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 (∼0.5g) 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 (∼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.     

Discrimination between immature and mature green coffees by attenuated total reflectance and diffuse reflectance Fourier transform infrared spectroscopy

The objective of this work was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) in the characterization and discrimination between immature and mature or ripe coffee beans. Arabica coffee beans were submitted to FTIR analysis by reflectance readings employing attenuated total reflectance (ATR) and diffuse reflectance (DR) accessories. The obtained spectra were similar, but in general higher absorbance values were observed for nondefective beans in comparison to immature ones. Multivariate statistical analysis (principal component analysis, PCA, and agglomerative hierarchical clustering, AHC) was performed in order to verify the possibility of discrimination between immature and mature coffee samples. A clear separation between immature and mature coffees was observed based on AHC and PCA analyses of the normalized spectra obtained by employing both ATR and DR accessories. Linear discriminant analysis was employed for developing classification models, with recognition and prediction abilities of 100%. Such results showed that FTIR analysis presents potential for the development of a simple routine methodology for separation of immature and mature coffee beans. Practical Application: The ultimate goal of this research is to be able to propose improvements in the way immature coffee beans are separated from graded mature beans in coffee facilities (cooperatives and other coffee producer's associations). The results obtained herein point toward FTIR as a potential tool for the aimed improvements.     

The determination of frying oil quality using Fourier transform infrared attenuated total reflectance

The possibility of using the whole spectra (wave numbers between 4000 and 850 cm⁻¹) from Fourier transform infrared attenuated total reflectance spectroscopy (FTIR-ATR) to differentiate between good, marginal and unacceptable oils with regard to various intensities of oil rancidity was investigated. Fresh, used, and discarded oils were collected from several fast food restaurants from each frying cycle for 4 weeks. Dielectric constant, peroxide value, free fatty acid content, and density of oil samples significantly (P<0.01) increased with frying time. The correlation (r) between FTIR absorbance at 3300 cm⁻¹ and free fatty acid content was from 0.84 to 0.94 for oils from the three restaurants. Similarly, the correlation between FTIR absorbance at 3471 cm⁻¹ and peroxide value was from 0.90 to 0.97. The results of principal component analysis using the whole spectra (4000-850 cm⁻¹) showed good discrimination and stability for identification between acceptable, marginal and unacceptable frying oils.     

Quantitative determination of fatty acid compositions in micro-encapsulated fish-oil supplements using Fourier transform infrared (FTIR) spectroscopy

The research describes a rapid method for the determination of fatty acid (FA) contents in a micro-encapsulated fish-oil (μEFO) supplement by using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic technique and partial least square regression (PLSR) analysis. Using the ATR-FTIR technique, the μEFO powder samples can be directly analysed without any pre-treatment required, and our developed PLSR strategic approach based on the acquired spectral data led to production of a good linear calibration with R(2)=0.99. In addition, the subsequent predictions acquired from an independent validation set for the target FA compositions (i.e., total oil, total omega-3 fatty acids, EPA and DHA) were highly accurate when compared to the actual values obtained from standard GC-based technique, with plots between predicted versus actual values resulting in excellent linear fitting (R(2)≥0.96) in all cases. The study therefore demonstrated not only the substantial advantage of the ATR-FTIR technique in terms of rapidness and cost effectiveness, but also its potential application as a rapid, potentially automated, online monitoring technique for the routine analysis of FA composition in industrial processes when used together with the multivariate data analysis modelling.     

Differentiation of Greek red wines on the basis of grape variety using attenuated total reflectance Fourier transform infrared spectroscopy

Mid-infrared spectroscopy combined with appropriate software was used in an attempt to differentiate Greek red wines of different varietals origin, including the cultivars Agiorgitiko (Nemea-Peloponnesus), Xinomavro (Naousa-Central Macedonia) and Merlot from Greece. Extract of wine phenolic components were investigated by attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy. The wine extracts were obtained by solid-phase extraction with C-18 columns and elution by methanol containing 0.01% hydrochloric acid. Libraries of spectra were created using sample from each wine variety. Spectra of unknown wine extracts were recorded and compared with those of the wine libraries and the rate of affinity (the match value) was measured automatically using the appropriate software (OMNIC ver. 7.3). The spectral region 1800–900 cm⁻¹ was used to ‘fingerprint’ wine on the basis of grape variety. This simple and fast method of analysis showed that wines from different grape varieties can be differentiated between them.     

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 (∼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.     

Identification and differentiation of goat and sheep milk based on diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) using cluster analysis

A new methodology for identification and differentiation of goat and sheep milk was developed based on FT-IR spectroscopy using hierarchical and discriminant analysis. Forty-nine goat and 38 sheep defatted and freeze-dried Greek milk samples were analyzed. FT-IR spectra were obtained in the diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) mode. The spectral region 1840–950 cm⁻¹ was used to ‘fingerprint’ milk types. Main peak used for differentiation of goat/sheep milk is located at 1745 cm⁻¹, which is correlated to the degree of sugars carboxyl methyl esterification. Hierarchical and discriminant analyses were based on the absorptions of the above spectral region. These analyses showed that the samples of goat milk can be differentiated from the samples of sheep’s.     

Analysis of pork adulteration in beef meatball using Fourier transform infrared (FTIR) spectroscopy

Meatball is one of the favorite foods in Indonesia. The adulteration of pork in beef meatball is frequently occurring. This study was aimed to develop a fast and non destructive technique for the detection and quantification of pork in beef meatball using Fourier transform infrared (FTIR) spectroscopy and partial least square (PLS) calibration. The spectral bands associated with pork fat (PF), beef fat (BF), and their mixtures in meatball formulation were scanned, interpreted, and identified by relating them to those spectroscopically representative to pure PF and BF. For quantitative analysis, PLS regression was used to develop a calibration model at the selected fingerprint regions of 1200-1000 cm(-1). The equation obtained for the relationship between actual PF value and FTIR predicted values in PLS calibration model was y = 0.999x + 0.004, with coefficient of determination (R(2)) and root mean square error of calibration are 0.999 and 0.442, respectively. The PLS calibration model was subsequently used for the prediction of independent samples using laboratory made meatball samples containing the mixtures of BF and PF. Using 4 principal components, root mean square error of prediction is 0.742. The results showed that FTIR spectroscopy can be used for the detection and quantification of pork in beef meatball formulation for Halal verification purposes.     

Characterization of Pinus pinaster bark and its alkaline extracts by diffuse reflectance Fourier transform infrared (DRIFT) spectroscopy

bark and of the raffinates obtained after an alkaline extraction, and also the Stiasny number of the corresponding extracts. By means of a stepwise regression analysis a selection of the DRIFT spectra bands which allow to correlate satisfactorily the experimental results has been made.     

Characterization of Pinus pinaster bark and its alkaline extracts by diffuse reflectance Fourier transform infrared (DRIFT) spectroscopy

Pinus pinaster bark and of the raffinates obtained after an alkaline extraction, and also the Stiasny number of the corresponding extracts. By means of a stepwise regression analysis a selection of the DRIFT spectra bands which allow to correlate satisfactorily the experimental results has been made.

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Discrimination of Alicyclobacillus strains using nitrocellulose membrane filter and attenuated total reflectance fourier transform infrared spectroscopy

Alicyclobacillus spp. are thermoacidophilic, spore-forming bacteria, some of which cause spoilage in pasteurized and heat-treated apple juice products through the production of guaiacol. It would be helpful if a rapid method to detect and discriminate Alicyclobacillus strains was available. A simple and rapid sample preparation method using nitrocellulose membrane filter (NMF) and a single reflection horizontal attenuated total reflection (HATR) accessory with Fourier transform infrared (FT-IR) was developed here. Fourier transform infrared (FT-IR) spectroscopy was used and tested on 8 Alicyclobacillus strains (KF, WAC, NWN-13501, NWN-12697, NWN-12654, NWN-10682, 1016, 1101). A linear discriminant analysis (LDA) was established to discriminate Alicyclobacillus strains. The sample preparation method could successfully separated strains into different groups by principal component analysis (PCA). High identification accuracy (95%) was achieved with the LDA model. PRACTICAL APPLICATION: The method developed in the paper can be used to discriminate different Alicyclobacillus strains from each other making it possible to easily determine whether the strain of Alicyclobacillus present is associated with juice spoilage.     

Discrimination between defective and non-defective roasted coffees by diffuse reflectance infrared Fourier transform spectroscopy

The objective of this work was to evaluate the feasibility of employing Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) for discrimination between defective and non-defective coffees after roasting and grinding. Defective (black, immature and sour) and non-defective Arabica coffee beans were submitted to light, medium and dark roasts at 220, 235 and 250 °C. Principal Components Analysis of the DRIFTS spectra (normalized or not) and of the first derivatives of the spectra provided separation of the samples into four groups: non-defective, black, dark sour and light sour, with immature beans scattered among the sour samples. Classification models were developed based on Linear Discriminant Analysis and recognition and prediction abilities of these models ranged from 95 to 100%. Such results indicate that DRIFTS presents potential for the development of a fast and reliable analytical methodology for discrimination between defective and non-defective coffee after roasting and grinding.     

A chemometric approach for the quantification of free fatty acids in cottonseed oil by Fourier transform infrared spectroscopy

The aim of this study was to quantify free fatty acid in cottonseed oil (Gossypium) variety by a chemometric approach using Fourier transform infrared spectroscopy. Calibration standards were prepared by gravimetrical mixing of oleic acid (0.1–40 g/100 g) in neutralized cottonseed oil containing <0.1% free fatty acids. Fourier transform infrared technique coupled with partial least square and principle component regression models were used to develop calibrations in the specific absorption region of carbonyl between 1690–1727 cm^?1. On the basis of regression coefficient and evaluated free fatty acids results with comparison to titration method, partial least square was found to be more accurate than principle component regression calibration model. All the analyzed cottonseed oil varieties showed high content of free fatty acids in the range of 17.1–38.5%. The results of the present study indicated that Fourier transform infrared method in combination with partial least square or principle component regression could be used as a greener alternative to the standard titration method.     

Determination of polygalacturonic acid content in pectin extracts by diffuse reflectance Fourier transform infrared spectroscopy

A simple, rapid diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) method was developed for pectin measurement. Pectin calibration standards were prepared by blending polygalacturonic acid with potassium bromide to cover a range of polygalacturonic acid concentrations (10–98%). A linear relationship between pectin content and total carbonyl absorption band area was found (R²=0.982). Linearity was up to 80% pectin, since there was no significant difference in peak areas of 80% and greater. Pectin contents of various commercial pectin samples were calculated from the linear fit equation. Accuracy of the DRIFTS method was determined by comparing the pectin contents to the values obtained by colorimetric and HPLC methods. For four different sources of samples, the pectin contents by FTIR method were 78.2, 89.4, 65.9 and 67.1%, which were comparable to values obtained by colorimetric analysis (79.1, 87.9, 64.7 and 57.7%) and HPLC (84.1, 91.4, 69.5 and 67.9%).     

Rapid discrimination of Alicyclobacillus strains in apple juice by Fourier transform infrared spectroscopy

Alicyclobacillus spp. are thermoacidophilic, spore-forming bacteria. Some of which cause spoilage in pasteurized and heat-treated apple juice products through the production of guaiacol. Fourier transform infrared (FT-IR) spectroscopy was used to discriminate between eight Alicyclobacillus strains (WAC, 81-2, Oly#21, 51-1, KF, 1016, 1101, and A-Gala A4) in apple juice. FT-IR vibrational combination bands reflected compositional differences in the cell membranes of Alicyclobacillus strains in the "fingerprint region" at wavenumbers between 1500 and 800 cm(-1). Distinctive segregation among spectral sample clusters of different Alicyclobacillus strains was observed using principal component analysis (PCA). Two closely related strains (1016 and 1101) of Alicyclobacillus acidoterrestris could be distinguished, suggesting that this method can be highly selective. Results of soft independent modeling of class analogy (SIMCA) demonstrated that guaiacol-producing and non-guaiacol producing Alicyclobacillus strains could be differentiated up to 89% of the time. This technique may provide a tool for fruit juice producers to detect Alicyclobacillus rapidly and to monitor and control guaiacol formation.     

Determination of fatty acid composition of pork fat by Fourier transform infrared spectroscopy

The fatty acid composition of pork fat determines its processing quality. FTIR spectroscopic methods were evaluated on pork back and breast fat, directly on fat slices and on the fat extracts. Near infrared transmission and middle infrared using an ATR method were developed to determine the fatty acid content in the fat extracts. The results obtained with 80 back and 80 breast samples showed the validity of infrared spectroscopy to estimate SFA (saturated fatty acids), MUFA (monounsaturated fatty acids), PUFA (polyunsaturated fatty acids), C16:0, C18:0, C18:1 and C18:2 contents in fat extracts. Correlation coefficients (R(2)) were around 0.91 and 0.98 for MIR (ATR) and around 0.85 and 0.96 for NIR (transmission). Direct measurements on fat slices by NIR predicted SFA, PUFA, C18:1 and C18:2, although the coefficient correlations were less good; 0.69-0.79. This method though, is easier and faster than other techniques and is accurate enough to discriminate fat samples separated by standard visual and texture classification. Measurements could be made in 1 min.     

Analysis of lard in meatball broth using Fourier transform infrared spectroscopy and chemometrics

Meatball is one of the favorite foods in Indonesia. For the economic reason (due to the price difference), the substitution of beef meat with pork can occur. In this study, FTIR spectroscopy in combination with chemometrics of partial least square (PLS) and principal component analysis (PCA) was used for analysis of pork fat (lard) in meatball broth. Lard in meatball broth was quantitatively determined at wavenumber region of 1018–1284 cm^− 1. The coefficient of determination (R²) and root mean square error of calibration (RMSEC) values obtained were 0.9975 and 1.34% (v/v), respectively. Furthermore, the classification of lard and beef fat in meatball broth as well as in commercial samples was performed at wavenumber region of 1200–1000 cm^− 1. The results showed that FTIR spectroscopy coupled with chemometrics can be used for quantitative analysis and classification of lard in meatball broth for Halal verification studies. The developed method is simple in operation, rapid and not involving extensive sample preparation.