Revisiting rice breeding methods – evaluating the use of rapid generation advance (RGA) for routine rice breeding

Rice production needs to increase in the future in order to meet increasing demands. The development of new improved and higher yielding varieties more quickly will be needed to meet this demand. However, most rice breeding programmes in the world have not changed in several decades. In this article, we revisit the evidence in favour of using rapid generation advance (RGA) as a routine breeding method. We describe preliminary activities at the International Rice Research Institute (IRRI) to re-establish RGA on a large scale as the main breeding method for irrigated rice breeding. We also describe experiences from the early adoption at the Bangladesh Rice Research Institute. Evaluation of RGA breeding lines at IRRI for yield, flowering time and plant height indicated transgressive segregation for all traits. Some RGA lines were also higher yielding than the check varieties. The cost advantages of using RGA compared to the pedigree method were also empirically determined by performing an economic analysis. This indicated that RGA is several times more cost effective and advantages will be realized after 1 year even if facilities need to be built. Based on our experience, and previous independent research empirically testing the RGA method in rice, we recommend that this method should be implemented for routine rice breeding in order to improve breeding efficiency.     

Bread wheat cultivar PBW 343 carries residual additive resistance against virulent stripe rust pathotype

With continuous outbreaks of stripe rust (Puccinia striiformis f. sp. tritici) epidemics and rapid breakdown of deployed resistance in bread wheat (Triticum aestivum L.) cultivars in North West Plains Zone (NWPZ) in India warrant knowledge and deployment of new and durable sources of resistance to stripe rust. Bread wheat cultivar PBW 343, until recently the most widely cultivated wheat variety in India, is now highly susceptible to stripe rust (score 9 on a 1–9 scale), whereas PBW 621 (score 5.05–5.65) and HD 2967 (score 5.40–6.20) show low levels of resistance. We conducted an experiment, spanning three crop seasons (2013–2014 to 2015–2016), in which parental lines, F₁ and F₂ populations, F₃ and F₄ families from two bread wheat crosses, PBW 621/PBW 343 and HD 2967/PBW 343 were generated and evaluated for stripe rust resistance against a virulent pathotype. While the F₁ revealed partial dominance, the segregation pattern for stripe rust resistance in F₂ and F₃ showed transgressive segregation for resistance in both crosses. Chi-square analysis indicated that resistant segregants possessed two genes, one contributed by PBW 621 or HD 2967 (depending on the cross) and the other, unexpectedly but obviously, came from the most susceptible cultivar, PBW 343. Possible genetic mechanisms for this residual resistance and implications for breeding programs are discussed.     

Genetic analysis of early-maturing maize (Zea Mays L.) inbred lines under stress and nonstress conditions

Early-maturing maize (Zea Mays L.) germplasm developed from diverse sources has the potential for use in developing maize hybrids suitable for increasing maize production in the dry ecologies of eastern Africa. A diallel study was conducted to estimate general combining ability (GCA) of 12 early-maturing maize inbred lines, identify potential single-cross hybrids for use as parents, assess genetic diversity among the inbred lines, and relate genetic distance to specific combining ability (SCA) and hybrid performance. Sixty-six F₁ diallel hybrids were evaluated under optimal and drought stress conditions at four locations in Kenya and Uganda. The parental inbred lines were genotyped using 94 single nucleotide polymorphism (SNP) markers. Additive gene action was more important than nonadditive gene action for inheritance of grain yield (GY) under optimal conditions. However, nonadditive gene effects were more important in the inheritance of GY under drought and across all environments. Inbred lines CKL0722, VL058014, and CZL0724 were among the best with positive GCA effects for GY across both optimal and drought stress conditions. The correlation between SCA and both genetic distance and F₁ GY was significant under both drought stress and across all environments. Inbred lines with desirable GCA effects for GY and other agronomic traits and hybrids with good performance under both optimal and drought stress conditions are potential parents for development of various types of high-yielding, stress-tolerant, and early-maturing hybrids.     

Genetic divergence in two tropical maize composites after four cycles of reciprocal recurrent selection

Two tropical maize composites were subjected to four cycles of reciprocal recurrent selection to develop divergent inbred lines with good combining ability. This study was conducted to examine the extent of genetic diversity, changes in allele composition and genetic structure, of 100 randomly selected S₁ lines each from the original (C₀) and advanced (C₄) selection cycles of TZL COMP3 and TZL COMP4, genotyped using single nucleotide polymorphism (SNP) markers. Results revealed that the proportion of alleles at both low and high frequencies decreased from C₀ to C₄, whereas those at intermediate frequencies increased at C₄ in the two composites. More unique and other alleles were lost at C₄ in TZL COMP3 relative to those in TZL COMP4. The changes in different measures of genetic diversity were either small or negligible with selection in the two composites. The proportion of markers departing from Hardy–Weinberg equilibrium (HWE) decreased with selection, whereas the total number of pairs of markers in linkage disequilibrium increased with selection in the two composites. Examination of changes in population structures using a model‐based approach as well as cluster and multivariate analyses found a high degree of concordance in stratifying the 400 S₁ lines into four non‐overlapping groups corresponding to the two selection cycles each within the reciprocal composites. The observed molecular‐based divergence between cycles within the same composite and the clear differentiation between the complementary composites highlight the importance of reciprocal recurrent selection for preserving genetic diversity for long‐term selection. This increases the potential of the advanced selection cycles to sustain genetic gain in productivity of hybrids adapted to the savannas in West and Central Africa.     

苹果分子标记及辅助育种研究进展

从基于集群分离分析法、杂交群体、全基因组关联分析和功能基因分子标记4个方面对苹果相关的分子标记及其在辅助育种上的应用进行了综述,为苹果分子标记辅助育种和揭示重要性状的遗传提供依据。     

New Approaches to Modeling Methyl Jasmonate Effects on Pomegranate Quality during Postharvest Storage

Adaptive neuro fuzzy inference system (ANFIS) and genetic algorithm–artificial neural network (GA-ANN) models were used to predict the effect of methyl jasmonate (at three levels 0, 0.01, and 0.1 mM) and storage time (0, 14, 28, 42, 56, 70, and 84 days) on quality parameters and physiological changes of pomegranate fruits during storage. Methyl jasmonate reduced chilling injury and improved quality characteristics of pomegranates during postharvest storage. The GA-ANN and ANFIS were fed with two inputs of methyl jasmonate and storage time. The results showed that GA-ANN predictions agreed with experimental data and the GA-ANN with 14 neurons in one hidden layer can predict physiological changes and quality parameters of pomegranate (weight loss, pH, chilling injury index, ion leakage, ethylene, respiration, polyphenols, anthocyanins, and total antioxidant activity) with correlation coefficients equal to 0.87. The ANFIS model was trained by a hybrid method and agreement between experimental data and ANFIS predictions was significant (r = 0.90).     

磁化处理的全尾砂料浆沉降参数优化模型

为了提高全尾砂料浆的脱水浓缩效果,将磁化处理技术引入到全尾砂料浆脱水浓缩中,并建立GA-SVM模型优选全尾砂料浆的沉降参数。建立支持向量机（SVM）沉降参数优化模型,以磁感应强度、磁化处理时间、料浆流速、料浆浓度、絮凝剂单耗为输入因子,沉降速度为综合输出因子,通过正交试验建立样本数据对SVM模型进行训练与检验,采用遗传算法（GA）对SVM模型参数进行优化,进而得到磁化全尾砂料浆沉降参数的GA-SVM优化模型。将GA-SVM模型运用到某铁矿磁化全尾砂料浆沉降参数优化中,得到的最佳沉降参数为磁感应强度0.192 T、磁化处理时间1.85 min、料浆速度1.92 m/s、PAC单耗28 g/t,沉降速度可达约155 cm/h。研究表明：适宜的磁化处理条件可提高全尾砂料浆的脱水浓缩效果,节约30.0%~42.5% PAC用量,GA-SVM模型对全尾砂料浆沉降参数预测结果相对误差在5%以内、预测精度高,为全尾砂料浆脱水浓缩及其参数优选提供了一种新思路。     

机采棉加工过程智能控制与试验优化

机采棉杂质含量高,多级籽棉清理和皮棉清理会造成纤维损伤,为综合提高皮棉产品的外观形态和纤维内在质量,提出了对机采棉加工工艺进行过程优化控制的研究方法和试验方案。在充分分析典型机采棉加工流程的基础上,根据最新的棉花质量检测标准,确定杂质面积、杂质颗粒数、反射率、黄度、上半部长度、长度整齐度、短纤维指数、马克隆值、断裂比强度9个参数作为优化目标,建立以加工皮棉产品成交价格最大化的总体优化控制目标。选取对棉花清理有显著影响效果的倾斜式籽清机I和II、提净式籽清机、回收式籽清机、轧花机上部、锯齿式皮清机I和II 7个关键设备的转速作为优化控制变量。采用监控层、控制层、设备层的构架模式,完成关键设备自动化升级改造。使用响应面分析法的中心组合设计试验方法建立控制变量与控制目标之间的数据模型。以建立的总体优化控制目标为适应度评价函数,利用遗传算法完成对多变量数据模型的求解,7个设备的转速分别为495、484、727、472、1 131、822、763 r/min。试验结果表明,加工后的皮棉产品杂质面积变化率降低约7个百分点,上半部长度变化率提高约2个百分点,质量较为稳定。本文方法在降低机采棉含杂率的同时,提高了棉花的综合质量水平。     

基于GA-BP神经网络的池塘养殖水温短期预测系统

为解决传统的水温小样本非实时预测方法预测精度低、鲁棒性差等问题,基于物联网实时数据,提出了遗传算法(GA)优化BP神经网络的池塘养殖水温短期预测方法,并在此基础上设计开发了池塘养殖水温预测系统,首先采用主成分分析法筛选出影响池塘水温的关键影响因子,减少输入元素;然后使用遗传算法对初始权重和阈值进行优化,获取最优参数并构建了基于BP神经网络的水温预测模型;最后采用Java语言开发了基于B/S体系结构的预测系统。该系统在江苏省宜兴市河蟹养殖池塘进行了预测验证。结果表明:该系统在短期的水温预测中具有准确的预测效果,与传统的BP神经网络算法相比,研究内容评价指标平均绝对误差(MAE)、平均绝对百分误差(MAPE)和误差均方根(MSE)分别为0.196 8、0.007 9和0.059 2,均优于单一BP神经网络预测,可满足实际的养殖池塘水温管理需要。     

马铃薯地上部绿色组织中糖苷生物碱合成调控的研究

为提高马铃薯品种(系)地上部分糖苷生物碱(SGAs)的含量,增强其抗逆性并改良块茎的品质。克隆了马铃薯茄啶鼠李糖基转移酶基因(sgt3)cDNA和1,5–二磷酸核酮糖羧化酶小亚基基因启动子(rbcS P);对sgt3亚细胞定位预测显示,该蛋白不具有叶绿体转运肽、线粒体导肽和分泌信号肽序列,推测可能位于细胞质;将克隆的sgt3 cDNA片段及rbcS重组到pCEPSP载体上,构建了具有草甘膦抗性标记的绿色组织特异表达sgt3基因植物表达载体。通过农杆菌介导法对马铃薯品种‘陇薯3号’和‘夏波蒂’进行转化,共获得了12株抗草甘膦的阳性转基因植株。对转基因植株的目的基因表达水平和SGAs含量分析发现,地上部sgt3基因相对表达量较未转化植株提高1.3~3.0倍,SGAs含量增加20%~37%,而转基因植株的块茎中SGAs含量变化不显著。本研究的结果为进一步培育枝、叶中高SGAs而块茎中低SGAs的马铃薯抗性品种提供了理论依据。