Repositorio Nacional

BACKGROUND: Continuous development of new wheat varieties is necessary to satisfy the demands of farmers, industry, and consumers. The evaluation of candidate genotypes for commercial release under different on-farm conditions is a strategy that has been strongly recommended to assess the performance and stability of new cultivars in heterogeneous environments and under different farming systems. The main objectives of this study were to evaluate the grain yield and quality performance of ten different genotypes across six contrasting farmers' field conditions with different irrigation and nitrogen fertilization levels, and to develop suggestions to aid breeding programs and farmers to use resources more efficiently. Genotype and genotype by environment (GGE) interaction biplot analyses were used to identify the genotypes with the strongest performance and greatest stability in the Yaqui Valley. RESULTS: Analyses showed that some traits were mainly explained by the genotype effect, others by the field management conditions, and the rest by combined effects. The most representative and diverse field conditions in the Yaqui Valley were also identified, a useful strategy when breeders have limited resources. The independent effects of irrigation and nitrogen levels and their interaction were analyzed for each trait. The results showed that full irrigation was not always necessary to maximize grain yield in the Yaqui Valley. Other suggestions for more efficient use of resources are proposed. CONCLUSIONS: The combination of on-farm trials with GGE interaction analyses is an effective strategy to include in breeding programs to improve processes and resources. Identifying the most outstanding and stable genotypes under real on-farm systems is key to the development of novel cultivars adapted to different management and environmental conditions.

Wheat Quality Bread Wheat Bread-Making CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SOFT WHEAT QUALITY FARMING SYSTEMS

CIMMYT seed systems Interventions

lessons to Pakistan

AbduRahman Issa (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SEED SYSTEMS VALUE CHAINS POLICIES HYBRIDS MAIZE WOMEN FARMERS

Demonstration of service provider model of solar irrigation system for smallholder farmers

Md Abdul Matin (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA IRRIGATION SMALLHOLDERS IRRIGATION SYSTEMS

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

Monitoreo con drones en gráficas con viento dinámico

Jovanni Manuel López Elisea (2024, [Tesis de maestría])

108 páginas. Maestría en Optimización.

Dada una gráfica completa no dirigida, se desea recorrer un subconjunto de sus aristas usando una flotilla de drones. Los drones tienen baterías limitadas que pueden recargarse al regresar a la base y, en principio, el tiempo para recorrer una arista está en función de la distancia entre sus vértices. Sin embargo, ante la presencia de viento el tiempo de recorrer una arista puede depender del sentido en el que se haga. La dificultad del problema aumenta si además la intensidad del viento puede variar de un instante a otro. En esta tesis se aborda el problema anteriormente descrito para el caso particular en el que los vértices son puntos en el plano, el impacto del viento en los tiempos de recorrido de las aristas está relativamente acotado y el subconjunto de las aristas a recorrer inducen un árbol que abarca todos los vértices excepto la base de los drones. Dado que los drones operan simultáneamente y pueden recorrer distintas partes de la gráfica de manera independiente, se desea minimizar el tiempo que emplea el dron con el recorrido más tardado. Esta tesis presenta un modelo matemático para resolver el problema de manera exacta, así como tres heurísticas diferentes para obtener buenas soluciones factibles. La primera de estas heurísticas transforma una solución sin viento y sin batería en una solución con viento y batería. La segunda heurística es un algoritmo glotón sin comunicación entre los drones y la última heurística también es un algoritmo glotón, pero con comunicación entre los drones. Aunque el problema abordado resulta ser lo suficientemente difícil como para que su resolución exacta sea inviable en la práctica, las heurísticas diseñadas son fáciles de implementar y obtuvieron resultados razonables en un tiempo corto de cómputo.

Drone aircraft--Control systems. Drone aircraft--Mathematical models. Mathematical optimization. Heuristic programming. Dynamical systems. Graph theory. Micro vehículos aéreos. Optimización matemática. Programación heurística. Teoría de grafos. TL589.4 CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA MATEMÁTICAS INVESTIGACIÓN OPERATIVA DISTRIBUCIÓN Y TRANSPORTE

Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics

Xu Wang Sandesh Kumar Shrestha Philomin Juliana Suchismita Mondal Francisco Pinto Govindan Velu Leonardo Abdiel Crespo Herrera JULIO HUERTA_ESPINO Ravi Singh Jesse Poland (2023, [Artículo])

New Crop Varieties Plant Breeding Programs Yield Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA LEARNING GRAIN YIELDS WHEAT BREEDING FOOD SECURITY