Chu Yunxia, Ren Li, Deng Shan, Li Shouguo, Zhang Yiying, Chen Hairong
Institute for Agri-food Standards and Testing Technology, Shanghai Academy of Agricultural Sciences, Shanghai 201403, China.
Shanghai Sub-Center for New Plant Variety Tests, Ministry of Agriculture and Rural Affairs, Shanghai 201415, China.
Plants (Basel). 2023 Jun 22;12(13):2417. doi: 10.3390/plants12132417.
The determination of the grades and interval of quantitative characteristics is an important job while we draft new distinctness, uniformity and stability (DUS) test guidelines. Grading criteria should be adjusted because of the effect of year and site; it is also a key task to establish applicable criteria in the DUS test. Excellent criteria will improve the accuracy of the DUS evaluation. In this study, we analyzed the variability and distribution patterns of nine quantitative characteristics of 251 anthurium varieties. Three methods were used to establish the grade criteria: the two standard deviation methods, the two LSD methods and the multiple comparison method. The results showed that the coefficient of variation within varieties varied from 6.96% to 10.11%. The quantitative characteristics observed in this study did not follow a normal distribution, except spadix thickness at the middle and spathe size. In most characteristics, the standard deviations and LSD were similar, except for spathe size. The state interval set by multiple comparison methods for every characteristic was variable, and its mean was about 1.25 times that of the other two methods. The process of establishing grading criteria using the multiple comparison method was simpler, and the criteria were more accurate, with a lower error rate.
在起草新的植物新品种特异性、一致性和稳定性(DUS)测试指南时,确定数量性状的等级和区间是一项重要工作。由于年份和地点的影响,分级标准应进行调整;在DUS测试中建立适用的标准也是一项关键任务。优秀的标准将提高DUS评价的准确性。在本研究中,我们分析了251个红掌品种9个数量性状的变异性和分布模式。采用三种方法建立等级标准:两种标准差法、两种最小显著差法和多重比较法。结果表明,品种内变异系数在6.96%至10.11%之间。本研究中观察到的数量性状除佛焰苞中部厚度和佛焰苞大小外,均不服从正态分布。在大多数性状中,标准差和最小显著差相似,但佛焰苞大小除外。多重比较法为每个性状设定的状态区间是可变的,其均值约为其他两种方法的1.25倍。采用多重比较法建立分级标准的过程更简单,标准更准确,错误率更低。