刘 哲, 王 虎, 杨建宇, 李绍明, 马 钦, 李 林, 张晓东, 朱德海. 品种筛选多环境测试作图分析方法[J]. 农业工程学报, 2011, 27(10): 142-147.
    引用本文: 刘 哲, 王 虎, 杨建宇, 李绍明, 马 钦, 李 林, 张晓东, 朱德海. 品种筛选多环境测试作图分析方法[J]. 农业工程学报, 2011, 27(10): 142-147.
    Liu Zhe, Wang Hu, Yang Jianyu, Li Shaoming, Ma Qin, Li Lin, Zhang Xiaodong, Zhu Dehai. Analytical graphics for multi-environment trials of breed selection[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(10): 142-147.
    Citation: Liu Zhe, Wang Hu, Yang Jianyu, Li Shaoming, Ma Qin, Li Lin, Zhang Xiaodong, Zhu Dehai. Analytical graphics for multi-environment trials of breed selection[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(10): 142-147.

    品种筛选多环境测试作图分析方法

    Analytical graphics for multi-environment trials of breed selection

    • 摘要: 作图分析是挖掘品种多环境测试信息的有效手段。为充分挖掘测试信息,高效而准确地实现品种评价、筛选与预测这一目标,有必要引进更多可适用众多性状、易于理解和使用的直观作图分析方法。该研究根据近年分析品种多环境测试的经验,提出3种作图分析方法——雷达图、蜡烛图和条件格式,以国家玉米品种区试数据为例,对3种作图方法的使用进行分析。结果表明:3种方法均为适用于品种多环境测试数据的有效作图分析方法,对不同观测性状均可适用,并易于理解和使用;雷达图有助于多指标综合分析,包括品种或环境的认知度、一致性分析,以及品种的筛选和对比;蜡烛图有助于单指标的详细对比和规律挖掘,如试点区辨力、品种稳定性与优异性规律等;条件格式则是数据浏览与直观表达的结合。应用3种作图方法可提高多环境测试的决策效率。

       

      Abstract: Graphic analysis is an efficient way of data mining for multi-environment trials (MET). In order to fully exploit useful information in trials, make variety evaluation, selection and prediction efficiently and accurately, more analytical graphics that are suitable for various traits, understandable and easy-operating, need be introduced into MET. In this paper, three kinds of analytical graphics—radar, candlestick, and conditional format, accompany with their application methods were put forward based on the national MET data of maize in China. The results showed that: the 3 analytical graphics were suitable for various traits of MET, understandable, and easy-operating. Radar chart was good at comprehensive analysis of multi-index, including reliability and consistency of certain variety or environment, selection and comparison of varieties. Candlestick chart did well in comparing varieties or environments in detail and pattern discovery of single index, such as discriminating ability of test environment, superiority and stability of a variety. Conditional format is a good combination of data viewing and visualization. Using the 3 kinds of graphics will improve the efficiency of analyzing and decision making of MET.

       

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