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28 results for “laying hens”
Dataset: Green light during incubation: effects on hatching characteristics in brown and white laying hens
<p>Dataset used for the paper "Green light during incubation: effects on hatching characteristics in brown and white laying hens".<br> <br> Abstract:</p> <p>Providing light during incubation is being investigated as a method to improve welfare in later life in poultry. This incubation method would more closely approximate chicken natural environment compared to the current incubation in darkness. Previous studies showed promising results of light during incubation on broiler welfare, but little is known about effects of light during incubation on laying hens. Especially, information about its effects on hatching characteristics (hatch time, hatchability, chick quality, body weight and embryonic age of death) is scarce and requires investigation in both white and brown egg layers. In the current study, Dekalb White (DW) and ISA Brown (ISA) eggs were incubated in complete darkness (dark) or in a light:dark cycle of 12L:12D throughout incubation (light), resulting in four treatment groups: DW-dark, DW-light, ISA-dark, and ISA-light. In the light treatments, green LEDs of 520nm wavelength were used, at an intensity of 400 lux. First, light transmission through the eggshell was measured through 27 eggs. Then, an analysis of the effects of light during incubation on hatching characteristics was performed on 711 chicks in two consecutive experimental rounds. Light transmission was higher through white eggshells than through brown eggshells (N = 27, p < 0.001). Light during incubation had no effects on hatching characteristics (N = 711, p ≥ 0.1). Despite the difference of light transmission through eggshell between hybrids, there was no interaction between incubation treatment and hybrid on hatching characteristics (N = 471, p ≥ 0.06). Hatch time was longer and navel quality was better in DW than in ISA, while body weight and embryonic age of death were lower in DW than in ISA (all p < 0.001). Males and females had similar chick quality scores except for the beak quality, which was better for males (N = 486, p = 0.003). To conclude, green light during incubation did not negatively affect hatching characteristics in either DW nor ISA laying hen hybrids. Future research should therefore focus on its potential benefits for laying hen welfare.</p>
Dataset used for upcoming paper: The effects of mild disturbances on sleep behaviour in laying hens
<p>2 Excel .csv files for statistical analysis using R-Studio. The first is a constants file for temporal coding, the second is the raw data.</p>
[Dataset] Pattern and repeatability of ascarid-specific antigen excretion through chicken faeces, and the diagnostic accuracy of copro-antigen measurements as compared with McMaster egg counts and plasma and egg yolk antibody measurements in laying hens
<p>Comprehensive data examining the pattern and repeatability of ascarid-specific antigen excretion in chicken faeces and the diagnostic accuracy of copro-antigen measurements compared to McMaster egg counts and antibody measurements in laying hens.</p> <p>The dataset consists of observations and measurements obtained from a controlled study involving laying hens infected with mixed <em>Ascaridia galli</em> and<em> Heterakis gallinarum</em>. A total of 179 individual hens were monitored between wpi 2 and 18 and their fecal samples/blood samples were collected at specific time points. Faecel samples were repeatedly collected four(4) consecutive times in one wpi.Hence antigen measurements is 4 X 179 = 716 measurements</p>
Dataset used for upcoming paper: The effects of commercially-relevant disturbances on sleep behaviour in laying hens
<p>2 Excel .csv files for statistical analysis using R-Studio. The first is a constants file for temporal coding, the second is the raw data.</p>
Dataset used for upcoming paper: The effects of commercially-relevant disturbances on sleep behaviour in laying hens
<p>2 Excel .csv files for statistical analysis using R-Studio. The first is a constants file for temporal coding, the second is the raw data.</p>
Vocalization Patterns in Laying Hens - An Analysis of Stress-Induced Audio Responses
<p>This repository houses a comprehensive collection of data and resources from the study "Vocalization Patterns in Laying Hens - An Analysis of Stress-Induced Audio Responses." Led by Dr. Suresh Neethirajan at Mooanalytica, Department of Agriculture & Aquaculture, Faculty of Agriculture & Computer Science, Dalhousie University, this research represents a significant foray into the field of poultry ethology and welfare monitoring using advanced machine learning techniques.</p> <p><strong>Key Components of the Repository</strong></p> <ol> <li> <p><strong>Experimental Audio Data</strong></p> <ul> <li><strong>Control and Treatment Vocalizations</strong>: Audio recordings of laying hens under two different stress conditions – sudden umbrella opening (Treatment 1) and simulated dog barking sounds (Treatment 2), along with control groups. The processed dataset is approximately 460 MB for the control group experimental data and about 2 GB for the 2 treatment group experimental data, capturing the nuanced responses of hens to these stressors.</li> <li><strong>Original Raw Data</strong>: The original, unprocessed audio data is around 9 GB in size. Though not included in the repository, it can be made available upon reasonable request.</li> </ul> </li> <li> <p><strong>Algorithm and Code Files</strong></p> <ul> <li><strong>CNN Feature Extraction and Classification Algorithms</strong> Python scripts used for the extraction of features from the audio data using Convolutional Neural Networks (CNN) and subsequent classification.</li> <li><strong>Supplementary Algorithms</strong> Additional code files that support the processing and analysis of the audio data.</li> </ul> </li> <li> <p><strong>MFCC Feature Dataset</strong></p> <ul> <li>An Excel file containing the 40 Mel Frequency Cepstral Coefficients (MFCC) features extracted from the vocalization data. This dataset provides a detailed spectral analysis of the hen's vocalizations, crucial for understanding their response to stress.</li> </ul> </li> </ol> <p><strong>Study Overview</strong></p> <p>This study aimed to classify and analyze the vocalization patterns of laying hens subjected to different stressors. Using a CNN model, the research identified distinct vocal patterns between control and treated groups, indicating unique vocal responses to different types of stressors. This study is pivotal in understanding the impact of environmental stressors on poultry welfare and behavior. The age of the chickens and the timing of stressor application were also critical factors influencing vocalization patterns.</p> <p><strong>Implications and Applications:</strong></p> <p>The findings from this study have significant implications for poultry welfare monitoring and management. By providing a non-invasive method to assess the well-being of chickens, this research contributes valuable insights into enhancing poultry management practices and welfare standards.</p> <p>The resources in this repository are intended for researchers, academicians, and professionals in animal behavior, veterinary science, and poultry management. We encourage the use of these data and tools for further research and practical applications in the field of precision (Digital) livestock farming and animal welfare.</p> <p>For any queries or requests related to the raw dataset, please contact Dr. Suresh Neethirajan.</p>
Perch positioning affects laying hen locomotion and forces experienced at the keel - FULL DATA SET
<p>Full data set for publication in Animals</p> <p><strong>Perch positioning affects laying hen locomotion and forces experienced at the keel</strong></p> <p><em>Christina Rufener, Ana K. Rentsch, Ariane Stratmann, Michael J. Toscano</em></p>
Beak lengths of young laying hens (pullets) from flocks provided with potential beak-blunting materials and from control flocks
<p class="MsoNormal">Injurious Pecking, commonly controlled by beak trimming (BT) is a widespread issue in laying hens associated with thwarted foraging. This controlled study compared the effect in intact and beak-trimmed pullets of providing pecking pans to 8 treatment flocks from 6 weeks of age. Flocks (mean size 6,843) comprised 8 British Blacktail, 6 Lohmann Brown and 2 Bovans Brown. All young birds (6-7 weeks) pecked more frequently at the pecking pans (mean 40.4) than older pullets (mean 26.0, 23.3 pecks/bird/minute at 10-11 weeks and 14-15 weeks respectively) (p<0.005). There was no effect on feather pecking or plumage cover. Mean side-beak length and mean top-beak lengths were shorter in treatment flocks at 6-7 weeks and 10-11 weeks (p <0.001). Intact-beak treatment flocks had shorter mean side-beak length at 10-11 weeks (p < 0.001) and at 14-15 weeks (p<0.05) and mean top-beak length at 6-7 weeks (p < 0.05) and at 10-11 weeks (p < 0.05). BT treatment flocks had shorter side-beak and top-beak lengths at 6-7 weeks and at 10-11 weeks (p<0.001). Beak lengths showed linear growth, with individual bird variation indicating a potential for genetic selection. The study demonstrated that abrasive material can reduce beak length in pullets.</p>
Whole-body X-ray images of laying hens with keel bone annotations and masks for training deep learning models
<p>This dataset contains whole-body x-ray images of laying hens (n=1051), with the corresponding keel bone annotations and masks. This dataset was basically used to train deep learning models to segment the keel bone from the whole-body x-ray images. But can be used by others for further developments of similar models. This dataset was generated during the research project funded by Svenska Forskningsrådet Formas (2019-02116). The project aimed to develop a digital tool to assess bones of laying hens using x-ray imaging. All images are in JPEG format. All images are named with informative codes indicating bird ID, date and time of x-raying. For instance, in this "001_20230419_0957_PM.Dicom.jpg" image name, "001" stands for the bird ID, "20230419" for the x-raying date, "0957" for the x-raying time, and "PM.Dicom.jpg" indicates that the bird was x-rayed postmortem "PM" with "Dicom" file output and converted to the ".jpg" format. </p> <p>Update on 28/08/2024: This dataset is linked to publication</p> <p>Sallam et al. (2024) Research Note: A deep learning method segments chicken keel bones from whole-body X-ray images,<br>Poultry Science, Volume 103, Issue 11, 2024, 104214, ISSN 0032-5791,<br>https://doi.org/10.1016/j.psj.2024.104214</p>
Varying digestible isoleucine level to determine effects on performance, egg quality, serum biochemistry, and ileal protein digestibility in diets of young laying hens
<p class="CxSpFirst">To ascertain an appropriate level of isoleucine for LSL-LITE layers (23- to 30-week-old), diets containing total isoleucine concentrations (levels) of 0.66 (Control), 0.69, 0.72, 0.75, 0.78, 0.81, and 0.84% were fed as 7 treatments (2730 kcal/kg metabolizable energy) x 7 replicates x 10 birds per replicate. Significance for performance, egg quality, serum bioc Level, week, and level*week (L*W) were significant for production, egg mass, and feed intake. Level and week were significant for FCR. Week was significant for weight gain.</p> <p>Level was significant for egg weight, specific gravity, and shell thickness; week was also significant for these external egg parameters as well as shape index and proportional shell thickness. L*W was significant for all except shape index. For internal egg measurements, level was significant for proportional yolk, proportional albumen, yolk index, and yolk:albumen. Week was significant for internal egg parameters while L*W significantly affected Haugh unit, proportional albumen weight, yolk index, albumen index, and yolk color. Level was significant for <span class="Heading1Char"><span>globulin and glucose in serum. </span></span></p> <p><span class="Heading1Char"><span>Is</span></span>oluecine at 0.72%, 0.81% and 0.84% produced the lowest FCR, an important standard in the poultry industry. Considering the low FCR of 1.45 and cost for inclusion as a dietary ingredients, 0.72% isoleucine was chosen for further study.</p>
Beak lengths of young laying hens (pullets) from flocks provided with potential beak-blunting materials and from control flocks
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Data from: Implications for welfare, productivity and sustainability of the variation in reported levels of mortality for laying hen flocks kept in different housing systems: a meta-analysis of ten studies.
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Varying digestible isoleucine level to determine effects on performance, egg quality, serum biochemistry, and ileal protein digestibility in diets of young laying hens
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Data from: Space use by 4 strains of laying hens to perch, wing flap, dust bathe, stand and lie down
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Transcriptome profile of liver at different physiological stages in laying hens
GEO Series GSE70010. Gallus gallus. 6 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic Data Reveals MYC as an Upstream Transcriptional Regulator in Laying Hen Pre-ovulatory Follicles using Ingenuity Pathway Analysis
GEO Series GSE228994. Gallus gallus. 12 samples. Type: Expression profiling by high throughput sequencing.
Gene expression data of two different strains of laying hens from a small group housing system
GEO Series GSE55570. Gallus gallus. 60 samples. Type: Expression profiling by array.
Transcriptome sequencing reveals key potential long non-coding RNAs related to duration of fertility trait in the uterovaginal junction of egg-laying hens
GEO Series GSE101163. Gallus gallus. 14 samples. Type: Non-coding RNA profiling by high throughput sequencing.
miRNA expression profiling in liver of juvenile and egg-laying hens
GEO Series GSE74242. Gallus gallus. 6 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Transciptomic profiling of the magnum of laying and non-laying hens using RNA-seq
GEO Series GSE123588. Gallus gallus. 6 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.