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中国美利奴羊(新疆型)新品系选育研究 总被引：1，自引：0，他引：1
以羊毛弯曲明显整齐度、油汗洁白度及光泽明亮度为选育性状 ,采用 5分制评分方法将这些质量指标数量化 ;通过采用群体继代选育法 ,经过 10年 4个世代选育研究 ,在中国美利奴 (新疆型 )中育成毛质优品系。品系群三个选育性状的平均评分值分别达到 4 87± 0 16、4 90± 0 19和 4 90± 0 17,较 0世代分别提高 2 7 15 %、2 7 93 %和 2 7 2 7% ;品系群平均净毛量达 3 92kg。各项指标全面超过育种目标 相似文献
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对山西瘦肉型猪SD -Ⅱ系的肥育性能和胴体性状进行了研究 ,结果如下 :(1)SD -Ⅱ系猪有较快的生长速度 ,5世代日增重达 6 82 .33g/天 ,体重 90kg日龄为 179.88天 ,饲料转化率 3.2 4 ,与 0世代相比 ,有很大的提高。 (2 )SD -Ⅱ系猪 5世代胴体重 6 4 .70kg ,平均膘厚 2 .6 6cm ,瘦肉率 5 6 .10 % ,具有较好的胴体性状。 (3)从遗传力的估计结果来看 ,日增重、瘦肉率的遗传力较高 ,分别为 0 .6 4 1和 0 .5 32 ,可以作为育种过程中的主选指标 相似文献
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高性能杜洛克专门化品系选育及其利用 总被引：5，自引：0，他引：5
采用开放与闭锁相结合的群体继代选育法,以原有杜洛克群体为基础,导入高性能的台系杜洛克血缘,运用综合选择指数、最佳线性无偏估计(BLUP)法和分子标记辅助选择(MAS)等育种新方法,主选日增重和活体背膘厚等性状。经6个世代选育,产仔数达10.01头,产活仔数9.02头;肥育期日增重817g,料重比2.74,活体背膘厚9.03mm;瘦肉率67.73%,肌内脂肪含量2.28%(五世代),主选性状全面达到或超过育种目标,成功培育了一个高性能的杜洛克专门化新品系。2000～2006年,共推广种猪1600多头,获得了显著的经济效益和社会效益。 相似文献
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《畜牧与兽医》2014,(12):47-49
对蕨麻小型猪母猪的主要繁殖性状进行统计分析,筛选影响繁殖性能的性状,以指导实验动物选育工作。依据相关国家标准和操作技术规范测定普通级蕨麻小型猪种猪繁殖性状,主要有总产仔数(X1)、产活仔数(X2)、初生头重(X3)、初生窝重(X4)、断奶头数(X5)、断奶头重(X6)和断奶窝重(Y)等7个繁殖性状,并与产地数据进行对比,通过SAS8.01软件进行相关与通径分析。结果发现,蕨麻小型猪在广东地区的繁殖性能较原产地放牧型蕨麻小型猪显著提高。在所分析的7个性状中,X4-X6与断奶窝重直接相关,所建立的多元回归方程为:Y=-10.373 5+0.616 2X4+4.397 7X5+1.864 6X6(R2=0.988 1)。蕨麻小型猪经过系统的实验动物化选育后,繁殖性能获得了明显提高,部分性状尚存在较大变异,提示仍需进一步选育纯化。 相似文献
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《中国畜牧杂志》2016,(17)
为探讨新疆褐牛育种目标性状的相对选择重要性,为今后新疆褐牛良种选育和综合选择指数的制定奠定基础,本研究采用差额法和系统分析法,基于新疆褐牛当前生产水平和市场价格体系,对新疆褐牛3类性状10个育种目标的边际效益进行了评估,结果表明:新疆褐牛乳用性状、肉用性状和功能性状的相对经济重要性比例为36∶34∶30,近似于1∶1∶1,其中产奶量、日增重、18月龄体重和生产寿命4个性状的相对权重最大,分别为27.2、19.4、12.9和10.3。本研究结果符合新疆褐牛实际生产情况,在加强乳用和肉用性能选育的同时还应该重视功能性状的选择,以平衡育种为主加快新疆褐牛遗传进展,提高育种效率,增加育种效益。 相似文献
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Prediction of response to marker-assisted and genomic selection using selection index theory 总被引：1，自引：0，他引：1
J. C. M. Dekkers 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2007,124(6):331-341
Selection index methods can be used for deterministic assessment of the potential benefit of including marker information in genetic improvement programmes using marker-assisted selection (MAS). By specifying estimates of breeding values derived from marker information (M-EBV) as a correlated trait with heritability equal to 1, it was demonstrated that marker information can be incorporated in standard software for selection index predictions of response and rates of inbreeding, which requires specifying phenotypic traits and their genetic parameters. Path coefficient methods were used to derive genetic and phenotypic correlations between M-EBV and the phenotypic data. Methods were extended to multi-trait selection and to the case when M-EBV are based on high-density marker genotype data, as in genomic selection. Methods were applied to several example scenarios, which confirmed previous results that MAS substantially increases response to selection but also demonstrated that MAS can result in substantial reductions in the rates of inbreeding. Although further validation by stochastic simulation is required, the developed methodology provides an easy means of deterministically evaluating the potential benefits of MAS and to optimize selection strategies with availability of marker data. 相似文献
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本研究针对猪育种中重点考虑的窝产活仔猪数（NBA）、达100 kg体重日增重（ADG）、饲料利用率（FCR）、达100 kg体重的背膘厚（BF）、肌内脂肪含量（IMF） 5个性状,利用连锁平衡（linkage equilibrium,LE）、连锁不平衡（linkage disequilibrium,LD）标记和直接标记（direct marker,DR）3种类型的分子遗传标记,设计了3个规模不同的基础群,母猪数分别为100、200、300头,公猪数都为10头,基础群个体间无亲缘关系,育种群实施闭锁繁育。用Monte Carlo方法模拟了MAS的5个世代选择试验。育种值估计采用标准BLUP（Standard BLUP,SBLUP）模型（此育种值作为对照）、QBLUP模型（使用DR标记）、MBLUP模型（使用LD和LE标记）。结果表明,利用DR标记在各种情况下都比利用LD和LE标记获得的选择效率高;5个性状中,MAS对低遗传力、限性性状NBA的选择效率最高;当性状的QTL方差占遗传方差基本相同时,中等遗传力性状FCR的选择效率比高遗传力性状BF的更高;当性状的遗传力差异不大时,QTL方差占遗传方差比例大的性状FCR的选择效率比QTL方差占遗传方差比例小的性状ADG的更高。当利用QBLUP模型时,MAS对NBA的选择效率最高,ADG的选择效率最低。 相似文献
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The effectiveness of five selection methods for genetic improvement of net merit comprising trait 1 of low heritability (h2 = 0.1) and trait 2 of high heritability (h2 = 0.4) was examined: (i) two‐trait quantitative trait loci (QTL)‐assisted selection; (ii) partial QTL‐assisted selection based on trait 1; (iii) partial QTL‐assisted selection based on trait 2; (iv) QTL‐only selection; and (v) conventional selection index without QTL information. These selection methods were compared under 72 scenarios with different combinations of the relative economic weights, the genetic correlations between traits, the ratio of QTL variance to total genetic variance of the trait, and the ratio of genetic variances between traits. The results suggest that the detection of QTL for multiple‐trait QTL‐assisted selection is more important when the index traits are negatively correlated than when they are positively correlated. In contrast to literature reports that single‐trait marker‐assisted selection (MAS) is the most efficient for low heritability traits, this study found that the identified QTL of the low heritability trait contributed negligibly to total response in net merit. This is because multiple‐trait QTL‐assisted selection is designed to maximize total net merit rather than the genetic response of the individual index trait as in the case of single‐trait MAS. Therefore, it is not economical to identify the QTL of the low heritability traits for the improvement of total net merit. The efficient, cost‐effective selection strategy is to identify the QTL of the moderate or high heritability traits of the QTL‐assisted selection index to facilitate total economic returns. Detection of the QTL of the low h2 traits for the QTL‐assisted index selection is justified when the low h2 traits have high negative genetic correlation with the other index traits and/or when both economic weights and genetic variances of the low h2 traits are larger as compared to the other index traits of higher h2. This study deals with theoretical efficiency of QTL‐assisted selection, but the same principle applies to SNP‐based genomic selection when the proportion of the genetic variance ‘explained by the identified QTLs’ in this study is replaced by ‘explained by SNPs’. 相似文献
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Long N Gianola D Rosa GJ Weigel KA 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2011,128(4):247-257
Genome‐assisted prediction of genetic merit of individuals for a quantitative trait requires building statistical models that can handle data sets consisting of a massive number of markers and many fewer observations. Numerous regression models have been proposed in which marker effects are treated as random variables. Alternatively, multivariate dimension reduction techniques [such as principal component regression (PCR) and partial least‐squares regression (PLS)] model a small number of latent components which are linear combinations of original variables, thereby reducing dimensionality. Further, marker selection has drawn increasing attention in genomic selection. This study evaluated two dimension reduction methods, namely, supervised PCR and sparse PLS, for predicting genomic breeding values (BV) of dairy bulls for milk yield using single‐nucleotide polymorphisms (SNPs). These two methods perform variable selection in addition to reducing dimensionality. Supervised PCR preselects SNPs based on the strength of association of each SNP with the phenotype. Sparse PLS promotes sparsity by imposing some penalty on the coefficients of linear combinations of original SNP variables. Two types of supervised PCR (I and II) were examined. Method I was based on single‐SNP analyses, whereas method II was based on multiple‐SNP analyses. Supervised PCR II was clearly better than supervised PCR I in predictive ability when evaluated on SNP subsets of various sizes, and sparse PLS was in between. Supervised PCR II and sparse PLS attained similar predictive correlations when the size of the SNP subset was below 1000. Supervised PCR II with 300 and 500 SNPs achieved correlations of 0.54 and 0.59, respectively, corresponding to 80 and 87% of the correlation (0.68) obtained with all 32 518 SNPs in a PCR model. The predictive correlation of supervised PCR II reached a plateau of 0.68 when the number of SNPs increased to 3500. Our results demonstrate the potential of combining dimension reduction and variable selection for accurate and cost‐effective prediction of genomic BV. 相似文献
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随着科学技术的发展,畜禽的选择及遗传评定方法也在不断提高,并经历了从经验式育种到全基因组选择的巨大演变与发展,这种发展也不断地改进了选择效率。综述了畜禽选择方法的发展历程,并对各种选择方法作了简要评述。 相似文献
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黑龙江省通河县乌拉浑林场黑熊的生境选择 总被引：2，自引：0，他引：2
应用资源选择函数和资源选择指数对通河县乌拉浑林场内黑熊的生境选择进行了研究。结果表明,黑熊对生境的选择受到水源、倒木、地形因素以及隐蔽条件等因子的影响显著。黑熊对海拔较高（〉350 m）、处于上坡位及适中坡度的生境表现为喜爱选择。黑熊生境资源选择函数为：Logistic（P）=-5.254＋8.644×坡度＋1.896×坡位＋2.728×隐蔽级＋4.626×郁闭度-1.795×地理性-14.901×距水源距离＋2.356×距人为干扰距离＋6.078×倒木数量＋2.138×乔木种类。黑熊对生境的选择概率为：P=elogistic（p）/[1＋elogistic（p）]。模型的正确率为96.2%。 相似文献
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OBJECTIVE: To find out what criteria and methods are used by Australian employers to select new graduates to work in their practices. DESIGN: Questionnaires were completed by 258 employers and the responses were analysed using the SAS system. RESULTS: During selection, employers placed most reliance on formal interviews or visits to the practice. These occasions were used to assess the applicant's personal qualities including their ability to interact effectively with clients and colleagues. Employers used resumes mainly in selection of applicants to interview and many discounted nominated referees as being insufficiently critical. Academic knowledge was regarded as less important than personal qualities and very few employers reported using gender as a basis for selection. CONCLUSIONS: Senior veterinary students need to be aware of the importance placed by employers on interpersonal skills and personal qualities and should make every effort to engage in practical work, paid work and other activities that will help develop these attributes. They should be conscious that practitioners with whom they work may be contacted by potential employers and they should learn to present themselves realistically in a resume. 相似文献
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Takeshi Yamazaki Kenji Togashi Satoru Iwama Shigeo Matsumoto Kimihiro Moribe Takatoshi Nakanishi Koichi Hagiya Kiyoshi Hayasaka 《Animal Science Journal》2014,85(6):639-649
The effectiveness of the incorporation of genomic pre‐selection into dairy cattle progeny testing (GS‐PT) was compared with that of progeny testing (PT) where the fraction of dam to breed bull (DB) selected was 0.01. When the fraction of sires to breed bulls (SB) selected without being progeny tested to produce young bulls (YB) in the next generation was 0.2, the annual genetic gain from GS‐PT was 13% to 43% greater when h2 = 0.3 and 16% to 53% greater when h2 = 0.1 compared with that from PT. Given h2 = 0.3, a selection accuracy of 0.8 for both YB and DB, and selected fractions of 0.117 for YB and 0.04 for DB, GS‐PT produced 40% to 43% greater annual genetic gain than PT. Given h2 = 0.1, a selection accuracy of 0.6 for both YB and DB, and selected fractions of 0.117 for YB and 0.04 for DB, annual genetic gain from GS‐PT was 48% to 53% greater than that from PT. When h2 = 0.3, progeny testing capacity had little effect on annual genetic gain from GS‐PT. However, when h2 = 0.1, annual genetic gain from GS‐PT increased with increasing progeny testing capacity. 相似文献