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Background: The starting point of this work is to propose a qualitative approach for authenticity confirmation of the composition of liquid egg products. To this end, it was aimed to detect the liquid egg authenticity and adulteration (with water) by using attenuated total reflectance Fourier-transform infrared (ATR-FTIR), near infrared (NIR) spectroscopy and chemometrics., Results: Liquid (n = 50) and dry (n = 50) samples of whole egg, egg yolk, egg white, and whole egg containing extra egg white (BXEW) and water (BXW) were prepared. Principal component analysis (PCA) models were formed using the data obtained from ATR-FTIR and NIR measurements of liquid and dry samples. A better classification was achieved with PCA model of ATR-FTIR measurements formed by using dry samples (100%) instead of liquid ones (80%). The best separation was obtained between dry sample groups of BXEW and BXW (adulterated). The presence of water content in liquid samples showed a negative effect on classification of the samples, while a good classification (100%) was obtained for NIR measurements of both liquid and dry sample groups. The developed PCA models achieved classification regardless of the form of egg samples (liquid or dry)., Conclusion: The results of the study revealed that adulterated egg samples (with water) could be qualitatively detected using ATR-FTIR and NIR spectroscopy techniques in combination with PCA. © 2019 Society of Chemical Industry., (© 2019 Society of Chemical Industry.)

The aim of present study was to determine liquid egg adulteration based on yolk:white ratio of egg using sodium dodecyl sulphate-polyacrylamide gel electrophoresis and by measuring Brix. To construct a calibration model, liquid egg samples were prepared by mixing egg yolk and white (yolk:white) at different concentrations. A high coefficient of determination value ( R 2  = 0.992) was obtained. Limit of detection and limit of quantification were estimated as 62 g/kg and 187 g/kg. The accuracy of the model was tested using eleven LWE samples, and the yolk ratios of 90.9% of these samples were predicted successfully. Liquid whole egg (LWE) containing additional egg white up to 30% was also predicted with a low relative error of less than 10%. Yolk:white ratio of LWE samples and authentication of the components of LWE (containing extra white or water) can be determined using proposed method., Competing Interests: Conflict of interestThe authors declare that they have no conflict of interest., (© The Korean Society of Food Science and Technology 2019.)

Background: The use of liquid whole egg (LWE) in the food industry as a substitute for shell eggs has been on the increase lately. Since the composition of LWE can easily be changed, determination of protein, lipid, moisture and total soluble solid (TSS) contents of LWE has also gained importance. Traditional methods usually require more time and effort, and the use of toxic chemicals for sample preparation; hence more efficient techniques (faster, cheaper and more reliable) are needed. In this regard, a novel technique that determines LWE components using attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy with partial least squares regression (PLS) is presented in this study., Results: The actual values of LWE components were determined by applying reference methods. The accuracy of the PLS model was demonstrated by comparing the obtained predictions with the actual values of the components. High coefficients of determination values, which are 0.950, 0.992, 0.994 and 0.972, were achieved for protein, lipid, moisture, and TSS validation datasets, respectively. The error values, namely RMSEC, RMSECV and RMSEP, were obtained in the ranges 0.404-0.978, 0.57-1.82 and 0.83-1.84, respectively., Conclusions: ATR-FTIR spectroscopy coupled with chemometrics can provide a rapid and sensitive method for quality control of liquid egg composition. © 2019 Society of Chemical Industry., (© 2019 Society of Chemical Industry.)

The aim of this study was to analyse the effect of heat treatment parameters on liquid whole egg (LWE) proteins by using ultraviolet-visible (UV-VIS) spectroscopy and capillary electrophoresis (CE). Heat treatment (at 60-68°C for 1-5min) was applied to LWE. Treated LWE was centrifuged and supernatant was taken for measurement of UV-VIS spectroscopy and CE. The change in UV absorbance showed loss of protein solubility depending on heat treatments parameters. Electropherograms of samples demonstrated the effect of treatment parameters on composition of LWE proteins. It was found that conalbumin and lysozyme were influenced by the treatment, while ovalbumin and ovomucoid were not affected. CE combined with principal component analysis (PCA) was used for classification of samples untreated or treated and treated at different treatment parameters. The results of the study revealed that the extent of heat treatment in LWE samples could be determined with PCA of the CE measurements., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

A new approach, based on the usage of Raman spectroscopy in combination with chemometrics, was developed for the rapid determination of beef adulteration with horsemeat. The data mining process of collected Raman spectra was performed with principal component analysis (PCA). Pure fat samples, extracted from forty-nine meat beef and horsemeat samples, were analysed using the Raman spectroscopy. All meat samples were classified successfully according to their origins. The presence of different concentrations (25%, 50%, 75%, w/w) of horsemeat in beef was also differentiated using the developed model system. This study offers a rapid assay for determination of meat adulteration by discriminating beef and horsemeat with high accuracy, a short analysis time (30s) and no requirement for time-consuming sample preparation procedures., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

In this study, adulteration of butter with margarine was analysed using Raman spectroscopy combined with chemometric methods (principal component analysis (PCA), principal component regression (PCR), partial least squares (PLS)) and artificial neural networks (ANNs). Different butter and margarine samples were mixed at various concentrations ranging from 0% to 100% w/w. PCA analysis was applied for the classification of butters, margarines and mixtures. PCR, PLS and ANN were used for the detection of adulteration ratios of butter. Models were created using a calibration data set and developed models were evaluated using a validation data set. The coefficient of determination (R(2)) values between actual and predicted values obtained for PCR, PLS and ANN for the validation data set were 0.968, 0.987 and 0.978, respectively. In conclusion, a combination of Raman spectroscopy with chemometrics and ANN methods can be applied for testing butter adulteration., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

In this study, the utility of Raman spectroscopy (RS) with chemometric methods for quantification of multiple components in the fermentation process was investigated. Vinegar, the product of a two stage fermentation, was used as a model and glucose and fructose consumption, ethanol production and consumption and acetic acid production were followed using RS and the partial least squares (PLS) method. Calibration of the PLS method was performed using model solutions. The prediction capability of the method was then investigated with both model and real samples. HPLC was used as a reference method. The results from comparing RS-PLS and HPLC with each other showed good correlations were obtained between predicted and actual sample values for glucose (R(2)=0.973), fructose (R(2)=0.988), ethanol (R(2)=0.996) and acetic acid (R(2)=0.983). In conclusion, a combination of RS with chemometric methods can be applied to monitor multiple components of the fermentation process from start to finish with a single measurement in a short time., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

The aim of this study was to determine clinical and US factors associated with pain in patients with knee osteoarthritis (OA). The study included 143 patients. Patients were divided into two groups: group 1 consisted of 94 patients with unilateral or bilateral knee pain ≥3 cm during physical activity for at least 48 h prior to inclusion, measured by the visual analog scale from 0 to 10 cm. Group 2 consisted of 49 patients with knee OA without knee pain at least 1 month prior to inclusion. In both knees, range of motion was measured by goniometry and anteroposterior, and lateral knee radiographs were taken during weight-bearing. OA grading was performed in accordance with the Kellgren-Lawrence criteria by a specialist in radiology experienced in this field. A knee ultrasound (US) examination was performed in all patients by a blinded radiologist. Women were more often symptomatic than men (p < 0.005). Patients in group 1 tended to have a higher body mass index (BMI; p<0.001). Radiographic grades III (52.1%) and II (37.2%) were most frequently found in group 1, whereas I (30.6%), II (46.9%), and III (22.4%) were found in group 2. When radiographic grades in both groups were compared, group 1 had greater radiographic grades than group 2 (p<0.001). US findings in group 1 were effusion of the suprapatellar pouch (72.3%), Baker's cyst (42.6%), protrusion of the anterior horn of the medial meniscus associated with medial collateral ligament displacement (9.6%), and loose body (9.6%). In group 2, the only US finding was Baker's cyst (6.1%). Regression analysis revealed that BMI, degree of knee flexion, and thickness of the quadriceps tendon were factors that were related with pain in the knee. Increased BMI, decrease in the degree of knee flexion, and decreased quadriceps tendon thickness are factors that increase the risk of pain in knee OA.