Figure 3 A coefficient-symmetric generation tree composed of the operators (pmb^{mathrm{CF}}C^{alpha}}) and (pmb^{mathrm{CF}}C^{beta}}).
In conclusion, we discuss future directions and how next generation tree viewers can be more efficient to handle the upcoming vast amounts of biological data.
Species of lower economic interests or long generation tree species, for which no breeding activities could be conducted, have been largely unexplored for their natural genetic variation.
Breeders have usually aimed to develop genotypes that are satisfactory for a wide range of conditions (i.e. showing low genotype × environment interaction in field trials); however, care must be taken when maximising growth rates with second- or third-breeding-generation trees in drought-prone sites.
After 750,000 generations, trees were saved and 250 of them with standard deviation of split frequency < 0.01 were used later for the calculation of posterior probability.
Four simultaneous Markov chains were run for 1,200,000 (Tub1) or 2,000,000 (Tub2) generations; trees were sampled every 100 generations, with 300,000 (Tub1) or 500,000 (Tub2) initial trees discarded as burn-in, based on visual inspection.
In total, four MCMC chains were run for 3 million generations, trees were sampled every 100th generation.
A consensus tree was constructed from 1575 trees and 525 burn-in through 210,000 generations (trees were sampled every 100 generations) and 0.008094 split frequency probability.
Bayesian analyses reached stationary after 100,000 generations; trees from the first 125,000 generations were discarded as burn-in, leaving 11,764 trees for phylogeny estimation.
