Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples

One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness.The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary,for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis.Fourier Transform Infrared Spectroscopy(FTIR)is used in this work to identify lard adulteration in cow,lamb,and chicken samples.A simplified extraction method was implied to obtain the lipids from pure and adulterated meat.Adulterated samples were obtained by mixing lard with chicken,lamb,and beef with different concentrations(10%–50%v/v).Principal component analysis(PCA)and partial least square(PLS)were used to develop a calibration model at 800–3500 cm^(−1).Three-dimension PCA was successfully used by dividing the spectrum in three regions to classify lard meat adulteration in chicken,lamb,and beef samples.The corresponding FTIR peaks for the lard have been observed at 1159.6,1743.4,2853.1,and 2922.5 cm−1,which differentiate chicken,lamb,and beef samples.The wavenumbers offer the highest determination coefficient R2 value of 0.846 and lowest root mean square error of calibration(RMSEC)and root mean square error prediction(RMSEP)with an accuracy of 84.6%.Even the tiniest fat adulteration up to 10%can be reliably discovered using this methodology.

Process Characterization of the Transesterification of Rapeseed Oil to Biodiesel Using Design of Experiments and Infrared Spectroscopy

For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality.The present study aims at characterizing a well-known industrial process,the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters(FAME)for usage as biodiesel in a continuous micro reactor set-up.To this end,a design of experiment approach is applied,where the effects of two process factors,the molar ratio and the total flow rate of the reactants,are investigated.The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield.The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression.The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis.A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination(R^(2))of 0.9608.Thus,we applied a PAT approach to generate further insight into this established industrial process.

Acupuncture enhances brain function in patients with mild cognitive impairment: evidence from a functional-near infrared spectroscopy study

Mild cognitive impairment(MCI)is a precursor to Alzheimer’s disease.It is imperative to develop a proper treatment for this neurological disease in the aging society.This observational study investigated the effects of acupuncture therapy on MCI patients.Eleven healthy individuals and eleven MCI patients were recruited for this study.Oxy-and deoxy-hemoglobin signals in the prefrontal cortex during working-memory tasks were monitored using functional near-infrared spectroscopy.Before acupuncture treatment,working-memory experiments were conducted for healthy control(HC)and MCI groups(MCI-0),followed by 24 sessions of acupuncture for the MCI group.The acupuncture sessions were initially carried out for 6 weeks(two sessions per week),after which experiments were performed again on the MCI group(MCI-1).This was followed by another set of acupuncture sessions that also lasted for 6 weeks,after which the experiments were repeated on the MCI group(MCI-2).Statistical analyses of the signals and classifications based on activation maps as well as temporal features were performed.The highest classification accuracies obtained using binary connectivity maps were 85.7%HC vs.MCI-0,69.5%HC vs.MCI-1,and 61.69%HC vs.MCI-2.The classification accuracies using the temporal features mean from 5 seconds to 28 seconds and maximum(i.e,max(5:28 seconds))values were 60.6%HC vs.MCI-0,56.9%HC vs.MCI-1,and 56.4%HC vs.MCI-2.The results reveal that there was a change in the temporal characteristics of the hemodynamic response of MCI patients due to acupuncture.This was reflected by a reduction in the classification accuracy after the therapy,indicating that the patients’brain responses improved and became comparable to those of healthy subjects.A similar trend was reflected in the classification using the image feature.These results indicate that acupuncture can be used for the treatment of MCI patients.

Mathematic Models for Analysis of Quality Components in Sugarcane Juice with Fourier Transform Near Infrared Spectroscopy

With the technique of Fourier transform near infrared (FT-NIR) spectroscopy, the calibration models for quantitative analysis of sucrose and polarization in sugarcane juice were developed by using transmission mode and calibrating with partial least square (PLS) algorithm. The determination coefficients (R2) of the predicted models for sucrose and polarization in juice were 0. 9980 and 0. 9979 respectively; the root mean square errors of cross validation (RMSECV) were 0. 143 and 0. 155% for sucrose and polarization in juice respectively. The predictive errors measured by FT-NIR were close to those by routine laboratory methods. The results demonstrated that the FT-NIR methods had high accuracy and they were able to replace the routine laboratory analysis. It was also demonstrated that as a rapid and accurate measurement, the FT-NIR technique had potential applications in quality control of mill sugarcane, establishment of payment system based on sugarcane quality, and selection of clones in sugarcane breeding.

Application of Wavelet Transform in the Prediction of Navel Orange Vitamin C Content by Near-Infrared Spectroscopy

This study was to search for an approach for rapid measurement of orange vitamin C （Vc） content. By using different decomposing levels of Daubechies 3 wavelet transform, the near-infrared spectra signals obtained from intact fruits of 100 navel orange samples were denoised, and the results of the predicted Vc contents for the corresponding samples determined by the reconstructed spectra after denoising were validated by means of PLS-CV （partial least squared-cross validation）. It was shown that the prediction effects verified by PLS-CV analysis varied when different wavelet transform decomposing levels were employed. At the wavelet decomposing level 4, the best prediction effect was obtained, with the correlation coefficient R between the prediction and true values being 0.9574 and the expected variance RMSECV being as low as 3.9 mg 100 g^-1. Furthermore, the 11 different approaches for the pretreatment of the near-infrared spectrum were compared. It was found that the calibration model established by PLS using spectra pretreated by wavelet transform denoising provided the best prediction for Vc content, exhibiting the highest correlation between the prediction and true values by cross validation. In conclusion, the near infrared spectral model denoised by means of wavelet transform can be used for accurate, rapid, and nondestructive quantitative analysis on navel orange Vc content.

Deep belief network-based drug identification using near infrared spectroscopy

Near infrared spectroscopy(NIRS)analysis technology,combined with chemometrics,can be effectively used in quick and nondestructive analysis of quality and category.In this paper,an effective drug identification method by using deep belief network(DBN)with dropout mecha-nism(dropout-DBN)to model NIRS is introduced,in which dropout is employed to overcome the overfitting problem coming from the small sample.This paper tests proposed method under datasets of different sizes with the example of near infrared diffuse refectance spectroscopy of erythromycin ethylsuccinate drugs and other drugs,aluminum and nonaluminum packaged.Meanwhile,it gives experiments to compare the proposed method's performance with back propagation(BP)neural network,support vector machines(SVMs)and sparse denoising auto-encoder(SDAE).The results show that for both binary classification and multi-classification,dropout mechanism can improve the classification accuracy,and dropout-DBN can achieve best classification accuracy in almost all cases.SDAE is similar to dropout-DBN in the aspects of classification accuracy and algorithm stability,which are higher than that of BP neural network and SVM methods.In terms of training time,dropout-DBN model is superior to SDAE model,but inferior to BP neural network and SVM methods.Therefore,dropout-DBN can be used as a modeling tool with effective binary and multi-class classification performance on a spectrum sample set of small size.

Infrared Spectroscopy and Morphological Assessments on the Nutritional Value of Prickly Pear Fruit

The prickly pear fruit helps in combating viral based infections.It is used to treat diabetes and declared to possess hypoglycemic effects.There is also record of the usage of the fruit in the olden days as a remedy for diabetes,lipid disorders,inflammation,ulcers,and pharmacologic side effects.The chemical composition and nutritional values of skin,flesh and seed of prickly pear fruit were investigated and discussed on a dry weight situation.The infrared spectra as well as scanning electron microscopy(SEM)techniques were used to identify the functional groups of carbohydrates,amino acids,and protein.The infrared spectral data of all three(skin,flesh,and seeds)species were recorded and assigned to the presence of distinguish peaks that referred to the three different sugars(glucose,fructose and saccharose)and cyclic aliphatic hydrocarbons moieties.On the other hand,the SEM is a powerful tool to investigate the morphological features of the components.SEM assays were examined on the surfaces of skin,flesh and seed branches showing a small particle that tends to form clusters with different shapes compared to each other.The Energy-dispersive X-ray spectroscopy(EDX)is an analytical technique used for the elemental analysis or chemical characterization of a sample.The EDX spectral technique of the skin,flesh and seeds were confirmed the presence of different essential and useful elements such as carbon,oxygen,magnesium,calcium,potassium,sulfur,aluminum,silicon,chloride,and phosphorus.

A simple,sensitive and non-destructive technique for characterizing bovine dental enamel erosion:attenuated total reflection Fourier transform infrared spectroscopy

Although many techniques are available to assess enamel erosion in vitro, a simple, non-destructive method with sufficient sensitivity for quantifying dental erosion is required. This study characterized the bovine dental enamel erosion induced by various acidic beverages in vitro using attenuated total reflection Fourier transform infrared （ATR-FTIR） spectroscopy. Deionized water （control） and 10 acidic beverages were selected to study erosion, and the pH and neutralizable acidity were measured. Bovine anterior teeth （110） were polished with up to 1 200-grit silicon carbide paper to produce flat enamel surfaces, which were then immersed in 20 mL of the beverages for 30 min at 37 ℃. The degree of erosion was evaluated using ATR-FTIR spectroscopy and Vickers＇ microhardness measurements. The spectra obtained were interpreted in two ways that focused on the ~1, ~3 phosphate contour： the ratio of the height amplitude of ~3 P04 to that of/11 P04 （Method 1） and the shift of the v3 P04 peak to a higher wavenumber （Method 2）. The percentage changes in microhardness after the erosion treatments were primarily affected by the pH of the immersion media. Regression analyses revealed highly significant correlations between the surface hardness change and the degree of erosion, as detected by ATR-FTIR spectroscopy （P〈0.001）. Method 1 was the most sensitive to these changes, followed by surface hardness change measurements and Method 2. This study suggests that ATR- FTIR spectroscopy is potentially advantageous over the microhardness test as a simple, non-destructive, sensitive technique for the quantification of enamel erosion.

The evolving role of Fourier-transform midinfrared spectroscopy in genetic improvement of dairy cattle

Over the last 100 years,significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs.Technological progress has enabled a shift from labour intensive,on-farm collection and processing of samples that assess yield and fat levels in milk,to large-scale processing of samples through centralised laboratories,with the scope extended to include quantification of other traits.Fourier-transform midinfrared(FT-MIR)spectroscopy has had a significant role in the transformation of milk composition phenotyping,with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally.Increasingly,there is interest in analysing the individual FT-MIR wavenumbers,and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs.This includes traits related to the nutritional value of milk,the processability of milk into products such as cheese,and traits relevant to animal health and the environment.The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits,and the genetic correlations between the FT-MIR predicted and actual trait values.Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis.The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes.Additionally,there are other molecular phenotypes such as those related to the metabolome,chromatin accessibility,and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest.Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets,and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.

Study on Detection of Pesticide Residues on Winter Jujube Surface by Near-infrared Spectroscopy Combined with PLS and SPA

With fresh winter jujube from the southern region of Xinjiang as the object of study, the method for detecting pesticide residues on winter jujube surface by near-infrared spectroscopy （NIR） combined with successive projections algorithm （SPA） and partial least squares （PLS） was investigated. The absorbance information of winter jujube sample surface was obtained through NIR technology, for the building of a full-wave band PLS model of fresh winter jujube sample sprayed with different concentrations of pesticide （taking chlorpyrifos as an example） as well as an SPA-PLS model which was built with the characteristic wavelengths extracted with SPA as the input variables for PLS, and the prediction precision of the two kinds of models was compared. The model built with the five characteristic waveslengths extected by SPA method only used the variables 0.32% of all the variables in the full wave band, but its accuracy and precision were better than the model built with the full wave band. It is feasible to build a model for different concentrations of chlorpyrifos on fresh winter jujube surfarce by NIR technology combined with SPA and PLS, and SPA method could simplify the complexity of the model and improve the precision and stablity of the model.

Study on evaluation of gamma oryzanol of germinated brown rice by near infrared spectroscopy

Germinated brown rice(GBR)is rich in gamma oryzanol which increase its consumption popularity,particularly in the health food market.The objective of this research was to apply the near infraredspectroscopy(NIRS)for evaluation of gamma oryzanol of the germinated brown rice.The germinated brown rice samples were prepared from germinated rough rice(soaked for 24 and 48 h,incubated for 0,6,12,18,24,30 and 36 h)and purchased from local supermar kets.The germinated brown rice sampleswere subjected to NIR scanning before the evaluation of gamma oryzanol by using partial extractionmet hodology.The prediction model was established by partial least square regression(PLSR)andvalidated by full cross validation method.The NIRS model established from various varieties of germinated brown rice bought from diferent markets by first derivatives+vector normalizationpretreated spectra showed the optimal prediction with the correlation of determination(R?),root mean squared error of cross validation(RMSECV),and bias of 0.934,8.84×10^(-5) mg/100 g drymatter and 1.06×10^(-5) mg/100 g dry matter,respectively.This is the first report on the application of NIRS in the evaluation of gamma oryzanol of the germinated brown rice.This information is veryuseful to the germinated brown rice production factory and consumers.

Rapid Non-destructive Detection for Molds Colony of Paddy Rice Based on Near Infrared Spectroscopy

Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artificial infection with moulds to build the calibration models to calculate the total number colony of moulds based on the principal component regression method and multiple linear regression method. The results of statistical analysis indicated that multiple linear regression method was applicable to the detection of the total number colony of moulds. The correlation of calibration data set was 0.943. The correlation of prediction data set was 0.897. Therefore, the result showed that near infrared spectroscopy could be a useful instrumental method for determining the total number colony of moulds in paddy rice. The near infrared spectroscopy methodology could be applied for monitoring mould contamination in postharvest paddy rice during storage and might become a powerful tool for monitoring the safety of the grain.

Fourier transform infrared spectroscopy analysis of the active components in serum of rats treated with Zuogui Pill

Objective:To investigate the active components Zuogui Pill,a typical recipe for nourishing kidney essence in the traditional Chinese medicine.Methods:Adult male Sprague Dawley rats were treated with the traditional Chinese herbal medicine Zuogui Pill and the active components found in the serum of the animals were analyzed by Fourier transform infrared(FTIR)spectroscopy.FTIR spectra of serum samples of treated and untreated rats were analyzed and the A2960/A2931 and A1540/A1080 ratios were calculated.Results:A2960/A2931 ratios of the serum samples collected following the administration of Zuogui Pill were significantly higher than those of the normal serum samples.FTIR data were then fitted using a Gaussian equation for wave numbers in the range of 1140e1000 cm
1.ARNA/ADNA ratios in the serum of rats treated with Zuogui Pill were higher than those found in normal rat serum.Conclusion:FTIR spectroscopy could be used as an analytical tool to detect the activecomponents in serum of animals treated with Zuogui Pill.

On-Line Measurement of the Chemical Oxygen Demand in Wastewater in a Pulp and Paper Mill Using Near Infrared Spectroscopy

Although near infrared (NIR) spectroscopy has been evaluated for numerous applications, the number of actual on-line or even on-site industrial applications seems to be very limited. In the present paper, the attempts to produce online predictions of the chemical oxygen demand (COD) in wastewater from a pulp and paper mill using NIR spectroscopy are described. The task was perceived as very challenging, but with a root mean square error of prediction of 149 mg/l, roughly corresponding to 1/10 of the studied concentration interval, this attempt was deemed as successful. This result was obtained by using partial least squares model regression, interpolated reference values for calibration purposes, and by evenly distributing the calibration data in the concentration space. This work may also represent the first industrial application of online COD measurements in wastewater using NIR spectroscopy.

Cortical activation pattern during shoulder simple versus vibration exercises： a functional near infrared spectroscopy study

To date, the cortical effect of exercise has not been fully elucidated. Using the functional near infrared spectroscopy, we attempted to compare the cortical effect between shoulder vibration exercise and shoulder simple exercise. Eight healthy subjects were recruited for this study. Two different exercise tasks（shoulder vibration exercise using the flexible pole and shoulder simple exercise） were performed using a block paradigm. We measured the values of oxygenated hemoglobin in the four regions of interest： the primary sensory-motor cortex（SM1 total, arm somatotopy, and leg and trunk somatotopy）, the premotor cortex, the supplementary motor area, and the prefrontal cortex. During shoulder vibration exercise and shoulder simple exercise, cortical activation was observed in SM1（total, arm somatotopy, and leg and trunk somatotopy）, premotor cortex, supplementary motor area, and prefrontal cortex. Higher oxygenated hemoglobin values were also observed in the areas of arm somatotopy of SM1 compared with those of other regions of interest. However, no significant difference in the arm somatotopy of SM1 was observed between the two exercises. By contrast, in the leg and trunk somatotopy of SM1, shoulder vibration exercise led to a significantly higher oxy-hemoglobin value than shoulder simple exercise. These two exercises may result in cortical activation effects for the motor areas relevant to the shoulder exercise, especially in the arm somatotopy of SM1. However, shoulder vibration exercise has an additional cortical activation effect for the leg and trunk somatotopy of SM1.

Identification of Plant-Pathogenic Fungi Using Fourier Transform Infrared Spectroscopy Combined with Chemometric Analyses

Identification of plant-pathogenic fungi is time-consuming due to cultivation and microscopic examination and can be influenced by the interpretation of the micro-morphological characters observed.The present investigation aimed to create a simple but sophisticated method for the identification of plant-pathogenic fungi by Fourier transform infrared(FTIR)spectroscopy.In this study,FTIR-attenuated total reflectance(ATR)spectroscopy was used in combination with chemometric analysis for identification of important pathogenic fungi of horticultural plants.Mixtures of mycelia and spores from 27fungal strains belonging to nine different families were collected from liquid PD or solid PDA media cultures and subjected to FTIR-ATR spectroscopy measurements.The FTIR-ATR spectra ranging from 4 000to 400cm-1 were obtained.To classify the FTIRATR spectra,cluster analysis was compared with canonical vitiate analysis(CVA)in the spectral regions of3 050~2 800and 1 800~900cm-1.Results showed that the identification accuracies achieved 97.53%and99.18%for the cluster analysis and CVA analysis,respectively,demonstrating the high potential of this technique for fungal strain identification.

Study on the Hydrogen Bond Interaction Between Soy Protein Isolate and Glycerol Using Two-Dimensional Correlation Fourier-Transform Infrared Spectroscopy

A series of soy protein isolate(SPI)films plasticized by glycerol(Gly)were studied using attenuated total reflectance-Fourier transform infrared spectroscopy(ATR/FTIR).Perturbation-correlation movingwindow two-dimensional(PCMW2D)and two-dimensional correlation(2DCOS)analyses were applied to the amideⅠband and thus the hydrogen bond interaction between SPI and Gly was systematically investigated.When Gly concentrations were in the range 0~35%,the hydrogen bond amongβ-sheets was replaced by the one between SPI chain and Gly molecule,which caused these protein chains being changed toα-helix.However,the transformation ofβ-sheet toα-helix was saturated and both of them tend to change to random coil when Gly concentrations were in the range 35%~60%.

pH value monitoring during human albumin purification with near infrared spectroscopy and chemometrics

Human albumin(HA)is a very important blood product which requires strict quality controlstrategy.Acid precipitation is a key step which has a great effect on the quality of final product.Therefore,a new method based on quality by design(QbD)was proposed to investigate thefeasibility of realizing online quality control with the help of near infrared spectroscopy(NIRS)and chemometrics.The pH value is the critical process parameter(CPP)in acid precipitationprocess,which is used as the end-point indicator.Six batches,a total of 74 samples of acidprecipitation process,were simulated in our lab.Four batches were selected randomly as cali-bration set and remaining two batches as validation set.Then,the analysis based on materialinformation and three dfferent variable selection methods,including interval partial least squaresregression(iPLS),competitive adaptive reweighted sampling(CARS)and correlation coeficient(CC)were compared for eliminating irrelevant variables,Fimally,iPLS was used for variablesselection.The quantitative model was built up by partial least squares regression(PLSR).Thevalues of determination coeficients(R^(2)_(C) and R^(2)_(P)),root mean squares error of prediction(RMSEP),root mean squares error of calibration(RMSEC)and root mean squared error of crossvalidation(RMSECV)were 0.969,0.953,0.0496,0.0695 and 0.0826,respectively.The paired t test and repeatability test showed that the model had good prediction ability and stability.The results indicated that PLSR model could give accurate measurement of the pH value.

Wavelet-based classification and influence matrix analysis method for the fast discrimination of Chinese herbal medicines according to the geographical origins with near infrared spectroscopy

A discriminant analysis technique using wavelet transformation(WT)and influence matrixanalysis(CAIMAN)method is proposed for the near infrared(NIR)spectroscopy classifi-cation.In the proposed methodology,NIR spectra are decomposed by WT for data com-pression and a forward feature selection is further employed to extract the relevant informationfrom the wavelet coefficients,reducing both classification errors and model complexity.Adiscriminant-CAIMAN(D-CAIMAN)method is utilized to build the classification model inwavelet domain on the basis of reduced wavelet coefficients of spectral variables.NIR spectradata set of 265 salviae miltiorrhizae radia samples from 9 different geographical origins is usedas an example to test the classification performance of the algorithm.For a comparison,k-nearest neighbor(KNN),linear discriminant analysis(LDA)and quadratic discriminant analysis(QDA)methods are also employed.D-CAIMAN with wavelet-based feature selection(WD-CAIMAN)method shows the best performance,achieving the total classification rate of ioo%in both cross-validation set and prediction set.It is worth noting that the WD-CAIMANclassifier also shows improved sensitivity,selectivity and model interpretability in thecla.ssifications.

Rapid Detection of Cement Raw Meal Composition Based on Near Infrared Spectroscopy

The composition of cement raw materials was detected by near-infrared spectroscopy.It was found that the BiPLS-SiPLS method selected the NIR spectral band of cement raw materials,and the partial least squares regression algorithm was adopted to establish a quantitative correction model of cement raw materials with good prediction effect.The root-mean-square errors of SiO_(2),Al_(2)O_(3),Fe_(2)O_(3) and CaO calibration were 0.142,0.072,0.034 and 0.188 correspondingly.The results show that the NIR spectroscopy method can detect the composition of cement raw meal rapidly and accurately,which provides a new perspective for the composition detection of cement raw meal.