AndreaBozzo/ceres-open-data-index huggingface dataset:
Data and code from: Distribution of <i>Pseudomonas amygdali</i> pv. <i>loropetali</i> in the twig phylloplane of <i>Loropetalum chinense</i> shrubs in ornamental plant nurseries

<p dir="ltr">This dataset contains all raw data and R statistical software code needed to reproduce the data processing, statistical model fitting, and data/model visualizations presented in the associated manuscript, titled “Distribution of <i>Pseudomonas amygdali</i> pv. <i>loropetali</i> in the twig phylloplane of <i>Loropetalum chinense</i> shrubs in ornamental plant nurseries.”</p><p dir="ltr">The manuscript describes a survey done across six ornamental plant nurseries to assess the prevalence of galling symptoms in loropetalum plants caused by the bacterium <i>Pseudomonas amygdali </i>pv. <i>loropetali </i>(PAL), and the abundance of the PAL bacterium. The presence of symptoms was assessed, and the abundance of PAL estimated with a PAL-specific qPCR method, on twigs at three height strata on each plant. In the associated analysis notebook, we present a spatial analysis of the symptom prevalence (Moran’s <i>I </i>and logistic regression), and a Gamma generalized linear mixed model comparing PAL abundance across nurseries, height strata, and galled versus gall-free plants. Significant differences in PAL number were found between nurseries, between strata, and between galled and gall-free plants. The raw data are provided here in .csv format, and the R statistical software code in an RMarkdown notebook, with .Rmd source code and rendered .html output.</p><h2>Included files</h2><ul><li><b>PALqantitData.csv</b>: Copy numbers obtained from the PAL qPCR.</li><li><b>PALplantData_withcoords.csv</b>: Spatial locations (row and column coordinates) of surveyed plants.</li><li><b>SymptSpatial.csv</b>: Row and column coordinates and field symptom rating of surveyed plants.</li><li><b>Loropetalum_PAL_qPCR_analysis.Rmd</b>: RMarkdown notebook containing all R statistical software code to import and process data, fit statistical models, create maps, and create graphs and tables of raw data and model output.</li><li><b>Loropetalum_PAL_qPCR_analysis.html</b>: Rendered output of .Rmd notebook</li><li><b>column_metadata.pdf</b>: Description of columns in .csv files.</li></ul><p><br></p>

Tags: galls, horticulture, loropetalum-chinense, nursery, ornamental-plants, pseudomonas-amygdali-pv-loropetali, qpcr, source-code
Organization: Department of Agriculture
Forest Inventory and Analysis Forest Soil Carbon (Image Service)

Through application of a nearest-neighbor imputation approach, mapped estimates of forest carbon density were developed for the contiguous United States using the annual forest inventory conducted by the USDA Forest Service Forest Inventory and Analysis (FIA) program, MODIS satellite imagery, and ancillary geospatial datasets. This data product contains the following 8 raster maps: total forest carbon in all stocks, live tree aboveground forest carbon, live tree belowground forest carbon, forest down dead carbon, forest litter carbon, forest standing dead carbon, forest soil organic carbon, and forest understory carbon. The paper on which these maps are based may be found here: https://dx.doi.org/10.2737/RDS-2013-0004. Access to full metadata and other information can be accessed here: https://dx.doi.org/10.2737/RDS-2013-0004

Tags: analysis, atmosphere, carbon, climate-change, climatology, conus, ecology, ecosystems, environment, forest, forest-service, inventory, litter, meteorology, monitoring, plant-ecology, soil, stocks, united-states, usfs
Organization: Department of Agriculture
Code for: Understanding genetic architecture overcomes tradeoffs between seed quality and insect resistance

<p dir="ltr">Linkage map creation and functions.R R code for creating linkage maps using R/qtl. Code is annotated. Additional resources can be found at: <a href="https://rqtl.org/tutorials/" rel="nofollow" target="_blank">https://rqtl.org/tutorials/</a></p>

Tags: insect-resistance, oil-content, pericarp-strength, qtl-mapping, quantitative-trait-loci, source-code, sunflower
Organization: Department of Agriculture
Data and code from: Effects of an Unblanched Peanut and/or Peanut Skin Diet on Egg Quality, Egg Lipid Chemistry and Performance of Hens Housed in a Cage-Free Environment

<h2>Summary</h2><p dir="ltr">This dataset includes all raw data (.csv) and R software code (.Rmd notebook and rendered .html output) needed to reproduce the results presented in the associated manuscript. All exploratory data visualizations and tables of statistical model results are included. The associated manuscript presents the results of a feeding trial with four treatments: layer hens were fed a control diet or diets supplemented with high-oleic peanuts, peanut skin, or oleic acid. Response variables were measured over the course of eight weeks. Generalized linear mixed models include fixed effects of treatment, time, and their interaction, and repeated measures error structure where appropriate. Body weight was significantly greater than the control in the peanut skin and whole peanut treatment. Statistically significant effects of treatment were found for other responses, but overall the results suggest little adverse effects of peanut supplementation on layer performance or egg quality.</p><h2>Description of common columns</h2><p dir="ltr">Data sheets include a column titled "Rep" indicating either experimental replication or repeated observation within an experimental unit, "Week" for time point (week 1-8), "Pen" representing an experimental unit within each replication, or group of birds randomly assigned to a treatment, and "Trmt" to indicate one of the four treatments: </p><ul><li><b>Con</b>: control diet</li><li><b>HO PN</b>: diet supplemented with 24% high-oleic peanut</li><li><b>PN Skin</b>: diet supplemented with 3% peanut skin</li><li><b>OA</b>: diet supplemented with 2.5% oleic acid</li></ul><h2>Files included</h2><ul><li><b>body_weight.csv</b>: total body weight per pen in kg, number of birds per pen, and mean weight per bird in kg</li><li><b>egg_weight.csv</b>: weights of individual eggs in g</li><li><b>egg_quality.csv</b>: different egg quality measurements, units given in column headings</li><li><b>feed_consumed.csv</b>: total feed consumed per pen in kg</li><li><b>egg_production.csv</b>: counts of number of eggs produced</li><li><b>fatty_acid_profile.csv</b>: fatty acid concentrations, in percentage units</li><li><b>HOPN_hen_feeding_trial_analysis_supplement.Rmd</b>: RMarkdown notebook with R statistical software code</li><li><b>HOPN_hen_feeding_trial_analysis_supplement.html</b>: rendered output of RMarkdown notebook</li></ul><p></p>

Tags: cage-free-housing, layers, peanut, peanut-skin, poultry, poultry-diet, source-code
Organization: Department of Agriculture
Data From: Using microencapsulated liquid pheromone for the control of Indian meal moth (<i>Plodia interpunctella</i>) in a retail environment

<p dir="ltr">The pet food and accessories industry is a multi-billion-dollar business. Goods are shipped and stored in a scheduled manner, but consumers also dictate what is bought and when, introducing extreme variability in the retail system. These products are susceptible to stored product insect pests, such as the Indian meal moth, <i>Plodia interpunctella </i>Hübner (Lepidoptera: Pyralidae) which can cause significant damage to the product. Mating disruption is a form of control where extremely high doses of sex pheromone are used to disable mating.<i> </i>A new formulation of microencapsulated <i>P. interpunctella</i> female sex pheromone was tested in four pet food retail stores from 2021 to 2022 with monthly monitoring. Three stores, classified as high, medium/low, and low starting populations were sprayed with microencapsulated pheromone at 90-day intervals for a year. The fourth store remained an untreated control. Data were analyzed by store, month, and host product category (cat food and supplies; dog food and supplies; cat litter; fish, bird, and small animal products; and backroom area). Stores that were treated with encapsulated pheromone showed significantly lower populations over time. Heat maps demonstrated how unpredictable human interactions in this unique environment. These results show that this new formulation significantly reduces <i>P. interpunctella </i>populations over time and in combination with other IPM strategies can be recommended and brought to the forefront in a challenging commercial retail environment. </p><p dir="ltr">The stores that are labeled "Not Used" were assessed for baseline populations but numbers were so low that they were not used in further analyses. The numbers in each month column indicate counts of <i>P. interpunctella </i>moths caught in each trap. </p>

Tags: insect-pest-monitoring, mating-disruption-pheromone, mating-disruption-treatment, pet-supply, retail-store-environment, spatial-distribution, stored-products-pests
Organization: Department of Agriculture
Data for: Development and characterization of a wild emmer wheat backcross introgression population for hard winter wheat improvement

<p dir="ltr">This dataset describes a set of 1473 accessions derived from first backcrosses of hexaploid bread wheat (<i>Triticum aestivum </i>L.) to a diversity panel of wild emmer wheat (<i>Triticum turgidum </i>subsp. <i>dicoccoides </i>(Körn) Thell.). Wild emmer is the tetraploid progenitor of hexaploid bread wheat and is known to be a valuable source of genetic variation for wheat improvement. However, direct evaluation of wild emmer diversity for agronomic potential has limited value unless performed in the backgrounds of adapted cultivars. Here, we present a genetic characterization of a population of 1,473 backcross recombinant inbred lines, with an average genome composition of 75% bread wheat and 25% wild emmer. Low coverage whole-genome sequencing allowed introgressions and aneuploidies to be identified at relatively low cost per sample. These data identify the counts of hexaploid and wild emmer alleles in 1 Mb bins and 10 Mb sliding windows along each of the A- and B-genome chromosomes of each accession, using the IWGSC 'Chinese Spring' reference sequence v2.1. Allele proportions in 1 Mb bins and 10 Mb sliding windows also are provided for the introgression lines.</p>

Tags: ancient-grains, wheat-triticum-asetivum-l, wild-emmer-wheat-t-turgidum-ssp-dicoccoides
Organization: Department of Agriculture
Data from: Can manure application method and timing with cover crops reduce ammonia (NH3) and nitrous oxide (N2O) gas losses and sustain corn yield?

<p dir="ltr">Ammonia (NH3) loss following manure application is an environmental concern and nitrogen (N) loss for crop production. Manure injection typically reduces NH3 loss compared to surface application without incorporation but increases emissions of nitrous oxide (N2O) a potent greenhouse gas. Synchronizing manure in spring with cover crop (CC) growth may increase N recovery and reduce N2O emissions compared to applying manure later in the absence of growing crops. We compared two manure application methods: shallow-disk injection (IM) or surface banding without incorporation (BM) to annual ryegrass (Lolium multiflorum L.) and red clover (Trifolium pratense L.) CC at two times: early spring on growing CC (EARLY) or late spring on terminated CC (LATE). The randomized split-plot block experiment was conducted at Rock Springs, PA, during 2021-2022. After manure application, we measured NH3 for 72 hours and N2O throughout the growing season. Aboveground CC biomass, N, and carbon to nitrogen (C:N) ratio; pre-side dress soil nitrate, corn (Zea mays L.) stalk nitrate and silage yield were assessed. Averaged across application times, compared to BM, IM reduced cumulative NH3 loss, increased soil N, resulted in 13% greater corn yield but increased yield-scaled N2O. Compared to BM LATE, BM EARLY reduced NH3 loss 43%, increased CC N, reduced N2O emission 50%, but decreased corn yield 11%. When IM was EARLY compared to LATE, CC N increased 84%, cumulative N2O loss decreased 55%, and corn yield was similar. Injecting manure to growing cover crops offers a strategy for reducing detrimental NH3 and N2O emissions and maintaining corn yield.</p>

Tags: ammonia-loss, corn-silage, dairy-manure, manure-application-methods, manure-application-timing, manure-injection, manure-management, manure-nitrogen-management, nitrous-oxide-emission
Organization: Department of Agriculture
Data from: Avian Sentinels Neural Nest: AI-Powered Bird Monitoring System for Real-Time Detection and Species Identification

<p dir="ltr">Traditional bird deterrent methods, such as scarecrows, loud noise emitters, and netting, can become less effective over time due to bird habituation. This study presents an AI-driven avian monitoring system, integrating advanced deep learning models and real-time environmental sensing as a baseline for potential adaptive deterrent mechanisms to manage bird populations in aquaculture environments. The proposed system leverages high-resolution imaging, motion tracking, and environmental sensors to identify species and analyze behavioral patterns. The AI-powered classification is driven by the developed Avian Eye Net, a specialized neural network optimized for avian species detection and classification, ensuring high precision in real-time monitoring. The AI framework utilizes a multi-stage image processing pipeline, starting with region of interest (ROI) extraction using adaptive image segmentation. Image metadata is then processed through AI-based feature extraction and context-aware metadata parsing, which fuses structured data with neural network outputs. The final dataset is compiled into structured formats, exporting key parameters—including image filename, date, time, location, detected species, and population count—to a ready to analyze data file for further analysis. This structured approach enhances system efficiency, providing real-time, high-fidelity bird population monitoring. Experimental results demonstrate a classification accuracy of 97.2%, with a precision rate of 95.8% and a recall rate of 96.4% for avian species identification for three important species associated with aquaculture farms. In the future, the system’s integration with Internet of Things (IoT) devices may enable the deployment of non-invasive deterrent measures—such as LED lighting, ultrasonic sound waves, and airflow manipulation—to mitigate avian interference with aquaculture operations. This IoT with AI-powered approach enhances sustainable aquaculture management by ensuring minimal disruption to avian species while optimizing fish farm productivity.</p><p dir="ltr">The dataset contains a subset of images used to build the species identification and quantification models, highlighting the main predatory birds in the area: great blue heron, egret, and Canada goose. Also included in classification are humans. Meta-data annotation from camera trap images is also included in the code and extraction from the images.  </p>

Tags: aquaculture-applications, artificial-intelligence, bird-identification, computer-vision, deep-learning, non-invasive-avian-control, pest-detection-and-counting
Organization: Department of Agriculture
Data from: Persistence of Microcystin in Three Agricultural Ponds in Southeastern Georgia, USA

<table><tr><td><p dir="ltr">Microcystins in agricultural ponds can affect agricultural productivity, posing risks to nearby crops and health risks to livestock. Little information is known about microcystins and water quality within agricultural ponds despite surface waters being a primary water source for many farms in the eastern United States. Three agricultural ponds were sampled monthly over 17 months from June 2022 to October of 2023. Pond 1 is located on a farm near Sumner, Georgia, and is primarily used for livestock watering and irrigation. Pond 2 and Pond 3 are located on a farm near Ty Ty, Georgia, and are primarily used for irrigation. At each pond, 500 ml surface (0-10cm) water samples were collected along the nearshore (littoral sites) and in the interior (limnetic sites) of the ponds. Sampling locations did not change during the sample collection period. Water quality parameters were measured in situ with a YSI EXO-2 sonde (Yellow Spring Instruments, Yellows Springs, OH). Measured parameters included chlorophyll a, fluorescent dissolved organic matter, dissolved oxygen, specific conductance, phycocyanin, turbidity, pH, temperature, and nitrate. A 20 ml aliquot was pulled from each water sample and promptly frozen at – 20 °C until analysis for microcystin. Each aliquot underwent three freeze-thaw cycles before being assessed on a microcystin-ADDA ELISA test kit (Gold Standard Diagnostics, Warminster, PA).</p></td></tr></table><p><br></p>

Tags: cyanotoxin, in-situ-sensing, irrigation-pond, microcystin, water-quality
Organization: Department of Agriculture
USDA ARS National Rhizobium Germplasm Collection

<p>Our mission is to support application of low-input sustainable agriculture by: Providing, to the best of our ability, technical information about rhizobia, their preservation, and cultural and symbiotic characteristics; Acquiring and preserving the nitrogen-fixing bacterial symbionts of leguminous plants with the goal of maintaining widest possible genetic diversity; Maintaining quality control of new and existing germplasm by evaluation of microbiological purity and by examination of nodulation of the original trap host plant; Distributing cultures to the public and private sectors without charge for these services; Developing or adapting techniques in molecular biology for the determination of genetic diversity of rhizobia, to investigate interactions with their host plants and to identify novel characteristics; Acquiring, maintaining, evaluating quality, and distributing type strains for all the different taxa of nitrogen-fixing legume symbionts; Participating in the UNESCO program.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: USDA ARS National Rhizobium Germplasm Collection.</p> <p>File Name: Web Page, url: <a href="https://www.ars-grin.gov/Rhizobium" target="_blank">https://www.ars-grin.gov/Rhizobium</a> </p></li></ul><p></p>

Tags: ars, data-gov, np301, online-database
Organization: Department of Agriculture
Data and Supplementary Information from: Oligosaccharide Production Using β-galactosidase from <i>Lactobacillus bulgaricus</i> and <i>Kluyveromyces lactis</i> in Sweetened Reconstituted Nonfat Dry Milk

<p dir="ltr">Supplementary information and raw data for the publication entitled "Oligosaccharide Production Using β-galactosidase from <i>Lactobacillus bulgaricus</i> and <i>Kluyveromyces lactis</i> in Sweetened Reconstituted Nonfat Dry Milk"</p><p dir="ltr">ß-galactosidase (B-gal) is a vital enzyme used in the food industry to reduce lactose from dairy ingredients through hydrolysis and to synthesize galacto-oligosaccharides (GOS), a known bifidogenic prebiotic, from galactose through transgalactosylation. To favor transgalactosylation, high carbohydrate concentrations must be available to accept the galactose. Many dairy products rely on sweeteners for flavor and texture, but it is not known if high non-lactose sugar concentrations in milk can also favor transgalactosylation. B-gal from GRAS status Lactobacillus bulgaricus strains B548, LB11, YB1, or Kluyveromyces lactis (KL) in the commercial product Lactozyme® 2600L were used to determine if the transgalactosylation activity is greater in reconstituted nonfat dry milk (NDM, 10%, wt/wt) with commercial sweeteners compared to the transgalactosylation activity that occurs in unsweetened NDM at 50 °C for 20 h. Sucrose (14.4%, wt/wt), corn syrup solids (14.4%, wt/wt), or a mixture of sucrose (9.9%, wt/wt) and corn syrup solids (4.5%, wt/wt) were dissolved with NDM (n=3), then heated with stirring for 30 minutes at 70 °C for batch pasteurization. For L. bulgaricus, whole cells were inoculated at 7 log CFU/mL, or the same quantity of cells were lysed prior to adding to the milk and carbohydrate mixtures, or 1.85 U of KL B-gal was used. The sucrose mixture released the highest glucose from all whole cell, lysate, and KL enzyme preps, with LB11 lysate releasing the highest (245.57 ± 25.16 mM). High-Performance Anion-Exchange Chromatography with Pulsed Amperometric Detection was used to visualize the presence of oligosaccharides with degrees of polymerization of 3 to 7. Oligosaccharides from YB1 lysate treated sucrose mixtures also increased the anaerobic growth of Bifidobacterium breve 2141 at 37 °C compared to untreated or KL B-gal treated sucrose mixtures. B-gal treatment of sucrose in nonfat milk with and without corn syrup can be a source of prebiotic oligosaccharides, although more work is needed to determine if background microbiota are involved in hydrolyzing sucrose, and if fructose is also polymerizing to form novel oligosaccharides.</p>

Tags: corn-syrup, sucrose-physiological-effect, transgalactosylation
Organization: Department of Agriculture
Data from: Complex Reticulation in Backbone Subfamily Relationships in Leguminosae

<p dir="ltr">Contradictory lines of evidence have made it difficult to resolve the phylogenetic history of the legume diversification era; this is true for the backbone topology, and for the number and timing of whole genome duplications (WGDs). By analyzing the transcriptomic data for 473 gene families in 76 species covering all six accepted legume subfamilies, we assessed the phylogenetic relationships of the legume backbone and uncovered evidence of independent whole genome duplications in each of the six legume subfamilies. Three subfamilies — Cercidoideae, Dialioideae, and Caesalpinioideae — bear evidence of an allopolyploid duplication pattern suggestive of ancient hybridization. In Cercidoideae and Dialioideae, the hybridization appears to be within-subfamily, with the basal genera Cercis and Poeppigia appearing to be unduplicated descendants of one of the parental lineages; in Caesalpinioideae, the hybridization appears to involve a member of the Papilionoid lineage, and some other lineage, potentially extinct. Three independent lines of evidence, consisting of a concatenated superalignment, concordance factor analysis of the set of gene family alignments and topologies, and direct inference of reticulation events via maximum pseudolikelihood implemented by PhyloNet, converged on a single backbone hypothesis and the above hypotheses of reticulate evolution.</p>

Tags: allopolyploidy, caesalpinioideae, cercidoideae, cercis, detarioideae, dialioideae, duparquetioideae, fabaceae, leguminosae, papilionoideae, phylogenetics
Organization: Department of Agriculture