In this paper, a double artificial neural network （DANN） algorithm was used to parse near infrared （NIR） reflectance spectrum of Cofrel medicines. The contents of benproperine phosphate, which is the effective ing...In this paper, a double artificial neural network （DANN） algorithm was used to parse near infrared （NIR） reflectance spectrum of Cofrel medicines. The contents of benproperine phosphate, which is the effective ingredient in Cofrel medicines, were accurately nondestructive quantitatively predicted. Compared the results with those of HPLC, the relative errors （RE %） were less than 0.18%. The analytical results could be applied to qualitative control of Cofrel medicines.展开更多
Human serum albumin(HSA)is the most abundant protein in plasma and plays an essential physiological role in the human body.Ethanol precipitation is the most widely used way to obtain HSA,and pH and ethanol are crucial...Human serum albumin(HSA)is the most abundant protein in plasma and plays an essential physiological role in the human body.Ethanol precipitation is the most widely used way to obtain HSA,and pH and ethanol are crucial factors affecting the process.In this study,infrared(IR)spectroscopy and near-infrared(NIR)spectroscopy in combination with chemometrics were used to investigate the changes in the secondary structure and hydration of HSA at acidic pH(5.6-3.2)and isoelectric pH when ethanol concentration was varied from 0%to 40%as a perturbation.IR spectroscopy combined with the two-dimensional correlation spectroscopy(2DCOS)analysis for acid pH system proved that the secondary structure of HSA changed significantly when pH was around 4.5.What's more,the IR spectroscopy and 2DCOS analysis showed different secondary structure forms under different ethanol concentrations at the isoelectric pH.For the hydration effect analysis,NIR spectroscopy combined with the McCabe-Fisher method and aquaphotomics showed that the free hydrogen-bonded water fluctuates dynamically,with ethanol at 0-20%enhancing the hydrogen-bonded water clusters,while weak hydrogen-bonded water clusters were formed when the ethanol concentration increased continuously from 20%to 30%.These measurements provide new insights into the structural changes and changes in the hydration behavior of HSA,revealing the dynamic process of protein purification,and providing a theoretical basis for the selection of HSA alcoholic precipitation process parameters,as well as for further studies of complex biological systems.展开更多
Filtration processes are worldwide used for sterilizing solutions and substrates. Filtration seems to induce the formation of aqueous nanostructures. The aim of this work was to verify the influence of filtration proc...Filtration processes are worldwide used for sterilizing solutions and substrates. Filtration seems to induce the formation of aqueous nanostructures. The aim of this work was to verify the influence of filtration processes on water structure detected by spectral variations in NIR region. Samples of ultrapure water （MilliQ-Millipore, Vimodrone, Milan, Italy） before and after iterated filtrations were analyzed. NIR spectra were collected in transmission mode in the whole NIR range, by using NIRFIex N500 spectrometer at constant temperature （40 ± 1 ℃）. NIR data were processed using Unscrambler software v. 9.2 in evaluating qualitative differences between filtered and not filtered samples. The information related to possible solvent physical stresses were highlighted in the range 6500-7500 cm^-1. The shifts observed were ascribable to a different distribution of the number of water molecules involved in hydrogen bonds in filtered and not filtered water samples, at constant temperature. NIR spectroscopy, commonly used to study relationship between spectral changes and hydrogen bonds in water at increasing temperature values, was applied to evaluate effects of filtration processes on water structure. The obtained results are in agreement with literature data and allowed the improvement of the knowledge about pure water characteristics when some mechanical perturbations are applied.展开更多
The near infrared （NIR） spectroscopy technique has been applied in many fields because of its advantages of simple preparation, fast response, and non-destructiveness. We investigated the potential of NIR spectrosco...The near infrared （NIR） spectroscopy technique has been applied in many fields because of its advantages of simple preparation, fast response, and non-destructiveness. We investigated the potential of NIR spectroscopy in diffuse reflectance mode for determining the soluble solid content （SSC） and acidity （pH） of intact loquats. Two cultivars of loquats （Dahongpao and Jiajiaozhong） harvested from two orchards （Tangxi and Chun＇an, Zhejiang, China） were used for the measurement of NIR spectra between 800 and 2500 nm. A total of 400 loquats （100 samples of each cultivar from each orchard） were used in this study. Relationships between NIR spectra and SSC and acidity of loquats were evaluated using partial least square （PLS） method. Spectra preprocessing options included the first and second derivatives, multiple scatter correction （MSC）, and the standard normal variate （SNV）. Three separate spectral windows identified as full NIR （800-2500 nm）, short NIR （800-1100 rim）, and long NIR （1100-2500 nm） were studied in factorial combination with the preprocessing options. The models gave relatively good predictions of the SSC of loquats, with root mean square error of prediction （RMSEP） values of 1.21, 1.00, 0.965, and 1.16 °Brix for Tangxi-Dahongpao, Tangxi-Jiajiaozhong, Chun＇an-Dahongpao, and Chun＇an-Jiajiaozhong, respectively. The acidity prediction was not satisfactory, with the RMSEP of 0.382, 0.194, 0.388, and 0.361 for the above four loquats, respectively. The results indicate that NIR diffuse reflectance spectroscopy can be used to predict the SSC and acidity of loquat fruit.展开更多
Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models...Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R<sup>2</sup> 0.85) is better than the whole seed (0.33 R<sup>2</sup> 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R<sup>2</sup>_whole seed = 0.78, R<sup>2</sup>_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.展开更多
A non-destructive technique should be developed for performance analysis of mango fruits because the spongy tissue or internal defects could lower the quality of mango fruit and incur a lack of productivity.In this st...A non-destructive technique should be developed for performance analysis of mango fruits because the spongy tissue or internal defects could lower the quality of mango fruit and incur a lack of productivity.In this study,wavelength selection methods were proposed to identify the range of wavelengths for the classification of defected and healthy mango fruits.Feature selection methods were adopted here to achieve a significant selection of wavelengths.To measure the goodness of themodel,the datasetwas collected using the NIR(Near Infrared)spectroscopy with wavelength ranging from 673 nm–1900 nm.The classification was performed using Euclidean distance measure both in the original feature space and in FLD(Fisher's Linear Discriminant)transformed space.The experimental results showed that the lower range wavelength(673 nm–1100 nm)was the efficient wavelength for the detection of internal defects in mangoes.Further to express the effectiveness of the model,different feature selection techniques were investigated and found that the Fisher's criterion based technique appeared to be the best method for effective wavelength selection useful for classification of defected and healthy mango fruits.The optimal wavelengths were found in the range of 702.72 nm to 752.34 nm using Fisher's criterionwith a classification accuracy of 84.5%.This study showed that NIR systemis a useful technology for the automaticmango fruit assessmentwhich has the potential to be used for internal defects in online sorting,easily distinguishable by those who do not meet minimum quality requirements.展开更多
To develop near-infrared （NIR） reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders ...To develop near-infrared （NIR） reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders of cefoperazone sodium/ sulbactam sodium were directly analyzed by non-destructive NIR reflectance spectroscopy using the spectrometer EQUINOX55. Two quantitative methods via integrating sphere （IS） and fiberoptic probe （FOP） models were explored from 6 batches of commercial samples and 42 batches of laboratory samples at a content ranging from 30% to 70% for cefoperazone and 60% to 20% for sulbactam. The root mean square errors of cross validation （RMSECV） and the root mean square errors of prediction （RMSEP） of IS were 1.79% and 2.85%, respectively, for cefoperazone sodium, and were 1.86% and 3.08%, respectively, for sulbactam sodium; and those of FOP were 2.93% and 2.92%, respectively, for cefoperazone sodium, and were 2.23% and 3.01%, respectively, for sulbactam sodium. Based on the ICH guidelines and Ref. 12, the quantitative models were then evaluated in terms of specificity, linearity, accuracy, precision, robustness and model transferability. The non-destructive quantitative NIR methods used in this study are applicable for rapid analysis of injectable powdered drugs from different manufacturers.展开更多
Near infrared reflectance （N1R） spectroscopy is as a rapid, convenient and simple nondestructive technique useful for quantifying several soil properties. This method was used to estimate nitrogen （N） and organic ...Near infrared reflectance （N1R） spectroscopy is as a rapid, convenient and simple nondestructive technique useful for quantifying several soil properties. This method was used to estimate nitrogen （N） and organic matter （OM） content in a soil of Zhejiang Province, Hangzhou County. A total of 125 soil samples were taken from the field. Ninety-five samples spectra were used during the calibration and cross validation stage. Thirty samples spectra were used to predict N and OM concentration. NIR spectra of these samples were correlated using partial least square regression. The regression coefficients between measured and predicted values of N and OM was 0.92 and 0.93, and SEP （standard error of prediction） were 3.28 and 0.06, respectively, which showed that NIR method had potential to accurately predict these constituents in this soil. The results showed that NIR spectroscopy could be a good tool for precision farming application.展开更多
The encapsulation of essential oil components in cyclodextrins(CDs)to form inclusion complexes(ICs)is an effective strategy for improving their stability and bioaccessibility.The aim of the present study was to obtain...The encapsulation of essential oil components in cyclodextrins(CDs)to form inclusion complexes(ICs)is an effective strategy for improving their stability and bioaccessibility.The aim of the present study was to obtain a deeper understanding of the encapsulation behavior of multi-components inβ-CD.vip molecules ofα-pinene,myrcene,and 3-carene,having the same molecular weight,formed ICs withβ-CD by a freeze-drying method.A simplex lattice mixture design with 28 experiments was carried out.Statistical analysis was applied to analyze the encapsulation behavior of vip components,and quantitative models of vip components in ICs were constructed by coupling with near-infrared(NIR)spectroscopy and chemometrics analysis.Besides,the molecular docking technique was used to obtain the optimal conformation and explain the binding behavior of inclusion.The results suggested that the spatial structure and ratio of vip molecules were the key factors affecting the encapsulation effect.A non-destructive and rapid NIR analytical model for the vip component in ICs could be obtained by second derivative(2nd der)pretreatment.Collectively,the encapsulation of vip components inβ-CD was differentiated,and NIR could be used as a rapid and non-destructive tool for quantitative analysis of ICs.展开更多
The near infrared spectra of 178 recombinant inbred lines （RILs） from the cross of Ⅱ-32B/Yuezaoxian 6 （YZX6） and 511 varieties in rice were acquired. A total of 80 RILs and 96 cultivars were selected as modeling ...The near infrared spectra of 178 recombinant inbred lines （RILs） from the cross of Ⅱ-32B/Yuezaoxian 6 （YZX6） and 511 varieties in rice were acquired. A total of 80 RILs and 96 cultivars were selected as modeling samples by comparing the spectra similarity primarily. Three partial least square （PLS） regression models were developed, based on the RILs （RIL-model）, the varieties （Var-model） and their mixture （Mix-model）, for protein content （PC） and amylose content （AC）, respectively. Cross validation and outer prediction showed that the models were largely influenced by the range and distribution of modeling samples. The regression model of PC based on the cultivars and the model of AC based on RILs had higher coefficient of determination （r^2 ≥ 0.9） and lower root mean square error of cross validation （RMSECVs）. The disadvantages of RIL samples for PC model and variety samples for AC model were probably caused by the narrow range of variance. Aberrant predictions were obtained for outer sample with PC or AC outside the range or within the distribution gap of modeling samples. The Mix-models gave more reliable prediction as the distribution of RIL and variety modeling samples were complementary to each other.展开更多
A new strategy for quantitative analysis of a major clinical biochemical indicator called glycatedhemoglobin(Hb·A1c)was proposed.The technique was based on the simultaneous near-infrared(NIR)spectral determinatio...A new strategy for quantitative analysis of a major clinical biochemical indicator called glycatedhemoglobin(Hb·A1c)was proposed.The technique was based on the simultaneous near-infrared(NIR)spectral determination of hemoglobin(Hb)and absolute HbAlc content(Hb·HbA1c)inhuman hemolysate samples.Wavelength selections were accomplished using the improvedmoving window partial least square(MWPLS)method for stability.Each model was establishedusing an approach based on randomness,similarity,and stability to obtain objective,stable,andpractical models.The optimal wavebands obtained using MWPLS were 958 to 1036 nm for Hband 1492 to 1858 nm for Hb·HbA1c,which were within the NIR overtone region.The validationroot mean square error and validation correlation coeficients of prediction(V-SEP,V-Rp)were 3.4g L^(-1) and 0.967 for Hb,respectively,whereas the corresponding values for Hb.HbAic were 0.63 g L^(-1) and 0.913.The corresponding V-SEP and V-Rp were 0.40% and 0.829 for the relativepercentage of HbA1c.The experimental results confirm the feasibility for the quantification of HbAlc based on simultaneous NIR spectroscopic analyses of Hb and Hb·HbA1c.展开更多
This research aimed to establish near infrared(NIR)spectroscopy models for identification ofsyrup types in which the maple syrup was discriminated from other syrup types.Thirty syruptypes were used in this research;th...This research aimed to establish near infrared(NIR)spectroscopy models for identification ofsyrup types in which the maple syrup was discriminated from other syrup types.Thirty syruptypes were used in this research;the NIR spectra of each type were recorded with 10 replicates.The repeatability and reproducibility of NIR scamning were perfomed,and the absorbance atG940cn-1 was used for calculation,.Principal component analysis was used to group the syruptype.Identification models were developed by soft independent modeling by,class analogy(SIMCA)and partial least-squares diseriminant analysis(PLS.DA),The SiMCA models of alsyrup types exhibited accuracy percentage of 93.3-100%for identifying syrup types,whereasmaple syrup discrimination models showed percentage of accuracy between 83.2%and 100%.The PLS-DA technique gave the accuracy of syrup types classification bet ween 96.6%and 100%and presented ability on discrimination of maple syrup form other types of syrup with accuracyof 100%.The finding presented the potential of NIR spectroscopy for the syrup typeidentification.展开更多
Variable selection is applied widely for visible-near infrared(Vis-NIR)spectroscopy analysis of internal quality in fruits.Different spectral variable selection methods were compared for online quantitative analysis o...Variable selection is applied widely for visible-near infrared(Vis-NIR)spectroscopy analysis of internal quality in fruits.Different spectral variable selection methods were compared for online quantitative analysis of soluble solids content(SSC)in navel oranges.Moving window partial least squares(MW-PLS),Monte Carlo uninformative variables elimination(MC-UVE)and wavelet transform(WT)combined with the MC-UVE method were used to select the spectral variables and develop the calibration models of online analysis of SSC in navel oranges.The performances of these methods were compared for modeling the Vis NIR data sets of navel orange samples.Results show that the WT-MC-UVE methods gave better calibration models with the higher correlation cofficient(r)of 0.89 and lower root mean square error of prediction(RMSEP)of 0.54 at 5 fruits per second.It concluded that Vis NIR spectroscopy coupled with WT-MC-UVE may be a fast and efective tool for online quantitative analysis of SSC in navel oranges.展开更多
Objective To observe the effect of acupuncture at Kongzui（孔最LU 6）,Sanyinjiao（三阴交 SP 6） and Zusanli（足三里 ST 36） on cerebral blood oxygenation level and explore the relevance between acupuncture and cerebra...Objective To observe the effect of acupuncture at Kongzui（孔最LU 6）,Sanyinjiao（三阴交 SP 6） and Zusanli（足三里 ST 36） on cerebral blood oxygenation level and explore the relevance between acupuncture and cerebral blood oxygenation level using near-infrared spectroscopy（NIRS）.Methods Quasi-randomized design（random test sequence） was used.In clinical trial ①,placebo acupuncture was applied at Baihui（百会GV 20） of18 adults.In clinical trial ②,54 adults were divided into three groups with 18 each in which acupuncture was applied at LU 6,SP 6 and ST 36 respectively.Before and after acupuncture,verbal fluency test（VFT） was performed and the blood oxygenation level of cerebral cortex was measured using NIRS.Quantized data was processed with JMP10.0.2 software and SPSS software.Results In clinical trial ①,the mean integral values of cerebral blood oxygenation level were 10.8 mMcm·s and 9.2 mMcm·s respectively before and after acupuncture at GV 20 in placebo acupuncture group.There was no significant difference in the cerebral blood oxygenation level after acupuncture.In clinical trial ②,the mean integral values of cerebral blood oxygen level were18.1 mMcm·s and 8.6 mMcm·s respectively before and after acupuncture at LU 6 in[LU 6]acupuncture group,the cerebral blood oxygenation level was significantly decreased after acupuncture（P = 0.001）.The mean integral values of cerebral blood oxygenation level were 16.1 mMcm·s and 17.4 mMcm·s respectively before and after acupuncture at SP 6 in[SP 6]acupuncture group,the cerebral blood oxygenation level was slightly increased after acupuncture,but the increase was not statistically significant.The mean integral values of cerebral blood oxygenation level were 13.8 mMcnvs and 10.1 mMcnvs respectively before and after acupuncture at ST 36 in[ST 36]acupuncture group,the cerebral blood oxygenation level was slightly deceased after acupuncture,but the increase was not statistically significant.Conclusion The cerebral blood oxygenation level of frontal head was decreased by acupuncture at LU 6,the cerebral blood oxygenation level of frontal head was intended to decrease by acupuncture at ST 36.The cerebral blood oxygenation level of frontal head is intended to increase by acupuncture at SP 6.展开更多
Sweetpotato starch thermal properties and its noodle quality were analyzed using a rapid predictive method based on near-infrared spectroscopy （NIRS）. This method was established based on a total of 93 sweetpotato g...Sweetpotato starch thermal properties and its noodle quality were analyzed using a rapid predictive method based on near-infrared spectroscopy （NIRS）. This method was established based on a total of 93 sweetpotato genotypes with diverse genetic background. Starch samples were scanned by NIRS and analyzed for quality properties by reference methods. Results of statistical modelling indicated that NIRS was reasonably accurate in predicting gelatinization onset temperature （To） （standard error of prediction SEP=2.014 ℃, coefficient of determination RSQ=0.85）, gelatinization peak temperature （Tp） （SEP=-1.371 ℃, RSQ=0.89）, gelatinization temperature range （Tr） （SEP=2.234 ℃, RSQ=0.86）, and cooling resistance （CR） （SEP=0.528, RSQ=0.89）. Gelatinization completion temperature （To）, enthalpy of gelatinization （△H）, cooling loss （CL） and swelling degree （SWD）, were modelled less well with RSQ between 0.63 and 0.84. The present results suggested that the NIRS based method was sufficiently accurate and practical for routine analysis of sweetpotato starch and its noodle quality.展开更多
Near-infrared (NIR) spectroscopy combined with chemometrics techniques was used to classify the pure bayberry juice and the one adulterated with 10% (w/w) and 20% (w/w) water. Principal component analysis (PCA) was ap...Near-infrared (NIR) spectroscopy combined with chemometrics techniques was used to classify the pure bayberry juice and the one adulterated with 10% (w/w) and 20% (w/w) water. Principal component analysis (PCA) was applied to reduce the dimensions of spectral data, give information regarding a potential capability of separation of objects, and provide principal component (PC) scores for radial basis function neural networks (RBFNN). RBFNN was used to detect bayberry juice adulterant. Multiplicative scatter correction (MSC) and standard normal variate (SNV) transformation were used to preprocess spectra. The results demonstrate that PC-RBFNN with optimum parameters can separate pure bayberry juice samples from water-adulterated bayberry at a recognition rate of 97.62%, but cannot clearly detect water levels in the adulterated bayberry juice. We conclude that NIR technology can be successfully applied to detect water-adulterated bayberry juice.展开更多
The near-infrared（NIR） diffuse reflectance spectroscopy was used to study the content of Berberine in the processed Coptis. The allocated proportions of Coptis to ginger, yellow liquor or Evodia rutaecarpa changed a...The near-infrared（NIR） diffuse reflectance spectroscopy was used to study the content of Berberine in the processed Coptis. The allocated proportions of Coptis to ginger, yellow liquor or Evodia rutaecarpa changed according to the results of orthogonal design as well as the temperature. For as withdrawing the full and effective information from the spectral data as possible, the spectral data was preprocessed through first derivative and multiplicative scatter correetion（MSC） according to the optimization results of different preprocessing methods. Firstly, the model was established by partial least squares（PLS）; the coefficient of determination（R2） of the prediction was 0.839, the root mean squared error of prediction（RMSEP） was 0.1422, and the mean relative error（RME） was 0.0276. Secondly, for reducing the dimension and removing noise, the spectral variables were highly effectively compressed via the wavelet transformation（WT） technology and the Haar wavelet was selected to decompose the spectral signals. After the wavelet coefficients from WT were input into the artificial neural network（ANN） instead of the spectra signal, the quantitative analysis model of Berberine in processed Coptis was established. The R^2 of the model was 0.9153, the RMSEP was 0.0444, and the RME was 0.0091. The values of appraisal index, namely R^2, RMSECV, and RME, indicate that the generalization ability and prediction precision of ANN are superior to those of PLS. The overall results show that NIR spectroscopy combined with ANN can be efficiently utilized for the rapid and accurate analysis of routine chemical compositions in Coptis. Accordingly, the result can provide technical support for the further analysis of Berberine and other components in processed Coptis. Simultaneously, the research can also offer the foundation of quantitative analysis of other NIR application.展开更多
Silica-based monolithic column material was synthesized and an enrichment device was fabricated with the material by assembling the material inside a glass column. The enrichment device was applied for the determinati...Silica-based monolithic column material was synthesized and an enrichment device was fabricated with the material by assembling the material inside a glass column. The enrichment device was applied for the determination of micro-carbaryl with near-infrared spectroscopy （NIRS）. The aqueous solutions of carbaryl passed through the device and the carbaryl was enriched on the surface of the material where diffuse reflection NIR spectra were measured. These procedures of enrichment and measurement ensured to concentrate analytes for the measurement, so that the sensitivity of determination of MRS could be improved. NIR spectra of carbaryl solutions （0.01-1.00μg mL^-1）, measured after the application of the enrichment device, were pretreated with multiplicative scatter correction （MSC） and regressed against the concentrations of the carbaryl solutions with partial least squares （PLS） method. The results showed that the minimum value of root-mean-square error of prediction （RMSEP） was 0.1771 μg mL^-1 when the number of latent variables was 3 of PLS regression. Therefore, the number of latent variables 3 was selected as the optimum value. RMSEP was not very low but acceptable considering that NIRS is commonly used in macro amount analysis and it is quite difficult for NIRS to determine micro amount analytes, especially, less than 1 μg mL^-1.展开更多
Partial least squares（PLS）,back-propagation neural network（BPNN）and radial basis function neural network（RBFNN）were respectively used for estalishing quantative analysis models with near infrared（NIR）diffuse r...Partial least squares（PLS）,back-propagation neural network（BPNN）and radial basis function neural network（RBFNN）were respectively used for estalishing quantative analysis models with near infrared（NIR）diffuse reflectance spectra for determining the contents of rifampincin（RMP）,isoniazid（INH）and pyrazinamide（PZA）in rifampicin isoniazid and pyrazinamide tablets.Savitzky-Golay smoothing,first derivative,second derivative,fast Fourier transform（FFT）and standard normal variate（SNV）transformation methods were applied to pretreating raw NIR diffuse reflectance spectra.The raw and pretreated spectra were divided into several regions,depending on the average spectrum and RSD spectrum.Principal component analysis（PCA）method was used for analyzing the raw and pretreated spectra in different regions in order to reduce the dimensions of input data.The optimum spectral regions and the models＇ parameters were chosen by comparing the root mean square error of cross-validation（RMSECV）values which were obtained by leave-one-out cross-validation method.The RMSECV values of the RBFNN models for determining the contents of RMP,INH and PZA were 0.00288,0.00226 and 0.00341,respectively.Using these models for predicting the contents of INH,RMP and PZA in prediction set,the RMSEP values were 0.00266,0.00227 and 0.00411,respectively.These results are better than those obtained from PLS models and BPNN models.With additional advantages of fast calculation speed and less dependence on the initial conditions,RBFNN is a suitable tool to model complex systems.展开更多
文摘In this paper, a double artificial neural network （DANN） algorithm was used to parse near infrared （NIR） reflectance spectrum of Cofrel medicines. The contents of benproperine phosphate, which is the effective ingredient in Cofrel medicines, were accurately nondestructive quantitatively predicted. Compared the results with those of HPLC, the relative errors （RE %） were less than 0.18%. The analytical results could be applied to qualitative control of Cofrel medicines.
基金support of the National Key Research and Development Program of China (Grant Numbers 2021YFB3201200 and 2021YFB3201202)the Shandong Province Natural Science Foundation (Grant Numbers ZR2021QB177 and ZR2022QB205).
文摘Human serum albumin(HSA)is the most abundant protein in plasma and plays an essential physiological role in the human body.Ethanol precipitation is the most widely used way to obtain HSA,and pH and ethanol are crucial factors affecting the process.In this study,infrared(IR)spectroscopy and near-infrared(NIR)spectroscopy in combination with chemometrics were used to investigate the changes in the secondary structure and hydration of HSA at acidic pH(5.6-3.2)and isoelectric pH when ethanol concentration was varied from 0%to 40%as a perturbation.IR spectroscopy combined with the two-dimensional correlation spectroscopy(2DCOS)analysis for acid pH system proved that the secondary structure of HSA changed significantly when pH was around 4.5.What's more,the IR spectroscopy and 2DCOS analysis showed different secondary structure forms under different ethanol concentrations at the isoelectric pH.For the hydration effect analysis,NIR spectroscopy combined with the McCabe-Fisher method and aquaphotomics showed that the free hydrogen-bonded water fluctuates dynamically,with ethanol at 0-20%enhancing the hydrogen-bonded water clusters,while weak hydrogen-bonded water clusters were formed when the ethanol concentration increased continuously from 20%to 30%.These measurements provide new insights into the structural changes and changes in the hydration behavior of HSA,revealing the dynamic process of protein purification,and providing a theoretical basis for the selection of HSA alcoholic precipitation process parameters,as well as for further studies of complex biological systems.
文摘Filtration processes are worldwide used for sterilizing solutions and substrates. Filtration seems to induce the formation of aqueous nanostructures. The aim of this work was to verify the influence of filtration processes on water structure detected by spectral variations in NIR region. Samples of ultrapure water （MilliQ-Millipore, Vimodrone, Milan, Italy） before and after iterated filtrations were analyzed. NIR spectra were collected in transmission mode in the whole NIR range, by using NIRFIex N500 spectrometer at constant temperature （40 ± 1 ℃）. NIR data were processed using Unscrambler software v. 9.2 in evaluating qualitative differences between filtered and not filtered samples. The information related to possible solvent physical stresses were highlighted in the range 6500-7500 cm^-1. The shifts observed were ascribable to a different distribution of the number of water molecules involved in hydrogen bonds in filtered and not filtered water samples, at constant temperature. NIR spectroscopy, commonly used to study relationship between spectral changes and hydrogen bonds in water at increasing temperature values, was applied to evaluate effects of filtration processes on water structure. The obtained results are in agreement with literature data and allowed the improvement of the knowledge about pure water characteristics when some mechanical perturbations are applied.
基金Project supported by the National Natural Science Foundation of China(No.30825027)the National Key Technology R&D Program of China(No.2006BAD11A12)
文摘The near infrared （NIR） spectroscopy technique has been applied in many fields because of its advantages of simple preparation, fast response, and non-destructiveness. We investigated the potential of NIR spectroscopy in diffuse reflectance mode for determining the soluble solid content （SSC） and acidity （pH） of intact loquats. Two cultivars of loquats （Dahongpao and Jiajiaozhong） harvested from two orchards （Tangxi and Chun＇an, Zhejiang, China） were used for the measurement of NIR spectra between 800 and 2500 nm. A total of 400 loquats （100 samples of each cultivar from each orchard） were used in this study. Relationships between NIR spectra and SSC and acidity of loquats were evaluated using partial least square （PLS） method. Spectra preprocessing options included the first and second derivatives, multiple scatter correction （MSC）, and the standard normal variate （SNV）. Three separate spectral windows identified as full NIR （800-2500 nm）, short NIR （800-1100 rim）, and long NIR （1100-2500 nm） were studied in factorial combination with the preprocessing options. The models gave relatively good predictions of the SSC of loquats, with root mean square error of prediction （RMSEP） values of 1.21, 1.00, 0.965, and 1.16 °Brix for Tangxi-Dahongpao, Tangxi-Jiajiaozhong, Chun＇an-Dahongpao, and Chun＇an-Jiajiaozhong, respectively. The acidity prediction was not satisfactory, with the RMSEP of 0.382, 0.194, 0.388, and 0.361 for the above four loquats, respectively. The results indicate that NIR diffuse reflectance spectroscopy can be used to predict the SSC and acidity of loquat fruit.
文摘Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R<sup>2</sup> 0.85) is better than the whole seed (0.33 R<sup>2</sup> 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R<sup>2</sup>_whole seed = 0.78, R<sup>2</sup>_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.
文摘A non-destructive technique should be developed for performance analysis of mango fruits because the spongy tissue or internal defects could lower the quality of mango fruit and incur a lack of productivity.In this study,wavelength selection methods were proposed to identify the range of wavelengths for the classification of defected and healthy mango fruits.Feature selection methods were adopted here to achieve a significant selection of wavelengths.To measure the goodness of themodel,the datasetwas collected using the NIR(Near Infrared)spectroscopy with wavelength ranging from 673 nm–1900 nm.The classification was performed using Euclidean distance measure both in the original feature space and in FLD(Fisher's Linear Discriminant)transformed space.The experimental results showed that the lower range wavelength(673 nm–1100 nm)was the efficient wavelength for the detection of internal defects in mangoes.Further to express the effectiveness of the model,different feature selection techniques were investigated and found that the Fisher's criterion based technique appeared to be the best method for effective wavelength selection useful for classification of defected and healthy mango fruits.The optimal wavelengths were found in the range of 702.72 nm to 752.34 nm using Fisher's criterionwith a classification accuracy of 84.5%.This study showed that NIR systemis a useful technology for the automaticmango fruit assessmentwhich has the potential to be used for internal defects in online sorting,easily distinguishable by those who do not meet minimum quality requirements.
基金National Key Technologies R&D Program Foundation of China (Grant No. 2006BAK04A11)
文摘To develop near-infrared （NIR） reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders of cefoperazone sodium/ sulbactam sodium were directly analyzed by non-destructive NIR reflectance spectroscopy using the spectrometer EQUINOX55. Two quantitative methods via integrating sphere （IS） and fiberoptic probe （FOP） models were explored from 6 batches of commercial samples and 42 batches of laboratory samples at a content ranging from 30% to 70% for cefoperazone and 60% to 20% for sulbactam. The root mean square errors of cross validation （RMSECV） and the root mean square errors of prediction （RMSEP） of IS were 1.79% and 2.85%, respectively, for cefoperazone sodium, and were 1.86% and 3.08%, respectively, for sulbactam sodium; and those of FOP were 2.93% and 2.92%, respectively, for cefoperazone sodium, and were 2.23% and 3.01%, respectively, for sulbactam sodium. Based on the ICH guidelines and Ref. 12, the quantitative models were then evaluated in terms of specificity, linearity, accuracy, precision, robustness and model transferability. The non-destructive quantitative NIR methods used in this study are applicable for rapid analysis of injectable powdered drugs from different manufacturers.
基金Project supported by the National Natural Science Foundation of China (No. 30270773), and the Teaching and Research Award Pro-gram for Outstanding Young Teachers in Higher Education Institu-tions & the Specialized Research Fund for the Doctoral Program o
文摘Near infrared reflectance （N1R） spectroscopy is as a rapid, convenient and simple nondestructive technique useful for quantifying several soil properties. This method was used to estimate nitrogen （N） and organic matter （OM） content in a soil of Zhejiang Province, Hangzhou County. A total of 125 soil samples were taken from the field. Ninety-five samples spectra were used during the calibration and cross validation stage. Thirty samples spectra were used to predict N and OM concentration. NIR spectra of these samples were correlated using partial least square regression. The regression coefficients between measured and predicted values of N and OM was 0.92 and 0.93, and SEP （standard error of prediction） were 3.28 and 0.06, respectively, which showed that NIR method had potential to accurately predict these constituents in this soil. The results showed that NIR spectroscopy could be a good tool for precision farming application.
基金National Natural Science Foundation of China (Grant No. 82003953)China Postdoctoral Science Foundation (Grant No. 2019M662278)+2 种基金Science and Technology Project of Education Department of Jiangxi Province (Grant No. GJJ190688, GJJ201252)Po stdoctoral Science Foundation of Jiangxi Province (Grant No. 2019KY42)Key Scientific Research Foundation of Jiangxi University of Traditional Chinese Medicine (Grant No. 2004/538200010402)。
文摘The encapsulation of essential oil components in cyclodextrins(CDs)to form inclusion complexes(ICs)is an effective strategy for improving their stability and bioaccessibility.The aim of the present study was to obtain a deeper understanding of the encapsulation behavior of multi-components inβ-CD.vip molecules ofα-pinene,myrcene,and 3-carene,having the same molecular weight,formed ICs withβ-CD by a freeze-drying method.A simplex lattice mixture design with 28 experiments was carried out.Statistical analysis was applied to analyze the encapsulation behavior of vip components,and quantitative models of vip components in ICs were constructed by coupling with near-infrared(NIR)spectroscopy and chemometrics analysis.Besides,the molecular docking technique was used to obtain the optimal conformation and explain the binding behavior of inclusion.The results suggested that the spatial structure and ratio of vip molecules were the key factors affecting the encapsulation effect.A non-destructive and rapid NIR analytical model for the vip component in ICs could be obtained by second derivative(2nd der)pretreatment.Collectively,the encapsulation of vip components inβ-CD was differentiated,and NIR could be used as a rapid and non-destructive tool for quantitative analysis of ICs.
文摘The near infrared spectra of 178 recombinant inbred lines （RILs） from the cross of Ⅱ-32B/Yuezaoxian 6 （YZX6） and 511 varieties in rice were acquired. A total of 80 RILs and 96 cultivars were selected as modeling samples by comparing the spectra similarity primarily. Three partial least square （PLS） regression models were developed, based on the RILs （RIL-model）, the varieties （Var-model） and their mixture （Mix-model）, for protein content （PC） and amylose content （AC）, respectively. Cross validation and outer prediction showed that the models were largely influenced by the range and distribution of modeling samples. The regression model of PC based on the cultivars and the model of AC based on RILs had higher coefficient of determination （r^2 ≥ 0.9） and lower root mean square error of cross validation （RMSECVs）. The disadvantages of RIL samples for PC model and variety samples for AC model were probably caused by the narrow range of variance. Aberrant predictions were obtained for outer sample with PC or AC outside the range or within the distribution gap of modeling samples. The Mix-models gave more reliable prediction as the distribution of RIL and variety modeling samples were complementary to each other.
基金supported by National Natural Science Foundation of China(No.61078040)the Science and Technology,Project of Guangdong Province(No.2012B031800917).
文摘A new strategy for quantitative analysis of a major clinical biochemical indicator called glycatedhemoglobin(Hb·A1c)was proposed.The technique was based on the simultaneous near-infrared(NIR)spectral determination of hemoglobin(Hb)and absolute HbAlc content(Hb·HbA1c)inhuman hemolysate samples.Wavelength selections were accomplished using the improvedmoving window partial least square(MWPLS)method for stability.Each model was establishedusing an approach based on randomness,similarity,and stability to obtain objective,stable,andpractical models.The optimal wavebands obtained using MWPLS were 958 to 1036 nm for Hband 1492 to 1858 nm for Hb·HbA1c,which were within the NIR overtone region.The validationroot mean square error and validation correlation coeficients of prediction(V-SEP,V-Rp)were 3.4g L^(-1) and 0.967 for Hb,respectively,whereas the corresponding values for Hb.HbAic were 0.63 g L^(-1) and 0.913.The corresponding V-SEP and V-Rp were 0.40% and 0.829 for the relativepercentage of HbA1c.The experimental results confirm the feasibility for the quantification of HbAlc based on simultaneous NIR spectroscopic analyses of Hb and Hb·HbA1c.
文摘This research aimed to establish near infrared(NIR)spectroscopy models for identification ofsyrup types in which the maple syrup was discriminated from other syrup types.Thirty syruptypes were used in this research;the NIR spectra of each type were recorded with 10 replicates.The repeatability and reproducibility of NIR scamning were perfomed,and the absorbance atG940cn-1 was used for calculation,.Principal component analysis was used to group the syruptype.Identification models were developed by soft independent modeling by,class analogy(SIMCA)and partial least-squares diseriminant analysis(PLS.DA),The SiMCA models of alsyrup types exhibited accuracy percentage of 93.3-100%for identifying syrup types,whereasmaple syrup discrimination models showed percentage of accuracy between 83.2%and 100%.The PLS-DA technique gave the accuracy of syrup types classification bet ween 96.6%and 100%and presented ability on discrimination of maple syrup form other types of syrup with accuracyof 100%.The finding presented the potential of NIR spectroscopy for the syrup typeidentification.
基金support provided by National Natural Science Foundation of China (60844007,61178036,21265006)National Science and Technology Support Plan (2008BAD96B04)+1 种基金Special Science and Technology Support Program for Foreign Science and Technology Cooperation Plan (2009BHB15200)Technological expertise and academic leaders training plan of Jiangxi Province (2009DD00700)。
文摘Variable selection is applied widely for visible-near infrared(Vis-NIR)spectroscopy analysis of internal quality in fruits.Different spectral variable selection methods were compared for online quantitative analysis of soluble solids content(SSC)in navel oranges.Moving window partial least squares(MW-PLS),Monte Carlo uninformative variables elimination(MC-UVE)and wavelet transform(WT)combined with the MC-UVE method were used to select the spectral variables and develop the calibration models of online analysis of SSC in navel oranges.The performances of these methods were compared for modeling the Vis NIR data sets of navel orange samples.Results show that the WT-MC-UVE methods gave better calibration models with the higher correlation cofficient(r)of 0.89 and lower root mean square error of prediction(RMSEP)of 0.54 at 5 fruits per second.It concluded that Vis NIR spectroscopy coupled with WT-MC-UVE may be a fast and efective tool for online quantitative analysis of SSC in navel oranges.
文摘Objective To observe the effect of acupuncture at Kongzui（孔最LU 6）,Sanyinjiao（三阴交 SP 6） and Zusanli（足三里 ST 36） on cerebral blood oxygenation level and explore the relevance between acupuncture and cerebral blood oxygenation level using near-infrared spectroscopy（NIRS）.Methods Quasi-randomized design（random test sequence） was used.In clinical trial ①,placebo acupuncture was applied at Baihui（百会GV 20） of18 adults.In clinical trial ②,54 adults were divided into three groups with 18 each in which acupuncture was applied at LU 6,SP 6 and ST 36 respectively.Before and after acupuncture,verbal fluency test（VFT） was performed and the blood oxygenation level of cerebral cortex was measured using NIRS.Quantized data was processed with JMP10.0.2 software and SPSS software.Results In clinical trial ①,the mean integral values of cerebral blood oxygenation level were 10.8 mMcm·s and 9.2 mMcm·s respectively before and after acupuncture at GV 20 in placebo acupuncture group.There was no significant difference in the cerebral blood oxygenation level after acupuncture.In clinical trial ②,the mean integral values of cerebral blood oxygen level were18.1 mMcm·s and 8.6 mMcm·s respectively before and after acupuncture at LU 6 in[LU 6]acupuncture group,the cerebral blood oxygenation level was significantly decreased after acupuncture（P = 0.001）.The mean integral values of cerebral blood oxygenation level were 16.1 mMcm·s and 17.4 mMcm·s respectively before and after acupuncture at SP 6 in[SP 6]acupuncture group,the cerebral blood oxygenation level was slightly increased after acupuncture,but the increase was not statistically significant.The mean integral values of cerebral blood oxygenation level were 13.8 mMcnvs and 10.1 mMcnvs respectively before and after acupuncture at ST 36 in[ST 36]acupuncture group,the cerebral blood oxygenation level was slightly deceased after acupuncture,but the increase was not statistically significant.Conclusion The cerebral blood oxygenation level of frontal head was decreased by acupuncture at LU 6,the cerebral blood oxygenation level of frontal head was intended to decrease by acupuncture at ST 36.The cerebral blood oxygenation level of frontal head is intended to increase by acupuncture at SP 6.
基金Project supported by the Hi-Tech Research and Development Pro-gram (863) of China (No. 2004AA241180), and the Scientific Re-search Foundation for the Returned Overseas Chinese Scholars of State Education Ministry, and the Science and Technology Depart-ment of Zhejiang Province, China
文摘Sweetpotato starch thermal properties and its noodle quality were analyzed using a rapid predictive method based on near-infrared spectroscopy （NIRS）. This method was established based on a total of 93 sweetpotato genotypes with diverse genetic background. Starch samples were scanned by NIRS and analyzed for quality properties by reference methods. Results of statistical modelling indicated that NIRS was reasonably accurate in predicting gelatinization onset temperature （To） （standard error of prediction SEP=2.014 ℃, coefficient of determination RSQ=0.85）, gelatinization peak temperature （Tp） （SEP=-1.371 ℃, RSQ=0.89）, gelatinization temperature range （Tr） （SEP=2.234 ℃, RSQ=0.86）, and cooling resistance （CR） （SEP=0.528, RSQ=0.89）. Gelatinization completion temperature （To）, enthalpy of gelatinization （△H）, cooling loss （CL） and swelling degree （SWD）, were modelled less well with RSQ between 0.63 and 0.84. The present results suggested that the NIRS based method was sufficiently accurate and practical for routine analysis of sweetpotato starch and its noodle quality.
基金supported by the National Natural Science Foundation of China (Nos. 60778024 and 30825027)the National Basic Re-search Program (973) of China (No. 2006BAD11A12)
文摘Near-infrared (NIR) spectroscopy combined with chemometrics techniques was used to classify the pure bayberry juice and the one adulterated with 10% (w/w) and 20% (w/w) water. Principal component analysis (PCA) was applied to reduce the dimensions of spectral data, give information regarding a potential capability of separation of objects, and provide principal component (PC) scores for radial basis function neural networks (RBFNN). RBFNN was used to detect bayberry juice adulterant. Multiplicative scatter correction (MSC) and standard normal variate (SNV) transformation were used to preprocess spectra. The results demonstrate that PC-RBFNN with optimum parameters can separate pure bayberry juice samples from water-adulterated bayberry at a recognition rate of 97.62%, but cannot clearly detect water levels in the adulterated bayberry juice. We conclude that NIR technology can be successfully applied to detect water-adulterated bayberry juice.
基金Supported by the National Natural Science Foundation of China(No.50635030)the Key Project of Jilin Provincial De-partment of Science & Technology, China(Nos.20060902-02, 200705C07)
文摘The near-infrared（NIR） diffuse reflectance spectroscopy was used to study the content of Berberine in the processed Coptis. The allocated proportions of Coptis to ginger, yellow liquor or Evodia rutaecarpa changed according to the results of orthogonal design as well as the temperature. For as withdrawing the full and effective information from the spectral data as possible, the spectral data was preprocessed through first derivative and multiplicative scatter correetion（MSC） according to the optimization results of different preprocessing methods. Firstly, the model was established by partial least squares（PLS）; the coefficient of determination（R2） of the prediction was 0.839, the root mean squared error of prediction（RMSEP） was 0.1422, and the mean relative error（RME） was 0.0276. Secondly, for reducing the dimension and removing noise, the spectral variables were highly effectively compressed via the wavelet transformation（WT） technology and the Haar wavelet was selected to decompose the spectral signals. After the wavelet coefficients from WT were input into the artificial neural network（ANN） instead of the spectra signal, the quantitative analysis model of Berberine in processed Coptis was established. The R^2 of the model was 0.9153, the RMSEP was 0.0444, and the RME was 0.0091. The values of appraisal index, namely R^2, RMSECV, and RME, indicate that the generalization ability and prediction precision of ANN are superior to those of PLS. The overall results show that NIR spectroscopy combined with ANN can be efficiently utilized for the rapid and accurate analysis of routine chemical compositions in Coptis. Accordingly, the result can provide technical support for the further analysis of Berberine and other components in processed Coptis. Simultaneously, the research can also offer the foundation of quantitative analysis of other NIR application.
基金sponsored by Shanghai Pujiang Program(2006)supported by Science and Technology Commission of Shanghai Municipality(No.0652nm020).
文摘Silica-based monolithic column material was synthesized and an enrichment device was fabricated with the material by assembling the material inside a glass column. The enrichment device was applied for the determination of micro-carbaryl with near-infrared spectroscopy （NIRS）. The aqueous solutions of carbaryl passed through the device and the carbaryl was enriched on the surface of the material where diffuse reflection NIR spectra were measured. These procedures of enrichment and measurement ensured to concentrate analytes for the measurement, so that the sensitivity of determination of MRS could be improved. NIR spectra of carbaryl solutions （0.01-1.00μg mL^-1）, measured after the application of the enrichment device, were pretreated with multiplicative scatter correction （MSC） and regressed against the concentrations of the carbaryl solutions with partial least squares （PLS） method. The results showed that the minimum value of root-mean-square error of prediction （RMSEP） was 0.1771 μg mL^-1 when the number of latent variables was 3 of PLS regression. Therefore, the number of latent variables 3 was selected as the optimum value. RMSEP was not very low but acceptable considering that NIRS is commonly used in macro amount analysis and it is quite difficult for NIRS to determine micro amount analytes, especially, less than 1 μg mL^-1.
基金Supported by the Science Technology Development Project of Jilin Province,China(No.20020503-2).
文摘Partial least squares（PLS）,back-propagation neural network（BPNN）and radial basis function neural network（RBFNN）were respectively used for estalishing quantative analysis models with near infrared（NIR）diffuse reflectance spectra for determining the contents of rifampincin（RMP）,isoniazid（INH）and pyrazinamide（PZA）in rifampicin isoniazid and pyrazinamide tablets.Savitzky-Golay smoothing,first derivative,second derivative,fast Fourier transform（FFT）and standard normal variate（SNV）transformation methods were applied to pretreating raw NIR diffuse reflectance spectra.The raw and pretreated spectra were divided into several regions,depending on the average spectrum and RSD spectrum.Principal component analysis（PCA）method was used for analyzing the raw and pretreated spectra in different regions in order to reduce the dimensions of input data.The optimum spectral regions and the models＇ parameters were chosen by comparing the root mean square error of cross-validation（RMSECV）values which were obtained by leave-one-out cross-validation method.The RMSECV values of the RBFNN models for determining the contents of RMP,INH and PZA were 0.00288,0.00226 and 0.00341,respectively.Using these models for predicting the contents of INH,RMP and PZA in prediction set,the RMSEP values were 0.00266,0.00227 and 0.00411,respectively.These results are better than those obtained from PLS models and BPNN models.With additional advantages of fast calculation speed and less dependence on the initial conditions,RBFNN is a suitable tool to model complex systems.
