Correlation and Principal Component Analysis on Main Agronomic Traits of New Waxy Corn Varieties

[Objective] This study was conducted to provide certain theoretical reference for the comprehensive evaluation and breeding of new fresh waxy corn vari- eties. [Method] With 5 good fresh waxy corn varieties as experimental materials, correlation analysis and principal component anatysis were performed on 13 agronomic traits, i.e., plant height, ear position, ear weight, ear diameter, axis diameter, ear length, bald tip length, ear row number, number of grains per row, 100-kernel weight, fresh ear yield, tassel length, and tassel branch number. [Result] The principal component analysis performed to the 13 agronomic traits showed that the first three principal components, i.e., the fresh ear yield factors, the tassel factors and the bald top factors, had an accumulative contribution rate over 87.2767%, and could basically represent the genetic information represented by the 13 traits. The first principal component is the main index for the selection and evaluation of good corn varieties which should have large ear, large ear diameter but small axis diameter, i.e., longer grains, larger number of grains per ear, higher, 100-grain weight and higher plant height. As to the second principal component, the plants of fresh corn varieties are best to have longer tassel and not too many branches, and under the premise of ensuring enough pollen for the female spike, the varieties with fewer tassel branches shoud be selected as far as possible. From the point of the third principal component, bald tip length affects the marketing quality of fresh corn, and during fariety evaluation and breeding, the bald top length should be control at the Iowest standard. [Conclusion] The fresh ear yield of corn is in close positive correlation with ear weight, 100-grain weight, ear diameter, number of grains per row and ear length, and plant height also affects fresh ear yield.

Correlation, Principal Component and Grey Relation Analysis of Sweetpotato Root Biological Traits

[Objective] This study was conducted to explore the internal relationship among root biological traits of sweetpotato, as well as the regularity in their formation and differentiation. [Method] The root traits of 10 sweetpotato cultivars were measured through hydroponic culture in a greenhouse and field survey, and then their correlations were analyzed by statistical methods. [Result] The root morphological traits of sweetpotato at seedling stage such as projected area, surface area, average diameter and volume processed the highest contribution rate （80.56%） 10 d after transplanting, and the contribution rate of root average diameter reached 27.79% 20 d after transplanting. Storage root fresh weight per plant shared extremely significant positive correlations with storage root fresh weight of penultimate node and storage root fresh weight of antepenultimate node, and a significant positive corre- lation with commercial storage root number, and a significant negative correlation with storage root number of penultimate node. Among them, the correlation coeffi- cient of storage root fresh weight per plant with storage root fresh weight of antepenultimate node was the highest （0.659 5）. Fifteen days after transplanting, storage root fresh weight per plant had significant negative correlations with root projected area, surface area and volume. There was a significant positive correlation between root dry weight and storage root fresh weight per plant 25 d after transplanting. Root dry weight, volume, length, average diameter of sweetpotato seedlings had higher relational degrees with storage root fresh weight per plant. Ten and twenty days after transplanting were important time for the growth and differentiation of sweetpotato roots. In addition, node length and planting depth had certain influence on sweetpotato yield, and direct relationship existed between the seedling root biological traits and storage root yield of sweetpotato. [Conclusion] The results provide theoretical support for standard cultivation and new variety breeding of sweetpotato.

Genetic Variation Analysis, Correlation Analysis and Principal Component Analysis on Agronomic Traits of Summer Sowing Soybean (Glycine max Merr.) in Huang-Huai-Hai Region

Genetic variation analysis, correlation analysis and principal component analysis were conducted to investigate the relationship between 12 yield-related agronomic traits of 87 summer sowing soybean eultivars in Huang-Huai-Hai region. According to the experimental results, effective branch number showed the maxi- mum variation coefficient and growth duration showed the minimum variation coefficient. The variation coefficient of bottom pod height, pod number per plant, grain number per plant, grain weight per plant and 100-grain weight of semi-determinate summer sowing soybean ranged between 18.38% -27.56. The variation coeffi- eient of plant height, bottom pod height, pod number per plant, grain number per plant and grain weight per plant of determinate summer sowing soybean ranged from 21.02% to 8.04%. In semi-determinate summer sowing soybean, yield showed extremely significantly positive correlation with grain number per pod, grain weight per plant and 100-grain weight, but extremely significantly negative correlation with effective branch number and significantly negative correlation with growth duration. In determinate summer sowing soybean, yidd showed extremely significantly positive correlation with stem diameter but significantly positive correlation with bottom pod height, while it showed no significant correlation with other agronomic traits. Principal component analysis of yield-rdated agronomic traits showed that cumulative contribution rates of the former four principal components to the variation of seml-determinate and determinate summer sowing soybean were 79.92% and 79.50%, respectively. Agronomic traits with the greatest variation should be selected first. Semi-determinate and determinate summer sowing soybean individu- als in Huang-Hnai-Hai region should be selected according to different podding habits. In addition, semi-determlnate soybean varieties with moderate plant height and growth duration, fewer effective branches, more grains per pod and greater 100-grain weight should be selected; determinate soybean varieties with thicker stem diameter, higher plant height and bottom pod height, more nodes on main stem, fewer grains per pod, more pods per plant and grains per plant should be selected.

Study on Segmented Correlation in EEG Based on Principal Component Analysis

In order to explore the correlation between the adjacent segments of a long term EEG, an improved principal component analysis(PCA) method based on mutual information algorithm is proposed. A one-dimension EEG time series is divided equally into many segments, so that each segment can be regarded as an independent variables and multi-segmented EEG can be expressed as a data matrix. Then, we substitute mutual information matrix for covariance matrix in PCA and conduct the relevance analysis of segmented EEG. The experimental results show that the contribution rate of first principal component(FPC) of segmented EEG is more larger than others, which can effectively reflect the difference of epileptic EEG and normal EEG with the change of segment number. In addition, the evolution of FPC conduce to identify the time-segment locations of abnormal dynamic processes of brain activities,these conclusions are helpful for the clinical analysis of EEG.

Correlation Analysis and Principal Component Analysis of Eight Agronomic Traits of Autumn Broad Beans (Vicia faba L.)

[Objectives] This study was conducted to give play to the yield-increasing potential of new broad bean varieties. [Methods] The correlation analysis and principal component analysis of eight main agronomic traits of 15 autumn-sown broad bean varieties in 2017-2018 were carried out. [Results] There were extremely complicated correlations between the agronomic traits. Among the various agronomic traits, the number of pods per plant showed a significant negative correlation from the number of seeds per pod(P<0.05), and significant negative correlations with pod length and 100-grain weight(P<0.01). The number of seeds per pod was significantly positively correlated with pod length(P<0.01). The 100-grain weight of broad beans was significantly positively correlated with the pod length(P<0.01), and was significantly negatively correlated with the number of pods per plant(P<0.01). Three principal components were established by principal component analysis, and the contribution rate of the first principal component was the highest, which was 40.18%. The contribution rates of the second principal component and the third principal component to the total variance were 24.08% and 13.55%, respectively. The score equations of the principal components were derived. [Conclusions] This study provides a theoretical reference for the application and promotion of new varieties of autumn broad beans.

Analysis of the Employment Situation of Non Private Enterprises in Various Regions of China

In the past 30 years, Chinese enterprises have been a hot topic of discussion and concern among the general public in terms of economic and social status, ownership structure, business mechanism, and management level. Solving the problem of employment for the people is an important prerequisite for their peaceful living and work, as well as a prerequisite and foundation for building a harmonious society. The employment situation of private enterprises has always been of great concern to the outside world, and these two major jobs have always occupied an important position in the employment field of China that cannot be ignored. With the establishment of the market economy system, individual and private enterprises have become important components of the socialist economy, making significant contributions to economic development and social progress. The rapid development of China’s economy, on the one hand, is the embodiment of the superiority of China’s socialist market economic system, and on the other hand, it is the role of the tertiary industry and private enterprises in promoting the national economy. Since the 1990s, China’s private enterprises have become a new economic growth point for local and even national countries, and are one of the important ways to arrange employment and achieve social stability. This paper studies the employment of private enterprises and individuals from the perspective of statistics, extracts relevant data from China statistical Yearbook, uses the relevant knowledge of statistics to process the data, obtains the conclusion and puts forward relevant constructive suggestions.

Operation Risk of Rural Cooperative Economic Organization Based on Principal Component Analysis——A Case of Sichuan Province,China

Based on the previous research,a total of 10 risk indices are selected according to the specific situation in Sichuan Province,such as natural risk,resource constraint risk,internal management risk,capital risk,technical input and output risk,market risk,contract credit risk,property risk and policy support risk.According to the questionnaire survey by cooperative economic organization of Sichuan Province,principal component analysis is used to analyze the importance and influence degree of the operation risk of rural cooperative economic organization.Result shows that in the operation of cooperative economic organization,management risk has greater influence degree and importance degree,which should be paid special attention to.Capital,property,price fluctuation,and quality of members have great degree of risk and are paid little attention to.The technical input and output risk and the contract credit risk have relatively low impact on the operation risk of cooperative economic organization and their importance is relatively low.Therefore,we should continue to maintain its advantages.Nature,resource constraint and policy support have relatively high risk awareness and low influence degree,belonging to the factors with priority attention which are controlled to some extent.Finally,suggestions are put forward,such as enhancing the management level of cooperative economic organizations,strengthening the farmer's risk awareness,and improving the risk aversion ability of cooperative economic organization.

The Establishment of Mathematical Models for the Composition Analysis and Identification of Ancient Glass Products

Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on.

Analysis and Evaluation of Nutritional Quality in Chinese Radish (Raphanus sativus L.)

Radish （Raphanus sativus L.） is an important vegetable crop worldwide. High nutritional quality was critical in its genetic improvement and production. The nutritional quality of 42 Chinese radish cultivars was analyzed in this study. The contents of six nutritional facts, dry matter （DM）, crude fiber （CF）, total soluble sugar （TSS）, vitamin C （Vc）, protein, and nitrate, ranged from 29.7 to 88.2, 4.507 to 18.546, 2.233 to 15.457, 0.1416 to 0.3341, 0.34 to 1.15, and 1.81 to 5.89 g·kg^-1 fresh weight （FW）, respectively. Significant differences among the 42 radish cultivars were detected in the contents of nutritional facts. The data were subjected to cross-correlation analysis and principal component analysis （PCA）. It was found that DM content was positively correlated with the content of TSS （r=0.7104）, Vc （r=0.4011） and protein （r=0.4120）. Vitamin C （Vc） content of radish showed a positive correlation （r = 0.3300） with the protein content. According to the principal component analysis, out of the 42 radish cultivars, Nau-17, Nau-28, Nau-6, Nau-11, Nau-10, Nau-27, and Nau-31 were detected with very high scores in comprehensive evaluation. It could be concluded that abundant diversity of nutritional fact content occurred in different radish genotypes, and PCA analysis was effective for selecting radish germplasm with high quality. The results could contribute useful knowledge of nutritional quality, and provide important germplasms for the elite cultivar development and the inheritance study of nutritional facts in radish.

Statistical Analysis of Leaf Water Use Efficiency and Physiology Traits of Winter Wheat Under Drought Condition

Five statistical methods including simple correlation, multiple linear regression, stepwise regression, principal components, and path analysis were used to explore the relationship between leaf water use efficiency （WUE） and physiological traits （photosynthesis rate, stomatal conductance, transpiration rate, intercellular CO2 concentration, etc.） of 29 wheat cultivars. The results showed that photosynthesis rate, stomatal conductance, and transpiration rate were the most important leaf WUE parameters under drought condition. Based on the results of statistical analyses, principal component analysis could be the most suitable method to ascertain the relationship between leaf WUE and relative physiological traits. It is reasonable to assume that high leaf WUE wheat could be obtained by selecting breeding materials with high photosynthesis rate, low transpiration rate, and stomatal conductance under dry area.

Analysis of Main Climatic Factors Affecting Potato Yields of Western Guizhou

The climatic factors affecting potato yields in western Guizhou were analyzed by using the way of grey correlation degree and principal component analysis.The average yield of potato from 1978 to 2008 in western Guizhou was used as the sequence of numbers for reference.And the climatic factors including accumulated temperature(≥5 ℃),average temperature,precipitation,sunshine hours,daily average maximum temperature and daily average minimum temperature from March to August of potato at growth stage were used as the series for comparison.The results showed that the three integrative factors including temperature,moisture and light had a synergistic effect on potato production.The heat factor played a leading role in potato production with abundant light and ample water supply.Gray correlation analysis and principal component analysis could be used to estimate the influence factors of potato yield in western Guizhou.Very good agreement was found between the evaluation results obtained by the above-mentioned two methods.

Analysis on the Influencing Factors of Low-carbon Economy and Its Mitigation Countermeasures in Sichuan Province

[Objective]The study aimed to analyze the influencing factors of low-carbon economy and its mitigation countermeasures in Sichuan Province.[Method]Taking Sichuan Province as an example,an extended STIRPAT model was established firstly,then the impacts of population,economy and technology on carbon emissions from 2000 to 2009 were analyzed econometrically by using the principal component analysis method.Finally,some corresponding countermeasures to reduce carbon dioxide emissions were put forward.[Result]At present,population scale had the greatest influence on carbon emissions in Sichuan Province,then energy consumption per industrial added value and the proportion of industrial added value to GDP.In addition,the influence of population scale on carbon emissions was still greater than that of population structure,and technical factor also has certain explanatory power on carbon emissions.Some countermeasures,like controlling population growth,advocating low-carbon life style and consumption model,paying more attention to the strategic adjustment of industrial structure to gradually reduce the proportion of high-carbon industries,encouraging energy consumption and emissions reduction plus scientific and technological innovation in a new energy technology filed,could be adopted to reduce carbon dioxide emissions,so as to adjust to the development of low-carbon economy in Sichuan Province.[Conclusion]The research could provide references for the establishment of policies for reducing carbon emissions.

Nonlinear Dynamic Analysis of MPEG-4 Video Traffic

The main research motive is to analysis and to veiny the inherent nonlinear character of MPEG-4 video. The power spectral density estimation of the video trafiic describes its 1/f^β and periodic characteristics.The priraeipal compohems analysis of the reconstructed space dimension shows only several principal components can be the representation of all dimensions. The correlation dimension analysis proves its fractal characteristic. To accurately compute the largest Lyapunov exponent, the video traffic is divided into many parts.So the largest Lyapunov exponent spectrum is separately calculated using the small data sets method. The largest Lyapunov exponent spectrum shows there exists abundant nonlinear chaos in MPEG-4 video traffic. The conclusion can be made that MPEG-4 video traffic have complex nonlinear be havior and can be characterized by its power spectral density,principal components, correlation dimension and the largest Lyapunov exponent besides its common statistics.

Determination and Multidimensional Analysis of 22 Kinds of Inorganic Elements in Leontopodium franchetii Beauv. from Different Production Areas

[Objectives]To determine the content of inorganic elements in Leontopodium franchetii Beauv. from different production areas, and provide a reference for quality control, safety assessment, and clinical application of L. franchetii Beauv.. [Methods] The contents of Al, B, Ba, Ca, Cd, Cu, Fe, K, Mn, Mo, Na, Ni, P, Pb, Si, Sn, Sr, Ti, V, Zn, Hg, Cr in the sample of L. franchetii Beauv. were determined by the wet digestion and technique of inductively coupled plasma optical emission spectrometry(ICP-OES), and the principal component analysis was carried out for the determination results. [Results] A total of 20 inorganic elements were detected from the samples of L. franchetii Beauv. from different production areas, among which the contents of Ca, Al, P and Fe were higher. There were significant differences among different elements, and samples of different production areas show similar distribution patterns of main elements. Correlation analysis shows that 17 elements had an extremely significant positive correlation and 19 elements had a significant positive correlation. According to the principal component analysis, B, Ca, K, Mn, Mo, Pb, Sn, Sr, Fe, Ni, Ti, V, Zn, Al, and Cd were characteristic inorganic elements of L. franchetii Beauv. [Conclusions] This method is simple, rapid and accurate, and can be used for the analysis and determination of inorganic elements in L. franchetii Beauv., and provides a theoretical basis for better development and utilization of L. franchetii Beauv.

Principal Component-Discrimination Model and Its Application

Having researched for many years, seismologists in China presented about 80 earthquake prediction factors which reflected omen information of earthquake. How to concentrate the information that the 80 earthquake prediction factors have and how to choose the main factors to predict earthquakes precisely have become one of the topics in seismology. The model of principal component-discrimination consists of principal component analysis, correlation analysis, weighted method of principal factor coefficients and Mahalanobis distance discrimination analysis. This model combines the method of maximization earthquake prediction factor information with the weighted method of principal factor coefficients and correlation analysis to choose earthquake prediction variables, applying Mahalanobis distance discrimination to establishing earthquake prediction discrimination model. This model was applied to analyzing the earthquake data of Northern China area and obtained good prediction results.

Analysis of Chaotic Characters for the Monthly Runoff Se-ries at Fudedian Station in Liaohe Bain

The evolution of monthly runoff is affected both by climate environment and human activities, and its characteristics play an important role in runoff prediction and simulation. In this paper, the G-P and the principal component analysis method, which are both based on the reconstruction theory of the phase space, are used to study the chaos characteristics of the monthly runoff series at Fudedian station in Liaohe basin. The results show that the monthly runoff series have a large probability of chaos.

Variation and Statistic Analysis of Agronomic Traits of Recombinant Inbred Lines of Brassica juncea L.

Correlation analysis and principal component analysis( PCA) were conducted for some agronomic traits of 139 recombinant inbred lines of Brassica juncea L. The results showed that under the environmental conditions in Guiyang,the flowering time,number of seeds per silique,plant height and thousand seed weight differed significantly among different lines. The results of principal component analysis showed that the lines could be classified into three groups. The results of Pearson correlation tests showed that the plant height was positively correlated with the flowering time( P < 0. 05),and the thousand seed weight was negatively correlated with the flowering time and number of seeds per silique( P < 0. 01).

Factor-Cluster Analysis and Effect of Particle Size on Total Recoverable Metal Concentration in Sediments of the Lower Tennessee River Basin

Total recoverable concentration of five elements of concern: Aluminum, Iron, Manganese, Arsenic and Lead (Al, Fe, Mn, As, Pb) were measured by inductively coupled plasma atomic emission spectrometry, and mass spectrometry. The results show that sediment texture plays a controlling role in the concentrations and their spatial distribution. Principal Component Analysis and Cluster Analysis were used to analyze the grain sizes of the sediments. Result of texture analysis classified the samples into three main components in percentages: sand, silt, and clay. Significant differences among the element concentrations in the three groups were observed, and the concentrations of the elements in each group are reported in this study. Most of the elements have their highest concentrations in the fine-grained samples with clay playing an important role, in comparison with the sand component of the soil/sediment samples. There appears to be a strong correlation between samples with high silt, and clay content with the areas of elevated concentrations for Al, Fe, and Mn. There was a strong correlation between aluminum and lead with clay;lead with silt;and sand with manganese, aluminum, and lead. However, there was no strong relationship between the soil textures and iron or arsenic. All elements measured were statistically significant (at P ≤ 0.05) by watershed. The upland areas, and depositional areas’ spatial variation of element concentrations in the sediments were also observed, which was in line with the spatial distribution of the grain size and was thought to be related to the watersheds hydrological dynamics.

Research on Liquor Storage Based on Statistical Analysis Model

According to the physical and chemical indexes of different periods,different storage containers and different storage sites,a two overall T test was used to show that there were significant differences in physical and chemical indexes of liquor body in different detection sites.Correlation analysis of wine storage in different storage methods by Spearman correlation coefficient.By using the principal component analysis method,the comprehensive evaluation index system of the quality of the wine body was constructed,and the classification model of the detection location based on the comprehensive evaluation was established by using the index system.The detection sites were classified,and the results showed that the detection sites were divided into four grades.

淡水养殖池塘水质评价及与底质相关性分析

在哈尔滨地区面积6 600 m^(2)、平均水深1.2 m、多年未清淤的泥沙底质典型淡水精养池溏中混养鲤(Cyprinus carpio)、鲇(Silurus asotus)、草鱼(Ctenopharyngodon idella)和鲢(Hypophthalmichthys molitrix),春季(4—5月)、夏季(6—8月)和秋季(9月)不同时间采集池塘水体和表层底泥样品,监测养殖周期内水质总氮(TN)、总磷(TP)、氨氮(NH_(4)^(+)-N)、亚硝酸盐氮(NO_(2)^(-)-N)、硝酸盐氮(NO_(3)^(-)-N)和总有机碳(TOC)含量及高锰酸盐指数(COD_(Mn))、p H的季节性变化,利用单项污染指数法、综合污染指数法评价水体污染程度,利用主成分分析法解析水质污染的主要驱动因子,并结合底质指标绘制网络关系图。结果表明:池塘水质整体处于严重污染水平,春季优于夏季和秋季。参与评价时池塘水质为Ⅳ类、Ⅴ类和劣Ⅴ类,水质超标数随着养殖时间延长而增加,TN在全养殖周期内均超出警戒水平;TN、TP、NH_(4)^(+)-N和COD_(Mn)是池塘水体的主要污染物。因子分析结果表明,池塘水质主要受鱼类的生长代谢、溶解氧和投饵的影响,污染物以N、P营养盐为主。水体TP、TN、NH_(4)^(+)-N和底泥NO_(2)^(-)-N呈极显著正相关关系(P<0.01),与底泥TOC呈显著正相关关系(P<0.05)。池塘水体和底泥中的有机物污染具有共现性,水体TOC和底泥TOC呈极显著正相关关系(P<0.01)。