During the course of calculating the rice evapotranspiration using weather factors,we often find that some independent variables have multiple correlation.The phenomena can lead to the traditional multivariate regress...During the course of calculating the rice evapotranspiration using weather factors,we often find that some independent variables have multiple correlation.The phenomena can lead to the traditional multivariate regression model which based on least square method distortion.And the stability of the model will be lost.The model will be built based on partial least square regression in the paper,through applying the idea of main component analyze and typical correlation analyze,the writer picks up some component from original material.Thus,the writer builds up the model of rice evapotranspiration to solve the multiple correlation among the independent variables (some weather factors).At last,the writer analyses the model in some parts,and gains the satisfied result.展开更多
Reversed phase chromatographic separations are optimized for analytes containing ionizable groups by adjustment of pH of mobile phases.As it seems the pKavalues of compounds affect their retention because of the varie...Reversed phase chromatographic separations are optimized for analytes containing ionizable groups by adjustment of pH of mobile phases.As it seems the pKavalues of compounds affect their retention because of the variety in their solvation.However,it is of stressful need to predict their behavior taking into account also a series of other parameters.This work focuses on the development of ten different models,using partial least squares regression,which will identify and quantify the impact of several factors in the chromatographic behavior of 104 analytes.The combined effect of their numerous characteristics is obvious since along with pH(at 2.3 and 6.2),factors such as lipophilicity,molecular volume,polar surface area and the presence of specific moieties in their structures are not diminished.On the contrary,they work increasing or counterbalancing several effects on the retention time.The models compiled can be applied to predict with reliability(R^2>0.865and Q^2>0.777)the behavior of unknown drugs.展开更多
Background Fiber maturity is a key cotton quality property,and its variability in a sample impacts fiber processing and dyeing performance.Currently,the maturity is determined by using established protocols in laborat...Background Fiber maturity is a key cotton quality property,and its variability in a sample impacts fiber processing and dyeing performance.Currently,the maturity is determined by using established protocols in laboratories under a controlled environment.There is an increasing need to measure fiber maturity using low-cost(in general less than $20000)and small portable systems.In this study,a laboratory feasibility was performed to assess the ability of the shortwave infrared hyperspectral imaging(SWIR HSI)technique for determining the conditioned fiber maturity,and as a comparison,a bench-top commercial and expensive(in general greater than $60000)near infrared(NIR)instrument was used.Results Although SWIR HSI and NIR represent different measurement technologies,consistent spectral characteristics were observed between the two instruments when they were used to measure the maturity of the locule fiber samples in seed cotton and of the well-defined fiber samples,respectively.Partial least squares(PLS)models were established using different spectral preprocessing parameters to predict fiber maturity.The high prediction precision was observed by a lower root mean square error of prediction(RMSEP)(<0.046),higher R_(p)^(2)(>0.518),and greater percentage(97.0%)of samples within the 95% agreement range in the entire NIR region(1000-2500 nm)without the moisture band at 1940 nm.Conclusion SWIR HSI has a good potential for assessing cotton fiber maturity in a laboratory environment.展开更多
文摘During the course of calculating the rice evapotranspiration using weather factors,we often find that some independent variables have multiple correlation.The phenomena can lead to the traditional multivariate regression model which based on least square method distortion.And the stability of the model will be lost.The model will be built based on partial least square regression in the paper,through applying the idea of main component analyze and typical correlation analyze,the writer picks up some component from original material.Thus,the writer builds up the model of rice evapotranspiration to solve the multiple correlation among the independent variables (some weather factors).At last,the writer analyses the model in some parts,and gains the satisfied result.
文摘Reversed phase chromatographic separations are optimized for analytes containing ionizable groups by adjustment of pH of mobile phases.As it seems the pKavalues of compounds affect their retention because of the variety in their solvation.However,it is of stressful need to predict their behavior taking into account also a series of other parameters.This work focuses on the development of ten different models,using partial least squares regression,which will identify and quantify the impact of several factors in the chromatographic behavior of 104 analytes.The combined effect of their numerous characteristics is obvious since along with pH(at 2.3 and 6.2),factors such as lipophilicity,molecular volume,polar surface area and the presence of specific moieties in their structures are not diminished.On the contrary,they work increasing or counterbalancing several effects on the retention time.The models compiled can be applied to predict with reliability(R^2>0.865and Q^2>0.777)the behavior of unknown drugs.
基金supported partially by the USDA-ARS Research Project#6054-44000-080-00D.
文摘Background Fiber maturity is a key cotton quality property,and its variability in a sample impacts fiber processing and dyeing performance.Currently,the maturity is determined by using established protocols in laboratories under a controlled environment.There is an increasing need to measure fiber maturity using low-cost(in general less than $20000)and small portable systems.In this study,a laboratory feasibility was performed to assess the ability of the shortwave infrared hyperspectral imaging(SWIR HSI)technique for determining the conditioned fiber maturity,and as a comparison,a bench-top commercial and expensive(in general greater than $60000)near infrared(NIR)instrument was used.Results Although SWIR HSI and NIR represent different measurement technologies,consistent spectral characteristics were observed between the two instruments when they were used to measure the maturity of the locule fiber samples in seed cotton and of the well-defined fiber samples,respectively.Partial least squares(PLS)models were established using different spectral preprocessing parameters to predict fiber maturity.The high prediction precision was observed by a lower root mean square error of prediction(RMSEP)(<0.046),higher R_(p)^(2)(>0.518),and greater percentage(97.0%)of samples within the 95% agreement range in the entire NIR region(1000-2500 nm)without the moisture band at 1940 nm.Conclusion SWIR HSI has a good potential for assessing cotton fiber maturity in a laboratory environment.
