Additional sources of agricultural data

Kevin Wright


Rothamsted Library

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 


“Die Landwirtschaftlichen Versuchs-Stations”

Full view of research station reports 1859-1920. In German.

D. F. Andrews and A. M. Herzberg (1985). “Data”.

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

D. Bayisa (2010). “Application of Spatial Mixed Model in Agricultural Field Experiment”.

Master thesis. Department of Statistics, Addis Ababa University. One dataset from wheat, RCB, with field coordinates.

M. N. Das & Narayan C. Giri (1987). “Design and Analysis of Experiments”.

 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

Peter Diggle, Patrick Heagerty, Kung-Yee Liang, Scott Zeger. “Analysis of Longitudinal Data”.

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.

Federer, Walt (1955). “Experimental Design”.

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

Finney 1972. “An Introduction to Statistical Science in Agriculture”.

Small, mostly simulated data.

Galwey, N.W. (2014). “Introduction to Mixed Modelling”, 2nd ed.

 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

Grover, Deepak & Lajpat Rai. “Experimental Designing And Data Analysis In Agriculture And Biology”.

Agrotech Publishing Academy, 2010.

43 Percent insect survival in 12 rice varieties, 3 reps
50 CRD
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

O.V.S. Heath (1970). “Investigation by experiment”.

23 uniformity trial of radish - agridat::heath.raddish.uniformity
50 uniformity trial of cabbage - agridat::heath.cabbage.uniformity

Kwanchai A. Gomez & Gomez (1984). “Statistical Procedures for Agricultural Research”.

Extensive collection of datasets from rice experiments. Many added to agridat.

Cyril H. Goulden (1939), “Methods of Statistical Analysis”.

First edition:

 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

Second edition: (broken)

216 Latin square - agridat::goulden.latin 
423 Control chart with egg weights - agridat::goulden.eggs

Harry Love (1936). “Applications of Statistical Methods to Agricultural Research”.

379 MET 4 year, 2 field, 5 block, 5 gen

Kang, Manjit (2003). “Handbook of Formulas and Software for Plant Geneticists and Breeders”

Kuehl, Robert. “Design of Experiments”, 2nd ed.

357 alfalfa quadruple lattice
358 alpha design
488 split-plot sorghum hybrid,density
516 alfalfa rcb, two-year
521 crossover design cattle feedstuff

Erwin LeClerg, Warren Leonard, Andrew Clark (1962). “Field Plot Technique”

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

Thomas M Little & F. Jackson Hills (1978). “Agricultural Experimentation”.

 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

Harald Martens & Magni Martens. “Multivariate Analysis of Quality”

The ‘NIR’ data has NIR spectra measurements of wheat for the purpose of understanding protein quality.

Roger Mead, Robert N. Curnow, Anne M. Hasted (2002). “Statistical Methods in Agriculture and Experimental Biology”, 3rd ed.

 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)

Roger Mead (1988). “The Design of Experiments”

323 Turnip spacing data - agridat::mead.turnip

Leonard C. Onyiah (2008).

“Design and Analysis of Experiments: Classical and Regression Approaches with SAS”.

334 Two examples of 5x5 Graeco-Latin squares in cassava and maize

Bernard Ostle (1963). “Statistics in Research”, 2nd ed.

455 2 factors, 1 covariate - agridat::woodman.pig
458 1 factor, 2 covariates - agridat::crampton.pig

V. G. Panse and P. V. Sukhatme (1957). “Statistical Methods for Agricultural Workers”.

  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

D. D. Paterson (1939). “Statistical Technique in Agricultural Research”.

 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

Roger Petersen, “Agricultural Field Experiments”

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

Richard Plant, “Spatial Data Analysis in Ecology and Agriculture using R”

Arthur Asquith Rayner (1969). “A First Course In Biometry For Agriculture Students”.

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

F.S.F. Shaw (1936). “A Handbook of Statistics For Use in Plant Breeding and Agricultural Problems”

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

G. W. Snedecor & W. G. Cochran. “Statistical Methods”.

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

Robert G. D. Steel & James Hiram Torrie. “Principles and Procedures of Statistics”, 2nd ed.

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

Oliver Schabenberger and Francis J. Pierce. “Contemporary Statistical Models for the Plant and Soil Sciences”.

Many datasets. Some added to agridat.

S. J. Welham et al. (2015). “Statistical Methods In Biology”.

The online-supplements contain many small datasets for the examples and exercises.

Pesticides in the Nation’s Streams and Ground Water, 1992-2001

Extensive data for detection of pesticides in water samples. See Appendix 5 and Appendix 6 of the supporting info.

Data Repositories

Ag Data Commons

CyVerse Data Commons


Harvard Dataverse

IRRI Rice Research includes plot-level data for long term rice experiments.

Kellogg Biological Station Long-Term Research

KBS037:Precision Agriculture Yield Monitoring in Row Crop Agriculture Yield monitor data across several years and crops. Un-friendly license.

Nature Scientific Data

Open Data Journal for Agricultural Research

Plant Genomics and Phenomics Research Data Repository

Wolfram Data Repository

Journals - Bulletins

Iowa State Agricultural Research Bulletins

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.


Bakare et al

Exploring genotype by environment interaction on cassava yield and yield related traits using classical statistical methods

36 gen, 20 env, 3 rep. Analysis and data here:

Chaves 2023 et al

Analysis of multi-harvest data through mixed models: an application in Theobroma grandiflorum breeding 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.

Cleveland, M.A. and John M. Hickey, Selma Forni (2012).

A Common Dataset for Genomic Analysis of Livestock Populations. G3, 2, 429-435.

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.

Coelho 2021 et al

Accounting for spatial trends in multi-environment diallel analysis in maize breeding

78 hybrids in a diallel, 4 environments, 3 reps. Compared spatial and non-spatial analyses.

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.

The data are in ClustVarLV::apples_sh$pref and ClustVarLV::apples_sh$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.

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,

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

Supplemental information contains phenotypic data and markers and environmental covariates for PLS analysis.

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.

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.

Has a large haplotype dataset (83 MB) and two-year phenotype data with multiple traits.

Oakey, Cullis, Thompson 2016

Genomic Selection in Multi-environment Crop Trials 648 genotypes planted in pots yr 1, 856 lines yr 2, 639 common to both years. 7864 SNP markerks

Peixoto, Marco Antonio et al (2020)

Random regression for modeling yield genetic trajectories in Jatropha curcas breeding.

Repeated measurements over six years. Data in supplemental Word doc.

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.;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).

Snedecor, George and E. S. Haber (1946).

Statistical Methods For an Incomplete Experiment on a Perennial Crop. Biometrics Bulletin, 2, 61-67.

Harvest of asparagus over 10 years, three cutting dates per year, 6 blocks.

Tanaka, Takashi X. T.

Assessment of design and analysis frameworks for on-farm experimentation through a simulation study of wheat yield in Japan.

Yield-monitor data for 3 fields.

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.

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.

Uses 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.

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.

Large phenotypic dataset with 691 wheat lines, 33 years, 670 environments, 3-4 reps, 120000 datapoints. No genotypic data is included.

Schmitz Carley et al (2018)

Genetic Covariance of Environments in the Potato National Chip Processing Trial

Supp 2 contains genomic data, but there is no easy way to find the phenotypic data.

van der Voet et al. (2017).

Equivalence testing using existing reference data: An example with genetically modified and conventional crops in animal feeding studies.

The full datasets for the GRACE studies A-E are available here: CC license.

Xavier, Alencar et al..

Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population.

Data are in the SoyNAM and NAM packages.

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.

R packages on CRAN, Github, etc.

See also:


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:

aml - Adaptive Mixed LASSO

Data aml::wheat genetic and phenotypic data for wheat. Modest size.

BGLR - Bayesian Generalized Linear Regression.

Has an A matrix (but no pedigree) for 499 genotypes at 4 locations.

BLR - Bayesian Linear Regression.

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.

cropcc - Climate change on crops

drc - Dose response curves

Has nice herbicide dose response curves and germination data for mungbean, rice, wheat.


Contains 10 historical datasets for plant disease epidemics.

FW - Finlay-Wilkinson regression

Has phenotype data and marker data for 599 wheat lines in 4 environments.


Data sbGeneal contains a soybean pedigree with 230 varieties.


Data gRbase::carcass: thickness of meat and fat on slaughter pigs



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”.

OFPE - On-Farm Precision Experiments



pbkrtest::beets Yield and percent sugar in split-plot experiment.


Data: fulldial
Data: linetester
Data: peanut - same as agridat::kang.peanut

SDaA - Survey Data and Analysis

This 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

soilDB Soil database interface.

sommer - Solving mixed model equations in R

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: RICE

Data: FDdata taken from agridat::bond.diallel


data(DT_technow) # From
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

SoyNAM - Soybean nested association mapping

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: SoyNAM::ENV().

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 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:


Blog posts with example analyses.

Biometris - statgenGxE

AMMI, FW, GGE stability analyses.

Biometris - 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: And publication: Millet 2016, Genome-Wide Analysis of Yield in Europe: Allelic Effects Vary with Drought and Heat Scenarios,

Biometris - statgenSTA

Analysis of phenotypic data from field experiments using SpATS, lme4, or asreml.

st4gi - Stat for genetic improvement

Web sites

ARS oat trials

CIMMYT Research Data

Gardian Platform for Big Data in Agriculture

Grain genes

  1. 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.

  2. . This data is agridat::steptoe.morex.

GLTEN - A network of Long-Term trials around the world

Ideals 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)

International Potato Center

ILRI International Livestock Research Institute

Case study 4 is a nice diallel example with sheep data. Available as agridat::ilri.sheep

IRRI Biometrics and Breeding Informatics

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.

MIAPPE Minimum Information About Plant Phenotyping Experiments

Very limited data.

Rothamsted Electronic Archive Data from Broadbalk and other long-term experiments.

Github draft data:

Rothamsted Documents Archive

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
1926-1927 agridat::sawyer.multi.uniformity 
1927-1928 agridat::sawyer.multi.uniformity
1931,143 agridat::yates.oats
1934,215-222 Sugar beet multi-environment trial with 3^3 fertilizer 
  treatments at each site Roots, SugarPercent, SugarWeight, PlantNumber, Tops, Purity.
1936,241 Similar to the 1934 experiment, but only gives the main effects, 
  not the actual data.


Yates (1937), The Design and analysis of factorial experiments

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

Statistical Analysis of Agricultural Experiments with R (no http included here because of firewall problems).

Datasets for mixed models, ancova, dose response curves, competition.

Syngenta Crop Challenge

Annual Kaggle-style competition sponsored by Syngenta.


Sensor observations, plant phenotypes, derived traits, genetic and genomic data. Beta version until Nov 2018.

USDA National Agricultural Statistics Service

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.