This is done by _overlaying_ design matrices of the factors associated with male and female parents. In quantitative genetic analyses, monoecious species present a particular challenge, as a given parent can contribute to the estimation of its breeding value (or GCA) as both a male and a female, something that needs to be taken into consideration when a statistical model is fitted. Some examples of monoecious species are corn, squash, banana, and many conifers, particularly those of the genus _Pinus_. In contrast, dioecious species have distinctive male and female plants. However, several commercial plant species are monoecious, which means that a given genotype will bear both male and female flowers. In most cases it is easy to assign the sex of a given individual. In many plant breeding programs, a parent is considered in several crosses. These BLUPs, which are the _general combining ability_ (GCA), or 1/2 of the _breeding value_ (BV, with BV = 2 ×× GCA) of each parent, are then used to select the best parents for future crosses or operational deployment. The progeny are later evaluated in a field experiment, and this information is used to assess the genetic worth of the parents by fitting parental linear mixed models (LMMs) and obtaining best linear unbiased predictions (BLUPs). Most breeding programs plan several controlled crosses between outstanding parents to detect favorable alleles in their offspring.
