Short communication: Effect of storage temperature on the solubility of milk protein concentrate 80 (MPC80) treated with NaCl or KCl.

A previous study in our laboratory showed that addition of 150 mM NaCl or KCl into diafiltration water improved the solubility of freshly made milk protein concentrate 80 (MPC80). In the present study, the objectives were (1) to evaluate the solubility of NaCl- or KCl-treated MPC80 samples kept at varying temperatures and then stored for extensive periods at room temperature (21 °C ± 1 °C); and (2) to determine if MPC80 samples stored at different temperatures and protein conformation can be grouped or categorized together. Freshly manufactured MPC80 samples were untreated (control), processed with NaCl, or processed with KCl. One set of sample bags was stored at 4 °C; second and third sets of bags were kept at 25 °C and 55 °C for 1 mo (31 d) and then transferred to room temperature (21 °C ± 1 °C) storage conditions for 1 yr (365 d). Samples were tested for nitrogen solubility index (NSI) and for protein changes by Fourier-transform infrared (FTIR) spectroscopy. Analysis of variance results for NSI showed 2 significantly different groupings of MPC80 samples. The more soluble group contained samples treated with NaCl or KCl and stored at either 4 °C or 25 °C. These samples had mean NSI >97.5%. The less soluble groups contained all control samples, regardless of storage temperature, and NaCl- or KCl-treated samples stored at 55 °C. These samples had mean NSI from 39.5 to 58%. Within each of these groups (more soluble and less soluble), no significant differences in solubility were detected. Pattern recognition analysis by soft independent modeling of class analogy (SIMCA) was used to assess protein changes during storage by monitoring the amide I and amide II (1,700(-1) to 1,300 cm(-1)) regions. Dominant bands were observed at 1,385 cm(-1) for control, 1,551 cm(-1) for KCl-treated samples, and 1,694 cm(-1) for NaCl-treated samples. Moreover, SIMCA clustered the MPC80 samples stored at 4 °C separately from samples stored at 25 °C and 55 °C. This study demonstrates that (1) the addition of NaCl or KCl during MPC80 manufacture reduces the deleterious changes in solubility upon prolonged storage at 4 °C or 25 °C, and (2) the solubility of samples stored at 55 °C is poor irrespective of salt treatment.

Rapid detection and quantification of milk adulteration using infrared microspectroscopy and chemometrics analysis.

The application of attenuated total reflectance mid-infrared microspectroscopy (MIR-microspectroscopy) was evaluated as a rapid method for detection and quantification of milk adulteration. Milk samples were purchased from local grocery stores (Columbus, OH, USA) and spiked at different concentrations of whey, hydrogen peroxide, synthetic urine, urea and synthetic milk. Samples were place on a 192-well microarray slide, air-dried and spectra were collected by using MIR-microspectroscopy. Pattern recognition analysis by Soft Independent Modeling of Class Analogy (SIMCA) showed tight and well-separated clusters allowing discrimination of control samples from adulterated milk. Partial Least Squares Regression (PLSR) showed standard error of prediction (SEP) ~2.33, 0.06, 0.41, 0.30 and 0.014 g/L for estimation of levels of adulteration with whey, synthetic milk, synthetic urine, urea and hydrogen peroxide, respectively. Results showed that MIR-microspectroscopy can provide an alternative methodology to the dairy industry for screening potential fraudulent practice for economic adulteration of cow's milk.

Use of FTIR for rapid authentication and detection of adulteration of food.

Fourier transform infrared (FTIR) spectroscopy is an appealing technology for the food industry because simple, rapid, and nondestructive measurements of chemical and physical components can be obtained. Advances in FTIR instrumentation combined with the development of powerful multivariate data analysis methods make this technology ideal for large volume, rapid screening and characterization of minor food components down to parts per billion (ppb) levels. Because of the use of FTIR techniques in quality and process control applications, the food industry is already familiar with the technology and its potential to expand to monitoring for food adulteration. The aim of this review is to compile the current research on applications of near infrared (NIR) and mid-infrared (MIR) spectroscopy for rapid authentication and detection of adulteration in food.

Solubility of commercial milk protein concentrates and milk protein isolates.

High-protein milk protein concentrate (MPC) and milk protein isolate (MPI) powders may have lower solubility than low-protein MPC powders, but information is limited on MPC solubility. Our objectives in this study were to (1) characterize the solubility of commercially available powder types with differing protein contents such as MPC40, MPC80, and MPI obtained from various manufacturers (sources), and (2) determine if such differences could be associated with differences in mineral, protein composition, and conformational changes of the powders. To examine possible predictors of solubility as measured by percent suspension stability (%SS), mineral analysis, Fourier transform infrared (FTIR) spectroscopy, and quantitative protein analysis by HPLC was performed. After accounting for overall differences between powder types, %SS was found to be strongly associated with the calcium, magnesium, phosphorus, and sodium content of the powders. The FTIR score plots were in agreement with %SS results. A principal component analysis of FTIR spectra clustered the highly soluble MPC40 separately from the rest of samples. Furthermore, 2 highly soluble MPI samples were clustered separately from the rest of the MPC80 and MPI samples. We found that the 900 to 1,200 cm⁻¹ region exhibited the highest discriminating power, with dominant bands at 1,173 and 968 cm⁻¹, associated with phosphate vibrations. The 2 highly soluble MPI powders were observed to have lower κ-casein and α-(S1)-casein contents and slightly higher whey protein contents than the other powders. The differences in the solubility of MPC and MPI were associated with a difference in mineral composition, which may be attributed to differences in processing conditions. Additional studies on the role of minerals composition on MPC80 solubility are warranted. Such a study would provide a greater understanding of factors associated with differences in solubility and can provide insight on methods to improve solubility of high-protein milk protein concentrates.

Quality of shell eggs pasteurized with heat or heat-ozone combination during extended storage.

The physical quality and functionality of shell eggs, pasteurized with heat or a combination of heat and ozone, were assessed during eight weeks of storage at 4 or 25 °C. Shell eggs were treated as follows: (1) immersion heating that mimics commercial pasteurization processes (egg internal temperature of 56 ± 0.1 °C for 32 min), or (2) a newly developed combination process comprised of heating (56 ± 0.1 °C, internal, for 10 min) followed by gaseous ozone treatment. Eggs were tested for yolk index, Haugh units, albumen pH, albumen turbidity, and percent overrun. Additionally, albumen samples were assayed for lysozyme activity and free sulfhydryl group content, and were analyzed using differential scanning calorimetry and Fourier transform infrared (FTIR) spectroscopy. Both processed and unprocessed eggs maintained superior quality when stored at 4 °C, as opposed to 25 °C. Pasteurization, regardless of method, led to superior maintenance of Haugh units during storage but also increased albumen opacity and decreased albumen overrun. Detrimental effects on quality markers were more severe in heat-pasteurized eggs than those treated with the ozone-based process. Pasteurization of shell eggs by either process did not affect lysozyme activity or sulfhydryl group content. Changes in protein secondary structure, as indicated by FTIR analysis, suggest that the ozone-based process is less damaging to albumen proteins than is the heat-alone process. In conclusion, heat-ozone pasteurization, by virtue of its less severe heat treatment, yields a safe final product that more closely resembles untreated shell eggs.

Rapid profiling of Swiss cheese by attenuated total reflectance (ATR) infrared spectroscopy and descriptive sensory analysis.

The acceptability of cheese depends largely on the flavor formed during ripening. The flavor profiles of cheeses are complex and region- or manufacturer-specific which have made it challenging to understand the chemistry of flavor development and its correlation with sensory properties. Infrared spectroscopy is an attractive technology for the rapid, sensitive, and high-throughput analysis of foods, providing information related to its composition and conformation of food components from the spectra. Our objectives were to establish infrared spectral profiles to discriminate Swiss cheeses produced by different manufacturers in the United States and to develop predictive models for determination of sensory attributes based on infrared spectra. Fifteen samples from 3 Swiss cheese manufacturers were received and analyzed using attenuated total reflectance infrared spectroscopy (ATR-IR). The spectra were analyzed using soft independent modeling of class analogy (SIMCA) to build a classification model. The cheeses were profiled by a trained sensory panel using descriptive sensory analysis. The relationship between the descriptive sensory scores and ATR-IR spectra was assessed using partial least square regression (PLSR) analysis. SIMCA discriminated the Swiss cheeses based on manufacturer and production region. PLSR analysis generated prediction models with correlation coefficients of validation (rVal) between 0.69 and 0.96 with standard error of cross-validation (SECV) ranging from 0.04 to 0.29. Implementation of rapid infrared analysis by the Swiss cheese industry would help to streamline quality assurance.

Application of infrared microspectroscopy and multivariate analysis for monitoring the effect of adjunct cultures during Swiss cheese ripening.

Improved cheese flavor has been attributed to the addition of adjunct cultures, which provide certain key enzymes for proteolysis and affect the dynamics of starter and nonstarter cultures. Infrared microspectroscopy provides unique fingerprint-like spectra for cheese samples and allows for rapid monitoring of cheese composition during ripening. The objective was to use infrared microspectroscopy and multivariate analysis to evaluate the effect of adjunct cultures on Swiss cheeses during ripening. Swiss cheeses, manufactured using a commercial starter culture combination and 1 of 3 adjunct Lactobacillus spp., were evaluated at d 1, 6, 30, 60, and 90 of ripening. Cheese samples (approximately 20 g) were powdered with liquid nitrogen and homogenized using water and organic solvents, and the water-soluble components were separated. A 3-microL aliquot of the extract was applied onto a reflective microscope slide, vacuum-dried, and analyzed by infrared microspectroscopy. The infrared spectra (900 to 1,800 cm(-1)) produced specific absorption profiles that allowed for discrimination among different cheese samples. Cheeses manufactured with adjunct cultures showed more uniform and consistent spectral profiles, leading to the formation of tight clusters by pattern-recognition analysis (soft independent modeling of class analogy) as compared with cheeses with no adjuncts, which exhibited more spectral variability among replicated samples. In addition, the soft independent modeling of class analogy discriminating power indicated that cheeses were differentiated predominantly based on the band at 1,122 cm(-1), which was associated with S-O vibrations. The greatest changes in the chemical profile of each cheese occurred between d 6 and 30 of warm-room ripening. The band at 1,412 cm(-1), which was associated with acidic AA, had the greatest contribution to differentiation, indicating substantial changes in levels of proteolysis during warm-room ripening in addition to propionic acid, acetic acid, and eye formation. A high-throughput infrared microspectroscopy technique was developed that can further the understanding of biochemical changes occurring during the ripening process and provide insight into the role of adjunct nonstarter lactic acid bacteria on the complex process of flavor development in cheeses.

Rapid prediction of composition and flavor quality of cheddar cheese using ATR-FTIR spectroscopy.

Multiple methods are required for analysis of cheese flavor quality and composition. Chromatography and sensory analyses are accurate but laborious, expensive, and time consuming. A rapid and simple instrumental method based on Fourier transform infrared (FTIR) spectroscopy was developed for simultaneous analysis of Cheddar cheese composition and flavor quality. Twelve different Cheddar cheese samples ripened for 67 d were obtained from a commercial cheese manufacturer along with their moisture, pH, salt, fat content, and sensory flavor quality data. Water-soluble components were extracted from the cheese, dried on zinc selenide FTIR crystal and scanned (4000 to 700 cm(-1)). Infrared spectra of the samples were correlated with their composition and flavor quality data to develop multivariate statistical regression and classification models. The models were validated using an independent set of ten 67-d-old test samples. The infrared spectra of the samples were well defined, highly consistent within each sample and distinct from other samples. The regression models showed excellent fit (r > 0.92) and could accurately determine moisture, pH, salt, and fat contents as well as the flavor quality rating in less than 20 min. Furthermore, cheeses could also be classified based on their flavor quality (slight acid, whey taint, good cheddar, and so on). The discrimination of the samples was due to organic acids, amino acids, and short chain fatty acids (1800 to 900 cm(-1)), which are known to contribute significantly to cheese flavor. The results show that this technique can be a rapid, inexpensive, and simple tool for predicting composition and flavor quality of cheese.

Cheddar cheese classification based on flavor quality using a novel extraction method and Fourier transform infrared spectroscopy.

Analysis of Cheddar cheese flavor using trained sensory and grading panels is expensive and time consuming. A rapid and simple solvent extraction procedure in combination with Fourier transform infrared spectroscopy was developed for classifying Cheddar cheese based on flavor quality. Fifteen Cheddar cheese samples from 2 commercial production plants were ground into powders using liquid nitrogen. The water-soluble compounds from the cheese powder, without interfering compounds such as fat and protein, were extracted using water, chloroform, and ethanol. Aliquots (10 microL) of the extract were placed on a zinc selenide crystal, vacuum dried, and scanned in the mid-infrared region (4,000 to 700 cm(-1)). The infrared spectra were analyzed by soft independent modeling of class analogy (SIMCA) for pattern recognition. Sensory flavor quality of these cheeses was determined by trained quality assurance personnel in the production facilities. The SIMCA models provided 3-dimensional classification plots in which all the 15 cheese samples formed well-separated clusters. The orientation of the clusters in 3-dimensional space correlated well with their cheese flavor characteristics (fermented, unclean, low flavor, sour, good Cheddar, and so on). The discrimination of the samples in the SIMCA plot was mainly due to organic acids, fatty acids and their esters, and amino acids (1,450 to 1,350 and 1,200 to 990 cm(-1)), which are known to contribute significantly to cheese flavor. The total analysis time, including the sample preparation time, was less than 20 min per sample. This technique can be a rapid, inexpensive, and simple tool to the cheese industry for predicting the flavor quality of cheese.

Application of Fourier transform infrared spectroscopy for monitoring short-chain free fatty acids in Swiss cheese.

Short-chain free fatty acids (FFA) are important sources of cheese flavor and have been reported to be indicators for assessing quality. The objective of this research was to develop a simple and rapid screening tool for monitoring the short-chain FFA contents in Swiss cheese by using Fourier transform infrared spectroscopy (FTIR). Forty-four Swiss cheese samples were evaluated by using a MIRacle three-reflection diamond attenuated total reflectance (ATR) accessory. Two different sampling techniques were used for FTIR/ATR measurement: direct measurement of Swiss cheese slices (approximately 0.5 g) and measurement of a water-soluble fraction of cheese. The amounts of FFA (propionic, acetic, and butyric acids) in the water-soluble fraction of samples were analyzed by gas chromatography-flame ion-ization detection as a reference method. Calibration models for both direct measurement and the water-soluble fraction of cheese were developed based on a cross-validated (leave-one-out approach) partial least squares regression by using the regions of 3,000 to 2,800, 1,775 to 1,680, and 1,500 to 900 cm(-1) for short-chain FFA in cheese. Promising performance statistics were obtained for the calibration models of both direct measurement and the water-soluble fraction, with improved performance statistics obtained from the water-soluble extract, particularly for propionic acid. Partial least squares models generated from FTIR/ATR spectra by direct measurement of cheeses gave standard errors of cross-validation of 9.7 mg/100 g of cheese for propionic acid, 9.3 mg/100 g of cheese for acetic acid, and 5.5 mg/100 g of cheese for butyric acid, and correlation coefficients >0.9. Standard error of cross-validation values for the water-soluble fraction were 4.4 mg/100 g of cheese for propionic acid, 9.2 mg/100 g of cheese for acetic acid, and 5.2 mg/100 g of cheese for butyric acid with correlation coefficients of 0.98, 0.95, and 0.92, respectively. Infrared spectroscopy and chemometrics accurately and precisely predicted the short-chain FFA content in Swiss cheeses and in the water-soluble fraction of the cheese.

Rapid determination of Swiss cheese composition by Fourier transform infrared/attenuated total reflectance spectroscopy.

There is a need for rapid and simple techniques that can be used to predict the quality of cheese. The aim of this research was to develop a simple and rapid screening tool for monitoring Swiss cheese composition by using Fourier transform infrared spectroscopy. Twenty Swiss cheese samples from different manufacturers and degree of maturity were evaluated. Direct measurements of Swiss cheese slices (approximately 0.5 g) were made using a MIRacle 3-reflection diamond attenuated total reflectance (ATR) accessory. Reference methods for moisture (vacuum oven), protein content (Kjeldahl), and fat (Babcock) were used. Calibration models were developed based on a cross-validated (leave-one-out approach) partial least squares regression. The information-rich infrared spectral range for Swiss cheese samples was from 3,000 to 2,800 cm(-1) and 1,800 to 900 cm(-1). The performance statistics for cross-validated models gave estimates for standard error of cross-validation of 0.45, 0.25, and 0.21% for moisture, protein, and fat respectively, and correlation coefficients r > 0.96. Furthermore, the ATR infrared protocol allowed for the classification of cheeses according to manufacturer and aging based on unique spectral information, especially of carbonyl groups, probably due to their distinctive lipid composition. Attenuated total reflectance infrared spectroscopy allowed for the rapid (approximately 3-min analysis time) and accurate analysis of the composition of Swiss cheese. This technique could contribute to the development of simple and rapid protocols for monitoring complex biochemical changes, and predicting the final quality of the cheese.

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.

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.

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.

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)).

Molar absorptivity and color characteristics of acylated and non-acylated pelargonidin-based anthocyanins.

The effects of glycosylation and acylation on the spectral characteristics, molar absorptivity, and color attributes of purified acylated and non-acylated pelargonidin derivatives were compared. Pigments were obtained from strawberries, radishes, red-fleshed potatoes, and partially hydrolyzed radish pigments. Individual pigments were isolated by using semipreparative HPLC. Spectral and color (CIELch) attributes of purified pigments were measured. Molar absorptivity ranged from 15 600 to 39 590 for pelargonidin-3-glucoside (pg-3-glu) and pg-3-rutinoside-5-glucoside acylated with p-coumaric acid, respectively. The presence of cinnamic acid acylation had a considerable impact on spectral and color characteristics, causing a bathochromic shift of lambda(max). Sugar substitution also played an important role, with a hypsochromic shift caused by the presence of glycosylation. Pg-3, 5-diglu and pg-3,5-triglu possessed a higher hue angle (>40 degrees ) than the other pg derivatives at pH 1.0, corresponding to the yellow-orange region of the color solid. Acylation with malonic acid did not affect lambda(max) and showed little effect on color characteristics. The solvent system had an effect not only on the molar absorptivity, but also on the visual color characteristic of the pigments.

Electrospray and tandem mass spectroscopy as tools for anthocyanin characterization.

The utility of electrospray and tandem mass spectroscopy (ES-MS and MS-MS) in anthocyanin characterization was tested using different anthocyanin extracts. Anthocyanins were semipurified by using a C-18 resin, washed with acidified water followed by ethyl acetate, and recovered with acidified methanol. Samples were directly injected into a mass spectrometer in either aqueous or methanolic solutions. The positive charge of anthocyanins favored fast and effective ES-MS detection of intact molecular ions. Little interference from other compounds was observed when the ethyl acetate cleaning procedure was used. Tandem mass spectroscopy provided clear and characteristic fragmentation patterns. The voltage used affected only the proportions at which these fragments were present. ES-MS may be used as a fast procedure for identification of anthocyanins, requiring minimal sample preparation. In combination with HPLC, ES-MS and MS-MS could be very powerful tools for anthocyanin characterization and monitoring the authenticity of anthocyanin-containing fruit juices and vegetable extracts.