Full view of research station reports 1859-1920. In German.
Table 2.1: agridat::darwin.maize Table 5.1: agridat::broadbalk.wheat Table 6.1: agridat::mercer.wheat.uniformity Table 6.2: agridat::wiebe.wheat.uniformity Table 58.1: agridat::caribbean.maize
Master thesis. Department of Statistics, Addis Ababa University. One dataset from wheat, RCB, with field coordinates.
31 wool from 24 ewes, 6 cuttings 116 grass NPK factorial, 3 years, 36 obs 116 2^5 factorial, 1 rep, 32 obs 117 2^3 factorial, 3 rep 117 sugar beet 3^3 factorial, 2 rep, 54 obs 139 alfalfa 3x2^2 factorial 149 cabbage NPK split-plot, xy, 2 rep, 108 obs 150 soybean nitro-variety split-plot 193 wheat variety inc block, 9 block 201 rice variety balanced lattice, 80 obs 279 maize covariate, yield & plant count, 4 rep, 32 obs
Pig weight data is found in
Sitka spruce data is found in:
Milk protein data is found in:
nlme::Milk. A thorough description of this data can be found in Molenberghs & Kenward, Missing Data in Clinical Studies, p. 377. Original source: A. P. Verbyla and B. R. Cullis, Modelling in Repeated Measures Experiments. https://www.jstor.org/stable/2347384
192 3x3 factorial 204 3x2 factorial 236 2x2x2 factorial with confounding 257 2x3x2 factorial with confounding 276 split-plot with layout 285 nested multi-loc (Also problems page 22) 350 cubic lattice 420 balanced inc block 491 Latin square with covariate
Small, mostly simulated data.
2 83 variety x nitro split-plot - agridat::yates.oats 3 104 doubled-haploid barley 3 135 wheat/rye competition, heritability 5 190 chickpea flowering in families 7 250 canola oil gxe, sowing date, rainfall, oil. Si & Walton 2004. 7 284 pig growth, 4 diets 7 285 sheep milk fat and lactose 7 290 wheat anoxia root porosity, 9 gen 7 291 wool fibers, 3 trt, 21 animals 9 370 alphalpha design (row-column inc block), xy 10 434 hollamby wheat trial, xy - agridat::gilmour.serpentine
? uniformity trial of raddish - agridat::heath.raddish.uniformity 50 uniformity trial of cabbage 6x8 plots
Extensive collection of datasets from rice experiments. Many added to agridat.
First edition: https://archive.org/details/methodsofstatist031744mbp
18 Uniformity trial - agridat::goulden.barley.uniformity 153 Split-split plot with factorial sub-plot treatment - agridat::goulden.splitsplit 194 Incomplete block 197 Inc block 205 Latin square 208 Inc block 255 Covariates in feeding trial - agridat::crampton.pig
216 Latin square - agridat::goulden.latin 423 Control chart with egg weights - agridat::goulden.eggs
379 MET 4 year, 2 field, 5 block, 5 gen
357 alfalfa quadruple lattice 358 alpha design 488 split-plot sorghum hybrid,density 516 alfalfa rcb, two-year 521 crossover design cattle feedstuff
Many small datasets.
27 uniformity - agridat::goulden.barley.uniformity 213 split-plot 234 immer multi-environment 260 lattice pinto-bean 276 triple lattice cotton 280 lattice sugar beet 289 balanced lattice 336 repeated wheat
79 Latin square 89 Split-plot 103 Split-split 117 Split-block - agridat::little.splitblock 126 Repeated harvests
The ‘NIR’ data has NIR spectra measurements of wheat for the purpose of understanding protein quality.
10 weekly milk yields 24 carrot weight 96 cabbage fertilizer 143 intercropping cowpea maize 177 honeybee repellent non-normal 251 cauliflower poisson - agridat::mead.cauliflower 273 rhubarb RCB covariate 296 onion density 316 lambs 341 germination 350 germination factorial - agridat::mead.germination 352 poppy 359 lamb loglinear - agridat::mead.lambs 375 rats 386 intercrop 390 intercrop cowpea maize - agridat::mead.cowpeamaize 404 apple characteristics (incomplete)
323 Turnip spacing data - agridat::mead.turnip
Design and Analysis of Experiments: Classical and Regression Approaches with SAS. https://books.google.com/books?id=_P3LBQAAQBAJ&pg=PA334
334 Two examples of 5x5 Graeco-Latin squares in cassava and maize
455 2 factors, 1 covariate 458 1 factor, 2 covariates - agridat::crampton.pig
3 Length and number of grains per ear of wheat 138 Uniformity trial - agridat::panse.cotton.uniformity 154 RCB 8 blocks 167 two factorial, 6 rep trial 178 2^4 factorial, 8 blocks, partial confounding 192 3^3 factorial, 3 reps/9 blocks, partial confounding 200 split-plot, 6 rep 212 strip-plot, 6 rep 219 cotton variety trial, yield & stand counts 256 8x8 simpple lattice, 4 reps 282 5 varieties at 6 locations 295 5 N levels at 5 locations 332 4 regions, 9 villages each, 3 treatments
84 Distribution of purple/white starchy/sweet seeds from 11 ears 190 Sugar cane MET: 2 year, 5 block, 5 variety 199 Tea MET: 3 year, 2^2 factorial fertilizer 206 Grass: 4 rep, 2 gen, 4 cutting treatments 211 Cotton: 4 dates, 3 spacings, 3 irrigation, 2 nitro - agridat::gregory.cotton
19 456 2x2x4 Factorial, 2 rep 19 466 2x4 factorial, layout, plot size, kale (from Rothamsted) 19 466 3x5 factorial, 3 rep, potato 20 494 3x4 Split-plot with layout 21 505 2x2x2 Factorial, 5 rep 21 515 2x2x2x2 Factorial, 3 rep, with layout. (Evaluated, rejected as too variable) 22 537 2x2x2 factorial, 6 rep, potato 22 537 2x2x2x2 factorial, 2 rep, wheat, layout
5 - Length of ear head and number of grains per ear, 400 ears. 95 - variety RCB, 5 gen, 25 rep, diagonal layout 107 - Latin square, 8 entries. 117 - Factorial: 8 blocks, 3 varieties, 5 treatments, 2 infections 126 - Multi-environment trial, 3 year, 13 varieties, 2 loc, 5 blocks agridat::shaw.oats
168 regression 352 3x3 factorial, 4 blocks 359 2x2x2 factorial, 8 blocks, daily pig gain 362 2x3x4 factorial, 2 blocks, daily pig gain 371 3x4 split-plot, 3 var, 4 date, 6 blocks 374 2x3x3 split-split-plot, irrig, stand, fert, block 378 4x4 split-plot, 4 block, 4 year, 4 cuttings asparagus 384 regression with 2 predictors 428 covariates, 6 varieties, 4 blocks, yield vs stand 440 pig gain vs initial weight, 4 treatments, 40 pigs 454 protein vs yield for wheat, 91 plots, quadratic regression
154 Mint plant growth, 2-way + pot + plant 244 Trivariate data 319 Regression with three predictors 384 Split-plot yield 387 Split-plot row spacing 400 Soybean 3 loc 423 Pig weight gain 429 Guinea pig weight gain 434 Soybean lodging
Many datasets. Some added to agridat.
The online-supplements contain many small datasets for the examples and exercises.
Extensive data for detection of pesticides in water samples. See Appendix 5 and Appendix 6 of the supporting info. https://water.usgs.gov/nawqa/pnsp/pubs/circ1291/supporting_info.php
IRRI Rice Research includes plot-level data for long term rice experiments. https://dataverse.harvard.edu/dataverse/RiceResearch
Vol 26/ 281. Cox: Analysis of Lattice and Triple Lattice. Page 11: Lattice, 81 hybs, 4 reps Page 24: Triple lattice, 81 hybs, 6 reps Vol 29/347. Homeyer. Punched Card and Calculating Machine Methods for Analyzing Lattice Experiments Including Lattice Squares and the Cubic Lattice. Page 37: Triple lattice (9 blocks * 9 hybrids) with 6 reps. Page 60: Simple lattice, 8 blocks * 8 hybrids, 4 reps. Page 76: Balanced lattice, 25 hybrids Page 87: Lattice square with (k+1)/2 reps, 121 hybrids, 6 rep Page 109: Lattice square with k+1 reps, 7 blocks * 7 hyb, 8 reps Page 126: Cubic lattice, 16 blocks * 4 plots = 64 varieties, 9 reps, cotton Vol 32/396. Wassom. Bromegrass Uniformity Trial: agridat::wassom.bromegrass.uniformity Vol 33/424. Heady. Crop Response Surfaces and Economic Optima in Fertilizer - agridat::heady.fertilizer Vol 34/358. Schwab. Research on Irrigation of Corn and Soybeans At Conesville. Page 257. 2 year, 2 loc, 4 rep, 2 nitro. Stand & yield. Nice graph of soil moisture deficit (fig 9) Vol. 34/463. Doll. Fertilizer Production Functions for Corn and Oats. Table 1, 1954 Clarion Loam. N,P,K. Table 14, 1955 McPaul Silt Loam. N,P. Table 25, 1955 corn. K,P,N. Table 31, 1956 oats, K,P,N. Trends difficult to establish. Vol 34/472. Pesek. Production Surfaces and Economic Optima For Corn Yields. Same data published in SSA journal? Vol 34/488. Walker. Application of Game Theory Models to Decisions. Vol 35/494. North Central Regional Potassium Studies with Alfalfa. Page 176. Two years, several locs per state, multiple states, multiple fertilizer levels, multiple cuttings. Soil test attributes. Page 183. Yield and %K. Vol 35/503. North Central Regional Potassium Studies with Corn.
Xavier, Alencar et al.. Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population, https://www.g3journal.org/content/8/2/519
Data are in the SoyNAM and NAM packages.
Barrero, Ivan D. et al. (2013). A multi-environment trial analysis shows slight grain yield improvement in Texas commercial maize. Field Crops Research, 149, Pages 167-176. https://doi.org/10.1016/j.fcr.2013.04.017
This is a large (14500 records), multi-year, multi-location, 10-trait data. Sent a note encouraging the authors to formally publish the data. Source: http://maizeandgenetics.tamu.edu/CTP/CTP.html
Cleveland, M.A. and John M. Hickey, Selma Forni (2012). A Common Dataset for Genomic Analysis of Livestock Populations. G3, 2, 429-435. https://doi.org/10.1534/g3.111.001453
The supplemental information for this paper contains data for 3534 pigs with high-density genotypes (50000 SNPs), and a pedigree including parents and grandparents of the animals.
Daillant-Spinnler (1996). Relationships between perceived sensory properties and major preference directions of 12 variaties of apples from the southern hemisphere. Food Quality and Preference, 7(2), 113-126. https://dx.doi.org/10.1016/0950-3293(95)00043-7
The data are in
ClustVarLV::apples_sh$senso 12 apple varieties, 43 traits, 60 consumers
Gregory, Crowther & Lambert (1932). The interrelation of factors controlling the production of cotton under irrigation in the Sudan. Jour Agric Sci, 22, p. 617.
Hedrick (1920). Twenty years of fertilizers in an apple orchard. https://books.google.com/books?hl=en&lr=&id=SqlJAAAAMAAJ&oi=fnd&pg=PA446
The authors found no significant differences between fertilizer treatments.
Meehan & Gratton (2016). A Landscape View of Agricultural Insecticide Use across the Conterminous US from 1997 through 2012. PLOS ONE, https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0166724
Supplemental material contains county-level data for each of 4 years. Complete R-INLA code for analysis.
Monteverde et al Integrating Molecular Markers and Environmental Covariates To Interpret Genotype by Environment Interaction in Rice (Oryza sativa L.) Grown in Subtropical Areas https://doi.org/10.1534/g3.119.400064 https://gsajournals.figshare.com/articles/dataset/Supplemental_Material_for_Monteverde_et_al_2019/7685636
Supplemental information contains phenotypic data and markers and environmental covariates for PLS analysis.
Roger W. Hexem, Earl O.Heady, Metin Caglar (1974) A compendium of experimental data for corn, wheat, cotton and sugar beets grown at selected sites in the western United States and alternative production functions fitted to these data. Technical report: Center for Agricultural and Rural Development, Iowa State University. https://babel.hathitrust.org/cgi/pt?id=wu.89031116783;view=1up;seq=3
The technical report provides data from experiments on corn, wheat, cotton & sugar beets, each crop tested at several locations over two years, with a factorial structure on irrigation and nitrogen treatments, with replications. Three polynomial functions were fit to the data for each location (quadratic, square root, three-halves).
Kenward, Michael G. (1987). A Method for Comparing Profiles of Repeated Measurements. Applied Statistics, 36, 296-308.
An ante-dependence model is fit to repeated measures of cattle weight.
Klumper & Qaim (2015). A Meta-Analysis of the Impacts of Genetically Modified Crops. https://doi.org/10.1371/journal.pone.0111629
Nice meta-analysis dataset. Published data only include differences, not standard-errors. See the comments on PLOS article for some peculiarities in the data.
Lado, B. et al. (2013). Increased Genomic Prediction Accuracy in Wheat Breeding Through Spatial Adjustment of Field Trial Data. G3, 3, 2105-2114. https://doi.org/10.1534/g3.113.007807
Has a large haplotype dataset (83 MB) and two-year phenotype data with multiple traits.
Payne, Roger (2015). The Design and Analysis of Long-Term Rotation Experiments. Agronomy Journal, 107, 772-784. https://doi.org/10.2134/agronj2012.0411
The data and R code appeared in the paper. Free access, but closed copyright.
Snedecor, George and E. S. Haber (1946). Statistical Methods For an Incomplete Experiment on a Perennial Crop. Biometrics Bulletin, 2, 61-67. https://doi.org/10.2307/3001959
Harvest of asparagus over 10 years, three cutting dates per year, 6 blocks.
Technow, Frank, et al. (2014). Genome Properties and Prospects of Genomic Prediction of Hybrid Performance in a Breeding Program of Maize. August 1, 2014 vol. 197 no. 4 1343-1355. https://doi.org/10.1534/genetics.114.165860
Genotype and phenotype data appears in the sommer package.
Tian, Ting (2015). Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data. https://doi.org/10.1371/journal.pone.0144370
agridat::australia.soybean data and one other real dataset with 4 traits that are not identified. All data and code available.
Randall J. Wisser et al. (2011). Multivariate analysis of maize disease resistances suggests a pleiotropic genetic basis and implicates a GST gene. PNAS. https://doi.org/10.1073/pnas.1011739108
The supplement contains genotype data, but no phenotype data.
Rife et al. (2018) Genomic analysis and prediction within a US public collaborative winter wheat regional testing nursery. https://doi.org/10.5061/dryad.q968v83
Large phenotypic dataset with 691 wheat lines, 33 years, 670 environments, 3-4 reps, 120000 datapoints. No genotypic data is included.
van der Voet et al. (2017). Equivalence testing using existing reference data: An example with genetically modified and conventional crops in animal feeding studies. https://doi.org/10.1016/j.fct.2017.09.044
The full datasets for the GRACE studies A-E are available here: https://www.cadima.info/index.php/area/publicAnimalFeedingTrials CC license.
Yan, Weikei (2002). Singular value partitioning in biplots. Agron Journal.
Winter wheat, 31 gen in 8 loc. This data is different from Yan’s earlier papers. Unfortunately, the data given in the paper are missing two rows.
Three datasets with censored observations for the paper “Analyzing interval-censored data in agricultural research: A review with examples and software tips”.
Five datasets used to illustrate analyses.
Has assorted data and functions for analysis of agricultural data.
Datasets for agriculture and applied biology. Referenced by this blog: https://www.statforbiology.com/
aml::wheat genetic and phenotypic data for wheat. Modest size.
Has an A matrix (but no pedigree) for 499 genotypes at 4 locations.
Has an A matrix (but no pedigree) for 499 genotypes at 4 locations.
Safety assessment in agriculture trials
apples_sh sensory attributes and preference scores for 12 apple varieties.
Has nice herbicide dose response curves and germination data for mungbean, rice, wheat.
Contains 10 historical datasets for plant disease epidemics.
Has phenotype data and marker data for 599 wheat lines in 4 environments.
sbGeneal contains a soybean pedigree with 230 varieties.
gRbase::carcass: thickness of meat and fat on slaughter pigs
lmtest::ChickEgg time series of annual chicken and egg production in the United States 1930-1983.
Recon contain measurements of Atrazine in water samples.
Miguez. Non-linear models in agriculture.
agridat::miguez.biomass Vignettes and functions for working with (non)linear mixed models
nlme::Orange: Growth of orange trees
nlme::Soybean: Growth of soybean plants. From the book “Nonlinear Models for Repeated Measurement Data”.
pbkrtest::beets Yield and percent sugar in split-plot experiment.
Data: fulldial Data: linetester Data: peanut same as agridat::kang.peanut
This package has county-level data from the United States Census of Agriculture, along with a vignette to illustrate survey sampling analyses.
SemiPar::onions is same as agridat::ratkowski.onions
https://ncss-tech.github.io/AQP/soilDB/soilDB-Intro.html Soil database interface.
Data: h2. Modest-sized GxE experiment in potato Data: cornHybrid. Yield/PLTHT for 100 hybrids from 20 inbred * 20 inbred, 4 locs. Phenotype and relationship matrix.
data(DT_wheat) # CIMMYT wheat data DT_wheat # 599 varieties, yield in 4 envts GT_wheat # 599 varieties, 1279 markers coded -1,1
Data: FDdata taken from agridat::bond.diallel
data(DT_technow) # From http://www.genetics.org/content/197/4/1343.supplemental DT <- DT_technow # 1254 hybs, parents, GY=yield, GM=moisture Md <- Md_technow # 123 dent parents, 35478 markers Mf <- Mf_technow # 86 flint parents, 37478 markers Ad <- Ad_technow # 123 x 123 A matrix Af <- Af_technow # 86 x 85 A matrix
Dataset with phenotype data 3 yr, 9 locations, 18 environments, 60 thousand observations for height, maturity, lodging, moisture, protein, oil, fiber, seed size. There are 5000+ strains, 40 families.
Data formatted for the analysis of the NAM package is available with the following command:
Has a vignette ‘The Problem of Spatial Autocorrelation: forty years on’ that examines agriculture in Irish counties. See also the data
spuRs::trees has data for 107 trees that were cut into cross sections with the volume calculated at roughly 10-year increments. This is a subset of the much-larger original data from Guttenberg: https://archive.org/stream/wachstumundertra00gutt
Blog posts with example analyses.
https://CRAN.R-project.org/package=statgenSTA See vignette: Modeling field trials using statgenSTA
Includes a worked example with data from: https://data.inra.fr/dataset.xhtml?persistentId=doi:10.15454/IASSTN
Very large GxE data here for 2014 and 2015. Hybrid & inbred phenotype data, weather data, genomic data. Very nice.
Links to long-term experiments.
https://wheat.pw.usda.gov/ggpages/HxT/ The Harrington x TR306 Barley Mapping Population. The genotype and phenotype data comes from Mapmaker, but seems to be in a slightly non-standard format; 145 DH lines, 217 markers, 25 env, 1 rep.
https://wheat.pw.usda.gov/ggpages/SxM/ . This data is agridat::steptoe.morex.
https://www.ideals.illinois.edu/handle/2142/3528 Data File : Raw data from each ear analyzed each year of the Illinois long-term selection experiment for oil and protein in corn (1896-2004)
Case study 4 is a nice diallel example with sheep data. Available as agridat::ilri.sheep
STAR, PBTools, CropStat. The STAR user guide has well-documented data (even using 2 from agridat), but the PBTools user guide does not document the data.
http://www.era.rothamsted.ac.uk/index.php Data from Broadbalk and other long-term experiments.
Github draft data: https://github.com/Rothamsted-Ecoinformatics/YieldbookDatasetDrafts
Annual reports from Rothamsted 1908-1987. Many have data, especially in the early years (before WWII) there are data given for the ‘Classical Experiments’.
Year, page 1908-1926 1926-1927 agridat::sawyer.multi.uniformity 1927-1928 agridat::sawyer.multi.uniformity 1929-1930 1931,143 agridat::yates.oats 1932 1933 1934,215-222 Sugar beet multi-environment trial with 3^3 fertilizer treatments at each site Roots, SugarPercent, SugarWeight, PlantNumber, Tops, Purity. 1935 1936,241 Similar to the 1934 experiment, but only gives the main effects, not the actual data. 1937-1939 1946-1953
Potato and Tomato genotype and phenotype data.
rstats4ag.org (no http included here because of firewall problems).
Datasets for mixed models, ancova, dose response curves, competition.
Annual Kaggle-style competition sponsored by Syngenta.
Sensor observations, plant phenotypes, derived traits, genetic and genomic data. Beta version until Nov 2018.
Box of uniformity trial data
STATS17 WG Cochran Uniformity trial data. Genstat data. Data received since publication of the catalogue. 1935-1943. Uniformity trial data. 1930-1936. Uniformity trials. 1936-1938. Uniformity trials. R data. 1936-1937. O. V. S. Heath. Cotton uniformity trial data. 1934-1935. Data. Yields of grain per foot length. 1934. Catalogue of field uniformity trial data. N. d. Demandt. 1931. One box