gauch.soy: Multi-environment trial of soybeans in New York, 1977 to 1988

In kwstat/agridat: Agricultural Datasets

Multi-environment trial of soybeans in New York, 1977 to 1988

Description

New York soybean yields, 1977 to 1988, for 7 genotypes, 55 environments (9 loc, 12 years), 2-3 reps.

Format

A data frame with 1454 observations on the following 4 variables.

yield

yield, kg/ha

rep

repeated measurement

gen

genotype, 7 levels

env

environment, 55 levels

year

year, 77-88

loc

location, 10 levels

Details

Soybean yields at 13 percent moisture for 7 genotypes in 55 environments with 4 replicates. Some environments had only 2 or 3 replicates. The experiment was an RCB design, but some plots were missing and there were many other soybean varieties in the experiment. The replications appear in random order and do _NOT_ define blocks. Environment names are a combination of the first letter of the location name and the last two digits of the year. The location codes are: A=Aurora, C=Chazy, D=Riverhead, E=Etna, G=Geneseo, I=Ithica, L=Lockport, N=Canton, R=Romulus, V=Valatie. Plots were 7.6 m long, four rows wide (middle two rows were harvested).

This data has been widely used (in various subsets) to promote the benefits of AMMI (Additive Main Effects Multiplicative Interactions) analyses.

The gen x env means of Table 1 (Zobel et al 1998) are least-squares means (personal communication).

Retrieved Sep 2011 from https://www.microcomputerpower.com/matmodel/matmodelmatmodel_sample_.html

Used with permission of Hugh Gauch.

Source

Zobel, RW and Wright, MJ and Gauch Jr, HG. 1998. Statistical analysis of a yield trial. Agronomy journal, 80, 388-393. https://doi.org/10.2134/agronj1988.00021962008000030002x

References

None

Examples

## Not run: 
  
  library(agridat)
  data(gauch.soy)
  dat <- gauch.soy

  ## dat <- transform(dat,
  ##                  year = substring(env, 2),
  ##                  loc = substring(env, 1, 1))

  # AMMI biplot
  libs(agricolae)
  # Figure 1 of Zobel et al 1988, means vs PC1 score
  dat2 <- droplevels(subset(dat, is.element(env, c("A77","C77","V77",
       "V78","A79","C79","G79","R79","V79","A80","C80","G80","L80","D80",
       "R80","V80","A81","C81","G81","L81","D81","R81","V81","A82","L82",
       "G82","V82","A83","I83","G83","A84","N84","C84","I84","G84"))))

  m2 <- with(dat2, AMMI(env, gen, rep, yield))
  bip <- m2$biplot
  with(bip, plot(yield, PC1, type='n', main="gauch.soy -- AMMI biplot"))
  with(bip, text(yield, PC1, rownames(bip),
                 col=ifelse(bip$type=="GEN", "darkgreen", "blue"),
                 cex=ifelse(bip$type=="GEN", 1.5, .75)))

## End(Not run)

kwstat/agridat documentation built on Nov. 2, 2024, 6:19 a.m.