Comparative Analysis about Plot Average Method and Transformation Analysis Method in Forest Progeny Tests

In order to evaluate the analysis effect of plot average method in the nonequilibrium test data of trees, the advantages and disadvantages of plot average method were compared and evaluated by using Monte Carlo simulation data and transformation analysis method as the reference object, which provided scientific basis for the selection of appropriate statistical method. Considering the workload and universality, five types of experiments and single factor random block design were used. First, the observed value of a single plant was used for statistical analysis to obtain the results of transformation analysis. Then the average value of the plot was used to participate in the calculation, and the analysis result of the plot average method was obtained. On this basis, the statistical effect of the plot average value method for non-equilibrium test data was evaluated. Through comparative analysis, the results were as follows: （1） For the non-equilibrium test data, transformation analysis method was scientific and superior, and plot average method was only suitable for clone test; （2） The genetic variability information of individual plant could not be obtained by plot average method, so the statistical efficiency was low; （3） Monte carlo simulation data of five experiments, plot average method, the probability of negative variance components of block repetition factor of increased the decrease of block repetition number. In experiment IV,, 3% of the middle group factors showed negative variance components, and In experiment V, 6% of the middle group factors showed negative variance components, and the transformation analysis law eliminated the negative variance components; （4） The bias and error of the plot average method were greater than those of the transformation method; （5） The family heritability of plot average method was lower than that of transformation analysis method, and the accuracy of experimental analysis was lower than that of transformation analysis method, which was not conducive to adverse selection and forward selection; （6） Under the condition of fixed model, there was certain error in the mean value of family effect by plot average method, and the rank of many families was not consistent with the results of transformation analysis method, and the error probability of selection was 1/8-2/8. According to the above results, although plot average method had the advantage of small computation, it is suggested that transformation analysis method should be preferred in the field of forest tree genetics and breeding because of its many advantages.