Genomic selection: A tool for accelerating the efficiency of molecular breeding for development of climate-resilient crops

UTTAM KUMAR Rajeev Ranjan Kumar Philomin Juliana Sundeep Kumar (2022, [Artículo])

Genomic Selection Single-Trait Genomic Selection Multi-Trait Genomic Selection Genomic Estimated Breeding Value Climate-Resilient Crops CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MARKER-ASSISTED SELECTION CLIMATE CHANGE STRESS CLIMATE RESILIENCE CROPS ABIOTIC STRESS BIOTIC STRESS

Gender, rainfall endowment, and farmers’ heterogeneity in wheat trait preferences in Ethiopia

Hom Nath Gartaula Moti Jaleta (2024, [Artículo])

Wheat is a vital cereal crop for smallholders in Ethiopia. Despite over fifty years of research on wheat varietal development, consideration of gendered trait preferences in developing target product profiles for wheat breeding is limited. To address this gap, our study used sex-disaggregated survey data and historical rainfall trends from the major wheat-growing regions in Ethiopia. The findings indicated heterogeneity in trait preferences based on gender and rainfall endowment. Men respondents tended to prefer wheat traits with high straw yield and disease-resistance potential, while women showed a greater appreciation for wheat traits related to good taste and cooking quality. Farmers in high rainfall areas seemed to prioritize high straw yield and disease resistance traits, while those in low rainfall areas valued good adaptation traits more highly. Most of the correlation coefficients among the preferred traits were positive, indicating that farmers seek wheat varieties with traits that serve multiple purposes. Understanding men's and women's preferences and incorporating them in breeding and seed systems could contribute to the development of more targeted and effective wheat varieties that meet the diverse needs of men and women farmers in Ethiopia.

Trait Preferences Multivariate Probit Model CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT AGRONOMIC CHARACTERS GENDER RAINFALL PROBIT ANALYSIS

Towards an Emotional Validation of Heuristic Approaches for Usability Evaluation

YAZMIN MAGALLANES VELAZQUEZ ARIEL MOLINA RUEDA JOSE ALFREDO SANCHEZ HUITRON MARIBEL YENNY MENDEZ BERNAL (2012, [Artículo])

Este artículo presenta una investigación inicial sobre las maneras en que la evaluación emocional de interfaces de usuario puede extender y validar la evaluación heurística de sistemasinteractivos. Mediante la recolección de respuestas de dos grupos de usuarios, este trabajo seenfoca a detectar si existe una correlación entre la evaluación emocional de aspectos específicos de interfaces de usuario y la evaluación correspondiente realizada por expertos en interacción. Primero se obtuvo retroalimentación de expertos en interacción acerca de los problemas potenciales de una interfaz multi-táctil, con base en un enfoque heurístico. Posteriormente, se plantearon escenarios para observar a usuarios inexpertos y obtener respuestas emocionales a los aspectos considerados problemáticos por los expertos. Nuestros hallazgos iniciales indican que hay una correlación importante entre los aspectos problemáticos señalados por los expertos y las respuestas emocionales de los usuarios inexpertos, pero también que algunos de los aspectos problemáticos no necesariamente implican emociones negativas duraderas. Sugerimos entonces que una evaluación emocional de sistemas interactivos puede enriquecer y validar los enfoques heurísticos para evaluación de usabilidad.

This paper presents an initial investigation on how an emotional assessment of user interfaces may extend and validate the heuristic evaluation of the usability of interactive systems. Through the elicitation of responses from two groups of users, we focused on detecting whether a correlation exists between emotional assessment of specific interface issues and the corresponding evaluation by interaction experts. Using a prototypical multi-tactile interface and a heuristic

approach, we first obtained feedback from interaction experts regarding its potential problems and issues. We then devised scenarios for observing novel users and eliciting their emotional responses to the issues raised by our experts. Our initial findings indicate a significant correlation exists between the issues raised by expert users and the emotional responses of novel users, but also that some of those issues do not necessarily lead to long lasting negative emotions. We thus posit that emotional evaluation of interactive systems may be helpful for enriching and validating heuristic approaches for usability evaluation.

INGENIERÍA Y TECNOLOGÍA Usabilidad Evaluación emocional Evaluación Heurística Interfaces multi-táctiles Usability Emotional evaluation Heuristic evaluation Multi-tactile interfaces

REMATTOOL-R: a smart tool for identifying superior maize genotypes from multi-environment yield trials

Lewis Machida Dan Makumbi (2023, [Artículo])

Maize Variety Testing Multienvironment Trial Analysis Relative Maturity REMATTOOL-R Superior Varieties Identification CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE VARIETIES MATURITY IDENTIFICATION YIELDS

Character association study in maize hybrids developed through integration of rapid cycle genomic selection and doubled haploid technology for heat stress tolerance

Prakash Kuchanur Ayyanagouda Patil Pervez Zaidi vinayan mt (2023, [Artículo])

Multi-Parental Synthetics Rapid Cycle Genomic Selection Phenotypic Correlation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE HEAT STRESS MARKER-ASSISTED SELECTION DOUBLED HAPLOIDS PHENOTYPIC VARIATION CLIMATE CHANGE

Using Observed Residual Error Structure Yields the Best Estimates of Individual Growth Parameters

Marcelo Vidal Curiel Bernal EUGENIO ALBERTO ARAGON NORIEGA MIGUEL ANGEL CISNEROS MATA LAURA SANCHEZ VELASCO SYLVIA PATRICIA ADELHEID JIMENEZ ROSENBERG ALEJANDRO FRANCISCO PARES SIERRA (2021, [Artículo])

"Obtaining the best possible estimates of individual growth parameters is essential in studies of physiology, fisheries management, and conservation of natural resources since growth is a key component of population dynamics. In the present work, we use data of an endangered fish species to demonstrate the importance of selecting the right data error structure when fitting growth models in multimodel inference. The totoaba (Totoaba macdonaldi) is a fish species endemic to the Gulf of California increasingly studied in recent times due to a perceived threat of extinction. Previous works estimated individual growth using the von Bertalanffy model assuming a constant variance of length-at-age. Here, we reanalyze the same data under five different variance assumptions to fit the von Bertalanffy and Gompertz models. We found consistent significant differences between the constant and nonconstant error structure scenarios and provide an example of the consequences using the growth performance index _0 to show how using the wrong error structure can produce growth parameter values that can lead to biased conclusions. Based on these results, for totoaba and other related species, we recommend using the observed error structure to obtain the individual growth parameters."

multimodel inference, error structure, totoaba, growth performance BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA ANIMAL (ZOOLOGÍA) FISIOLOGÍA ANIMAL FISIOLOGÍA ANIMAL

Genotype by Environment Interaction (GEI) of maize varieties resistant to maize lethal necrosis for Mid Altutides of Rwanda

Claver Ngaboyisonga Suresh L.M. (2022, [Artículo])

Additive Main Effect and Multiplicative Interaction Area Under Disease Progress Curve Maize Lethal Necrosis Variety x Environment Interaction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE CHLOROTIC MOTTLE VIRUS RESISTANCE VARIETIES INOCULATION DISEASE MANAGEMENT SUGARCANE MOSAIC VIRUS

Response of African sorghum genotypes for drought tolerance under variable environments

Hussein Shimelis Baloua Nébié (2023, [Artículo])

Additive Main Effect and Multiplicative Interaction Best Linear Unbiased Estimates Drought Tolerance Indices CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ABIOTIC STRESS DROUGHT TOLERANCE SORGHUM GENOTYPES

Assessing the Spatiotemporal Relationship between Coastal Habitats and Fish Assemblages at Two Neotropical Estuaries of the Mexican Pacific

VICTOR MANUEL MURO TORRES FELIPE AMEZCUA MARTINEZ Gerogina Ramírez Ortiz FRANCISCO JAVIER FLORES DE SANTIAGO Felipe Amezcua Linares Yareli Hernández Álvarez (2022, [Artículo])

"Differences in fish assemblages’ structures and their relations with environmental variables (due to the variations in sampled seasons, habitats, and zones) were analyzed in two adjacent estuaries on the north Pacific coast of Mexico. Environmental variables and fish catches were registered monthly between August 2018 and October 2020. Multivariate analyses were conducted to define habitats and zones based on their environmental characteristics, and the effect of this variability on fish assemblages’ composition, biomass, and diversity (α and β) was evaluated. A total of 12,008 fish individuals of 143 species were collected using different fishing nets. Multivariate analyses indicated that fish assemblages’ structures were different between zones due to the presence, height, and coverage of distinct mangrove species. Additionally, depth and salinity showed effects on fish assemblages’ diversity (α and β-nestedness), which presented higher values in the ocean and remained similar in the rest of the analyzed zones and habitats. These results and the differences in species replacement (β-turnover) indicate the singularity of fish assemblages at estuaries (even in areas close to the ocean) and the necessity to establish local management strategies for these ecosystems."

mangrove forests, marine protected areas, alpha diversity, beta diversity, multivariate analyses CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGRARIAS PECES Y FAUNA SILVESTRE DINÁMICA DE LAS POBLACIONES DINÁMICA DE LAS POBLACIONES

A Comparison of Multi-Label Text Classification Models in Research Articles Labeled With Sustainable Development Goals

Roberto Carlos Morales-Hernández Joaquín Gutiérrez Jaguey David Becerra-Alonso (2022, [Artículo])

"The classification of scientific articles aligned to Sustainable Development Goals is crucial for research institutions and universities when assessing their influence in these areas. Machine learning enables the implementation of massive text data classification tasks. The objective of this study is to apply Natural Language Processing techniques to articles from peer-reviewed journals to facilitate their classification according to the 17 Sustainable Development Goals of the 2030 Agenda. This article compares the performance of multi-label text classification models based on a proposed framework with datasets of different characteristics. The results show that the combination of Label Powerset (a transformation method) with Support Vector Machine (a classification algorithm) can achieve an accuracy of up to 87% for an imbalanced dataset, 83% for a dataset with the same number of instances per label, and even 91% for a multiclass dataset."

Classification algorithm, multi-label text classification, problem transformation method, scientific articles, sustainable development goals, text classification INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES LENGUAJES ALGORÍTMICOS LENGUAJES ALGORÍTMICOS