Estimation of general and specific combining ability effects for quality protein maize inbred lines

Adefris Teklewold Dagne Wegary Gissa (2022, [Artículo])

General Combining Ability Specific Combining Ability CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA COMBINING ABILITY MAIZE PROTEIN QUALITY INBRED LINES DATA ANALYSIS

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

Análisis de las conexiones matemáticas en la enseñanza y aprendizaje de la derivada basado en un networking of theories entre la Teoría de las conexiones y el Enfoque ontosemiótico.

CAMILO ANDRES RODRIGUEZ NIETO (2021, [Tesis de doctorado])

Consejo Nacional de Ciencia y Tecnología No. 602990

In research in Mathematics Education, models have been reported to analyze mathematical connections in which specific connection categories are considered. In the literature, it was identified that the most used model is the Businskas with contributions from other researchers. However, the problem refers to the fact that some categories of connections limit the analysis of mathematical activity and, therefore, the research suggests that the established categories are validated and, if possible, new categories of connections are reported. Other investigations focused on exploring mathematical connections and understanding the derivative reveal that high school students, pre-service teachers, and some in-service mathematics teachers have difficulty connecting multiple representations of the derivative (e.g., algebraic, or symbolic, verbal, graphic, tabular) and establish connections between partial meanings about this concept.

Networking of theories Mathematical connections Onto-semiotic approach semiotic function derivative teacher students HUMANIDADES Y CIENCIAS DE LA CONDUCTA PEDAGOGÍA TEORÍA Y MÉTODOS EDUCATIVOS TEORÍAS EDUCATIVAS

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

Physiological and molecular aspects of seed longevity: exploring intra-species variation in eight Pisum sativum L. accessions

Maraeva Gianella Daniele Dondi Andreas Börner Anca Macovei Andrea Pagano Filippo Guzzon Alma Balestrazzi (2022, [Artículo])

Thermogravimetry CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CARBOHYDRATES PROLINE TOCOPHEROLS GENETICS PHYSIOLOGY PEAS SEEDS SUGARS DIFFERENTIAL SCANNING CALORIMETRY SEED LONGEVITY THERMOGRAVIMETRIC ANALYSIS

Mapping of SARS-CoV-2 spike protein evolution during the first and second waves of COVID-19 infections in India

Shailendra Sharma Avinash Kumar Apekshita Singh deepmala sehgal Shailendra Goel SoomNath Raina (2022, [Artículo])

Immune Evasion Mutation Analysis Novel Spike Mutations Reduced Neutralization SARS-CoV-2 CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA COVID-19 NEUTRALIZATION SPIKES

Identification and characterization of resistance loci to wheat leaf rust and stripe rust in Afghan landrace “KU3067”

CAIXIA LAN Ravi Singh JULIO HUERTA_ESPINO Zaifeng Li Evans Lagudah sridhar bhavani (2022, [Artículo])

Genetic Analysis Molecular Mapping Wheat Rusts APR Genes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ADULT PLANT RESISTANCE LANDRACES WHEAT RUSTS

Manicaland inception meeting: Feed the future mechanization and extension a ctivity (October 2022 to September 2024)

Md Abdul Matin (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SMALLHOLDERS ECONOMIC ANALYSIS

Review of Nationally Determined Contributions (NCD) of Kenya from the perspective of food systems

Tek Sapkota (2023, [Documento de trabajo])

Agriculture is one of the fundamental pillars of the 2022–2027 Bottom-up Economic Transformation Plan of the Government of Kenya for tackling complex domestic and global challenges. Kenya's food system is crucial for climate change mitigation and adaptation. Kenya has prioritized aspects of agriculture, food, and land use as critical sectors for reducing emissions towards achieving Vision 2030's transformation to a low-carbon, climate-resilient development pathway. Kenya's updated NDC, as well as supporting mitigation and adaptation technical analysis reports and other policy documents, has identified an ambitious set of agroecological transformative measures to promote climate-smart agriculture, regenerative approaches, and nature-positive solutions. Kenya is committed to implementing and updating its National Climate Change Action Plans (NCCAPs) to present and achieve the greenhouse gas (GHG) emission reduction targets and resilience outcomes that it has identified.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE GREENHOUSE GAS EMISSIONS FOOD SYSTEMS LAND USE CHANGE AGRICULTURE POLICIES DATA ANALYSIS FOOD WASTES