El uso del NIRS como alternativa viable en el análisis químico en dietas para alimento animal El uso del NIRS como alternativa viable en el análisis químico en dietas para alimento animal

Yuneisy Milagro Agüero Fernández Edilmar Cortés Jacinto FERNANDO VEGA VILLASANTE Manuel Alejandro Vargas Ceballos MIRIAM VICTORIA MARTIN MANZO (2021, [Artículo])

"El análisis de la composición química de los insumos utilizados en la preparación de alimentos para producción animal es relevante dentro del proceso productivo. La medición de la reflectancia en el espectro infrarrojo cercano en los alimentos ha permitido describir la composición química de los mismos. La técnica que se emplea para estas mediciones se conoce como Espectroscopía de Reflectancia en el Infrarrojo Cercano, también conocida como NIRS (por sus siglas en inglés, Near Infrared Reflectance Spectroscopy)."

reflectancia, infrarrojo, alimento, muestras, ventajas CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGRARIAS PRODUCCIÓN ANIMAL NUTRICIÓN NUTRICIÓN

Entretejiendo la historia biocultural del Agave cocui (Asparagaceae: Agavoideae) en Venezuela

SILVIA GOMEZ RANGEL (2022, [Artículo])

La presente contribución es un acercamiento a la historia biocultural del Agave cocui Trelease. En la América tropical (Neotrópico), pueblos indígenas y comunidades rurales evidencian una milenaria riqueza de conocimientos en el manejo y aprovechamiento de especies nativas. Sin embargo, los datos sobre A. cocui son fragmentarios e imprecisos. Desde la condición diacrónica de la antropología, son enunciadas y confrontadas diversas líneas de evidencias, a partir de la temprana descripción de Galeotto Cey en el siglo XVI y los orígenes amerindios de su nombre vernáculo. Revitalizar los conocimientos tradicionales sobre la especie contribuiría a mitigar eventuales impactos ambientales y a su aprovechamiento integral y sostenible.

ALIMENTO BEBIDA FERMENTADA CAQUETIO CORMO HORNEADO SUR AMERICA VICUYES BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL

El duraznillo (Tapirira mexicana): una especie comestible poco conocida

Leonardo Díaz Sánchez CESAR ISIDRO CARVAJAL HERNANDEZ ELIA NORA AQUINO BOLAÑOS MARIA DEL SOCORRO HERRERA MEZA (2023, [Artículo])

Tapirira mexicana es un árbol de la familia Anacardiaceae (familia del mango), que se conoce como “duraznillo” o “huichini” (entre otros nombres comunes). En algunos lugares de México se consume la semilla como alimento secundario. Las semillas contienen ácidos grasos poliinsaturados y monoinsaturados cuyo potencial alimenticio y efectos en el organismo humano se desconocen. Resaltamos la importancia de Tapirira mexicana, en particular el consumo de sus semillas, una especie comestible que es poco valorada y reconocida en México.

ALIMENTO ANACARDIACEAE DURAZNILLO ESPECIE MEXICANA SEMILLAS BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL

El amaranto o huauhtli sagrado del México prehispánico y alimento de alto valor nutricional del México contemporáneo

JESUS ALFREDO ARAUJO LEON Ivonne Sánchez del Pino Víctor Aguilar Hernández SERGIO RUBEN PERAZA SANCHEZ ROLFFY RUBEN ORTIZ ANDRADE ANDRES XINGU LOPEZ Ligia Guadalupe Brito Argáez J. NAHIM ALCOCER ESPEJEL (2023, [Artículo])

El amaranto o huauhtli es uno de los alimentos más versátiles y nutritivos del continente americano. Los frailes españoles documentaron en sus crónicas del siglo XVI, la amplia variedad de platillos que los mexicas elaboraban con huauhtli. También destaca la importancia de las semillas de amaranto en las prácticas religiosas y su uso en la elaboración de imágenes sagradas (principalmente comestibles) para los dioses. El amaranto fue importante para la agricultura, la gastronomía y los rituales del México antiguo. El presente ensayo documenta la historia del amaranto en las ceremonias mexicas y su importancia como "súper alimento" en la actualidad

AMARANTHUS HYPOCHONDRIACUS ALEGRIAS SUPER ALIMENTO MEXICAS HERENCIA PREHISPANICA BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL

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

Microbiological Analysis of the Air in a Popular Fish Processing and Marketing Area

Angélica Sinaí Quintanilla Martínez Lizet Aguirre Güitrón Luis Daniel Espinosa Chaurand MAYRA DIAZ RAMIREZ ALEJANDRO DE JESUS CORTES SANCHEZ (2022, [Artículo])

"Fish are marketed as a food and consumed worldwide. During the production of food, contamination by microorganisms is possible through the air, soil, water, surfaces, food handlers, etc. The air does not have a natural microbial composition, but it is a vehicle for the transmission of microorganisms of economic and health interest because they are associated with food spoilage and human diseases. The objective of this study was the microbiological analysis of the air in an area popular for the processing and marketing of fish products in the city of Tepic Nayarit. Using the passive or sedimentation method to collect microorganisms present in the air, the proportion of aerobic mesophile bacteria, coliform bacteria, fungi and yeast was determined at different locations in the fish processing and marketing area for four weeks. The results indicated that the aerobic mesophiles had the highest counts among all the microbial groups analyzed at the twelve different sampling points during the four weeks of the study; their numbers ranged from 2.44 to 2.95 log CFU/m3/h, followed by molds with counts from 1.44 to 2.75 log CFU/m3/h, yeasts with counts from 0.7 to 2.01 log CFU/m3/h and coliforms with counts that ranged from 0.7 to 1.68 log CFU/m3/h. We determined the proportion of the viable microbiological population present in the air at the different sampling points of the study area; several of these sampling points presented values above those recommended by various agencies around the world. Knowledge of the biological hazards transported through the air is important to establish and reduce the risk to the health of occupants and the contamination pathways of processed and marketed fishery products that may be associated with spoilage and foodborne diseases."

food safety, food quality, air pollution, airborne biohazard, environmental monitoring INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS HIGIENE DE LOS ALIMENTOS HIGIENE 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

Indicadores industriales en el uso del agua: industria alimentaria

RAMON LOPEZ HERNANDEZ (2001, [Libro])

Tabla de contenido: 1. Industria alimentaria -- 2. Proceso de fabricación -- 3. Control de la contaminación -- 4. Parámetros e índices específicos de uso del agua -- 5. Conclusiones -- 6. Bibliografía.

1. Industria alimentaria -- 2. Proceso de fabricación -- 3. Control de la contaminación -- 4. Parámetros e índices específicos de uso del agua -- 5. Conclusiones -- 6. Bibliografía.

Industria de alimentos Consumo industrial de agua Usos del agua Indicadores industrailes CIENCIAS SOCIALES

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