Correlation analysis and multiple regression formulas of refractive errors and ocular components

The multiple regression formulas and correlation of ocular components with refractive errors are presented by Gaussian optics. The refractive error changing rate for the cornea and lens power, the axial length, anterior chamber depth(ACD) and vitreous chamber depth(VCD) are calculated, including nonlinear terms for more accurate rate functions than the linear theory. Our theory, consistent with the empirical data, shows that the Pearson correlation coefficients for spherical equivalent(SE) and ocular components are highest for SE with axial length, ACD and VCD and weakest for corneal power, lens power and lens thickness. Moreover, our regression formulas show the asymmetric feature of the correlation that the axial length, ACD and VCD are more strongly correlated(with higher negative regression constants) with refractive errors in eyes with hyperopia than in eyes with myopia, particularly for severe hyperopia.

Correlation Analysis of Fiscal Revenue and Housing Sales Price Based on Multiple Linear Regression Model

This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis and regression analysis to comprehensively study the correlation between financial revenue and housing sales price in China,and establishes the relationship between financial revenue and housing sales price When the average selling price of commercial housing increases by one unit,the fiscal revenue will increase by 27.855 points.

SFGA-CPA: A Novel Screening Correlation Power Analysis Framework Based on Genetic Algorithm

Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.

Regression analysis and its application to oil and gas exploration:A case study of hydrocarbon loss recovery and porosity prediction,China

In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not just at predicting geophysical logging curve values but also innovatively mitigate hydrocarbon depletion observed in geochemical logging.Through a rigorous assessment,we explore the efficacy of eight regression models,bifurcated into linear and nonlinear groups,to accommodate the multifaceted nature of geological datasets.Our linear model suite encompasses the Standard Equation,Ridge Regression,Least Absolute Shrinkage and Selection Operator,and Elastic Net,each presenting distinct advantages.The Standard Equation serves as a foundational benchmark,whereas Ridge Regression implements penalty terms to counteract overfitting,thus bolstering model robustness in the presence of multicollinearity.The Least Absolute Shrinkage and Selection Operator for variable selection functions to streamline models,enhancing their interpretability,while Elastic Net amalgamates the merits of Ridge Regression and Least Absolute Shrinkage and Selection Operator,offering a harmonized solution to model complexity and comprehensibility.On the nonlinear front,Gradient Descent,Kernel Ridge Regression,Support Vector Regression,and Piecewise Function-Fitting methods introduce innovative approaches.Gradient Descent assures computational efficiency in optimizing solutions,Kernel Ridge Regression leverages the kernel trick to navigate nonlinear patterns,and Support Vector Regression is proficient in forecasting extremities,pivotal for exploration risk assessment.The Piecewise Function-Fitting approach,tailored for geological data,facilitates adaptable modeling of variable interrelations,accommodating abrupt data trend shifts.Our analysis identifies Ridge Regression,particularly when augmented by Piecewise Function-Fitting,as superior in recouping hydrocarbon losses,and underscoring its utility in resource quantification refinement.Meanwhile,Kernel Ridge Regression emerges as a noteworthy strategy in ameliorating porosity-logging curve prediction for well A,evidencing its aptness for intricate geological structures.This research attests to the scientific ascendancy and broad-spectrum relevance of these regression techniques over conventional methods while heralding new horizons for their deployment in the oil and gas sector.The insights garnered from these advanced modeling strategies are set to transform geological and engineering practices in hydrocarbon prediction,evaluation,and recovery.

Seismic response and correlation analysis of a pile-supported wharf to near-fault pulse-like ground motions

Earthquake investigations have shown that near-fault pulse-like(NF-P)ground motions have unique characteristics compared to near-fault non-pulse-like(NF-NP)and far-field(FF)ground motions.It is necessary to study the seismic response of pile-supported wharf(PSW)structures under NF-P ground motions.In this study,a three-dimensional finite element numerical model is created to simulate a PSW.By imparting three types of ground motion,the engineering demand parameters(EDPs)of PSW under NF-P ground motions were analyzed and compared,in which EDPs are the maximum displacement and bending moment of the piles.Twenty intensity measures(IMs)were selected to characterize the properties of ground motions.The correlation between IMs and EDPs was explored.The results show that the piles present larger displacement and bending moment under NF-P ground motions compared to NF-NP and FF ground motions.None of the IMs have a high correlation with EDPs under NF-P ground motions,and these IMs are more applicable to FF ground motions.The correlation coefficients between EDPs and IMs under three types of ground motion were obtained,which will provide a valuable reference for the seismic design of PSWs.

Cross-Project Software Defect Prediction Based on SMOTE and Deep Canonical Correlation Analysis

Cross-Project Defect Prediction(CPDP)is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target project.However,existing CPDP methods only consider linear correlations between features(indicators)of the source and target projects.These models are not capable of evaluating non-linear correlations between features when they exist,for example,when there are differences in data distributions between the source and target projects.As a result,the performance of such CPDP models is compromised.In this paper,this paper proposes a novel CPDP method based on Synthetic Minority Oversampling Technique(SMOTE)and Deep Canonical Correlation Analysis(DCCA),referred to as S-DCCA.Canonical Correlation Analysis(CCA)is employed to address the issue of non-linear correlations between features of the source and target projects.S-DCCA extends CCA by incorporating the MlpNet model for feature extraction from the dataset.The redundant features are then eliminated by maximizing the correlated feature subset using the CCA loss function.Finally,cross-project defect prediction is achieved through the application of the SMOTE data sampling technique.Area Under Curve(AUC)and F1 scores(F1)are used as evaluation metrics.This paper conducted experiments on 27 projects from four public datasets to validate the proposed method.The results demonstrate that,on average,our method outperforms all baseline approaches by at least 1.2%in AUC and 5.5%in F1 score.This indicates that the proposed method exhibits favorable performance characteristics.

Tongue image feature correlation analysis in benign lung nodules and lung cancer

Objective To analyze the differences in the correlation of tongue image indicators among patients with benign lung nodules and lung cancer.Methods From July 1;2020 to March 31;2022;clinical information of lung cancer patients and benign lung nodules patients was collected at the Oncology Department of Longhua Hos-pital Affiliated to Shanghai University of Traditional Chinese Medicine and the Physical Ex-amination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chi-nese Medicine;respectively.We obtained tongue images from patients with benign lung nod-ules and lung cancer using the TFDA-1 digital tongue diagnosis instrument;and analyzed these images with the TDAS V2.0 software.The extracted indicators included color space pa-rameters in the Lab system for both the tongue body(TB)and tongue coating(TC)(TB/TC-L;TB/TC-a;and TB/TC-b);textural parameters[TB/TC-contrast(CON);TB/TC-angular second moment(ASM);TB/TC-entropy(ENT);and TB/TC-MEAN];as well as TC parameters(perAll and perPart).The bivariate correlation of TB and TC features was analyzed using Pearson’s or Spearman’s correlation analysis;and the overall correlation was analyzed using canonical correlation analysis(CCA).Results Samples from 307 patients with benign lung nodules and 276 lung cancer patients were included after excluding outliers and extreme values.Simple correlation analysis indi-cated that the correlation of TB-L with TC-L;TB-b with TC-b;and TB-b with perAll in lung cancer group was higher than that in benign nodules group.Moreover;the correlation of TB-a with TC-a;TB-a with perAll;and the texture parameters of the TB(TB-CON;TB-ASM;TB-ENT;and TB-MEAN)with the texture parameters of the TC(TC-CON;TC-ASM;TC-ENT;and TC-MEAN)in benign nodules group was higher than lung cancer group.CCA further demon-strated a strong correlation between the TB and TC parameters in lung cancer group;with the first and second pairs of typical variables in benign nodules and lung cancer groups indicat-ing correlation coefficients of 0.918 and 0.817(P<0.05);and 0.940 and 0.822(P<0.05);re-spectively.Conclusion Benign lung nodules and lung cancer patients exhibited differences in correla-tion in the L;a;and b values of the TB and TC;as well as the perAll value of the TC;and the texture parameters(TB/TC-CON;TB/TC-ASM;TB/TC-ENT;and TB/TC-MEAN)between the TB and TC.Additionally;there were differences in the overall correlation of the TB and TC be-tween the two groups.Objective tongue diagnosis indicators can effectively assist in the diag-nosis of benign lung nodules and lung cancer;thereby providing a scientific basis for the ear-ly detection;diagnosis;and treatment of lung cancer.

Composition Analysis and Identification of Ancient Glass Products Based on L1 Regularization Logistic Regression

In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluster analysis, hyper-parameter test and other models, and SPSS, Python and other tools were used to obtain the classification rules of glass products under different fluxes, sub classification under different chemical compositions, hyper-parameter K value test and rationality analysis. Research can provide theoretical support for the protection and restoration of ancient glass relics.

Correlation analysis of human papillomavirus E6/E7 mRNA detection with diagnosis,prognosis and recurrence risk in patients with cervical epithelioma

BACKGROUND Cervical intraepithelial neoplasia(CIN)is an important precursor of cervical cancer.Early detection and treatment can reduce the incidence of cervical cancer.AIM To investigate the detection rate of human papillomavirus(HPV)E6/E7 mRNA in cervical tissue of patients with different types of epithelial cell neoplasia(CIN)and its relationship with CIN progression and diagnosis.METHODS One hundred women with HPV infection detected by cervical exfoliation cytology between January 2022 and January 2023 were retrospectively selected.These patients were graded CIN based on colposcopy and cervical pathology.The positive expression rates of HPV E6/E7 mRNA and HPV[polymerase chain reaction(PCR)-reverse dot crossing]were compared among all groups.Patients with HPV E6/E7 mRNA expression in the grade 1 CIN group were followed up for 1 yr.The relationship between atypical squamous epithelium and high malignant epithelial neoplasia was investigated by univariate and multivariate analysis.RESULTS The diagnostic sensitivity,specificity,and sensitivity of PCR-reverse point hybrid ization technology for secondary CIN were 70.41%,70.66%,and 0.714,respectively.Sensitivity and specificity for secondary CIN were 752%and 7853%,respectively,the area under the curve value was 0.789.Logistic Multifactorial model analysis revealed that the HPV positive rates and the HPV E6/E7 mRNA positive rates were independent risk factors of CIN grade I(P<0.05).In CIN grade I patients with positive for HPV E6/E7 mRNA,in its orientation to grade CIN patients,in its orientation to grade CIN patients,at 69.2%,compared with patients negative for HPV E6/E7 mRNA(30.8%),significant difference(P<0.05).CONCLUSION HPV E6/E7 mRNA and HPV(PCR-reverse dot hybrid)positive expression have a close relationship with CINgrade disease progression and is an independent risk factor for high-grade CIN lesions.

Correlation Analysis between Well-cellar Early Transplanting of Robust Seedlings and Diseases in Shiyan Tobacco-growing Area

[Objectives]The paper was to investigate the relationship between the well-cellar early transplanting of robust seedlings and the prevalence of diseases in the Shiyan tobacco-growing area.[Methods]The relationship between disease occurrence and meteorological factors during the field growth period was examined by analyzing the prevalence of flue-cured tobacco virus diseases,brown spot,and total disease in the Shiyan tobacco-growing area before(2013-2017)and after(2018-2022)the well-cellar early transplanting of robust tobacco seedlings.[Results]The implementation of a well-cellar early transplanting technique of robust seedlings resulted in a reduction in the average incidence of tobacco virus disease,brown spot,and total disease by 0.83%,8.85%,and 7.91%,respectively,in comparison to the incidence observed prior to early transplanting.These findings suggest that early transplanting can significantly reduce the incidence of flue-cured tobacco diseases.Prior to the well-cellar early transplanting of robust tobacco seedlings,there was a significant(including highly significant)positive correlation between the incidence of brown spot and total disease and precipitation in August and September.The incidence of brown spot and total disease in tobacco plants was found to be significantly positively correlated with May precipitation and significantly negatively correlated with May sunshine hours following the well-cellar early transplanting of robust seedlings.The advancement of the transplanting period by 20 d resulted in a reduction in the growing period of tobacco plants in the field under autumn rains(late August to November)in western China.This effectively circumvented the suitable conditions for disease occurrence and can reduce the incidence of disease.[Conclusions]This study offers a framework for enhancing the quality and efficiency of flue-cured tobacco production in the northwest tobacco-growing area of Hubei.

Correlation Analysis Between Changes of D-Dimer Level and Rheumatoid Arthritis Complicated with Interstitial Lung Disease

Objective:To explore the correlation between the change of D-dimer level and rheumatoid arthritis complicated with interstitial lung disease.Methods:From January 2022 to February 2024,20 rheumatoid arthritis patients complicated with interstitial lung disease(interstitial lung disease group),20 rheumatoid arthritis patients without interstitial lung disease(without interstitial lung disease group),and 20 healthy people(control group)in Xijing Hospital were selected for this study.The fasting venous blood of the three groups of subjects was collected and their D-dimer,C-reactive protein(CRP),rheumatoid factor(RF),and erythrocyte sedimentation rate(ESR)were detected.Subsequently,the correlation between each index and rheumatoid arthritis complicated with interstitial lung disease was analyzed.Results:The D-dimer level of the interstitial lung disease group was significantly higher than the other two groups(P<0.05).The D-dimer level of the group without interstitial lung disease was significantly higher than the control group(P<0.05).CRP levels in the interstitial lung disease group and the group without interstitial lung disease were significantly higher than those of the control group(P<0.05).The ESR and RF levels of the interstitial lung disease group were significantly higher than the other two groups(P<0.05).The levels of ESR and RF levels of the group without interstitial lung disease were significantly higher than the control group(P<0.05).Conclusion:D-dimer levels of rheumatoid arthritis patients are higher than those of healthy individuals,and those complicated with interstitial lung disease present even higher levels.This finding shows that there is a correlation between D-dimer levels and rheumatoid arthritis with interstitial lung disease,which may facilitate the evaluation and diagnosis of this disease.

Correlation and Path Analysis for Growth Traits in F_1 Population of Pearl Oyster Pinctada martensii

120 pearl oysters （Pinctada martensii） were randomly sampled from F1 population, and shell length, shell width, shell height, shell weight and total weight of each sample were measured. Correlation and path analysis were conducted on the basis of measurement data. The results showed that shell length, shell width, shell height, shell weight and total weight were significantly correlated （P 〈 0.05）. Total weight was significantly and positively correlated with shell weight （r = 0.8970）, shell height （r = 0.6974）, shell width （r = 0.6521） and shell length （r = 0.5486）. Shell weight, shell height, shell width and shell length had positive and direct effects on total wet weight, with the values of 0.6356, 0.1872, 0.1814 and 0.0599, respectively. The results indicated that growth traits （shell length, shell width, shell height, shell weight and total wet weigh） of the F1 population could be improved by direct or indirect selection.

Correlation Analysis of SPAD Value with Chlorophyll Content and Economic Yield Traits of Brassica napus L.

[Objective] The aim was to compare differences of SPAD value, chloro- phyll content, agronomic characters, economic characters and yield traits to analyze correlation of SPAD value with other indices and establish regression functions. [Method] Based on 34 Brassica napus L. varieties, SPAD value, chlorophyll content, agronomic characters, economic characters and yield traits were measured and re- gression functions were established according to correlations. [Result] SPAD value, chlorophyll content, agronomic and economic characters and yield traits all achieved significant level in differences among 34 varieties. Specifically, SPAD value was of extremely significant correlation with chlorophyll a and b, total chlorophyll and carotenoid, and the correlation from high to low was chl-b〉chl-z〉chl-a〉chl-x. SPAD value was of significantly positive correlation with total pod number per plant, plant height, seed number per pod, yield per plant and harvest yield, and of insignificant correlation with branch point height, effective branch number, pod density of main stem, and pod length. [Conclusion] It is simple and rapid to predict chlorophyll con- tent, economic characters and yields of Brassica napus L. with SPAD value and re- gression functions.

Correlation Analysis between Fruit Cracking and Influencing Factors in Apricot

In this study, 14 representative apricot cultivars in the production were selected as the experimental materials, and their fruit cracking characteristics, as well as the correlations between fruit cracking and influencing factors （e.g., pedcarp structure, mineral elements contents, DW/FW ratio and soluble sugar content） were analyzed to provide some reference for systematic study on fruit cracking mecha- nism of apricot. The results showed the cultivars with small orderly-and compactlyarranged epidermal cells were difficult to crack, while the cultivars with big disorderly-and loosely-arranged epidermal cells were easy to crack. There was no significant correlation between pericarp thickness and cracking index. The correlations between cracking and mineral elements contents of apricot fruit were in the order as Ca 〉 Zn 〉 Mn 〉 Fe 〉 K 〉 Mg 〉 Cu. The cracking index of apricot fruit was significantly negatively correlated with Ca content, was weakly correlated with Zn and Mn contents, and was uncorrelated with Fe, K, Mg and Cu contents. Ca deficiency was the main factor affecting the fruit cracking in apricot. Under the same conditions, the higher the water content is, the lower the cracking index is; and the higher the soluble sugar content is, the higher the cracking index is.

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.

Application of cluster analysis and stepwise regression in predicting the traffic volume of lanes

Because of the difficulty to obtain the traffic flow information of lanes at non-detector intersections in most metropolises of the world,based on the relationships between the lanes of signal-controlled intersections,cluster analysis and stepwise regression are integrated to predict the traffic volume of lanes at non-detector isolated controlled intersections.First cluster analysis is used to cluster the lanes of non-detector isolated signal-controlled intersections and the lanes of all signal-controlled intersections with detectors.Then, by the results of cluster analysis,the traffic volume samples are selected randomly and stepwise regression is used to predict the traffic volume of lanes at non-detector isolated signal-controlled intersections.The method is tested by the traffic volume data of lanes of the road network of Nanjing city.The problem of predicting the traffic volume of lanes at non-detector isolated signal-controlled intersections was resolved and can be widely used in urban traffic flow guidance and urban traffic control in cities without enough intersections equipped with detectors.

Correlation and path coefficient analysis for phenotypic traits of noble scallop Chlamys nobilis

In April of 2006, a base population of the noble scallop Chlamys nobilis was established by collecting parental breeders from the stocks in Wushi, Zhanjiang. In December of 2006, 200 individuals were randomly sampled from the base population and subjected for correlation and path coefficient analysis. It was found that there were statistically significant phenotypic correlations among the traits （P 〈 0.01）. Total weight was significantly and positively correlated with the shell length （r = 0.934 3）, shell height （r = 0.895 9）, shell width （r = 0.899 1 ）, muscle weight （r = 0.882 0） and shell weight （r = 0.937 9）, respectively. Shell length, shell width, muscle weight, shell height and shell weight had positive and direct effects on the total weight, with values of 0.397 1, 0.321 9, 0.172 1, 0.089 6 and 0.066 9, respectively. Shell length, shell width and muscle weight had higher direct effects on the total weight than shell height and shell weight. A combined evaluation of correlation, direct effects and indirect effects showed that direct selection for shell length, shell width, muscle weight, shell height and shell weight would be effective to improving the total weight. It was concluded that these traits could be regarded as the selection criteria in breeding programs of the species.

Analysis of Correlation between Yield and Quality Traits of Quality Hybrid Rapeseed

[Objective] This study aimed to investigate the correlation between yield and quality traits of rape. [Method] Taking ＂Sanbei 98＂ and ＂Youyan 599＂ as ex- periment materials, correlation between yield and quality traits of Brassica napus L. cultivars was explored by orthogonal rotation method. [Result] The results showed that： 1 In both the two varieties-Sanbei98 and Youyan599, erucic acid content had the largest coefficient of variation, but its average content was lower than 2% in both the two varieties （0.90% in Sanbei98 and 1.24% in Youyan599）, and the palmitic acid content had the smallest coefficient of variation. 2 In terms of the dif- ferences in quality traits at different yield levels, only the mean of eicosenoic acid content revealed significant difference in Sanbei98, and only the mean of seed-pro- tein content revealed significant difference in Youyan599, and there was no signifi- cant difference in any combined quality traits in both the two varieties. 3 The yield was negatively correlated with the erucic acid content or oil content, and posi- tively correlated with the content of seed-protein, linoleic acid, or linolenic acid, and the coefficient of correlation between the yield and either of the contents of glucosi- nolates, oleic acid, palmitic acid, stearic acid, and eicosenoic acid was smaller. ~, when the yield of a variety increased considerably, there was a certain decreasing trend in erucic acid content, oil content, the total amount of erucic chain fatty acids （El ＆ Er）, while there was an increasing trend in seed-protein content, linoleic acid content, linolenic acid content, saturated fatty acids （SFA）, the total amount of fat and protein （P ＆ F）, unsaturation index （IUFA）, unsaturated fatty acids （UFA）, the total amount of 18 carbon fatty acids （18-C FA）, unsaturated fatty acids [UFA/（Ei ＆ Er） ], and the sum of oleic acid and linoleic acid （OI ＆ Li）. 5 When the seed-pro- tein content is increased, the quality of rape oil cake is also improved; when the unsaturated index is increased, the oil stability is decreased. The increase in the total amount of unsaturated fatty acids, oleic acid and linoleic acid helps to increase in the total amount of fatty acids absorbed by human bodies. [Conclusion] This study provides a theoretical foundation for the cultivation of high-yielding and top- quality hybrid rape cultivars.

Correlation Analysis and Path Analysis between Yield and Yield-Related Traits of Yunmai 52

[Objective] This study was tween yield-related traits and yield of conducted to understand the relationship be- Yunmai 52 which is a high-quality high-yield multi-resistant new wheat variety, and make contribution of yield-related traits to the yield of Yunmai 52 clear. [Method] Wheat variety regional trial data in Yunnan Province in 2005-2007 were subjected to correlation analysis and path analysis in the paper. [Result] Correlationanalysis showed that the yield of Yunmai 52 was in- very significant positive correlation with spikelet number per ear, maximum tiller number and grains per ear （r=0.726^＊＊, 0.717^＊＊ and 0.695^＊＊, respectively）, in signif- icant positive correlation with 1 000-grain weight （r=0.491^＊）, but in significant nega- tive correlation with sterile spikelet number per ear, and in non-significant correlation with basic seedlings, effective ears and percentage of ear bearing tillers. Partial correlation analysis showed that the yield of Yunmai 52 was in very significant posi- tive correlation with spikelet number per ear （r=0.711^＊＊）, significant positive correla- tion with 1 000-grain weight （r=0.641 =）, but in non-significant correlation with other 6 traits. Path analysis showed that spikelet number per ear （P=-0.595）, maximum tiller number （P=0.462） and t 000-grain weight （P=0.263） had more contribution to yield of Yunmai 52. [Conclusion] Therefore, in extension and application of Yunmal 52 that is a high-quality high-yield multi-resistant new wheat variety, supply of fertilizer and water should be increased in tillering stage and jointing stage, to ensure its characteristics of high tilledng ability and large ear, as well as high 1 000-grain weight, and coordinated development of other yield-related traits is beneficial to im- provement of yield of Yunmai 52.

Correlation Analysis Between Yield Components and Yield Per Plant of Double-low Hybrid Rapeseed

[Objective] The experiment aimed to study the relation between yield components and yield per plant of double-low hybrid rapeseed and provide reference for breaking yield limitation of rapeseed and culturing new double-low hybrid rapeseed variety. [Method]The yield components and yield per plant of two cross combination of double-low hybrid rapeseed (B02, D04) and Shuza 6 were correlatively analyzed and compared, besides, the path analysis was also carried on to them. [Result] Among B02, D04 and Shuza No.6, effective pod number per plant and seeds per silique, seeds per pod and 1 000-grain weight were all negative correlation. In high yield hybrid, pod number per plant, seeds per pod had more impaction on yield per plant than 1 000-grain weight and the difference was at 0.01 significant level. In the control variety Shuza No.6, the impactions of pod number per plant and seeds per pod on yield per plant were bigger than that of 1 000-grain weight on yield per plant, however, the difference was not significant. [Conclusion] The improvement of effective pod number per plant was an important aim of breeding work of double low rapeseed breeding in Sichuan ecological region.