Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojia...Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.展开更多
The applications of laser-induced breakdown spectroscopy(LIBS) on classifying complex natural organics are relatively limited and their accuracy still requires improvement.In this work,to study the methods on classifi...The applications of laser-induced breakdown spectroscopy(LIBS) on classifying complex natural organics are relatively limited and their accuracy still requires improvement.In this work,to study the methods on classification of complex organics,three kinds of fresh leaves were measured by LIBS.100 spectra from 100 samples of each kind of leaves were measured and then they were divided into a training set and a test set in a ratio of 7:3.Two algorithms of chemometric methods including the partial least squares discriminant analysis(PLS-DA) and principal component analysis Mahalanobis distance(PCA-MD) were used to identify these leaves.By using 23 lines from 16 elements or molecules as input data,these two methods can both classify these three kinds of leaves successfully.The classification accuracies of training sets are both up to 100% by PCA-MD and PLS-DA.The classification accuracies of the test set are 93.3% by PCA-MD and 97.8% by PLS-DA.It means that PLS-DA is better than PCA-MD in classifying plant leaves.Because the components in PLS-DA process are more suitable for classification than those in PCA-MD process.We think that this work can provide a reference for plant traceability using LIBS.展开更多
Human serum albumin(HSA)injectable product is a severely afflicted area on drug safety due to its high price and restricted supply.Raman spectroscopy performances high specificity on HSA detection and it is even possi...Human serum albumin(HSA)injectable product is a severely afflicted area on drug safety due to its high price and restricted supply.Raman spectroscopy performances high specificity on HSA detection and it is even possible to determine HSA injectable products noninvasively.In this study,we developed a noninvasive rapid screening method for of HSA injectable products by using portable Raman spectrometer.Qualitative models were established by using principal component analysis combined with classical least squares(PCA-CLS)algorithm,while quanti-tative model was established by using partial least squares(PLS)algorithm.Model transfer in different instruments of both the same and different apparatus modules was further discussed in this paper.A total of 34 HSA injectable samples collected from markets were used for verification.The identification results showed 100%accuracy and the predicted concentrations of those identified as true HSA were consistent with their labeled concentrations.The quantitative results also indicated that model transfer was excellent in the same apparatus modules of Raman spectrometer at all concentration levels,and still good enough in the different apparatus modules although the relative standard deviation(RSD)value showed a little increasing trend at low HSA concentration level.In conclusion,the method was proved to be feasible and efficient for screening HSA injections,especially on its screening speed and the consideration of glass containers.Moreover,with inspiring results on the model transfer,the method could be used as a universal screening mean to different Raman instruments.展开更多
文摘Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.
基金supported by the Fundamental Research Funds for the Central Universities of Ministry of Education of China(No.JB190501)Science and Technology Innovation Team of Shaanxi Province(No.2019TD-002)National Natural Science Foundation of China(No.11774277)。
文摘The applications of laser-induced breakdown spectroscopy(LIBS) on classifying complex natural organics are relatively limited and their accuracy still requires improvement.In this work,to study the methods on classification of complex organics,three kinds of fresh leaves were measured by LIBS.100 spectra from 100 samples of each kind of leaves were measured and then they were divided into a training set and a test set in a ratio of 7:3.Two algorithms of chemometric methods including the partial least squares discriminant analysis(PLS-DA) and principal component analysis Mahalanobis distance(PCA-MD) were used to identify these leaves.By using 23 lines from 16 elements or molecules as input data,these two methods can both classify these three kinds of leaves successfully.The classification accuracies of training sets are both up to 100% by PCA-MD and PLS-DA.The classification accuracies of the test set are 93.3% by PCA-MD and 97.8% by PLS-DA.It means that PLS-DA is better than PCA-MD in classifying plant leaves.Because the components in PLS-DA process are more suitable for classification than those in PCA-MD process.We think that this work can provide a reference for plant traceability using LIBS.
基金Youth Develop-ment Research Foundation(No.2015C03)of Na-tional Institutes of Food and Drug Control,P.R.China.
文摘Human serum albumin(HSA)injectable product is a severely afflicted area on drug safety due to its high price and restricted supply.Raman spectroscopy performances high specificity on HSA detection and it is even possible to determine HSA injectable products noninvasively.In this study,we developed a noninvasive rapid screening method for of HSA injectable products by using portable Raman spectrometer.Qualitative models were established by using principal component analysis combined with classical least squares(PCA-CLS)algorithm,while quanti-tative model was established by using partial least squares(PLS)algorithm.Model transfer in different instruments of both the same and different apparatus modules was further discussed in this paper.A total of 34 HSA injectable samples collected from markets were used for verification.The identification results showed 100%accuracy and the predicted concentrations of those identified as true HSA were consistent with their labeled concentrations.The quantitative results also indicated that model transfer was excellent in the same apparatus modules of Raman spectrometer at all concentration levels,and still good enough in the different apparatus modules although the relative standard deviation(RSD)value showed a little increasing trend at low HSA concentration level.In conclusion,the method was proved to be feasible and efficient for screening HSA injections,especially on its screening speed and the consideration of glass containers.Moreover,with inspiring results on the model transfer,the method could be used as a universal screening mean to different Raman instruments.
