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65 results for “sow”
Data of "Decreasing the level of hemicelluloses in sow's lactation diet affects the milk composition and post-weaning performances of low birthweight piglets"
<p>This study showed the effects of decreasing the levels of hemicelluloses in sow’s lactation diet on milk composition and on sow and piglet performances.</p> <p>Sow_performances.csv: A comma separated value file of data used to investigate the relationship between the performances of Swiss Large White sows and decreasing levels of hemicelluloses in lactation diet.</p> <p>Milk_composition.csv: A comma separated value file of data used to investigate the relationship between the milk composition of Swiss Large White sows and decreasing levels of hemicelluloses in lactation diet.</p> <p>Piglets_performances.csv: A comma separated value file of data used to investigate the relationship between the performances of Swiss Large White pigs and decreasing levels of hemicelluloses in lactation maternal diet.</p> <p>Feed_intake_piglets.csv: A comma separated value file of data used to investigate the relationship between the feed intake of Swiss Large White pigs and decreasing levels of hemicelluloses in lactation maternal diet.</p> <p>Diarrhea_postweaning.csv: A comma separated value file of data used to investigate the relationship between the post-weaning diarrhoea of Swiss Large White pigs and decreasing levels of hemicelluloses in lactation maternal diet.</p> <p>data_description.xlsx: meta data for Sow_performances.csv, Milk_composition.csv, Piglets_performances.csv, Feed_intake_piglets.csv and Diarrhea_postweaning.csv with description of variables.</p> <p> </p>
Sowing storms: how model timestep can control tropical cyclone frequency in a GCM
<p>Supplementary dataset to JAMES article "Sowing storms: how model timestep can control tropical cyclone frequency in a GCM" DOI:10.1029/2021MS002791</p>
Genotypes for Iberian sows
<p>This file contains SNP genotype information for 435 sows of Iberian pigs. This is one inpute file of software developed for implementation of the Corner Algorithm</p> <p><a href="https://github.com/lgomezraya/CORNER">https://github.com/lgomezraya/CORNER</a></p>
Figure 3 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat
Figure 3. Relationships between yield components and Vulpia myuros density at two sowing times and crop densities in the growing seasons of 2017–2018 (A and C) and 2018– 2019 (B and D). Number of crop ears per square meter (A and B) and 1,000-kernel weight (C and D) data are shown with fitted curves. Data from the growing seasons of 2017–2018 and 2018–2019 were fit to the linear regression (Equation 2) and asymptotic nonlinear regression (Equation 3) models, respectively.
Figure 4 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat
Figure 4. Relationships between the per-plant seed production and Vulpia myuros density at two crop densities solely at normal sowing time in the growing season of 2017–2018 (A) and at two sowing times and crop densities in 2018–2019 (B). Data from the growing seasons of 2017–2018 and 2018–2019 were fit to the linear regression (Equation 2) and asymptotic nonlinear regression (Equation 3) models, respectively.
Figure 2 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat
Figure 2. Relationships between crop grain yield (kg ha−1) and Vulpia myuros density at two sowing times and crop densities in winter wheat in the growing seasons of 2017–2018 (A) and 2018–2019 (B). Data were fit to the rectangular hyperbola model (Equation 1).
Figure 1 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat
Figure 1. Cumulative emergence dynamics of Vulpia myuros at normal sowing time and late sowing time in relation to thermal time (C) in 2017–2018 (A) and 2018–2019 (B). Regression equation and parameter estimates described in Table 2.
Fig. 3 in The Impact Of Sowing Time On Sugar Content And Snow Mould Development In Winter Wheat
Fig. 3. The content of carbohydrates depending Fig. 4. The average content of residual carbohyon the sowing time. drates in comparison with the carbohydratecon- tent in autumn (2005-2007).
Model inputs and outputs for: Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
<p>Files used in initial submission of manuscript to <em>Geoscientific Model Development</em>. Files with names beginning sdates and gdds were used as model inputs for some experiments. File with name beginning hdates was used in postprocessing. ZIP archives are model experimental outputs.</p>
Reforestation of high elevation pines: Direct seeding success depends on seed source and sowing environment
<p>Forest persistence in regions impacted by increasing water and temperature stress will depend upon species' ability to either rapidly adjust to novel conditions or migrate to track ecological niches. Predicted, rapid climate change is likely to outpace the adaptive and migratory capacity of long-lived isolated tree species, and reforestation may be critical to species' persistence. Facilitating persistence both within and beyond a species' range requires identification of seed lots best adapted to the current and future conditions predicted with rapid climate change. We evaluate variation in emergent seedling performance that leads to differential survival among species and populations for three high-elevation five-needle pines. We paired a fully reciprocal field common garden experiment with a greenhouse common garden study to a) quantify variation in seedling emergence and functional traits, b) ask how functional traits affect performance under different establishment conditions, and c) evaluate whether trait and performance variation demonstrates local adaptation and plasticity. Among study species – limber, Great Basin bristlecone, and whitebark pines – we found divergence in emergence and functional traits, though soil moisture was the strongest driver of seedling emergence and abundance across all species. Generalist limber pine had a clear emergence advantage as well as traits associated with drought adaptation, while edaphic specialist bristlecone pine was characterized by low emergence yet high early survival once established. Despite evidence for edaphic specialization, soil characteristics alone did not explain bristlecone success. Across species, trait-environment relationships provided some evidence for local adaptation in drought-adapted traits, but we found no evidence of local adaptation in emergence or survival at this early life stage. For managers looking to promote persistence, sourcing seed from drier environments is likely to impart greater drought resistance into reforestation efforts through strategies such as greater root investment, increasing the probability of early seedling survival. This research demonstrates, through a rigorous reciprocal transplant experimental design, that it may be possible to select climate- and soil-appropriate seed sources for reforestation. However, planting success will ultimately rely on a suitable establishment environment, requiring careful consideration of interannual climate variability for management interventions in these climate- and disturbance-impacted tree species.</p>
Fast-food consumption by adolescent girls may sow the seeds of breast cancer decades later
<p>An hypothesis of breast cancer development:</p> <p>•Breast development occurs largely during the years of puberty in adolescent girls</p> <p>•Environmental assaults during that vulnerable time window can seed changes that take decades to complete</p> <p>•Advanced glycation end-products (AGE) are found in high concentrations in processed foods, especially fast-food</p> <p>•In mice, AGE produce pubertal breast changes in both epithelium and stroma, including atypical hyperplasia</p> <p>•The stromal changes in humans may be manifest as increased breast density as measured by mammography</p> <p>•These data provide a link between processed, fast-food, high breast density, and future breast cancer</p> <p>•Breast cancer prevention may include the avoidance of fast-food, especially in adolescent girls undergoing pubertal breast development</p>
Reforestation of high elevation pines: Direct seeding success depends on seed source and sowing environment
Open the record for dataset details and reuse information.
Microbiota of sows and their offspring
<p>Microbiota composition was determined of sow feces, sow vaginal swabs and piglet jejunal digesta. Samples were frozen on dry-ice and stored at -80°C. To isolate DNA, samples were mixed in a 1:1 ratio with phosphate buffered saline (PBS) and centrifuged for 5 min at 4°C at 300<em>xg</em>. Supernatant was collected and centrifuged for 10 min at 4°C at 9000<em>xg</em>. DNA was extracted from the pellet using the “QIAamp DNA stool minikit” (Qiagen, Valencia, CA, USA) according to manufacturers’ instructions, after mechanical shearing of the bacteria in Lysing Matrix B tubes using the FastPrep-24 (MP Biomedicals, Solon, OH, USA). Quality and quantity of DNA were checked using the NANOdrop (Agilent Technologies, Santa Clara, CA, USA). PCR was used to amplify (20 cycles) the 16S rRNA gene V3 fragment using forward primer V3_F (CCTACGGGAGGCAGCAG) and reverse primer V3_R (ATTACCGCGGCTGCTGG). PCR efficiency was checked on agarose gel. Amplicons were sequenced using paired-end, excluding one sample that did not pass the quality control, 150bp technology on a MiSeq sequencer (Illumina, San Diego, CA, USA) at a sequencing depth in the range of 196K-1.2M read-pairs per sample (median 670,647 read-pairs per sample).</p> <p> </p>
Effects of high dietary zinc supplementation timing on the biological responses of gestating sows and their piglets
<p class="MsoNormal">High dietary zinc (Zn) fed to gestating sows may have utility as a fetal imprinting strategy to decrease pre-weaning mortality of piglets. However, the biological action that Zn may work through is unknown. High Zn may modulate the microbiome of the sow and the microbial seeding of the offspring's gut microbiome. Additonally, high dietary Zn and piglet birth weight may alter gene expression in piglet whole blood. Sows (n = 267) were fed 1 of 3 dietary treatments: 1) Control: a corn-soybean meal-based diet containing 125 ppm total supplemental zinc, 2) Breed-to-Farrow: as Control + 141 ppm supplemental Zn as ZnSO<sub>4 </sub>fed from 5 days post-breeding to farrowing; and 3) Day 110-to-Farrow: as Control + 2,715 ppm supplemental Zn as ZnSO<sub>4 </sub>starting on day 110 of gestation until farrowing. A subset of third parity sows (n = 30) were selected to assess the microbiome of colostrum, milk, and rectal and vaginal surfaces of sows. At farrowing, 4 pigs per litter (n = 120) were selected based on birthweight (BiW), as 2 average BiW pigs and 2 pigs with BiW below the litter average were selected for assessing the piglet gut microbiome on the day of birth (day 0) and day 5 of age. 16S rRNA sequencing were implemented for milk and colostrum samples while all other sample types were sequenced using shotgun metagenomics to determine taxonomic and functional profiles. On a different subset of pigs, whole blood was collected from 9 LBW pigs per treatment and 8 ABW Control pigs for RNA-sequencing to evaluate differentially expressed genes (DEGs) and pathways. Only 2 to 3 genes were differentially expressed between Control LBW and LBW pigs born to sows fed high Zn. However, 262 DEGs were identified when comparing LBW and ABW pigs, mostly reflecting pathways associated with translation, ribosome biogenesis, and amino acid and protein synthesis. Measures of alpha diversity (richness and Shannon's H Index) and beta diversity (Bray-Curtis, PERMANOVA) were conducted along with indicator species analyses. Species with an indicator value of > 0.50 were confirmed with a generalized linear mixed model as each <em>P</em>-value was corrected for false discovery rate (FDR) to generate a Q-value. For piglet samples, the MaAsLin2 R package was used to determine multivariate associations between dietary treatment and piglet BiW. High dietary concentrations of Zn fed to gestating sows did not affect the colostrum, milk, or vaginal microbial diversity or populations of sows. Pathogenic bacteria such as <em>Shigella flexneri </em>and <em>Salmonella enterica</em> were less abundant in fecal samples from Breed-to-Farrow sows compared to Control sows. For piglets born to Breed-to-Farrow sows, their gut microbiome favored fiber fermenting, short chain fatty acid generating microbial species compared to Control pigs. Day 110-to-Farrow piglets demonstrated a lower abundance of SCFA producing bacteria compared to Control piglets. Gene families and pathways playing roles in central metabolic functions (starch, pyruvate, sucrose, amino acid metabolism) were more abundant in Breed-to-Farrow piglets compared to pigs born to Control sows. In conclusion, high Zn fed to gestating sows may influence SCFA-producing species and may reduce the abundance of potential pathogenic bacteria in the sow and piglet. Piglet birth weight may have greater effects on gene expression of neonatal pigs. </p>
Fig. 2 in The Impact Of Sowing Time On Sugar Content And Snow Mould Development In Winter Wheat
Fig. 2. The content of carbohydrates depending on the year and the sowing time.
Fig. 1 in The Impact Of Sowing Time On Sugar Content And Snow Mould Development In Winter Wheat
Fig. 1. The average temperature of ten-day periods during overwintering.
A fifteen-tile tomographic micro-CT dataset of a panel painting "Cadmus sowing dragon's teeth" 2/3
<p><strong>Summary</strong><br> This submission contains a fifteen-tile tomographic dataset of a panel painting and 15 postprocessed images used for dendrochronological measurements (see related datasets).The data is made available as part of [Domínguez-Delmás et al., 2021].</p> <p><strong>Apparatus</strong><br> The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].<br> <br> <strong>Sample Information</strong><br> The sample is panel painting Cadmus Sowing dragon's teeth. H 26.2cm x w 42.3cm [Rijksmuseum inventory number SK-A-4051, https://www.rijksmuseum.nl/en/collection/SK-A-4051]. It was mounted on a foam base on the rotation stage, see [Domínguez-Delmás et al., 2021] for images.</p> <p><br> <strong>Experimental Plan</strong><br> The data in this submission was collected to facilitate measurements of the tree rings (dendrochronological research) in a cross-section. The panel was mounted in such a way that the desired cross section would be obtained in the vertical direction. A section of a few cm wide along the entire height was imaged slightly off centre of the painting, to avoid metal nails that had showed up in several projections. In total 15 tiled CT scans were collected, moving source and detector vertically by the same distance. Each tile consisted of 1600 projections, each an average of 2 projections with 300ms acquisition time. We used tube settings 70 kV, 70 mA and a 0.1 cm thickness copper filter. Dark-field (closed-shutter), and 2 flat-field (open-shutter) images were taken for each tile after the acquisition with 100 averaged images of 300 ms acquisition time. Reconstructed image resolution was 37 µm.<br> All raw data (i.e. no corrections) is made available in .tif format. Postprocessing steps are described in the supplementary material of [Domínguez-Delmás et al., 2021].<br> <br> <strong>List of Contents</strong><br> The content of the submission is divided in three datasets, with in total 16 subfolders: Images, containing the 15 postprocessed images used for dendrochronological measurements and Tile1-Tile15, each containing the data from one of the tiled scans.<br> Each data folder contains:</p> <ul> <li>dark-field (or closed-shutter) image, di000000.tif,</li> <li>flat-field (or open-shutter) image after acquisition, io000000.tif,</li> <li>raw (unprocessed or uncorrected) projections, scan_*.tif,</li> <li>data settings XRE.txt, a text file with scanner metadata,</li> <li>metadata.toml, a text file with a summary of the scanner metadata</li> </ul> <p><strong>Additional Links</strong><br> These datasets are produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's GitHub page.</p> <p><strong>Contact Details</strong><br> For more information or guidance in using these datasets, please get in touch with</p> <ul> <li>bossema [at] cwi.nl</li> </ul> <p> <br> <strong>Acknowledgments</strong><br> We thank Petria Noble for providing us with the opportunity to scan this interesting object. We thank Erma Hermens , Moorea Hall-Aquitania and Marta Domínguez Delmás for bringing the object and research questions to our attention and inviting our collaboration on this research project.<br> The authors would like to acknowledge the funding from the Netherlands Organisation for Scientific Research (NWO), project numbers 341-60-001, 639.073.506 and 628.007.033 and Netherlands Institute for Conservation, Art and Science (NICAS).</p>
A fifteen-tile tomographic micro-CT dataset of a panel painting "Cadmus sowing dragon's teeth" 1/3
<p><strong>Summary</strong><br> This submission contains a fifteen-tile tomographic dataset of a panel painting and 15 postprocessed images used for dendrochronological measurements (see related datasets).The data is made available as part of [Domínguez-Delmás et al., 2021].</p> <p><strong>Apparatus</strong><br> The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].<br> <br> <strong>Sample Information</strong><br> The sample is panel painting Cadmus Sowing dragon's teeth. H 26.2cm x w 42.3cm [Rijksmuseum inventory number SK-A-4051, https://www.rijksmuseum.nl/en/collection/SK-A-4051]. It was mounted on a foam base on the rotation stage, see [Domínguez-Delmás et al., 2021] for images.</p> <p><br> <strong>Experimental Plan</strong><br> The data in this submission was collected to facilitate measurements of the tree rings (dendrochronological research) in a cross-section. The panel was mounted in such a way that the desired cross section would be obtained in the vertical direction. A section of a few cm wide along the entire height was imaged slightly off centre of the painting, to avoid metal nails that had showed up in several projections. In total 15 tiled CT scans were collected, moving source and detector vertically by the same distance. Each tile consisted of 1600 projections, each an average of 2 projections with 300ms acquisition time. We used tube settings 70 kV, 70 mA and a 0.1 cm thickness copper filter. Dark-field (closed-shutter), and 2 flat-field (open-shutter) images were taken for each tile after the acquisition with 100 averaged images of 300 ms acquisition time. Reconstructed image resolution was 37 µm.<br> All raw data (i.e. no corrections) is made available in .tif format. Postprocessing steps are described in the supplementary material of [Domínguez-Delmás et al., 2021].<br> <br> <strong>List of Contents</strong><br> The content of the submission is divided in three datasets, with in total 16 subfolders: Images, containing the 15 postprocessed images used for dendrochronological measurements and Tile1-Tile15, each containing the data from one of the tiled scans.<br> Each data folder contains:</p> <ul> <li>dark-field (or closed-shutter) image, di000000.tif,</li> <li>flat-field (or open-shutter) image after acquisition, io000000.tif,</li> <li>raw (unprocessed or uncorrected) projections, scan_*.tif,</li> <li>data settings XRE.txt, a text file with scanner metadata,</li> <li>metadata.toml, a text file with a summary of the scanner metadata</li> </ul> <p><strong>Additional Links</strong><br> These datasets are produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's GitHub page.</p> <p><strong>Contact Details</strong><br> For more information or guidance in using these datasets, please get in touch with</p> <ul> <li>bossema [at] cwi.nl</li> </ul> <p> <br> <strong>Acknowledgments</strong><br> We thank Petria Noble for providing us with the opportunity to scan this interesting object. We thank Erma Hermens , Moorea Hall-Aquitania and Marta Domínguez Delmás for bringing the object and research questions to our attention and inviting our collaboration on this research project.<br> The authors would like to acknowledge the funding from the Netherlands Organisation for Scientific Research (NWO), project numbers 341-60-001, 639.073.506 and 628.007.033 and Netherlands Institute for Conservation, Art and Science (NICAS).</p>
A fifteen-tile tomographic micro-CT dataset of a panel painting "Cadmus sowing dragon's teeth" 3/3
<p><strong>Summary</strong><br> This submission contains a fifteen-tile tomographic dataset of a panel painting and 15 postprocessed images used for dendrochronological measurements (see related datasets).The data is made available as part of [Domínguez-Delmás et al., 2021].</p> <p><strong>Apparatus</strong><br> The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].<br> <br> <strong>Sample Information</strong><br> The sample is panel painting Cadmus Sowing dragon's teeth. H 26.2cm x w 42.3cm [Rijksmuseum inventory number SK-A-4051, https://www.rijksmuseum.nl/en/collection/SK-A-4051]. It was mounted on a foam base on the rotation stage, see [Domínguez-Delmás et al., 2021] for images.</p> <p><br> <strong>Experimental Plan</strong><br> The data in this submission was collected to facilitate measurements of the tree rings (dendrochronological research) in a cross-section. The panel was mounted in such a way that the desired cross section would be obtained in the vertical direction. A section of a few cm wide along the entire height was imaged slightly off centre of the painting, to avoid metal nails that had showed up in several projections. In total 15 tiled CT scans were collected, moving source and detector vertically by the same distance. Each tile consisted of 1600 projections, each an average of 2 projections with 300ms acquisition time. We used tube settings 70 kV, 70 mA and a 0.1 cm thickness copper filter. Dark-field (closed-shutter), and 2 flat-field (open-shutter) images were taken for each tile after the acquisition with 100 averaged images of 300 ms acquisition time. Reconstructed image resolution was 37 µm.<br> All raw data (i.e. no corrections) is made available in .tif format. Postprocessing steps are described in the supplementary material of [Domínguez-Delmás et al., 2021].<br> <br> <strong>List of Contents</strong><br> The content of the submission is divided in three datasets, with in total 16 subfolders: Images, containing the 15 postprocessed images used for dendrochronological measurements and Tile1-Tile15, each containing the data from one of the tiled scans.<br> Each data folder contains:</p> <ul> <li>dark-field (or closed-shutter) image, di000000.tif,</li> <li>flat-field (or open-shutter) image after acquisition, io000000.tif,</li> <li>raw (unprocessed or uncorrected) projections, scan_*.tif,</li> <li>data settings XRE.txt, a text file with scanner metadata,</li> <li>metadata.toml, a text file with a summary of the scanner metadata</li> </ul> <p><strong>Additional Links</strong><br> These datasets are produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's GitHub page.</p> <p><strong>Contact Details</strong><br> For more information or guidance in using these datasets, please get in touch with</p> <ul> <li>bossema [at] cwi.nl</li> </ul> <p> <br> <strong>Acknowledgments</strong><br> We thank Petria Noble for providing us with the opportunity to scan this interesting object. We thank Erma Hermens , Moorea Hall-Aquitania and Marta Domínguez Delmás for bringing the object and research questions to our attention and inviting our collaboration on this research project.<br> The authors would like to acknowledge the funding from the Netherlands Organisation for Scientific Research (NWO), project numbers 341-60-001, 639.073.506 and 628.007.033 and Netherlands Institute for Conservation, Art and Science (NICAS).</p>
Data - Sow what you sell: strategies for integrating organic breeding and seed production into value chain partnerships
<p>Online survey targeting organic farmers on organic seed use; 25 questions in the survey. The survey was conducted between November 2018 and June 2019 and distributed through the networks of partners involved in the Horizon2020 project LIVESEED, including 23 breeding & research institutes, seven breeding companies, eight seed companies, and 11 organic associations. 752 complete entries by farmers from 20 countries from Central, Northern, Southern and Eastern Europe could be used from the 1,475 total accesses to the survey.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.