This has now been scanned and PDFs put into the GitHub repository for the agridat package.
Box of uniformity trial data
STATS17 WG Cochran 1. Uniformity trial data. 2. Genstat data. Data received since publication of the catalogue. 1935-1943. 3. Uniformity trial data. 1930-1936. 4. Uniformity trials. 1936-1938. 5. Uniformity trials. R data. 1936-1937. 6. O. V. S. Heath. Cotton uniformity trial data. 1934-1935. 7. Data. Yields of grain per foot length. 1934. 8. Catalogue of field uniformity trial data. N. d. 9. Demandt. 1931. One box
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
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 for 2 reps) (not latinized row col) 10 434 hollamby wheat trial - agridat::gilmour.serpentine
Agrotech Publishing Academy, 2010. https://archive.org/details/expldesnanddatanalinagblg00023
43 Percent insect survival in 12 rice varieties, 3 reps 50 CRD 57 RCBD 67 Latin Square 85 Sampling, 4 rep, 9 trt, 4 sub-samples agridat::grover.rcb.subsample 88 Split-plot, 3 rep, 2 measurements/plot, plant height (unusual subsample example) 97 Missing plot 105 Latin square with missing plot 115 2^2 factorial, 6 block 118 2^3 factorial, 3 block 120 Two factor asymmetrical, 5 rep 140 2^3 fractional factorial, 3 rep 160 Split-plot (planting date, variety), 3 rep 168 Strip-plot, 3 rep 176 Milk yield with covariate 188 Multi-year nitrogen treatment 197 BIBD 13 varieties 205 Lattice 4 blocks, 3 reps, 16 trt 226 Augmented BIBD 236 Group-divisible 239 PBIB 241 Augmented group-divisible 245 Augmented PBIB 250 6x6 full diallel, 4 rep agridat::grover.diallel
23 uniformity trial of radish - agridat::heath.raddish.uniformity 50 uniformity trial of cabbage - agridat::heath.cabbage.uniformity
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. In data-unused. 144 Non-IID errors 155 Square root transform 158 Germination, 3 reps, 24 treatments 261 Response surface, nitrogen, harvest 277 Count data
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 - agridat::woodman.pig 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, 9-11 villages in each region, 3 fertilizer treatments
Note: The 1954 edition can be found at https://archive.org/details/dli.scoerat.949statisticalmethodsforagriculturalworkers/page/138/mode/2up
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
8 Uniformity trial 18 * 6 plots 56 RCB 4 rep, 5 trt 71 Latin square 5x5 86 Factorial 4x2, 3 rep 97 Factorial 2x3x2, 3 rep 125 Fertilizer trial, 3 rep, 5 levels 136 Split plot variety x planting date, 3 rep 148 Strip plot 2 potash x 3 potassium, 3 rep 170 Augmented breeding trial with 3 checks, 6 inc blocks 174 Inc Block 182 Lattice 5x5, 2 rep 192 GxE 10 gen, 12 env. Stability analysis. 208 Factorial 2x3 at 8 locs, homogeneous variance, early lentils 217 GxE 8 gen, 5 loc, heterogeneous variance 232 Factorial 2x3 at 8 locs, late lentils (see also page 208) 249 On-farm trial, 24 entries, 3 rep RCB 257 Demonstration trials, 5 locs 272 Covariance example, RCB 6 rep, 4rt 278 Multi-year 2x2 factorial, 4 rep 309 Pasture trial 323 On-farm trial, 2 variety 8 loc 327 On-farm trial 6 trt, 5 loc 334 On-farm trial 4 trt, 6 loc 343 On-farm trial 2x3 factorial, 3 loc 351 Feeding trial, 2 trt, 2 periods 357 Intercrop, 2 crops 372 Intercrop, 2 crop, 4 mixtures, 4 rep. agridat::petersen.sorghum.cowpea
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
KBS037:Precision Agriculture Yield Monitoring in Row Crop Agriculture https://lter.kbs.msu.edu/datasets/40 https://doi.org/10.6073/pasta/423c07d6ea3317c545beabb4b8e502c8 Yield monitor data across several years and crops. Un-friendly license.
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.
Exploring genotype by environment interaction on cassava yield and yield related traits using classical statistical methods https://doi.org/10.1371/journal.pone.0268189
36 gen, 20 env, 3 rep. Analysis and data here: https://github.com/mab658/classical_analysis_GxE
Analysis of multi-harvest data through mixed models: an application in Theobroma grandiflorum breeding https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/csc2.20995 Nice. Complete data and R code. They found FA3 best for genetic covariances, AR1H best for residual structure. Used FAST and OP (by Cullis) for selection.
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.
Accounting for spatial trends in multi-environment diallel analysis in maize breeding https://doi.org/10.1371/journal.pone.0258473
78 hybrids in a diallel, 4 environments, 3 reps. Compared spatial and non-spatial analyses.
Food Quality and Preference, 7(2), 113-126. https://doi.org/10.1016/0950-3293(95)00043-7
The data are in
ClustVarLV::apples_sh$senso 12 apple varieties, 43 traits,
Jour Agric Sci, 22, p. 617.
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.
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.
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.
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.
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.
“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.
Genomic Selection in Multi-environment Crop Trials https://www.g3journal.org/content/6/5/1313 http://www.g3journal.org/content/6/5/1313/suppl/DC1 648 genotypes planted in pots yr 1, 856 lines yr 2, 639 common to both years. 7864 SNP markerks
Random regression for modeling yield genetic trajectories in Jatropha curcas breeding. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244021
Repeated measurements over six years. Data in supplemental Word doc.
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).
Statistical Methods For an Incomplete Experiment on a Perennial Crop. Biometrics Bulletin, 2, 61-67. https://www.jstor.org/stable/3001959
Harvest of asparagus over 10 years, three cutting dates per year, 6 blocks.
Assessment of design and analysis frameworks for on-farm experimentation through a simulation study of wheat yield in Japan. https://github.com/takashit754/geostat
Yield-monitor data for 3 fields.
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.
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
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.
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.
Genetic Covariance of Environments in the Potato National Chip Processing Trial https://dl.sciencesocieties.org/publications/cs/articles/59/1/107
Supp 2 contains genomic data, but there is no easy way to find the phenotypic data.
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.
Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population. https://doi.org/10.1534/g3.117.300300
Data are in the SoyNAM and NAM packages.
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.
See also: https://cran.r-project.org/web/views/Agriculture.html
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.
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
gRbase::carcass: thickness of meat and fat on
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
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
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:
https://github.com/mdkrause/SoyURT Large historical data to study GxE and identify mega-environments with genetic and non-genetic factors.
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
Blog posts with example analyses.
AMMI, FW, GGE stability analyses.
This is a very nice package with full GxE data and marker data with 41722 loci on 246 lines.
256 hybrids, 29 envts across 2 years, multi-trait (yield, silking, pltht, earht, etc). Includes a worked example with data from: https://data.inra.fr/dataset.xhtml?persistentId=doi:10.15454/IASSTN And publication: Millet 2016, Genome-Wide Analysis of Yield in Europe: Allelic Effects Vary with Drought and Heat Scenarios, https://academic.oup.com/plphys/article/172/2/749/6115953
Analysis of phenotypic data from field experiments using SpATS, lme4, or asreml.
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.
Very limited 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 1946-1955 1986
9 2x2x2, 4 rep 27 2x2x2x2x2 factorial 33 2x2x2 factorial in two 4x4 Latin Squares 42 3x3x3 factorial 59 3x2x2 factorial in 3 reps. See also page 39. 74 Split-plot agridat::yates.oats
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.
Group: Field Crops Commodity: Corn Category: Area Harvested, Yield
Data Item: Corn grain Acres Harvested, Yield Bu/Ac Domain: Total
Geography: State See