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Parametrización de hidrogramas mediante interpolantes hermitianos

ALVARO ALBERTO ALDAMA RODRIGUEZ ALDO IVAN RAMIREZ OROZCO (1998, [Artículo])

La parametrización de hidrogramas resulta útil en la definición de avenidas de diseño, por lo que diversas opciones de parametrización han sido propuestas en la literatura. No obstante, éstas exhiben ciertas limitaciones que restringen su aplicación en la representación de hidrogramas naturales. Esto ha motivado a los autores a desarrollar una parametrización polinomial basada en el empleo de interpolantes hermitianos, cuyas principales propiedades son la continuidad de derivadas hasta de cierto orden y la invariancia de volumen. Dichas propiedades se demuestran en este artículo. También se presentan dos ejemplos de aplicación en los cuales se ha utilizado el procedimiento propuesto para definir la forma de un hidrograma unitario generado sintéticamente y para la representación de un hidrograma real de un solo pico.

Parametrización de avenidas Hidrogramas Avenidas de diseño INGENIERÍA Y TECNOLOGÍA

Genome-wide association analyses of agronomic traits and Striga hermonthica resistance in pearl millet

Hussein Shimelis Chris Ojiewo Abhishek Rathore (2023, [Artículo])

Pearl millet (Pennisetum glaucum [L.] R. Br.) is a nutrient-dense, relatively drought-tolerant cereal crop cultivated in dry regions worldwide. The crop is under-researched, and its grain yield is low (< 0.8 tons ha−1) and stagnant in the major production regions, including Burkina Faso. The low productivity of pearl millet is mainly attributable to a lack of improved varieties, Striga hermonthica [Sh] infestation, downy mildew infection, and recurrent heat and drought stress. Developing high-yielding and Striga-resistant pearl millet varieties that satisfy the farmers’ and market needs requires the identification of yield-promoting genes linked to economic traits to facilitate marker-assisted selection and gene pyramiding. The objective of this study was to undertake genome-wide association analyses of agronomic traits and Sh resistance among 150 pearl millet genotypes to identify genetic markers for marker-assisted breeding and trait introgression. The pearl millet genotypes were phenotyped in Sh hotspot fields and screen house conditions. Twenty-nine million single nucleotide polymorphisms (SNPs) initially generated from 345 pearl millet genotypes were filtered, and 256 K SNPs were selected and used in the present study. Phenotypic data were collected on days to flowering, plant height, number of tillers, panicle length, panicle weight, thousand-grain weight, grain weight, number of emerged Striga and area under the Striga number progress curve (ASNPC). Agronomic and Sh parameters were subjected to combined analysis of variance, while genome-wide association analysis was performed on phenotypic and SNPs data. Significant differences (P < 0.001) were detected among the assessed pearl millet genotypes for Sh parameters and agronomic traits. Further, there were significant genotype by Sh interaction for the number of Sh and ASNPC. Twenty-eight SNPs were significantly associated with a low number of emerged Sh located on chromosomes 1, 2, 3, 4, 6, and 7. Four SNPs were associated with days-to-50%-flowering on chromosomes 3, 5, 6, and 7, while five were associated with panicle length on chromosomes 2, 3, and 4. Seven SNPs were linked to thousand-grain weight on chromosomes 2, 3, and 6. The putative SNP markers associated with a low number of emerged Sh and agronomic traits in the assessed genotypes are valuable genomic resources for accelerated breeding and variety deployment of pearl millet with Sh resistance and farmer- and market-preferred agronomic traits.

High-Yielding Varieties Striga-Resistant Agronomic Parameters CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOME-WIDE ASSOCIATION STUDIES STRIGA HERMONTHICA PEARL MILLET

Hidrología de avenidas

ALVARO ALBERTO ALDAMA RODRIGUEZ (2000, [Artículo])

La hidrología de avenidas es un tema que ha cobrado mucha relevancia debido a las inundaciones recientemente provocadas por eventos hidrometeorológicos extremos en todo el mundo. Este artículo presenta los resultados de una serie de investigaciones que el autor y sus colaboradores han obtenido a lo largo de los años en la materia. En particular, se discuten métodos para la estimación de avenidas de diseño en presas y redes de ríos, para el tránsito hidrológico de avenidas en cauces y para el tránsito hidráulico de avenidas en redes de ríos con lagunas de interconexión.

Tránsito inverso Parametrización de avenidas Hidrogramas Probabilidad multivariada INGENIERÍA Y TECNOLOGÍA

Comparación de parámetros meteorológicos dentro y fuera de un invernadero para el cálculo de los requerimientos hídricos de un cultivo bajo condiciones de invernadero en Ocuituco, Morelos

Helene Emmi Karin Unland Weiss JUAN MANUEL ANGELES HERNANDEZ (2011, [Ítem publicado en memoria de congreso])

En la República Mexicana, la agricultura de riego actualmente consume el 78% del agua total utilizada, mientras que, la demanda de agua por otros usos (doméstico, servicios, industrial y recreación) está en aumento continuo, lo que ha causado una tendencia a reducir el porcentaje de agua disponible para la agricultura, aunando que la demanda de alimentos por la población es cada vez mayor. Para ofrecer una solución a esta problemática de la agricultura de riego, se busca incrementar la productividad del agua. La agricultura protegida bajo condiciones de invernadero representa una excelente alternativa para reducir los volúmenes de agua aplicados a los cultivos y al mismo tiempo, elevar la producción, lo cual se refleja en el incremento de la superficie con invernaderos en los últimos años y en el incremento de la tecnificación de riego incluyendo el uso de sistemas de riego de alta eficiencia. Un aspecto emergente del proceso de tecnificación es la instrumentación de los invernaderos con sensores agrometeorológicos para determinar los requerimientos hídricos reales de los cultivos bajo condiciones de invernadero, ya que hay diferencias importantes entre las condiciones ambientales dentro y fuera del invernadero. Como parte de este estudio, se instrumentó un invernadero en la población de Ocuituco, estado de Morelos, para llevar a cabo la producción de un cultivo de jitomate indeterminado, desarrollado bajo condiciones de ambiente protegido. Los datos de los sensores adentro y afuera del invernadero se utilizaron para estimar la evapotranspiración de referencia (ETo).

Cultivos alimenticios Parámetros meteorológicos Invernaderos INGENIERÍA Y TECNOLOGÍA

Determinación en laboratorio de los parámetros reológicos de mezclas agua-sedimentos para el cálculo de flujos de lodos y debris

ISAAC BONOLA ALONSO (2002, [Artículo])

Con el fin de predecir y tomar medidas de prevención, se presentan los modelos numéricos desarrollados para conocer parámetros reológicos de las mezclas de agua-sedimentos.

Flujo de lodos Parámetros reológicos Simulación INGENIERÍA Y TECNOLOGÍA

A Novel Technique for Classifying Bird Damage to Rapeseed Plants Based on a Deep Learning Algorithm.

Ali Mirzazadeh Afshin Azizi Yousef Abbaspour_Gilandeh José Luis Hernández-Hernández Mario Hernández Hernández Iván Gallardo Bernal (2021, [Artículo])

Estimation of crop damage plays a vital role in the management of fields in the agricultura sector. An accurate measure of it provides key guidance to support agricultural decision-making systems. The objective of the study was to propose a novel technique for classifying damaged crops based on a state-of-the-art deep learning algorithm. To this end, a dataset of rapeseed field images was gathered from the field after birds¿ attacks. The dataset consisted of three classes including undamaged, partially damaged, and fully damaged crops. Vgg16 and Res-Net50 as pre-trained deep convolutional neural networks were used to classify these classes. The overall classification accuracy reached 93.7% and 98.2% for the Vgg16 and the ResNet50 algorithms, respectively. The results indicated that a deep neural network has a high ability in distinguishing and categorizing different image-based datasets of rapeseed. The findings also revealed a great potential of Deep learning-based models to classify other damaged crops.

rapeseed classification damaged crops deep neural networks INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

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

Comparison of Different Classifiers and the Majority Voting Rule for the Detection of Plum Fruits in Garden Conditions.

Razieh Pourdarbani Sajad Sabzi Mario Hernández Hernández José Luis Hernández-Hernández Ginés García_Mateos Davood Kalantari José Miguel Molina Martínez (2019, [Artículo])

Color segmentation is one of the most thoroughly studied problems in agricultural applications of remote image capture systems, since it is the key step in several different tasks, such as crop harvesting, site specific spraying, and targeted disease control under natural light. This paper studies and compares five methods to segment plum fruit images under ambient conditions at 12 different light intensities, and an ensemble method combining them. In these methods, several color features in different color spaces are first extracted for each pixel, and then the most e

ective features are selected using a hybrid approach of artificial neural networks and the cultural algorithm (ANN-CA). The features selected among the 38 defined channels were the b* channel of L*a*b*, and the color purity index, C*, from L*C*h. Next, fruit/background segmentation is performed using five classifiers: artificial neural network-imperialist competitive algorithm (ANN-ICA); hybrid artificial neural network-harmony search (ANN-HS); support vector machines (SVM); k nearest neighbors (kNN); and linear discriminant analysis (LDA). In the ensemble method, the final class for each pixel is determined using the majority voting method. The experiments showed that the correct classification rate for the majority voting method excluding LDA was 98.59%, outperforming the results of the constituent methods.

remote sensing in agriculture artificial neural network hybridization environmental conditions majority voting plum segmentation INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

In vitro Digestibility of Yarrowia lipolytica Yeast and Growth Performance in Whiteleg Shrimp Litopenaeus vannamei

ANA RUTH ALVAREZ SANCHEZ CLAUDIO HUMBERTO MEJIA RUIZ Héctor Gerardo Nolasco Soria Alberto Peña Rodríguez (2018, [Artículo])

"Marine yeasts used in aquaculture disease control can also be an important protein source for improving feeding and nutrition of crustaceans. Yarrowia lipolyticca has been studied for its capacity to secrete heterologous proteins and high content of unsaturated fatty acids, beta-glucan, and mannane polymers in the cell wall. We measured in vitro digestibility of Y. lipolyticca by whiteleg shrimp Litopenaeus vannamei digestive enzymes, and an in vivo assay of Y. lipolytica in feed onwhiteleg shrimp growth. We found that digestive gland enzymes of shrimp digest Y. lipolytica, based on reduced optical density of a yeast suspension. Digestion was –0.00236 ± 0.00010 OD U min–1 for intact cells and –0.00325 ± 0.00010 OD U min–1 for lysed cells. Release of reducing sugars in intact cells (5.3940 ± 0.1713 μmol h–1), and lysed cells (0.8396 ± 0.2251 μmol h–1) was measured. Digestive gland treatment significantly reduced cell viability (near 100%), relative to the control. Electron microscopy shows that the cell wall of Y. lipolytica exposed to the digestive gland enzymes was severely damaged. Shrimp diet containing Y. lipolytica resulted in significantly higher weight gain and specific growth rate of whiteleg shrimp."

Marine yeast, cell digestibility, cell viability, turbidimetry, reduced sugars BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOQUÍMICA BIOQUÍMICA DE ALIMENTOS BIOQUÍMICA DE ALIMENTOS