Identification of pork in beef meatballs using Fourier transform infrared spectrophotometry and real-time polymerase chain reaction

A study on development of Fourier-transform infrared spectrophotometric method combined with principle component analysis as well as real-time polymerase chain reaction for determination of pork–beef mixture in meatballs has been performed. A lipid component extracted from pork and beef in meatballs is analyzed using Fourier-transform infrared spectroscopy, while DNA extracted from meatball was analyzed using real-time polymerase chain reaction. The correlation between actual and predicted concentration of lard using Fourier-transform infrared spectroscopy was performed by aid of partial least squares, while grouping of lard and beef fat components in meatball was carried out by Fourier-transform infrared spectra coupled with principle component analysis. The results showed that Fourier-transform infrared spectra at wavenumbers of 1000–1200 cm^?1 coupled with partial least square and principle component analysis are successfully used for quantification and classification of pork in beef meatballs. The relationship between actual value and predicted value of lard (lipid fraction obtained from meatballs containing pork) with Fourier-transform infrared spectrophotometric method revealed good correlation, with coefficient determination (R²) value of 0.997 and standard error of calibration of 0.04%. Principle component analysis is able to classify samples containing pork and beef meatballs. Fourier-transform infrared spectroscopy using normal spectra is fast technique for identification and quantification of lard extracted from pork in meatball. In addition, real-time polymerase chain reaction using Leptin Primer–AJ 865080 can be used for amplification of pork DNA specifically in meatballs containing pork.     

Use of Fourier Transform Infrared (FTIR) Spectroscopy and Chemometrics for Analysis of Lard Adulteration in “Rambak” Crackers

“Rambak” crackers are one of the traditional foods consumed among Indonesian people made from various kinds of animal skin. The present study highlights the analysis of lard obtained from extraction of “rambak” crackers using Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of partial least square and principle component analysis. FTIR spectroscopy at wavenumber regions of 1200–1000 cm^–1 was successfully used for quantification and classification of lard in “rambak” crackers. The relationship between actual value of lard and Fourier transform infrared predicted value has R² value of 0.946 with low errors in calibration and validation models. Furthermore, the chemometrics principle component analysis can be successfully used for determination of pig skin through analysis of lard in commercial “rambak” crackers. The developed method (FTIR spectroscopy coupled with chemometrics) is rapid and reliable for quantification and classification of lard in “rambak” crackers.     

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.     

The use of Fourier transform mid infrared (FT-MIR) spectroscopy for detection and quantification of adulteration in virgin coconut oil

Currently, the authentication of virgin coconut oil (VCO) has become very important due to the possible adulteration of VCO with cheaper plant oils such as corn (CO) and sunflower (SFO) oils. Methods involving Fourier transform mid infrared (FT-MIR) spectroscopy combined with chemometrics techniques (partial least square (PLS) and discriminant analysis (DA)) were developed for quantification and classification of CO and SFO in VCO. MIR spectra of oil samples were recorded at frequency regions of 4000–650 cm⁻¹ on horizontal attenuated total reflectance (HATR) attachment of FTIR. DA can successfully classify VCO and that adulterated with CO and SFO using 10 principal components. Furthermore, PLS model correlates the actual and FTIR estimated values of oil adulterants (CO and SFO) with coefficient of determination (R²) of 0.999.     

Determination of Chinese honey adulterated with high fructose corn syrup by near infrared spectroscopy

The use of fibre optic diffuse reflectance near infrared spectroscopy (NIR) in combination with chemometric techniques has been investigated to discriminate authenticity of honey. NIR spectra of unadulterated honey and adulterated honey samples with high fructose corn syrup were registered within 10,000–4000 cm⁻¹ spectral region. Discriminant partial least squares (DPLS) models were constructed to distinguish between unadulterated honey and adulterated honey samples and main bands responsible for the discrimination of samples are in the range of 6000–10,000 cm⁻¹. For these models, the correct classification rate for calibration samples were above 90%. Hundred percentage of unadulterated honey and 95% of adulterated honey samples from test set were correctly classified after appropriate preprocessing of first derivative, 13 smoothing points, followed by mean centering pre-treatment and eight model factors, respectively. Our results showed that NIR spectroscopy data with chemometrics techniques can be applied to rapid detecting honey adulteration with high fructose corn syrup.     

Simultaneous determination of pyruvate and acetate levels in xanthan biopolymer by infrared spectroscopy: effect of spectral pre-processing for solid-state analysis

A rapid, direct, and reagent-free procedure based on solid-state Fourier transform infrared spectroscopy (FT-IR) coupled with partial least squares (PLS) data analysis has been developed for simultaneous determination of pyruvate and acetate levels in a microbial xanthan biopolymer. The influences of various spectral pre-processing procedures were studied in order to eliminate effects caused by sample preparation. It was determined that the combination of first derivative and orthogonal signal correction pre-processing contributes to a significant increase in the predictive performance of PLS-1 regression models. By employing the wavenumber region 1320–1350 cm⁻¹ for pyruvate determination and 1500–1600 cm⁻¹ for acetate determination, the root mean square error of cross-validation (RMSECV) for pyruvate and acetate contents were obtained 0.13% and 0.29% w/w, respectively. Results of the proposed procedure for different real samples and those obtained by their reference methods were compared.     

Meat species identification and Halal authentication using PCR analysis of raw and cooked traditional Turkish foods

The method performance characteristics of commercially available PCR kits for animal species identification were established. Comminuted meat products containing different levels of pork were prepared from authentic beef, chicken, and turkey. These meat products were analysed in the raw state and after cooking for 20 min at 200 °C. For both raw and cooked meats, the PCR kit could correctly identify the animal species and could reliably detect the addition of pork at a level below 0.1%. A survey of 42 Turkish processed meat products such as soudjouk, salami, sausage, meatball, cured spiced beef and doner kebap was conducted. Thirty-six samples were negative for the presence of pork (< 0.1%) and four were found to be correctly labelled as containing pork. However, one sausage sample was labelled as containing 5% beef, but beef DNA was not detected and a meatball sample labelled as 100% beef was found to contain chicken. Another turkey meatball sample was predominantly chicken.     

Non-volatile taste components of various broth cubes

Commercial soup bases, in the form of broth cubes available in the market, include chicken, mushroom, pork and seafood broth cubes. The non-volatile taste components of four broth cubes were studied. Equivalent umami concentration (EUC) values of these broth cubes were evaluated and compared with their sensory results from hedonic tests. Only two soluble sugars, lactose and sucrose, were found. Contents of total free amino acids and monosodium glutamate (MSG)-like components ranged from 0.51 to 1.04 mg g⁻¹ and 0.48 to 0.56 mg g⁻¹, respectively. Contents of 5′-nucleotides and flavour 5′-nucleotides ranged from 2.67 to 3.66 mg g⁻¹ and 2.58 to 3.33 mg g⁻¹, respectively. EUC values were low and the umami intensities of one gramme of four soup bases were equivalent to those given by 0.14–0.32 g MSG. Mushroom and pork soups were more preferred, whereas seafood soup was less preferred. Correlations of EUC values with sensory scores were established for chicken, pork and seafood soups.     

Authentication of sweetness of mango juice using Fourier transform infrared-attenuated total reflection spectroscopy

Fourier transform infrared spectrometer equipped with attenuated total reflection and chemometrics were used to determine added sugar content (ASC), total soluble solids (TSS) and real juice content (RJC) in fresh and commercial mango juice. Sucrose solutions (0-27%), fresh mango juice adulterated with 0-27% sucrose, and two commercial brands were evaluated in wavenumber range of 4000-650 cm⁻¹. Partial least squares (PLS) discrimination and principal component analysis (PCA) were used to classify the samples with or without ASC. PLS and multiple linear regression (MLR) were carried out with and without data treatments. The detection limit for ASC was 3% for samples with low natural TSS, 5% for samples with natural TSS more than 10% and 3.6% for commercial samples. ASC, TSS, and RJC were predicted in the wavenumber range of 1476-912 cm⁻¹ using PLS (multiple correlation coefficient, R = 0.99) and three wavenumbers (1088, 1050, 991 cm⁻¹) using MLR (R = 0.98).     

Utilisation of mid-infrared spectroscopy for determination of the geographic origin of Gruyère PDO and L’Etivaz PDO Swiss cheeses

The potential of mid-infrared spectroscopy (MIR), using an attenuated total reflectance (ATR) cell, was evaluated for the authentication of 25 Gruyère PDO and L’Etivaz PDO cheeses produced at different altitudes in Switzerland. In order to test the ability of MIR to authenticate the investigated cheeses, chemometric tools, such as principal component analysis (PCA) and factorial discriminant analysis (FDA), were applied to the three spectral regions of the MIR (e.g. 3000–2800 cm⁻¹, 1700–1500 cm⁻¹, and 1500–900 cm⁻¹). By applying the FDA to the first 10 principal components (PCs) of the PCA applied to each spectral regions, the best rate of correct classification was obtained in the 3000–2800 cm⁻¹ and 1500–900 cm⁻¹ spectral regions, since 90.5% and 90.9% were achieved, respectively. It can be concluded that these two spectral regions could be considered as valuable tools for the determination of the geographical origin of the investigated cheeses.     

Characterising protein,salt and water interactions with combined vibrational spectroscopic techniques

In this paper a combination of NIR spectroscopy and FTIR and Raman microspectroscopy was used to elucidate the effects of different salts (NaCl, KCl and MgSO₄) on structural proteins and their hydration in muscle tissue. Multivariate multi-block technique Consensus Principal Component Analysis enabled integration of different vibrational spectroscopic techniques: macroscopic information obtained by NIR spectroscopy is directly related to microscopic information obtained by FTIR and Raman microspectroscopy. Changes in protein secondary structure observed at different concentrations of salts were linked to changes in protein hydration affinity. The evidence for this was given by connecting the underlying FTIR bands of the amide I region (1700–1600 cm⁻¹) and the water region (3500–3000 cm⁻¹) with water vibrations obtained by NIR spectroscopy. In addition, Raman microspectroscopy demonstrated that different cations affected structures of aromatic amino acid residues differently, which indicates that cation–π interactions play an important role in determination of the final structure of protein molecules.     

Application of mid-infrared spectroscopy with multivariate analysis and soft independent modeling of class analogies (SIMCA) for the detection of adulterants in minced beef

Chemometric MID-FTIR methods were developed to detect and quantify the adulteration of mince meat with horse meat, fat beef trimmings, and textured soy protein. Also, a SIMCA (Soft Independent Modeling Class Analogy) method was developed to discriminate between adulterated and unadulterated samples. Pure mince meat and adulterants (horse meat, fat beef trimmings and textured soy protein) were characterized based upon their protein, fat, water and ash content. In order to build the calibration models for each adulterant, mixtures of mince meat and adulterant were prepared in the range 2–90% (w/w). Chemometric analyses were obtained for each adulterant using multivariate analysis. A Partial Least Square (PLS) algorithm was tested to model each system (mince meat + adulterant) and the chemical composition of the mixture. The results showed that the infrared spectra of the samples were sensitive to their chemical composition. Good correlations between absorbance in the MID-FTIR and the percentage of adulteration were obtained in the region 1800–900 cm^− 1. Values of R² greater than 0.99, standard errors of calibration (SEC) in the range to 0.0001–1.278 and standard errors of prediction (SEP estimated) between 0.001 and 1.391 for the adulterant and chemical parameters were obtained. The SIMCA model showed 100% classification of adulterated meat samples from unadulterated ones. Chemometric MID-FTIR models represent an attractive option for meat quality screening without sample pretreatments which can identify the adulterant and quantify the percentage of adulteration and the chemical composition of the sample.     

Rapid detection and quantification of soya bean oil and common sugar in bovine milk using attenuated total reflectance–fourier transform infrared spectroscopy

Attenuated total reflectance–Fourier transform infrared spectroscopy, along with chemometrics, were used to detect and quantify soya bean oil (SO) and sugar (CS) adulteration in milk. Bovine milk was artificially adulterated with SO (0.2–2.0%; v/v) and CS (1–10%; w/v) separately. Spectra revealed significant differences in specific wavenumber regions (SO: 1450–1250 cm^?1; CS: 1200–900 cm^?1). Soya bean oil adulteration was best predicted in wavenumber range of 1262–1164 cm^?1, using partial least square regression (coefficient of determination (R²: 0.90 and 0.88 for calibration and validation, respectively). Common sugar adulteration was best predicted in wavenumber range of 1010–910 cm^?1 (R²: 0.99 for calibration and validation) using partial least square.     

Influence of fatty acid chain length and unsaturation on mid-infrared milk analysis

Our first objective was to optimize center wavelengths and bandwidths for virtual filters used in a Fourier transform mid-infrared (MIR) milk analyzer. Optimization was accomplished by adjusting center wavelengths and bandwidths to minimize the size of intercorrection factors. Once optimized, the virtual filters were defined as follows: fat B sample, 3.508 μm (2,851 cm⁻¹), and bandwidth of 0.032 μm (26 cm⁻¹); fat B reference, 3.556 μm (2812 cm⁻¹), and bandwidth of 0.030 μm (24 cm⁻¹); lactose sample, 9.542 μm (1,048 cm⁻¹), and bandwidth of 0.092 μm (20 cm⁻¹); lactose reference, 7.734 μm (1,293 cm⁻¹), and bandwidth of 0.084 μm (14 cm⁻¹); protein sample, 6.489 μm (1,541 cm⁻¹), and bandwidth of 0.085 μm (20 cm⁻¹); protein reference, 6.707 μm (1491 cm⁻¹), and bandwidth of 0.054 μm (12 cm⁻¹); fat A sample, 5.721 μm (1,748 cm⁻¹), and bandwidth of 0.052 μm (16 cm⁻¹); fat A reference, 5.583 μm (1,791 cm⁻¹), and bandwidth of 0.050 μm (16 cm⁻¹). The bandwidth and its proximity to areas of intense water absorption had the largest effect on the intercorrection factors. The second objective was to quantify the impact of fatty acid chain length and unsaturation on fat B and fat A MIR measurements. Increasing the chain length increased the difference (i.e., MIR minus reference) between MIR prediction and reference chemistry by 0.0429% and by −0.0566% fat per unit of increase in carbon number per 1% change in fat, for fat B and fat A, respectively. Increasing the unsaturation decreased the difference (i.e., MIR minus reference) between MIR prediction of fat and chemistry for fat B by −0.4021% and increased fat A by 0.0291% fat per unit of increase in double bonds per 1% change in fat concentration.     

Mid infrared attenuated total reflection spectroscopy as a rapid tool to assess the quality of Sicilo-Sarde ewe’s milk during the lactation period after replacing soybean meal with scotch bean in the feed ration

This study investigates the potential of attenuated total reflection spectroscopy in the mid infrared (MIR) for monitoring changes in the quality of ewe’s milk as a function of lactation period and feeding systems. Twelve 5-year-old lactating Sicilo-Sarde ewes (third lambing) were kept in environmentally controlled sheepfolds and were divided into two homogenous weight matched groups (n = 6). Ewes were fed ad libitum with two iso-energetic diets (20% barley, 3% vitamin and mineral premix, and 77% soybean meal or scotch bean). Physico–chemical analyses and MIR (3000–900 cm⁻¹) were performed on milk samples after 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10 weeks of lactation period. The inclusion of scotch bean in the diet resulted in a significant decrease (P ? 0.05) of fat content (7.85 g 100 g⁻¹ vs. 6.75 g 100 g⁻¹) and a significant increase (P ? 0.05) of lactose level (3.49 g 100 g⁻¹ vs. 3.61 g 100 g⁻¹). The principal component analysis (PCA) applied to the 1700–1500 cm⁻¹ spectral region showed only some discrimination between milk samples according to diet compositions. The best results were obtained in the 3000–2800 cm⁻¹ and 1500–900 cm⁻¹ spectral regions since a good discrimination between milk from ewes fed soybean meal from those fed scotch bean meal was observed. It can be concluded that these spectral regions could be considered as fingerprint, regions allowing a good identification of milk according to diet composition. However, the MIR failed to discriminate milk samples according to the lactation period for the two feeding systems.     

Microwave improvement of soy protein isolate–saccharide graft reactions

Soy protein isolate (SPI) was mixed with lactose, maltose, dextran or soluble starch (SS) and heated (temperature ?90 °C) by microwave irradiation. Compared to the classical heating, the microwave heating (MH) speeded up the graft reactions of SPI with sugars. From the results calculated, the rate constants of free amino groups in the grafts of SPI with lactose, maltose, dextran and SS by MH were, respectively, 6, 7, 57 and 12.3 times of those by classical heating. After heating by microwave, the lysine and arginine decreased and from, the FTIR spectroscopy of SPI and its grafts by MH, the absorbance of –C–O stretching and –OH deformation vibrations (1050–1150 cm⁻¹) and free –OH form (3643–3630 cm⁻¹) in SPI grafts increased compared to SPI. The temporal development of the graft reactions of SPI with sugars by MH was also shown by SDS–PAGE.     

Comparison of various methods for determination of water in white yoghurts

Water content was determined in 11 samples of white yoghurts. Several techniques, namely Karl Fischer (KF) volumetric titration, near and middle infrared spectroscopy (MIR), oven drying and moisture analyser were used. Optimisations of solvent, titration temperature and extraction time were carried out for the KF titration. Methanol at room temperature with 5 min extraction period was used as final conditions. For the infrared spectroscopy (FTIR) the suitable solvent and the appropriate wavenumbers for water analysis were chosen. The measurement in the near infrared (NIR) region at the wavenumber 10270 cm⁻¹ using acetonitrile as solvent and transmission method was evaluated as the best of the FTIR methods. Based on the comparison of individual methods the oven drying at 105 °C seems to be the most suitable, but it is the most time consuming. However, KF volumetric titration and especially FTIR methods appear to be good alternatives to the drying methods.     

Use of Fourier transform infrared spectroscopy for rapid comparative analysis of Bacillus and Micrococcus isolates

The identification of foodborne microorganisms and their endospores in food products are important for food safety. The present work compares Bacillus (Bacillus licheniformis, Bacillus circulans and Bacillus subtilis) and Micrococcus (Micrococcus luteus) species with Fourier transform infrared (FTIR) spectroscopy. Our results show that there are several characteristic peaks belonging to both the Micrococcus and Bacillus species which can be used for the identification of these foodborne bacteria and their endospores. For Micrococcus species, a new band was observed at 1338 cm⁻¹ which may be due to acetate oxidation via the carboxylic acid cycle. The bands at 1313 cm⁻¹ and 1256 cm⁻¹ can be explained by an exopolymer formation and the other bands at 1074 cm⁻¹ and 550 cm⁻¹, may be due to the glycogen-like storage material in Micrococcus spp. There are also characteristic peaks at 993 cm⁻¹ and 801 cm⁻¹ for these bacterial species. Different Bacillus species also showed characteristic peaks at 1000–500 cm⁻¹ region. Dipicolinic acid (DPA) bands at ∼728 cm⁻¹ and ∼703 cm⁻¹ seen only in B. circulans were the marker of an endospore formation.     

Near infrared reflectance spectroscopy predicts the content of polyunsaturated fatty acids and biohydrogenation products in the subcutaneous fat of beef cows fed flaxseed

This study examined the ability of near infrared reflectance spectroscopy (NIRS) to estimate the concentration of polyunsaturated fatty acids and their biohydrogenation products in the subcutaneous fat of beef cows fed flaxseed. Subcutaneous fat samples at the 12th rib of 62 cows were stored at − 80 °C, thawed, scanned over a NIR spectral range from 400 to 2498 nm at 31 °C and 2 °C, and subsequently analysed for fatty acid composition. Best NIRS calibrations were with samples at 31 °C, showing high predictability for most of the n−3 (R²: 0.81-0.86; RMSECV: 0.11-1.56 mg g^− 1 fat) and linolenic acid biohydrogenation products such as conjugated linolenic acids, conjugated linoleic acids (CLA), non-CLA dienes and trans-monounsaturated fatty acids with R² (RMSECV_, mg g^− 1 fat) of 0.85-0.85 (0.16-0.37), 0.84-0.90 (0.21-2.58), 0.90 (5.49) and 0.84-0.90 (4.24-8.83), respectively. NIRS could discriminate 100% of subcutaneous fat samples from beef cows fed diets with and without flaxseed.