Biomedical subjects

Long-lian Zhao

Publications and source records attributed to Long-lian Zhao.

6 recordsLinked to original sources

PubMed2006

[Study on NPLS model with three-dimensional hyperspectrum for assessing per-mu-yield of winter wheat].

The present study piled a cube array with the winter wheat's cap reflection hyperspectra sampled from 35 experimental districts during 8 growth periods, and then used a multiway partial least squares (NPLS) algorithm to establish a model to assess the per-mu-yield of winter wheat. The model was used to predict the per-mu-yields of other 13 experimental districts. The correlation coefficient of predicted and actual values was 0.9366, and the mean relative error was 4.44%. These results showed a good prediction of the model. The study has guiding meaning to actual yield assessment.

English Abstract↗

PubMed2005

[Study on the application for near-infrared spectroscopy quantitative analysis and selecting optimum wavelength by the MAXR regression procedure].

This paper introduces the principle and method with which the model about the quantitative analysis of Fourier transformation near infrared (NIR) spectroscopy by MAXR regression procedure can be established. In this way, the authors have selected the wave length information by Matlab language design programming in order to establish the quantitative analysis models with near infrared spectroscopy. Taking sixty-six wheat samples as experiment materials, quantitative analysis models to determine protein content are established with thirty-three samples. The relative coefficient are 0.977 1 and 0.976 5 respectively and the standard error are 0.335 and 0.340 between the predication result of the two models which include respectively two or three wave length information and Kjeldahl's value for the protein content of the another thirty-three wheat samples. When selecting the wave length information, the MAXR regression procedure can establish the optimum regression models which contain 1 or 2...or k wavelength information respectively. MAXR regression procedure is a useful method when selecting the optimum wavelength information because of its shorter computation time, and the method not only can carefully select the essential wavelength information to establish NIR spectroscopy quantitative analysis models of resisting multicollinearity information disturbance, but also to establish the work for selecting optimum wavelength information which can direct to design the special NIR analysis instrument for analyzing specific component in the special samples.

Algorithms↗

PubMed2005

[Applied study on support vector machine (SVM) regression method in quantitative analysis with near-infrared spectroscopy].

This paper introduced the application of support vector machines(SVM) regression method based on statistics studytheory to the quantitative analysis with near-infrared (NIR) spectroscopy. Sixty-six wheat samples were used as experimental materials, and thirty-three of them were used as calibration samples. The protein contents and NIR spectra of the calibration samples were used to build SVM regression models by four different kernel functions. The protein content of the predicting samples are estimated by four different SVM regression models. All of the correlation coefficients between the estimated values by different SVM regression models and the standard chemical values of protein content by Kjeldahl's method are more than 0.97. The average absolute error is less than 0.32. To investigate the predicting effect, it is compared with PLS regression models. The result suggested that the SVM regression, which was built to estimate the protein content of wheat samples, can also be used in the quantitative analysis of real samples by NIR.

Algorithms↗

PubMed2004

[Influence of FT-NIR spectrometer scanning requirements on the math model's precision].

This study is based on the agriculture product near infrared spectra database, which is a foundation database. The database has very important effects on agriculture products quality analysis and agriculture breeding. What the NIR researchers and NIR users care about is how to utilize information of the foundation database fully. To share the NIR resource, unifying the scanning term to get high quality spectra is the first step. This article uses wheat powder as sample to study the influence of different resolution, different He-Ne frequency and sample granularity on the wheat powder protein model. The results show that scanning sample by 4, 8 or 16 cm(-1) resolution has little influence on the wheat powder protein math model. The change in He-Ne frequency has influence to wavenumber accuracy, but when the change is within 1 cm(-1), the influence is indistinctive. For FT-NIR instruments with He-Ne to have better stability, we needn't often adjust the He-Ne wavenumber. Sample granularity has more distinctive influence on the NIR math models.

Chemistry, Pharmaceutical↗

PubMed2002

[The rapid analysis of functional components of P. Lobata by near infrared spectrum].

The functional components of P. Lobata were analyzed rapidly by near infrared (NIR) spectral technology. The optimum conditions of mathematics model of three components (total isoflavones, puerarin, daidzin) were studied, including the sample set selection, chemical value analysis, the detection methods and conditions. The analytical results demonstrated that the correlation between the chemical value (true value) of the three components of sample set and the NIR predicated value is 0.975, 0.984, 0.996, respectively. The correlation between the chemical value of the testing sample set and the NIR predicated value is 0.982, 0.975 and 0.981, respectively. It proved that the mathematical model that we established can be used in practice.

Isoflavones↗

PubMed2002

[Study on quantitative analysis with near-infrared spectra using latent root regression model].

The latent root regression model with near-infrared spectra of 40 soybean samples was founded for analyzing the content of soybean protein in this study. The contents of protein in another 32 soybean samples were predicted by this model. The predicting results were compared with PLS, which shows that the latent root regression model can practically be used for the quantitative analysis of the biological samples with near-infrared spectra. This method is a new kind of chemometrics calibration method, which is modified from PCR. Because the method takes the role of sample composition into account when extracting the principal component from the NIR spectra of samples, the model has a good result in analyzing samples. Further more, the results showed that it is necessary to take account of the role of sample composition when building quantitative analysis model using NIR spectra.

Calibration↗