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Data used in the article 'Effect of defatted melon seed residue (DMSR) on dough development and bread quality'
Get PDFThis dataset contains data obtained from experimental work on defatted melon seed residue (DMSR) in the production of a white loaf of bread. Three doughs and bread formulations were evaluated including a control (100% wheat flour) and two formulations in which wheat flour was replaced with 5% and 10% of DMSR. Data was obtained using a farinograph (dough water absorption, dough development time, dough stability time, and mixing tolerance index), texture analyser with a Kieffer rig (dough extensibility; hardness, springiness, cohesiveness, chewiness of breads), moisture balance (bread moisture), oven (weight loss during baking), Volscan Profiler (bread specific volume), chroma meter (bread crust and crumb colour), Image J software (cell number and cell average size)
Data supporting the PhD Thesis 'Socio-economic responses to Late Holocene climate variability and environmental change in the Peruvian Andes'
No full textPrimary data included within the Handley 2022 PhD Thesis 'Socio-economic responses to Late Holocene climate variability and environmental change in the Peruvian Andes'. Data consists of pollen, phytolith, micro-XRF, and organic matter content records for three infilled basins in the Peruvian Andes (Huarca, Callejón de Huaylas, Ancash Region; Antaycocha, Chillón Valley, Lima Region; Ayapampa, Chicha-Soras Valley, Apurímac Region). The three sites provide a transect across the Andes to better understand regional differences in social responses to, and variations in, environmental change over the past 2500 years. The three basins span from full-Holocene (Huarca ~11,500 yrs) sequences to Late Holocene timescales (Antaycocha ~3000 yrs; Ayapampa ~4000 yrs). However the focus for most of the analysis for this thesis has focused on the last 2500 years as this is the period of greatest cultural and agricultural development in the Peruvian Andes.
Pollen data was obtained by standard procedures following Faegri and Irersen (1989) and Moore, Web and Collinson (1991) and involving the sieving, heavy liquid density separation and acetolysis of pollen samples. Phytolith analysis was carried out using the dry-ashing method outlined in Parr et al., 2001, with the addition of a sonication step (Lombardo et al., 2016). Both phytolith and pollen analysis was carried out using a high-powered stereo microscope and the raw counts obtained from these analyses is included within this dataset.
Micro-XRF data was obtained using a ITRAX core scanner housed at the British Ocean Sediment Core Research Facility, National Oceanography Centre, Southampton (BOSCORF). XRF exposure time was 15 seconds per sampling point, using a Mo tube and run at a voltage of 30KV and a current of 30mA. Data presented in this dataset are in counts per second as obtained via the ITRAX scanner. Organic Matter Content (OMC) was obtained via Loss on Ignition, with material being heated to 550oC (following Bengtsson and Enell, 1986)
Screen air temperature measurements 2019-2020
Get PDFA comparison between two different thermometer enclosures was undertaken at the Reading University Atmospheric Observatory, to investigate the uncertainties associated with conventional meteorological measurements of air temperature using platinum resistance thermometers. One thermometer was contained within a conventional, naturally ventilated large MetSpec thermometer screen and another within a forced ventilated (electrically aspirated) thermometer screen (Young model 43502). Measurements were obtained between 7 November 2019 (day 188 of 2019) and 16 August 2020 (day 229 of 2020), alongside a wide range of other meteorological measurements also made at the site
Temporal variation in global crop pollinator communities
No full textThis dataset is in a single Excel file that contains information on the richness and abundance of insect pollinators in crop systems collated from previous studies on crop systems from across the world.
The data file has five spreadsheets, details of which are outlined below:
1. Metadata
2. Summary - Information on study ID, country, crop, years of sampling and no. of sites
3. Abundance data - Species level data on pollinator abundance recorded at each study site
4. Site data - Site data on type of field/farm/orchard, and years of sampling
5. Climate data - Temperature data for sampling dates for each study and site where availabl
EMBSeCBIO pollen database
Get PDFThe EMBSeCBIO pollen database is a compilation of pollen counts or pollen percentages for 1132 modern entities (modern is defined as younger than 150 cal. years) and 187 fossil entities, in the Mediterranean-Black Sea Caspian-Corridor, located between 28°-49°N and 20°-62°E. The database includes tables describing the characteristics of the sites from which the records were obtained. Information on dating and the original age-depth models for the fossil records are included. New age-depth models have been created using the IntCal20 calibration curve for 148 records
Deep learning for the estimation of water-levels using river cameras: networks and datasets
No full textThis dataset contains:
- The networks weights (weights.zip) that were obtained and used in our papers [1, 2]. We refer to these papers for the methodology used to obtain those weights. Those weights can be used for the binary water semantic segmentation of new images, or for comparison with our methods.
- The river camera images (DIGLIS.zip/EVESHAM.zip/STRENSHAM.zip/TEWKESBURY.zip) for the experiments that we presented in [2]. The images can be used for water segmentation and flood analysis purposes.
Related publications:
[1] Remy Vandaele, Sarah L. Dance, Varun Ojha; Automated water segmentation and river level detection on camera images using transfer learning; 2020; Proceedings of the DAGM German Conference on Pattern Recognition (Accepted)
[2] Remy Vandaele, Sarah L. Dance, Varun Ojha; Deep learning for the estimation of water-levels using river cameras; 2020; Hydrology and Earth System Science (in preparation
Crop pollinator communities - global dataset
No full text***This dataset has been withdrawn: An updated version of the dataset is available at http://dx.doi.org/10.17864/1947.291***
This dataset is in a single Excel file that contains information on the richness and abundance of insect pollinators in crop systems collated from previous studies on crop systems from across the world.
The data file has five spreadsheets, details of which are outlined below:
1. Metadata
2. Summary - Information on study ID, country, crop, years of sampling and no. of sites
3. Abundance data - Species level data on pollinator abundance recorded at each study site
4. Site data - Site data on area covered, years of sampling and geographic coordinates
5. Climate data - Climate data where available for each study recorded during pollinator sampling
This dataset was generated by collating data on previous published/unpublished studies on crop pollinator communities from different crop systems in multiple countries. The collated data in this dataset has information from 31 studies on 17 different crops from 9 different countries. The information collated included site locations, climate data (if recorded), pollinator abundance data and species level information on crop pollinator communities observed in these study systems
Sonning Farm fog modification experiment
Get PDFAn experiment investigating introducing charge into a natural fog was conducted at Sonning Farm (51.48155 °N, 0.897154 °W), University of Reading, in Spring 2020. This archive contains data files from measuring instruments deployed there, for 15th and 16th March 2020, when fog events occurred. Measurements of droplet concentration were made with a LOAC (Light Optical Aerosol Counter), atmospheric electric field with a JCI131 electric field mill, and three-dimensional wind speed with a Gill sonic anemometer. Switching times of a negative corona ion source were also recorded
Apple fruit set and quality under contrasting pollination treatments for multiple apple varieties from multiple countries
Get PDFThese data include information on fruit set and fruit quality (size, weight, seed number, sugar content and firmness) of apples grown under different pollination treatments including pollinator exclusion (no visitation by insects), open pollination (visitation by insects) and supplementary pollination (hand pollinated). Data were collected as part of several projects, and include data on multiple different varieties of apples from several different countries
The Reading Everyday Emotion Database (REED)
Get PDFWe developed a set of audio-visual recordings of emotions called the Reading Everyday Emotion Database (REED). Twenty-two native British English adults (12 females + 10 males) from a diverse age range and with drama/acting experience were recorded producing utterances of various lengths in spoken and sung conditions in 13 various emotions (neutral, the 6 basic emotions, and 6 complex emotions) using everyday recording devices (e.g., laptops, mobile phones, etc.). All the recordings were validated by a separate, independent group of raters (n = 155 adults), and the database consists only of recordings that were recognised above chance.
This dataset contains metadata about the files in the database (in the README file). In addition, it also contains:
- data_validation.csv -- Data for the validation task
- UoR-DataAccessAgreement-000336.pdf -- The REED Data Access Agreement
- example_clips.zip -- Example clips of the REED
- InfoSheet.pdf -- Information sheet (the copy used for participants involved in the REED study)
- ConsentForm.pdf -- Consent form (the copy used for participants involved in the REED study)
Not available in current dataset:
- The REED (will be sent to user once they have signed the Data Access Agreement)
To request access to the REED, please complete a data access request at https://redcap.link/data-request. If your application meets the criteria, a Data Access Agreement (see "UoR-DataAccessAgreement-000336.pdf" for a copy) will be sent to your nominated institutional signatory. Once the agreement is signed and returned, the Research Data Service team will arrange secure access to the dataset