Analyzing strawberry spoilage via its volatile compounds using longpath Fourier transform infrared spectroscopy.
Ontology highlight
ABSTRACT:
SUBMITTER: Dong D
PROVIDER: S-EPMC3761230 | biostudies-other | 2013
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Fourier transform infrared (FTIR) spectroscopy, a technology traditionally used in chemistry to determine the molecular composition of a wide range of sample types, has gained growing interest in microbial typing. It is based on the different vibrational modes of the covalent bonds between atoms of a given sample, as bacterial cells, induced by the absorption of infrared radiation. This technique has been largely used for the study of pathogenic species, especially in the clinical field, and has been proposed also for the typing at different subspecies levels. The high throughput, speed, low cost, and simplicity make FTIR spectroscopy an attractive technique also for industrial applications, in particular, for probiotics. The aim of this study was to compare FTIR spectroscopy with established genotyping methods, pulsed-field gel electrophoresis (PFGE), whole-genome sequencing (WGS), and multilocus sequence typing (MLST), in order to highlight the FTIR spectroscopy potential discriminatory power at strain level. Our study focused on bifidobacteria, an important group of intestinal commensals generally recognized as probiotics. For their properties in promoting and maintaining health, bifidobacteria are largely marketed by the pharmaceutical, food, and dairy industries. Strains belonging to Bifidobacterium longum subsp. longum and Bifidobacterium animalis subsp. lactis were taken into consideration together with some additional type strains. For B. longum subsp. longum, it was possible to discriminate the strains with all the methods used. Although two isolates were shown to be strictly phylogenetically related, constituting a unique cluster, based on PFGE, WGS, and MLST, no clustering was observed with FTIR. For B. animalis subsp. lactis group, PFGE, WGS, and MLST were non-discriminatory, and only one strain was easily distinguished. On the other hand, FTIR discriminated all the isolates one by one, and no clustering was observed. According to these results, FTIR analysis is not only equivalent to PFGE, WGS, and MLST, but also for some strains, in particular, for B. animalis subsp. lactis group, more informative, being able to differentiate strains not discernible with the other two methods based on phenotypic variations likely deriving from certain genetic changes. Fourier transform infrared spectroscopy has highlighted the possibility of using the cell surface as a kind of barcode making tracing strains possible, representing an important aspect in probiotic applications. Furthermore, this work constitutes the first investigation on bifidobacterial strain typing using FTIR spectroscopy.
| S-EPMC8473902 | biostudies-literature
Project description:Okra seeds (OSD) have been proved to possess significantly anti-fatigue activity and due to their high contents of flavonoids and polyphenols. While, the quality of OSD is easily affected by harvest time, region and other factors. In this research, the rapid method based on Fourier transform near infrared (FT-NIR) spectroscopy was developed for quality assessment of okra seeds. Firstly, 120 samples' spectra were acquired, and quantification of isoquercitrin, quercetin-3-O-gentiobioside, total phenols (TP) and antioxidant assays including 1-diphenyl-2-picrylhydrazyl (DPPH) scavenging, ferric reducing antioxidant power (FRAP) were conducted. Next, partial least squares (PLS) regression and full cross-validation were applied to develop calibration models for these data, and external validation was used to determine models' quality. The coefficient of determination for calibration ( R c 2 ), the root mean square error of cross validation (RMSECV) and the corresponding determination coefficients for cross-validation ( R cv 2 ) proved all these models have excellent precision. Besides, the residual predictive deviation (RPD) of models (4.07 for isoquercitrin, 4.04 for quercetin-3-O-gentiobioside, 9.79 for TP, 4.58 for DPPH and 4.12 for FRAP) also demonstrated that these models possessed good predicative ability. All these results showed that FT-NIR spectroscopy could be used to rapidly determine active compounds and antioxidant activity of okra seeds.
| S-EPMC6017380 | biostudies-literature
Project description:Carboxylic acid groups impart hydrophilicity and ionizable moieties to polyamide membranes for desalination, hence influencing water and ion transport through the material. Model polyamide films were synthesized via molecular layer-by-layer deposition on planar substrates to study the formation process of these materials and overcome the chemical and topological inhomogeneity inherent to conventional interfacially polymerized polyamide membranes. The carboxylic acid content in these model films was characterized using Fourier transform infrared (FTIR) spectroscopy by quantifying the C=O band at 1718 cm-1. The concentration of carboxylic acid groups decreased as the thickness of the membrane increased, suggestive of an increase in crosslink density as the polyamide network develops. For the thinnest molecular layer-by-layer (mLbL) samples, the carboxylic acid concentration for films on gold was 0.35 mmol g-1, whereas analogous films on silicon had an acid content of 0.56 mmol g-1, indicating a clear influence of the substrate on the initial network formation. As the thickness of the membrane increased, the influence of the substrate and initial layer growth became less significant as the carboxylic acid concentration on both substrates reached a value of 0.12 mmol g-1. We demonstrate that FTIR spectroscopy is a practical and accessible way to quantify the carboxylic acid content in these types of extremely thin polyamide membranes to help quantify network formation in these materials.
| S-EPMC6459611 | biostudies-literature
Project description:We assess the assembly of supramolecular complexes by hydrogen bonding between azocompounds and a diacylaminopyridine monomer by temperature-dependent Fourier transform infrared spectroscopy (FT-IR) and density functional theory (DFT) calculations. The electronic delocalisation in the supramolecular rings formed by multiple hydrogen bonds stabilises the complexes, which coexist with dimeric species in temperature-dependent equilibria. We show how the application of readily available molecular modelling and spectroscopic techniques can predict the stability of new supramolecular entities coexisting in equilibria, ultimately assessing the success of molecular recognition.
| S-EPMC6225378 | biostudies-literature
Project description:The ability to diagnose cancer rapidly with high sensitivity and specificity is essential to exploit advances in new treatments to lead significant reductions in mortality and morbidity. Current cancer diagnostic tests observing tissue architecture and specific protein expression for specific cancers suffer from inter-observer variability, poor detection rates and occur when the patient is symptomatic. A new method for the detection of cancer using 1 μl of human serum, attenuated total reflection-Fourier transform infrared spectroscopy and pattern recognition algorithms is reported using a 433 patient dataset (3897 spectra). To the best of our knowledge, we present the largest study on serum mid-infrared spectroscopy for cancer research. We achieve optimum sensitivities and specificities using a Radial Basis Function Support Vector Machine of between 80.0 and 100 % for all strata and identify the major spectral features, hence biochemical components, responsible for the discrimination within each stratum. We assess feature fed-SVM analysis for our cancer versus non-cancer model and achieve 91.5 and 83.0 % sensitivity and specificity respectively. We demonstrate the use of infrared light to provide a spectral signature from human serum to detect, for the first time, cancer versus non-cancer, metastatic cancer versus organ confined, brain cancer severity and the organ of origin of metastatic disease from the same sample enabling stratified diagnostics depending upon the clinical question asked.
| S-EPMC4835510 | biostudies-literature
Project description:In this study we explore the potential of using Fourier-transform infrared (FTIR) spectra of trifluoroacetate-protein and peptide complexes for monitoring proteolytic reactions. The idea of treating dry-films of protein hydrolysates with trifluoroacetic acid (TFA) prior to FTIR analysis is based on the unique properties of TFA. By adding a large excess of TFA to protein hydrolysate samples, the possible protonation sites of the proteins and peptides will be saturated. In addition, TFA has a low boiling point when protonated as well as complex-forming abilities. When forming TFA-treated dry-films of protein hydrolysates, the excess TFA will evaporate and the deprotonated acid (CF3COO-) will interact as a counter ion with the positive charges on the sample materials. In the study, spectral changes in TFA-treated dry-films of protein hydrolysates from a pure protein and poultry by-products, were compared to the FTIR fingerprints of untreated dry-films. The results show that time-dependent information related to proteolytic reactions and, consequently, on the characteristics of the protein hydrolysates can be obtained. With additional developments, FTIR on dry-films treated with TFA may be regarded as a potential future tool for the analysis of all types of proteolytic reactions in the laboratory as well as in industry.
| S-EPMC7217958 | biostudies-literature
Project description:Fourier transform infrared (FTIR) spectroscopy provides a unique molecular fingerprint of tissue from endogenous sources of light absorption; however, specific molecular components of the overall FTIR signature of precancer have not been characterized. In attenuated total reflectance mode, infrared light penetrates only a few microns of the tissue surface, and the influence of water on the spectra can be minimized, allowing for the analyses of the molecular composition of tissues. Here, spectra were collected from 98 excised specimens of the distal esophagus, including 38 squamous, 38 intestinal metaplasia (Barrett's), and 22 gastric, obtained endoscopically from 32 patients. We show that DNA, protein, glycogen, and glycoprotein comprise the principal sources of infrared absorption in the 950- to 1,800-cm(-1) regime. The concentrations of these biomolecules can be quantified by using a partial least-squares fit and used to classify disease states with high sensitivity, specificity, and accuracy. Moreover, use of FTIR to detect premalignant (dysplastic) mucosa results in a sensitivity, specificity, positive predictive value, and total accuracy of 92%, 80%, 92%, and 89%, respectively, and leads to a better interobserver agreement between two gastrointestinal pathologists for dysplasia (kappa = 0.72) versus histology alone (kappa = 0.52). Here, we demonstrate that the concentration of specific biomolecules can be determined from the FTIR spectra collected in attenuated total reflectance mode and can be used for predicting the underlying histopathology, which will contribute to the early detection and rapid staging of many diseases.
| S-EPMC2000401 | biostudies-literature
Project description:The moisture content of beetroot varies during long-term cold storage. In this work, we propose a strategy to identify the moisture content and age of beetroot using principal component analysis coupled Fourier transform infrared spectroscopy (FTIR). Frequent FTIR measurements were recorded directly from the beetroot sample surface over a period of 34 days for analysing its moisture content employing attenuated total reflectance in the spectral ranges of 2614-4000 and 1465-1853 cm-1 with a spectral resolution of 8?cm-1. In order to estimate the transmittance peak height (T p ) and area under the transmittance curve [Formula: see text] over the spectral ranges of 2614-4000 and 1465-1853 cm-1, Gaussian curve fitting algorithm was performed on FTIR data. Principal component and nonlinear regression analyses were utilized for FTIR data analysis. Score plot over the ranges of 2614-4000 and 1465-1853 cm-1 allowed beetroot quality discrimination. Beetroot quality predictive models were developed by employing biphasic dose response function. Validation experiment results confirmed that the accuracy of the beetroot quality predictive model reached 97.5%. This research work proves that FTIR spectroscopy in combination with principal component analysis and beetroot quality predictive models could serve as an effective tool for discriminating moisture content in fresh, half and completely spoiled stages of beetroot samples and for providing status alerts.
| S-EPMC5964165 | biostudies-literature
Project description:Leishmania species are protozoan parasites and the causative agents of leishmaniasis, a vector borne disease that imposes a large health burden on individuals living mainly in tropical and subtropical regions. Different Leishmania species are responsible for the distinct clinical patterns, such as cutaneous, mucocutaneous, and visceral leishmaniasis, with the latter being potentially fatal if left untreated. For this reason, it is important to perform correct species identification and differentiation. Fourier transform infrared spectroscopy (FTIR) is an analytical spectroscopic technique increasingly being used as a potential tool for identification of microorganisms for diagnostic purposes. By employing mid-infrared (MIR) spectral data, it is not only possible to assess the chemical structures but also to achieve differentiation supported by multivariate statistic analysis. This work comprises a pilot study on differentiation of Leishmania species of the Old World (L. major, L. tropica, L. infantum, and L. donovani) as well as hybrids of distinct species by using vibrational spectroscopic fingerprints. Films of intact Leishmania parasites and their deoxyribonucleic acid (DNA) were characterized comparatively with respect to their biochemical nature and MIR spectral patterns. The strains' hyperspectral datasets were multivariately examined by means of variance-based principal components analysis (PCA) and distance-based hierarchical cluster analysis (HCA). With the implementation of MIR spectral datasets we show that a phenotypic differentiation of Leishmania at species and intra-species level is feasible. Thus, FTIR spectroscopy can be further exploited for building up spectral databases of Leishmania parasites in view of high-throughput analysis of clinical specimens. Graphical abstract For Leishmania species discrimination, sample films of intact parasites and their extracted DNA were analyzed by FTIR micro-spectroscopy. Hyperspectral datasets that comprise mid-infrared fingerprints were submitted to multivariate analysis tools such as principal components analysis (PCA) and hierarchical cluster analysis (HCA).
| S-EPMC5670197 | biostudies-literature
Project description:Multiple sclerosis (MS) is a chronic, progressive, inflammatory and degenerative disease of central nervous system. Here, we aimed to develop a method for differential diagnosis of Relapsing-Remitting MS (RRMS) and clinically isolated syndrome (CIS) patients, as well as to identify CIS patients who will progress to RRMS, from cerebrospinal fluid (CSF) by infrared (IR) spectroscopy and multivariate analysis. Spectral analyses demonstrated significant differences in the molecular contents, especially in the lipids and Z conformation of DNA of CSF from CIS, CIS to RRMS transformed (TCIS) and RRMS groups. These changes enables the discrimination of diseased groups and controls (individuals with no neurological disease) from each other using hierarchical cluster and principal component analysis. Some CIS samples were consistently clustered in RRMS class, which may indicate that these CIS patients potentially will transform to RRMS over time. Z-DNA band at 795?cm-1 that is existent only in diseased groups and significant increase in carbonyl amount, decrease in amideI/amide II and lipid/protein ratios observed only for RRMS groups can be used as diagnostic biomarkers. The results of the present study shed light on the early diagnosis of RRMS by IR spectroscopy complemented with multivariate analysis tools.
| S-EPMC5773569 | biostudies-literature