Total proteins extracted from Pinellia ternata with different types of leaves have been assayed by UV absorbance, blue native polyacrylamide gel electrophoresis （BN-PAGE） and sodium dodecyl sulfate-polyacrylamide ge...Total proteins extracted from Pinellia ternata with different types of leaves have been assayed by UV absorbance, blue native polyacrylamide gel electrophoresis （BN-PAGE） and sodium dodecyl sulfate-polyacrylamide gel electrophoresis （SDS- PAGE）. We found that the total protein contents of P. ternata with the herbaceous peony and claw types of leaves were much higher than that with other types of leaves. P. ternata collected from Nanchuan County, except the ones with herbaceous peony leaves, displayed a high similarity with each other. Both UV absorbance and cluster analysis indicated that the protein content in P. ternata with the herbaceous peony leaves was less affected by habitats than that with other types of leaves. The results showed that it was necessary to increase the homogeneity of seeds for improving the protein content ofP. ternata.展开更多
Consensus methods have presented promising tools for improving the reliability of quantitative models in near-infrared(NIR) spectroscopic analysis.A strategy for improving the performance of consensus methods in multi...Consensus methods have presented promising tools for improving the reliability of quantitative models in near-infrared(NIR) spectroscopic analysis.A strategy for improving the performance of consensus methods in multivariate calibration of NIR spectra is proposed.In the approach,a subset of non-collinear variables is generated using successive projections algorithm(SPA) for each variable in the reduced spectra by uninformative variables elimination(UVE).Then sub-models are built using the variable subsets and the calibration subsets determined by Monte Carlo(MC) re-sampling,and the sub-model that produces minimal error in cross validation is selected as a member model.With repetition of the MC re-sampling,a series of member models are built and a consensus model is achieved by averaging all the member models.Since member models are built with the best variable subset and the randomly selected calibration subset,both the quality and the diversity of the member models are insured for the consensus model.Two NIR spectral datasets of tobacco lamina are used to investigate the proposed method.The superiority of the method in both accuracy and reliability is demonstrated.展开更多
基金Natural Science Foundation of Chongqing (Grant No. 2006BB5403)
文摘Total proteins extracted from Pinellia ternata with different types of leaves have been assayed by UV absorbance, blue native polyacrylamide gel electrophoresis （BN-PAGE） and sodium dodecyl sulfate-polyacrylamide gel electrophoresis （SDS- PAGE）. We found that the total protein contents of P. ternata with the herbaceous peony and claw types of leaves were much higher than that with other types of leaves. P. ternata collected from Nanchuan County, except the ones with herbaceous peony leaves, displayed a high similarity with each other. Both UV absorbance and cluster analysis indicated that the protein content in P. ternata with the herbaceous peony leaves was less affected by habitats than that with other types of leaves. The results showed that it was necessary to increase the homogeneity of seeds for improving the protein content ofP. ternata.
基金supported by the National Natural Science Foundation of China (20835002)
文摘Consensus methods have presented promising tools for improving the reliability of quantitative models in near-infrared(NIR) spectroscopic analysis.A strategy for improving the performance of consensus methods in multivariate calibration of NIR spectra is proposed.In the approach,a subset of non-collinear variables is generated using successive projections algorithm(SPA) for each variable in the reduced spectra by uninformative variables elimination(UVE).Then sub-models are built using the variable subsets and the calibration subsets determined by Monte Carlo(MC) re-sampling,and the sub-model that produces minimal error in cross validation is selected as a member model.With repetition of the MC re-sampling,a series of member models are built and a consensus model is achieved by averaging all the member models.Since member models are built with the best variable subset and the randomly selected calibration subset,both the quality and the diversity of the member models are insured for the consensus model.Two NIR spectral datasets of tobacco lamina are used to investigate the proposed method.The superiority of the method in both accuracy and reliability is demonstrated.
