dasilva.maize {agridat} | R Documentation |
Multi-environment trial of maize with 3 reps.
data("dasilva.maize")
A data frame with 1485 observations on the following 4 variables.
env
environment
rep
replicate block
gen
genotype
yield
yield (tons/hectare)
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.
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.
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.
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))