equivalent (CO2eq) GHGs, accounting for 8.2% of total national GHG emissions and 2% of global emissions. According to the Third National Communication (TNC) Report, in 2010, GHG emissions from energy, industrial processes, agriculture, and waste accounted for 78.6%, 12.3%, 7.9%, and 1.2% of total emissions, respectively, (excluding emissions from land use, land-use change and forestry (LULUCF). Total GHG emissions from the waste sector in 2010 were 132 Mt CO2 eq, with municipal solid waste landfills accounting for 56 Mt. The average temperature in China has risen by 1.1°C over the last century (1908–2007), while nationally averaged precipitation amounts have increased significantly over the last 50 years. The sea level and sea surface temperature have risen by 90 mm and 0.9°C respectively in the last 30 years. A regional climate model predicted an annual mean temperature increase of 1.3–2.1°C by 2020 (2.3–3.3°C by 2050), while another model predicted a 1–1.6°C temperature increase and a 3.3–3.7 percent increase in precipitation between 2011 and 2020, depending on the emissions scenario. By 2030, sea level rise along coastal areas could be 0.01–0.16 meters, increasing the likelihood of flooding and intensified storm surges and causing the degradation of wetlands, mangroves, and coral reefs. Addressing climate change is a common human cause, and China places a high value on combating climate change. Climate change has been incorporated into national economic and social development plans, with equal emphasis on mitigation and adaptation to climate change, including an updated Nationally Determined Contribution (NDC) in 2021. The following overarching targets are included in China's updated NDC: • Peaking carbon dioxide emissions “before 2030” and achieving carbon neutrality before 2060. • Lowering carbon intensity by “over 65%” by 2030 from the 2005 level. • Increasing forest stock volume by around 6 billion cubic meters in 2030 from the 2005 level. The targets have come from several commitments made at various events, while China has explained very well the process adopted to produce its third national communication report. An examination of China's NDC reveals that it has failed to establish quantifiable and measurable targets in the agricultural sectors. According to the analysis of the breakdown of food systems and their inclusion in the NDC, the majority of food system activities are poorly mentioned. China's interventions or ambitions in this sector have received very little attention. The adaptation component is mentioned in the NDC, but is not found to be sector-specific or comprehensive. A few studies have rated the Chinese NDC as insufficient, one of the reasons being its failure to list the breakdown of each sector's clear pathway to achieving its goals. China's NDC lacks quantified data on food system sub-sectors. Climate Action Trackers' "Insufficient" rating indicates that China's domestic target for 2030 requires significant improvements to be consistent with the Paris Agreement's target of 1.5°C temperature limit. Some efforts are being made: for example, scientists from the Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences (IEDA-CAAS) have developed methods for calculating GHG emissions from livestock and poultry farmers that have been published as an industrial standard by the Ministry of Agriculture and Rural Affairs, PRC (Prof Hongmin Dong, personal communication) but this still needs to be consolidated and linked to China’s NDC. The updated Nationally Determined Contributions fall short of quantifiable targets in agriculture and food systems as a whole, necessitating clear pathways. China's NDC is found to be heavily focused on a few sectors, including energy, transportation, and urban-rural development. The agricultural sectors' and food systems' targets are vague, and China's agrifood system has a large carbon footprint. As a result, China should focus on managing the food system (production, processing, transportation, and food waste management) to reduce carbon emissions. Furthermore, China should take additional measures to make its climate actions more comprehensive, quantifiable, and measurable, such as setting ambitious and clear targets for the agriculture sector, including activity-specific GHG-reduction pathways; prioritizing food waste and loss reduction and management; promoting sustainable livestock production and low carbon diets; reducing chemical pollution; minimizing the use of fossil fuel in the agri-system and focusing on developing green jobs, technological advancement and promoting climate-smart agriculture; promoting indigenous practices and locally led adaptation; restoring degraded agricultural soils and enhancing cooperation and private partnership. China should also prepare detailed NDC implementation plans including actions and the GHG reduction from conditional targets.
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GREENHOUSE GAS EMISSIONS CLIMATE CHANGE FOOD SYSTEMS LAND USE CHANGE AGRICULTURE POLICIES DATA ANALYSIS FOOD WASTES
Do provisioning ecosystem services change along gradients of increasing agricultural production?
Ronju Ahammad Stephanie Tomscha Sarah Gergel Frédéric Baudron Jean-Yves Duriaux Chavarría Samson Foli Dominic Rowland Josh Van Vianen Terence Sunderland (2024, [Artículo])
Context: Increasing agricultural production shapes the flow of ecosystem services (ES), including provisioning services that support the livelihoods and nutrition of people in tropical developing countries. Although our broad understanding of the social-ecological consequences of agricultural intensification is growing, how it impacts provisioning ES is still unknown. Objectives: We examined the household use of provisioning ES across a gradient of increasing agricultural production in seven tropical countries (Bangladesh, Burkina Faso, Cameroon, Ethiopia, Indonesia, Nicaragua and Zambia). We answered two overarching questions: (1) does the use of provisioning ES differ along gradients of agriculture production ranging from zones of subsistence to moderate and to high agriculture production? and (2) are there synergies and/or trade-offs within and among groups of ES within these zones? Methods: Using structured surveys, we asked 1900 households about their assets, livestock, crops, and collection of forest products. These questions allowed us to assess the number of provisioning ES households used, and whether the ES used are functionally substitutable (i.e., used similarly for nutrition, material, and energy). Finally, we explored synergies and trade-offs among household use of provisioning ES. Results: As agricultural production increased, provisioning ES declined both in total number and in different functional groups used. We found more severe decreases in ES for relatively poorer households. Within the functional groups of ES, synergistic relationships were more often found than trade-offs in all zones, including significant synergies among livestock products (dairy, eggs, meat) and fruits. Conclusions: Considering landscape context provides opportunities to enhance synergies among provisioning services for households, supporting resilient food systems and human well-being.
Agricultural Production Zones Agricultural Intensifcation Synergies and Trade-Offs Landscape Multifunctionality Social-Ecological Systems CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE INTENSIFICATION ECOSYSTEM SERVICES LANDSCAPE SOCIAL-ECOLOGICAL RESILIENCE ECOSYSTEM SERVICES
Testing innovations for adoption of newer and more adapted maize varieties
Michael Ndegwa Pieter Rutsaert Jason Donovan Jordan Chamberlin (2023, [Objeto de congreso])
Changing Production Conditions Genetic Innovations Maize Hybrids CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA TESTING MAIZE VARIETIES YIELDS FARMERS EXPERIMENTATION