Soybean frogeye leaf spot(FLS) disease is a global disease affecting soybean yield, especially in the soybean growing area of Heilongjiang Province. In order to realize genomic selection breeding for FLS resistance of...Soybean frogeye leaf spot(FLS) disease is a global disease affecting soybean yield, especially in the soybean growing area of Heilongjiang Province. In order to realize genomic selection breeding for FLS resistance of soybean, least absolute shrinkage and selection operator(LASSO) regression and stepwise regression were combined, and a genomic selection model was established for 40 002 SNP markers covering soybean genome and relative lesion area of soybean FLS. As a result, 68 molecular markers controlling soybean FLS were detected accurately, and the phenotypic contribution rate of these markers reached 82.45%. In this study, a model was established, which could be used directly to evaluate the resistance of soybean FLS and to select excellent offspring. This research method could also provide ideas and methods for other plants to breeding in disease resistance.展开更多
[目的]嫩度是肉品质量的首要指标,其影响牛肉的消费和商业价值;寻找合适的嫩度指标,快速、无损、客观地预测牛肉嫩度一直是肉品学研究的热点之一。[方法]本文基于机器视觉技术和图像处理方法,分割牛肉图像的肌间结缔组织区域,提取肌间...[目的]嫩度是肉品质量的首要指标,其影响牛肉的消费和商业价值;寻找合适的嫩度指标,快速、无损、客观地预测牛肉嫩度一直是肉品学研究的热点之一。[方法]本文基于机器视觉技术和图像处理方法,分割牛肉图像的肌间结缔组织区域,提取肌间结缔组织的特征参数,运用统计学方法关联该特征参数和熟肉剪切力值,结合经过专门训练的评级小组的分级,采用Stepwise多元线性回归(Stepwise-MLR)建模,对牛肉嫩度进行预测和分级。[结果]70个样本图像的结缔组织特征数据全部用于训练模型,采用留一法交叉验证(Leave-one-out cross validation)测试模型,验证模型的牛肉嫩度判别系数(R^2)为0.857,剩余标准误差(residual standard error,RSEC)为6.453;将牛肉分为嫩、中等、老3个等级,全部预测集的总体等级预测正确率为88.57%。[结论]肌间结缔组织特征是预测牛肉嫩度的重要指标,本文所用的软硬件方法对牛肉嫩度的快速、无损、客观预测和分级具有一定的实用价值及指导意义。展开更多
Visible and near-infrared(VNIR)spectroscopy is an eco-friendly method used for estimating plant nutrient deficiencies.The aim of this study was to investigate the possibility of using VNIR method for estimating Zn con...Visible and near-infrared(VNIR)spectroscopy is an eco-friendly method used for estimating plant nutrient deficiencies.The aim of this study was to investigate the possibility of using VNIR method for estimating Zn content in cherry orchard leaves under field conditions.The study was conducted in 3different locations in Isparta region of Turkey.Fifteen cherry orchards containing normal and Zn deficient plants were chosen,and 60 leaf samples were collected from each location.The reflectance spectra of the leaves were measured with an ASD FieldSpec HandHeld spectroradiometer and a plant probe.The Zn contents of leaf samples were predicted through laboratory analysis.The spectral reflectance measurements were used to estimate the Zn levels using stepwise multiple linear regression analysis method.Prediction models were created using the highest coefficient of determination value.The results show that Zn content of cherry trees can be estimated using the VNIR spectroscopic method(87.5<r2<96.79).Moreover,plant nutrient contents can be estimated without using chemicals.However,further research is necessary to develop a standard method for field conditions.Because spectral reflectance is affected by ecological conditions,agricultural applications and nutrient interactions,more effective models must be developed depending on the geographical location,period and plant type.展开更多
Introduction The success in lineage-specific differentiation of human embryonic and induced pluripotent stem(hES/iPS)cells raises new hopes for cell-based therapies.It is envisioned that cells differentiated from hES/...Introduction The success in lineage-specific differentiation of human embryonic and induced pluripotent stem(hES/iPS)cells raises new hopes for cell-based therapies.It is envisioned that cells differentiated from hES/iPS cells can be used to replace or repair damaged or diseased cells and tissues in body.This has not yet been possible due to the difficulty in generating biologically functional cells in vitro.While many factors may contribute to these failures,the lack of tissue niches in the current differentiation systems has been viewed in impairing the maturation of these cells.As revealed by studying mice embryo development,organ development requires strict temporal and spatial control at each stage.The stepwise hESC differentiation展开更多
Though traditional methods could recognize some facies, e.g. lagoon facies, backshoal facies and foreshoal facies, they couldn't recognize reef facies and shoal facies well. To solve this problem, back propagation...Though traditional methods could recognize some facies, e.g. lagoon facies, backshoal facies and foreshoal facies, they couldn't recognize reef facies and shoal facies well. To solve this problem, back propagation neural network(BP-ANN) and an improved BP-ANN with better stability and suitability, optimized by a particle swarm optimizer(PSO) algorithm(PSO-BP-ANN) were proposed to solve the microfacies' auto discrimination of M formation from the R oil field in Iraq. Fourteen wells with complete core, borehole and log data were chosen as the standard wells and 120 microfacies samples were inferred from these 14 wells. Besides, the average value of gamma, neutron and density logs as well as the sum of squares of deviations of gamma were extracted as key parameters to build log facies(facies from log measurements)-microfacies transforming model. The total 120 log facies samples were divided into 12 kinds of log facies and 6 kinds of microfacies, e.g. lagoon bioclasts micrite limestone microfacies, shoal bioclasts grainstone microfacies, backshoal bioclasts packstone microfacies, foreshoal bioclasts micrite limestone microfacies, shallow continental micrite limestone microfacies and reef limestone microfacies. Furthermore, 68 samples of these 120 log facies samples were chosen as training samples and another 52 samples were gotten as testing samples to test the predicting ability of the discrimination template. Compared with conventional methods, like Bayes stepwise discrimination, both the BP-ANN and PSO-BP-ANN can integrate more log details with a correct rate higher than 85%. Furthermore, PSO-BP-ANN has more simple structure, smaller amount of weight and threshold and less iteration time.展开更多
A new type of iron-based matrix formula as a potential substitute for traditional WC-based matrix formula for hot pressed diamond bit was investigated.Iron,phosphor-iron,663-Cu,nickel,cobalt and certain additives were...A new type of iron-based matrix formula as a potential substitute for traditional WC-based matrix formula for hot pressed diamond bit was investigated.Iron,phosphor-iron,663-Cu,nickel,cobalt and certain additives were selected as the studied formula constituents.Among matrix performances,the hardness and wear resistance were chosen as experimental indexes in this paper.Constrained uniform design method was used for the formula design of iron-based matrix.Two forms of regression models of matrix hardness and wear resistance were obtained by regression analysis using MATLAB.Moreover,the optimization of matrix formulae and matrix performances were also achieved through constrained nonlinear programming.It was found that matrix hardness,significantly affected by the factor of Ni-Co-additives and Fe,increased with the increment of Ni-Co-additives,Fe and P-Fe,but reduced with the increase of 663-Cu.On the other hand,matrix wear resistance is mainly affected by Fe;the effect of the interaction between Fe and P-Fe is also relatively obvious. The increment of 663-Cu powder may result in a slight improvement in matrix wear resistance.In addition,the results of nonlinear programming revealed that the predictive optimum value of hardness was 139.5 HRB and the optimum wear resistance was 0.056 g,whereas they could not reach the optimum value at the same time.展开更多
A quantitative structure–activity relationship(QSAR) was performed to analyze antimalarial activities against the D10 strains of Plasmodium falciparum of triazole-linked chalcone and dienone hybrid derivatives using ...A quantitative structure–activity relationship(QSAR) was performed to analyze antimalarial activities against the D10 strains of Plasmodium falciparum of triazole-linked chalcone and dienone hybrid derivatives using partial least squares regression coupled with stepwise forward–backward variable selection method. QSAR analyses were performed on the available IC50 D10 strains of Plasmodium falciparum data based on theoretical molecular descriptors. The QSAR model developed gave good predictive correlation coefficient(r2) of 0.8994, significant cross validated correlation coefficient(q2) of 0.7689, r2 for external test set)(2predr of 0.8256, coefficient of correlation of predicted data set)(2sepred,r of 0.3276. The model shows that antimalarial activity is greatly affected by donor and electron-withdrawing substituents. The study implicates that chalcone and dienone rings should have strong donor and electron-withdrawing substituents as they increase the activity of chalcone. Results show that the predictive ability of the model is satisfactory, and it can be used for designing similar group of antimalarial compounds. The findings derived from this analysis along with other molecular modeling studies will be helpful in designing of the new potent antimalarial activity of clinical utility.展开更多
In this study,a total of 36 blackcurrant(Ribes nigrum L.)cultivars grown in the Northeast of China were selected,including 12 cultivars introduced from Russia,10 from Poland and the rest from local areas.The physicoch...In this study,a total of 36 blackcurrant(Ribes nigrum L.)cultivars grown in the Northeast of China were selected,including 12 cultivars introduced from Russia,10 from Poland and the rest from local areas.The physicochemical properties and amino acid compositions of these varieties were studied,and the geographical origins of blackcurrants were tracked by multivariate statistical analysis.A total of 23 amino acids were detected in all cultivars,which were rich in glutamine,glutamate,aspartate,asparagine,α-alanine,γ-aminobutyric acid,valine and serine.The content of the total amino acids in these cultivars was from 31.21 mg•100 g-1 to 319.40 mg•100 g-1.Stepwise linear discriminant analysis(SLDA)was introduced to perform satisfactory categorization for blackcurrant cultivars,which achieved a success rate of 88.9%for the identification of geographical origins.These results suggested that the compositions of amino acids in blackcurrants could effectively predict geographical origins.展开更多
基金Supported by the National Key Research and Development Program of China(2021YFD1201103-01-05)。
文摘Soybean frogeye leaf spot(FLS) disease is a global disease affecting soybean yield, especially in the soybean growing area of Heilongjiang Province. In order to realize genomic selection breeding for FLS resistance of soybean, least absolute shrinkage and selection operator(LASSO) regression and stepwise regression were combined, and a genomic selection model was established for 40 002 SNP markers covering soybean genome and relative lesion area of soybean FLS. As a result, 68 molecular markers controlling soybean FLS were detected accurately, and the phenotypic contribution rate of these markers reached 82.45%. In this study, a model was established, which could be used directly to evaluate the resistance of soybean FLS and to select excellent offspring. This research method could also provide ideas and methods for other plants to breeding in disease resistance.
文摘[目的]嫩度是肉品质量的首要指标,其影响牛肉的消费和商业价值;寻找合适的嫩度指标,快速、无损、客观地预测牛肉嫩度一直是肉品学研究的热点之一。[方法]本文基于机器视觉技术和图像处理方法,分割牛肉图像的肌间结缔组织区域,提取肌间结缔组织的特征参数,运用统计学方法关联该特征参数和熟肉剪切力值,结合经过专门训练的评级小组的分级,采用Stepwise多元线性回归(Stepwise-MLR)建模,对牛肉嫩度进行预测和分级。[结果]70个样本图像的结缔组织特征数据全部用于训练模型,采用留一法交叉验证(Leave-one-out cross validation)测试模型,验证模型的牛肉嫩度判别系数(R^2)为0.857,剩余标准误差(residual standard error,RSEC)为6.453;将牛肉分为嫩、中等、老3个等级,全部预测集的总体等级预测正确率为88.57%。[结论]肌间结缔组织特征是预测牛肉嫩度的重要指标,本文所用的软硬件方法对牛肉嫩度的快速、无损、客观预测和分级具有一定的实用价值及指导意义。
文摘Visible and near-infrared(VNIR)spectroscopy is an eco-friendly method used for estimating plant nutrient deficiencies.The aim of this study was to investigate the possibility of using VNIR method for estimating Zn content in cherry orchard leaves under field conditions.The study was conducted in 3different locations in Isparta region of Turkey.Fifteen cherry orchards containing normal and Zn deficient plants were chosen,and 60 leaf samples were collected from each location.The reflectance spectra of the leaves were measured with an ASD FieldSpec HandHeld spectroradiometer and a plant probe.The Zn contents of leaf samples were predicted through laboratory analysis.The spectral reflectance measurements were used to estimate the Zn levels using stepwise multiple linear regression analysis method.Prediction models were created using the highest coefficient of determination value.The results show that Zn content of cherry trees can be estimated using the VNIR spectroscopic method(87.5<r2<96.79).Moreover,plant nutrient contents can be estimated without using chemicals.However,further research is necessary to develop a standard method for field conditions.Because spectral reflectance is affected by ecological conditions,agricultural applications and nutrient interactions,more effective models must be developed depending on the geographical location,period and plant type.
文摘Introduction The success in lineage-specific differentiation of human embryonic and induced pluripotent stem(hES/iPS)cells raises new hopes for cell-based therapies.It is envisioned that cells differentiated from hES/iPS cells can be used to replace or repair damaged or diseased cells and tissues in body.This has not yet been possible due to the difficulty in generating biologically functional cells in vitro.While many factors may contribute to these failures,the lack of tissue niches in the current differentiation systems has been viewed in impairing the maturation of these cells.As revealed by studying mice embryo development,organ development requires strict temporal and spatial control at each stage.The stepwise hESC differentiation
基金Project(41272137) supported by the National Natural Science Foundation of China
文摘Though traditional methods could recognize some facies, e.g. lagoon facies, backshoal facies and foreshoal facies, they couldn't recognize reef facies and shoal facies well. To solve this problem, back propagation neural network(BP-ANN) and an improved BP-ANN with better stability and suitability, optimized by a particle swarm optimizer(PSO) algorithm(PSO-BP-ANN) were proposed to solve the microfacies' auto discrimination of M formation from the R oil field in Iraq. Fourteen wells with complete core, borehole and log data were chosen as the standard wells and 120 microfacies samples were inferred from these 14 wells. Besides, the average value of gamma, neutron and density logs as well as the sum of squares of deviations of gamma were extracted as key parameters to build log facies(facies from log measurements)-microfacies transforming model. The total 120 log facies samples were divided into 12 kinds of log facies and 6 kinds of microfacies, e.g. lagoon bioclasts micrite limestone microfacies, shoal bioclasts grainstone microfacies, backshoal bioclasts packstone microfacies, foreshoal bioclasts micrite limestone microfacies, shallow continental micrite limestone microfacies and reef limestone microfacies. Furthermore, 68 samples of these 120 log facies samples were chosen as training samples and another 52 samples were gotten as testing samples to test the predicting ability of the discrimination template. Compared with conventional methods, like Bayes stepwise discrimination, both the BP-ANN and PSO-BP-ANN can integrate more log details with a correct rate higher than 85%. Furthermore, PSO-BP-ANN has more simple structure, smaller amount of weight and threshold and less iteration time.
文摘A new type of iron-based matrix formula as a potential substitute for traditional WC-based matrix formula for hot pressed diamond bit was investigated.Iron,phosphor-iron,663-Cu,nickel,cobalt and certain additives were selected as the studied formula constituents.Among matrix performances,the hardness and wear resistance were chosen as experimental indexes in this paper.Constrained uniform design method was used for the formula design of iron-based matrix.Two forms of regression models of matrix hardness and wear resistance were obtained by regression analysis using MATLAB.Moreover,the optimization of matrix formulae and matrix performances were also achieved through constrained nonlinear programming.It was found that matrix hardness,significantly affected by the factor of Ni-Co-additives and Fe,increased with the increment of Ni-Co-additives,Fe and P-Fe,but reduced with the increase of 663-Cu.On the other hand,matrix wear resistance is mainly affected by Fe;the effect of the interaction between Fe and P-Fe is also relatively obvious. The increment of 663-Cu powder may result in a slight improvement in matrix wear resistance.In addition,the results of nonlinear programming revealed that the predictive optimum value of hardness was 139.5 HRB and the optimum wear resistance was 0.056 g,whereas they could not reach the optimum value at the same time.
文摘A quantitative structure–activity relationship(QSAR) was performed to analyze antimalarial activities against the D10 strains of Plasmodium falciparum of triazole-linked chalcone and dienone hybrid derivatives using partial least squares regression coupled with stepwise forward–backward variable selection method. QSAR analyses were performed on the available IC50 D10 strains of Plasmodium falciparum data based on theoretical molecular descriptors. The QSAR model developed gave good predictive correlation coefficient(r2) of 0.8994, significant cross validated correlation coefficient(q2) of 0.7689, r2 for external test set)(2predr of 0.8256, coefficient of correlation of predicted data set)(2sepred,r of 0.3276. The model shows that antimalarial activity is greatly affected by donor and electron-withdrawing substituents. The study implicates that chalcone and dienone rings should have strong donor and electron-withdrawing substituents as they increase the activity of chalcone. Results show that the predictive ability of the model is satisfactory, and it can be used for designing similar group of antimalarial compounds. The findings derived from this analysis along with other molecular modeling studies will be helpful in designing of the new potent antimalarial activity of clinical utility.
基金Supported by the National Natural Science Foundation of China(32172521)the Natural Science Fund Joint Guidance Project of Heilongjiang Province(LH2019C031)+1 种基金Postdoctoral Scientific Research Development Fund of Heilongjiang Province,China(LBH-Q16020)the Natural Science Fund Project of Heilongjiang Province(SS2021C001)。
文摘In this study,a total of 36 blackcurrant(Ribes nigrum L.)cultivars grown in the Northeast of China were selected,including 12 cultivars introduced from Russia,10 from Poland and the rest from local areas.The physicochemical properties and amino acid compositions of these varieties were studied,and the geographical origins of blackcurrants were tracked by multivariate statistical analysis.A total of 23 amino acids were detected in all cultivars,which were rich in glutamine,glutamate,aspartate,asparagine,α-alanine,γ-aminobutyric acid,valine and serine.The content of the total amino acids in these cultivars was from 31.21 mg•100 g-1 to 319.40 mg•100 g-1.Stepwise linear discriminant analysis(SLDA)was introduced to perform satisfactory categorization for blackcurrant cultivars,which achieved a success rate of 88.9%for the identification of geographical origins.These results suggested that the compositions of amino acids in blackcurrants could effectively predict geographical origins.
