国家棉花品种区域试验纤维品质时空分布与发展趋势

本文选用2005—2014年国家棉花区域试验参试品种纤维品质性状作为试验材料,运用灰色预测法,旨在构建黄河流域、长江流域和西北内陆棉区的灰色预测模型,探索国家棉花区域试验纤维品质时空分布规律,并对未来5年和10年纤维品质发展趋势进行预测.结果表明: 10年期间国家棉花区域试验参试品种的综合纤维品质总体呈逐年提升趋势.纤维长度表现较优,分布阈值有所提高(27.0～32.0 mm),且多数品种纤维长度达到29或30 mm级.断裂比强度总体呈增强趋势,长江流域棉区比强度达到“很强”档水平(31.0 cN·tex^-1)的品种所占比例2011年达到61.1%.马克隆值在棉区间差异显著,黄河流域逐年增高,由B₂档(4.3～4.9)向C₂档(5.0及以上)变化;长江流域马克隆值偏高,基本维持在C₂档水平;西北内陆棉区马克隆值较优,分布在A档(3.7～4.2)和B₂档(4.3～4.9).纺纱均匀性指数由高到低依次为西北内陆棉区、长江流域棉区、黄河流域棉区,其中分布在130～149范围(可纺40～50中支纱)品种所占比例为80.0%.总之,近10年国家棉花品种区试验参试品种综合纤维品质总体上西北内陆棉区相对较优,其次为长江流域棉区,再次为黄河流域棉区.预测在未来5年和10年,国家棉花品种区域试验参试品种综合纤维品质表现为黄河流域呈明显下降趋势,长江流域略微上升,而西北内陆棉区则呈显著下降趋势,这些变化应该引起所在区域棉花育种工作者、国家棉花品种区域试验及审定管理部门的高度重视.     

Causality between pillars of sustainable development: Global stylized facts or regional phenomena?

Since the Brundtland report, most governments have committed themselves to sustainable development. For this purpose, different global and national organizations and institutions have tried to find the relationships, and especially causalities, between sustainability pillars, which are interesting for them from a policy point of view. With respect to their findings, some questions need to be answered before appropriate policies can be formulated. Are causalities between sustainability pillars global stylized facts or regional phenomena? Can countries with different characteristics follow the same rules, or are causalities between the pillars sensitive to the regional and intrinsic features of countries? Using principal component analysis for the construction of sustainability indicators and the Granger causality model (GMM approach) for testing the causalities between sustainability pillars in different samples, this study finds that causal patterns among the pillars of sustainability are completely sensitive to the characteristics of the countries that are grouped. Therefore, it is recommended that researchers concentrate more on homogeneous case studies and avoid generalizations of causal relationships between sets of heterogeneous countries.     

Analysis of the genetic diversity of garlic (Allium sativum L.) germplasm by SRAP

Cluster analysis and principal component analysis were used to investigate the genetic diversity of 40 garlic germplasms analyzed with 23 sequence-related amplified polymorphism (SRAP) primer combinations. A total of 130 polymorphic loci were detected among these germplasms, with an average of 5.65 polymorphic loci per SRAP primer combination. The percentage of polymorphic loci was 69.1%, whereas the mean effective number of alleles, the mean Nei's gene diversity, and the mean Shannon's information index were 1.4446, 0.2788, and 0.4365, respectively. Cluster analysis revealed that the 40 germplasms could be divided into 3 groups. The results of principal component analysis were consistent with those of unweighted pair-group method with arithmetic averages (UPGMA) clustering analysis. The Shannon-Weaver information index ranged from 0.2419 to 0.4202, indicating that the garlic germplasms had high genetic diversity.     

内蒙古78份葱属野生种表型遗传多样性分析

为了揭示内蒙古葱属野生种表型遗传多样性,采用方差分析、主成分分析、聚类分析等方法,对收集的78份野生种的种质资源14个表型性状进行了遗传多样性评价。结果表明:内蒙古葱属野生资源存在丰富的遗传多样性。(1)14个表型性状平均变异系数为43.0%,叶片宽的变异系数最大,为94.7%;种子厚的变异系数最小,为14.6%。14个表型性状在居群间的差异除叶片宽达到显著(P0.05)水平外,其余性状均表现差异不显著;(2)14个表型性状可归成为6个主成分因子,累计贡献率达到80.77%,最大程度上反映了所有78份葱属种质资源的表型特征,在前6个主成分包括的14个农艺性状中的株丛直径、叶片长、叶片宽、单株叶片数、花序长度、花序宽度和种子宽等性状是造成葱属种质资源表型差异的主要因素;(3)14个表型性状间存在显著或极显著的相关性;(4)采用欧氏距离系统聚类法将供试材料分为7大类,78份葱属种质资源基本上按种区分开,并和地理条件有一定的关系,种间和材料间表型差异很明显。本研究为内蒙古葱属资源的利用提供了科学依据。     

不同大豆品种抗旱性综合评价

选用10个不同生态类型的大豆品种,在盆栽和大田条件下进行抗旱性研究.在正常供水与水分胁迫条件下,分别测定并分析了开花结荚期与品种抗旱性有关的多项生理生态指标.把大豆各性状的抗旱系数作为衡量各单项抗旱能力大小的指标,用主成分分析将各单项抗旱系数综合成几个新的、相互独立的综合指标,再利用隶属函数求出综合指标的隶属值,可以较准确地评价各大豆品种（系）的抗旱性.通过该方法评选出两个高抗旱大豆品种晋大74号和晋大53号,评定结果符合生产实际.     

Insights from the clustering of microarray data associated with the heart disease

Heart failure (HF) is the major of cause of mortality and morbidity in the developed world. Gene expression profiles of animal model of heart failure have been used in number of studies to understand human cardiac disease. In this study, statistical methods of analysing microarray data on cardiac tissues from dogs with pacing induced HF were used to identify differentially expressed genes between normal and two abnormal tissues. The unsupervised techniques principal component analysis (PCA) and cluster analysis were explored to distinguish between three different groups of 12 arrays and to separate the genes which are up regulated in different conditions among 23912 genes in heart failure canines'' microarray data. It was found that out of 23912 genes, 1802 genes were differentially expressed in the three groups at 5% level of significance and 496 genes were differentially expressed at 1% level of significance using one way analysis of variance (ANOVA). The genes clustered using PCA and clustering analysis were explored in the paper to understand HF and a small number of differentially expressed genes related to HF were identified.     

农业生态系统综合评价与调控研究

对农业生态系统的综合评价与调控的指标体系和研究方法进行了研究，首次把综合评价与综合调控作为一个整体进行研究，并给出一套较完整的研究方法体系．研究结果及调控方案与实际吻合．     

Vector space classification of DNA sequences

Revisiting the problem of intron-exon identification, we use a principal component analysis (PCA) to classify DNA sequences and present first results that validate our approach. Sequences are translated into document vectors that represent their word content; a principal component analysis then defines Gaussian-distributed sequence classes. The classification uses word content and variation of word usage to distinguish sequences. We test our approach with several data sets of genomic DNA and are able to classify introns and exons with an accuracy of up to 96%. We compare the method with the best traditional coding measure, the non-overlapping hexamer frequency count, and find that the PCA method produces better results. We also investigate the degree of cross-validation between different data sets of introns and exons and find evidence that the quality of a data set can be detected.     

基于高频系数小波分析的高维蛋白质波谱数据特征提取

高维蛋白质波谱数据分析过程中,对于数据的特征提取一直是许多学者专注解决的问题。本文提出了一种基于高频系数的小波分析和主成份分析技术(Principal component analysis,PCA)的特征提取方法,首先采用小波分析技术对数据进行降噪,提取高频系数作为特征,之后用主成份分析技术进行降维。实验显示:本论文中提出的方法在8-7-02、4/3/02数据集上的实验识别率分别可以达到100%和99.45%,可以有效提高分类识别率。     

不同放牧强度下高寒灌丛群落特征和演替规律的数量研究

本文应用多样性指数、聚类分析等数学方法,研究了不同放牧强度下高寒灌丛群落特征的变化,用主分量分析方法,研究了不同放牧强度下高寒灌丛的演替规律。多样性分析结果表明,植物多样性指数在放牧强度为C组的草场达到最大。聚类分析结果,当相关系数R≥0.90 时,以重要值为特征的植物聚合为10类,它们分别属于植物群落不同演替阶段的建群种、优势种和伴生种。主分量分析表明,5个不同放牧强度的高寒灌丛群落聚合为3类,A和B组草场属于以灌木和杂类草为优势植物的2层结构的植物群落,C组草场属于以灌木为建群植物、杂类草和耐牧的莎草为共优势植物的2层结构的植物群落,D和E组草场属于以灌木为建群植物、禾草和莎草为共优势植物的3层结构的植物群落。     

PEG胁迫条件下41份陆地棉种质资源萌发特性研究及其抗旱性综合评价

摘要：干旱是一种广泛存在且严重影响作物及棉花的产量的一种自然灾害。本实验采用15%PEG6000竖直滤纸法对41份陆地棉种子进行萌发期抗旱性进行研究,分别测定在胁迫条件下及清水对照条件下的发芽势、发芽率、3天芽长、3天芽重、7天下胚轴长、7天胚根长、胚根长/胚芽长、芽长生长率等8个指标,结果表明,这8个指标在PEG6000胁迫条件下,均比对照降低,除3天芽重外,41个材料的变异系数均大大增加,说明陆地棉种子萌发受15%PEG6000的抑制,且材料间受抑制程度差异较大。同时计算出胁迫条件下与对照条件的相对值,通过对这8个指标的相对值进行方差分析和主成分分析,筛选出相对发芽势、相对发芽率、相对7天下胚轴长、相对7天胚根长、相对胚根长/胚芽长、芽长生长率等7个指标与陆地棉萌发期抗旱性有关。利用这7个指标对41个陆地棉材料进行隶属函数分析和相关性分析,并以平均隶属函数值代表抗旱性强弱,平均隶属函数值越大,抗旱性越强,结果表明,相对7天胚根长与平均隶属函数值存在着极显著的正相关（r=0.839**）,同时筛选出陆地棉萌发期抗旱性较强的材料有7份：冀668、鲁棉研21、9409选系、DP99B、创棉22、sGK中980、邯177,抗旱性中等的材料有10份：中23A-12、中23A抗棉F12、中棉所35、冀1286、GKZ19F6、双豫97-2067、光籽2、耐高温-2、中S9612、光籽1。 关键词：萌发期;棉花抗旱性;主成份分析;隶属函数法     

Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress

Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-00977-5.     

绿色草莓(Fragaria viridis Duch.)自交后代的生物学特性观察及评价

本文对绿色草莓（Fragaria viridis Duch.）及其自交后代5个株系的生物学特性进行了观察,其生物学特性与母本均存在一定程度差异,在观察的67个性状中,我们获得了可溶性固形物等42个差异明显的性状。利用SPSS软件对其中15个差异明显性状进行主成分分析和变异系数分析,结果表明植株高度、植株冠径、小花梗长、小花梗粗、叶柄粗、花序梗粗及花粉生活力是区分绿色草莓及其自交后代株系的重要指标。5个自交一代株系自交坐果率差异明显,其中株系Ls-S1-4属于自交不亲和最强的株系。本研究为绿色草莓自交亲和/不亲和系的创建奠定基础。     

槭树种质资源的翅果数量性状研究

为了探讨槭属树种的亲缘关系及演化趋势,对采集的68份槭树种质材料（包括27个槭属树种以及7个变种）的7个翅果性状用SAS8.0统计分析软件进行主成分分析,结果表明：前3个主成分的累计贡献率达83.9%,可分别代表翅果大小、翅果角度和产量的综合因子。另外,根据翅果的7个性状进行聚类分析,进一步明确槭属树种的亲缘关系,为槭树种质资源的研究提供了重要依据。     

粤西海域浮游植物群落结构特征的多元分析与评价

根据1998-1999年对粤西海域浮游植物的周年调查资料,本文采用主成分分析和聚类分析等多元统计分析方法研究该海域浮游植物的主要种类组成和群落结构的基本特征。研究结果表明,中肋骨条藻（Skeletonema costatum）、伏氏海毛藻（Thalassiothrix fauenfeldii）、小舟形藻（Navicula subminuscula）、颤藻（Oscillatoria sp．）、菱形海线藻（Thalassionema nitzschioides）、细弱海链藻（Thalassiosira subtilis）、齿角毛藻（Chaetoceros denticulatus）、北方劳德藻（Lauderia borealis）、中华盒形藻（Biddulphia sinensis）、纺锤角藻（Ceratium fusus）、翼根管藻（Rhizosolenia alata）、斯氏根管藻（Rhizosolenia stolterforthii）、短角弯角藻（Eucampia zoodiacu）、笔尖形根管藻（Rhizosolenia styliformis）、拟弯角毛藻（Chaetoceros pseudocurvisetus）等种类构成了粤西海域浮游植物的主体。春季、夏季和秋季该海域浮游植物可明显划分为近岸类群和近外海类群2个群落,冬季群落结构分化不显著,不形成明显的类群。各主要种类的季节演替现象十分明显。     

Systematic tuning of parameters in support vector clustering

Clustering algorithms divide a set of observations into groups so that members of the same group share common features. In most of the algorithms, tunable parameters are set arbitrarily or by trial and error, resulting in less than optimal clustering. This paper presents a global optimization strategy for the systematic and optimal selection of parameter values associated with a clustering method. In the process, a performance criterion for the optimization model is proposed and benchmarked against popular performance criteria from the literature (namely, the Silhouette coefficient, Dunn's index, and Davies-Bouldin index). The tuning strategy is illustrated using the support vector clustering (SVC) algorithm and simulated annealing. In order to reduce the computational burden, the paper also proposes an alternative to the adjacency matrix method (used for the assignment of cluster labels), namely the contour plotting approach. Datasets tested include the iris and the thyroid datasets from the UCI repository, as well as lymphoma and breast cancer data. The optimal tuning parameters are determined efficiently, while the contour plotting approach leads to significant reductions in computational effort (CPU time) especially for large datasets. The performance criteria comparisons indicate mixed results. Specifically, the Silhouette coefficient and the Davies-Bouldin index perform better, while the Dunn's index is worse on average than the proposed performance index.     

Discrimination of higher plant calluses based on embryogenic capacity and taxonomic classification by pyrolysis mass spectrometry

Pyrolysis mass spectrometry (PyMS) is a rapid, simple, high-resolution analytical method based on thermal degradation of complex material in a vacuum, and has been widely applied to the discrimination of closely related microbial strains. Minimally prepared samples of embryogenic and non-embryogenic calluses derived from various higher plants (sweet potato, morning glory, Korean ginseng, Siberian ginseng, and balloon flower) were subjected to PyMS for spectral fingerprinting. A dendrogram based on the unweighted pair group method, with arithmetic mean of pyrolysis mass spectra, divided the calluses into Siberian ginseng embryogenic callus and the others, which were subsequently divided into embryogenic and non-embryogenic callus groups, regardless of plant species from which the calluses were derived. In the non-embryogenic callus group, the dendrogram was in agreement with the known taxonomy of the plants. These results indicate that PyMS analysis could be applied for discriminating plant calluses based on embryogenic capacity and taxonomic classification.