# Additional sources of agricultural data

#### Kevin Wright

# Other

## Rothamsted Library

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

# Books

### “Die Landwirtschaftlichen Versuchs-Stations”

https://catalog.hathitrust.org/Record/000549685

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

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

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.maize

### Gemechu, “Application of Spatial Mixed Model in Agricultural Field Experiment”

Dibaba 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”

### 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”.

https://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.

### 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.

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.serpentine

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

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

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

https://archive.org/details/investigationbye0000heat

    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: 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

Second edition: `http://krishikosh.egranth.ac.in/handle/1/2034118` (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”

https://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

### 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”

https://www.wiley.com/legacy/wileychi/chemometrics/datasets.html

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”

https://books.google.com/books?id=CaFZPbCllrMC&pg=PA323

    323 Turnip spacing data - agridat::mead.turnip

### Leonard C. Onyiah (2008).

“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

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

https://archive.org/details/secondeditionsta001000mbp

    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 https://archive.org/details/dli.scoerat.949statisticalmethodsforagriculturalworkers/page/138/mode/2up

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

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.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”

https://psfaculty.plantsciences.ucdavis.edu/plant/

### 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”

https://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

### 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. https://water.usgs.gov/nawqa/pnsp/pubs/circ1291/supporting_info.php

# Data Repositories

### Ag Data Commons

https://data.nal.usda.gov/about-ag-data-commons https://data.nal.usda.gov/search/type/dataset

### CyVerse Data Commons

https://datacommons.cyverse.org/ https://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated

### DataDryad

### Harvard Dataverse

https://dataverse.harvard.edu/

IRRI Rice Research includes plot-level data for long term rice experiments. https://dataverse.harvard.edu/dataverse/RiceResearch

### Kellogg Biological Station Long-Term Research

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.

### Nature Scientific Data

https://www.nature.com/sdata/

### Open Data Journal for Agricultural Research

https://library.wur.nl/ojs/index.php/odjar/

### Plant Genomics and Phenomics Research Data Repository

### Wolfram Data Repository

https://datarepository.wolframcloud.com/

# Journals - Bulletins

### Iowa State Agricultural Research Bulletins

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.

# Papers

### Bakare et al

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

### Chaves 2023 et al

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.

### 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.

### Coelho 2021 et al

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.

### 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://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

### 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.

### 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.

### Oakey, Cullis, Thompson 2016

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

### Peixoto, Marco Antonio et al (2020)

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.

### Perez-Valencia (2022).

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.

### 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).

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

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.

### Tanaka, Takashi X. T.

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.

### 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

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. 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.

### Schmitz Carley et al (2018)

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.

### 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.

### Volpato et al (2024)

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.

### Xavier, Alencar et al..

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.

### 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: https://cran.r-project.org/web/views/Agriculture.html

### AgML

https://github.com/Project-AgML/AgML

Datasets for agricultural machine learning such as image classification, semantic segmentation, object detection, etc.

### agriCensData

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”.

### agriTutorial

https://myaseen208.github.io/agriTutorial/

Five datasets used to illustrate analyses.

### agricolae

Has assorted data and functions for analysis of agricultural data.

### agroBioData

https://github.com/OnofriAndreaPG/agroBioData

Datasets for agriculture and applied biology. Referenced by this blog: https://www.statforbiology.com/

### 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.

### BSagri

Safety assessment in agriculture trials

### ClustVarLV

Data `apples_sh` sensory attributes and preference scores for 12 apple varieties.

### cropcc - Climate change on crops

https://r-forge.r-project.org/projects/cropcc/

### drc - Dose response curves

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

### epiphy

https://github.com/chgigot/epiphy

Contains 10 historical datasets for plant disease epidemics.

### FW - Finlay-Wilkinson regression

https://github.com/lian0090/FW/

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

### ggenealogy

https://doi.org/10.18637/jss.v089.i13

Data `sbGeneal` contains a soybean pedigree with 230 varieties.

### gRbase

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

### lmDiallel

https://github.com/OnofriAndreaPG/lmDiallel/tree/master/data

### lmtest

Data `lmtest::ChickEgg` time series of annual chicken and egg production in the United States 1930-1983.

### NADA

Data `Atra` and `Recon` contain measurements of Atrazine in water samples.

### nlraa

Miguez. Non-linear models in agriculture. `nlraa::sm` = `agridat::miguez.biomass` Vignettes and functions for working with (non)linear mixed models

### nlme

`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

https://paulhegedus.github.io/OFPE-Website/ https://github.com/paulhegedus/OFPEDATA/

### onfant.dataset

https://github.com/AnabelleLaurent/onfant.dataset

### pbkrtest

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

### plantbreeding

https://r-forge.r-project.org/projects/plantbreeding/

    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.

### SemiPar

Data: `SemiPar::onions` is same as agridat::ratkowski.onions

### soilDB

https://ncss-tech.github.io/AQP/soilDB/soilDB-Intro.html 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:

    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:

    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

### 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

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/

### spdep

Has a vignette ‘The Problem of Spatial Autocorrelation: forty years on’ that examines agriculture in Irish counties. See also the data `ade4::irishdata`.

### spuRs

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

### StatForBiology

https://www.statforbiology.com/

Blog posts with example analyses.

### Biometris - statgenGxE

https://github.com/Biometris/statgenGxE https://biometris.github.io/statgenGxE/

AMMI, FW, GGE stability analyses.

### Biometris - statgenGWAS

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

### Biometris - statgenSTA

https://github.com/Biometris/statgenSTA/ https://CRAN.R-project.org/package=statgenSTA

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

### st4gi - Stat for genetic improvement

https://github.com/reyzaguirre/st4gi

# Web sites

### ARS oat trials

https://www.ars.usda.gov/Main/docs.htm?docid=8419&page=4

### CIMMYT Research Data

https://data.cimmyt.org/dataverse/cimmytdatadvn

### Gardian Platform for Big Data in Agriculture

### Grain genes

1. 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.

2. https://wheat.pw.usda.gov/ggpages/SxM/ . This data is agridat::steptoe.morex.

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

https://glten.org/

### Ideals

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)

### International Potato Center

https://data.cipotato.org/dataverse.xhtml

### 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

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.

### MIAPPE Minimum Information About Plant Phenotyping Experiments

https://www.miappe.org/

Very limited data.

### Rothamsted Electronic Archive

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

### Rothamsted Documents Archive

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

    1986

### 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

rstats4ag.org (no http included here because of firewall problems).

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

### Syngenta Crop Challenge

https://www.ideaconnection.com/syngenta-crop-challenge/

Annual Kaggle-style competition sponsored by Syngenta.

### Terra-Ref

https://terraref.org/

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

### USDA National Agricultural Statistics Service

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.