QTL-based analysis of genotype-by-environment interaction for grain yield of rice in stress and non-stress environments

Use of DNA-based markers can accelerate cultivar development in variable cultivation environments since, in contrast to phenotype, DNA markers are environment-independent. In an effort to elucidate the genetic basis of genotype-by-environment interaction (G × E) for yield of rice (Oryza sativa L.), the associations between 139 AFLP markers and grain yield were determined for rice grown in fresh water (EC of 0.65 dS m⁻¹) and saline conditions (EC of 4–8 dS m⁻¹) with 0 kg ha⁻¹ or 100 kg ha⁻¹ nitrogen fertilizer in the years 2000 and 2001. A population of recombinant inbred lines of rice, developed from an IR29 × Pokkali cross, was used in the study. Both genotype × salinity and genotype × nitrogen level interactions were significant, with the genotype × salinity interaction being stronger. Through multiple regression analysis using a stepwise procedure for selecting markers, 36 markers were detected for grain yield in the four test conditions and of these 28 were detected in only one test condition implying strong environmental specificity for yield QTL expression. However, the fact that eight QTLs were detected in more than one test condition points to the existence of wide-adaptability genes in this cross. Markers with significant associations with yield explained between 37% and 48% of the yield variation in each test condition. Superior genotypes of rice were identified in all four test conditions based on their marker signatures. Furthermore, across N fertilizer regimes, yield predicted from summed additive effects of QTLs were significantly correlated with observed yield in the same year and across years. Thus marker-assisted selection can help breeders overcome the problem of low selection efficiency encountered during phenotypic selection for yield in stress environments.     

Evaluation of genotype, environment, and genotype-by-environment interaction for capsaicinoids in Capsicum annuum L.

The response, in terms of capsaicinoid content, of chile (Capsicum annuum L.) genotypes to different environments was studied. Double haploidlines, an F₁ hybrid, and an open-pollinated cultivar estimated the genotype, environment, and genotype-by-environment interaction effect on the total capsaicinoids and on individual capsaicinoids. Significant differences were observed among the genotypes and among genotype-by-environment interactions over the environments. Among the genotypes in an environment, the within-genotype variances were also significantly different. The double haploid line, HDA 207, had low within-genotype variance for individual and total capsaicinoids, with the exception of the isomer of dihydrocapsaicin. Also for HDA 270, the genotype-by-environment interaction was negligible for individual and total capsaicinoids, Indicating stability across environments. This revised version was published online in July 2006 with corrections to the Cover Date.     

Limited contribution of water availability in genotype-by-environment interaction in sugarcane yield and yield components

Water deficit is an important abiotic stress factor limiting sugarcane production. Understanding the effect of water deficit on cane yield, yield components and genotype × environment (G × E) interaction can aid in selecting genotypes that are adapted to water deficit conditions. In this study, response of cane yield and yield components of 10 sugarcane genotypes grown under 3 irrigation treatments—fully irrigated, semi-irrigated and rainfed—was examined across 3 locations and 3 crop-years within each location. Cane yield reduced by 32% and 9% in the rainfed and semi-irrigated treatments, respectively, compared to the fully irrigated treatment. Genotypic variation was highly significant for cane yield and yield components in all three irrigation regimes. Cane yield in the rainfed treatment showed significant genetic correlation with stalk diameter (r_g = 0.68), leaf number (r_g = 0.64), node number (r_g = 0.67) and stalk number (r_g = 0.68). Genotype × irrigation variance was negligible compared to genotype, genotype × location and genotype × crop-year variances. Commercial genotypes had higher yield in most environments except in low-yield potential environments, which caused a significant genotype × location × irrigation effect, suggesting opportunities for improving sugarcane productivity in these environments.     

Analysis of genotype-by-environment interaction for grain yield of rainfed durum wheat genotypes in warm winter areas of Iran

This study was performed for pattern analysis of genotype-by-environment (GE) interaction on 20 durum wheat genotypes grown in 15 testing environments during 2004–06 in Iran. Combined analysis of variance showed significant genotypes (G), environments (E), and GE interactions (P < 0.01), with environmental main effects being the predominant source of variation, followed by GE interaction. The results showed various patterns of genotype responses to different environment groups and assisted in structuring the durum wheat testing locations with identification of two major-environment groups with high genotype discrimination ability. The locations (Gachsaran and Ilam) corresponding to warm and semi-arid aresa were similar in genotype discrimination and showed no association with the other testing locations (Gonbad, Moghan, and Khoramabad) representing the Mediterranean area, indicating they differ in rankings of genotypes. The top-yielding genotypes, G13, G14 and G9, were highly adapted to warm and semi-arid environments, but those corresponding to the Mediterranean area had a high ability to discriminate the genotypes G16, G11, and Saimareh. The stability and adaptability of specific genotypes were assessed by plotting their nominal grain yields at specific environments in an ordination biplot, which aided in the identification of environment groups. Appropriate check genotypes for all environments or for specific environments were also identified. Pattern analysis allowed a sensible and useful summarization of GE interaction data set and helped to facilitate selecting superior genotypes for target-growing sites.     

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.     

Mixed models including environmental covariables for studying QTL by environment interaction

The study of the phenotypic responses of a set of genotypes in their dependence on the environment has always been an important area of research in plant breeding. Non-parallelism of those responses is called genotype by environment interaction (GEI). GEI especially affects plant breeding strategies, when the phenotypic superiority of genotypes changes in relation to the environment. The study of the genetic basis of GEI involves the modelling of quantitative trait locus (QTL) expression in its dependence on environmental factors. We present a modelling framework for studying the interaction between QTL and environment, using regression models in a mixed model context. We integrate regression models for QTL main effect expression with factorial regression models for genotype by environment interaction, and, in addition, take care to model adequately the residual genetic variation. Factorial regression models describe GEI as differential genotypic sensitivity to one or more environmental covariables. We show how factorial regression models can be generalized to make also QTL expression dependent on environmental covariables. As an illustrative example, we reanalyzed yield data from the North American Barley Genome Project. QTL by environment interaction for yield, as identified at the 2H chromosome could be described as QTL expression in relation to the magnitude of the temperature range during heading. This revised version was published online in July 2006 with corrections to the Cover Date.     

Genotype x environment interaction for root traits in maize,as analysed with factorial regression models

Summary The efficiency of genotopic and climatic characteristics in accounting for the interaction between genotypes and environments has been assessed in a three-year trial involving a set of genotypes presenting a range of root morphology characteristics (number and size). Climatic information on rainfall and temperature was recorded during the experiments, together with extra data on the growth and development of the genotypes. Their effects have been tested in factorial regression models.Climatic covariates were very powerful in accounting for the genotype by year interaction as well as the year main effect alone. For the number of adventitious roots on internode 7, the main effect of year could be described as a linear function of the average temperature and precipitation that occurred during the period of root initiation and growth. For internode 6, no clear conclusion was possible. For the root traits studied, 74 to 98% of the interaction could be explained by one climatic covariate. The regression coefficients can be considered as measures of genotypic stability.The genotypic covariates describing aerial development performed rather poorly, compared with environmental ones, even though the physiological and functional relationships between root and shoot are well known. Neither genotype main effect nor genotype by year interaction could be described sufficiently by factorial regression. Still, the genotypic covariates performing best clearly differed between root counts and size. Also the best genotypic covariates differed for main effect and interaction.     

Multiplicative models for cultivar by location interaction in testing sugar beets for resistance to beet necrotic yellow vein virus

Summary Sugar beet cultivars were evaluated for resistance to beet necrotic yellow vein virus (BNYVV) on various locations in two consecutive years. Resistance levels of cultivars were measured by virus assays of plants from the field and the greenhouse. Infection levels in the fields were characterised by sampling plants of a susceptible indicator cultivar. For each year, statistical analyses were performed on two-way tables of cultivar by location for yield and quality parameters. In analysis of variance (ANOVA) significant main effects and significant cultivar by location interaction were found for all parameters (P<0.05). Interactions were further investigated by multiplicative models. In the Additive Main effects and Multiplicative Interaction effects (AMMI) model, interaction was written as the product of a cultivar score and a location score. Cultivar interaction scores were highly correlated to virus concentrations of the cultivars, and location interaction scores to virus concentrations of the susceptible indicator cultivar. Main effects of cultivars and locations were less clearly related to virus concentrations than interaction effects. In general, virus concentrations of plants from a greenhouse test gave higher correlations than virus concentrations of plants from the field. In the factorial regression model, virus concentrations were incorporated in the model. The model can be understood as a two-way ANOVA, with greenhouse virus concentrations and virus concentration of the indicator cultivar as concomitant variables on the cultivar and location factor. Results of analyses with both multiplicative interaction models showed that interactions of all yield and quality parameters can be described in terms of virus concentrations. Therefore, the relative performance of susceptible and partially resistant cultivars in infested fields can be estimated by means of three independent parameters, (i) the level of resistance determined in a greenhouse experiment, (ii) the yield and quality in non-infested fields, and (iii) the level of infection in the field.Abbreviations AMMI model Additive Main effects and Multiplicative Interaction effects model - ANOVA analysis of variance - BNYVV beet necrotic yellow vein virus - ELISA enzyme-linked immunosorbent assay - -amino N -amino nitrogen - K Kalium (potassium) - Na Natrium (sodium)     

Challenges and opportunities for conservation of forest genetic resources

Increased use of forest resources and a shrinking forestland base threaten the sustainability of forest genetic resources and highlight the importance of conservation and sustainable management of these resources. As forest trees are normally the keystone species of forest ecosystems, their continued existence is essential for many floral and faunal associations of these ecosystems. Major concepts, challenges and opportunities for conservation of forest genetic resources are briefly discussed in this paper. The major challenges include population decline and population structure changes due to forest removal and conversion of forest land to other uses,forest fragmentation, forestry practices, climate change, disease conditions,introduced pests, atmospheric pollution, and introgressive hybridization. Developing scientifically sound conservation strategies, maintaining minimum viable population sizes, and deployment of genetically engineered organisms represent other important challenges in conservation. The usefulness of various biochemical and molecular genetic markers, adaptive traits, and genetic diversity measures for developing conservation strategies for in situ and ex situ genetic resource conservation are also discussed. Major opportunities for conservation of forest genetic resources include: use of molecular genetic markers and adaptive traits for developing conservation strategies; in situ conservation through natural reserves,protected areas, and sustainable forest management practices; ex situ conservation through germplasm banks, common garden archives, seed banks, DNA banks, and tissue culture and cryopreservation; incorporation of disease, pest, and stress tolerance traits through genetic transformation;plantation forestry; and ecological restoration of rare or declining tree species and populations. Forest genetic resource conservation and resource use should be considered complementary rather than contradictory to each other. This revised version was published online in July 2006 with corrections to the Cover Date.     

Low complexity rate control scheme for real-time video coding

Considering the deficiency of H.264 rate control scheme and the coding efficiency requirements for real-time encoding,a low complexity rate control algorithm in MB-layer is proposed..MAD is predicted by combining motion vector and the temporal and spatial correlation to reduce the complexity of G012-MAD prediction algorithm from linear regression to the complexity of the weighted average. For the rate-distortion model,the linear model with low computational complexity instead of the quadratic fitting algorithm in G012 is used,while the possibility of is discussed combining with SSIM. For the fluctuation of the PSNR of the coded image with large movement,the determination of QP in GOP layer and the bit allocation of P frame are improved,and the current quantization parameter is adjusted by making full use of the information of coded MBto control the rateeffectively. The experimental results show that the algorithm is more effective in resisting the fluctuation of PSNR for smoothly output sequence,and can decrease computational complexity.     

Challenges and opportunities for developing maize cultivars in the public sector

Maize (Zea mays L.) breeding programs integrating pre-breeding with cultivar development are needed. The objectives of the North Dakota corn breeding program are to adapt exotic and unique germplasm, maximize the genetic improvement of adapted germplasm, and develop unique short-season products for breeding and commercial use. This applied program has significant support from state maize grower organizations, farmers, food and fuel processors, and industry. As a result 25 inbred lines and 17 improved populations, carrying unique alleles not present in the B73 line and the Nested Association Mapping population (NAM) genomes, were released in the past 10 years and six hybrids were identified for commercial purposes. These included the first releases from our NDSU EarlyGEM program to increase the genetic diversity of U.S. northern hybrids and break environmental margins. These are not registered nationally due to exclusive agreements with industry. The strategic location of this research program allows the exploitation of challenging environmental conditions making evolution toward desirable goals faster, discarding unstable and weak maize varieties effectively. There are still several challenges to be addressed though. Retailer companies offer fewer products with more events making maize more vulnerable due to similar genetics. The confidential nature of the maize business limits breeding rights to develop better industry products, which currently reduces the breeding efficiency to identify the most outstanding hybrids for farmers across regions. Maize research, development, and production in marginal regions can be uniquely positioned to lead breeding research for climate changes and the development of the next generation of genetically broad-based elite products. Improvements in intellectual property and re-thinking of breeding rights access are encouraged.     

用于齿面扭曲消减的齿向修形曲线设计方法

针对蜗杆砂轮磨消减齿面扭曲时存在成本高、效率低等问题,探讨在设计阶段消减齿面扭曲的途径。首先,基于蜗杆砂轮磨齿时的接触迹分析,给出了一种齿面扭曲的计算方法,分析了鼓形量及螺旋角对扭曲量的影响;其次,提出一种常用鼓形齿修形曲线的改进设计方法,将修形曲线分成三段,分别计算齿向左右两段各处扭曲量。在满足齿轮设计要求的前提下,通过调整三段曲线的比例因子以及各处的鼓形量,实现齿面扭曲量的消减。计算实例表明,该方法可有效消减齿面扭曲现象,减小齿向修形误差。     

早龄期混凝土蠕变模型比较

针对早龄期混凝土的蠕变松弛特性,以配比、强度以及不同加载龄期的混凝土蠕变试验数据为依据,对比研究了CEB-FIP模型、Muller模型、B3模型与笔者所建立变系数四参数Burgers模型的蠕变预测差异。研究结果表明:常用经验模型中,CEB-FIP模型具有较好的适应性,Muller模型对于高强混凝土的蠕变预测较好,基于固化理论的B3模型对于早龄期混凝土的蠕变预测值偏大,准确性较差。对比研究验证了变系数四参数Burgers模型中参数的物理意义与经验取值范围及其合理性与适用性。     

Exploring soybean management options for environments with contrasting water availability

Soybean is commonly cultivated under rainfed conditions being water availability the main constraint. We evaluated the performance of different managements under contrasting water availability to test possible trade‐offs among managements, and to determine physiological variables explaining these yield differences. Four treatments were designed through specific combinations of cultivar, row spacing and stand density. They were classified as stress tolerance or yield potential strategies and were evaluated under two contrasting water availability treatments. Treatments ranged from 349 to 954 mm total water availability. Water stress treatments yielded 72% and 59% of the well‐watered treatment each year, similar to frequent soybean water stress levels for our production region. Management treatments showed significant yield differences (p < 0.05), but the management × water availability interaction did not (p = 0.42). No management option helped reduce negative water stress effects. Highest yields were achieved using 0.25 m row spacing, a stand density of 60 pl per m², and a high yield potential genotype. Yield variations were explained by differences in harvested seeds per unit area (R² = 0.75; p < 0.001) and total N uptake at maturity (R² = 0.93; p < 0.001) across environments. Because management strategies specifically tailored to cope with water shortages showed limited value, farmers need to target yield potential management options.     

棉秆循环利用理论模式探讨

摘要：棉花秸秆是重要的农作物秸秆之一。综合考虑了棉秆的生物、物理和化学特性,并将国内外棉秆利用现状进行了分析汇总后,得出了棉秆循环利用的理论模式,集中在工业化利用、农畜牧业利用和能源利用三个方面,其中棉秆作为能源利用是前景最广阔的利用方式。     

Significance of host complexity and diversity for race-specific leaf-rust resistance in self-fertile synthetic rye populations

Leaf rust (Puccinia recondita Rob. ex. Des.) is the most frequently occurring leaf disease in German winter rye (Secale cereale L.). To test the usefulness of race‐specific resistance genes, the effects of increased host diversity and complexity by producing two‐ and four‐line synthetics from inbred lines carrying different resistance genes were analysed. Thirty‐three synthetics along with two full‐sib families and one hybrid variety were tested in 17 environments in Germany under natural infections. For comparison, the parent lines of the synthetics were evaluated in 11 environments. Only two synthetics and the full‐sib families were resistant across all environments. Observed resistance levels of the synthetics were highly correlated (r = 0.83, P = 0.01) with those predicted from the parental values. Host complexity had a minor effect in two‐line synthetics only. In conclusion, the effectiveness of race‐specific leaf‐rust resistances among environments, and increasing the host complexity and diversity does not lead to a higher resistance level than that expected from the resistances of the parents.     

Urban poverty alleviation strategies in Yogyakarta,Indonesia: Contrasting opportunities for community development

A multidimensional understanding of poverty includes the access of poor groups to decision‐making processes based on their needs and aspirations. However, the realisation of this ‘right to make decisions’ faces multiple obstacles. Over the last 20 years in Indonesia, in a context of a more democratic political environment and policy decentralisation, poverty alleviation policies have followed institutional arrangements to provide communities with opportunities for greater participation in development projects. Poverty data show a clear improvement in the living conditions of urban poor citizens in Indonesia; however, it is unclear whether poor communities have become stronger and more independent from public grants and better able to make their own decisions. This research analysed two urban poor communities in Yogyakarta, Indonesia, and found that some communities working on participatory poverty alleviation strategies still face obstacles to becoming more independent and making their own decisions because they remain part of an historical legacy of top‐down approaches to poverty, highly dependent on government support and working only within ‘invited spaces’. Conversely, those communities with more limited access to government funding have been more innovative in their strategies and have created ‘invented spaces’ for collective action that allows them to be more independent and empowered.     

广西特定蔗区甘蔗专用肥配方初探

应用广西旱地甘蔗模式施肥公式及参数,确定适合特定蔗区崇左、驮卢、扶绥、宁明等糖厂蔗区施用的甘蔗专用肥配方为总养分29.8%,N、P、K配比为8-11.8-10。经田间肥效验证试验结果表明,施用29.8%甘蔗专用肥、30%普通复混肥和常规施肥（CK）甘蔗平均公顷有效茎数(条)分别为61650、60150、61350,平均公顷产量分别为102435kg、91530kg、84345kg,平均蔗糖分分别为14.49%（绝对值,下同）14.30%、14.06%;施用29.8%甘蔗专用肥比30%普通复混肥和常规施肥（CK）的农业纯收入公顷分别增加1962.9元和3256.2元