Analysis of residuals for stability assessment of rice genotypes

The analysis of residuals computes general adaptabilities (GAs) and specific adaptabilities (SAs) of genotypes similar to combining ability analysis. The residual analysis is simple and robust being based on the first-degree statistics, and is assumption-free. A unique statistic of ratio of variances (VR) of residuals for individual genotypes allows comparing their stability. The residuals analysis of genotype × environment (GE) interactions was performed for grain yield (t ha^?1) of 25 rice (Oryza sativa L.) genotypes, including two developed by marker-assisted selection for root traits quantitative trait loci (QTL), tested across 16 sites. Results were compared with the linear regression analysis for (i) full set of 16 sites showing adequacy of linear model and (ii) subset of nine-poor sites showing inadequacy of linear model. There was agreement between the two analyses for situation (i) but not for situation (ii) when the regression analysis fails because of nonlinearity but the residual analysis retains its validity.     

Ostrich meat: Production,quality parameters,and nutritional comparison to other types of meats

The poultry industry is considered one of the most efficient industries in producing animal protein. Poultry production consists of several main segments: broilers, commercial eggs, turkeys, ducks, and other poultry, including geese, guinea-fowl, pheasants, quail, and ratites. Currently, ostrich meat is marketed as a healthy red meat because it is characterized by high polyunsaturated fatty acid contents, low saturated fatty acid content, and low cholesterol level compared with red meats, such as beef, while tasting similar to lean beef. Ostrich meat contains lower sodium and higher iron contents than other kinds of meat, making it preferable to hypertensive people and those with anemia. Taken together, ostrich meat is considered as an ideal red meat for individuals seeking healthier lifestyle. Moreover, many different ostrich products, such as leather and feathers, are used by people. The current review paper considers the quality characteristics of ostrich meat, including physical traits, and compares it to other types of meats, such as bovine and other poultry meats.     

玉米脱粒破碎率关键影响因子及其最优预测模型研究

子粒破碎率高是当前中国玉米机械收获子粒的重要限制因素,解析破碎率变化原因,建立其简便预测模型是需要解决的重要问题。本文采集7个玉米品种在3个种植密度下组合的果穗,在不同子粒含水率梯度条件下开展单穗脱粒试验。种植密度在6万～9万株/hm2范围内对子粒破碎率没有影响,品种、子粒的含水率、抗侧压碎力和穿刺强度等的影响均达到统计显著水平。品种对破碎率变化的偏贡献率为12.7%,且品种的偏贡献率子粒含水率的偏贡献率抗侧压碎力的偏贡献率穿刺强度的偏贡献率,种植密度的偏贡献率接近于零。破碎率的最优预测因子是穿刺强度,预测模型:破碎率=10.25×0.990穿刺强度,满足破碎率不高于5%约束的穿刺强度值不得低于60 MPa。研究结果可为玉米破碎率预测、宜机收玉米新品种培育与鉴定、脱粒机具设计与制造提供数据支撑和技术参考。     

Quantitative trait loci mapping for yield-related traits under low and high planting densities in maize (Zea mays)

Average maize yield per hectare has increased significantly because of the improvement in high-density tolerance, but little attention has been paid to the genetic mechanism of grain yield response to high planting density. Here, we used a population of 301 recombinant inbred lines (RILs) derived from the cross YE478 × 08–641 to detect quantitative trait loci (QTLs) for 16 yield-related traits under two planting densities (57,000 and 114,000 plants per ha) across four environments. These yield-related traits responded differently to high-density stress. A total of 110 QTLs were observed for these traits: 33 QTLs only under low planting density, 50 QTLs under high planting density and 27 QTLs across both densities. Only two major QTLs, qCD6 and qWKEL2-2, were identified across low- and high-density treatments. Seven environmentally stable QTLs were also observed containing qED6, qWKEL3, qRN3-3, qRN7-2, qRN9-2 and qRN10 across both densities, as well as qRN9-1 under low density. In addition, 16 and eight pairs of loci with epistasis interaction (EPI) were detected under low and high planting densities, respectively. Additionally, nine and 17 loci showed QTL × environment interaction (QEI) under low- and high-density conditions, respectively. These interactions are of lesser importance than the main QTL effects. We also observed 26 pleiotropic QTL clusters, and the hotspot region 3.08 concentrated nine QTLs, suggesting its great importance for maize yield. These findings suggested that multiple minor QTLs, loci with EPI and QEI, pleiotropy and the complex network of “crosstalk” among them for yield-related traits were greatly influenced by plant density, which increases our understanding of the genetic mechanism of yield-related traits for high-density tolerance.     

Mapping and validation of the quantitative trait loci for leaf stay‐green‐associated parameters in maize

Functional stay‐green is generally regarded as a desirable trait of varieties in major crops including maize. In this study, we used an F_3:4 recombinant inbred line population with 165 lines from a cross between a stay‐green inbred line (Zheng58) and a model inbred line (B73) using 211 polymorphic simple sequence repeat markers to map quantitative trait loci for three stay‐green‐associated parameters, chlorophyll content, photosystem II photochemical efficiency and stay‐green area, at maturity stage, detected a total of 23 quantitative trait loci (QTL) on nine chromosomes. Single QTL explained 3.7–13.5% of the phenotypic variance. Additionally, we validated some important stay‐green QTL using a heterogeneous inbred family approach and found that the stay‐green‐associated parameters were significantly correlated with the plant yield. This study may contribute to a better insight into the regulatory mechanism behind leaf stay‐green in maize and a novel development of elite maize varieties with delayed leaf senescence through molecular marker‐assisted selection.     

普通菜豆籽粒大小与形状的QTL定位

普通菜豆是世界上最重要的食用豆类作物之一,其籽粒大小和形状与产量及外观品质密切相关。本研究以来自安第斯基因库的大粒品种龙270709和来自中美基因库的小粒品种F5910配置杂交组合,获得的F2分离群体分别在哈尔滨大田与北京昌平温室种植,对百粒重、粒长、粒宽、粒厚、长宽比和长厚比6个籽粒性状进行了相关性分析和QTL定位。相关性分析表明,百粒重与粒长、粒宽、粒厚、长宽比、长厚比5个衡量籽粒大小和形状的性状均显著正相关。利用基于完备区间作图方法的Ici Mapping 4.1进行QTL定位,哈尔滨环境下定位到38个与百粒重、粒长、粒宽、粒厚、长宽比、长厚比相关的QTL,表型贡献率介于2.39%~17.37%之间,分布在除第1染色体外的其余10条染色体上;北京昌平环境下定位到21个上述性状的QTL,表型贡献率介于5.92%~22.53%之间,分布在第1、第3、第6、第7、第8、第9和第11染色体上。其中,百粒重QTLSW7与SW7’,SW6.1与SW6’,粒长QTLSL6.1与SL6.1’,粒厚QTLSH11与SH11’在2个环境下的标记区间重叠或者重合,SW7、SW6.1、SL6.1、SW6’和SL6.1’的表型贡献率在10%以上。     

多叶苜蓿自交二代农艺性状分析

多叶苜蓿(Medicago sativa L.)的形态特征与苜蓿的产量和品质有直接关系,建立多叶苜蓿自交系进一步研究评估苜蓿多叶性状的遗传特性和规律,为多叶苜蓿新品系的选育提供科学依据。筛选多叶苜蓿自交亲本,进行亲本选配,田间试验观察测量多叶苜蓿自交S2代的多叶率、株高等农艺性状,与亲本材料进行比较分析。发现多叶苜蓿自交S2代农艺性状变异较为丰富,变异系数达19.54%~55.66%,分离出单株多叶率达100%的单株,S2群体生长速率变缓,多叶性状的表达呈多样化。     

青藏高原东北部3种野豌豆植物学特性及资源储量

采用野外定点法、最小样方法和统计学方法对生长于青藏高原东北部的3种野豌豆属植物的植物学特性、生态环境、群落数量特征及资源储量进行研究。结果显示,救荒野豌豆、山野豌豆和三齿萼野豌豆的植物学特性、生态环境和群落数量特征具有一定差异,3种野豌豆在青海省的资源总储量分别为0.46×10~6、0.23×10~6、0.27×10~6 kg,表明3种野豌豆属植物的资源总量在青海省并不高,应对其进行有效的引种驯化,实现人工繁育和增加资源储量,这既可保护青海省甚至青藏高原的生态环境,也可对其资源进行有效地保护和合理开发利用。     

外源硒处理对优质地方水稻品种产量及稻米硒氮磷钾含量的影响

旨在研究外源硒处理对不同类型优质地方常规稻产量及硒氮磷钾含量的影响。以籼稻品种(‘泰选1号’)和粳稻品种(‘粳选1号’)为材料,采用完全随机设计,于较高海拔山区试验田(800 m以上)进行不同浓度硒处理试验。结果表明:施用外源硒处理后不会降低两个品种的稻谷产量;随外施硒浓度的提高,两个水稻品种精米及米糠硒含量均显著提高,粳稻品种在0~15 g/hm2外源硒浓度范围内随硒浓度的增加,精米中硒含量的增加率呈较高的线性模式增长;而高浓度硒处理下,粳稻精米率、整精米率显著降低;随外施硒浓度的增加,水稻精米中氮钾元素含量与硒含量从极显著正相关变为极显著负相关。在硒浓度较低的环境下,适当增加氮、钾肥的施用量能促进水稻对硒元素的吸收积累,高浓度反之。因此,对优质地方常规稻外施硒以提高品质与硒元素积累的研究是可行的。     

Genetic analysis for sow stayability at different parities in purebred Landrace and Large White pigs

Genetic parameters for sow stayability were estimated from farrowing records of 10,295 Landrace sows and 8192 Large White sows. The record for sow stayability from parity k to parity k + 1 (k = 1, …, 6) was 0 when a sow had a farrowing record at parity k but not at parity k + 1, and 1 when a sow had both records. Heritability was estimated by using single-trait linear and threshold animal models. Genetic correlations among parities were estimated by using two-trait linear–linear and single-trait random regression linear animal models. Genetic correlations with litter traits at birth were estimated by using a two-trait linear–linear animal model. Heritability estimates by linear model analysis were low (0.065–0.119 in Landrace & 0.061–0.157 in Large White); those by threshold model analysis were higher (0.136–0.200 & 0.110–0.283). Genetic correlations among parities differed between breeds and models. Genetic correlation between sow stayability and number born alive was positive in many cases, implying that selection for number born alive does not reduce sow stayability. The results seem to be affected by decisions on culling made by farmers.