cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/y5h6v8w6ms.1
title: Multispectral images of apples for ripeness, sweetness and variety grading [Data set]

description: This dataset originates from an extensive research effort focused on the development and application of a cost-effective, custom-built multi-spectral imaging chamber designed for evaluating the quality of apples. The imaging setup is capable of capturing spectral reflectance across a range of wavelength bands, enabling detailed, non-invasive analysis of fruit characteristics such as ripeness, sweetness, and varietal differences. In this study, a total of 8 wavelengths were considered. All images were collected under uniform and controlled lighting to minimize environmental variability and enhance data consistency.

For Grading by Ripeness, three classes were considered: Under-Ripe, Ripe and Over-Ripe. For Grading by Ripeness, the following five types of apples were considered, each of four in quantity.
1. Red Delicious (USA)
2. Royal Gala
3. Red Delicious (New Zealand)
4. Washington
5. Kinnaur

For Grading by Variety, three classes- Red Delicious USA, Alpita and Royal Gala were considered. For Grading by Variety for all 3 types, each of the seven in quantity was taken. 

For Grading by Sweetness, four classes were considered according to sugar content in % Brix in apples: 10, 12, 13, and 15 classes. For Grading by Sweetness, five varieties were considered, each of four in quantity. The following types of apples were considered for Grading by Sweetness.
1. Red Delicious (USA) 
2. Royal Gala 
3. Red Delicious (New Zealand) 
4. Washington 
5. Kinnaur 
The images are concatenated with the help of MATLAB code and the concatenated dataset is created for grading by sweetness, ripeness and variety. For this study, APPLENET, a CNN-based architecture, was used to process the concatenated images, and the accuracy achieved was 87 %,65 % and 92 % for grading by ripeness, sweetness and variety, respectively. 
The dataset is labelled and structured to support a wide range of applications, particularly in the domains of agricultural technology and food quality monitoring. It offers possible use cases for developing classification and regression models for fruit grading, maturity evaluation, and early detection of surface-level defects. Researchers working on agricultural automation, deep learning in food quality inspection, or horticulture may find this dataset particularly valuable.

Beyond apples, the methodology used for image acquisition and data annotation can be adapted for other fruits, offering scalability for broader agricultural research. The detailed documentation and consistent imaging protocol enhance reproducibility, making this dataset a useful benchmark for relative studies.

This data collection contributes meaningfully to ongoing efforts in computer vision and AI-powered agriculture by providing a reliable, annotated source of multi-spectral fruit images for non-destructive quality evaluation.
DOI: 10.17632/y5h6v8w6ms.2
title: Multispectral images of apples for ripeness, sweetness and variety grading [Data set]

description: This dataset originates from an extensive research effort focused on the development and application of a cost-effective, custom-built multi-spectral imaging chamber designed for evaluating the quality of apples. The imaging setup is capable of capturing spectral reflectance across a range of wavelength bands, enabling detailed, non-invasive analysis of fruit characteristics such as ripeness, sweetness, and varietal differences. In this study, a total of 8 wavelengths were considered. All images were collected under uniform and controlled lighting to minimize environmental variability and enhance data consistency.

For Grading by Ripeness, three classes were considered: Under-Ripe, Ripe and Over-Ripe. For Grading by Ripeness, the following five types of apples were considered, each of four in quantity.
1. Red Delicious (USA)
2. Royal Gala
3. Red Delicious (New Zealand)
4. Washington
5. Kinnaur

For Grading by Variety, three classes- Red Delicious USA, Alpita and Royal Gala were considered. For Grading by Variety for all 3 types, each of the seven in quantity was taken. 

For Grading by Sweetness, four classes were considered according to sugar content in % Brix in apples: 10, 12, 13, and 15 classes. For Grading by Sweetness, five varieties were considered, each of four in quantity. The following types of apples were considered for Grading by Sweetness.
1. Red Delicious (USA) 
2. Royal Gala 
3. Red Delicious (New Zealand) 
4. Washington 
5. Kinnaur 
The images are concatenated with the help of MATLAB code and the concatenated dataset is created for grading by sweetness, ripeness and variety. For this study, APPLENET, a CNN-based architecture, was used to process the concatenated images, and the accuracy achieved was 87 %,65 % and 92 % for grading by ripeness, sweetness and variety, respectively. 
The dataset is labelled and structured to support a wide range of applications, particularly in the domains of agricultural technology and food quality monitoring. It offers possible use cases for developing classification and regression models for fruit grading, maturity evaluation, and early detection of surface-level defects. Researchers working on agricultural automation, deep learning in food quality inspection, or horticulture may find this dataset particularly valuable.

Beyond apples, the methodology used for image acquisition and data annotation can be adapted for other fruits, offering scalability for broader agricultural research. The detailed documentation and consistent imaging protocol enhance reproducibility, making this dataset a useful benchmark for relative studies.

This data collection contributes meaningfully to ongoing efforts in computer vision and AI-powered agriculture by providing a reliable, annotated source of multi-spectral fruit images for non-destructive quality evaluation.
DOI: 10.15468/dl.4cx9k6
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Ethiopia, Kenya)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Typha latifolia L."
 ]
}

 The dataset includes 23 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030343-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/gp4n7xwwsw.1
title: Spatiotemporal Dynamics and Driving Mechanisms of Water Erosion in the Shiyang River Basin, Northwest China (2001–2020)

description: This dataset was developed to investigate the spatiotemporal patterns and driving factors of water erosion in the Shiyang River Basin from 2001 to 2020. Water erosion intensity in this region is influenced not only by natural factors such as precipitation and topography, but also significantly by land use change and vegetation dynamics. Moreover, these driving factors may interact to amplify erosion risks. The dataset includes the following components:
(1)Simulated Water Erosion Data:
Annual raster layers of potential soil erosion, transport capacity, and net water erosion rate, generated using an integrated RUSLE and TLSD model. These data capture both the potential for soil detachment and the actual sediment transport across the basin landscape. In addition, multi-year spatial trend data and inter-annual change maps are provided to illustrate erosion dynamics over time.
(2)Erosion Classification and Transition Data:
Net water erosion intensity was categorized into seven classes. The spatial variation in erosion severity and the area transition matrix across different years were compiled to assess temporal changes and spatial dynamics in erosion patterns.
(3)Driving Factor Analysis (Random Forest):
Output from the Random Forest model quantifies the relative importance of various natural and anthropogenic drivers of erosion. Summary tables and maps illustrate erosion responses under different environmental gradients, including topography, LUCC, and NDVI.
(4)Supplementary Data:
Raster datasets for all RUSLE input factors (rainfall erosivity, soil erodibility, slope and slope length, cover management, and support practice), NDVI, topsoil texture, and LUCC data are included. The dataset also provides statistics on net soil erosion rate, sediment deposition, and NDVI values across different slope classes and under various land use change scenarios.
Data Collection and Processing:
Climate and topographic data were obtained from national and international geospatial databases. Slope and slope length were derived from DEM data, and rainfall data were used to calculate rainfall erosivity. NDVI and land use/land cover (LUCC) data were extracted from MODIS and Landsat imagery and reclassified based on regional characteristics.
Soil erosion was simulated using a calibrated RUSLE-TLSD model. Model inputs include rainfall erosivity, soil erodibility, topographic factors, vegetation cover, and land management practices. Sediment yield observations were used for model validation.
Random forest analysis was conducted in R using the “randomForest” and “rfPermute” packages. The model was trained with 500 trees to evaluate the importance of environmental variables in driving net water erosion.
 All raster datasets were resampled to a uniform 90 m resolution for spatial analysis.
DOI: 10.17632/xmv76cvvsx.1
title: Dataset for the evaluation of the cooling performance of parks, cemeteries, and allotments in Berlin (Germany)

description: This study inspected 230 parks, 154 cemeteries, and 512 allotments over six dates for the city of Berlin (Germany) using Landsat 8 TM images. For this purpose, the three cooling capacity indicators, Park Cooling Distance (PCD), Park Cooling Intensity (PCI), and Park Cooling Area (PCA), were calculated using the turning point method. To explain the cooling capacity of the three urban green spaces, various influencing factors were considered and statistically analyzed using correlations and random forest. The results show that cemeteries have a more constant cooling capacity (PCD &gt; 0 over all six dates) with 85.7 % than parks (79.1 %) and allotments (53.4 %). Parks show the highest mean PCD of 259 meters, compared to 217 meters for cemeteries and 187 meters for allotments, while the cemeteries have the highest mean PCI of 2.23 °C, compared to parks (2.04 °C) and allotments (1.08 °C). The proportion of vegetation and sealed surfaces influences the PCI of all three urban green spaces. In addition, the area size and perimeter show a high influence on the PCI of the cemeteries. The water areas in the surroundings show a high influence on the PCD of the three urban green spaces. The results indicate that, in addition to parks, cemeteries also have a high cooling capacity, but are of less benefit to the residents due to their usage and location in the urban area.
DOI: 10.15468/dl.dv6e6c
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (India, China, Myanmar, Viet Nam, Cambodia, Indonesia, Nepal, Philippines, Malaysia, Chinese Taipei, Bangladesh, Lao People’s Democratic Republic, Thailand, Bhutan)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Anagallis L."
 ]
}

 The dataset includes 9 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030345-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2ts4mpby8r.1
title: Certified Lab Grown Diamond Infinity Wedding Band Ring – Eternal Love in Every Detail

description: Celebrate your everlasting bond with this Certified Lab Grown Diamond Infinity Wedding Band Ring. Featuring 100 brilliant EF-VS quality lab grown diamonds totaling approximately 0.80 carats, this 10 mm wide band showcases a unique wave-like pattern intertwined with a smooth infinity symbol. Perfect as a Lab Grown Diamond Wedding Band or paired with Lab Grown Diamond Engagement Rings, it symbolizes infinite love and commitment.

Why choose Rosec Jewels?

- Certified EF-VS quality lab grown diamonds with exceptional brilliance

- Ethically sourced, conflict-free diamonds for peace of mind

- Secure prong settings ensuring durability and sparkle

- Expertly handcrafted with a modern infinity design

- Free one-year warranty, 30-day returns, and insured shipping
DOI: 10.17632/wwvwgvb8n7.1
title: TRAF2 saxs
DOI: 10.17632/wwvwgvb8n7.2
title: TRAF2 saxs
DOI: 10.17632/3nrpj45hwz.1
title: Data to: Titanium, Sr and Nd isotopic compositions of Lake Qarun sediments; assessing sediment provenance in the Nile and Ti isotope fractionation in the Nile Delta

description: We present Sr, Nd, and Ti isotope data from Nile sediments at Lake Qarun, along with Ti isotopic compositions from Nile Delta samples collected in Wadi Natrun. The Ti isotopic compositions of all sediments analysed range from +0.11‰ to +0.20‰ and average at +0.149 ± 0.015 ‰ (2SE, n=14). The 87Sr/86Sr ratios and Nd values of Lake Qarun sediments exhibit small variations and average at 0.70754 and -2.5, respectively. These radiogenic isotope signatures are characteristic for Nile sediments and plot in between those from the Nile in Sudan and the Nile Delta. Furthermore, the heavy Ti isotopic compositions of Lake Qarun samples match those of the Eastern Mediterranean Sea sediments. Therefore, Nile sediments carry a heavy 49Ti signature already before entering the delta, proofing that hydrodynamic mineral sorting within it is not responsible for the Ti isotope values of the Eastern Mediterranean Sea sediments. Instead, we show with trace element modelling that the proportion of felsic material transported in Nile sediments increases from the Atbara (3%) to the Blue Nile (22%) and reaches between 44% to 68% in the Nile Delta. These estimated proportions of felsic lithologies correlate favourably with Sr and Nd isotopes, suggesting that the observed variations in these isotopes along the Nile are primarily driven by the addition of felsic source rocks to the sediment load. The heavy Ti isotopic composition of Nile sediments entering the delta can be plausibly explained by a contribution of approximately 45% felsic rock material, derived from felsic Ethiopian Trap lithologies as well as from bedrock or sediments within the diverse Nile catchment areas.
DOI: 10.17632/mg7chh6w7z.1
title: TRAF2 saxs H5
DOI: 10.17632/ryzkp4g2bz
title: Data from the Sina Weibo platform during the 2023-2024 influenza season (October 2023 to March 2024)

description: This document consists of two parts data for sentiment analysis, content analysis and developed a dynamic PSHSLCR model to quantify emotional contagion patterns driven by heterogeneous risk perception among netizens and post influence, and conducted intervention simulations to develop strategies for mitigating the spread of negative emotions among netizens. The first part collected the public data of the # Influenza # topic on Sina Weibo from October 1, 2023 to March 25, 2024. The dataset includes the original posts (username, user ID, posting time, content, and geolocation by IP city) and the corresponding comments (commenter’s username, ID, comment time, content, and geolocation by IP city), and the final dataset comprised 439 posts and 4,968 comments. The second part is the key words and stop words of this topic required for drawing the word clouds.
DOI: 10.17632/ryzkp4g2bz.1
title: Data from the Sina Weibo platform during the 2023-2024 influenza season (October 2023 to March 2024)

description: This document consists of two parts data for sentiment analysis, content analysis and developed a dynamic PSHSLCR model to quantify emotional contagion patterns driven by heterogeneous risk perception among netizens and post influence, and conducted intervention simulations to develop strategies for mitigating the spread of negative emotions among netizens. The first part collected the public data of the # Influenza # topic on Sina Weibo from October 1, 2023 to March 25, 2024. The dataset includes the original posts (username, user ID, posting time, content, and geolocation by IP city) and the corresponding comments (commenter’s username, ID, comment time, content, and geolocation by IP city), and the final dataset comprised 439 posts and 4,968 comments. The second part is the key words and stop words of this topic required for drawing the word clouds.
DOI: 10.15468/dl.xhmywk
title: Occurrence Download

description: A dataset containing 54676 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oecanthus Serville, 1831"
 ]
}

 The dataset includes 54676 records from 1088 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030332-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mcdhd7
title: Occurrence Download

description: A dataset containing 355981 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Fomitopsis pinicola (Sw.) P.Karst., Xiphinema americanum Cobb, 1913, Phymatotrichopsis omnivora (Duggar) Hennebert, Grovesinia moricola (I.Hino) Redhead, Botryosphaeria dothidea (Moug.) Ces. & De Not., Gloeodes pomigena (Schwein.) Colby, Belonolaimus longicaudatus Rau, 1958, Diaporthe orthoceras (Fr.) Nitschke, Trametes elegans (Spreng.) Fr., Pseudocercospora angraeci (Feuilleaub. & Roum.) U.Braun & Urtiaga, Ramularia brunnea Peck, Fusarium acaciae-mearnsii O'Donnell, T.Aoki, Kistler & Geiser, Phyllosticta allii Baudyš, Septoria aciculosa Ellis & Everh., Kretzschmaria deusta (Hoffm.) P.M.D.Martin, Meripilus giganteus (Pers.) P.Karst., Xeromphalina fraxinophila A.H.Sm., Nemania serpens (Pers.) Gray, Phytophthora cinnamomi Rands, Ceratocystis fimbriata Ellis & Halst., Fabisporus sanguineus (L.) Zmitr., Phoradendron racemosum (Aubl.) Krug & Urb., Pappia fissilis (Berk. & M.A.Curtis) Zmitr., Thyrostroma compactum (Sacc.) Höhn., Ganoderma lucidum (Curtis) P.Karst., Rhizomorpha subcorticalis P.Micheli ex Pers., 1801, Didymella arachidicola (Khokhr.) Tomilin, Mycosphaerella punctiformis (Pers.) Starbäck, Oidium arachidis Chorin, Microsphaera variabilis Y.N.Yu, Phellinus gilvus (Schwein.) Pat., Phytophthora palmivora (E.J.Butler) E.J.Butler, Phyllactinia guttata (Wallr.) Lév., Rhizoctonia solani J.G.Kühn, Pythium acanthicum Drechsler, Botryosphaeria stevensii Shoemaker, Ganoderma applanatum (Pers.) Pat., Erysiphe penicillata (Wallr.) Link, Meloidogyne incognita (Kofoid & White, 1919) Chitwood, 1949, Corythucha ciliata (Say, 1832), Phomopsis radula (Berk. & Broome) Grove, Dichomera mutabilis (Berk. & Broome) Sacc., Hapalocystis berkeleyi Auersw. ex Fuckel, Bloxamia leucophthalma (Lév.) Höhn., Inonotus hispidus (Bull.) P.Karst., Pholiota squarrosa (Vahl) P.Kumm., Perenniporia fraxinea (Bull.) Ryvarden, Vuilleminia comedens (Nees) Maire, Heterobasidion annosum (Fr.) Bref., Gibberella zeae (Schwein.) Petch)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 355981 records from 1029 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002775-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.thajjf
title: Occurrence Download

description: A dataset containing 4927117 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Polypodiales)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1981",
 "Geometry POLYGON((-30 25,50 25,50 75,-30 75,-30 25))"
 ]
}

 The dataset includes 4927117 records from 3453 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002780-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29148452.v2
title: Replication Kit for "In a Dataspace Far, Far Away: Incompatible ML-Enabled System Data Pairs"

description: Replication kit for [ASE 2025] In a Dataspace Far, Far Away: Measuring the 'Distance' of Incompatible ML-Enabled System Data Pairs
DOI: 10.6084/m9.figshare.29148452.v1
title: Replication Kit for "In a Dataspace Far, Far Away: Incompatible ML-Enabled System Data Pairs"

description: Replication kit for [ASE 2025] In a Dataspace Far, Far Away: Measuring the 'Distance' of Incompatible ML-Enabled System Data Pairs
DOI: 10.3535/6we-ss1-a08
title: Capra Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/9fq-4ec-yxa
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/rc5-b03-8wz
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/yc7-13z-hm8
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/6sf-f2c-b8r
title: Argentina

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ea6-plt-1bv
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/473-b2m-6qz
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/pbc-kc3-03m
title: Sus scrofa Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/6p2-27k-am3
title: Odontaspis

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/v90-wwn-j0l
title: †Sigmomorphina soluta Brotzen, 1948

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/8cz-k17-9bh
title: Chondrichthyes

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ts5-lmv-zq4
title: †Discorbis supracretacea Schijfsma, 1946

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/yve-w68-1f5
title: Mollusca

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/jdw-p80-htm
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/yjh-5ry-jm2
title: Pollicipes

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7x2-7hn-g0z
title: Heterocyathus aequicostatus Milne Edwards & Haime, 1848

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/gw7-efy-6ya
title: Cnidaria

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/wv3-m92-dlw
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/shx-rgv-02h
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/zl9-bpv-mjz
title: Chordata

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.57837/actris-ares/50fh-cc03
title: ACTRIS-EARLINET 2025 lidar ratio profiles at 355nm over POT Potenza-Italy

description: ACTRIS-EARLINET 2025 lidar ratio profiles at 355nm over POT Potenza-Italy.
This dataset collects all the lidar ratio profiles at 355nm collected in 2025 at the aerosol remote sensing POT station (Potenza – Italy). This dataset is incremental: data collected in 2025 are added as soon as a new observation is collected in 2025 and added to the ACTRIS/EARLINET database.