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Selection method for excellent individuals of Chinese firs

A Chinese fir and individual technology, which is applied in the field of selection of excellent Chinese fir individuals, can solve problems such as the reduction of genetic diversity, and achieve the effects of high accuracy and good practicability.

Inactive Publication Date: 2015-03-25
NANJING FORESTRY UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The excellent individuals obtained according to the breeding value and selection index are often concentrated in some families with good performance, which greatly reduces the genetic diversity

Method used

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  • Selection method for excellent individuals of Chinese firs
  • Selection method for excellent individuals of Chinese firs
  • Selection method for excellent individuals of Chinese firs

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0031] Material source: The second-generation Chinese fir seed orchard of Guanzhuang State-owned Forest Farm, Sha County, Fujian Province, is located in Shijingshan, Chicun Industrial Zone, 40 Class 54 Class 2 Subclass, and covers an area of ​​195 mu. The anvil was set in February 1982, and grafted from March to April 1, 1984. The front stubble of the seed orchard is a natural forest. After felling and smelting, the entire seed orchard is divided into 17 groups and 34 plots, of which there are two groups in 7, 14, 26, and 27 subdivisions, and the area code is 30 plots, and 256 asexual System, adopts the sequence dislocation design configuration method. Among them, 256 families came from the provenance test forest, the excellent trees selected locally in Fujian, and the hybrid progeny of the early selected excellent trees in Nanping area.

[0032] The seedlings used in the present invention are all provided by the Guanzhuang State-owned Forest Farm in Shaxian County, Fujian Provi...

Embodiment 2

[0063] Taking the data measured in Example 1 as the original data, using spatial analysis methods to estimate the spatial residual variance and spatial autocorrelation, the restricted maximum likelihood method to estimate the genetic variance and the best linear unbiased prediction of the mixture of the values ​​of Chinese fir species The linear model method analyzes the genetic variation, genetic control, and genetic correlation between the economic traits of Chinese fir, and predicts the breeding value of each individual trait of Chinese fir; the specific process is as follows:

[0064] (1) Data sorting and standardization to make the data conform to the normal distribution.

[0065] (2) Spatial analysis. The spatial analysis model is as follows:

[0066] Y=Xb+Zf+ξ+η

[0067] Among them, Y is the data vector, the fixed effect vector is the mean vector, b and f are the random effect vectors, X and Z are the design matrices corresponding to the observations and the random effects, ξ ...

Embodiment 3

[0078] According to the selection formula of the multi-character index of Chinese fir, select the excellent individuals with both genetic advantages in growth and wood properties of Chinese fir; the selection formula of the multi-character index is as follows:

[0079] I i = 0.7 a ^ i 1 + 0.3 a ^ i 2

[0080] Where I i Is the selection index value of genotype i; 0.7 and 0.3 are the weights of Chinese fir growth traits and wood traits, respectively; with It is the best linear unbiased predicted breeding value for each trait of genotype i (that is, the breeding value at breast height and the breeding value of wood density calculated in Example 2).

[0081] (1) Guanzhuang State-owned Forest Farm, Sha County, Fujian Province

[0082] A total of 2243 strains were investigated. The average value of each trait, estimated value of genetic variance, additive genetic variation coefficient and narrow sense heritability per plant are shown in Table 3...

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Abstract

The invention discloses a selection method for excellent individuals of Chinese firs. The selection method is a mixed linear model method, utilizes a spatial analysis method for estimating a spatial residual variance and spatial autocorrelation, utilizes a restrictive maximum likelihood method for estimating a genetic variance, and utilizes best linear unbiased prediction for individual breeding value of the Chinese firs. The method analyzes genetic variation, genetic control and genetic correlation among characters for main economic characters such as tree height, diameter at breast height, wood basic density, micro fiber angle and the like of the Chinese fir, predicts the breeding value of each character for each individual of the Chinese firs, and according to a multi-character index selection formula of the Chinese fir, picks out individuals which are genetically excellent both in growth and wood property. According to the method, when the environmental impact is eliminated in generic parameter estimation, the multi-character index selection based on the breeding value can select the individuals with generically excellent comprehensive characters effectively, the accuracy is high, and the selected excellent individuals can serve as both the material for asexual reproduction of the Chinese firs and the breeding material for next-generation breeding population of the Chinese firs.

Description

Technical field [0001] The invention relates to the technical field of forest tree breeding, in particular to a method for selecting excellent individuals of Chinese fir. Background technique [0002] At present, excellent individual plants of Chinese fir are often selected according to their phenotype, and the phenotype is the result of the interaction between genotype and environment. A good phenotype depends on the positional effect and genetic factors caused by the environment, whether it can be passed to the offspring and The intensity is unknown, so it is very difficult to determine the quality of the offspring and to establish a high-generation seed orchard based solely on performance. In the high-generation breeding of Chinese fir, phenotypic selection is currently the main focus, and genetically superior individuals cannot be truly selected. The most important advantage of the best linear unbiased prediction is that all data from multiple generations of genetic testing c...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A01G23/00A01G7/00
Inventor 边黎明郑仁华施季森陈金慧杨立伟
Owner NANJING FORESTRY UNIV
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