Data in Brief最新文献_第2页

Monitoring moisture content in parchment coffee beans during drying using Fourier Transform near infrared (FT-NIR) spectroscopy: A dataset for calibrating chemometric-based models for moisture prediction

IF 1

Data in Brief Pub Date : 2025-02-28 DOI: 10.1016/j.dib.2025.111436

Sandrith Ordoñez-Lozano , Gentil A. Collazos-Escobar , Andrés F. Bahamón-Monje , Nelson Gutiérrez-Guzmán

{"title":"Monitoring moisture content in parchment coffee beans during drying using Fourier Transform near infrared (FT-NIR) spectroscopy: A dataset for calibrating chemometric-based models for moisture prediction","authors":"Sandrith Ordoñez-Lozano , Gentil A. Collazos-Escobar , Andrés F. Bahamón-Monje , Nelson Gutiérrez-Guzmán","doi":"10.1016/j.dib.2025.111436","DOIUrl":"10.1016/j.dib.2025.111436","url":null,"abstract":"<div><div>Maintaining the quality of coffee across each stage of the coffee value chain is critical, with proper bean drying being essential for preserving product shelf life and moisture stability. This work compiles a dataset collected during the mechanical drying process of parchment coffee beans, monitoring moisture content alongside their corresponding near-infrared (NIR) spectra. The aim was to evaluate the application of NIR spectroscopy for predicting moisture content during drying, leveraging NIR as a reliable, rapid, and non-destructive technology for routine monitoring of the coffee drying process. Drying kinetics of parchment coffee beans were determined using a mechanical coffee dryer, with moisture content gravimetrically monitored at various drying times. At each drying point, NIR spectra were acquired using a Spectrum Two N FT-NIR Spectrometer equipped with a high-resolution Indium Gallium Arsenide (InGaAs) detector, operating in diffuse reflectance mode. NIR spectra were collected over a wavelength range of 4000–12000 cm⁻¹ (830–2500 nm), with a 4 cm⁻¹ interval, 8 cm⁻¹ resolution, and 64 scans. This work explored moisture content from fresh coffee (52 % wet basis; w.b.) to 8 % w.b., examining spectral changes throughout the entire drying process. The compiled dataset includes experimental drying kinetics and FT-NIR spectra in Excel format, organized according to experimental conditions. This dataset provides a valuable foundation for further analysis and for calibrating predictive models of moisture content during coffee drying, highlighting the high potential of NIR spectroscopy for industrial-scale drying control and monitoring in the coffee industry.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111436"},"PeriodicalIF":1.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580531","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

A data-driven approach to turmeric disease detection: Dataset for plant condition classification

IF 1

Data in Brief Pub Date : 2025-02-27 DOI: 10.1016/j.dib.2025.111435

A K M Fazlul Kobir Siam, Md. Asraful Sharker Nirob, Prayma Bishshash, Md Assaduzzaman, Apurba Ghosh, Sheak Rashed Haider Noori

{"title":"A data-driven approach to turmeric disease detection: Dataset for plant condition classification","authors":"A K M Fazlul Kobir Siam, Md. Asraful Sharker Nirob, Prayma Bishshash, Md Assaduzzaman, Apurba Ghosh, Sheak Rashed Haider Noori","doi":"10.1016/j.dib.2025.111435","DOIUrl":"10.1016/j.dib.2025.111435","url":null,"abstract":"<div><div>Turmeric, Curcuma longa, is an economically and medicinally important crop. However, the crop has often suffered from diseases such as rhizome disease roots, leaf blotch, and dry conditions of leaves. The control of these diseases essentially requires early and accurate diagnosis to reduce losses and help farmers adopt sustainable farming methods. The conventional methods of diagnosis involve a visual examination of symptoms, which is laborious, subjective, and rather impossible in large areas. This paper proposes a new dataset consisting of 1037 originals and 4628 augmented images of turmeric plants representing five classes: healthy leaf, dry leaf, leaf blotch, rhizome disease roots, and rhizome healthy roots. The dataset was pre-processed to enhance its applicability to deep learning applications by resizing, cleaning, and augmenting the data through flipping, rotation, and brightness adjustment. The turmeric plant disease classification was conducted using the Inception-v3 model, attaining an accuracy of 97.36% with data augmentation, compared to 95.71% without augmentation. Some of the major key performance metrics are precision, recall, and F1-score, which establish the efficacy and robustness of the model. This work attempts to show the potential of AI-aided solutions towards precision farming and sustainable crop production in developing agriculture disease management. The publicly available dataset and the results obtained are expected to attract more research interest for innovations in AI-driven agriculture<em>.</em></div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111435"},"PeriodicalIF":1.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143627977","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 accumulated internal gas pressure and temperature during lithium-ion battery operation and ageing

IF 1

Data in Brief Pub Date : 2025-02-26 DOI: 10.1016/j.dib.2025.111420

Begum Gulsoy, Timothy Vincent, Calum Briggs, Ashima Kalathingal, Mona Faraji Niri, James Marco

{"title":"Dataset of accumulated internal gas pressure and temperature during lithium-ion battery operation and ageing","authors":"Begum Gulsoy, Timothy Vincent, Calum Briggs, Ashima Kalathingal, Mona Faraji Niri, James Marco","doi":"10.1016/j.dib.2025.111420","DOIUrl":"10.1016/j.dib.2025.111420","url":null,"abstract":"<div><div>The experimental data presented are relates to the research article entitled “in-situ measurement of internal gas pressure within cylindrical lithium-ion cells” [<span><span>1</span></span>]. In brief, internal gas pressure that provides deeper insights into the reversible and irreversible gas generation inside a lithium-on cell was directly measured using a novel bespoke embedded sensor system during cell operation and long-term ageing. Battery performance assessment data was obtained from reference performance tests (RPTs) conducted after each instrumentation stages (defined in [<span><span>1</span></span>] as: pristine, modified and instrumented conditions) and at 20-cycle ageing intervals, while ageing data was collected over a total of 100 cycles. Key characterisation parameters, such as cell voltage, discharge capacity at a current of 1C discharge, direct current internal resistance (DCIR) at different states of charge (100 %, 80 % and 50 % SOC), cell surface temperature and internal gas temperature were recorded using instrumented commercial cylindrical cells (LG-Chem INR21700-M50) with embedded pressure sensors. This data provides insights into gas generation within cylindrical cells and demonstrates the inherent coupling between state of charge (SOC), degradation and temperature and pressure variation. The published data provides valuable resources for enhanced battery diagnostics and development of data-driven models to estimate state of charge and state of health (SOH) for advanced battery safety monitoring and BMS control systems.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111420"},"PeriodicalIF":1.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563103","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

2D data arrangement to train ANN for depression levels measurement

IF 1

Data in Brief Pub Date : 2025-02-26 DOI: 10.1016/j.dib.2025.111429

Al Fathjri Wisesa , Eny Latifah , Sutrisno , Suyatno , Tutut Chusniyah , Kukuh Setyo Pambudi , Mochamad Khoirul Rifai , Moh. Fariq Firdaus Karim , Anugerah Agung Dwi Putra

{"title":"2D data arrangement to train ANN for depression levels measurement","authors":"Al Fathjri Wisesa , Eny Latifah , Sutrisno , Suyatno , Tutut Chusniyah , Kukuh Setyo Pambudi , Mochamad Khoirul Rifai , Moh. Fariq Firdaus Karim , Anugerah Agung Dwi Putra","doi":"10.1016/j.dib.2025.111429","DOIUrl":"10.1016/j.dib.2025.111429","url":null,"abstract":"<div><div>We arranged data to train Artificial Neural Networks (ANNs) designed as a depression-level measurement tool. Even though, as an advanced form of stress, depression impacts many physical parameters disorder, measuring depression using only physical parameters is insufficient. It is urgent to integrate comprehensively psychological and physical parameters as two dimensions, 2D, data. We harvested the dataset of 95 respondents from college students. The physical dimension consisted of four parameters measured noninvasively, and the psychological dimension was assessed using the Perceived Stress Scale (PSS). The initial analysis revealed notable correlations between increased stress perception and certain physical parameters analysis, particularly an elevated heart rate and reduced sleep quality. The highly significant p-value provided strong evidence that the observed difference in means is not coincidental. According to data processing, we have the data set including all levels of depression to enhance the effectiveness of measuring depression. Using two-dimensional data, we aim for the ANNs to learn interaction patterns between these parameters, improving accuracy in depression detection.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111429"},"PeriodicalIF":1.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580532","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

Linked avian influenza epidemiological and genomic data in EMPRES-i for epidemic intelligence (2012–2021)

IF 1

Data in Brief Pub Date : 2025-02-25 DOI: 10.1016/j.dib.2025.111410

Nejat Arınık , Roberto Interdonato , Mathieu Roche , Maguelonne Teisseire

{"title":"Linked avian influenza epidemiological and genomic data in EMPRES-i for epidemic intelligence (2012–2021)","authors":"Nejat Arınık , Roberto Interdonato , Mathieu Roche , Maguelonne Teisseire","doi":"10.1016/j.dib.2025.111410","DOIUrl":"10.1016/j.dib.2025.111410","url":null,"abstract":"<div><div>Due to its highly contagious nature, Avian Influenza (AI) is considered an animal health emergency affecting commercial sector and wild bird populations. Several genome sequencing databases have been created to help researchers understand how AI viruses evolve, spread, and cause disease. However, for a global epidemic monitoring approach, they need to be combined to public health surveillance systems, the well-one being EMPRES-i from the World Organisation for Animal Health (WOAH) and the Food and Agriculture Organization of the United Nations (FAO).</div><div>This paper presents a new AI dataset, in which EMPRES-i is enriched thanks to the genome sequence data of Avian Influenza cases affecting bird species from 2012 to 2021, publicly provided by the Bacterial and Viral Bioinformatics Resource Center (BV-BRC). This dataset is obtained by automatically linking sequence information in BV-BRC to the AI events in EMPRES-i, which results in “<em>putatively</em>” linked events between these two sources. The collected data is structured by nature, but it is preprocessed and normalized for the purpose of high-quality data linkage. Moreover, several data linkage strategies and missing information handling are introduced. To show the usefulness of our dataset, we quantitatively evaluate the proposed strategies in randomly sampled events and present in the end a diffusion network inference task.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111410"},"PeriodicalIF":1.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562951","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

Complete chloroplast genome data of Trollius ledebourii Rehb, an important medicinal plant species

IF 1

Data in Brief Pub Date : 2025-02-25 DOI: 10.1016/j.dib.2025.111408

Bo Liu , Lingyang Kong , Yuhua Zhang , Yu long Zhang , Weichao Ren , Xiubo Liu , Jiao Xu , Wei Ma

引用次数: 0

Multifrequency low-level laser-assisted mastopexy in 231 consecutive patients: A dataset

IF 1

Data in Brief Pub Date : 2025-02-24 DOI: 10.1016/j.dib.2025.111423

Gabriel Cubillos-Valencia , Neidalis Vasquez , Andrés Miguel Ortegón Pulido , Diego Rivera-Porras , Julio Cesar Contreras-Velásquez , Valmore Bermúdez

{"title":"Multifrequency low-level laser-assisted mastopexy in 231 consecutive patients: A dataset","authors":"Gabriel Cubillos-Valencia , Neidalis Vasquez , Andrés Miguel Ortegón Pulido , Diego Rivera-Porras , Julio Cesar Contreras-Velásquez , Valmore Bermúdez","doi":"10.1016/j.dib.2025.111423","DOIUrl":"10.1016/j.dib.2025.111423","url":null,"abstract":"<div><div>Breast ptosis, the inferior displacement of the nipple–areola complex, is predominantly attributed to age-related collagen degradation within the breast parenchyma as a result of fibroblast senescence and postmenopausal estrogen depletion, which together result in skin ageing and mammary adipose tissue reduction. This Dataset reports the clinical information and measurements of 231 patients who underwent multifrequency low-level laser-assisted mastopexy. Data were collected prospectively between February 2021 and November 2023. All patients' references and identification data were anonymized to ensure compliance with Colombian legal regulations. Subsequently, data were translated from Spanish to English and stored in both .xls and .csv formats. This study aimed to evaluate the effect of the procedure on breast ptosis degree and the sternal notch to nipple distance (SNND) to assess the evolution of breast ptosis. This article presents demographic, personal, and familial history data, anthropometric measurements, breast ptosis degree classified according to the Regnault system, SNND measurements, and complications categorized using the Clavien-Dindo classification system.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111423"},"PeriodicalIF":1.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529053","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

CORHOH: Text corpus of holocaust oral histories

IF 1

Data in Brief Pub Date : 2025-02-24 DOI: 10.1016/j.dib.2025.111426

Daban Q. Jaff

{"title":"CORHOH: Text corpus of holocaust oral histories","authors":"Daban Q. Jaff","doi":"10.1016/j.dib.2025.111426","DOIUrl":"10.1016/j.dib.2025.111426","url":null,"abstract":"<div><div>This paper outlines the compilation and annotation process of CORHOH: Text CORpus of <strong>H</strong>olocaust <strong>O</strong>ral <strong>H</strong>istories. The corpus consists of 500 oral histories, each narrative form one survivor. The transcripts of the oral histories are retrieved from the <em>Let Them Speak Project</em> [1]. The transcripts are normalized and further annotated. The corpus offers rich metadata about both the testimony givers and the interviews. All technical content is removed, and a unique identifier is assigned to each question (posed by the interviewer) and answer (provided by the survivor). The corpus complies with the TEI guidelines [2]. The corpus includes 106,519 questions and 107,125 answers, making it easy to distinguish between the utterances that belong to the holocaust survivor or anyone else who is involved in the interview, primarily the interviewer. CORHOH is particularly suited for studies on trauma expression and psychological concepts embedded in survivors' narratives. Additionally, it offers potential for data mining to uncover patterns (e.g., migration trends) and supports natural language processing techniques, such as topic modelling, sentiment analysis, and named entity recognition. The CORHOH data is courtesy of the United States Holocaust Memorial Museum (USHMM) and is publicly available under the CC BY-NC-SA 4.0 license.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111426"},"PeriodicalIF":1.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549923","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

Transcriptome dataset to investigate the effect of deep seawater on the gene expression and functional compounds of leaves of Ligularia stenocephala

IF 1

Data in Brief Pub Date : 2025-02-22 DOI: 10.1016/j.dib.2025.111427

Dewi Komang Anggita , Bimpe Suliyat Azeez , Se-Jin Oh , Jong-Kuk Na

{"title":"Transcriptome dataset to investigate the effect of deep seawater on the gene expression and functional compounds of leaves of Ligularia stenocephala","authors":"Dewi Komang Anggita , Bimpe Suliyat Azeez , Se-Jin Oh , Jong-Kuk Na","doi":"10.1016/j.dib.2025.111427","DOIUrl":"10.1016/j.dib.2025.111427","url":null,"abstract":"<div><div>Seawater is often applied to improve crop quality by supplying minerals to the crop. Due to high salt concentration of seawater, one of key factors for successful utilization of seawater in agriculture would be optimal dilution ratios, which can be determined by physiological and genomic studies. However, genomic studies of crops treated with seawater have rarely been investigated. <em>Ligularia stenocephala</em>, a vegetable and medicinal crop [<span><span>1</span></span>], is used to examine the genomic changes in response to the application of deep seawater (DSW) from 605 m depth. RNA sequencing was carried out for three different leaf samples of <em>L. stenocephala</em> treated with 0% (NT), 5% (DSW5), or 10% (DSW10) of DSW using the Illumina NovaSeq 6000 sequencing system. The RNA sequencing generated 38.1 million raw reads for NT, 29.2 for DSW5, and 30.5 for DSW10, respectively. The length of total raw reads was 2.94 (DSW5), 3.08 (DSW10), and 3.85 Gb (NT), while the total length of filtered clean reads ranged between 2.88 Gb (DSW5) and 3.75 Gb (NT). GC contents range between 42.9% (DSW5) and 43.58 (DSW10), while the Q20 quality score ranged between 98.63% (DSW10) and 98.66% (DSW5). Due to the lack of the reference genome for read mapping, the three transcriptome data from this study were merged to generate a reference transcriptome. The percentage of mapped reads ranged from 89.63 (DSW10) to 98.66% (DSW5). The data is accessible at NCBI BioProject: <span><span>PRJNA1149490</span><svg><path></path></svg></span>. These data provide invaluable information not only for understanding genes responsive to deep seawater application in crop cultivation but also for determining the optimal dilution ratio of DSW without causing salt stress on crops by examining expression profiles of stress-responsive genes.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111427"},"PeriodicalIF":1.0,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534457","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 the long-term monitoring of foundation vertical deformations on medium-expansive soil

IF 1

Data in Brief Pub Date : 2025-02-21 DOI: 10.1016/j.dib.2025.111422

Hawkar Hashim Ibrahim, Rizgar Ali Hummadi

{"title":"Dataset on the long-term monitoring of foundation vertical deformations on medium-expansive soil","authors":"Hawkar Hashim Ibrahim, Rizgar Ali Hummadi","doi":"10.1016/j.dib.2025.111422","DOIUrl":"10.1016/j.dib.2025.111422","url":null,"abstract":"<div><div>This paper presents a complete data set from the long-term field monitoring of vertical deformation in four footings resting on medium-expansive soil. The four key variables (vertical deformation, daily average air temperature, weekly cumulative rainfall, and soil water content at a depth of 60 cm) were recorded over a period of 974 days. The vertical deformations were measured with high-precision dial gauges. At the same time, the advanced instruments, Bosch GLL 3-80 G Professional line laser and LEICA DNA 10 digital levels were cross-used for measurement to ensure the accuracy and reliability of the results. The data collection was designed to include the effects of expansive soil properties, such as swelling during wet seasons and shrinkage during dry seasons. This is necessary for understanding the soil-structure interaction under natural field conditions, which differs considerably from controlled laboratory studies. This dataset presents a great possibility of being reused by researchers to support further studies on soil-structure interaction, develop predictive models for expansive soils, and analyze long-term structural stability. It is particularly useful in developing machine learning algorithms that can be used to predict foundation behavior in response to different environmental conditions, optimize foundation designs on expansive soils, and specifically predict foundation heave. The availability of this dataset provides an invaluable resource in advancing geotechnical engineering research.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111422"},"PeriodicalIF":1.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534478","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