群钻钻削精度试验

通过群钻钻头直径Ｄ，进给量ｆ和切削速度ｎ对孔径扩张量，圆度，孔中心线垂直度和直线度影响的试验，得出它们的变化规律。     

The influence of sampling scheme and interpolation method on the power to detect spatial effects of forest birds in Ontario (Canada)

Spatial ecology is becoming an increasingly important component of resource management, and the general monitoring of how human activities affect the distribution and abundance of wildlife. Yet most work on the reliability of sampling strategies is based on a non-spatial analysis of variance paradigm, and little work has been done assessing the power of alternative spatial methods for creating reliable maps of animal abundance. Such a map forms a critical response variable for multiple scale studies relating landscape structure to biotic function. The power to reconstruct patterns of distribution and abundance is influenced by sample placement strategy and density, the nature of spatial auto-correlation among points, and by the technique used to extrapolate points into an animal abundance map. Faced with uncertainty concerning the influence of these factors, we chose to first synthesize a model reference system of known properties and then evaluate the relative performance of alternative sampling and mapping procedures using it. We used published habitat associations of tree nesting boreal neo-tropical birds, a classified habitat map from the Manitou Lakes area of northwestern Ontario, and point count means and variances determined from field studies in boreal Canada to create 4 simulated models of avian abundance to function as reference maps. Four point sampling strategies were evaluated by 4 spatial mapping methods. We found mixed-cluster sampling to be an effective point sampling strategy, particularly when high habitat fragmentation was avoided by restricting samples to habitat patches >10 ha in size. We also found that of the 4 mapping methods, only stratified ordinary point kriging (OPK) was able to generate maps that reproduced an embedded landscape-scale spatial effect that reduced nesting bird abundance in areas of higher forest age-class fragmentation. Global OPK was effective only for detecting broader, regional-scale differences. This revised version was published online in July 2006 with corrections to the Cover Date.     

Including an additional systematic environmental effect within a generation in an evaluation model improves accuracy of prediction of breeding values in a closed herd of pigs

The present study evaluated the advantage of mixed‐model techniques over a selection index under different magnitudes of an additional systematic environmental effect (ASEE) in terms of accuracy of prediction and expected genetic gain. The data attempted to simulate a closed herd in a pig breeding program. The base population (G₀) consisted of 10 males and 50 females. Six generations (G₀ to G₅) were selected by using a selection index of three traits without overlapping. Additional systematic environmental constants with four levels in a generation were assigned from a uniform distribution at different ranges. Breeding values of animals in the last generation (G₅) were estimated on the basis of an index of individual phenotype (SI‐U), SI‐U adjusted for ASEE using a least‐squares mean (SI‐A), best linear unbiased prediction using an animal model excluding ASEE (AM‐E), and an animal model including ASEE (AM‐I). Accuracy of prediction and expected genetic gain were larger by the animal model than by the selection index, even if heritability of the traits selected was high and ASEE was set to zero. When ASEE was zero, the accuracy of prediction and expected genetic gain given by SI‐U and AM‐I were similar to those given by SI‐A and AM‐E, respectively. However, the differences in accuracy and expected gain between SI‐U and AI‐A and between AM‐I and AM‐E increased as the range of ASEE increased. It was concluded that selection based on an animal model was more effective than index selection, even if the herd environment was uniform and traits with high heritability were selected, and that it should be always included in an evaluation model, however slight any systematic environmental effect may be in a closed herd.     

单站式大气电场仪探测距离分析

通过对电子设备防雷需求的计算,确定大气电场仪应有的探测距离;通过对几种情况下大气电场的分析、计算,结合大气电场仪的探测原理及探测公式,确定大气电场仪的探测距离,并对其进行分析.通过对大气电场仪探测距离和电子设备防雷需求的预警距离对比,得出单站式大气电场仪应根据使用者的需求,降低探测距离,提高探测准确度.     

吉林省西部新开发水田遥感动态监测研究

为了响应土地整理开发项目的政策,吉林省西部地区开发了大面积的水田。为掌握新开发水田的动态变化,有必要对吉林省地区进行土地利用分类。以吉林省前郭县为例,利用2010年环境卫星数据进行不同土地利用分类方法的比较,进而对另外3景图像进行信息提取,分析4个年份新开发水田的分布及变化情况。结果表明,支持向量机法比最大似然法的耕地分类精度高约5%,其产品和用户精度分别为95%和84%。加入纹理信息没有显著提高分类精度。2009~2012年水田面积分别增加-67.7 km2,111.7 km2和265.01 km2。     

快速型黄羽肉鸡饲料利用效率性状的基因组选择研究

旨在探究快速型黄羽肉鸡饲料利用效率性状的遗传参数,评估不同方法所得估计育种值的准确性。本研究以自主培育的快速型黄羽肉鸡E系1 923个个体（其中公鸡1 199只,母鸡724只）为研究素材,采用"京芯一号"鸡55K SNP芯片进行基因分型。分别利用传统最佳线性无偏预测（BLUP）、基因组最佳线性无偏预测（GBLUP）和一步法（SSGBLUP）3种方法,基于加性效应模型进行遗传参数估计,通过10倍交叉验证比较3种方法所得估计育种值的准确性。研究性状包括4个生长性状和4个饲料利用效率性状：42日龄体重（BW42D）、56日龄体重（BW56D）、日均增重（ADG）、日均采食量（ADFI）和饲料转化率（FCR）、剩余采食量（RFI）、剩余增长体重（RG）、剩余采食和增长体重（RIG）。结果显示,4个饲料利用效率性状均为低遗传力（0.08~0.20）,其他生长性状为中等偏低遗传力（0.11~0.35）;4个饲料利用效率性状间均为高度遗传相关,RFI、RIG与ADFI间为中度遗传相关,RFI与ADG间无显著相关性,RIG与ADG间为低度遗传相关。本研究在获得SSGBLUP方法的最佳基因型和系谱矩阵权重比基础上,比较8个性状的估计育种值准确性,SSGBLUP方法获得的准确性分别比传统BLUP和GBLUP方法提高3.85%~14.43%和5.21%~17.89%。综上,以RIG为选择指标能够在降低日均采食量的同时保持日均增重,比RFI更适合快速型黄羽肉鸡的选育目标;采用最佳权重比进行SSGBLUP分析,对目标性状估计育种值的预测性能最优,建议作为快速型黄羽肉鸡基因组选择方法。     

参考群筛选方法及规模对基因型填充准确性的影响

为探究基于A矩阵期望遗传关系最大化（maximizing the expected genetic relationship for matrix A,RELA）、基于A矩阵目标群体遗传方差最小化（minimized the target population genetic variance for matrix A,MCA）、平均亲缘关系最大化（the highest mean kinship coefficients,KIN）、随机选择（random selection,RAN）、共同祖先筛选（common ancestor,CA）等不同参考群筛选方法及参考群规模对基因型填充准确性的影响。本研究使用矮小型黄羽肉鸡作为试验群体,采用鸡600K SNP芯片（Affymetrix Axion HD genotyping array）进行基因分型,测定435羽子代公鸡45、56、70、84、91日龄体重。利用Beagle软件将低密度SNP芯片填充为高密度SNP芯片数据,比较不同参考群筛选方法、参考群规模对基因型填充准确性的影响,以及填充芯片基因组预测准确性。结果表明,使用Beagle 4.0结合系谱信息进行填充效果最佳,其次为Beagle 4.0,而Beagle 5.1填充效果最差。使用MCA方法筛选参考群进行基因型填充准确性最高,使用RAN方法筛选参考群进行基因型填充准确性最低,MCA、RELA、CA 3种方法基因型填充准确性差别较小。相比其他方法,使用MCA方法筛选个体作为参考群将低密度SNP芯片填充至高密度SNP芯片进行基因组选择的预测准确性较高,与真实高密度SNP芯片的基因组预测准确性相差甚微。随着参考群规模增大,基因型填充准确性也随之增加,但增速逐渐下降,最后趋于平缓。综上所述,可以通过参考群筛选方法构建参考群以及控制参考群规模,以保证基因型填充和基因组预测准确性并节省成本,本研究为基因型填充在畜禽遗传育种中的应用提供技术参考。     

Accuracy of imputation of single nucleotide polymorphism marker genotypes from low‐density panels in Japanese Black cattle

Using target and reference fattened steer populations, the performance of genotype imputation using lower‐density marker panels in Japanese Black cattle was evaluated. Population imputation was performed using BEAGLE software. Genotype information for approximately 40 000 single nucleotide polymorphism (SNP) markers by Illumina BovineSNP50 BeadChip was available, and imputation accuracy was assessed based on the average concordance rates of the genotypes, varying equally spaced SNP densities, and the number of individuals in the reference population. Two additional statistics were also calculated as indicators of imputation performance. The concordance rates tended to be lower for SNPs with greater minor allele frequencies, or those located near the ends of the chromosomes. Longer autosomes yielded greater imputation accuracies than shorter ones. When SNPs were selected based on linkage disequilibrium information, relative imputation accuracy was slightly improved. When 3000 and 10 000 equally spaced SNPs were used, the imputation accuracies were greater than 90% and approximately 97%, respectively. These results indicate that combining genotyping using a lower‐density SNP chip with genotype imputation based on a population of individuals genotyped using a higher‐density SNP chip is a cost‐effective and valid approach for genomic prediction.