The maximal deoxynivalenol （DON） and fumonisins 131 ＋ B2 （FUM） contents in cereals are dictated by the European regulation 1126/2007. The direct measurement of these mycotoxins is a tedious and expensive process....The maximal deoxynivalenol （DON） and fumonisins 131 ＋ B2 （FUM） contents in cereals are dictated by the European regulation 1126/2007. The direct measurement of these mycotoxins is a tedious and expensive process. Our study is based on an alternative tool： near infrared spectroscopy. Different models were developed on 374 maize samples to predict their DON and FUM contents. Several parameters have been determined and used in a multivariate data analysis. Three models were developed： （1） a classification model based on Discriminant Factor Analysis （DFA）, （2） a linear model based on ANalysis of COVAriance （ANCOVA） and （3） a Partial Least Squares Discriminant Analysis model （PLS-DA）. Firstly, the performances of the DFA model for assessing DON and FUM risk were similar： 69 and 72% of the validation samples were respectively well classified. In the second part, the performances of the ANCOVA model for DON were higher than for FUM. The r2 was worth respectively 0.85 and 0.69. In the last part, the performances of the PLS-DA models were better for FUM than for DON. These results show that an evaluation of the mycotoxin risk is possible by analyzing selected kernel parameters measurable by secondary analytical such as near-infrared spectroscopy. Further work is needed to improve the models, adding more samples and using non linear approaches.展开更多
Discrimination of fatty acids （FAs） of lard in used cooking oil is important in halal determination. The aim of this study was to find the information related to the changes FAs of lard when frying in cooking oil. Q...Discrimination of fatty acids （FAs） of lard in used cooking oil is important in halal determination. The aim of this study was to find the information related to the changes FAs of lard when frying in cooking oil. Quantitative analysis of FAs composition extracted from a series of experiments which involving frying cooking oil spiked with lard at three different parameters; concentration of spiked lard, heating temperatures and period of frying. The samples were analyzed using Gas Chromatography （GC） and Principal Components Analysis （PCA） technique. Multivariate data from chromatograms of FAs were standardized and computed using Unscrambler X10 into covariance matrix and eigenvectors correspond to Principal Components （PCs）. Results have shown that the first and second PCs contribute to the FAs mapping which can be visualized by scores and loading plots to discriminate FAs of lard in used cooking oil展开更多
The flower bud of Tussilago farfara L.,also known as Farfarae Flos(FF),is commonly used in the traditional Chinese medicine(TCM)for the treatment of cough,bronchitis and asthmatic disorders.In this study,26 samples fr...The flower bud of Tussilago farfara L.,also known as Farfarae Flos(FF),is commonly used in the traditional Chinese medicine(TCM)for the treatment of cough,bronchitis and asthmatic disorders.In this study,26 samples from five provinces across northern China were collected,and internal transcribed spacer-polymerase chain reaction(ITS-PCR)coupled with high performance liquid chromatography(HPLC)fingerprint profiling was used for the quality evaluation of FF.The results of the ITS sequence analysis showed the high similarity values among these samples.ITS2 sequence exhibited less molecular diversity compared with ITS1,and no obvious correlation was found between the variation of ITS with the production areas or cultivation methods.The results of HPLC fingerprints in combination with the similarity analysis suggested that relative contents of phenylpropanoids and flavonoids varied among the 26 FF samples,and there was also no obvious difference among the different habitats.The phenylpropanoids and the flavonoids showed similar fluctuating patterns,and positive correlation among them was also observed.The results presented in this study suggested that FF from different habits showed high similarities,and ITS-PCR coupled with HPLC fingerprint profiling could be used as a valuable approach for the quality evaluation of FF.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
文摘The maximal deoxynivalenol （DON） and fumonisins 131 ＋ B2 （FUM） contents in cereals are dictated by the European regulation 1126/2007. The direct measurement of these mycotoxins is a tedious and expensive process. Our study is based on an alternative tool： near infrared spectroscopy. Different models were developed on 374 maize samples to predict their DON and FUM contents. Several parameters have been determined and used in a multivariate data analysis. Three models were developed： （1） a classification model based on Discriminant Factor Analysis （DFA）, （2） a linear model based on ANalysis of COVAriance （ANCOVA） and （3） a Partial Least Squares Discriminant Analysis model （PLS-DA）. Firstly, the performances of the DFA model for assessing DON and FUM risk were similar： 69 and 72% of the validation samples were respectively well classified. In the second part, the performances of the ANCOVA model for DON were higher than for FUM. The r2 was worth respectively 0.85 and 0.69. In the last part, the performances of the PLS-DA models were better for FUM than for DON. These results show that an evaluation of the mycotoxin risk is possible by analyzing selected kernel parameters measurable by secondary analytical such as near-infrared spectroscopy. Further work is needed to improve the models, adding more samples and using non linear approaches.
文摘Discrimination of fatty acids （FAs） of lard in used cooking oil is important in halal determination. The aim of this study was to find the information related to the changes FAs of lard when frying in cooking oil. Quantitative analysis of FAs composition extracted from a series of experiments which involving frying cooking oil spiked with lard at three different parameters; concentration of spiked lard, heating temperatures and period of frying. The samples were analyzed using Gas Chromatography （GC） and Principal Components Analysis （PCA） technique. Multivariate data from chromatograms of FAs were standardized and computed using Unscrambler X10 into covariance matrix and eigenvectors correspond to Principal Components （PCs）. Results have shown that the first and second PCs contribute to the FAs mapping which can be visualized by scores and loading plots to discriminate FAs of lard in used cooking oil
基金National Natural Science Foundation China(Grant No.31270008 and 81973466)National Standardization Program of Traditional Chinese Medicine(Grant No.ZYBZH-Y-JIN-34)。
文摘The flower bud of Tussilago farfara L.,also known as Farfarae Flos(FF),is commonly used in the traditional Chinese medicine(TCM)for the treatment of cough,bronchitis and asthmatic disorders.In this study,26 samples from five provinces across northern China were collected,and internal transcribed spacer-polymerase chain reaction(ITS-PCR)coupled with high performance liquid chromatography(HPLC)fingerprint profiling was used for the quality evaluation of FF.The results of the ITS sequence analysis showed the high similarity values among these samples.ITS2 sequence exhibited less molecular diversity compared with ITS1,and no obvious correlation was found between the variation of ITS with the production areas or cultivation methods.The results of HPLC fingerprints in combination with the similarity analysis suggested that relative contents of phenylpropanoids and flavonoids varied among the 26 FF samples,and there was also no obvious difference among the different habitats.The phenylpropanoids and the flavonoids showed similar fluctuating patterns,and positive correlation among them was also observed.The results presented in this study suggested that FF from different habits showed high similarities,and ITS-PCR coupled with HPLC fingerprint profiling could be used as a valuable approach for the quality evaluation of FF.
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.
