AndreaBozzo/ceres-open-data-index huggingface dataset:
Data from: Susceptibility of pESI positive <i>Salmonella</i> to treatment with biocide chemicals approved for use in poultry processing as compared to <i>Salmonella</i> without the pESI plasmid

<p dir="ltr">This repository contains all data and code required to reproduce the cumulative logistic mixed-effects model for the manuscript: </p><p dir="ltr">"Susceptibility of pESI positive <i>Salmonella</i> to treatment with biocide chemicals approved for use in poultry processing as compared to <i>Salmonella</i> without the pESI plasmid": citation to be added upon publication.</p><p dir="ltr">Abstract: <i>Salmonella</i> is a common cause of human foodborne illness which is frequently associated with consumption of contaminated or undercooked poultry meat. Serotype Infantis is among the most common serotypes isolated from poultry products. Isolates of serotype Infantis carrying the pESI plasmid have been shown to exhibit oxidizer tolerance. Therefore, sixteen strains of <i>Salmonella</i> with and without pESI carriage were investigated for susceptibility to biocide chemical processing aids approved for use in U.S. poultry processing. All strains tested were susceptible to all concentrations of peracetic acid, cetylpiridinium chloride, and sodium hypochlorite when applied for 90 minutes. When cetylpiridinium chloride, calcium hypochlorite, and sodium hypochlorite were applied for 15 seconds to simulate spray time, strains responded similarly to each other. However, strains responded variably to exposure to PAA. The variation was not statistically significant and appears unrelated to pESI carriage. Results highlight the necessity of testing biocide susceptibility in the presence of organic material and in relevant <i>in situ</i> applications.</p><p dir="ltr"><br></p>

Tags: ars, biocide, infantis, pesi-and-pesi-like-plasmids, salmonella
Organization: Department of Agriculture
Images and bounding box annotations of sound and rotten cranberry fruit from a postharvest imaging platform

<p dir="ltr">This data set provides the raw images and bounding box annotations from a postharvest berry imaging platform that was used to train an object detection model. Annotations are of fruit belonging to two classes: sound and rotten. Downstream image processing of detected and classified berries measures the percent fruit rot in a sample. Images were collected using a Nikon D7500 DSLR camera using manual shutter speed, focal length, f-stop, and ISO settings. The imaging platform was a custom-build LED lightbox and sample tray. The dataset contains 60 images with accompanying annotations in YOLOv8 format.</p>

Tags: breeding, cranberry, deep-learning, fruit-rot, imaging, lightbox, phenotyping, training-data
Organization: Department of Agriculture
Data from: Systematic Color Correction Pipeline for Controlled-Environment Imaging

<p dir="ltr">Raw data set to evaluate a stepwise color correction (CC) pipeline for controlled imaging environments. The workflow integrates flat-field correction (FFC), gamma correction (GC), and white-balance correction (WB), followed by a color-mapping (CM) stage using machine-learning regression—linear, partial least squares (PLS), and neural networks (NN)—to deliver reliable CC in digital images. The pipeline reduces perceptual color differences in the corrected images. An NN with a second-degree polynomial expansion consistently outperformed other CM methods, yielding the lowest color errors and robust performance across varying imaging conditions.</p><p dir="ltr">Tests showed that illumination quality and placement are critical: although the common 45° geometry produces favorable uncorrected images, top-mounted area lighting combined with FFC yielded the best corrected color. Imaging-environment materials also mattered; object background color and sidewalls affected fidelity, with diffusely reflective white performing best. Applied to various colored fruit samples, the proposed pipeline produced more consistent fruit colors across illuminants. An open-source Python package (https://github.com/collinswakholi/ColorCorrectionPackage) and an interactive user interface (https://github.com/collinswakholi/ColorCorrectionPackage_UI) implementing this pipeline is available, enabling reproducible analyses and straightforward adaptation to other controlled imaging tasks. Overall, the pipeline improved color reproduction and measurement in digital images and helped bridge the gap between sophisticated CC methods and practical, routine applications.</p>

Tags: color-correction-methods, digital-imaging-systems, flat-field-correction, gamma-correction, machine-learning, neural-networks, white-balance
Organization: Department of Agriculture
Data from: Near-infrared spectroscopy for the single-kernel analysis of sorghum protein content

<p dir="ltr">Protein content is a vital quality trait in sorghum that influences breeding approaches, end-use applications, and market value. Influenced by genetic, agronomic, and environmental variability, sorghum is characterized by its wide variation in composition, which may also be evident in kernels from the same sample. This study developed and evaluated a method for a non-destructive and rapid prediction of protein content in individual sorghum kernels using single-kernel near-infrared spectroscopy (SKNIR). Applying different pre-processing techniques to the spectra collected from intact kernels, the calibration models were developed using partial least squares regression and the reference protein content values obtained from the LECO combustion method. The best model was obtained using multiplicative scatter correction as pre-processing, resulting in a standard error of prediction of 0.83% and a relative predictive determinant of 3.40. These were indicative of the good predictive ability of the model and the instrument to be applied in quality control and sorting applications. These results highlight the potential of SKNIR to capture the interkernel variability in sorghum protein content and enhance screening for grain quality in breeding and grain processing.</p><p dir="ltr">Data contains raw spectra (940-1640 nm) for each sample used in the study and regression coefficients for each wavelength.   </p>

Tags: chemometrics, near-infrared-spectroscopy, protein-content, sorghum
Organization: Department of Agriculture
Hangry bees: Pollen dearth impacts honey bee (<i>Apis mellifera</i>) behavior and physiology

<p dir="ltr">Nutritional deprivation is known to contribute to increased honey bee mortality, physiological stress, aberrant behaviors, and disease incidence. To investigate the effect of a realistic nutritional protein deficiency, we simulated a pollen dearth in half of our experimental colonies by robbing incoming foragers of their pollen loads, the primary source of dietary protein, at the colony entrance. We then conducted temperament assays on each colony weekly for pollen deprived and control counterparts. We also identified the plant species bees foraged from and took various physiological measures of honey bee nutritional status including gland size, lipid quantification, and gene expression to further investigate and explain our behavioral results. We found that colonies deprived of pollen reacted by becoming more defensive and that immature bees likely receive cues during rearing which prime their gene expression and behavior as adults, ultimately suggesting that environmental stress caused significant behavioral changes. Temperament is primarily associated with genotype, but there are environmental cues which are less acknowledged and still important. As droughts become increasingly frequent and resource availability therefore changes over time, the impacts on behaviors of agricultural keystone species need additional consideration in order to form scientifically driven best management practices.</p>

Tags: colony-defense, honey-bee, source-code
Organization: Department of Agriculture
Data from: Chicken microRNA 26a-5p regulates replication of Orthoavulavirus javaense by direct targeting of the viral polymerase

<p dir="ltr">Newcastle disease (ND), caused by <i>Orthoavulavirus javaense </i>(OAVJ), is a significant threat to the poultry industry and outbreaks of virulent strains can lead to substantial economic losses. Studies to identify molecular pathways that can be used for intervention or to reduce pathology are critical for mitigating losses due to ND. In this study, we showed that chicken miR-26a-5p can inhibit the replication of both the lentogenic and velogenic pathotypes of OAVJ by acting via two distinct mechanisms, namely, by regulation of the host interferon response and by direct targeting of the viral polymerase gene. Mir-26a-5p upregulation inhibited the replication of both lentogenic and velogenic OAVJ strains. Stable overexpression of miR-26a-5p led to the down-regulation of multiple genes in the innate immune sensing pathway and led to a small but significant increase in viral titer for a velogenic OAVJ strain suggesting a pro-viral role. However, this study also identified a site for the direct binding of mir-26a-5p to the OAVJ polymerase gene which is highly conserved across the majority of class II strains. Furthermore, transfection of the miR-26a-5p mimic following viral infection demonstrated a direct inhibition of polymerase transcripts while inhibitor transfection led to partial rescue of the miR-26a-5p mediated repression. These data identified new roles for chicken miR-26a-5p in regulating OAVJ replication.</p>

Tags: interferon-stimulated-genes, interferons, micrornas, newcastle-disease-virus-ndv
Organization: Department of Agriculture
Data from: A trisiloxane surfactant interacts with ovarian gene expression in honey bee queens and elevates Deformed Wing Virus prevalence in queen ovaries

<p dir="ltr">A honey bee queen ability to produce eggs is critical to the function of a colony, yet little is known regarding the effects of stress on oviposition or the physiological processes underpinning those effects. Previous work has shown that exposure to field relevant doses of commonly used trisiloxane surfactant found in agricultural adjuvants reduced the oviposition rates of queens in a laboratory setting. Here, the work is expanded to include transcriptomic analysis of queen ovaries exposed to one of the trisiloxane surfactant targets. Our transcriptomic analysis identified a positive correlation between trisiloxane surfactant-exposure and increased abundance of Deformed Wing Virus in the ovaries of queens, also we highlight complex but significant effects between oviposition and reproductive gene expression patterns. Specifically, we note intriguing patterns involving expression of heat shock protein (HSP90) and a cytochrome P450 4C1 gene both tied to key physiological processes related to organismal stress response.</p>

Tags: honey-bee-castes, reproductive-activity-pattern, source-code, surfactant-added
Organization: Department of Agriculture
Data from: Stability of Hop Yield and Quality Factors in Response to Delivery of Irrigation and Harvest Timing

<p dir="ltr">This dataset supports field trials into the effects of irrigation configuration and harvest timing on yield, cone chemistry, and disease incidence in hop (Humulus lupulus L.) production systems. The dataset contains 113 observations collected across four growing seasons (2020–2023) from a replicated field experiment evaluating two irrigation configurations (1 vs. 2 drip tubes per row) and two harvest timings (EARLY and LATE). The experimental design followed a blocked structure with up to seven field blocks per year, enabling assessment of treatment effects across spatial replications and seasons. Each observation corresponds to a plot-level measurement and includes agronomic, pathological, and phytochemical variables. Agronomic metrics include fresh yield (kg/plant), dry yield (kg/plant), dry matter (%), cone color (1–10 scale), and hop storage index (HSI). Brewing-relevant quality parameters include alpha acids (%), beta acids (%), and total oil content (mL/100 g). Plant health variables include incidence or severity ratings for hop-associated pathogens and viroids (Hop stunt viroid (HSVd), Apple mosaic virus (ApMV), American hop latent virus (AHLV), Hop latent viroid (HLV), and Hop mosaic virus (HMV)), recorded as plot-level measures. These data enable examination of potential interactions between irrigation regime, harvest timing, and pathogen pressure. A major component of the dataset consists of detailed volatile and terpene profiles (mg/kg), quantified for individual compounds commonly associated with hop aroma and brewing quality. Measured compounds include monoterpenes (e.g., α-pinene, β-pinene, myrcene, limonene), oxygenated monoterpenes (e.g., linalool, geraniol, nerol, terpinen-4-ol), esters (e.g., methyl geranate, geranyl acetate, geranyl isobutyrate), and sesquiterpenes and their oxides (e.g., α-humulene, β-caryophyllene, caryophyllene oxide, humulene epoxides I and II).</p>

Tags: cone-yield, humulus-lupulus-l, irrigation-configuration, virus-incidence
Organization: Department of Agriculture
Data from: Bee communities and patterns in flower visitation in crested wheatgrass seedings in eastern Oregon sagebrush steppe

<p dir="ltr">We collected data on bee communities with two methods (pan traps and netting) across paired plots in and outside historic seedings of the non-native perennial grass, crested wheatgrass, in eastern Oregon sagebrush steppe. Included here are two datasets in spreadsheet form associated with this study:</p><p dir="ltr">BeeOccurrence: This dataset describes all of bees collected for this study. Most are identified to species. Each individual bee is associated with a collection location, the date and time, and the bee sampling method (pan traps versus netting). For netting samples, we included the plant species the bee was collected on. All bees are vouchered at the Utah National Pollinating Insects Collection.</p><p dir="ltr">LifeHistoryTraits; This dataset describes traits by bee species for all bees collected in the study. The dataset includes a metadata sheet, broken down by trait category. The metadata describe and define each trait and lists all publications screened for trait data.</p>

Tags: agropyron-cristatum, non-native-grasses, plant-communities, pollinator-networks, richness
Organization: Department of Agriculture
R Code and Output Files for: An Interactive R-Based Custom Quantification Program for Quantitative Analysis of Triacylglycerols in Bovine Milk

<p> This file contains all of the R code, notebooks, and output (web pages and figures) used to analyze the raw data in <a href="https://gcc02.safelinks.protection.outlook.com/?url=https://agdatacommons.nal.usda.gov/articles/dataset/Byrdwell_Bovine_Milk_Dataset_061021/24669096&data=05|02|Michal.McCullough@usda.gov|ca7455a5456f467f0a0508dc6623505c|ed5b36e701ee4ebc867ee03cfa0d4697|1|0|638497549060675941|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0=|0|||&sdata=/xd011Daqca/VGVF42x6mXeLPpzZvBV0bcqhCAimQ88=&reserved=0" target="_blank">https://agdatacommons.nal.usda.gov/articles/dataset/Byrdwell_Bovine_Milk_Dataset_061021/24669096</a> as described in the manuscript "An Interactive R-Based Custom Quantification Program for Quantitative Analysis of Triacylglycerols in Bovine Milk". </p>

Tags: bovine-milk, lipids, r-code, rstudio, triacylglycerols-tags, triglycerides
Organization: Department of Agriculture
Data from: Haplotype-resolved genome assemblies for the New World screwworm, <i>Cochliomyia hominivorax</i> (Diptera: Calliphoridae), using the trio binning approach

<p dir="ltr">These are supplemental data for producing haplotype-resolved genome assemblies of <i>C. hominivorax </i>using the trio-binning approach. Briefly, a single male progeny from the cross of a Panama line male with a production strain female was sequenced using PacBio HiFi and scaffolded using Hi-C chromatin conformation, while Illumina NextSeq 2000 was used for short read sequencing of both parents to facilitate trio-binning. We produced a linear haploid reference assembly by transferring a copy of the X chromosome and mitochondrial genome to the paternal haplotype. This assembly is comprised of five autosomes, two sex chromosomes, the mitogenome, and 75 unplaced scaffolds spanning 455.6 Mb, which is closer to the predicted size based on flow cytometry (443.8 Mb) than the previous assembly of 534.4 Mb. NCBI’s external Eukaryotic Genome Annotation Pipeline (EGAPx) was used to annotate the protein coding and non-coding genes in the linear haploid reference and the maternal haplotype assembly.</p><p dir="ltr">This research used resources provided by the SCINet project and/or the AI Center of Excellence of the USDA Agricultural Research Service, ARS project numbers 0201-88888-003-000D and 0201-88888-002-000D.</p>

Tags: blow-fly, livestock-pest, myiasis, obligate-parasite, screwworm, sterile-insect-technique
Organization: Department of Agriculture
Data from: Variability in vegetation outcomes in widespread post-fire non-native perennial grass seedings associated with site environment and weather

<p dir="ltr">Crested wheatgrass is widely, and historically, seeded across sagebrush steppe rangelands to increase perennial cover and compete with invasive annual grasses post-fire, however, outcomes vary, likely due to complex combinations of site environmental variables and weather. This study examines variation in vegetation characteristics in post-fire areas associated with crested wheatgrass seeding, and environmental variables, in the northern Great Basin. We selected 142 treatments on Bureau of Land Management lands seeded post-fire with crested wheatgrass over the past two decades in two ecoregions (Snake River Plain, Northern Basin and Range). We selected target 30 m pixels and matched them to 150 reference pixels based on environmental similarity and burn severity within 0.3-3.5 km radius in unseeded areas. We compared change overtime post-seeding in the target pixels to reference pixels with a synthetic control method, comparing pre-fire differences in vegetation between target and reference pixels to post-seeding outcomes. We extracted effect sizes at 5 and 10 years post-fire. We tested for the effects of fire severity, elevation, sand content, and spring precipitation in two time points on seeding effects for each type of cover.</p>

Tags: bare-ground, crested-wheatgrass, invasive-annual-grasses, sagebrush-steppe, shrub, synthetic-control
Organization: Department of Agriculture
Geisinger Rural Aging Study - Metadata document and dataset variables

<p>The <strong>Geisinger Rural Aging Study</strong> (GRAS) was initiated between 1994-99 as a longitudinal study of health outcomes in relation to nutritional status among 21,645 individuals ≥65-years of age. At the time of initiation, the participants were recruited from within the Geisinger Health System service area located in about 25 counties of north central and eastern Pennsylvania. Active participant data collection is complete but passive data collected through the Electronic Health Record continues for those surviving. Prior patient reported data were collected at baseline and at a rescreening visit occurring 3-4 years after baseline, using questionnaires that encompass multiple domains of nutrition risk. Our investigations have found high prevalence of poor-quality diets, obesity, and ill health. Low diet quality as revealed by the Diet Quality Screening Questionnaire (DQSQ) is associated with outcomes measured within our electronic medical record (low body mass index, increased co-morbidity, and increased mortality risk). The GRAS dataset currently spans more than two decades including patient reported data, clinical data captured within an electronic medical record, and includes novel sub-cohorts such as the oldest old (≥85 years) and centenarians (≥100 years).</p>

Tags: aging, diet, electronic-health-record, health, rural-population
Organization: Department of Agriculture
Data from: Beech leaf disease symptom detection using deep learning and computer vision tools

<p dir="ltr">This image dataset consists of symptomatic and non-symptomatic American beech (<i>Fagus grandifolia</i>) leaves collected for the purpose of training a convolutional neural network to distinguish between leaves affected by Beech Leaf Disease (BLD) and those without visible symptoms. Images were captured in Montgomery County and Prince George’s County, Maryland, during May and June of 2025.</p><p dir="ltr">Two types of image acquisition settings were used to ensure variation in lighting, background, and presentation. Leaves were photographed outdoors on trees. Additional leaves were imaged under natural field conditions and in a controlled laboratory environment. The dataset includes images captured using an iPhone 15 and a Nikon D600, representing a range of resolutions and optical characteristics.</p><p dir="ltr">The combined dataset provides diverse examples of symptomatic and non-symptomatic leaves across varying environmental and photographic conditions, supporting robust training and evaluation of machine learning models for BLD detection.</p>

Tags: beech-leaf-disease, computer-vision, litylenchus-crenatae-mccannii, machine-learning, training-data
Organization: Department of Agriculture
Data from: Chromosome-Scale Assemblies of Flowering Dogwood Cultivars Enable Identification of Candidate Genes Regulating Anthocyanin Biosynthesis in Leaves and Bracts

<p dir="ltr">For this study we generated diploid, chromosome-scale, annotated genome assemblies for flowering dogwood (<i>Cornus florida</i>). Genomes for two cultivars, Cherokee Brave™ (pink-bracted and red-leafed) and 'Appalachian Spring' (white-bracted and green-leafed), were assembled. Additionally, a phenotyping protocol for bract color and presence/absence diagnostic SNPs for bract and leaf color were established. We leveraged these resources to evaluate linkage associations and differential gene expression related to anthocyanin biosynthesis to identify candidate genes regulating bract and leaf pigmentation. Within a 14Mb locus we identified 14 anthocyanin-related candidate genes. Two genes, with MYB (<i>g19533</i>) and RING finger (<i>g19556)</i><i> </i>binding domains, had both differential gene expression and variants with the expected segregation pattern. These resources will be valuable in combining pink-red bracts with other traits to advance flowering dogwood breeding.</p><p><br></p><p dir="ltr">Here, we have included additional data and outputs for the study. This includes:</p><ul><li>Images used for phenotyping bracts of the "pseudo-F2" population</li><li>Raw outputs of image analysis</li><li>Final phenotype file used for QTL mapping</li><li>Filtered VCF file used for linkage map construction</li><li>Final linkage map</li></ul><p></p>

Tags: anthocyanin-biosynthesis-regulators, bract-coloration, flowering-dogwood, horticulture, linkage-analysis-mapping, myb-transcription-factor, ornamental, quantitative-trait-loci-locus-qtl, time-course-rna-seq
Organization: Department of Agriculture
Tongass Landslide Initiation (Feature Layer)

This is the point feature class for the once-over landslide inventory of the Tongass National Forest. Most of the landslide polygons were digitized on the 1998 to 2010 orthophotos in GIS. Many of them were age bracketed using air photos back to the 1929 Navy Trimegon photos. It includes both field and photo interpreted landslides. This point layer represents initiation points for debris avalanches, debris torrents, combination-debris avalanches/torrents, slumps, rock fall initiated failures, and rotational failures. There is an accompanying polygon feature class (Tongass_Landslide_Areas), which represents all mass wasting features, including talus slopes, snow avalanche fields, and snow avalanche chutes. <a href='https://data.fs.usda.gov/geodata/edw/datasets.php?xmlKeyword=tongass' target='_blank' rel='nofollow ugc noopener noreferrer'>Metadata</a>

Tags: avalanche, landslides, mass-wasting, open-data, tongass-national-forest
Organization: Department of Agriculture