Operaciones crud en datos semiestructurados.

SEVERINO FELICIANO MORALES Edgardo Solis Carmona José Luis Hernández-Hernández Mario Hernández Hernández Valentin Alvarez Hilario (2019)

La estructura de los datos puede evolucionar frecuentemente, sin necesidad de que haya cambios en la estructura

de un esquema. La principal característica de este tipo de datos, es el hecho de que no depende de una estructura de un esquema explicito pero existe implícitamente entre los datos o el código. Se puede saber qué tipo de datos se necesitan para obtener un análisis completo de una problemática, para ofrecer soluciones, a pesar de ser schemaless. Los tipos de datos se pueden identificar como Estructurados (Bases de Datos Relacionales, Data Warehouses), Semiestructurados (JSON, XML) y No Estructurados (Texto, Audio y Video), pero lo más que han tomado mayor relevancia son los dos primeros, ya que hacen más fácil el tratamiento de los datos. En este artículo se pretenden abordar los datos semiestructurados y las operaciones fundamentales para los datos en una base de datos NoSQL, específicamente MongoDB.

Artículo

Datos Semiestructurados Bases de Datos NoSQL Schemaless MongoDB INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS PROCESOS TECNOLÓGICOS

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)

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.

Artículo

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)

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.

Artículo

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)

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.

Artículo

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

CuO-NPs Improve Biosynthesis of Bioactive Compounds in Lettuce

JAZMIN MONTSERRAT GAUCIN DELGADO Luis Guillermo Hernández Montiel Manuel Fortis Hernández JUAN JOSE REYES PEREZ José Antonio González Fuentes Pablo Preciado Rangel (2022)

"The application of metallic nanoparticles improves the yield and content of bioactive compounds in plants. The aim of the present study was to determine the effects of the foliar application of copper nanoparticles (CuO-NPs) in the yield and content of bioactive compounds in lettuce. Different concentrations of CuO-NPs (0, 0.5, 1, 2, 4, and 6 mg mL−1 ) were applied in lettuce. The yield, nutraceutical quality, and enzymatic activity were determined. Foliar spraying of CuO-NPs induced an increase in the biosynthesis of bioactive compounds. In addition to an increase in the activity of the enzymes superoxide dismutase (SOD) and catalase (CAT) in lettuce plants, there were no negative effects on yield. Therefore, with the application of CuO-NPs, better quality lettuces are produced for the human diet due to the higher production of bioactive compounds."

Artículo

nano-biofortification, nanoparticles, antioxidants, Lactuca sativa L. CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGRARIAS AGROQUÍMICA REGULADORES DEL CRECIMIENTO DE LAS PLANTAS REGULADORES DEL CRECIMIENTO DE LAS PLANTAS

Use of organic substrates on the quality of watermelon seedlings

Benigno Rivera Hernández Victor Hugo Quej Chi Roberto Gutiérrez Burón José Luis Andrade Torres EUGENIO CARRILLO Vianey González CLAUDINA VILLARREAL (2022)

Watermelon (Citrullus lanatus) is a succulent fruit and vine-like plant that is cultivated in Mexico and it generates employment and currency for the country. However, there is the need to research what local organic substrates can substitute peat moss as a culture medium to produce watermelon seedlings of good quality and at low cost. The objective of this study was to evaluate the physical and chemical properties of five local organic substrates as substitutes of the commercial substrate “Peat Moss”, for the production of seedlings of two watermelon cultivars, Sun Sweet and Jubilee. Five local organic substrates were studied: cacao husk, compost, vermicompost, bovine manure, coconut fiber and the commercial substrate “Peat Moss” as control. The response variables were percentage of germination, indicators of morphological quality and morphological quality indexes, stability of the clod, and relative efficiency of the local substrates. The best morphological indicators and morphological quality index of the seedlings were found with the substrates cacao husk and vermicompost, with a seedling quality similar to those obtained with the commercial substrate. Compost presented the lowest stability of the clod and relative efficiency. The substrates of cacao husk and vermicompost can substitute the commercial substrate “Peat Moss”, in addition to being easy to obtain and of low cost; so they are a viable alternative for rural farmers in the production of watermelon seedlings. © 2022, Sociedade de Olericultura do Brasil. All rights reserved.

Artículo

CITRULLUS LANATUS CACAO HUSK VERMICOMPOST COCONUT FIBER BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA VEGETAL (BOTÁNICA) ECOLOGÍA VEGETAL ECOLOGÍA VEGETAL

Multiplication of native endomycorrhizae isolated from arid soils on organic substrates in wheat plants (Triticum aestivum)

JOSÉ RAFAEL PAREDES JÁCOME ROSALINDA MENDOZA VILLARREAL ROBERTO GREGORIO CHIQUITO CONTRERAS Luis Guillermo Hernández Montiel VALENTIN ROBLEDO TORRES Homero Ramírez Rodríguez (2023)

"Purpose Organic residues of coffee pulp, sugarcane bagasse and mature bovine manure are a source of organic matter and nutrients for the multiplication of endomycorrhizae consortia. Therefore, the purpose of this research is to multiply the AMFs in such substrates to decrease soil and water pollution. Method A pot experiment under greenhouse conditions was conducted in order to evaluate the influence of agricultural residues (C2-GEC, C3-PAR, C12-PRO, C14-ZAR) with different genera of endomycorrhizae isolated from semi-arid soils, 75 days after the crop was established. Agronomic characteristics and mineral content of N, K, Ca, Mg, and Fe in root and shoot were evaluated in wheat (Triticum aestivum). Results Multiplication of endomycorrhizae was influenced by the residue type. Greater production of spores was ob-served in the coffee pulp, followed by the sugarcane bagasse, where a higher colonization was obtained in combination of C2-GEC and C3-PAR consortia. This consortia combination also was one of those that have increased the content of N, K, Ca, Mg, and Fe in roots and shoots of wheat.Conclusion Combination of native endomycorrhiza substrates and consortia provides an alternative tool that benefits the physiology and nutrition of the plant to be used in sustainable agricultural production systems."

Artículo

Coffee pulp, Sugarcane bagasse, Bovine manure, Mycorrhizal fungi, Organic waste CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGRARIAS AGRONOMÍA FERTILIDAD DEL SUELO FERTILIDAD DEL SUELO