https://www.rothamsted.ac.uk/library-and-information-services
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 https://catalog.hathitrust.org/Record/000549685
Full view of research station reports 1859-1920. In German.
https://www2.stat.duke.edu/courses/Spring01/sta114/data/andrews.html
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.maizeDibaba Bayisa Gemechu and Aweke, Girma (or maybe Girma Taye)
Master thesis. Department of Statistics, Addis Ababa University. One dataset from wheat, RCB, with field coordinates.
Note: Forkman cites this author as “D. Bayisa”
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 obshttps://faculty.washington.edu/heagerty/Books/AnalysisLongitudinal/datasets.html
Pig weight data is found in SemiPar::pig.weights
Sitka spruce data is found in: geepack::spruce
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.
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 covariateSmall, mostly simulated data.
https://www.wiley.com/en-us/Introduction+to+Mixed+Modelling%3A+Beyond+Regression+and+Analysis+of+Variance%2C+2nd+Edition-p-9781119945499
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.serpentineAgrotech 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.diallelhttps://archive.org/details/investigationbye0000heat
23 uniformity trial of radish - agridat::heath.raddish.uniformity
50 uniformity trial of cabbage - agridat::heath.cabbage.uniformityExtensive 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.pigSecond edition:
http://krishikosh.egranth.ac.in/handle/1/2034118
(broken)
216 Latin square - agridat::goulden.latin
423 Control chart with egg weights - agridat::goulden.eggs379 MET 4 year, 2 field, 5 block, 5 gen357 alfalfa quadruple lattice
358 alpha design
488 split-plot sorghum hybrid,density
516 alfalfa rcb, two-year
521 crossover design cattle feedstuffhttps://archive.org/details/fieldplottechniq00leon
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 datahttps://www.wiley.com/legacy/wileychi/chemometrics/datasets.html
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)https://books.google.com/books?id=CaFZPbCllrMC&pg=PA323
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 maizehttps://archive.org/details/secondeditionsta001000mbp
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
https://archive.org/details/statisticaltechn031729mbp
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.cotton8 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.cowpeahttps://psfaculty.plantsciences.ucdavis.edu/plant/
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, layouthttps://archive.org/details/in.ernet.dli.2015.176662
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 lodgingMany 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
https://data.nal.usda.gov/about-ag-data-commons https://data.nal.usda.gov/search/type/dataset
https://datacommons.cyverse.org/ https://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated
https://dataverse.harvard.edu/
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.
https://www.nature.com/sdata/
https://library.wur.nl/ojs/index.php/odjar/
https://datarepository.wolframcloud.com/
https://lib.dr.iastate.edu/ag_researchbulletins/
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$pref and
ClustVarLV::apples_sh$senso 12 apple varieties, 43 traits,
60 consumers
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 two‑stage approach for the spatio‑temporal analysis of high‑throughput phenotyping data. https://doi.org/10.1038/s41598-022-06935-9
Time-series data for individual plots in a field of many genotypes.
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
Uses agridat::australia.soybean data and one other real
dataset with 4 traits that are not identified. All data and code
available.
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.
A retrospective analysis of historical data of multi-environment trials for dry bean ( Phaseolus vulgaris L.) in Michigan. https://github.com/msudrybeanbreeding/DryBean_MultiEnvTrials Full dataset and R code.
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
https://github.com/Project-AgML/AgML
Datasets for agricultural machine learning such as image classification, semantic segmentation, object detection, etc.
https://github.com/OnofriAndreaPG/agriCensData
Three datasets with censored observations for the paper “Analyzing interval-censored data in agricultural research: A review with examples and software tips”.
https://myaseen208.github.io/agriTutorial/
Five datasets used to illustrate analyses.
Has assorted data and functions for analysis of agricultural data.
https://github.com/OnofriAndreaPG/agroBioData
Datasets for agriculture and applied biology. Referenced by this blog: https://www.statforbiology.com/
Data 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
Data apples_sh sensory attributes and preference scores
for 12 apple varieties.
https://r-forge.r-project.org/projects/cropcc/
Has nice herbicide dose response curves and germination data for mungbean, rice, wheat.
https://github.com/chgigot/epiphy
Contains 10 historical datasets for plant disease epidemics.
https://github.com/lian0090/FW/
Has phenotype data and marker data for 599 wheat lines in 4 environments.
https://doi.org/10.18637/jss.v089.i13
Data sbGeneal contains a soybean pedigree with 230
varieties.
Data gRbase::carcass: thickness of meat and fat on
slaughter pigs
https://github.com/OnofriAndreaPG/lmDiallel/tree/master/data
Data lmtest::ChickEgg time series of annual chicken and
egg production in the United States 1930-1983.
Data Atra and Recon contain measurements of
Atrazine in water samples.
Miguez. Non-linear models in agriculture. nlraa::sm =
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”.
https://paulhegedus.github.io/OFPE-Website/ https://github.com/paulhegedus/OFPEDATA/
https://github.com/AnabelleLaurent/onfant.dataset
pbkrtest::beets Yield and percent sugar in split-plot
experiment.
https://r-forge.r-project.org/projects/plantbreeding/
Data: fulldial
Data: linetester
Data: peanut - same as agridat::kang.peanutThis package has county-level data from the United States Census of Agriculture, along with a vignette to illustrate survey sampling analyses.
Data: 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:
data(DT_wheat) # CIMMYT wheat data
DT_wheat # 599 varieties, yield in 4 envts
GT_wheat # 599 varieties, 1279 markers coded -1,1Data: RICE
Data: FDdata taken from agridat::bond.diallel
Data:
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 matrixDataset 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: SoyNAM::ENV().
https://github.com/mdkrause/SoyURT
Large historical data of yield trials from Uniform Soybean Tests Northern States. Years 1989-2019, 63 locations, 4257 genotypes. The package also contains soils and weather data for the trial locations.
Note: The USDA published papers with results from: National Cotton Variety Tests, Uniform Soybean Tests Northern States, and Uniform Soybean Tests Southern States here: https://www.ars.usda.gov/southeast-area/stoneville-ms/crop-genetics-research/docs/
Has a vignette ‘The Problem of Spatial Autocorrelation: forty years
on’ that examines agriculture in Irish counties. See also the data
ade4::irishdata.
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
https://www.statforbiology.com/
Blog posts with example analyses.
https://github.com/Biometris/statgenGxE https://biometris.github.io/statgenGxE/
AMMI, FW, GGE stability analyses.
https://github.com/Biometris/statgenGWAS/ https://CRAN.R-project.org/package=statgenGWAS
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
https://github.com/Biometris/statgenSTA/ https://CRAN.R-project.org/package=statgenSTA
Analysis of phenotypic data from field experiments using SpATS, lme4, or asreml.
https://github.com/reyzaguirre/st4gi
https://www.ars.usda.gov/Main/docs.htm?docid=8419&page=4
https://data.cimmyt.org/dataverse/cimmytdatadvn
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://glten.org/
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)
https://data.cipotato.org/dataverse.xhtml
Case study 4 is a nice diallel example with sheep data. Available as agridat::ilri.sheep
http://bbi.irri.org/products
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.
https://www.miappe.org/
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
http://www.era.rothamsted.ac.uk/eradoc/collections.php
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
19869 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.oatsrstats4ag.org (no http included here because of firewall problems).
Datasets for mixed models, ancova, dose response curves, competition.
https://www.ideaconnection.com/syngenta-crop-challenge/
Annual Kaggle-style competition sponsored by Syngenta.
https://terraref.org/
Sensor observations, plant phenotypes, derived traits, genetic and genomic data. Beta version until Nov 2018.
https://www.nass.usda.gov https://quickstats.nass.usda.gov/
Group: Field Crops Commodity: Corn Category: Area Harvested, Yield
Data Item: Corn grain Acres Harvested, Yield Bu/Ac Domain: Total
Geography: State See agridat::nass.corn, nass.wheat,
etc.