Maturity period is a critical trait in soybean breeding and determines the particularly ecological region of a cultivar.In present study,118 soybean varieties spanning three artificial breeding periods(1923-1970,the e...Maturity period is a critical trait in soybean breeding and determines the particularly ecological region of a cultivar.In present study,118 soybean varieties spanning three artificial breeding periods(1923-1970,the early breeding period;1971-1990,the mid-breeding period;and 1991-2010,the current breeding period)in northeast China were selected.Fourteen DNA-specified markers including cleaved amplified polymorphic sequences(CAPS),derived CAPS(d CAPS)and fragment length polymorphism(FLP)markers were filtered to analyze the genetic diversity from E1 to E4.The results were as the followings:the soybean varieties with more gene frequencies showed more gene diversities.Among the E genes,E1 and E3 genes showed more allelic diversities than E2,and E4 only had diversity in the early breeding period.During the artificial process,some alleles of E genes disappeared and some new ones were generated.More gene diversities were observed in soybean germplasms,and new excellent germplasms could be explored to improve yield traits in artificial breeding programs.Furthermore,six different E gene combinations were observed in the early breeding period,five in the mid-breeding period and 11 in the current breeding period.Three elite genotypes were identified through a century artificial selection,while new genotypes were also found in different breeding periods.Of them,e1-nle2e3-tr E4 was a new soybean genotype of extremely early maturity in the current breeding period,which was widely suitable for planting in 00 and 000 maturity groups.Moreover,significant correlation was found between E2 and E3,suggesting that light length and light quality were two key factors for soybean maturity in northeast China.The understanding of the E genes variation underlying soybean maturity could facilitate the procession to breed elite varieties adapted for diverse regions.展开更多
以风云四号B星数据Ka频段接收系统为研究对象,采用站址分集策略,在北京气象卫星地面站和乌兰察布气象卫星地面站同步接收卫星数据的支持下,选择信道存取数据单元(Channel Access Data Unit,CADU)数据作为两站间数据匹配的处理单元,通过...以风云四号B星数据Ka频段接收系统为研究对象,采用站址分集策略,在北京气象卫星地面站和乌兰察布气象卫星地面站同步接收卫星数据的支持下,选择信道存取数据单元(Channel Access Data Unit,CADU)数据作为两站间数据匹配的处理单元,通过基于数据质量信息的择优技术,实时将多路数据择优合成为一路高质量数据,实现了我国首个基于站址分集接收策略的卫星接收系统。实际验证结果证明,该策略大大降低了雨衰对Ka频段数据接收的负面影响,也为气象卫星事业高质量发展提供了技术支撑。展开更多
为了提高用于更新代理模型的解集的多样性和收敛性以提高代理模型准确度,提出一种基于行列式点过程(determinantal point process,DPP)的代理模型辅助多目标进化算法(surrogate-assisted evolutionary algorithm,SAEA)。首先,提出一种...为了提高用于更新代理模型的解集的多样性和收敛性以提高代理模型准确度,提出一种基于行列式点过程(determinantal point process,DPP)的代理模型辅助多目标进化算法(surrogate-assisted evolutionary algorithm,SAEA)。首先,提出一种基于行列式点过程的模型管理方法,从非支配解集基于行列式点过程选取子集并用真实目标函数评估,再从所有经真实目标函数评估的解中选取子集用于更新代理模型。另一方面,提出一种基于自适应行列式点过程的环境选择方法,在进化过程的早期侧重于提高种群的收敛性,在进化过程的后期侧重于提高种群的多样性。最后,基于DTLZ、WFG、MAF测试问题验证算法的有效性。将所提算法与K-RVEA、KTA2、CSEA等常用算法进行比较,使用IGD+指标进行评估。实验结果显示所提出的算法能得到更优的解集,从而证明了其高计算代价多目标优化问题上的有效性。展开更多
基金Supported by the National Nature Scienceof China(31571693)the National Soybean Industrial Technology System(CARS-04-04B)。
文摘Maturity period is a critical trait in soybean breeding and determines the particularly ecological region of a cultivar.In present study,118 soybean varieties spanning three artificial breeding periods(1923-1970,the early breeding period;1971-1990,the mid-breeding period;and 1991-2010,the current breeding period)in northeast China were selected.Fourteen DNA-specified markers including cleaved amplified polymorphic sequences(CAPS),derived CAPS(d CAPS)and fragment length polymorphism(FLP)markers were filtered to analyze the genetic diversity from E1 to E4.The results were as the followings:the soybean varieties with more gene frequencies showed more gene diversities.Among the E genes,E1 and E3 genes showed more allelic diversities than E2,and E4 only had diversity in the early breeding period.During the artificial process,some alleles of E genes disappeared and some new ones were generated.More gene diversities were observed in soybean germplasms,and new excellent germplasms could be explored to improve yield traits in artificial breeding programs.Furthermore,six different E gene combinations were observed in the early breeding period,five in the mid-breeding period and 11 in the current breeding period.Three elite genotypes were identified through a century artificial selection,while new genotypes were also found in different breeding periods.Of them,e1-nle2e3-tr E4 was a new soybean genotype of extremely early maturity in the current breeding period,which was widely suitable for planting in 00 and 000 maturity groups.Moreover,significant correlation was found between E2 and E3,suggesting that light length and light quality were two key factors for soybean maturity in northeast China.The understanding of the E genes variation underlying soybean maturity could facilitate the procession to breed elite varieties adapted for diverse regions.
文摘以风云四号B星数据Ka频段接收系统为研究对象,采用站址分集策略,在北京气象卫星地面站和乌兰察布气象卫星地面站同步接收卫星数据的支持下,选择信道存取数据单元(Channel Access Data Unit,CADU)数据作为两站间数据匹配的处理单元,通过基于数据质量信息的择优技术,实时将多路数据择优合成为一路高质量数据,实现了我国首个基于站址分集接收策略的卫星接收系统。实际验证结果证明,该策略大大降低了雨衰对Ka频段数据接收的负面影响,也为气象卫星事业高质量发展提供了技术支撑。
文摘为了提高用于更新代理模型的解集的多样性和收敛性以提高代理模型准确度,提出一种基于行列式点过程(determinantal point process,DPP)的代理模型辅助多目标进化算法(surrogate-assisted evolutionary algorithm,SAEA)。首先,提出一种基于行列式点过程的模型管理方法,从非支配解集基于行列式点过程选取子集并用真实目标函数评估,再从所有经真实目标函数评估的解中选取子集用于更新代理模型。另一方面,提出一种基于自适应行列式点过程的环境选择方法,在进化过程的早期侧重于提高种群的收敛性,在进化过程的后期侧重于提高种群的多样性。最后,基于DTLZ、WFG、MAF测试问题验证算法的有效性。将所提算法与K-RVEA、KTA2、CSEA等常用算法进行比较,使用IGD+指标进行评估。实验结果显示所提出的算法能得到更优的解集,从而证明了其高计算代价多目标优化问题上的有效性。
