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F S Fry

Publications and source records attributed to F S Fry.

9 recordsLinked to original sources
PubMed2004

Detection and identification of bacteria in a juice matrix with Fourier transform-near infrared spectroscopy and multivariiate analysis.

The use of Fourier transform-near infrared (FT-NIR) spectroscopy combined with multivariate pattern recognition techniques was evaluated to address the need for a fast and senisitive method for the detection of bacterial contamination in liquids. The complex cellular composition of bacteria produces FT-NIR vibrational transitions (overtone and combination bands), forming the basis for identification and subtyping. A database including strains of Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Bacillus cereus, and Bacillus thuringiensis was built, with special care taken to optimize sample preparation. The bacterial cells were treated with 70% (vol/vol) ethanolto enhance safe handling of pathogenic strains and then concentrated on an aluminum oxide membrane to obtain a thin bacterial film. This simple membrane filtration procedure generated reproducible FT-NIR spectra that allowed for the rapid discrimination among closely related strains. Principal component analysis and soft independent modeling of class analogy of transformed spectra in the region 5,100 to 4,400 cm(-1) were able to discriminate between bacterial species. Spectroscopic analysis of apple juices inoculated with different strains of E. coli at approximately 10(5) CFU/ml showed that FT-NIR spectralfeatures are consistent with bacterial contamination and soft independent modeling of class analogy correctly predicted the identity of the contaminant as strains of E. coli. FT-NIR in conjunction with multivariate techniques can be used for the rapid and accurate evaluation of potential bacterial contamination in liquids with minimal sample manipulation, and hence limited exposure of the laboratory worker to the agents.

Bacteria↗
PubMed2003

Identification of foodborne bacteria by infrared spectroscopy using cellular fatty acid methyl esters.

Identification of bacterial species by profiling fatty acid methyl esters (FAMEs) has commonly been carried out by using a 20-min capillary gas chromatographic procedure followed by library matching of FAME profiles using commercial MIDI databases and proprietary pattern recognition software. Fast GC (5 min) FAME procedures and mass spectrometric methodologies that require no lipid separation have also been reported. In this study, bacterial identification based on the rapid (2 min) infrared measurement of FAME mixtures was demonstrated. The microorganisms investigated included Gram positive bacteria Staphylococcus aureus, Listeria monocytogenes, Bacillus anthracis, and Bacillus cereus, and Gram negative bacteria from the family Enterobacteriacae: Yersinia enterocolitica, Salmonella typhimurium, Shigella sonnei, and Escherichia coli (four strains of E. coli), and non-Enterobacteriacae: Vibrio cholerae, Vibrio vulnificus, and Vibrio parahemolyticus. Foodborne bacterial mixtures of FAMEs were measured by using an attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopic procedure and discriminated by multivariate analysis. Results showed that the Enterobacteriacae could be discriminated from the vibrios. The identification was at the level of species (for the Bacillus and Vibrio genera) or strains (for the E. coli species). A series of bacterial FAME test samples were prepared and analyzed for accuracy of identification, and all were correctly identified. Our results suggest that this infrared strategy could be used to identify foodborne pathogens.

Fatty Acids↗
PubMed2003

Application of a disposable transparent filtration membrane to the infrared spectroscopic discrimination among bacterial species.

This study describes the application of filtration, infrared spectroscopy, and multivariate analysis to the identification of 10 foodborne bacterial species. The bacteria were applied by filtration to a disposable optical membrane that is transparent to infrared radiation. The filtration step was rapid (2 min). Observed cellular infrared spectra were unique and were used to discriminate among the different species. A dataset for the 10 bacterial species investigated was successfully used to correctly identify unknowns included in the dataset.

Bacteria↗
PubMed2001

Rapid analysis of sugars in fruit juices by FT-NIR spectroscopy.

A simple analytical procedure using FT-NIR and multivariate techniques for the rapid determination of individual sugars in fruit juices was evaluated. Different NIR detection devices and sample preparation methods were tested by using model solutions to determine their analytical performance. Aqueous solutions of sugar mixtures (glucose, fructose, and sucrose; 0-8% w/v) were used to develop a calibration model. Direct measurements were made by transflection using a reflectance accessory, by transmittance using a 0.5-mm cell, and by reflectance using a fiberglass paper filter. FT-NIR spectral data were transformed to the second derivative. Partial least-squares regression (PLSR) was used to create calibration models that were cross-validated (leave-one-out approach). The prediction ability of the models was evaluated on fruit juices and compared with HPLC and standard enzymatic techniques. The PLSR loading spectra showed characteristic absorption bands for the different sugars. Models generated from transmittance spectra gave the best performance with standard error of prediction (SEP) <0.10% and R(2) of 99.9% that accurately and precisely predicted the sugar levels in juices, whereas lower precision was obtained with models generated from reflectance spectra. FT-NIR spectroscopy allowed for the rapid ( approximately 3 min analysis time), accurate and non-destructive analysis of sugars in juices and could be applied in quality control of beverages or to monitor for adulteration or contamination.

Beverages↗
PubMed2001

Rapid detection and identification of bacterial strains by Fourier transform near-infrared spectroscopy.

The use of Fourier transform near-infrared (FT-NIR) spectroscopy and multivariate pattern recognition techniques for the rapid detection and identification of bacterial contamination in liquids was evaluated. The complex biochemical composition of bacteria yields FT-NIR vibrational transitions (overtone and combination bands) that can be used for classification and identification. Bacterial suspensions (Escherichia coli HB101, E. coli ATCC 43888, E. coli 1224, Bacillus amyloliquifaciens, Pseudomonas aeruginosa, Bacillus cereus, and Listeria innocua) were filtered to harvest the cells and eliminate the matrix, which has a strong NIR signal. FT-NIR measurements were done using a diffuse reflection-integrating sphere. Principal component analysis showed tight clustering of the bacterial strains at the information-rich spectral region of 6000-4000 cm(-1). The method reproducibly distinguished between different E. coli isolates and conclusively identified the relationship between a new isolate and one of the test species. This methodology may allow for the rapid assessment of potential bacterial contamination in liquids with minimal sample preparation.

Bacillus↗
PubMed2000

Use of fourier transform near-infrared reflectance spectroscopy for rapid quantification of castor bean meal in a selection of flour-based products.

Methodology was developed and evaluated for the rapid detection of castor bean meal (CBM) containing the toxic protein ricin by using Fourier transform near-infrared (FT-NIR) spectroscopy and multivariate techniques. The method is intended to be a prototype to develop a more general approach to detect food tampering. Measurements were made on an FT-NIR system using a diffuse reflection-integrating sphere. Flours spiked with caffeine, crystalline sugar, and corn meal, 1-20% w/w, were used as test articles to evaluate the methodologies. Food matrices (bleached flour, wheat flour, and blueberry pancake mix) spiked with CBM (0.5-8% w/w) were analyzed. Multiplicative scatter correction transformed partial least-squares regression models, using a specific NIR spectral region, predicted CBM contamination in foods with a standard error of cross-validation of <0.6% and a coefficient of determination (R(2)) of >94%. Models discriminated between flour samples contaminated with CBM and other protein sources (egg white, soybean meal, tofu, and infant formula). CBM had loading spectra with bands characteristic of amide groups (4880 and 4555 cm(-1)) and lipids (5800, 5685, 4340, and 4261 cm(-1)).

Caffeine↗
PubMed1996

Orange juice classification with a biologically based neural network.

Dystal, an artificial neural network, was used to classify orange juice products. Nine varieties of oranges collected from six geographical regions were processed into single-strength, reconstituted or frozen concentrated orange juice. The data set represented 240 authentic and 173 adulterated samples of juices; 16 variables [8 flavone and flavanone glycoside concentrations measured by high-performance liquid chromatography (HPLC) and 8 trace element concentrations measured by inductively coupled plasma spectroscopy] were selected to characterize each juice and were used as input to Dystal. Dystal correctly classified 89.8% of the juices as authentic or adulterated. Classification performance increased monotonically as the percentage of pulpwash in the sample increased. Dystal correctly identified 92.5% of the juices by variety (Valencia vs non-Valencia).

Algorithms↗
PubMed1986

Chiral recognition model for the resolution of ephedrine and related alpha,beta-aminoalcohols as enantiomeric oxazolidine derivatives.

The mechanism of chiral recognition has been investigated for a series of enantiomeric cis-oxazolidines on a commercially available high-performance liquid chromatographic chiral stationary phase (HPLC-CSP). The oxazolidine molecules were synthesized through the condensation of ephedrine and ephedrine-related molecules with aromatic aldehydes. The resulting molecules are rigid five-membered rings whose configuration has been determined by proton magnetic resonance and single-crystal X-ray diffraction. The oxazolidines derived from the condensation of ephedrine and aldehydes containing a pi-basic moiety such as naphthaldehyde were resolved on the HPLC-CSP as were those oxazolidines synthesized by using a pi-acidic aldehyde such as p-nitrobenzaldehyde. However, there was a reversal in the elution order for the two types of oxazolidines. Oxazolidines resulting from the condensation of ephedrine and a pi-neutral aldehyde such as benzaldehyde were not resolved. The results of this study suggest a chiral recognition model based on the formation of diastereomeric solute-CSP complexes through a single attractive interaction and chiral discrimination resulting from the difference in steric fit.

Amino Alcohols↗