胡芦巴的营养成分及其利用

胡芦巴为传统中药材,在我国许多地方都能种植。胡芦巴含有薯蓣皂苷元、黄酮、生物碱等多种药用成分,有降血脂、降血糖等作用。胡芦巴还含有丰富的蛋白质、油脂、多糖、维生素和矿物质等营养成分,在食品、药品、保健品、化妆品等方面有广泛用途。重点介绍胡芦巴的营养成分,为胡芦巴的进一步开发提供参考。     

Interpretation of the results of common principal components analyses

Common principal components (CPC) analysis is a new tool for the comparison of phenotypic and genetic variance-covariance matrices. CPC was developed as a method of data summarization, but frequently biologists would like to use the method to detect analogous patterns of trait correlation in multiple populations or species. To investigate the properties of CPC, we simulated data that reflect a set of causal factors. The CPC method performs as expected from a statistical point of view, but often gives results that are contrary to biological intuition. In general, CPC tends to underestimate the degree of structure that matrices share. Differences of trait variances and covariances due to a difference in a single causal factor in two otherwise identically structured datasets often cause CPC to declare the two datasets unrelated. Conversely, CPC could identify datasets as having the same structure when causal factors are different. Reordering of vectors before analysis can aid in the detection of patterns. We urge caution in the biological interpretation of CPC analysis results.     

Size correction: comparing morphological traits among populations and environments

Morphological relationships change with overall body size and body size often varies among populations. Therefore, quantitative analyses of individual traits from organisms in different populations or environments (e.g., in studies of phenotypic plasticity) often adjust for differences in body size to isolate changes in allometry. Most studies of among population variation in morphology either (1) use analysis of covariance (ANCOVA) with a univariate measure of body size as the covariate, or (2) compare residuals from ordinary least squares regression of each trait against body size or the first principal component of the pooled data (shearing). However, both approaches are problematic. ANCOVA depends on assumptions (small variance in the covariate) that are frequently violated in this context. Residuals analysis assumes that scaling relationships within groups are equal, but this assumption is rarely tested. Furthermore, scaling relationships obtained from pooled data typically mischaracterize within-group scaling relationships. We discuss potential biases imposed by the application of ANCOVA and residuals analysis for quantifying morphological differences, and elaborate and demonstrate a more effective alternative: common principal components analysis combined with Burnaby’s back-projection method.Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

普通菜豆种质资源表型鉴定及多样性分析

对646份普通菜豆核心种质在贵州毕节进行了表型鉴定,结果表明,普通菜豆具有丰富的形态性状多样性。总变异数为367,平均遗传丰富度为8.34,变异范围2~31;遗传多样性指数为0.63,变异范围为0.02~0.91。通过多变量的主成分分析,前3个主成分的贡献率较大,分别为17.73%、15.35%和11.33%。依据表型鉴定数据信息,将供试种质聚类并划分为4组。Ⅰ组的遗传多样性较高,主要为直立有限的大粒资源,大多资源属于安第斯基因库;Ⅱ组的遗传多样性最低,为直立无限生长习性的小粒资源,属于中美基因库;Ⅲ组的遗传多样性最高,主要以蔓生无限为主,包括小部分直立无限和匍匐无限的资源;Ⅳ组的遗传多样性较低,为蔓生无限生长习性、株高最高、分枝数最少的资源。筛选到大粒、多荚、长荚、宽荚等具有特异性状的种质资源35份。     

Application of bio-fertilizers for enhancing growth and yield of common bean plants grown under water stress conditions

This study was planned to enhance the growth and productivity of common bean plants (Phaseolus vulgaris L.) grown under different water stress level by using different microorganisms as bio-fertilizer agents. Water stress is a international problem that effects on morphological, functional and chemical processes of plants occasioning in altering growth, yield and water relations of economic plants like common bean plants. The interaction effect between water stress (WW as recommended irrigation after 6 days, WS1 after 12 days and WS2 after 18 days) and inoculation with different microorganisms [AMF (Glomus mosseae) and endophytic bacteria, (Bacillus amyloliquefaciens)] used alone or in mixed was examined on the development and productivity of common bean plants. Mutual application of AMF and endophytic bacteria significantly increased the average values of most of growth, water relations (photosynthetic rate, transpiration rate and stomatal conductance) and yield parameters of common bean plants grown at WS1 and WS2 comparing with non-colonized plants. In this connection, colonization with AMF and endophytic bacteria with WS1 are the greater pods number, pod length, pods weight, 100 seeds weight, Yield by ton /Fed and water-use efficiency (WUE) by ton/ m³ than other treatments. Common bean yielded seeds had significantly increased nutrients content (nitrogen, potassium, phosphorus, magnesium and calcium), vitamin B₁, Folic acid, crude protein and crude fibers at AMF + endophytic bacteria under second water stress (WS1) when compared to other treatments.     

The stability of P in coral reef fishes

The constancy of phenotypic variation and covariation is an assumption that underlies most recent investigations of past selective regimes and attempts to predict future responses to selection. Few studies have tested this assumption of constancy despite good reasons to expect that the pattern of phenotypic variation and covariation may vary in space and time. We compared phenotypic variance-covariance matrices (P) estimated for populations of six species of distantly related coral reef fishes sampled at two locations on Australia's Great Barrier Reef separated by more than 1000 km. The intraspecific similarity between these matrices was estimated using two methods: matrix correlation and common principal component analysis. Although there was no evidence of equality between pairs of P, both statistical approaches indicated a high degree of similarity in morphology between the two populations for each species. In general, the hierarchical decomposition of the variance-covariance structure of these populations indicated that all principal components of phenotypic variance-covariance were shared but that they differed in the degree of variation associated with each of these components. The consistency of this pattern is remarkable given the diversity of morphologies and life histories encompassed by these species. Although some phenotypic instability was indicated, these results were consistent with a generally conserved pattern of multivariate selection between populations.     

Investigations on the Similarity of the Structure of Two Covariance Matrices for Some Blood Pressure Data

We have two sample covariance matrices of size p × p, where p is the number of variables denoting measurements of arterial blood pressure recorded in various positions and methods for women and men. The hypothesis on equality of the two covariance matrices was rejected and we want to find, why this happened and in which covariances the two matrices differ. In § 2 we explore the primary (observed) data looking for outliers and deviations from normality. We do it by drawing χ² plots. In § 3 we look for common principal components. We use here Flury's method. We find that the data for blood pressure systolic might have a common principal axes system (P≈?0.0866), while for blood pressure diastolic this is dubious (p≈?0.0112). The variances of the first principal component found for woman are a little larger than those for men, and this fact explains the rejection of the classical test ∑₁ = ∑₂ on the equality of the two covariance matrices. After applying a common rotation to the two covariance matrices we reduce them to a nearly diagonal form. Looking at the non diagonal elements we see which covariances do not fit into the model. In § 4 we repeat the calculations from § 3 for covariance matrices calculated from the same data using robust methods.     

Combining data sharing with the master–worker paradigm in the common component architecture

Software component technologies are being accepted as an adequate solution for handling the complexity of applications. However, existing software component models tend to be specialized to some types of resource architectures (e.g. in-process, distributed environments, etc.) and/or do not provide a very high level of abstraction. This paper focuses on handling data sharing on operation invocations between components as a solution allowing applications to be efficiently executed on all kinds of resources. In particular, the data sharing pattern appears in master–worker applications, when workers need to access only a part of a large piece of data, either in read or write mode. This approach is applied to the Common Component Architecture model. Its benefits are discussed using an image rendering application.

PHYLOGENETIC ANALYSIS OF PHENOTYPIC COVARIANCE STRUCTURE. I. CONTRASTING RESULTS FROM MATRIX CORRELATION AND COMMON PRINCIPAL COMPONENT ANALYSES

Applications of quantitative techniques to understanding macroevolutionary patterns typically assume that genetic variances and covariances remain constant. That assumption is tested among 28 populations of the Phyllotis darwini species group (leaf-eared mice). Phenotypic covariances are used as a surrogate for genetic covariances to allow much greater phylogenetic sampling. Two new approaches are applied that extend the comparative method to multivariate data. The efficacy of these techniques are compared, and their sensitivity to sampling error examined. Pairwise matrix correlations of correlation matrices are consistently very high (> 0.90) and show no significant association between matrix similarity and phylogenetic relatedness. Hierarchical decomposition of common principal component (CPC) analyses applied to each clade in the phylogeny rejects the hypothesis that common principal component structure is shared in clades more inclusive than subspecies. Most subspecies also lack a common covariance structure as described by the CPC model. The hypothesis of constant covariances must be rejected, but the magnitudes of divergence in covariance structure appear to be small. Matrix correlations are very sensitive to sampling error, while CPC is not. CPC is a powerful statistical tool that allows detailed testing of underlying patterns of covariation.     

From micro- to macroevolution through quantitative genetic variation: positive evidence from field crickets

Quantitative genetics has been introduced to evolutionary biologists with the suggestion that microevolution could be directly linked to macroevolutionary patterns using, among other parameters, the additive genetic variance/ covariance matrix (G) which is a statistical representation of genetic constraints to evolution. However, little is known concerning the rate and pattern of evolution of G in nature, and it is uncertain whether the constraining effect of G is important over evolutionary time scales. To address these issues, seven species of field crickets from the genera Gryllus and Teleogryllus were reared in the laboratory, and quantitative genetic parameters for morphological traits were estimated from each of them using a nested full-sibling family design. We used three statistical approaches (T method, Flury hierarchy, and Mantel test) to compare G matrices or genetic correlation matrices in a phylogenetic framework. Results showed that G matrices were generally similar across species, with occasional differences between some species. We suggest that G has evolved at a low rate, a conclusion strengthened by the consideration that part of the observed across-species variation in G can be explained by the effect of a genotype by environment interaction. The observed pattern of G matrix variation between species could not be predicted by either morphological trait values or phylogeny. The constraint hypothesis was tested by comparing the multivariate orientation of the reconstructed ancestral G matrix to the orientation of the across-species divergence matrix (D matrix, based on mean trait values). The D matrix mainly revealed divergence in size and, to a much smaller extent, in a shape component related to the ovipositor length. This pattern of species divergence was found to be predictable from the ancestral G matrix in agreement with the expectation of the constraint hypothesis. Overall, these results suggest that the G matrix seems to have an influence on species divergence, and that macroevolution can be predicted, at least qualitatively, from quantitative genetic theory. Alternative explanations are discussed.     

The constancy of the G matrix through species divergence and the effects of quantitative genetic constraints on phenotypic evolution: a case study in crickets

Long-term phenotypic evolution can be modeled using the response-to-selection equation of quantitative genetics, which incorporates information about genetic constraints (the G matrix). However, little is known about the evolution of G and about its long-term importance in constraining phenotypic evolution. We first investigated the degree of conservation of the G matrix across three species of crickets and qualitatively compared the pattern of variation of G to the phylogeny of the group. Second, we investigated the effect of G on phenotypic evolution by comparing the direction of greatest quantitative genetic variation within species (g(max)) to the direction of phenotypic divergence between species (Delta(z)). Each species, Gryllus veletis, G. firmus, and G. pennsylvanicus, was reared in the laboratory using a full-sib breeding design to extract quantitative genetic information. Five morphological traits related to size were measured. G matrices were compared using three statistical approaches: the T method, the Flury hierarchy, and the MANOVA method. Results revealed that the differences between matrices were small and mostly caused by differences in the magnitude of the genetic variation, not by differences in principal component structure. This suggested that the G matrix structure of this group of species was preserved, despite significant phenotypic divergence across species. The small observed differences in G matrices across species were qualitatively consistent with genetic distances, whereas ecological information did not provide a good prediction of G matrix variation. The comparison of g(max) and Delta(z) revealed that the angle between these two vectors was small in two of three species comparisons, whereas the larger angle corresponding to the third species comparison was caused in large part by one of the five traits. This suggests that multivariate phenotypic divergence occurred mostly in a direction predicted by the direction of greatest genetic variation, although it was not possible to demonstrate the causal relationship from G to Delta(z). Overall, this study provided some support for the validity of the predictive power of quantitative genetics over evolutionary time scales.     

Numerical responses of an avian predator to prey fluctuations in a temperate latitude: breeders vs. entire population

Distinct numerical responses of predators to fluctuations in the abundance of their prey are often observed in northern regions but occur more rarely in temperate latitudes. This statement is, however, mostly based on observations of breeding populations, while in some predators, for example in raptors, numerous non-breeding floaters can occur. I estimated the breeding density and reproductive performance (nest survey) as well as the density of entire population (transects with distance sampling) of the common buzzard Buteo buteo in western Poland (52°N) in the years 2005–2014 to test the hypotheses that in temperate latitudes: (1) the breeding population of these birds does not show any numerical response, understood as annual changes in their abundance; (2) its reproductive success, however, changes with the abundance of main prey, the common vole Microtus arvalis; and (3) hence the entire buzzard population (including potential immature floaters) present in a given area during the nesting period responds numerically with some time delay. The reproductive success of buzzards was positively correlated with their prey abundance. Contrary to my predictions, however, the breeding population of buzzards showed a slight numerical response with a 3-year lag and the entire population tracked vole fluctuations without any time delay. The immediate numerical response of the entire buzzard population was probably caused by large-scale movements of floaters. Such rapid numerical responses of some predators may contribute to the relative stability of prey populations in temperate latitudes compared to northern regions.     

Fish-eating bird abundance in oligotrophic lakes in Kejimkujik National Park,Nova Scotia,Canada

Aquatic bird population data in 40 oligotrophic lakes and ponds in Nova Scotia, Canada indicates that only lakes > 20 ha support territorial pairs of Common Loon (Gavia immer) and only lakes 40 ha produce their young. Broods of Common Merganser (Mergus merganser americanus) occurred in lakes > 25 ha and loon and merganser broods together occurred only in lakes 80 ha. The fish production in the lakes was estimated from the total phosphorus vs fish yield relationship obtained in similar, oligotrophic lakes in Ontario. Considering the fish consumption and mergansers until fledging along with the maintenance of the adults during the same period (about 200 and 130 kg fish respectively) and the estimated fish production in these lakes, there is a close balance between the size of water body and its fish production to the occupancy and production of piscivorous birds.     

Genetics of fertility restoration in cytoplasmic male sterile Phaseolus vulgaris L.

Summary Restoration of fertility in cytoplasmic male sterile Phaseolus vulgaris by line R-351 was controlled by a single gene. The restorer gene (Fr) displayed incomplete dominance leading to partial restoration of fertility in F₁ generations; full restoration was not achieved until the F₂ generation. Once full restoration of fertility was produced in the F₂ generation, no segregation for sterility was observed in subsequent generations derived from heterozygotes Frfr, either by testcrossing (restored × maintainer) or in F₃ progenies. Implications of the irreversible nature of this restoration are discussed.Florida Agr. Exp. Sta. Journal Series No. 7733     

Inheritance of zingiberene in Lycopersicon

Summary The simple mating designs provide unbiased estimates for genetic components of variance (additive genetic variance and dominance variance) under the assumption of no epistatic effect. There is empirical evidence, however, that suggests the existence of epistatic gene effects. The triallel and double cross mating designs permit the estimation of epistatic gene effects. A systematic and mathematical approach is suggested for the estimation of variance components based on the alternate model for triallel mating design.     

普通甜荞主要数量性状相关遗传力的测定

对24个普通甜荞品种,7个主要数量性状,进行了遗传力、遗传相关和相关遗传力的测定．结果表明：株粒数与株粒重h_xy~2=0.8208,有效花序数与株粒重h_xy~2=0.6829,千粒重与株粒重h_xy~2=0.4498;株高、主茎节数,一级分枝数3个性状与株粒重的相关遗传力差异均不显著。     

小麦×天兰冰草杂种体细胞愈伤组织诱导及无性系建立

从普通小麦×天兰冰草杂种F_1的叶、茎、节、幼穗诱导出愈伤组织,建立了体细胞无性系,获得了大量试管苗并移栽成活。 愈伤组织诱导率及分化率以幼穗最高,茎、节、叶较低。完全展开的叶片不能形成愈伤组织,未伸展的幼叶能诱导出愈伤组织,分化程度越低的幼叶部位越容易脱分化。幼叶基部切段的愈伤组织诱导率可达90％以上。改良MS附加4mg/l 2,4-D、0.1mg/l KT、0.5mg/l NAA为最佳愈伤组织诱导培养基。最适宜的分化培养基为改良MS附加0.25mg/l KT、0.5 mg/l NAA、150 mg/l腺嘌呤核苷。杂种的愈伤组织诱导率及分化率高于两个亲本。杂种的愈伤组织长势旺盛,适应性强等都表现了小冰麦杂种在组织培养中的杂种优势,而且这种再生能力杂种优势可以通过无性系得到保持。