Propuesta de un programa de monitoreo y evaluación de sustancias tóxicas, persistentes y bioacumulables (STPB) en cuencas hidrológicas y acuíferos

ANNE MARGRETHE HANSEN HANSEN (2010, [Documento de trabajo])

El objetivo de este trabajo es contribuir en la preparación de un programa nacional de monitoreo de vigilancia de Sustancias Tóxicas Persistentes y Bioacumulables (STPB) en cuencas hidrológicas y acuíferos. Se definieron criterios de selección y se obtuvieron listas de STPB “prioritarias”, cuyo monitoreo puede implementarse de forma inmediata sin cambios en regulaciones existentes e infraestructura, y de STPB “candidatas”, que deben investigarse con mayor detalle antes de ser incluidas en el programa de monitoreo.

Cuencas Acuíferos Monitoreo del agua Sustancias tóxicas Informes de proyectos INGENIERÍA Y TECNOLOGÍA

Classification of Cucumber Leaves Based on Nitrogen Content Using the Hyperspectral Imaging Technique and Majority Voting.

Sajad Sabzi Razieh Pourdarbani Mohammad Hossein Rohban Alejandro Fuentes_Penna José Luis Hernández-Hernández Mario Hernández Hernández (2021, [Artículo])

Improper usage of nitrogen in cucumber cultivation causes nitrate accumulation in the fruit and results in food poisoning in humans; therefore, mandatory evaluation of food products becomes inevitable. Hyperspectral imaging has a very good ability to evaluate the quality of fruits and vegetables in a non-destructive manner. The goal of the present paper was to identify excess nitrogen in cucumber plants. To obtain a reliable result, the majority voting method was used, which takes into account the unanimity of five classifiers, namely, the hybrid artificial neural network¿imperialism competitive algorithm (ANN-ICA), the hybrid artificial neural network¿harmonic search (ANN-HS) algorithm, linear discrimination analysis (LDA), the radial basis function network (RBF), and the Knearest- neighborhood (KNN). The wavelengths of 723, 781, and 901 nm were determined as optimal wavelengths using the hybrid artificial neural network¿biogeography-based optimization (ANNBBO) algorithm, and the performance of classifiers was investigated using the optimal spectrum. The results of a t-test showed that there was no significant difference in the precision of the algorithm when using the optimal wavelengths and wavelengths of the whole range. The correct classification rate of the classifiers ANN-ICA, ANN-HS, LDA, RBF, and KNN were 96.14%, 96.11%, 95.73%, 64.03%, and 95.24%, respectively. The correct classification rate of majority voting (MV) was 95.55% for test data in 200 iterations, which indicates the system was successful in distinguishing nitrogen-rich leaves from leaves with a standard content of nitrogen.

artificial neural network cucumber hyperspectral imaging majority voting nitrogen INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

Using homosoils for quantitative extrapolation of soil mapping models

Andree Nenkam Alexandre Wadoux Budiman Minasny Alex McBratney Pierre C. Sibiry Traore Gatien Falconnier Anthony Whitbread (2022, [Artículo])

Cubist Digital Soil Mapping Model-Based Validation Soil Spatial Variation Soil-Forming Factors CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA LAND USE ORGANIC CARBON SOIL SURVEYS SPATIAL VARIATIONS

Distribution of Puccinia striiformis f. sp. tritici races and virulence in wheat growing regions of Kenya from 1970 to 2014

Lesley Boyd sridhar bhavani Cristobal Uauy Annemarie Fejer Justesen Mogens Hovmoller (2022, [Artículo])

Cereals and Grains Pathogen Diversity Puccinia f. sp. tritici Stripe Rust Yellow Rust CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CEREALS FIELD CROPS FUNGI PATHOGENICITY RUSTS TRITICUM AESTIVUM

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

Análisis preventivos de variables para la industria cerámica con base en la metodología de análisis a modo y efecto de falla (FMEA method)

Preventive analysis of variables for the ceramic industry based on the failure mode and effect analysis (FMEA method)

Rigel Hugo Carreón Reyes Juan Carlos Neri Guzmán (2023, [Artículo])

El presente estudio indica de una forma tangible la aplicación de la herramienta FMEA (Failure Mode And Effects Analysis -por sus siglas en inglés) en la aplicación de fabricación de cerámica sanitaria, en donde se evalúan las variables que están relacionadas con el proceso de diseño, procesamiento de piezas cerámicas y de su relación existente para poder alcanzar los requisitos normativos y que estos a su vez sean alcanzables. Dentro del estudio se presenta el análisis y elaboración de la matriz riesgos en modo de fallas, así como una serie de definiciones estadísticas con las cuales son evaluados los procesos de fabricación, así como la explicación clara de la metodología FMEA en donde se indica la adecuación de estos conceptos a este tipo de manufacturas (cerámica sanitaria). Este trabajo también describe a través del estudio de caso de las variables una metodología que detalla los conceptos básicos tales como severidad, detección y ocurrencia combinando el desarrollo de tablas parametrizadas y / o acopladas al tipo de proceso de manufactura cerámica .En los resultados que se obtienen se observa la disminución de la incertidumbre hasta de 85% en los valores de RPN y una mejora en el cpk >1,33 como índice de calidad los riesgos o incertidumbres disminuidos son de forma numérica a través de la comprobación de nuevas acciones y el reanálisis de los conceptos de ocurrencia y detección derivados de la implementación de acciones. Las conclusiones indican como una herramienta adecuada el uso de FMEA para el campo de aplicación de la manufactura de cerámica sanitaria.

The present study indicates in a tangible way the application of the FMEA tool (Failure Mode and Effects Analysis) in the application of sanitary ceramic manufacturing, where the variables that are related to the process of design, processing of ceramic pieces and their existing relationship are evaluated in order to achieve the regulatory requirements and that these in turn are achievable. The study presents the analysis and elaboration of the risk matrix in failure mode as well as a series of statistical definitions with which the manufacturing processes are evaluated as well as the clear explanation of the FMEA methodology (failure mode and effects analysis) where the application and adequacy of these concepts to this type of manufactures (sanitary ceramics) is indicated. This paper also describes through the case study of the variables a methodology that details the basic concepts such as severity, detection and occurrence combining the development of parameterized tables and / or coupled to the type of ceramic manufacturing process. In the results obtained, the decrease in uncertainty of until 85% in the values of RPN and an improvement in the cpk >1.33 as a quality index, the risks or uncertainties decreased are numerically through the verification of new actions and the reanalysis of the concepts of occurrence and detection derived from the implementation of actions. The conclusions indicate as an appropriate tool the use of FMEA for the field of application of the manufacture of sanitary ceramics.

AMEF (Análisis de Modo de Efecto y Falla) Productos cerámicos Cerámica sanitaria Procesos cerámicos Severidad Detección Ocurrencia FMEA (Failure Mode and Effects Analysis) Ceramic products Standard ASME Sanitary ceramic Ceramic processess INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

La eficiencia de aplicación y productividad del agua en los cultivos de trigo y cebada en el D.R. 011 "Alto río Lerma", Guanajuato

Juan Manuel Angeles HELENE EMMI KARIN UNLAND WEISS Maria Dolores Olvera Salgado (2017, [Objeto de congreso])

En México se estima que más del 90% de la superficie regada, principalmente en los distritos de riego, se utiliza el método de riego por gravedad. Algunos estudios indican que este método no es muy eficiente debido a la pérdida de agua por percolación profunda y escurrimiento superficial. El propósito de este artículo es determinar la eficiencia de aplicación del riego por gravedad, a través de la estimación del requerimiento de riego de los cultivos y de la medición de la lámina de riego obtenida de aforos volumétricos, en parcelas del distrito de riego 011 Alto río Lerma, Guanajuato.

Riego Cultivos alimenticios Producción agrícola Trigo Cebada INGENIERÍA Y TECNOLOGÍA

Variaciones en un transecto profundo frente a la costa de Nayarit, México

Emilio Palacios Hernández Luis Brito Castillo LAURA ELENA CARRILLO BIBRIEZCA CARLOS EDUARDO CABRERA RAMOS JORGE MANUEL MONTES ARECHIGA (2022, [Artículo])

"Six oceanographic cruises in a NE-SW transect were made nearshore of southern Sinaloa and Nayarit from March 2006 through May 2008, where no in situ hydrographic data are available. Applying the Thermodynamic Equation of Seawater 2010 (TEOS-10) to the observations, the hydrography and geostrophic currents of the region were characterized. Results indicate that surface variability (0-50 m) emerged mainly from seasonal atmospheric forcing. A relative salinity maximum was present during all cruises below this surface layer, which is attributed to a water mass intrusion of Subtropical Subsurface Water that could be associated with the Mexican Coastal Current. Another water mass intrusion is from the California Current. Samples from the 2007-2008 La Niña produced an uncommon circulation, where water flowing from the Gulf of California along the coast of Sinaloa was observed, opposite to what is commonly known as a mean circulation. This uncommon circulation matches the generation of anticyclonic eddies around the Islas Marias archipelago."

Gulf of California, Mexican Coastal Current, Nayarit Coast, seasonal variation, La Niña CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO OCEANOGRAFÍA OCEANOGRAFÍA DESCRIPTIVA OCEANOGRAFÍA DESCRIPTIVA

El futuro de la medicina está en tu boca: Las células madre de los dientes

ANGELICA ANAHI SERRALTA INTERIAN SOLEDAD MARIA TERESA HERNANDEZ SOTOMAYOR BEATRIZ ADRIANA RODAS JUNCO (2022, [Artículo])

En el cuerpo humano se han identificado varias fuentes de células madre; sin embargo, los dientes representan una nueva alternativa para la obtención de estas, debido a su fácil obténción, compatibilidad con biomateriales y escasos conflictos éticos; principalmente se han estudiado los tejidos de pulpa dental y ligamento periodontal, de los cuales se han logrado obtener diferentes tipos celulares que tienen el potencial de ser utilizadas para desarrollar estrategias para el tratamiento de enfermedades o la regeneración de órganos y tejidos.

CELULAS DENTALES LIGAMENTO PERIODONTAL LINAJE CELULAR PULPA DENTAL REGENERACION BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA MOLECULAR BIOLOGÍA MOLECULAR DE PLANTAS BIOLOGÍA MOLECULAR DE PLANTAS

A comprehensive review of wheat phytochemicals: From farm to fork and beyond

Wenfei Tian Michael Tilley Zhonghu He Yonghui Li (2022, [Artículo])

Cereal Nutrients Health Benefits Wheat Phytochemicals CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ALKYLRESORCINOLS ANTIOXIDANTS PHENOLIC ACIDS WHEAT