Parents were crossed in a circular mating design, constituting several full-sib families. The data used here originates from a loblolly pine clonal study published by Resende _et al._ (2012). We will illustrate this here using an example of loblolly pine (_Pinus taeda_) in which some individuals, depending on the availability of pollen or flowers, were used in several artificial crosses as both male and female in the breeding program. 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 Г—Г—В 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). At the last meeting of the Australasian Association for the Advancement of Breeding and Genetics, ASReml was cited in 41% of the papers presented.Most breeding programs plan several controlled crosses between outstanding parents to detect favorable alleles in their offspring. In the last decade, 30 scientific articles have been published on ASREml. Rothamsted Research is regarded as the UKвЂ™s premier agriculture research institute, and credits ASReml with having a major impact on ensuring science quality within the organisation. Recently a new version of the package, ASReml 2.0, was released after three years of testing and development. It is now sold commercially вЂ“ a move Dr Cullis says has facilitated significant improvements in the system. вЂњToday, researchers routinely use ASReml to undertake meta-analyses of data in the agricultural, biological, medical and biological sciences.вЂќДЄSReml is a joint project of NSW DPI and Rothamsted Research and was freely available from 1996 to 2002. The resulting meta-analysis established and quantified interactions between acid tolerance, crop maturity and sowing date of wheat varieties in southern NSW.ДЄccording to Dr Cullis, вЂњthe strength of the ASReml project is that it can implement up-to-date and efficient statistical methodogies quickly and make them available to the user. вЂњIt means farmers can get the best information available about performance of varieties in their own location and make an informed decision.вЂќДeveloped in the early 1990s by Dr Cullis, leading DPI biometrician Dr Arthur Gilmour and Professor Robin Thompson from Rothamsted Research in the UK, ASReml arose from a need to analyse12 years of data from 1,071 wheat variety trials.

Research Leader for DPI Biometrics, Dr Brian Cullis, says the package helps farmers, breeders and crop variety evaluators obtain the most reliable predictions of genetic value for a range of crops grown in different environments. It is also used in the sugar industry, which says it has led to new varieties being released earlier and greater genetic gain, adding an estimated $20 million annually in value to the industry in Australia. In Australia, ASReml is used to collate and predict varietal performance from more than 500 grain variety trials conducted each year.

Some of the big puzzles in animal and plant breeding are being solved as a result of the efforts of NSW Department of Primary Industries (DPI) biometricians.ДЄ statistical package known as ASReml, first developed to analyse data from the crop variety evaluation program in southern NSW, is currently being used in 35 countries, by scientists from 235 institutions.Д¬lients include Monsanto, various international food breeding programs CSIRO Plant Industries and agricultural research and development organisations.

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