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叶金俊, 叶金水, 包小梅, 等. 林木子代试验中小区平均值法与转化分析法比较[J]. 四川林业科技, 2022, 43(5): 107−114. DOI: 10.12172/202109240003
引用本文: 叶金俊, 叶金水, 包小梅, 等. 林木子代试验中小区平均值法与转化分析法比较[J]. 四川林业科技, 2022, 43(5): 107−114. DOI: 10.12172/202109240003
YE J J, YE J S, BAO X M, et al. Comparative analysis about plot average method and transformation analysis method in forest progeny tests[J]. Journal of Sichuan Forestry Science and Technology, 2022, 43(5): 107−114. DOI: 10.12172/202109240003
Citation: YE J J, YE J S, BAO X M, et al. Comparative analysis about plot average method and transformation analysis method in forest progeny tests[J]. Journal of Sichuan Forestry Science and Technology, 2022, 43(5): 107−114. DOI: 10.12172/202109240003

林木子代试验中小区平均值法与转化分析法比较

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

  • 摘要: 为了评价林木非平衡试验资料小区平均值法的分析效果,运用蒙特卡罗(Monte Carlo)模拟数据,以转化分析法为参照对象,比较评价了小区平均值法的优缺点,为筛选的统计方法提供科学依据。基于工作量和普遍性考虑,采用了5个试验,单因素随机区组设计,先以单株观察值参与统计分析,获得转化分析法的结果;然后以小区平均值参与计算,获得小区平均值法的分析结果。在此基础上,评价非平衡试验资料小区平均值法的统计效果。比较分析发现:(1)对于非平衡试验数据,转化分析法具有严密的科学性和优越性,小区平均值法仅适合于无性系试验;(2)小区平均值法无法获得单株遗传变异性信息,故统计效率较低;(3)5个试验的蒙特卡罗模拟数据,小区平均值法,其区组重复因子出现负的方差分量概率,随着区组重复数的减少而增加,试验Ⅳ中区组因子有3%的试验出现负方差分量,试验Ⅴ中区组因子有6%的试验出现负方差分量,而转化分析法则消灭了负的方差分量;(4)小区平均值法偏性和误差均大于转化分析法;(5)小区平均值法的家系遗传力比转化分析法的小,且试验分析的精确性比转化分析法低,这不利于逆向选择和前向选择;(6)在固定模型条件下,小区平均值法关于家系效应的平均值有一定的误差,许多家系的秩与转化分析法的结果不一致,选择的失误概率为1/8~2/8。综合以上结果得出:尽管小区平均值法具有计算量小的优势,但因其缺点太多,建议在林木遗传育种领域中,优先采用转化分析法。

     

    Abstract: 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.

     

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