Optimizing nitrogen fertilizer and planting density levels for maize production under current climate conditions in Northwest Ethiopian midlands

Kindie Tesfaye Dereje Ademe Enyew Adgo (2023, [Artículo])

This study determined the most effective plating density (PD) and nitrogen (N) fertilizer rate for well-adapted BH540 medium-maturing maize cultivars for current climate condition in north west Ethiopia midlands. The Decision Support System for Agrotechnology Transfer (DSSAT)-Crop Environment Resource Synthesis (CERES)-Maize model has been utilized to determine the appropriate PD and N-fertilizer rate. An experimental study of PD (55,555, 62500, and 76,900 plants ha−1) and N (138, 207, and 276 kg N ha−1) levels was conducted for 3 years at 4 distinct sites. The DSSAT-CERES-Maize model was calibrated using climate data from 1987 to 2018, physicochemical soil profiling data (wilting point, field capacity, saturation, saturated hydraulic conductivity, root growth factor, bulk density, soil texture, organic carbon, total nitrogen; and soil pH), and agronomic management data from the experiment. After calibration, the DSSAT-CERES-Maize model was able to simulate the phenology and growth parameters of maize in the evaluation data set. The results from analysis of variance revealed that the maximum observed and simulated grain yield, biomass, and leaf area index were recorded from 276 kg N ha−1 and 76,900 plants ha−1 for the BH540 maize variety under the current climate condition. The application of 76,900 plants ha−1 combined with 276 kg N ha−1 significantly increased observed and simulated yield by 25% and 15%, respectively, compared with recommendation. Finally, future research on different N and PD levels in various agroecological zones with different varieties of mature maize types could be conducted for the current and future climate periods.

Maize Model Planting Density CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE MODELS SPACING NITROGEN FERTILIZERS YIELDS

Informalidad laboral municipal en México: análisis de sus causas desde un enfoque espacial

Edison Smith Fonseca Correcha (2020, [Tesis de maestría])

Para el año 2019, más de 30 millones de trabajadores mexicanos estuvieron ejerciendo sus labores en condiciones informales, es decir, excluidos de la seguridad social. Para mitigar este problema público, las políticas públicas en diferentes niveles de gobierno han estado enfocadas principalmente en atacar dos de las posibles causas del problema: los incentivos económicos y la formación de la fuerza laboral. Con el fin de hacer una contribución sobre la relevancia de otras causas en la informalidad laboral, esta investigación presenta evidencia sobre el efecto que tienen los factores espaciales, sociodemográficos, de incentivos económicos y de estructura empresarial sobre la informalidad laboral municipal. Con base en los hallazgos, las recomendaciones de política pública se enfocan en aprovechar algunas estrategias de desarrollo económico regional para generar la conformación de aglomeraciones municipales de empleo formal.

Informal sector (Economics) -- Effect of space on -- Mexico -- Econometric models. Informal sector (Economics) -- Effect of demography on -- Mexico -- Econometric models. Informal sector (Economics) -- Effect of economic aspects on -- Mexico -- Econometric models. CIENCIAS SOCIALES CIENCIAS SOCIALES

Metrics for optimum allocation of resources on the composition and characterization of crop collections: The CIMMYT wheat collection as a proof of concept

M. Humberto Reyes-Valdés Juan Burgueño Carolina Sansaloni Thomas Payne Rosa Angela Pacheco Gil (2022, [Artículo])

Crop Genebanks Optimization Relative Balance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROPS GENE BANKS WHEAT

Chapter 17. Conserving wheat genetic resources

Filippo Guzzon Maraeva Gianella Thomas Payne (2022, [Capítulo de libro])

Genetic Reserves Seed Conservation Wheat Wild Relatives CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GERMPLASM BANKS ON-FARM CONSERVATION SEEDS SEED VIABILITY WHEAT

Corrección de defectos óseos en el área de Ingeniería tisular

Correction of bone defects by tissue Engineering

ROSA ALICIA SAUCEDO ACUÑA MONICA GALICIA GARCIA JUDITH VIRGINIA RIOS ARANA SIMON YOBANNY REYES LOPEZ (2012, [Artículo])

Hoy en día, los defectos óseos representan uno de los casos de mayor impacto en la salud debido a la frecuencia con que éstos ocurren a causa de traumatismos, fracturas, enfermedades congénitas o degenerativas. En la actualidad, los implantes de tejido óseo de gran volumen se encuentran severamente restringidos a causa de las limitaciones de difusión en la interacción con el ambiente del huésped para los nutrientes, intercambio gaseoso y eliminación de desechos. Es por ello que la corrección de los defectos óseos ha cobrado gran importancia en el área de Ingeniería tisular buscando mejorar las estrategias clínicas para su tratamiento. El propósito de esta revisión es proporcionar un panorama general del desarrollo de andamios para la regeneración de tejido óseo, mostrando los avances logrados en los ensayos in vitro e in vivo en la última década

Currently, bone defects cases represent a major impact on health due to how often they occur because of trauma, fractures, congenital or degenerative diseases. Now, bone implants to large volume are severely restricted because of the diffusion limitations in the interaction

with the environment of the host for nutrients, gas exchange and waste disposal. That is why the correction of bone defects has become very important in the field of tissue engineering looking to improve clinical strategies for treatment. The purpose of this review is to provide an overview of the development of scaffolds for bone tissue regeneration, showing the progress made in the in vitro and in vivo in recent decades.

MEDICINA Y CIENCIAS DE LA SALUD Ingeniería tisular regeneración ósea Andamio Tissue engineering Bone regeneration Scaffolds

Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding

Indian wheat genomics initiative for harnessing the potential of wheat germplasm resources for breeding disease-resistant, nutrient-dense, and climate-resilient cultivars

Sundeep Kumar Reyaz Mir Pawan Kulwal UTTAM KUMAR suneel kumar Shailendra Sharma Ravinder Singh Amit Singh Dr. Subhash Bhardwaj Manoj Prasad Kuldeep Singh (2022, [Artículo])

Indian Wheat Genomics Initiative Genomic Selection CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT GENETIC RESOURCES MARKER-ASSISTED SELECTION GENE BANKS STRESS ABIOTIC STRESS BIOTIC STRESS

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Estudio en modelo físico del funcionamiento hidráulico de la obra de excedencia del proyecto hidroeléctrico Arenal etapa I-II

Cecia Millán-Barrera LIDIA ZULEMA TOSTADO BOJORQUEZ WENDOLY FLORES ALARCON (2018, [Documento de trabajo])

El proyecto se conformó por las siguientes fases: 1. Calibración y ensayos preliminares – 2. Capacidad hidráulica y patrón del flujo – Conclusiones – Recomendaciones – Respuesta a las observaciones del informe final.

Centrales hidroeléctricas Calibración Experimento de laboratorio INGENIERÍA Y TECNOLOGÍA

Medición de flujo volumétrico en presas, canales y pozos

EDMUNDO PEDROZA-GONZALEZ VICTOR MANUEL ARROYO CORREA JULIO SERGIO SANTANA SEPULVEDA ARIOSTO AGUILAR CHAVEZ (2016, [Libro])

Tabla de contenido: Introducción -- 1. El círculo de la medición efectiva -- 2. Medición en centrales hidroeléctricas -- 3. Medición en presas de almacenamiento -- 4. Introducción a la metrología en el contexto de la medición de agua -- 5. Medición de volúmenes, selección de una técnica.

Introducción -- 1. El círculo de la medición efectiva -- 2. Medición en centrales hidroeléctricas -- 3. Medición en presas de almacenamiento -- 4. Introducción a la metrología en el contexto de la medición de agua -- 5. Medición de volúmenes, selección de una técnica.

Mediciones hidráulicas Medición de caudales Presas Pozos Centrales hidroeléctricas Telemetría INGENIERÍA Y TECNOLOGÍA