--- title: "Additional sources of agricultural data" author: "Kevin Wright" output: rmarkdown::html_vignette: md_extensions: -autolink_bare_uris vignette: > %\VignetteIndexEntry{Additional sources of agricultural data} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- # 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.