Fourier Transform Infrared Spectroscopy In Combination Research Articles

Validated differentiation of Listeria monocytogenes serogroups by FTIR spectroscopy using an Artificial Neural Network based classifier in an accredited official food control laboratory

Listeria monocytogenes is a well-known human pathogen, and especially the young, the elderly, otherwise immunocompromised individuals or pregnant women might suffer severe health consequences from listeriosis. Up to date, Fourier-Transform Infrared (FTIR) spectroscopical methods have been established for decades as a valuable means to differentiate between microbiological specimens at different taxonomical levels. In recent years, machine-based learning methods using Artificial Neural Networks (ANN) have highly advanced the discriminatory power of distinguishing spectrally closely related units such as serogroups of a given species. The present report describes the classification performance evaluation of a manufacturer (Bruker Daltonics, Bremen, Germany) - provided L. monocytogenes serogroup classifier by means of a formalized external validation carried out in a single laboratory. N = 630 absorption spectra from n = 94 food L. monocytogenes isolates pertaining to n = 11 serotypes / n = 3 serogroups were recorded on the IR Biotyper (Bruker Daltonics) and subsequently typed by the given classifier. The quantitative evaluation of inclusivity and exclusivity was performed following the principles of the Guidelines for Validating Species Identifications Using MALDI-TOF-MS issued by the German Federal Office of Consumer Protection (BVL) for a targeted identification. The FTIR classifier allocated all n = 486 spectra from n = 71 serogroup 1/2 and 4 isolates correctly to their respective serogroups, resulting in a true-positive rate of 100%. All remaining n = 144 spectra from n = 23 isolates of serogroup 3 were correctly allocated to an arbitrarily combined class entity of serogroups 3 and 7, likewise yielding both inclusivity and exclusivity rates of 100%. Consequently, in our official food control laboratory, this validated IR Biotyper method has been integrated into the accredited workflow for L. monocytogenes analysis in food samples according to ISO 11290, followed by MALDI-TOF MS confirmation on the species level to subsequent serogrouping and pre-selection by FTIR spectroscopy for Whole Genome Sequencing (WGS). This study confirmed that FTIR spectroscopy in combination with Artificial Neural Networks proves to be a reliable and thus valuable tool for the differentiation of the most common serogroups from Listeria monocytogenes. The application of FTIR spectroscopy saves valuable resources with respect to labor and time and thus facilitates outbreak analyses of the clinically relevant severe food-borne disease listeriosis where potentially a high number of isolates are involved.

Discrimination and Evaluation of Wild Paris Using UHPLC-QTOF-MS and FT-IR Spectroscopy in Combination with Multivariable Analysis.

Genus Paris has numerous bioactive constituents such as steroid saponins, flavonoids, and polysaccharose which are responsible for antitumor, hemostatic, and anthelmintic, etc. In this study, ultrahigh performance liquid chromatography coupled to time-of-flight mass spectrometer (UHPLC-QTOF-MS) and Fourier transform infrared (FT-IR) spectroscopy in combination with multivariable analysis were employed to discriminate the different species of Paris including P. polyphylla var. yunnanensis (PPY), P. polyphylla var. alba, P. mairei (PM), P. vietnamensis, and P. polyphylla var. stenophylla. Partial least square discriminate analysis based on UHPLC, FT-IR, and midlevel data fusion was used to distinguish 43 batches of Paris. Chemical constituents of different species Paris were determined by UHPLC-QTOF-MS. The result indicated that midlevel data fusion had a good performance in the classification compared to a single analytical technology. A total of 47 compounds were identified in different species Paris. The similar results indicated that PM could be treated as a proposal substitute of PPY.

Spectroscopic and Computational Observation of Glutamine Tautomerization in the Blue Light Sensing Using Flavin Domain Photoreaction.

Blue light sensing using flavin (BLUF) domains constitute a family of flavin-binding photoreceptors of bacteria and eukaryotic algae. BLUF photoactivation proceeds via a light-driven hydrogen-bond switch among flavin adenine dinucleotide (FAD) and glutamine and tyrosine side chains, whereby FAD undergoes electron and proton transfer with tyrosine and is subsequently re-oxidized by a hydrogen back-shuttle in picoseconds, constituting an important model system to understand proton-coupled electron transfer in biology. The specific structure of the hydrogen-bond patterns and the prevalence of glutamine tautomeric states in dark-adapted (DA) and light-activated (LA) states have remained controversial. Here, we present a combined femtosecond stimulated Raman spectroscopy (FSRS), computational chemistry, and site-selective isotope labeling Fourier-transform infrared spectroscopy (FTIR) study of the Slr1694 BLUF domain. FSRS showed distinct vibrational bands from the FADS1 singlet excited state. We observed small but significant shifts in the excited-state vibrational frequency patterns of the DA and LA states, indicating that these frequencies constitute a sensitive probe for the hydrogen-bond arrangement around FAD. Excited-state model calculations utilizing four different realizations of hydrogen bond patterns and glutamine tautomeric states were consistent with a BLUF reaction model that involved glutamine tautomerization to imidic acid, accompanied by a rotation of its side chain. A combined FTIR and double-isotope labeling study, with 13C labeling of FAD and 15N labeling of glutamine, identified the glutamine imidic acid C═N stretch vibration in the LA state and the Gln C═O in the DA state. Hence, our study provides support for glutamine tautomerization and side-chain rotation in the BLUF photoreaction.

Seasonal biochemical changes in Betula tortuosa Ledeb. annual rings in Alpine forest-tundra of Kuznetsk Ala Tau Mountains

Woody vegetation growth conditions have marked effects on hemicellulose, cellulose and lignin formation. In this study, the climatic responses of these major cell wall polymers in Betula tortuosa Ledeb. were analyzed. 35 annual rings (1980–2015) of Betula tortuosa Ledeb. trees growing in the alpine forest-tundra of Kuznetsk Ala Tau were studied using Fourier-transform infrared (FTIR) spectroscopy and pyrolysis–gas chromatography–mass spectrometry (Py–GC/MS). Analysis of the correlation of the resulting spectra and Py–GC/MS values with mean air temperature and precipitation showed that the polymeric composition of Betula tortuosa Ledeb. was mainly determined by June–August climate. The major factor limiting the development of the “unique” cell wall polymer composition of Betula tortuosa Ledeb. found in alpine forest-tundra of Kuznetsk Ala Tau was a deficit of heat. At the end of the growing season, precipitation had a largely negative impact on polymer formation in Betula tortuosa Ledeb. cell walls. The authors believe that combining FTIR spectroscopy and Py–GC/MS is an effective approach to quantifying the consequences of current climate trends for Siberian forest ecosystems.

Spectroscopic evidence of the radioresistance of Chroococcidiopsis biosignatures: A combined Raman, FT-IR and THz-TDs spectroscopy study

In the last decades, Mars has been widely studied with on-site missions and observations, showing a planet that could have hosted life in the past. For this reason, the recent and future space missions on the red planet will search for traces of past and, possibly, present life. As a basis for these missions, Space Agencies, such as the European Space Agency, have conducted many experiments on living organisms, studying their behavior in extraterrestrial conditions, learning to recognize their biosignatures with techniques remotely controllable such as Raman spectroscopy. Among these organisms, the radioresistant cyanobacterium Chroococcidiopsis was irradiated during the STARLIFE campaign with strong radiative insults. In this article we have investigated this cyanobacterium using Raman spectroscopy and extended the characterization of its biosignatures and its response to the radiative stress to the mid- Infrared and Terahertz spectral region using the Fourier Transform InfraRed (FT-IR) and Terahertz Time Domain spectroscopy (THz- TDs), which demonstrates the compatibility and suitability of these techniques for future space missions.

Analysis of beef meatballs with rat meat adulteration using Fourier Transform Infrared (FTIR) spectroscopy in combination with chemometrics

ABSTRACT Indonesia is a country with a majority Muslim population, and the halal food consumed should be assured. One type of food that must be considered halal is food from meat products. Due to the price difference between halal meat and non-halal meat, some unethical producers try to adulterate beef with non-halal meat of rat meat. The research objective was to employ FTIR spectroscopy in combination with chemometrics for the analysis of rat meat adulteration in beef meatballs. Lipid components in meatballs containing beef, rat meat, or its binary mixture were extracted using three extraction methods, namely Bligh and Dyer, Folch, and Soxhlet methods. The lipid components extracted were then analyzed using FTIR spectroscopy and FTIR spectra obtained were used as variables during chemometrics modeling. The absorbance values of FTIR spectra of lipid components extracted by Bligh and Dyer, Folch, and Soxhlet methods at selected wavenumbers regions of 3100–800 cm−1 were selected for discrimination between beef meatballs and meatballs adulterated with rat meat using chemometrics of linear discriminant analysis (LDA). LDA was successfully used to classify lipid components extracted by three lipid extraction methods from beef meatballs and rat meatballs with accuracy levels of 100%. The prediction of rat meatballs was successfully determined using multivariate calibrations of Partial Least Square (PLS) and Principle Component Regression (PCR) using optimized conditions. The difference in lipid composition, as indicated in FTIR spectra profiles of the analyzed samples, is used as a fingerprint technique for the analysis of rat meat in beef meatballs for halal authentication purposes.

Detection of diagenetic alteration in bones and teeth for migration and dietary studies \u2014 a combined FTIR and C-N\u2013O-Sr isotope study on tenth century CE cemeteries in northern and northeastern Hungary

Stable isotope-based dietary information on the tenth century CE Hungarian population serves as a valuable comparative tool to other dietary stable isotope studies in the region. This study presents a multiproxy approach involving skeletal samples with the least diagenetic alteration and the best-preserved primary signals. Dental and bone samples collected from three cemeteries in northeastern Hungary were investigated using a combination of Fourier-transform infrared spectroscopy (FTIR), stable isotope geochemistry, and strontium isotope analysis. FTIR measurements were used to detect the addition of secondary carbonate to the skeletal apatite carbonate component and to differentiate diagenetically altered samples. Our results suggest that all but the bone apatite carbonate stable isotope values and 87Sr/86Sr ratios are trustworthy and may be used to interpret the diet and migration of the researched individuals. We also determined that the inhabitants of the three tenth century CE Hungarian settlements relied primarily on C3 plants, but that C4 plants, most likely broomcorn millet (P. miliaceum), comprised a moderate portion of their plant-based diet and that animal products were generally consumed in moderate-high amounts. Coupled analyses of carbonate oxygen and strontium isotope compositions revealed that most of the bone apatite carbonate was heavily altered, whereas enamel apatite carbonate samples largely preserved their primary compositions. The bones showing the least amount of diagenetic alteration may partially preserve their primary apatite carbonate compositions, as well as show a combination of primary and secondary signals, which should be taken into consideration when bone apatite carbonate data are interpreted.

Discriminant Analysis of the Geographical Origin of Asian Red Pepper Powders Using Second-Derivative FT-IR Spectroscopy.

This study aimed to discriminate between the geographical origins of Asian red pepper powders distributed in Korea using Fourier-transform infrared (FT-IR) spectroscopy coupled with multivariate statistical analyses. Second-derivative spectral data were obtained from a total of 105 red pepper powder samples, 86 of which were used for statistical analysis, and the remaining 19 were used for blind testing. A one-way analysis of variance (ANOVA) test confirmed that eight peak variables exhibited significant origin-dependent differences, and the canonical discriminant functions derived from these variables were used to correctly classify all the red pepper powder samples based on their origins. The applicability of the canonical discriminant functions was examined by performing a blind test wherein the origins of 19 new red pepper powder samples were correctly classified. For simplicity, the four most significant variables were selected as discriminant indicator variables, and the applicable range for each indicator variable was set for each geographical origin. By applying the indicator variable ranges, the origins of the red pepper powders of all the statistical and blind samples were correctly identified. The study findings indicate the feasibility of using FT-IR spectroscopy in combination with multivariate analysis for identifying the geographical origins of red pepper powders.

Infrared spectroscopy coupled with chemometrics in coffee post-harvest processes as complement to the sensory analysis

Sensory evaluation provides subjective information about characteristics related to the crop management and post-harvesting of coffee. Fourier Transform Infrared Spectroscopy (FTIR) quickly and easily detects additional coffee characteristics to those obtained through sensory analysis. This work aimed to complement the sensory evaluation of Specialty coffee by using FTIR and chemometrics. Samples from all three post-harvest methods (dry, semi-dry, and wet) were sensory analysed using the protocol of the Specialty Coffee Association (SCA). Infrared spectra were obtained from samples of green beans, medium roast coffee, and dark roast coffee, previously processed by the three post-harvest methods. Sensory evaluation, according to the SCA quality criteria, classified the coffee obtained from semi-dry process as excellent specialty coffee, and coffees obtained by wet and dry processing methods as very good specialty coffees. PCAs discriminated the post-harvest treatments based on the FTIR data. Recognition based on prediction of samples of the post-harvest treatments by LDAs was over 95%. Results demonstrated that FTIR in combination with multivariate analysis complemented the information obtained from the sensory analysis, and allowed to discriminate and identify the post-harvest treatments for green beans, medium roast coffee, and dark roast coffee.

Systematic stability testing of insulins as representative biopharmaceuticals using ATR FTIR-spectroscopy with focus on quality assurance.

.Significance: Bioactive proteins represent the most important component class in biopharmaceutical products for therapeutic applications. Their production is most often biotechnologically realized by genetically engineered microorganisms. For the quality assurance of insulins as representatives of life-saving pharmaceuticals, analytical methods are required that allow more than total protein quantification in vials or batches. Chemical and physical factors such as unstable temperatures or shear rate exposure under storage can lead to misfolding, nucleation, and subsequent fibril forming of the insulins. The assumption is valid that these processes go parallel with a decrease in bioactivity.Aim: Infrared (IR) spectroscopy has been successfully utilized for secondary structure analysis in cases of protein misfolding and fibril formation.Approach: A reliable method for the quantification of the secondary structure changes has been developed using insulin dry-film Fourier-transform IR spectroscopy in combination with the attenuated total reflection (ATR) technique and subsequent data analyses such as band-shift determination, spectral band deconvolution, and principal component analysis.Results: A systematic study of insulin spectra was carried out on model insulin specimens, available either as original formulations or as hormones purified by ultrafiltration. Insulin specimens were stored at different temperatures, i.e., 0°C, 20°C, and 37°C, respectively, for up to three months. Weekly ATR-measurements allowed the monitoring of hormone secondary structure changes, which are supposed to be negatively correlated with insulin bioactivity.Conclusions: It could be shown that IR-ATR spectroscopy offers a fast and reliable analytical method for the determination of secondary structural changes within insulin molecules, as available in pharmaceutical insulin formulations and therefore challenges internationally established measurement techniques for quality control regarding time, costs, and effort of analysis.

Fourier transform infrared spectroscopy of milk samples as a tool to estimate energy balance, energy- and dry matter intake in lactating dairy cows.

The objective of the study was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) analysis of milk samples to predict body energy status and related traits (energy balance (EB), dry matter intake (DMI) and efficient energy intake (EEI)) in lactating dairy cows. The data included 2371 milk samples from 63 Norwegian Red dairy cows collected during the first 105 days in milk (DIM). To predict the body energy status traits, calibration models were developed using Partial Least Squares Regression (PLSR). Calibration models were established using split-sample (leave-one cow-out) cross-validation approach and validated using an external test set. The PLSR method was implemented using just the FTIR spectra or using the FTIR together with milk yield (MY) or concentrate intake (CONCTR) as predictors of traits. Analyses were conducted for the entire first 105 DIM and separately for the two lactation periods: 5 ≤ DIM ≤ 55 and 55 < DIM ≤ 105. To test the models, an external validation using an independent test set was performed. Predictions depending on the parity (1st, 2nd and 3rd-to 6th parities) in early lactation were also investigated. Accuracy of prediction (r) for both cross-validation and external test set was defined as the correlation between the predicted and observed values for body energy status traits. Analyzing FTIR in combination with MY by PLSR, resulted in relatively high r-values to estimate EB (r = 0.63), DMI (r = 0.83), EEI (r = 0.84) using an external validation. Only moderate correlations between FTIR spectra and traits like EB, EEI and dry matter intake (DMI) have so far been published. Our hypothesis was that improvements in the FTIR predictions of EB, EEI and DMI can be obtained by (1) stratification into different stages of lactations and different parities, or (2) by adding additional information on milking and feeding traits. Stratification of the lactation stages improved predictions compared with the analyses including all data 5 ≤ DIM ≤105. The accuracy was improved if additional data (MY or CONCTR) were included in the prediction model. Furthermore, stratification into parity groups, improved the predictions of body energy status. Our results show that FTIR spectral data combined with MY or CONCTR can be used to obtain improved estimation of body energy status compared to only using the FTIR spectra in Norwegian Red dairy cattle. The best prediction results were achieved using FTIR spectra together with MY for early lactation. The results obtained in the study suggest that the modeling approach used in this paper can be considered as a viable method for predicting an individual cow's energy status.

Detecting fentanyl using point-of-care drug checking technologies: A validation study

ObjectivesPoint-of-care drug checking services, wherein individuals can check the content and purity of their drugs, have emerged as a public health intervention to address the fentanyl crisis; however, there have been no rigorous evaluations of the technologies against reference standard laboratory techniques. MethodsTwo point-of-care technologies, fentanyl immunoassay strips and Fourier-Transform Infrared (FTIR) spectroscopy, were implemented at two supervised injection sites in Vancouver, Canada. We calculated sensitivity, specificity, and false negative rate for both testing methods as compared to a laboratory reference standard. ResultsBetween October 2017 and 2018, 331 samples were sent for confirmatory testing. Immunoassay strips had a sensitivity of 87.5% and specificity of 95.2%, with a false negative rate of 12.5%. FTIR spectroscopy had a sensitivity of 72.1% and specificity of 99.0%, with a false negative rate of 27.9%. ConclusionAs expected, while FTIR spectroscopy can quantify concentrations on a wide array of compounds, it can only do so above the detection limit. Using FTIR spectroscopy and immunoassay strips in combination has the potential to offset the limitations of each technology when used alone.

The use of FTIR and Raman spectroscopy in combination with chemometrics for analysis of biomolecules in biomedical fluids: A review

Fourier transform infrared (FTIR) and Raman spectroscopy are complementary techniques, typically called vibrational spectroscopy. Both techniques allow simple, rapid, non-destructive, specific, providing fingerprint spectra, and real-time analytical method for analysis of molecules in different states. Besides, these methods are simple without any excessive sample pre-treatment, therefore, they are sometimes called as “green analytical methods”. Biofluids have several biomolecules such as lipid, protein, nucleic acids, and carbohydrates. These biomolecules can be used as biomarkers to detect some types of diseases, since biomolecules are in direct contact with the human organs. FTIR and Raman spectra of biofluids are complex in nature, therefore sophisticated statistical techniques, known as chemometrics, must be used to solve the analytical problems related to quantitative analysis purposes. The objective of this review is to show the capability of FTIR and Raman spectroscopic techniques in combination with chemometrics techniques to analyze the biomolecules in biofluids through an extensive literature review. During performing this review, several databases in Science citation index, Scopus PubMed, and Google Scholar related to the topics are identified and downloaded. With the present review, it is known that FTIR and Raman techniques are rapid method for screening certain diseases by identifying the level changes of some biomolecules. In the future, this method will be widely used for clinicians as new diagnostic tools for many diseases.

Postmortem Diagnosis of Fatal Hypothermia by Fourier Transform Infrared Spectroscopic Analysis of Edema Fluid in Formalin-Fixed, Paraffin-Embedded Lung Tissues.

The goal of this study was to investigate whether pulmonary edema could become a specific diagnostic marker for fatal hypothermia using Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics. The spectral profile analysis indicated that hypothermia fatalities associated with pulmonary edema fluid contained more β-sheet protein conformational structures than the control causes of death, which included sudden cardiac death, brain injury, cerebrovascular disease, mechanical asphyxiation, intoxication, and drowning. Subsequently, the results of principal component analysis (PCA) further revealed that the content of β-sheet protein conformational structures in the pulmonary edema fluid was the main discriminatory marker between fatal hypothermia and the other causes of death. Ultimately, a robust postmortem diagnostic model for fatal hypothermia using a partial least-squares discriminant analysis (PLS-DA) algorithm was constructed. Pulmonary edema fluid spectra collected from eight new forensic autopsy cases that did not participate in the construction of the diagnostic model were predicted using the model. The results showed the causes of death of all these eight cases were correctly classified. In conclusion, this preliminary study demonstrates that FTIR spectroscopy in combination with chemometrics could be a promising approach for the postmortem diagnosis of fatal hypothermia.

Assessing the limit of detection of Fourier-transform infrared spectroscopy and immunoassay strips for fentanyl in a real-world setting.

Drug checking is a harm reduction intervention increasingly used in the context of the opioid overdose epidemic. The aim of the study was to determine the limit of detection for fentanyl of two point-of-care drug checking technologies. Samples tested at point-of-care using Bruker Fourier transform infrared (FTIR) spectroscopy and BTNX fentanyl immunoassay strips were sent for confirmatory laboratory analysis using quantitative nuclear magnetic resonance (qNMR) spectroscopy. Concentrations by weight were determined and compared to results obtained with point-of-care methods. In total, 283 samples were sent for qNMR analysis; among these, 173 (61.1%) tested positive for fentanyl. As determined by qNMR, fentanyl concentration by weight ranged from 1% to 91%. Among these 173 samples, fentanyl was not detected in 30 (17.3%) samples by FTIR and in 4 (2.3%) samples by test strip. Samples containing fentanyl that went undetected by FTIR had concentrations ≤10%. The four samples containing fentanyl that went undetected by test strip had concentrations ≤5% (i.e. 1%, 3%, 4%, 5%). Fentanyl immunoassay strips were able to consistently detect the presence of fentanyl in samples at lower concentrations than FTIR spectroscopy. Given that FTIR spectroscopy is able to quantify content, mixture and concentrations on an array of compounds beyond just fentanyl but requires concentrations generally greater than 10%, these findings provide evidence for use of FTIR spectroscopy and immunoassay strips in combination to compensate for the limitations of each technology alone.

The structure and interaction properties of two task-specific ionic liquids and acetonitrile mixtures: A combined FTIR and DFT study.

The mixtures of ionic liquid (IL) and acetonitrile (CH3CN) can be used as reaction media, supercapacitors and thermally stable electrolytes. The macroscopic properties of ILs-CH3CN mixtures have been extensively studied. However, some fundamental questions regarding the microscopic properties of ILs-CH3CN mixtures still remain to be answered. In this work, the structure properties and hydrogen-bond interactions of two task-specific ILs, i.e., 1-propylnitrile-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([PCNMIM][Tf2N]) and 1-(2'-hydroxylethyl)-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([C2OHMIM][Tf2N]), and CH3CN were studied using the combination of Fourier transform infrared spectroscopy (FTIR) and density functional theory (DFT) calculations. The aromatic C‒H stretching vibration region of the cation was an area of special focus. Excess infrared spectroscopy with enhanced resolution was applied to analyse the original infrared spectra. It is found that: (1) The two ILs form stable hydrogen-bonds with CH3CN. (2) Ion cluster, ion cluster-acetonitrile, and ion pair-acetonitrile are identified in the mixture. Acetonitrile cannot break apart the strong electronic interaction between the cation and anion in the examined concentration range. (3) The hydrogen-bonds are weak strength, closed shell and electrostatic dominant interactions. (4) The preferred interaction site of [PCNMIM]+ cation is the hydrogen atom at the C2 site, while that of [C2OHMIM]+ cation is the hydrogen atom in the hydroxyl group.

Detection of lard contamination in five different edible oils by FT-IRspectroscopy using a partial least squares calibration model

Lard is defined as animal fat acquired from the adipose tissue of pigs and is not permitted for human consumption or external use by certain religions such as Islam and Judaism. Due to its low-cost availability for commercial use, it is often mixed with other vegetable oils mistakenly or deliberately and causes loss of consumer trust; hence, its detection in food products is essential. Consumers tend to know the authenticity of commercially available edible oils. However, edible oils are subjected to adulteration risks with lard, which breaches consumer rights. In the present study, we designed a transmission Fourier transform infrared spectroscopy (FT-IR)-based method for the rapid detection of lard in sunflower, canola, coconut, olive, and mustard oils. For this purpose, the selected oils were adulterated with lard in different concentration ratios (10:0, 9:1, 7:3, 6:4, 4:6, 3:7, 0:10). A single calibration model was developed for 35 standards (seven standards from each individual five oils) in the frequency range between 1078.01 and 1246.75 cm$^{-1}$ to determine the relationship between actual adulterant concentration and FT-IR predicted concentrations using a partial least squares (PLS) method. The results of the present study indicated that FT-IR in combination with PLS has the potential to evaluate adulteration of edible oils with lard through single calibration as a rapid, nondestructive, and effective alternative method.

THE AUTHENTICATION OF VIRGIN COCONUT OIL FROM GRAPE SEED OIL AND SOYBEAN OIL USING FTIR SPECTROSCOPY AND CHEMOMETRICS

Objective: The objective of this study was to develop Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of multivariate calibration and discriminant analysis (DA) for the authentication of virgin coconut oil (VCO) from grape seed oil (GSO) and soybean oil (SO).&#x0D; Methods: FTIR spectra of VCO, GSO, SO and its binary mixture of VCO-SO, and VCO-GSO were scanned at mid-infrared region (4000-650 cm-1) using attenuated total reflectance technique. The wavenumbers were selected based on its capability to provide the best prediction models for quantification and classification of adulterants in VCO assisted by multivariate calibrations and DA, respectively.&#x0D; Results: The results showed that partial least square (PLS) calibration using absorbance values at combined wavenumbers of 1200-900 and 3027-2985 cm-1 revealed reliable method for quantification of GSO in VCO, as indicated by high value of coefficient of determination (R2) and low value of root mean square of calibration (RMSEC) and root mean square error of prediction (RMSEP). PLS using FTIR spectra at the combined wavenumbers of 1200-1000 and 3025-2995 cm-1 was suitable for quantitative analysis of SO in VCO. DAwas also successfully used for classification of VCO and VCO added with adulterants of GSO and SO.&#x0D; Conclusion: FTIR spectroscopy in combination with chemometrics of multivariate calibration and DA offered effective tools for the authentication of VCO

QUANTITATIVE ANALYSISOF STEVIOSIDE AND REBAUDIOSIDE A IN STEVIAREBAUDIANA LEAVES USING INFRARED SPECTROSCOPY AND MULTIVARIATE CALIBRATION

Objective: The objective of this research was to develop Fourier transform infrared (FTIR) spectroscopy in combination with multivariate analysis of partial least square (PLS) regression for quantitative analysis of stevioside and rebaudioside A in S. rebaudiana leaves extract.Methods: Stevia rebaudiana leaves with various ages were obtained from several high hills in Central Java, Indonesia. The extract samples were scanned using FTIR spectrophotometer in wavenumbers region of 4000–650 cm-1. PLS calibration model was established by plotting the actual value of stevioside and rebaudioside A as determined by high-performance liquid chromatography (HPLC) and FTIR predicted value. The performance of PLS regression was evaluated using coefficient determination (R2), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP).Results: PLS regression for stevioside determination was successfully established using the combined wavenumber region of 671–1450 and 3279-3301 cm-1. PLS regression revealed R2of 0.9952with RMSEC value of0.84%. Meanwhile, rebaudioside A was determined at wavenumber region of 921–1508 cm-1using normal spectra. PLS model revealed R2 and RMSEC of 0.9911 and 0.70%, respectively.Conclusion: FTIR spectroscopy in combination with multivariate analysis of PLS regression could be used as an alternative method for quantitative analysis ofstevioside and rebaudioside A in S. rebaudiana leaves.

Study of the structural order of native starch granules using combined FTIR and XRD analysis

The structural order of native starch granules with different crystalline patterns was analyzed by combined X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) and the results were compared to that of X-ray diffraction (XRD). The FTIR spectra of 13 starch samples were evaluated by principal component analysis (PCA). The main differences among the polymorphs were observed in the intensity of two regions: the OH vibration region, 3650–3000 cm−1, and the region of major adsorption bands, 1200–800 cm−1. The variation in these regions showed that two different groups can be distinguished, one for B-type starches and one for A- and C-type starches. A-type starches exhibited a well-resolved band at 1022 cm−1, suggesting that A-type starch granules have a greater amount of ordered short-range double helices than B-type starches. The intensity and shape of the OH band were different for the three starches and were associated with different local molecular environments of the two water populations of the starch granule. The PCA analysis for X-ray diffraction patterns showed a clear segregation between A- and B-type starches, defined by three typical diffraction peaks at 2θ = 15.0°, 18.1° and 23.1° for A-type starches. There was no correlation in the crystallinity degree obtained by the FTIR and XRD methods.