Variance component estimations and allocation of resources for breeding sweetpotato under East African conditions

In Africa, average sweetpotato storage root yields are low and breeding is considered to be an important factor in increasing production. The objectives of this study were to obtain variance component estimations for sweetpotato in this region of the world and then use these to determine the efficiency of variety trials and breeding systems. From an incomplete series of variety trials in Kenya and Uganda (comprising 15 genotypes, three locations, two crop durations and three seasons) variance components were estimated ‐ using the REML method ‐ for the following traits: storage root yield, biomass production, harvest index, storage root dry matter and the Elston index which was used to aggregate all four traits. The storage root yield of clones across all 12 environments ranged from 15.2 to 33.0 t/ha. The variance components were significant for all traits, except the genotype by season interactions for storage root dry matter. The efficiency of selection systems was determined for total test capacities of 450 and 900 plots and using not more than five locations. Two‐stage selection was 17‐81% more efficient than one‐stage selection after two seasons of testing. Two‐stage selection was optimized under the restriction of using at least two locations at step 1. Trials with two locations and one replication at step 1 and five locations and two replications at step 2 were appropriate both for selecting for storage root yield and for simultaneously selecting for storage root yield, biomass production, harvest index and storage root dry matter content by using the Elston index. There are indications that such an allocation of resources for breeding sweetpotato is also appropriate for other regions in Sub‐Saharan Africa.     

Analysis of sugar cane variety trials. I. Components of variance and genotype-environment interactions

Summary Surgarcane variety trial data from Barbados and Jamaica were analysed by the analysis of variance. From these analyses, components of variance were estimated in an attempt to quantify genotype x environment interactions. Sixteen sets of trials from Barbados and eight from Jamaica were analysed. The results show that GE effects in both countries were small. It is suggested, on the basis of these analyses that variety trials could use resources more efficiently by growing them at fewer sites, since the absence of site x variety interaction makes each site equally effective for identifying the best genotypes.     

Replicate allocation to improve selection efficiency in the early stages of a potato breeding scheme

Field data and simulation were used to investigate replication within trials and the allocation of replicates across trial sites using partial replication as an approach to improve the efficiency of early-stage selection in a potato breeding programme. Analysis of potato trial data using linear mixed models, based on four-plant (clonal) plots planted as augmented partially-replicated (p-rep) designs, obtained genetic and environmental components of variation for a number of yield and tuber components. Heritabilities, trial-to-trial genetic correlations and performance repeatability of clonal selections in p-rep trials and in subsequent fully replicated trial stages were high, and selection was effective for the economically important traits of marketable tuber yield and tuber cooking quality. Simulations using a parameter-based approach, pertaining to the variance components estimated from the p-rep field trials, and the parametric bootstrapping of historic empirical data showed improved rates of genetic gain with p-rep testing over one and two locations compared with testing in fully replicated trials. This potato breeding study suggests that the evaluation and selection of a clonal field crop in fully replicated trials may not be optimal in the early stages of a breeding cycle and that p-rep designs offer a more efficient and practical alternative.     

Comparison of stability statistics for yield and quality traits in bread wheat

The stability and genotypic mean of four traits, grain yield, grain protein content, alveograph W and bread volume, were evaluated in three multi-location trials, each covering two years. The stability of each genotype was evaluated by environmental variance (s² _E), interaction variance (s² _W) and variance of the ranks of the phenotypic values corrected for the genotypic effect (s² _R). The bootstrap method was used to study correlations between the genotypic mean and the three stability statistics and to calculate their accuracy. The repeatability of the stability statistics was measured by correlations between the values obtained in each of the two years. In addition, theoretical smaller trials were generated by random sampling and the stability values calculated were correlated with those of the original trial. Environmental variance appears to be usable both for yield and for quality traits, but there is a risk of counter-selecting a high genotypic mean of W. Whatever the trait and statistic envisaged, stability is poorly repeatable and its evaluation requires several years and a large number of locations per year to minimise sampling and environmental effects. This revised version was published online in August 2006 with corrections to the Cover Date.     

Contributions to the Analysis of Genotype × Environment Interactions: Experimental Results of the Application and Comparison of Clustering Techniques for the Stratification of Field Test Sites

The results from multienvironment field performance trials of cultivars are usually analysed as two‐way classification data with rows=genotypes/cultivars and columns=environments (locations and/or years). To reduce the impact of genotype × environment interaction effects, one commonly stratifies genotypes/cultivars or environments by cluster analysis techniques into homogeneous groups so that interactions within groups are minimized. By such a stratification, for example of test sites, with regard to similarity of genotype × environment interactions and the selection of only one representative test site from each group, the overall number of necessary test sites for yield trials can be reduced. In the literature, many clustering techniques have been proposed. Systematic comparisons between different cluster methods, however, are rather rare. A single cluster method is characterized by `measure of distance', `stopping criterion', `algorithm' and `level of significance'. In this paper, 11 clustering techniques were applied to extensive yield data sets of several agricultural crops (faba bean, fodder beet, oat, winter oilseed rape and sugar beet) from the official registration trials of the German `Bundessortenamt'. The results were compared with each other using two proposed parameters: measure of resemblance (for two classifications) and cluster size (for one classification). Neither the level of significance nor the algorithm has a substantial impact on the resulting clusters. The final results of clustering are therefore mainly determined by the stopping criterion with its associated measure of distance. If one uses tests for crossover interactions as stopping criteria, the resulting clusters are larger than the resulting clusters for the F‐test of conventional interactions in an analysis of variance. The cluster size decreases with increasing sensitivity of the tests that are used as stopping criteria. Finally, recommendations for the choice and handling of clustering techniques for practical applications are given.     

Optimum allocation of plots to years,seasons, locations,and replications,and its application to once-over-harvest cucumber trials

Summary Large experiments and breeding trials are often conducted over years, seasons (or planting dates), and locations, and with replication (blocks). This is costly and time-consuming, but it is usually deemed necessary to sample a range of environments. In this paper, we describe a general approach to optimum allocation of sampling effort, and apply it to once-over-harvest cucumber trials. Two criteria for optimality are considered: minimizing the variance of a genotype (or treatment) mean, and minimizing cost per unit information. Costs could include penalties for delaying a breeding program. Thus, costs may depend on the goal, as well as the size, of the experiment or breeding trial.We found that efficient allocation of resources favors using more years and/or season, with fewer locations and/or replications. Using more years with fewer locations and/or replications is suggested when genotypes are to be evaluated by yield alone. When both yield and quality variables are of interest, as is likely, using more seasons with fewer locations and/or replications is recommended.Paper No. 11302 of the Journal Series of the North Carolina Agricultural Research Service, Raleigh, North Carolina, USA 27695–7601.     

Effect of environmental variables on performance of Jerusalem artichoke (<Emphasis Type="Italic">Helianthus tuberosus</Emphasis> L.) cultivars in a long term trial: a statistical approach

Tuber yield, together with tuber number and size are the basic agronomic and breeding traits in Jerusalem artichoke and can be significantly affected by environmental factors. We report the results of a long term trial on the performance of 20 Jerusalem artichoke cultivars. The random model for means with restricted maximum likelihood (REML) procedure was used to estimate the overall effects of the genotype, environment and genotype by environment interaction on traits. The partial least square regression (PLSR) model was used for modeling genotype by environment interaction variance components with a set of available correlated environmental variables. The REML variance component estimates model revealed that tuber number and yield are more dependent on GE interaction which allowed identification of best genotypes for specific environments. The PLSR model revealed that the most important climatic variables for optimal emergence, canopy development, high tuber number and yield are adequate soil and air temperatures in April. For larger tuber mass, precipitation variables and even distribution of rainfall were the most important factor, together with soil and air temperature in June when tuber growth is initiated. The knowledge obtained in this study is valuable for the identification and understanding of key environmental factors that contribute to the performance of Jerusalem artichoke.     

玉米区域试验中误差方差的异质性及其对品种评价的影响

为了研究我国玉米区域试验中误差方差的异质性存在状况及其对品种评价的作用, 以2003-2006年东北和华北16组玉米区域试验资料为依据,对玉米区域试验各环境试验误差方差差异状况及误差方差同质模型和异质模型的拟合效果进行了验证,并对品种效应差异显著性测验在误差同质模型和误差异质模型分析结果的差异状况进行了比较。结果表明,在分析的所有试验中,试验误差方差在环境间具有较大差异;误差方差异质模型比误差方差同质模型对试验数据拟合效果普遍较好;模型是否考虑误差方差的异质性对品种-环境交互效应测验结果有较大影响,而对品种主效应测验结果影响极小;误差方差异质模型比误差方差同质模型测验效率高。     

Interaction of common beans cultivars of the black group with years, locations and sowing seasons

The objectives of this study were to assess which environmental factors (local, season or years) are the most important to contribute for the interactions with genotypes of common black beans and to verify the existence of genotypes with broad and/or specific adaptation to the diverse planting seasons in Central Brazil. Data of grain yields for 13 genotypes in 18 field trials used for cultivar registration were utilized, across 2?years (2003 and 2004). Analyses of variance were carried out with decomposition of the genotype x environment interactions. Firstly, data of 18 trials were used, allowing a partial isolation of factors and, subsequently, eight trials were used to allow a complete isolation of the factors. The genotype x sowing seasons (R²?=?4.2?%) and genotype x year (R²?=?4.1?%) interactions were of the greatest important, while genotype x location was less important (R²?=?3.0?%). It was concluded that is more important to conduct evaluations of genotypes in different seasons and years rather than in different locations. The majority of the genotypes tested presented specific adaptation, although it was possible to identify superior lines with wide adaptation.     

Genotypic yield responses of lowland rice in high-altitude cropping systems

Rising global mean temperatures open opportunities in high-altitude production systems for temperature-sensitive crops such as lowland rice. Currently, the cropping window for rice in higher altitudes is still narrow, and thus, genotypes that tolerate a certain degree of chilling are needed to achieve their potential yield. Final yield depends on the interaction between genotype and environmental conditions. Exposing the genotype to a wide range of environments is a way to evaluate its adaptability into an expanding cropping calendar. Over a 2-year period, an experiment was conducted in lowland rice systems in Madagascar at two locations differing in altitude. Twenty genotypes with contrasting levels of tolerance to low temperature were sown monthly in a non-replicated rice garden trial. Plant development was monitored and yield and yield components were determined. Yield stability across the different growing environments was investigated. While crop duration was affected by sowing dates and altitude, yield was mainly determined by sowing date. Panicle number per m² and number of spikelets per panicle were the most limiting factors for yield potential in mid-altitude, while in high altitude, yield was mainly limited by spikelet fertility. Resulting cropping calendar and genotype recommendations are discussed.     

Baking quality of hard winter wheat: Response of cultivars to environment in the Great Plains

Inconsistency of wheat end-use quality has long been a problem for the milling and baking industries, which require high levels of uniformity for modern, high speed, processing. Extensive research was conducted to characterise genetic, environmental, and biochemical factors that contribute to variation in wheat quality. Samples from 17 locations of trials with 30 cultivars grown over two years were evaluated for grain quality, milling yield, mixograph parameters and baking properties. Protein quality and composition of flour samples were determined by SDS sedimentation and size-exclusion chromatography. Test sites were monitored for soil fertility, and meteorological data was collected hourly during grain fill. Additional grain samples and data were collected from six cultivars grown at 11 locations in 1993. Significant variation in end-use quality was observed among samples; variation was attributed to environmental effects, genotype, and their interactions. For many mixograph and baking parameters, variation attributed to environmental effects was of greater magnitude than for genotype. Increasing levels of low molecular weight (LMW) saline soluble proteins were related to a general decline in dough mixing properties and loaf characteristics. However, correlations of protein components with baking parameters were generally low, suggesting limited predictive value. Hours of high temperature stress (>32 °C) during grain fill were associated with loaf volume and SDS sedimentation volume, although in a curvilinear fashion. Increasing temperature stress initially had a positive influence on loaf volume and protein quality; however, when temperature stress exceeded 90 hours, there was a strong negative influence on baking quality. Variation among cultivars for environmental stability was indicated and cultivar responses to temperature stress varied. Relationships with meteorological data suggest opportunities to predict wheat end-use quality through environmental modelling. This revised version was published online in August 2006 with corrections to the Cover Date.     

Effect of region on the uncertainty in crop variety trial programs with a reduced number of trials

Results from crop variety trials may vary between geographical regions because of differences in climate and soil types. Results are usually presented at regional level. To evaluate the importance of the regions used in the Swedish variety trial programs, we examined which regions produced similar levels of yield and similar ratios in yield between cultivars; the amount by which variance could be reduced by division into regions or clusters of regions; and the amount of trials per region and year, replicates per trial, and trials per year required in order to fulfill specifications on the precision of results. Yield data from spring barley and winter wheat trials performed during 1997–2006 were studied using cluster analysis and variance component estimation. The objectives were (1) to discuss the effects of regions on precision when the number of trials has decreased; (2) to demonstrate the method; and (3) to report the results obtained. In spring barley, clusters of regions produced different levels of yield, but similar yield ratios between cultivars. In winter wheat, clusters of regions giving different yield ratios were identified. When the option of a single analysis was compared with that of region-wise analysis, the reduction in variance with the former, due to the larger number of trials, outweighed the reduction in variance with the latter due to decreased random interaction between trials and cultivars.     

A method of choosing locations based on genotype × environment interaction for regional trials of rice

An ideal test location with particular environmental conditions should generate a relatively large genotype × environment interaction (GE) value in regional trials. A method of selecting test locations based on GE was proposed. Using the statistic D_j, the ranking of ability to discriminate the best genotypes for locations could be obtained. The locations among the group with the smallest D_j value were deleted from the whole set step by step, and the number of locations was reduced to a rational level at which most (over 85%) of the GE sum of squares of trials were maintained. A comparative evaluation based on data collected from Zhejiang Province (China) rice regional trials showed that the new method was more feasible than two other methods without loss of accuracy and reliability.     

我国棉花品种区域试验重复次数和试点数量的设计

农作物区域试验重复次数和试点数量设置直接影响试验的遗传力和品种选择效率。本研究以2000-2014年期间长江流域、黄河流域和西北内陆棉区国家棉花区试数据为资料,依据各棉区的试验发展现状和试验遗传力随着试点数量的变化,分析重复次数和试点数量设置的合理性,提出各棉区试点数量的设置方案。结果表明: (1)我国棉花品种区域试验采用3次重复是保证试验效率的充分条件;(2)长江流域和黄河流域国家棉花区试现行的试点数量设置已经可以充分满足试验的遗传力要求,西北内陆棉区的试点数也符合遗传力达到0.75的基本要求;(3)由于棉花区域试验对品种的推荐审定和应用十分重要,试验过程中也可能会因田间管理、自然灾害或其他异常情况导致试验报废,为充分保证试验的可靠性,长江流域棉区可保持当前20个左右的试点数量,遗传力即可达到0.90的水平;黄河流域和西北内陆棉区可以分别将试点数量增加到27个和19个左右,遗传力达到0.90和0.85的水平。该结果为国家棉花区域试验的优化配置提供理论依据,也为其他作物区域试验布局提供参考。     

Estimates of variance components and repeatability for total forage yield in rye: implications for breeding

Cereal rye (Secale cereale L.) is an important forage crop in the USA for stocker cattle (Bos sp.) production, thus making forage yield an important breeding objective for the crop. However, little information is known about the repeatability for forage yield in this crop. The objectives of this research were to: (i) estimate variance components for forage yield from long‐term variety trials, (ii) estimate the repeatability for forage yield and (iii) relate this to breeding strategies for increased forage yield in rye. Trials were conducted over 14 years where 97 USA open‐pollinated varieties (OPVs) were evaluated. Repeatability ranged from 0.57 to 0.86 when the data were analysed by year for the 3 years with significant genotype main effects. Possible explanations for the lack of significant genotype main effects are discussed. Practical implications of these findings indicate that the development of improved cultivars with greater forage yield will require improved methods of selection based on family performance rather than the current methods based primarily on single plant visual selection.     

Factors affecting the genotype × environment interaction in spring triticale grown in a Mediterranean environment

The identification of the genotypic and environmental factors responsible for the genotype by environment interaction is essential in any breeding program. A Multi Environmental Trial (MET) including 3 years, 3 locations and 14 lines of spring triticale (× TriticosecaleWittmack) was carried out in a Mediterranean environment (Sardinia, Italy). Water available to the crops was calculated through a model run with the environmental variables and the phenological data recorded in each environment. Yield, yield components and heading date were used to perform an Additive Main effects and Multiplicative Interaction (AMMI) analysis. Interaction for yield was relevant only in 2 environments out of 8, one characterised by a late sowing, the other by the warmest pre-anthesis period. Correlations between Interaction Principal Component Axis (IPCA) scores and environmental and genotypic variables showed that genotype by environment interaction for yield and kernels per m² is related to interaction for phenology but not to the yield level. Yield level was significantly correlated with the water availability. Genotype by environment interaction for yield is mainly determined by thermal conditions in the pre-anthesis period, genotypic photoperiodic sensitivity and sowing time. This revised version was published online in August 2006 with corrections to the Cover Date.     

应用GGE双标图分析我国春小麦的淀粉峰值粘度

将原始数据减去各试点均值后形成的数据集中只含基因型主效G和基因型与环境互作效应GE, 合称GGE. 对GGE做单值分解, 以第一和第二主成分近似, 按第一和第二主成分值将所有品种和试点绘于同一平面图即形成GGE双标图. 以其分析我国春麦区10个试点20个品种淀粉糊化特性的峰值粘度, 结果表明铁春1号在大部分试点峰值粘度表现较好,     

棉花区试中品种多性状选择的理想试验环境鉴别

农作物品种选育通常需要对多目标性状综合选择,依据育种目标性状和权重建立品种选择指数,选择遗传差异鉴别力强和目标环境代表性好的试验点,有助于提高品种选育的效率并降低实验成本。本研究依据国家棉花品种审定标准构建针对性和实用性强的品种选择指数,即SI=0.40?皮棉产量+0.13?纤维比强度+0.09?(纤维长度+马克隆值)+0.11?抗枯萎病+0.09?抗黄萎病+0.10?霜前花率,采用GGE双标图方法,对2000—2013年间39组(含585个单点试验)长江流域国家棉花区域试验中的15个试验点,综合评价品种选择指数的鉴别力、代表性和理想指数。结果表明,湖北黄冈和江苏南京试验环境被评为最理想的试验环境,湖北荆州、湖北武汉和江苏盐城为理想的试验环境,而河南南阳、湖北襄阳、湖南常德、四川简阳和四川射洪试验环境为不理想试验环境。可以看出,理想的试验环境均位于长江流域的中下游棉区,而不理想的试验环境中四川简阳和四川射洪位于上游的四川盆地、河南南阳和湖北襄阳位于长江流域北缘的南襄盆地、湖南常德虽然位于长江流域中游但栽培密度偏低。本研究构建的选择指数采用与国家棉花品种审定中品种评价准则相统一的目标性状和权重分配策略,理想试验环境对我国长江流域棉区的棉花生态育种试验点的选择提供了切实可行的决策方案。     

Contributions to the Analysis of Genotype × Environment Interactions: Comparison of Different Parametric and Non-parametric Tests for Interactions with Emphasis on Crossover Interactions

The objective of this study was to compare five statistical procedures (analysis of variance, the Azzalini/Cox test, the Hildebrand procedure, the Kubinger approach, and the de Kroon/van der Laan technique) for the analysis of genotype × environment interactions in cross‐classified data sets from cultivar performance yield trials with rows = cultivars and columns = environments (locations and/or years). The procedures Hildebrand, Kubinger and de Kroon/van der Laan are non‐parametric methods based on ranks, while analysis of variance and the Azzalini/Cox test proceed from the original absolute yield data. These very different statistical techniques were applied to extensive data sets from German official registration trials (1985–1989) with winter oilseed rape (Brassica napus L.), faba bean (Vicia faba L.), oat (Avena sativa L.), fodder beet (Beta vulgaris L.) and sugar beet (Beta vulgaris L.). The Azzalini/Cox and de Kroon/van der Laan methods are based on the crossover concept of interaction (different rank orders) while the other methods are based on the usual concept of interaction (deviations from additivity of main effects). For an analysis of usual interactions the procedures Hildebrand, Kubinger and analysis of variance are approximately equivalent. For the crossover concept of interaction, the Azzalini/Cox approach is recommended, especially if one is particularly interested in rank changes between environments within genotypes.     

Analysis of the genotype-by-environment interaction of spring barley tested in the Nordic Region of Europe: Relationships among stability statistics for grain yield

Variation in agronomic and quality characteristics was investigated in 220 Nordic spring barley cultivars across distinct environments (6 locations during 3 years) in the Nordic Region of Europe. The objectives of this research were to determine the importance of the genotype by environment interaction in all characteristics evaluated and to establish the relationship among different stability statistics for grain yield. Combined analysis of variance across locations indicated that both environments and genotype by environment interactions influenced significantly the cultivar phenotypes for all characteristics, irrespective of their type (row number) or earliness. The first two interaction principal component axes of the additive-main-effects-and-multiplicative-interaction (AMMI) model accounted together between 35% and 75% of the total genotype-by-environment interaction for all characteristics. Grain yield was, on average, higher in 2-row than in 6-row cultivars, which were significantly earlier in heading and grain maturity than the former. However, in some of the most northern locations, 6-row barley cultivars significantly outyielded on average 2-row barley lines. The genotype by location interaction variance (σ² _GL) accounted by each genotype was significantly associated to the deviation from regression (Tai's λ) while the coefficient of regression (β) was significantly correlated to the IPCA1 and IPCA2 of the AMMI model in 2-row, 6-row and early barley cultivars. This revised version was published online in August 2006 with corrections to the Cover Date.