共查询到16条相似文献，搜索用时 187 毫秒
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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。 相似文献
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为了研究我国玉米区域试验中误差方差的异质性存在状况及其对品种评价的作用, 以2003-2006年东北和华北16组玉米区域试验资料为依据,对玉米区域试验各环境试验误差方差差异状况及误差方差同质模型和异质模型的拟合效果进行了验证,并对品种效应差异显著性测验在误差同质模型和误差异质模型分析结果的差异状况进行了比较。结果表明,在分析的所有试验中,试验误差方差在环境间具有较大差异;误差方差异质模型比误差方差同质模型对试验数据拟合效果普遍较好;模型是否考虑误差方差的异质性对品种-环境交互效应测验结果有较大影响,而对品种主效应测验结果影响极小;误差方差异质模型比误差方差同质模型测验效率高。 相似文献
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空间统计分析在作物育种品系选择中的效果 总被引：2，自引：0，他引：2
为了研究空间统计分析法在作物育种田间试验品系选择中的效果,采用剩余误差空间相关线性混合模型对一个具有56个品系的小麦育种随机区组设计田间试验产量资料进行了空间统计分析。运用地理统计学中的半变异函数法确定剩余误差空间协方差的函数。结果表明,试验的剩余误差存在着典型的空间相关性,利用剩余误差空间协方差结构的信息可降低品系效应估计的误差和提高品系效应差异F检验与t检验的效率。此外,空间分析法对品系效应估计受试验条件不均匀的影响小,可导致较经典方差分析法不同的品系排序和优系选择结果。 相似文献
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非独立试验数据的一般线性混合模型分析 总被引：1，自引：0，他引：1
传统方差分析模型的假设条件之一是试验数据相互独立,实际的试验数据未必能满足其条件,这使方差分析的应用范围和分析的效果受到限制。近年来,一般线性混合模型得到发展,为分析非独立试验数据提供了新途径。本文讨论了一般线性混合模型分析非独立试验数据的方法及其在SAS软件的实现,对小麦品比和玉米灌溉2个不同试验的非独立数据进行了一般线性混合模型与方差分析模型的对比分析。结果表明,与传统方差分析法相比,一般线性混合模型数据拟合效果好,在小麦品比试验使小麦品系效应比较的平均标准误降低18.4%,平均分析相对效率为1.5,而在玉米灌溉试验使灌溉效应比较和品种×灌溉交互效应比较的平均标准误降低9.1%￣10.8%,平均分析相对效率均约为1.2。因此,对非独立试验数据,一般线性混合模型分析的准确性和效率要比传统方差分析模型高。 相似文献
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黄河流域棉花品种产量长期预测技术的比较研究 总被引：2，自引：2，他引：2
以黄河流域棉花品种区域试验参试品种的皮棉产量为原始资料,分别应用一元线性回归、GM(1,1)及谐波分析原理和技术建立模型,对三者的模型精度、拟合程度及预测结果进行比较研究。结果表明,对于波动性较大的皮棉产量时间序列,一元线性回归及GM(1,1)模型的精度低,拟合效果差,预测值不理想;而谐波分析模型的精度高,拟合效果好,预测值准确可信,其中,4个以上谐波迭加的模型可达"一级精度",历史符合率90%～100%,可直接应用于生产实践。分别选取4,5,6,...15个谐波迭加的谐波分析模型,预测2003年黄河流域棉花品种区域试验参试品种的皮棉产量为1181.73～1288.66kg·hm 2。 相似文献
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为了综合评价玉米区域试验的结果,采用Shukla模型、Finlay-Wilkinson模型、Eberhart-Russell模型和加性主效乘式互作模型(AMMI)等4种常用模型对中国5个类型的玉米品种区域试验资料进行了拟合与分析。结果表明,没有一个模型对所有试验资料的拟合效果都最佳,Finlay-Wilkinson模型对5个试验拟合效果均最差,AMMI模型对3个试验的数据拟合效果最佳,Shukla模型和Eberhart-Russell模型则分别对一个试验拟合效果最佳。各个模型在玉米品种产量差异显著性检验和稳定性排序等方面存在较大的差异。因此,在玉米区域试验的实际分析中应采用AMMI模型或者利用模型拟合信息量准则选用最佳的模型进行分析,以提高玉米区域试验对品种高产与稳产评价的准确性。 相似文献
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田间试验的空间变异性及其统计控制 总被引：6，自引：1，他引：6
利用空间相关模型和传统方差分析模型对小麦和玉米3个田间试验产量数据进行了拟合与分析。结果表明，3个试验都显著存在空间变异，空间变异方差占据剩余变异方差的83.5%~0.4%；相对于传统随机完全区组分析法，空间相关模型法效应比较的标准误平均降低18.4%~14.2%，分析相对效率平均为1.50~1.36，因而比区组控制空间变异更有效；不同空间相关模型分析的结果呈现出一定的差异。建议利用空间相关模型分析田间试验，并利用Akaike信息准则（AIC）进行最佳空间相关模型选择。 相似文献
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A one-stage analysis of a series of variety trials involves a combined analysis of the individual plot data across trials. Together with prudent modelling of the genetic effects across trials, this is considered to be the gold standard analysis of multi-environment field trial data. An alternative is a two-stage approach in which the variety means from an analysis of the individual trials in stage one are combined into a weighted mixed model analysis in stage two to give the full set of predicted variety by environment effects and an estimate of their associated variance structure. The two-stage analysis will exactly reproduce the one-stage analysis if the full variance-covariance matrix of the means from stage one is known and is utilised in stage two. Typically the full matrix is not stored and a diagonal approximation is used. This introduces a compromise to the full analysis. The impacts of a diagonal approximation are greater in the presence of sophisticated models for the genetic effects. A second compromise is through a loss of information in estimating the non-genetic variance parameters using the two-stage approach. In this paper we draw a direct link between the one and two-stage analysis approaches for crop variety evaluation data in Australia. We now have the computing power to analyse large and complex multi-environment variety trial data sets using the one-stage approach without the need for a two-stage approximation. This should motivate a move away from the two-stage approach in a range of contexts. 相似文献
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Replicate allocation to improve selection efficiency in the early stages of a potato breeding scheme
M. F. Paget P. A. Alspach J. A. D. Anderson R. A. Genet W. F. Braam L. A. Apiolaza 《Euphytica》2017,213(9):221
Field data and simulation were used to investigate replication within trials and the allocation of replicates across trial sites using partial replication as an approach to improve the efficiency of early-stage selection in a potato breeding programme. Analysis of potato trial data using linear mixed models, based on four-plant (clonal) plots planted as augmented partially-replicated (p-rep) designs, obtained genetic and environmental components of variation for a number of yield and tuber components. Heritabilities, trial-to-trial genetic correlations and performance repeatability of clonal selections in p-rep trials and in subsequent fully replicated trial stages were high, and selection was effective for the economically important traits of marketable tuber yield and tuber cooking quality. Simulations using a parameter-based approach, pertaining to the variance components estimated from the p-rep field trials, and the parametric bootstrapping of historic empirical data showed improved rates of genetic gain with p-rep testing over one and two locations compared with testing in fully replicated trials. This potato breeding study suggests that the evaluation and selection of a clonal field crop in fully replicated trials may not be optimal in the early stages of a breeding cycle and that p-rep designs offer a more efficient and practical alternative. 相似文献
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Mark F. Paget Peter A. Alspach John A.D. Anderson Russell A. Genet Luis A. Apiolaza 《Plant Breeding》2015,134(2):203-211
Genetic evaluation aims to identify genotypes with high empirical breeding values (EBVs) for selection as parents. In this study, 2157 potato genotypes were evaluated for tuber yield using 8 years of early‐stage trial data collected from a potato breeding programme. Using linear mixed models, spatial parameters to target greater control of localised spatial heterogeneity within trials were estimated and variance models to account for across‐trial genetic heterogeneity were tested. When spatial components improved model fit, correlations of errors were mostly small and negative for marketable tuber yield (MTY) and total tuber yield (TTY), suggesting the presence of interplot competition in some years. For the analysis of multi‐environment trials, a variance model with a simple correlation structure (with heterogeneous variances) was the most favourable variance structure fitted for TTY and PTY (per cent marketable yield). There was very little difference in model fit when comparing a factor analytic structure of order 2 (FA2) with either FA1 or simple correlation structures for MTY, indicating that simple variance models may be preferable for early‐stage genetic evaluation of potato yield. 相似文献
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我国棉花品种区域试验重复次数和试点数量的设计 总被引：2，自引：0，他引：2
农作物区域试验重复次数和试点数量设置直接影响试验的遗传力和品种选择效率。本研究以2000-2014年期间长江流域、黄河流域和西北内陆棉区国家棉花区试数据为资料,依据各棉区的试验发展现状和试验遗传力随着试点数量的变化,分析重复次数和试点数量设置的合理性,提出各棉区试点数量的设置方案。结果表明: (1)我国棉花品种区域试验采用3次重复是保证试验效率的充分条件;(2)长江流域和黄河流域国家棉花区试现行的试点数量设置已经可以充分满足试验的遗传力要求,西北内陆棉区的试点数也符合遗传力达到0.75的基本要求;(3)由于棉花区域试验对品种的推荐审定和应用十分重要,试验过程中也可能会因田间管理、自然灾害或其他异常情况导致试验报废,为充分保证试验的可靠性,长江流域棉区可保持当前20个左右的试点数量,遗传力即可达到0.90的水平;黄河流域和西北内陆棉区可以分别将试点数量增加到27个和19个左右,遗传力达到0.90和0.85的水平。该结果为国家棉花区域试验的优化配置提供理论依据,也为其他作物区域试验布局提供参考。