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作物学报 ›› 2017, Vol. 43 ›› Issue (03): 371-377.doi: 10.3724/SP.J.1006.2017.00371

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

经验性最佳线性无偏预测(eBLUP)在油菜区域试验品种评价的效果

任长宏1,2,格桑曲珍1,3,胡希远1,*   

  1. 1 西北农林科技大学农学院，陕西杨凌712100；2 西藏自治区康马县农牧综合服务中心，西藏康马857500；3 西藏自治区林木科学研究院, 西藏拉萨850000
  • 收稿日期:2016-04-20 修回日期:2016-09-18 出版日期:2017-03-12 网络出版日期:2016-09-28
  • 通讯作者: 胡希远, E-mail: xiyuanhu@aliyun.com, Tel: 13072926729
  • 基金资助:

    本研究由陕西省自然科学基金项目(2012JM3009)资助。

Performance of eBLUP in Variety Evaluation of Regional Rape Trials in China

REN Chang-Hong1,2,GESANGQUZHEN1,3,Hu Xi-Yuan1,*   

  1. 1 College of Agronomy, Northwest A&F University, Yangling 712100, China; 2 Kangma Integrated Service Center for Agriculture and Animal Husbandry of Xizang Autonomous Region, Kangma 857500, China; 3 Institute of Forestry Seedling Science & Technique of Xizang Autonomous Region, Lhasa 850000, China
  • Received:2016-04-20 Revised:2016-09-18 Published:2017-03-12 Published online:2016-09-28
  • Contact: 胡希远, E-mail: xiyuanhu@aliyun.com, Tel: 13072926729
  • Supported by:

    The study was supported by the Natural Science Foundation of Shaanxi Province of China (2012JM3009).

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摘要：

线性混合模型最佳线性无偏预测(BLUP)不仅适用于数据不平衡和误差方差异质试验的分析，而且对随机效应的排序会更准确。在实际试验分析中由于真实方差参数值未知而采用估计值时，BLUP转变为所谓经验性BLUP (eBLUP)。为了探讨eBLUP在作物区域试验品种评价的效果，本文以我国2012—2014年长江流域油菜区域试验12套产量资料为例，对eBLUP在品种主效应和特定环境中效应的估计、排序及差异比较t测验等方面与方差分析综合比较。结果表明, 对品种主效应，eBLUP与方差分析算术平均值仅有较小差异，品种排序在eBLUP与算术平均值法相同；对特定环境中品种效应，eBLUP与算术平均值法有较大差异，品种排序在eBLUP较算术平均值法更准确；用Kenward-Roger法估算基于eBLUP的效应差异t测验的自由度，无论对品种主效应还是对特定环境中品种效应，eBLUP和方差分析有着相近的显著性(α = 0.05)测验效果。

关键词: 油菜试验, eBLUP, 品种评价, Kenward-Roger法

Abstract:

The mixed model and its best linear unbiased prediction (BLUP) are more suitable for analysis of the trails with unbalanced data and heterogeneous errors, and BLUP can provide more accurate ranking for random effects. In analysis of practical trials, the variance parameters are unknown and their estimates have to be used. In this case, the BLUP become empirical BLUP (eBLUP). To investigate the performance of eBLUP in variety valuation of regional crop trials in China, this paper compared estimates, ranking and t-test for both variety main effects and location-specific variety effects between using ANOVA and eBLUP based on 12 yield data sets from the rape variety evaluation trials of China from 2012–2014. The method of Kenward and Roger was used for approximating denominator degrees of freedom in t-test for effect difference comparison based on eBLUP. The results showed that in view of variety main effects, there was only small discrepancy between eBLUP and arithmetic mean of ANOVA, variety ranking was the same between them; In view of location-specific variety effects, there was large discrepancy between eBLUP and arithmetic mean, variety ranking was more accurate in eBLUP than arithmetic mean; In t-test for both variety main effects and location-specific variety effects, eBLUP and ANOVA provided similar variety pairs with significant (α = 0.05) difference.

Key words: Rape trial, eBLUP, Variety evaluation, Kenward-Roger method

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