This package contains datasets from publications relating to agriculture, including field crops, tree crops, animal studies, and a few others.
If you use these data, please cite both the agridat package and the original source of the data.
Abbreviations in the 'other' column include: xy = coordinates, pls = partial least squares, rsm = response surface methodology, row-col = row-column design, ts = time series,
Uniformity trials with a single genotype
Yield monitor
name | reps | years | trt | other | model |
gartner.corn | xy,ym | ||||
lasrosas.corn | 3 | 2 | 6 | xy,ym | lm |
Animals
name | gen | years | trt | other | model | becker.chicken | 5,12 |
heritability | lmer | crampton.pig | 5 | ||||
2 cov | lm | brandt.switchback | 10 | 2 | aov | ||
depalluel.sheep | 4 | 4 | latin | diggle.cow | |||
4 | ts | foulley.calving | |||||
ordinal | polr | goulden.eggs | controlchart | ||||
harvey.lsmeans | 3,3 | lm | harville.lamb | 5 | |||
lmer | henderson.milkfat | ||||||
nls,lm,glm,gam | holland.arthropods | 5 | |||||
ilri.sheep | 4 | 6 | diallel | lmer, asreml | kenward.cattle | ||
2 | asreml | lucas.switchback | 12 | 3 | |||
aov | mead.lamb | 3 | 3 | glm | |||
patterson.switchback | 12 | 4 | aov | urquhart.feedlot | 11 | ||
3 | lm | zuidhof.broiler | |||||
ts | name | gen | years | trt | other | model |
Trees
name | gen | loc | reps | years | trt | other | model |
box.cork | repeated | radial, asreml | |||||
harris.wateruse | 2 | 2 | repeated | asreml,lme | |||
hanover.whitepine | 7*4 | 4 | heritability | lmer | |||
lavoranti.eucalyptus | 70 | 7 | svd | ||||
pearce.apple | 4 | 6 | cov | lm,lmer | |||
williams.trees | 37 | 6 | 2 |
Field and horticulture crops
name | gen | loc | reps | years | trt | other | model |
36 | 9 | 2 | 5 | nonnormal | gnm,ammi | ||
adugna.sorghum | 28 | 13 | 5 | ||||
aastveit.barley | 15 | 9 | yr*gen~yr*trt | pls | |||
allcroft.lodging | 32 | 7 | percent | tobit | |||
archbold.apple | 2 | 5 | 24 | split-split | lmer | ||
ars.earlywhitecorn96 | 60 | 9 | 6 traits | dotplot | |||
australia.soybean | 58 | 4 | 2 | 4-way, 6 traits | biplot | ||
battese.survey | 12 | 1-5 | 2 | lmer | |||
beall.webworms | 15 | 2,2 | xy | glm poisson | |||
beaven.barley | 8 | 20 | xy | ||||
besag.bayesian | 75 | 3 | xy | asreml | |||
besag.beans | 6 | 4*6 | xy | lm,competition | |||
besag.elbatan | 50 | 3 | xy | lm, gam | |||
besag.endive | xy,binary | autologistic | |||||
besag.met | 64 | 6 | 3 | xy, incblock | asreml, lme | ||
besag.triticale | 3 | 2,2,3 | xy | lm, asreml | |||
bliss.borers | 4 | glm | |||||
blackman.wheat | 12 | 7 | 2 | biplot | |||
bond.diallel | 6*6 | 9 | diallel | ||||
bridges.cucumber | 4 | 2 | 4 | xy, latin, hetero | asreml | ||
brandle.rape | 5 | 9 | 4 | 3 | lmer | ||
burgueno.alpha | 15 | 3 | xy, alpha | asreml,lmer | |||
burgueno.rowcol | 64 | 2 | xy, row-col | asreml,lmer | |||
burgueno.unreplicated | 280 | xy | asreml | ||||
butron.maize | 49 | 3 | 2 | diallel,pedigree | biplot,asreml | ||
caribbean.maize | 17 | 4 | 3 | ||||
carmer.density | 8 | 4 | nls,nlme | ||||
carlson.germination | 15 | 8 | glm | ||||
chinloy.fractionalfactorial | 9 | 1/3 3^5 | xy | aov | |||
christidis.competition | 9 | 5 | xy | ||||
cochran.beets | 6 | 7 | |||||
cochran.bib | 13 | 13 | bib | aov, lme | |||
cochran.crd | 7 | xy, crd | aov | ||||
cochran.factorial | 2 | 4^2 | factorial | aov | |||
cochran.latin | 6 | 6 | xy, latin | aov | |||
cochran.lattice | 5 | 16 | xy, latin | lmer | |||
cochran.wireworms | 5 | 5 | xy, latin | glm | |||
cochran.eelworms | 4 | 5 | xy | aov | |||
connolly.potato | 20 | 4 | xy, competition | lm | |||
cornelius.maize | 9 | 20 | svd | ||||
corsten.interaction | 20 | 7 | |||||
cramer.cucumber | 8 | pathcoef | |||||
crossa.wheat | 18 | 25 | ammi | ||||
crowder.seeds | 2 | 21 | 2 | glm,jags | |||
cox.stripsplit | 4 | 3,4,2 | split-block | aov | |||
cullis.earlygen | 532 | xy | asreml | ||||
dasilva.maize | 55 | 9 | 3 | ||||
darwin.maize | 12 | 2 | t.test | ||||
denis.missing | 5 | 26 | lme | ||||
denis.ryegrass | 21 | 7 | aov | ||||
digby.jointregression | 10 | 17 | 4 | lm | |||
durban.competition | 36 | 3 | xy, competition | lm | |||
durban.rowcol | 272 | 2 | xy | lm, gam, asreml | |||
durban.splitplot | 70 | 4 | 2 | xy | lm, gam, asreml | ||
eden.potato | 4 | 3 | 4-12 | xy, rcb, latin | aov | ||
eden.nonnormal | 4 | 4 | aov | ||||
engelstad.nitro | 2 | 5 | 6 | rsm1 | nls quadratic plateau | ||
fan.stability | 13 | 10 | 2 | 3-way | stability | ||
federer.diagcheck | 122 | xy | lm, lmer, asreml | ||||
federer.tobacco | 8 | 7 | xy | lm | |||
fisher.barley | 5 | 6 | 2 | ||||
fisher.latin | 5 | 5 | xy,latin | lm | |||
fox.wheat | 22 | 14 | lm | ||||
gathmann.bt | 2 | 8 | tost | ||||
gauch.soy | 7 | 7 | 4 | 12 | ammi | ||
giles.wheat | 19 | 13 | 2 traits | gnm | |||
gilmour.serpentine | 108 | 3 | xy, serpentine | asreml | |||
gilmour.slatehall | 25 | 6 | xy | asreml | |||
gomez.fractionalfactorial | 2 | 1/2 2^6 | xy | lm | |||
gomez.groupsplit | 45 | 3 | 2 | xy, 3 gen groups | aov | ||
gomez.heteroskedastic | 35 | 3 | hetero | ||||
gomez.multilocsplitplot | 2 | 3 | 3 | rsm1,nitro | aov, lmer | ||
gomez.nitrogen | 4 | 8 | aov, contrasts | ||||
gomez.nonnormal1 | 4 | 9 | log10 | lm | |||
gomez.nonnormal2 | 14 | 3 | sqrt | lm | |||
gomez.nonnormal3 | 12 | 3 | arcsin | lm | |||
gomez.seedrate | 4 | 6 | rate | lm | |||
gomez.splitplot.subsample | 3 | 8,4 | subsample | aov | |||
gomez.splitsplit | 3 | 3 | xy, nitro, mgmt | aov, lmer | |||
gomez.stripplot | 6 | 3 | xy, nitro | aov | |||
gomez.stripsplitplot | 6 | 3 | xy, nitro | aov | |||
gomez.wetdry | 3 | 2 | 5 | nitro | lmer | ||
gotway.hessianfly | 16 | 4 | xy | lmer | |||
goulden.latin | 5 | 5 | xy, latin | lm | |||
goulden.splitsplit | 2 | 4 | 2*5 | xy, split | aov | ||
graybill.heteroskedastic | 4 | 13 | hetero | ||||
gregory.cotton | 2 | 4*3*2*2 | polar | ||||
gumpertz.pepper | xy | glm | |||||
hanks.sprinkler | 3 | 3 | xy | asreml | |||
hayman.tobacco | 8 | 2 | 2 | diallel | asreml | ||
hazell.vegetables | 4 | 6 | linprog | ||||
heady.fertilizer | 2 | 9*9 | rsm2 | lm,rgl | |||
hernandez.nitrogen | 5 | 4 | rsm1 | lm, nls | |||
hildebrand.systems | 14 | 4 | asreml | ||||
holshouser.splitstrip | 4 | 4 | 2*4 | rsm1,pop | lmer | ||
huehn.wheat | 20 | 10 | huehn | ||||
hughes.grapes | 3 | 6 | binomial | lmer, aod, glmm | |||
hunter.corn | 12 | 3 | 1 | rsm1 | xyplot | ||
ivins.herbs | 13 | 6 | 2 traits | lm, friedman | |||
jansen.apple | 3 | 4 | 3 | binomial | glmer | ||
jansen.carrot | 16 | 3 | 2 | binomial | glmer | ||
jansen.strawberry | 12 | 4 | ordinal | mosaicplot | |||
jenkyn.mildew | 9 | 4 | lm | ||||
john.alpha | 24 | 3 | alpha | lm, lmer | |||
johnson.blight | 2 | logistic | |||||
kang.maize | 17 | 4 | 3 | 2,4 | |||
kang.peanut | 10 | 15 | 4 | gge | |||
karcher.turfgrass | 4 | 2,4 | ordinal | polr | |||
keen.potatodamage | 6 | 4 | 2,3,8 | ordinal | mosaicplot | ||
kempton.competition | 36 | 3 | xy, competition | lme AR1 | |||
kempton.rowcol | 35 | 2 | xy, row-col | lmer | |||
kempton.slatehall | 25 | 6 | xy | asreml, lmer | |||
lee.potatoblight | 337 | 4 | 11 | xy, ordinal, repeated | |||
lehner.soybeanmold | 35 | 4 | 11 | metafor, lmer | |||
lillemo.wheat | 24 | 13 | 7 | medpolish, huehn | |||
lin.superiority | 33 | 12 | superiority | ||||
lin.unbalanced | 33 | 18 | superiority | ||||
little.splitblock | 4 | 4,5 | xy, split-block | aov | |||
lonnquist.maize | 11 | diallel | asreml | ||||
lyons.wheat | 12 | 4 | |||||
lu.stability | 5 | 6 | huehn | ||||
mcconway.turnip | 2 | 4 | 2,4 | hetero | aov, lme | ||
mcleod.barley | 8 | 6 | aggregate | ||||
mead.cauliflower | 2 | poisson | glm | ||||
mead.cowpeamaize | 3,2 | 3 | 4 | intercrop | |||
mead.germination | 4 | 4,4 | binomial | glm | |||
mead.strawberry | 8 | 4 | |||||
mead.turnip | 3 | 5,4 | aov | ||||
minnesota.barley.weather | 6 | 10 | |||||
minnesota.barley.yield | 22 | 6 | 10 | dotplot | |||
omer.sorghum | 18 | 2 | 4 | 3 | jags | ||
onofri.winterwheat | 8 | 3 | 7 | ammi | |||
ortiz.tomato | 15 | 18 | 16 | env*gen~env*cov | pls | ||
pacheco.soybean | 18 | 11 | ammi | ||||
perry.springwheat | 28 | 5 | 4 | gain | lm,lmer,asreml | ||
piepho.cocksfoot | 25 | 7 | lmer | ||||
ratkowsky.onions | lm | ||||||
reid.grasses | 4 | 3 | 21 | nlme SSfpl | |||
ridout.appleshoots | 30 | 2,4 | zip | zeroinfl | |||
rothamsted.brussels | 4 | 6 | |||||
ryder.groundnut | 5 | 4 | xy, rcb | lm | |||
salmon.bunt | 10 | 2 | 20 | betareg | |||
senshu.rice | 40 | lm,Fieller | |||||
shafii.rapeseed | 6 | 14 | 3 | 3 | biplot | ||
silva.cotton | 5 | 5 | 5 traits | glm,poisson | |||
sinclair.clover | 5,5 | rsm2,mitzerlich | nls,rgl | ||||
snedecor.asparagus | 4 | 4 | 4 | split-plot, antedependence | |||
snijders.fusarium | 17 | 3 | 4 | percent | glm/gnm,gammi | ||
steptoe.morex.pheno | 152 | 16 | 10 traits | ||||
steptoe.morex.geno | 150 | 223 markers, qtl | |||||
streibig.competition | 2 | 3 | glm | ||||
stroup.nin | 56 | 4 | xy | asreml | |||
stroup.splitplot | 4 | asreml, MCMCglmm | |||||
student.barley | 2 | 51 | 6 | lmer | |||
tai.potato | 8 | 3 | 2 | tai | |||
talbot.potato | 9 | 12 | gen*env~gen*trt | pls | |||
theobald.barley | 3 | 5 | 2 | 5 | rsm1 | ||
theobald.covariate | 10 | 7 | 5 | cov | jags | ||
thompson.cornsoy | 5 | 33 | repeated measures | aov | |||
vaneeuwijk.fusarium | 20 | 4 | 7 | 3-way | aov | ||
vaneeuwijk.drymatter | 6 | 4 | 7 | 3-way | aov,lmer | ||
vaneeuwijk.nematodes | 11 | nonnormal,poisson | gnm, gammi | ||||
vargas.wheat1 | 7 | 6 | gen*yr~gen*trt, yr*gen~yr*cov | pls | |||
vargas.wheat2 | 8 | 7 | env*gen~env*cov | pls | |||
vargas.txe | 10 | 24 | yr*trt~yr*cov | pls | |||
verbyla.lupin | 9 | 8 | 2-3 | 2 | rsm1, xy, density | asreml | |
vold.longterm | 19 | 4 | rsm1 | nls,nlme | |||
vsn.lupin3 | 336 | 3 | xy | asreml | |||
wedderburn.barley | 10 | 9 | percent | glm/gnm | |||
weiss.incblock | 31 | 6 | xy,incblock | asreml | |||
weiss.lattice | 49 | 4 | xy,lattice | lm,asreml | |||
welch.bermudagrass | 4,4,4 | rsm3, factorial | lm, jags | ||||
wheatley.carrot | 3 | 11 | glm-binomial | ||||
yan.winterwheat | 18 | 9 | gge,biplot | ||||
yang.barley | 6 | 18 | biplot | ||||
yates.missing | 10 | 3^2 | factorial | lm, pca | |||
yates.oats | 3 | 6 | xy,split,nitro | lmer |
Time series
name | years | trt | other | model |
byers.apple | lme | |||
broadbalk.wheat | 74 | 17 | ||
hessling.argentina | 30 | temp,precip | ||
kreusler.maize | 4 | 5 | plant growth | |
lambert.soiltemp | 1 | 7 | ||
nass.barley | 146 | |||
nass.corn | 146 | |||
nass.cotton | 146 | |||
nass.hay | 104 | |||
nass.sorghum | 93 | |||
nass.wheat | 146 | |||
nass.rice | 117 | |||
nass.soybean | 88 | |||
walsh.cottonprice | 34 | cor |
Other
name | model |
cate.potassium | cate-nelson |
cleveland.soil | loess 2D |
harrison.priors | nls, prior |
nebraska.farmincome | choropleth |
pearl.kernels | chisq |
stirret.borers | lm, 4 trt |
turner.herbicide | glm, 4 trt |
usgs.herbicides | non-detect |
wallace.iowaland | lm, choropleth |
waynick.soil | spatial, nitro/carbon |
Comments of the package purpose
Box (1957) said, "I had hoped that we had seen the end of the obscene tribal habit practiced by statisticians of continually exhuming and massaging dead data sets after their purpose in life has long since been forgotten and there was no possibility of doing anything useful as a result of this treatment."
Massaging these dead data sets will not lead to any of the genetics being released for commercial use. The value of this package is: 1. Validating published analyses. 2. Providing data for testing new analysis methods. 3. Illustrating (and validating) the use of R.
White and van Evert (2008) present some guidelines for publication of data.
Some of the examples use the asreml
package since it is the
_only_ R tool for fitting mixed models with complex variance structures
to large datasets, and the best option for modelling AR1xAR1 residual
variance structures. Commercial use of asreml
requires a
license: http://www.vsni.co.uk/downloads/asreml.
Comments on the package structure
A large portion of these datasets appear in electronic form here for the first time.
A tremendous amount of effort has been given to the curating process of identifying datasets, extracting the data from source materials, checking data values, and documenting the data. In effect, to make the data somewhat 'computable' (Wolfram 2017).
The original sources for these data use several different words to refer
to genotypes including accession, breed, cultivar,
genotype, hybrid, line, progeny,
stock, type, and variety. For consistency, these
datasets mostly use gen
(genotype).
Also for consistency row
and col
are usually used for the
field coordinates.
In dataframes, 'block', 'rep', and similar terms are almost always coded like B1, B2, B3 instead of 1, 2, 3. This causes R to treat the data as a factor instead of a numeric covariate (which is a good thing).
Almost all of the data are presented as 'tidy' dataframes with 'observations' in rows and 'variables' in columns.
Although using data()
is not necessary to access the data files,
the example sections do include the use of data()
because
devtools::run_examples()
needs it.
Please report any bugs to the package author or at the package github site.
G. E. P. Box (1957), Integration of Techniques in Process Development, Transactions of the American Society for Quality Control.
J. White and Frits van Evert. (2008). Publishing Agronomic Data. Agron J. 100, 1396-1400. http://doi.org/10.2134/agronj2008.0080F
Stephen Wolfram (2017). Launching the Wolfram Data Repository: Data Publishing that Really Works. http://blog.stephenwolfram.com/2017/04/launching-the-wolfram-data-repository-data-publishing-that-really-works/