Data in Brief最新文献

Multivariate analysis for identifying drought-tolerant barley (Hordeum vulgare L.) genotypes using stress indices

IF 1

Data in Brief Pub Date : 2025-03-07 DOI: 10.1016/j.dib.2025.111452

Nadira Mokarroma , Md Romij Uddin , Imrul Mosaddek Ahmed , AHM Motiur Rahman Talukder , Abul Fazal Mohammad Shamim Ahsan , Zakaria Alam

{"title":"Multivariate analysis for identifying drought-tolerant barley (Hordeum vulgare L.) genotypes using stress indices","authors":"Nadira Mokarroma , Md Romij Uddin , Imrul Mosaddek Ahmed , AHM Motiur Rahman Talukder , Abul Fazal Mohammad Shamim Ahsan , Zakaria Alam","doi":"10.1016/j.dib.2025.111452","DOIUrl":"10.1016/j.dib.2025.111452","url":null,"abstract":"<div><div>The stress indicator widely expresses the impression of drought stress on barley genotypes throughout the crown root initiation period, highlighting its worldwide effect on production. So, it was urgent need to identify the drought-resilient genotypes considering the multi-trait genotype ideotype distance index (MGIDI). The study, conducted to evaluate the grain output and genetic variations of 50 barley genotypes using stress indicator. Under optimal conditions, genotype IBON14 achieved the highest grain yield of 9.55 g/plant, while under drought stress, genotype BD7194 produced 7.31 g/plant. Significant correlations, both positive and negative (ranging from 0.66 to 1.00), were observed among stress tolerance indices and yields. Using the MGIDI index, genotype BD7194 was selected as the most drought-tolerant, followed by BD7188, IBON14, BD8579, and IBON16, with a 5 % selection intensity. Factor study among the MGIDI revealed diverse tolerance and susceptibility indices, emphasizing the robustness of the certain genotypes, all of which were grouped under a single factor. The selected genotypes exhibited a selection gain (%) between 39.9 % and 113 %. Moreover, the selection differential, calculated from predicted values, varied from 0.25 to 2.54, and broad-sense heritability was determined to be ≥0.99. This study emphasizes the usefulness of the MGIDI index in selecting drought-tolerant barley genotypes, with BD7194 proving to be the most resilient, exhibiting high genetic stability and selection gains.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111452"},"PeriodicalIF":1.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Public database mapping UK seafood supplies and nutrients

IF 1

Data in Brief Pub Date : 2025-03-07 DOI: 10.1016/j.dib.2025.111444

Anneli Löfstedt , Bernhard Scheliga , Magaly Aceves-Martins , Baukje de Roos

{"title":"Public database mapping UK seafood supplies and nutrients","authors":"Anneli Löfstedt , Bernhard Scheliga , Magaly Aceves-Martins , Baukje de Roos","doi":"10.1016/j.dib.2025.111444","DOIUrl":"10.1016/j.dib.2025.111444","url":null,"abstract":"<div><div>Here we present a high-resolution perspective on United Kingdom (UK) seafood supplies and nutrient flows between 2009 and 2020 with data collected from publicly available datasets. The database combines secondary data on production (capture and aquaculture), trade (import and export), purchases, and consumption, for up to 73 seafood species. The nutritional composition (protein, omega-3 fatty acids, vitamin D, vitamin A, vitamin B<sub>12</sub>, calcium, iodine, iron, selenium, and zinc) for each species are also included. As the secondary data was obtained from different data sources, they were harmonised to efficiently link the data. Seafood species were categorised as lean, oily, and shellfish, to allow comparisons with UK dietary guidelines, and were assigned a species type according to the Food and Agricultural Organisation 'International Standard Statistical Classification for Aquatic Animals and Plants' classification. By the virtue of the integrated nature of our seafood database, it provides a unique opportunity for users to interrogate the entire UK seafood supply chain, at a species level, over a decade worth of data, allowing users to understand what seafood is being produced and ultimately consumed. The application of this database is described in an original research article entitled “Seafood supply mapping reveals production and consumption mismatches and large dietary nutrient losses through exports in the United Kingdom”.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111444"},"PeriodicalIF":1.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TELEIA: A Spanish language dataset for evaluating artificial intelligence models

IF 1

Data in Brief Pub Date : 2025-03-05 DOI: 10.1016/j.dib.2025.111437

Marina Mayor-Rocher , Nina Melero , Elena Merino-Gómez , Miguel González , Raquel Ferrando , Javier Conde , Pedro Reviriego

{"title":"TELEIA: A Spanish language dataset for evaluating artificial intelligence models","authors":"Marina Mayor-Rocher , Nina Melero , Elena Merino-Gómez , Miguel González , Raquel Ferrando , Javier Conde , Pedro Reviriego","doi":"10.1016/j.dib.2025.111437","DOIUrl":"10.1016/j.dib.2025.111437","url":null,"abstract":"<div><div>This paper presents TELEIA, a dataset for the evaluation of Spanish language knowledge in Large Language Models (LLMs). TELEIA is designed to complement existing LLMs tests that evaluate many knowledge areas or tasks and are written in English. To evaluate LLMs in Spanish these English tests are translated, which is reasonable for most technical areas and for many tasks, but not when evaluating the knowledge of the Spanish language. New tests specifically designed for Spanish are needed to evaluate the knowledge of the language. This paper introduces TELEIA, a dataset that is an initial step in that direction. The dataset is designed as a set of multiple-choice questions that have the same format and level as those used in several Spanish evaluation tests for humans. The multiple-choice questions enable automation of LLM testing and the use of TELEIA in existing LLM Leaderboards. The questions are divided in three blocks which resemble existing tests of Spanish for foreign learners and for University access. In total, one hundred questions are included that have been prepared and revised by experts on Spanish language, and that have been validated by comparing with the original exams. The dataset will be included in the first Leaderboard of Spanish LLMs.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111437"},"PeriodicalIF":1.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dataset on nematode assemblages of different ecosystems in Del Agua National Park, Costa Rica

IF 1

Data in Brief Pub Date : 2025-03-05 DOI: 10.1016/j.dib.2025.111443

Ingrid Varela-Benavides , Joaquín Abolafia , Howard Ferris , Reyes Peña-Santiago

{"title":"Dataset on nematode assemblages of different ecosystems in Del Agua National Park, Costa Rica","authors":"Ingrid Varela-Benavides , Joaquín Abolafia , Howard Ferris , Reyes Peña-Santiago","doi":"10.1016/j.dib.2025.111443","DOIUrl":"10.1016/j.dib.2025.111443","url":null,"abstract":"<div><div>Nematodes comprise a diverse and ubiquitous group, widely used as bioindicators for environmental monitoring. The characterization of nematode assemblages in soils, both arable and undisturbed, promotes the understanding of their ecology, diversity, and contribution to ecosystem functions. The present contribution is the dataset used in the study described in “Nematode assemblages in four ecosystems of Parque Nacional del Agua, Costa Rica” Applied Soil Ecology, 172, 104360. It contains tables of the estimated abundance of genera and a series of ecological indices (maturity index, plant parasitic index, sigma maturity index, basal index, enrichment index, channel index, structure index, Shannon-Wiener diversity index, and the true diversity) obtained for the nematode assemblages associated with soils of five locations with four different types of ecosystems (primary forest and, derived by conversion of the primary forest, secondary forest, tree plantation and pasture) at the edges of the park in the area of sustainable management of natural resources. Because the provided dataset was obtained following a precise methodological protocol, this contribution will be very useful for later comparative studies of nematode assemblages in tropical and non-tropical habitats.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111443"},"PeriodicalIF":1.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Kidney stone detection via axial CT imaging: A dataset for AI and deep learning applications

IF 1

Data in Brief Pub Date : 2025-03-05 DOI: 10.1016/j.dib.2025.111446

Peshraw Ahmed Abdalla , Muhammad Y. Shakor , Aso Khaleel Ameen , Bander Sidiq Mahmood , Nawzad Rasul Hama

引用次数: 0

FallVision: A benchmark video dataset for fall detection

IF 1

Data in Brief Pub Date : 2025-03-04 DOI: 10.1016/j.dib.2025.111440

Nakiba Nuren Rahman , Abu Bakar Siddique Mahi , Durjoy Mistry , Shah Murtaza Rashid Al Masud , Aloke Kumar Saha , Rashik Rahman , Md. Rajibul Islam

{"title":"FallVision: A benchmark video dataset for fall detection","authors":"Nakiba Nuren Rahman , Abu Bakar Siddique Mahi , Durjoy Mistry , Shah Murtaza Rashid Al Masud , Aloke Kumar Saha , Rashik Rahman , Md. Rajibul Islam","doi":"10.1016/j.dib.2025.111440","DOIUrl":"10.1016/j.dib.2025.111440","url":null,"abstract":"<div><div>This article presents a comprehensive video dataset curated specifically for fall detection research, comprising categorized fall and no-fall videos. The dataset encompasses three primary categories of falls: falls from a bed, chair, and standing position. Initially collected as raw footage, these videos were subsequently processed to produce landmark videos, both with and without a background.</div><div>Recorded using handheld devices such as mobile phones and digital cameras, the dataset was sourced from voluntary participants, ensuring ethical compliance and informed consent. The dataset holds significant value for advancing fall detection algorithms, offering a robust platform for algorithm development and testing.</div><div>Fall detection systems are of paramount importance, particularly in scenarios where individuals are alone and unable to regain their footing post-fall or in cases where elderly individuals experience medical emergencies resulting in falls requiring immediate assistance. Leveraging this dataset, researchers can explore a plethora of techniques, including computer vision and deep learning, to devise and refine fall detection systems. Given its accessibility to researchers, this video dataset can be used in the advancement of fall detection technology to enhance safety measures for vulnerable populations.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111440"},"PeriodicalIF":1.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DigitalExposome: A dataset for wellbeing classification using environmental air quality and human physiological data

IF 1

Data in Brief Pub Date : 2025-03-04 DOI: 10.1016/j.dib.2025.111442

Thomas Johnson

{"title":"DigitalExposome: A dataset for wellbeing classification using environmental air quality and human physiological data","authors":"Thomas Johnson","doi":"10.1016/j.dib.2025.111442","DOIUrl":"10.1016/j.dib.2025.111442","url":null,"abstract":"<div><div>Urban environments play a critical role in shaping mental wellbeing, yet their impact remains understudied, particularly in relation to environmental air quality and human physiology. Despite this growing awareness of the importance of mental health in urban planning, challenges in integrating diverse datasets, spanning environmental, physiological, and self-reported mental wellbeing data limit the scope of research in this area. The DigitalExposome dataset addresses this gap by providing a comprehensive resource for understanding the relationship between these factors. The resulting data was collected from October 2021 to September 2022 in Nottingham, UK with the dataset including over 42, 437 samples from 40 participants aged between 18-50. Participants conducted a walk through diverse urban environments including polluted and green spaces, while carrying a custom-built environmental monitoring system (Enviro-IoT), wearing an Empatica E4 wearable, and using a smartphone mobile application to self-label mental wellbeing via emojis. Environmental variables (e.g., a range of particulates and gases including particulate matter and nitrogen dioxide), physiological metrics (e.g., HR, HRV, EDA, BVP), and mental wellbeing labels were recorded. Data was processed following collection through resampling and interpolation, and normalization for analysis. This novel dataset lays the groundwork for exploring the relationships between air quality, physiological changes, and mental wellbeing, offering valuable insights for urban planning and public health<em>.</em></div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111442"},"PeriodicalIF":1.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

BanglaVeg: A curated vegetable image dataset from Bangladesh for precision agriculture

IF 1

Data in Brief Pub Date : 2025-03-04 DOI: 10.1016/j.dib.2025.111441

Md Jobayer Ahmed, Ratu Saha, Arpon Kishore Dutta, Mayen Uddin Mojumdar, Narayan Ranjan Chakraborty

{"title":"BanglaVeg: A curated vegetable image dataset from Bangladesh for precision agriculture","authors":"Md Jobayer Ahmed, Ratu Saha, Arpon Kishore Dutta, Mayen Uddin Mojumdar, Narayan Ranjan Chakraborty","doi":"10.1016/j.dib.2025.111441","DOIUrl":"10.1016/j.dib.2025.111441","url":null,"abstract":"<div><div>Vegetables are one of the most essential parts of the agricultural sector and the food supply chain; therefore, the identification and categorization of vegetable types require effective strategies. In this paper, we introduce the Vegetable Image Dataset, which is a meticulously developed collection of 4319 images representing 12 different vegetable species native to Bangladesh, including Potato, Onion, Green Chili, Garlic, Radish, Bean, Ladies Finger, Cucumber, Bitter Melon, Brinjal (Eggplant), Tomato, Pointed Gourd. The dataset contains images taken in natural environments, including local markets, agricultural fields, and homes, using phone cameras to represent real-world conditions better. All photos have undergone background removal and annotation to highlight features such as shape, texture, and color, thus making it a handy resource for deep-learning projects. Developed primarily for developing convolutional neural network (CNN) models, this dataset allows for the automatic identification and classification of vegetables for various applications. Applications range from improving the supply chain for agriculture to allowing instantaneous detection of vegetables in kitchens or marketplaces and increasing the efficiency of automation for sorting and packaging. With its unique characteristic of Bangladeshi vegetables, this dataset provides the valuable resource needed for improving agricultural practices using AI-driven ways and fostering further developments of technologies in underserved communities.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111441"},"PeriodicalIF":1.0,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dataset of a complete genome sequence of Vibrio owensii v2 isolated from diseased Sabah's red algae seaweed, Kappaphycus alvarezii

IF 1

Data in Brief Pub Date : 2025-03-04 DOI: 10.1016/j.dib.2025.111447

Vernon Vest Mangun , Wilson Thau Lym Yong , Mohd Faizal Abu Bakar , Nur Athirah Yusof

引用次数: 0

CabriTrack: Accelerometer data for automated behavioural monitoring of grazing Creole goats

IF 1

Data in Brief Pub Date : 2025-03-01 DOI: 10.1016/j.dib.2025.111431

Laura Faillot , Willy Troupe , Mathieu Bonneau

{"title":"CabriTrack: Accelerometer data for automated behavioural monitoring of grazing Creole goats","authors":"Laura Faillot , Willy Troupe , Mathieu Bonneau","doi":"10.1016/j.dib.2025.111431","DOIUrl":"10.1016/j.dib.2025.111431","url":null,"abstract":"<div><div>The availability of sensors and AI-based methods offers new perspectives for monitoring animal behaviour. In particular, accelerometers can record individual acceleration data for weeks, which can then be used to identify the activity of the animal. Several research articles have demonstrated the capacity of this technology, particularly using machine learning or deep learning, for behaviour estimation. These techniques need high-quality datasets to train and validate the models, particularly with a great diversity of examples for each considered behaviour and recorded animals. The diversity of the data is an important prerequisite for deploying these solutions at a large scale. In this context, the dataset presented here contains more than 144 hours of tri-axial accelerometer data, collected from 59 different animals. The data were collected from March 2023 until March 2024. Two to five adult Creole goats were equipped with an accelerometer on one horn and allowed to graze in a small experimental pasture. While grazing, the behaviour of the animals was recorded with a CCTV camera. The videos were then manually annotated using the software Boris to identify the behaviour of each animal when it was possible to do so. Five behaviours were considered: ruminating/chewing, grazing, resting, displacement, and other, which includes behaviours such as scratching or fighting with a congener. Finally, the behaviour sequences were associated with the corresponding acceleration sequences based on a time synchronization procedure, so that each acceleration sequence is associated with one behaviour. This dataset can be used to train and evaluate any prediction methods for behaviour prediction from acceleration data using tri-axial accelerometers mounted on the horn of grazing Creole goats.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111431"},"PeriodicalIF":1.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0