[Objective] This study was conducted to establish a near-infrared diffuse reflectance spectroscopy of Guizhou Aspidistra plants. [Method] Twenty three batch- es of Guizhou Aspidistra plants including A. chishuiensis, ...[Objective] This study was conducted to establish a near-infrared diffuse reflectance spectroscopy of Guizhou Aspidistra plants. [Method] Twenty three batch- es of Guizhou Aspidistra plants including A. chishuiensis, A. spinula, A. Caespitosa, A. sichuanensis, A. ebianensis, A. retusa, A. guizhouensis and A. liboensis were subjected to drying, pulverization and sieving and then directly determined for near- infrared reflectance spectrums; and the plants in this genus were classified by clus- ter analysis and principal component analysis （PCA）. [Result] The near-infrared re- flectance spectrums of the 23 batches of Guizhou Aspidistra plants showed very high similarity. The spectrums were processed by first derivative method, and the spectral range of 4 000-7 500 cm-1 was selected as the analytical range. Cluster analysis and PCA were employed to mass spectrum variables of plants in Aspidis- tra, fewer new variables became the linear combination of primary variables, and small differences between different varieties were enlarged, thereby facilitating intu- itive classification of plants in this genus. [Conclusion] Near-infrared diffuse re- flectance spectroscopy is nondestructive and rapid for determination of solid sam- pies, and provides a new method for the classification of Guizhou Aspidistra plants combined by information processing techniques.展开更多
[Objective] This study aimed to establish an identification system for drought-resistance in wheat by using near-infrared diffuse reflectance spectroscopy. [Method] In 2006-2007, 36 wheat varieties with different drou...[Objective] This study aimed to establish an identification system for drought-resistance in wheat by using near-infrared diffuse reflectance spectroscopy. [Method] In 2006-2007, 36 wheat varieties with different drought resistance were selected and were classified according to their drought resistance grades determined by the Technical Specification of Identification and Evaluation for Drought Resistance in Wheat （GB/T 21127-2007）. In addition, the harvested wheat seed samples were spectrally analyzed with FOSS NIRSystems5000 near-infrared spectrum analyzer for grain quality （full spectrum analyzer） and then the forecasted regression equations were established. [Result] After the establishment of a database and validation, dis- criminated functions were obtained. The determination coefficient （RSQ） and coeffi- cients of determination for cross validation （1-VR） in the discriminant function built with seed samples from water stress area were 0.846 0 and 0.781 8, respectively, which indicated that the consistency between drought resistance and spectral charac- teristics in wheat varieties was good, and there was high correlation between the near-infrared diffuse reflectance spectra of seeds and the drought resistance in wheat. [Conclusiou] Under water stress condition, it is feasible to establish a conve- nient, rapid and no-damage identification system for the drought resistance in wheat by using the near-infrared diffuse reflectance spectrum technique to scan wheat seeds.展开更多
In this paper,the Fourier transform near-infrared(FTNIR)diffuse reflectance spectroscopy is applied for the rapid determination of protein in millet.The partial least-squares(PLS)regression is successfully used as an ...In this paper,the Fourier transform near-infrared(FTNIR)diffuse reflectance spectroscopy is applied for the rapid determination of protein in millet.The partial least-squares(PLS)regression is successfully used as an effective multivariate calibration technique.The calibration set is composed of 20 standard millet samples that the protein contents were determined by the traditional Kjeldahl method.The optimal model dimension is found to be 5 by cross-validation.22 millet samples were determined by the proposed FTNIR-PLS method.The correlation coefficient between the concentration values obtained by the FTNIR-PLS method and the traditional Kjeldahl method is 0.9805.The standard error of prediction(SEP)is 0.28% and the mean recovery is 100.2%.The proposed method has been successfully applied for the routine analysis of protein in about 10,000 grain samples.展开更多
Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the ...Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.展开更多
A method for quantitative determination of fish sperm deoxyribonucleic acid(fsDNA)was developed by using titanium dioxide(TiO2)as an adsorbent and near-infrared diffuse reflectance spectroscopy(NIRDRS).The selective e...A method for quantitative determination of fish sperm deoxyribonucleic acid(fsDNA)was developed by using titanium dioxide(TiO2)as an adsorbent and near-infrared diffuse reflectance spectroscopy(NIRDRS).The selective enrichment of fsDNA was proved by comparing the adsorption efficiency of bovine serum albumin,tyrosine and tryptophan,and the low adsorption background of TiO2 was illustrated by comparing the spectra of four commonly-used inorganic adsorbents(alkaline aluminium oxide,neutral aluminium oxide,nano-hydroxyapatite and silica).The spectral feature of fsDNA can be clearly observed in the spectrum of the sample.Partial least squares(PLS)model was built for quantitative determination of fsDNA using 28 solutions,and 13 solutions with interferences were used for validation of the model.The results showed that the correlation coefficient(R)between the predicted and the reference concentration is 0.9727 and the recoveries of the validation samples are in the range of 98.2%-100.7%.展开更多
Enrichment technique has been proved to be an efficient way to make the near-infrared diffuse reflectancespectroscopy（NIRDRS） suitable for micro analysis. However, low selectivity presented by conventional enrichmen...Enrichment technique has been proved to be an efficient way to make the near-infrared diffuse reflectancespectroscopy（NIRDRS） suitable for micro analysis. However, low selectivity presented by conventional enrichmentmethods makes the quantitative analysis easy to be affected by the coexisting components. In this study, a specificenrichment method with chemical bonding via thiol-maleimide click reaction was used to achieve the reduction of theinterferences. Taking cysteine as the analyzing target, maleimide-functionalized SiO2 nanoparticles were prepared forthe enrichment of cysteine. Then determination of cysteine in aqueous solution and human serum was studied usingthe partial least squares model built from the NIRDRS spectra of the adsorbate. The results show that the concentra-tion that can be quantitatively detected is as low as 2.0 μg/mL, and the correlation coefficient（R） between thereference and predicted concentration is 0.9871 for the validation samples. The recoveries are in the range of89.5%-113.8% for human serum samples in the concentration range of 0--16.2 μg/mL.展开更多
Near infrared diffuse reflectance spectroscopy(NIRDRS) has gained wide attention due to its convenience for rapid quantitative analysis of complex samples. A method for rapid analysis of triglycerides in human serum u...Near infrared diffuse reflectance spectroscopy(NIRDRS) has gained wide attention due to its convenience for rapid quantitative analysis of complex samples. A method for rapid analysis of triglycerides in human serum using NIRDRS with silver mirror as the substrate is developed. Due to the even and high reflectance of the silver mirror, the spectral response is enhanced and the background interference is reduced.Furthermore, both linear and nonlinear modeling strategies were investigated adopting the partial least squares(PLS) and least squares support vector regression(LS-SVR), continuous wavelet transform(CWT)was used for spectral preprocessing, and variable selection was tried using Monte Carlo uninformative variable elimination(MC-UVE), randomization test(RT) and competitive adaptive reweighted sampling(CARS) for optimization the models. The results show that the determination coefficient(R) between the predicted and reference concentration is 0.9624 and the root mean squared error of prediction(RMSEP) is 0.21. The maximum deviation of the prediction results is as low as 0.473 mmol/L. The proposed method may provide an alternative method for routine analysis of serum triglycerides in clinical applications.展开更多
Based on the effect of sample size on the near- infrared （NIR） spectrum, the absorbance （log（R）） in any wavelength is divided into two parts, and one of them is defined as non-particle-size-related spectrometry ...Based on the effect of sample size on the near- infrared （NIR） spectrum, the absorbance （log（R）） in any wavelength is divided into two parts, and one of them is defined as non-particle-size-related spectrometry （nPRS） because it is not influenced by particle size. To study the relationship between the absorbance and l^article size, the experiment material including nine samples with different particle size was used. According to the regression analysis, the relationship was studied as the reciprocal regression model, y = a ~ bx ＋ c/x. Meanwhile, the model divides absorbance into two parts, one of them forms nPRS. According to the nPRS, a new correction method, particle size regression correction （PRC） was introduced. In discriminate analysis, the spectra from three different samples （rice, glutinous rice and sago）, pretreated by PRC, could be directly and accurately distinguished by principal component analysis （PCA）, while by the traditional correction method, such as multiplicative signal correction （MSC） and standard normal variate （SNV）, could not do that.展开更多
基金Supported by National Natural Science Foundation of China(81360623)~~
文摘[Objective] This study was conducted to establish a near-infrared diffuse reflectance spectroscopy of Guizhou Aspidistra plants. [Method] Twenty three batch- es of Guizhou Aspidistra plants including A. chishuiensis, A. spinula, A. Caespitosa, A. sichuanensis, A. ebianensis, A. retusa, A. guizhouensis and A. liboensis were subjected to drying, pulverization and sieving and then directly determined for near- infrared reflectance spectrums; and the plants in this genus were classified by clus- ter analysis and principal component analysis （PCA）. [Result] The near-infrared re- flectance spectrums of the 23 batches of Guizhou Aspidistra plants showed very high similarity. The spectrums were processed by first derivative method, and the spectral range of 4 000-7 500 cm-1 was selected as the analytical range. Cluster analysis and PCA were employed to mass spectrum variables of plants in Aspidis- tra, fewer new variables became the linear combination of primary variables, and small differences between different varieties were enlarged, thereby facilitating intu- itive classification of plants in this genus. [Conclusion] Near-infrared diffuse re- flectance spectroscopy is nondestructive and rapid for determination of solid sam- pies, and provides a new method for the classification of Guizhou Aspidistra plants combined by information processing techniques.
基金Supported by the Special Fund for the Industrial Technology System Construction of Modern Agriculture in Wheat(CARS-E-2-36)the Special Fund for Henan Industrial Technology System Construction of Modern Agriculture in Wheat(S2010-10-02)National Support Program for Science and Technology(2011BAD35B03)~~
文摘[Objective] This study aimed to establish an identification system for drought-resistance in wheat by using near-infrared diffuse reflectance spectroscopy. [Method] In 2006-2007, 36 wheat varieties with different drought resistance were selected and were classified according to their drought resistance grades determined by the Technical Specification of Identification and Evaluation for Drought Resistance in Wheat （GB/T 21127-2007）. In addition, the harvested wheat seed samples were spectrally analyzed with FOSS NIRSystems5000 near-infrared spectrum analyzer for grain quality （full spectrum analyzer） and then the forecasted regression equations were established. [Result] After the establishment of a database and validation, dis- criminated functions were obtained. The determination coefficient （RSQ） and coeffi- cients of determination for cross validation （1-VR） in the discriminant function built with seed samples from water stress area were 0.846 0 and 0.781 8, respectively, which indicated that the consistency between drought resistance and spectral charac- teristics in wheat varieties was good, and there was high correlation between the near-infrared diffuse reflectance spectra of seeds and the drought resistance in wheat. [Conclusiou] Under water stress condition, it is feasible to establish a conve- nient, rapid and no-damage identification system for the drought resistance in wheat by using the near-infrared diffuse reflectance spectrum technique to scan wheat seeds.
文摘In this paper,the Fourier transform near-infrared(FTNIR)diffuse reflectance spectroscopy is applied for the rapid determination of protein in millet.The partial least-squares(PLS)regression is successfully used as an effective multivariate calibration technique.The calibration set is composed of 20 standard millet samples that the protein contents were determined by the traditional Kjeldahl method.The optimal model dimension is found to be 5 by cross-validation.22 millet samples were determined by the proposed FTNIR-PLS method.The correlation coefficient between the concentration values obtained by the FTNIR-PLS method and the traditional Kjeldahl method is 0.9805.The standard error of prediction(SEP)is 0.28% and the mean recovery is 100.2%.The proposed method has been successfully applied for the routine analysis of protein in about 10,000 grain samples.
文摘Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.
基金supported by the National Natural Science Foundation of China(No.21775076)the fundamental research funds for central universities(China)
文摘A method for quantitative determination of fish sperm deoxyribonucleic acid(fsDNA)was developed by using titanium dioxide(TiO2)as an adsorbent and near-infrared diffuse reflectance spectroscopy(NIRDRS).The selective enrichment of fsDNA was proved by comparing the adsorption efficiency of bovine serum albumin,tyrosine and tryptophan,and the low adsorption background of TiO2 was illustrated by comparing the spectra of four commonly-used inorganic adsorbents(alkaline aluminium oxide,neutral aluminium oxide,nano-hydroxyapatite and silica).The spectral feature of fsDNA can be clearly observed in the spectrum of the sample.Partial least squares(PLS)model was built for quantitative determination of fsDNA using 28 solutions,and 13 solutions with interferences were used for validation of the model.The results showed that the correlation coefficient(R)between the predicted and the reference concentration is 0.9727 and the recoveries of the validation samples are in the range of 98.2%-100.7%.
文摘Enrichment technique has been proved to be an efficient way to make the near-infrared diffuse reflectancespectroscopy（NIRDRS） suitable for micro analysis. However, low selectivity presented by conventional enrichmentmethods makes the quantitative analysis easy to be affected by the coexisting components. In this study, a specificenrichment method with chemical bonding via thiol-maleimide click reaction was used to achieve the reduction of theinterferences. Taking cysteine as the analyzing target, maleimide-functionalized SiO2 nanoparticles were prepared forthe enrichment of cysteine. Then determination of cysteine in aqueous solution and human serum was studied usingthe partial least squares model built from the NIRDRS spectra of the adsorbate. The results show that the concentra-tion that can be quantitatively detected is as low as 2.0 μg/mL, and the correlation coefficient（R） between thereference and predicted concentration is 0.9871 for the validation samples. The recoveries are in the range of89.5%-113.8% for human serum samples in the concentration range of 0--16.2 μg/mL.
基金supported by the National Natural Science Foundation of China (Nos. 21475068, 21775076)
文摘Near infrared diffuse reflectance spectroscopy(NIRDRS) has gained wide attention due to its convenience for rapid quantitative analysis of complex samples. A method for rapid analysis of triglycerides in human serum using NIRDRS with silver mirror as the substrate is developed. Due to the even and high reflectance of the silver mirror, the spectral response is enhanced and the background interference is reduced.Furthermore, both linear and nonlinear modeling strategies were investigated adopting the partial least squares(PLS) and least squares support vector regression(LS-SVR), continuous wavelet transform(CWT)was used for spectral preprocessing, and variable selection was tried using Monte Carlo uninformative variable elimination(MC-UVE), randomization test(RT) and competitive adaptive reweighted sampling(CARS) for optimization the models. The results show that the determination coefficient(R) between the predicted and reference concentration is 0.9624 and the root mean squared error of prediction(RMSEP) is 0.21. The maximum deviation of the prediction results is as low as 0.473 mmol/L. The proposed method may provide an alternative method for routine analysis of serum triglycerides in clinical applications.
基金The work was made possible with support from two research projects by the National Natural Science Foundation of China （Grant Nos. 61144012 and 31101289）.
文摘Based on the effect of sample size on the near- infrared （NIR） spectrum, the absorbance （log（R）） in any wavelength is divided into two parts, and one of them is defined as non-particle-size-related spectrometry （nPRS） because it is not influenced by particle size. To study the relationship between the absorbance and l^article size, the experiment material including nine samples with different particle size was used. According to the regression analysis, the relationship was studied as the reciprocal regression model, y = a ~ bx ＋ c/x. Meanwhile, the model divides absorbance into two parts, one of them forms nPRS. According to the nPRS, a new correction method, particle size regression correction （PRC） was introduced. In discriminate analysis, the spectra from three different samples （rice, glutinous rice and sago）, pretreated by PRC, could be directly and accurately distinguished by principal component analysis （PCA）, while by the traditional correction method, such as multiplicative signal correction （MSC） and standard normal variate （SNV）, could not do that.
