BLUP方法在植物育种中的重要性

Tajalifar Mahdi, Rasooli Mohammad
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引用次数: 1

摘要

引言:最理想的线性中立预测(BLUP)是估计混合模型随机效应的标准方法。这种方法最初是在动物育种中开发的,用于估计繁殖价值,现在被广泛应用于许多研究领域。使用REML/BLUP的主要实际优势是:它允许在时间(世代、年份)和空间(位置、区块)上对个体或物种进行比较。同时校正环境影响、估计方差分量和预测遗传值的可能性。最佳BLUP预测方法以高精度估计平均值,特别是在混合模型中,也用于评估多环境实验数据(MET)。Blup是一种统计方法。基于谱系的模糊方法。材料和方法:BLUP方法通过一种称为家族指数选择的指数,将表型数据和谱系关系信息相结合,从而实现这一目标。该指数是根据阶级内部相关性系数估计的,利用了一个家庭中个人与人口中其他家庭的关系。结果:结果表明,与其他方法相比,BLUP具有良好的预测精度。基于系谱的BLUP方法可以提高P.zonale生产相关性状的选择产量或石竹的货架期。
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Importance of BLUP method in plant breeding
Introduction: The most desirable linear neutral prediction (BLUP) is a standard method for estimating the random effects of a hybrid model. This approach was originally developed in animal breeding to estimate breeding values and is now widely used in many fields of research. The main practical advantages of using REML/BLUP are: It allows the comparison of individuals or species over time (generation, year) and space (location, block). Possibility of simultaneous correction of environmental effects, estimation of variance components, and prediction of genetic values. The best BLUP prediction method, which estimates the averages with high accuracy, especially in mixed models, is also used to evaluate multi-environment experimental data (MET). Blup is one method is statistical. Pedigree-based blup method. Materials and methods: The BLUP method achieves this goal by combining phenotypic data and information on pedigree relationships through an index, known as family index selection. This index, which is estimated based on the coefficient of intra-class correlation, exploits the relationships of individuals within a family compared to other families in the population. Results: The results: show that BLUP has good prediction accuracy compared to other methods. Pedigree-based BLUP method can increase selection yield in production-related traits in P. zonale or shelf life of D. caryophyllus L.
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