dasilva.maize {agridat} | R Documentation

## Multi-environment trial of maize

### Description

Multi-environment trial of maize with 3 reps.

### Usage

    data("dasilva.maize")

### Format

A data frame with 1485 observations on the following 4 variables.

`env`

  environment

`rep`

  replicate block

`gen`

  genotype

`yield`

  yield (tons/hectare)

### Details

Each location had 3 blocks. Block numbers are unique across environments.

NOTE! The environment codes in the supplemental data file of da Silva 2015 do not match the environment codes of the paper. There appears to have been a shift in the environment number and one environment has a complete mismatch in mean yield. See the example below.

### Source

A Bayesian Shrinkage Approach for AMMI Models. Carlos Pereira da Silva, Luciano Antonio de Oliveira, Joel Jorge Nuvunga, Andrezza Kellen Alves Pamplona, Marcio Balestre. Plos One. Supplemental material. http://doi.org/10.1371/journal.pone.0131414

Used via Creative Commons Attribution License.

### References

J.J. Nuvunga, L.A. Oliveira, A.K.A. Pamplona, C.P. Silva, R.R. Lima and M. Balestre. Factor analysis using mixed models of multi-environment trials with different levels of unbalancing. Genet. Mol. Res. 14.

### Examples

    data(dasilva.maize)
    dat = dasilva.maize

    # Try to match Table 1 of da Silva 2015.
    # aggregate(yield ~ env, data=dat, FUN=mean)
    ##   env     yield
    ## 1  E1  6.211817  # match E2 in Table 1
    ## 2  E2  4.549104  # E3
    ## 3  E3  5.152254  # E4
    ## 4  E4  6.245904  # E5
    ## 5  E5  8.084609  # E6
    ## 6  E6 13.191890  # E7
    ## 7  E7  8.895721  # E8
    ## 8  E8  8.685448
    ## 9  E9  8.737089  # E9

    # Unable to match CVs in Table 2, but who knows what they used
    # for residual variance.
    # aggregate(yield ~ env, data=dat, FUN=function(x) 100*sd(x)/mean(x))

[Package agridat version 1.16 Index]