利用异源胞质雄性不育系选育不结球白菜品种翠夏

翠夏是以带有遗传标记的小白菜异源胞质雄性不育系黄苗寒青A-22为母本,以小白菜BC071为父本配制的耐热小白菜杂交品种。不育系黄苗寒青A-22不育株率达100%,不育度95%,性状稳定一致,苗期叶色表现黄色遗传标记。翠夏表现耐热、抗病、优质,具有较强的杂种优势,667m2产量4500～6200kg,目前已在国内推广种植。     

小黑麦F_1、F_2产量性状的遗传率和群体杂种优势分析

为了解小黑麦产量性状的遗传规律和群体杂种优势的表现,采用完全双列杂交试验设计,利用农艺性状的加性-显性遗传模型,分析了小黑麦15个F1、F2代组合7个主要产量性状的遗传表现。结果表明,单株产量、株高、穗下节间长、每穗粒数和千粒重的遗传率达到了显著水平,穗下节间长和株高的遗传率较高。单株产量、千粒重和株高在F1、F2代都具有很强的群体杂种优势,F2代优势比F1代降低了50%左右,F1杂种优势平均可延续1.1~2.0代,强优势组合杂种优势可延续到3代。     

CIMMYT和我国玉米种质群体的配合力及杂种优势分析

采用NCⅡ遗传交配设计,以丹340、Mo17、掖478和黄早四为测验种,通过2年1点田间试验,分析27个国内外玉米群体（14个CIMMYT热带、亚热带群体和13个国内群体）的主要性状配合力和产量杂种优势,并划分杂种优势群。结果表明,大多数CIMMYT群体的产量和产量性状配合力及杂种优势明显优于国内玉米群体,以Suwan l、Pob43、Pob21     

糯玉米淀粉RVA黏度的杂种优势分析

以糯玉米10个自交系为材料应用p+q+2pq交配设计组配了50个杂种,研究了淀粉RVA的7个黏度性状的杂种优势表现,结果表明,（1）淀粉RVA各性状均存在广泛的变异,其中以回落值的变异最大,最高的杂种达249 cP,最低的仅为122.33 cP;变异最小的是糊化温度,最高的为79.5℃,最低的为76.92℃;（2）所有性状之间的差异均杂种大于亲本,且峰值黏度、沉降值、回落值3个性状杂种平均数高于亲本;（3）沉降值存在显著的超中亲优势,峰值黏度和回落值仅存在极显著的超低亲优势,而谷值黏度、终值黏度、糊化温度和糊化时间均无杂种优势;（4）杂种与双亲淀粉RVA黏度性状之间的关系因性状而异,其中在峰值黏度、谷值黏度、沉降值、回落值四个性状上,杂种与母本、中亲值RVA参数均达到了极显著的正相关,而其余三个性状则因组合的不同而异,相关关系未达显著水平。     

用Rim2超级家族分子指纹鉴别杂交水稻及预测杂种优势

选用5对Rim2引物对21份籼稻和20份粳稻材料进行了DNA指纹扩增,共扩增出38条谱带,其中多态性谱带26条,多态性水平为69.64%;粳稻平均多态性水平为56.67%,明显高于籼稻。根据Nei’s遗传距离计算获得的聚类树状图表明,参试21份籼稻材料聚为6组,20份粳稻材料聚为7组。亲缘关系分析表明,Rim2分子指纹可以区分多数的籼稻或粳稻材料,且显示出材料的遗传特征。考察部分籼稻和粳稻杂交组合的产量对照优势与双亲间遗传距离的关系,发现杂交粳稻的遗传距离与杂交优势表现出相关性,而杂交籼稻无此相关性。     

玉米不同雄性不育胞质杂种优势分析

以3组不同的核质不育系及其保持系为材料,分别与4个高配合力的测验种测交,对测交种产量性状进行方差分析,分析不同胞质不育系类型对产量优势的影响。结果表明,T型不育系T103、DT-合344和ZT-合344所组配测交种和其保持系组配的测交种相比产量差异不显著;C型不育系85218A组配测交种的产量比保持系增产11.81%,达显著差异水平。     

超级稻Y两优2号种子萌发期及苗期中亲优势浅析

[目的]了解超级稻Y两优2号在种子萌发期和苗期的杂种优势表现,分析其杂种优势生理学基础。[方法]对杂交组合Y两优2号及其亲本的种子萌发情况和秧苗素质等主要指标进行了系统调查和研究。[结果]杂交组合Y两优2号的所测性状都表现出杂种优势,包括发芽率、发芽势、发芽指数、幼苗鲜重和幼苗干重等,Y两优2号从种子萌发开始就具有比亲本强的生长优势。苗期,无论是在室内的水培环境还是室外的大田环境,杂交组合Y两优2号在播种后20 d(DAS20)和播种后30 d(DAS30)的所有性状都表现出杂种优势,其中地上部鲜重的相对中亲优势值最高。随着幼苗生育进程的推进,Y两优2号的大部分性状在DAS30比DAS20都表现出更大的优势。[结论]Y两优2号这些生理特性的杂种优势表现为杂交水稻的植株形态建成和高产稳产奠定了良好的生理基础。     

利用单片段代换系测交群体定位玉米产量相关性状的杂种优势位点

杂种优势利用是提高农作物产量与品质的一种重要途径, 而明确杂种优势的遗传机制将促进优良玉米新品种的选育, 但是截至目前其遗传机制仍然不清楚。本研究以玉米自交系lx9801背景的昌7-2的单片段代换系为基础材料, 利用与自交系T7296的测交群体, 对昌7-2和lx9801对应染色体片段与T7296之间存在差异的杂种优势位点进行了分析, 共检测出64个不同穗部性状和产量的杂种优势位点(HL), 其中23个在2个环境中同时被检测到, 包括4个穗长的HL, 4个穗粗的HL, 4个穗行数的HL, 7个行粒数的HL和4个产量的HL, 并在多个染色体片段上鉴定出同时包含产量及其构成因子的杂种优势位点, 该研究为进一步解析玉米产量杂种优势形成的遗传机制奠定了材料基础。     

Genetic variability and heterotic groups of Brazilian popcorn populations

The development of successful advanced lines and cultivars in maize is dependent on parental selection and assignment to defined heterotic groups. So, the objectives of this study were to evaluate genetic variability and identify heterotic groups among Brazilian popcorn varieties. Thus, diallel crosses of advanced generations of the popcorn hybrids, IAC 112 and Zélia, and of three open-pollinated popcorn varieties, RS 20, Branco, and SAM were performed. Ten hybrid combinations, the five parents, and five check treatments were arranged in a block design with four replicates in two tropical-zone locations (CWb climate). Both additive and non-additive effects were important for grain yield, plant height, ear height, and husk cover. For popping expansion, only the additive effects were important. Hybrid combinations between the local variety (Branco) and F₂ populations (IAC 112 and Zelia) resulted in the third and fourth highest values for popping expansion. The best grain yields were obtained with hybrid combinations involving SAM. Cultivars Zélia, IAC 112, and RS 20 increased popping expansion, whereas cultivar Branco increased grain yield of hybrid combinations. The following conclusions may be drawn: Brazilian popcorn populations have reduced heterosis and genetic variability to popping expansion in relation commercial cultivars; there is genetic variability among Brazilian popcorn populations that allows the exploitation of additive and non-additive effects for grain yield; it is possible to increase grain yield by using local varieties; but it would be difficult to obtain commercial hybrids from local varieties because they have poor performance for popping expansion.     

Marker-based screening of maize inbred lines using support vector machine regression

The phenomenon of heterosis is widely used in hybrid breeding programmes, despite the fact that no satisfactory molecular explanation is available. Estimators of quantitative genetic components like GCA and SCA values are tools used by the plant breeder to identify superior parental individuals and to search for high heterosis combinations. Obtaining these estimators usually requires the creation of new parental combinations and testing their offspring in multi-environment field trials. In this study we explore the use of ɛ-insensitive Support Vector Machine Regression (ɛ-SVR) for the prediction of GCA and SCA values from the molecular marker scores of parental inbred lines as an alternative to these field trials. Prediction accuracies are obtained by means of cross-validation on a grain maize data set from the private breeding company RAGT R2n. Results indicate that the proposed method allows the routine screening of new inbred lines despite the fact that predicting the SCA value of an untested hybrid remains problematic with the available molecular marker information and standard kernel functions. The genotypical performance of a testcross hybrid, originating from a cross between an untested inbred line and a well-known complementary tester, can be predicted with moderate to high accuracy while this cannot be said for a cross between two untested inbred lines.