Fourier Transform Mid-infrared Spectroscopy Research Articles

Comparative analysis of different transformed Saccharomyces cerevisiae strains based on high-throughput Fourier transform infrared spectroscopy

This study shows the application of the Fourier transform mid-infrared spectroscopy (FT-MIR) associated with high-throughput technology to study the biochemical fingerprints of different Saccharomyces cerevisiae strains transformed with the same expression system along the similar cultivation in bioreactor. The phenotype, as well as the cellular metabolism and recombinant cyprosin biosynthesis, were determined. The differences observed were confirmed by conventional cyprosin activity protocol, and the metabolic evolution was analyzed using high-performance liquid chromatography technique. The spectral analysis based on chemometrics tools, such as the principal component analysis, is a useful methodology for the phenotypes characterization as well as the specific metabolic states along the cultivations according to the clusters created. The ratio bands of spectra also represented a useful tool to evaluate the metabolic and biochemical differences between both expression systems, allowing to have an additional parameter to the biomolecular comparison. Therefore, high-throughput FT-MIR spectroscopy associated with multivariate data analysis represent a valuable strategy for extracting significant specific biomolecular information along the cultivation, providing a complete bioprocess analysis, once it detects slight molecular changes which it will be useful for screening and optimization process in the biotechnological or pharmaceutical industry.

Short communication: Prediction of milk coagulation and acidity traits in Mediterranean buffalo milk using Fourier-transform mid-infrared spectroscopy

Milk coagulation and acidity traits are important factors to inform the cheesemaking process. Those traits have been deeply studied in bovine milk, whereas scarce information is available for buffalo milk. However, the dairy industry is interested in a method to determine milk coagulation and acidity features quickly and in a cost-effective manner, which could be provided by Fourier-transform mid-infrared (FT-MIR) spectroscopy. The aim of this study was to evaluate the potential of FT-MIR to predict coagulation and acidity traits of Mediterranean buffalo milk. A total of 654 records from 36 herds located in central Italy with information on milk yield, somatic cell score, milk chemical composition, milk acidity [pH, titratable acidity (TA)], and milk coagulation properties (rennet coagulation time, curd firming time, and curd firmness) were available for statistical analysis. Reference measures of milk acidity and coagulation properties were matched with milk spectral information, and FT-MIR prediction models were built using partial least squares regression. The data set was divided into a calibration set (75%) and a validation set (25%). The capacity of FT-MIR spectroscopy to correctly classify milk samples based on their renneting ability was evaluated by a canonical discriminant analysis. Average values for milk coagulation traits were 13.32 min, 3.24 min, and 39.27 mm for rennet coagulation time, curd firming time, and curd firmness, respectively. Milk acidity traits averaged 6.66 (pH) and 7.22 Soxhlet-Henkel degrees/100 mL (TA). All milk coagulation and acidity traits, except for pH, had high variability (17 to 46%). Prediction models of coagulation traits were moderately to scarcely accurate, whereas the coefficients of determination of external validation were 0.76 and 0.66 for pH and TA, respectively. Canonical discriminant analysis indicated that information on milk coagulating ability is present in the MIR spectra, and the model correctly classified as noncoagulating the 91.57 and 67.86% of milk samples in the calibration and validation sets, respectively. In conclusion, our results can be relevant to the dairy industry to classify buffalo milk samples before processing.

FT-MIR supported Electrical Impedance Spectroscopy based study of sugar adulterated honeys from different floral origin

This study sought to detect the presence of sucrose as an adulterant in selected honey varieties from different floral origins by employing Electrical Impedance Spectroscopy (EIS) technique which has been simultaneously supported by Fourier Transform-Mid Infrared Spectroscopy (FT-MIR) measurements to provide a rapid, robust yet simple platform for honey quality evaluation. Variation of electrical parameters such as impedance, capacitance and conductance for 10%, 20%, 30%, 40%, 50%, 60% and 70% (w/w) sucrose syrup (SS) adulterated honey samples are analyzed and their respective current-voltage (I-V) characteristics are studied. Capacitance, conductance and net current flowing through the system are observed to decrease linearly whereas system impedance has been found to increase similarly with the increase in adulterant content. Also, FT-MIR measurements in the spectral region between 1800cm−1 and 650cm−1 reveal the increment of absorbance values due to the addition of SS. Full-Width-at-Half-Maximum (FWHM) is estimated from the spectral peak 1056cm−1 for all pure and adulterated honey samples and is observed to be linearly increasing with increase in adulterant content. Finally, the coefficient of sensitivity has been extracted for all varieties of honey considered in terms of the measured conductance values.

ATR-FTIR as a potential tool for controlling high quality vinegar categories

Characterization of wine vinegars qualified with a Protected Designation of Origin (PDO) is crucial to certify their quality and authenticity. Spectroscopic techniques as Fourier transform mid infrared spectroscopy (FTIR) with Attenuated Total Reflectance (ATR) has been applied to investigate its potential as a rapid, cost-effective and non-destructive tool for characterizing different categories of high-quality vinegars. Spectra from 67 wine vinegars belonging to the PDOs “Vinagre de Jerez” and “Vinagre Condado de Huelva”, including their different established categories, were analyzed in the 4000–600 cm−1 infrared region. Changes associated to categories were observed in the region 1800–900 cm−1. These changes were assigned to certain compounds that increase during aging (e.g. acetic acids, alcohols, esters) or are characteristic of Pedro Ximenez category (e.g. sugars, furfural). Principal component analysis carried out on the most relevant spectral features, revealed that aging of vinegars clearly affect the ATR-FTIR spectra obtained in each PDO.

Analysis of Complex Carbohydrate Composition in Plant Cell Wall Using Fourier Transformed Mid-Infrared Spectroscopy (FT-IR).

Fourier transformed mid-infrared spectroscopy (FTIR) is a powerful tool for compositional analysis of plant cell walls (Acebes et al., Front Plant Sci 5:303, 2014; Badhan et al., Biotechnol Biofuels 7:1-15, 2014; Badhan et al., BioMed Res Int 2015: 562952, 2015; Roach et al., Plant Physiol 156:1351-1363, 2011). The infrared spectrum generates a fingerprint of a sample with absorption peaks corresponding to the frequency of vibrations between the bonds of the atoms making up the material. Here, we describe a method focused on the use of FTIR in combination with principal component analysis (PCA) to characterize the composition of the plant cell wall. This method has been successfully used to study complex enzyme saccharification processes like rumen digestion to identify recalcitrant moieties in low-quality forage which resist rumen digestion (Badhan et al., BioMed Res Int 2015: 562952, 2015), as well as to characterize cell wall mutant lines or transgenic lines expressing exogenous hydrolases (Badhan et al., Biotechnol Biofuels 7:1-15, 2014; Roach et al., Plant Physiol 156:1351-1363, 2011). The FTIR method described here facilitates high-throughput identification of the major compositional differences across a large set of samples in a low cost and nondestructive manner.

Fast Quantitative and Qualitative Monitoring of Mafurra Biodiesel Content Using Fourier Transform Mid-Infrared Spectroscopy, Chemometric Tools, and Variable Selection

This paper presents a feasible methodology to quantify and classify the mafurra methyl biodiesel content in a diesel blend using Fourier transform mid-infrared spectroscopy (FT-MIR) in combination with partial least squares (PLS) and partial least squares discriminant analysis (PLS-DA) and variable selection (siPLS and siPLS-DA). When the spectra were divided into 30 equally spaced intervals, the models combining four intervals (that is, si4PLS30 and si4PLS-DA30) showed statistically better results than PLS and overall PLS-DA. This comparison was performed on the basis of the application of F test values. The si4PLS30 model was validated on the basis of several figures of merit, and strong correlations between the actual concentration and forecasted values of the calibration and prediction sets, with a correlation coefficient higher than 0.99, were observed. The efficiency of the si4PLS-DA30 model was evaluated on the basis of sensitivity and specificity, and these parameters showed values of 1, indicatin...

Monitoring wheat mitochondrial compositional and respiratory changes using Fourier transform mid-infrared spectroscopy in response to agrochemical treatments

Fungicides and plant growth regulators can impact plant growth outside of their effects on fungal pathogens. Although many of these chemicals are inhibitors of mitochondrial oxygen uptake, information remains limited as to whether they are able to modify other mitochondrial constituents. Fourier transform mid-infrared spectroscopy (FT-mIR) offers a high sample throughput method to comparatively and qualitatively evaluate the effects of exogenously added compounds on mitochondrial components. Therefore the objective of this study was to determine the ability of FT-mIR to detect effects mitochondrial fractions isolated from wheat (Triticum aestivum L.) seedlings in response to several agrochemical treatments, with an emphasis on fungicides. The accessed need was to develop FT-mIR analytical and statistical routines as an effective approach to differentiate spectra obtained from chemically-treated or untreated mitochondria. An NADH-dependent oxygen uptake approach was initially used as a comparative method to determine whether the fungicides (azoxystrobin, boscalid, cyazofamid, fluazinam, isopyrazam, and pyraclostrobin) and the plant growth regulator, (trinexapac-ethyl) reduced respiration inhibition on isolated mitochondria. Pyraclostrobin was the most effective inhibitor, whereas amisulbrom did not impact oxygen uptake. However, hierarchical clustering of FT-mIR spectra of isolated mitochondria treated with these different compounds separated into clades consistent with each of their expected mode of action. Analysis of the FT-mIR amide protein region indicated that amisulbrom and pyraclostrobin interacted with the isolated wheat mitochondria. Both chemicals were statistically different from the control signifying that respiration was indeed influenced by these treatments. Moreover, the entire FT-mIR region showed differences in various biological bands thereby providing additional information on mitochondria responses to agrochemicals, if so warranted.

P.2.e.004 - Lithium levels in the public water supply and risk of suicide

In the presented study, an easy to implement workflow based on the evaluation of a quality control sample in non-targeted analysis (outlier detection and time related trend) is proposed for the first time. The novel concept was developed and demonstrated with Fourier transform-midinfrared spectroscopy using a rapeseed oil as quality control sample. Different data evaluation strategies for outlier detection were tested and compared: (i) principal component analysis (PCA), (ii) PCA combined with Hotelling's T-squared distribution and Q-residuals for data assessment as well as (iii) various outlier score-based methods. The build models were challenged by varying measurement and storage conditions to verify the applicability of the three evaluation types (i-iii) to identify these artificially induced variations as outliers. Analogous to a control chart in targeted analysis warning and action limits (numerical decision criteria) were calculated using outlier score-based methods. The best results were achieved by the four outlier score-based methods (pre-period n = 25), where 100 % of the deliberately generated outliers were identified as such.

Influence of smoking with smoke flavorings on the oxidative stability of farmed sea bass fillets monitored by 1H NMR and FTIR

Farmed European sea bass (Dicentrarchus labrax) fillets were smoked with three commercial smoke flavorings. Unsmoked and smoked fillets were submitted to oxidative conditions to study their oxidative stability. To this aim, at regular intervals of time under oxidative conditions, their lipids were extracted and studied by Fourier transform mid‐infrared spectroscopy (FTIR) and Proton nuclear magnetic resonance (1H NMR). Both kinds of spectra provide markers referred to the beginning and extension of the lipid degradation and of the formation of new compounds resulting from the oxidation process. Obtaining these data from FTIR is easier, simpler, and quicker than it is from 1H NMR, but this latter technique provides, simultaneously, additional interesting information about the sample. The increase of the oxidative stability of sea bass fillets as a consequence of smoking is proved, as well as the influence on this increase of the concentration of certain phenolic smoke components in the fillets.Practical applications: Farmed European sea bass is widely available in the market, in some occasions the supply being greater than the demand. This study could be very interesting for the seafood industry, because smoking of sea bass fillets with smoke flavorings not only extends their shelf‐life, but also provides them with special sensory characteristics, diversifying its presence in the market as a new ready‐to‐eat product. Nevertheless, it must be taken into account that not all the smoke flavorings show the same effect on fish. This study demonstrates that the smoke flavoring composition and its application method have a great influence on the oxidative stability of smoked sea bass fillets.A study of the lipid oxidative stability of unsmoked and smoked sea bass fillets with three different commercial smoke flavorings was undertaken. To this aim, unsmoked and smoked sea bass fillets were submitted to oxidative conditions and their lipids were extracted and analyzed by Fourier transform infrared spectroscopy (FTIR) and Proton nuclear magnetic resonance (1H NMR) periodically.

Supervision of Ethylene Propylene Diene M-Class (EPDM) Rubber Vulcanization and Recovery Processes Using Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectroscopy and Multivariate Analysis.

Ethylene propylene diene monomer (EPDM) rubber is widely used in a diverse type of applications, such as the automotive, industrial and construction sectors among others. Due to its appealing features, the consumption of vulcanized EPDM rubber is growing significantly. However, environmental issues are forcing the application of devulcanization processes to facilitate recovery, which has led rubber manufacturers to implement strict quality controls. Consequently, it is important to develop methods for supervising the vulcanizing and recovery processes of such products. This paper deals with the supervision process of EPDM compounds by means of Fourier transform mid-infrared (FT-IR) spectroscopy and suitable multivariate statistical methods. An expedited and nondestructive classification approach was applied to a sufficient number of EPDM samples with different applied processes, that is, with and without application of vulcanizing agents, vulcanized samples, and microwave treated samples. First the FT-IR spectra of the samples is acquired and next it is processed by applying suitable feature extraction methods, i.e., principal component analysis and canonical variate analysis to obtain the latent variables to be used for classifying test EPDM samples. Finally, the k nearest neighbor algorithm was used in the classification stage. Experimental results prove the accuracy of the proposed method and the potential of FT-IR spectroscopy in this area, since the classification accuracy can be as high as 100%.

Food Adulteration: From Vulnerability Assessment to New Analytical Solutions

Crises related to the presence of melamine in milk or horse meat in beef have been a wake-up call to the whole food industry showing that adulteration of food raw materials is a complex issue. By analysing the situation, it became clear that the risk-based approach applied to ensure the safety related to chemical contaminants in food is not adequate for food fraud. Therefore, a specific approach has been developed to evaluate adulteration vulnerabilities within the food chain. Vulnerabilities will require the development of new analytical solutions. Fingerprinting methodologies can be very powerful in determining the status of a raw material without knowing the identity of each constituent. Milk adulterated by addition of adulterants with very different chemical properties could be detected rapidly by Fourier-transformed mid-infrared spectroscopy (FT-mid-IR) fingerprinting technology. In parallel, a fast and simple multi-analytes liquid-chromatography tandem mass-spectrometry (LC/MS-MS) method has been developed to detect either high levels of nitrogen-rich compounds resulting from adulteration or low levels due to accidental contamination either in milk or in other sensitive food matrices. To verify meat species authenticity, DNA-based methods are preferred for both raw ingredients and processed food. DNA macro-array, and more specifically the Meat LCD Array have showed efficient and reliable meat identification, allowing the simultaneous detection of 32 meat species. While the Meat LCD Array is still a targeted approach, DNA sequencing is a significant step towards an untargeted one.

Prediction of olive oil sensory descriptors using instrumental data fusion and partial least squares (PLS) regression

Headspace-Mass Spectrometry (HS-MS), Fourier Transform Mid-Infrared spectroscopy (FT-MIR) and UV-Visible spectrophotometry (UV–vis) instrumental responses have been combined to predict virgin olive oil sensory descriptors. 343 olive oil samples analyzed during four consecutive harvests (2010–2014) were used to build multivariate calibration models using partial least squares (PLS) regression. The reference values of the sensory attributes were provided by expert assessors from an official taste panel. The instrumental data were modeled individually and also using data fusion approaches. The use of fused data with both low- and mid-level of abstraction improved PLS predictions for all the olive oil descriptors. The best PLS models were obtained for two positive attributes (fruity and bitter) and two defective descriptors (fusty and musty), all of them using data fusion of MS and MIR spectral fingerprints. Although good predictions were not obtained for some sensory descriptors, the results are encouraging, specially considering that the legal categorization of virgin olive oils only requires the determination of fruity and defective descriptors.

Application of Fourier transform-mid infrared reflectance spectroscopy for monitoring Korean traditional rice wine ‘Makgeolli’ fermentation

This study was performed to examine the application of Fourier transform-mid infrared (FT-MIR) spectroscopy to rapidly and non-destructively measure the quality of Makgeolli during fermentation process. A model using the entire ranges of the spectra and a Partial Least Squares Regression (PLSR) model using specific wavelength ranges closely associated with Makgeolli quality were compared to investigate the appropriate non-destructive monitoring method for Makgeolli production. In the global PLSR model using the entire range of the spectra and the local PLSR model using two separate regions (functional group spectral region and fingerprint spectral region), the optimal prediction model for alcohol concentration was from 2nd derivative of Savitzky-Golay pretreatment. The coefficient of determination of the developed model was 0.984, and standard error of prediction (SEP) was 0.595%. Reducing sugar was detected best with 1st derivative of Norris-Gap pretreatment, showing the determination coefficient of 0.983 and SEP of 0.579%. Titratable acidity was accurately predicted with 1st derivative of Savitzky-Golay pretreatment, showing the determination coefficient of 0.936 and SEP of 0.026%. This study showed that FT-MIR spectroscopy can be utilized to monitor the quality changes of Makgeolli.

Assessment of the main plasma parameters included in a metabolic profile of dairy cow based on Fourier Transform mid-infrared spectroscopy: preliminary results.

BackgroundAlthough a metabolic profile represents a valid tool utilized in dairy herds to determine abnormalities in blood chemistry related to an increased risk of production diseases, there are no studies on application of Fourier Transform mid-infrared (FT-MIR) spectroscopy. This study assesses the potential application of FT-MIR to analyze the main blood biochemical parameters included in the metabolic profile of dairy cows. Infrared transmission spectra were acquired for 35 plasma samples (two replicates on each sample) of Italian Friesian dairy cows (14 primiparous and 21 pluriparous), all without clinical events, and at different stages of lactation, although mainly in the transition phase. Each sample was also analyzed independently using accepted reference clinical chemical methods and these results were used as calibrating values to perform predictive models by PLS method using cross validation.ResultsMeasured blood parameters concentrations were all within the reference ranges reported for healthy dairy cows. The number of extracted factors with the PLS procedure for each prediction model ranged between 3 and 7. The coefficient of determination (R2) of the prediction models ranged between 0.1 to values close to 1. R2 values greater than 0.9 were observed for the prediction models of total cholesterol, total protein, globulin, and albumin; values between 0.75 and 0.9 were observed for urea, NEFA, and total bilirubin, while values of R2 lower than 0.6 were observed for all minerals and for enzyme activity. The range error ratio (RER) and prediction to deviation (RPD) ranged from 5.1 to 43.8 and from 1 to 13.8 for RER and RPD, respectively. Values of RPD greater than 5 were observed for total cholesterol, total protein, albumin, and globulin. RPD ranged between 2 and 5 for the prediction models of urea, NEFA, and total bilirubin, while RPD and RER were low for minerals and enzyme activities.ConclusionsAlthough the results of this study require further validation, the use of FT-MIR spectroscopy was possible and provides fairly accurate measurement of various parameters of great importance in the evaluation of the metabolic and inflammatory status in dairy cows.

Variability of Soil Micronutrients Concentration along the Slopes of Mount Kilimanjaro, Tanzania

Soil micronutrients are important elements for plant growth despite being required in small quantities. Deficiency of micronutrients can result in severe crop failure while excess levels can lead to health hazards; therefore, investigating their status in agricultural land is crucial. Fifty plots were established along an altitudinal gradient from 680 to 1696 m a.s.l. on the slopes of Mount Kilimanjaro, Tanzania. Soils were sampled at the top- (0–20 cm) and subsoils (21–50 cm) in four locations within each plot. Fourier Transform Mid-Infrared (FT-MIR) spectroscopy and wet chemistry were used for soil analysis. Results indicated that the mean concentrations of the micronutrients in the topsoil were Fe (130.4±6.9 mgkg−1), Mn (193.4±20.5 mgkg−1), Zn (2.8±0.2 mgkg−1), B (0.68±0.1 mgkg−1), and Cu (8.4±0.8 mgkg−1). Variations of the micronutrients were not statistically different by elevation (df = 41,p>0.05) and by soil depth (df = 49,p>0.05). Correlations among micronutrients were significant for FeversusMn (r=0.46,p<0.001), BversusZn (r=0.40,p=0.003), BversusCu (r=0.34,p=0.013), and CuversusZn (r=0.88,p<0.001). The correlated micronutrients implied that they were affected by similar factors. Soil pH correlated positively with B, Fe, and Mn and negatively with Cu and Zn, hence probably influencing their availability. Therefore, the need for sustaining micronutrient at sufficient levels is crucial. Management interventions may include moderating soil pH by reducing acidity through liming in the higher elevations and incorporation of organic matter in the lowlands.

Fourier transform mid-infrared spectroscopy (FT-MIR) combined with chemometrics for quantitative analysis of dextrin in Danshen (Salvia miltiorrhiza) granule

The granule of Chinese medicine (GCM) is prepared by water-soluble extract of single yinpian (WESY) of herbal medicine, and used as a drug ingredient for clinical formulation. The WESY content or corresponding yinpian amount is the most important parameter in evaluating the quality of GCM. Low WESY content reflects poor GCM. Classical quantitative methods, such as HPLC, cannot fully detect the adulteration by adding characteristic ingredients and less WESY production. GCM is composed of WESY and a high content of specific excipient. The WESY content in the GCM may be indirectly analyzed using mid-infrared spectroscopy (MIR).In this paper, a quantitative method to evaluate the quality of Danshen (Salvia miltiorrhiza) granule (DG) was developed using MIR combined with chemometrics. Appropriate characteristic quantitative regions (CQR) were extracted by selecting the spectral regions corresponding to altered excipient content in DG. The best model of dextrin content determination in DG with low RMSEC of 1.97, low RMSEP of 2.07, and excellent RPD of 5.03 (>5.0) was obtained using partial least-squares (PLS) regression, and validated using accepted values of precision and recovery. The results suggest that FT-MIR combined with PLS is a rapid and valuable analytical tool to determine the WESY in DG based on excipient content. The model enabling indirect calculation of WESY content in GCM represents a reference standard for rapid analysis of other WESYs in GCM industry.

Fourier Transform Mid-Infrared Photoacoustic Spectroscopy (FTIR-PAS) Coupled with Chemometrics for Non-Destructive Determination of Oil Content in Rapeseed

Fourier Transform Mid-Infrared Photoacoustic Spectroscopy (FTIR-PAS) Coupled with Chemometrics for Non-Destructive Determination of Oil Content in Rapeseed

DETECTION AND QUANTIFICATION OF SOYBEAN AND CORN OILS AS ADULTERANTS IN AVOCADO OIL USING FOURIER TRANSFORM MID INFRARED (FT-MIR) SPECTROSCOPY AIDED WITH MULTIVARIATE CALIBRATION

Authentication of high value edible oils like avocado oil (AO) is an emerging issue. AO can be target of adulteration with low priced oils like soybean and corn oils. The present study is intended to quantify soybean oil (SO) and corn oil (CO) in avocado oil (AO) using the combination of Fourier transform mid infrared (FT-MIR) spectroscopy and chemometrics. The quantification was carried out by partial least square (PLS) calibration using some spectral processing, namely normal spectra, smoothing, and derivation treatment. Frequencies of 1427-779 cm-1 with normal spectra were suitable for the quantification of SO in AO which revealed high coefficient determination (R2), i.e. 0.9994 and low root mean square error of calibration (RMSEC), i.e 0.86% (v/v). Meanwhile, R2 of 0.9994 and RMSEC of 0.87% (v/v) were obtained by PLS at the combined spectra at frequency regions of 1477-721, 1728-1685, and 3035-2881 cm-1 for quantification of CO in AO. The model was further validated using independent samples and offered high R2 values of 0.9994 (for CO) and 0.9998 (for SO) with root mean square error of prediction (RMSEP) of 0.88% (v/v) (CO) and 0.52 % (v/v) (SO), respectively. In general, FT-MIR spectroscopy serves rapid and accurate determination of CO and SO in AO for authenticity studies.

Permafrost Carbon: What soil science has to say about its distribution and fate

Permafrost Carbon: What soil science has to say about its distribution and fate

Liquid Chromatography Tandem Mass Spectrometry Combined with Fourier Transform Mid-Infrared Spectroscopy and Chemometrics for Comparative Analysis of Raw and Processed Gentiana rigescens

Herbal medicines have been shown to change chemical constituents upon different processing approaches, which might lead to different pharmacological activities and therapeutic effects. In this study, raw and processed Gentiana rigescens (wine-, vinegar-, and salt water-processed) were extracted and profiled by ultra-fast liquid chromatography tandem mass spectrometry (UFLC–MS/MS) and Fourier transform mid-infrared spectroscopy (FT-MIR). Hierarchical cluster analysis (HCA) based on FT-MIR revealed potential relationships between raw and processed samples, while the processed sample displayed chemical variation. Partial least-squares discriminate analysis (PLS-DA) was used for screening the marker metabolites. The results indicated that UFLC–UV-MS/MS and FT-MIR fingerprints with chemometrics could effectively evaluate the quality of G. rigescens under different processed approaches. Eight compounds were selected as potential marker metabolites for contributing to the most effective classification of raw and processed samples. In addition, these potential marker metabolites were tentatively identified by matching mass information with the fragmentation patterns of the published literature or standard compounds. These results revealed that UFLC–UV-MS/MS and FT-MIR methods coupled with chemometrics could provide an effective platform for monitoring quality variations of G. rigescens under different processed approaches.