Investigation of the Effect of Different Seed Flours on Gluten-Free Products: Baton Cake Production, Characterization, and TOPSIS Application.

The present study aims to develop gluten-free product formulations by using different seed flours to determine their effectiveness in gluten-free products. For this purpose, a baton cake model was selected; the cake production process was conducted by adding hemp, okra, mustard, or coriander seed flours with rice flour at a ratio of 25% seed flour to 75% rice flour to prepare the cake batters. The physicochemical, textural, and sensory properties, as well as the baking behaviors of the resulting products, were determined. The TOPSIS method was used in the sensory analyses. With the addition of seed flours, a color change occurred in the inner and crust values of the baton cake samples. It was observed that the hardness value of the baton cake samples increased with the addition of seed flour. In the TOPSIS evaluation, which is a multi-criteria decision-making method, the most preferred product in the free baton cake samples was the cake with hemp seed flour added, while the least preferred product was the control group baton cake. According to the findings, it was concluded that the use of seed flours can be used as an alternative ingredient in the production of gluten-free baton cakes that celiac patients can consume in their diets.

A rapid spectroscopic method for the identification of the filamentous fungi isolated from Turkish traditional mold-ripened cheeses.

Fourier transform infrared spectroscopy (FTIR) is an alternative microbial identification technique due to its faster analysis times and lower cost compared to molecular methods. In this study, forty-three fungal strains isolated from different Turkish traditional mold-ripened cheeses representing nine different Penicillium species (P. roqueforti, P. corylophilum, P. before, P. crustosum, P. spinulosum, P. rubens, P. brevicompactum, P. paneum, and P. solitum) were analyzed by using FTIR HTS-XT (High Throughput Screening Extension) method in the 4000-400 cm-1 wavenumber range. The spectra of the isolates were evaluated, and the chemical structures corresponding to the fungus-specific spectral regions were determined as fatty acids (3600-2800 cm-1), amide I and amide II of proteins and peptides (1740-1500 cm-1), polysaccharides (1200-900 cm-1) and carbohydrates (900-600 cm-1). The isolates were grouped according to the hierarchical clustering analysis (HCA) by applying chemometrics combined with FTIR spectroscopy. Results showed that FTIR spectroscopy has a high capability for rapid determination of cheese fungi based on their FTIR spectra.

Nondestructive Metabolomic Fingerprinting: FTIR, NIR and Raman Spectroscopy in Food Screening.

In recent years, there has been renewed interest in the maintenance of food quality and food safety on the basis of metabolomic fingerprinting using vibrational spectroscopy combined with multivariate chemometrics. Nontargeted spectroscopy techniques such as FTIR, NIR and Raman can provide fingerprint information for metabolomic constituents in agricultural products, natural products and foods in a high-throughput, cost-effective and rapid way. In the current review, we tried to explain the capabilities of FTIR, NIR and Raman spectroscopy techniques combined with multivariate analysis for metabolic fingerprinting and profiling. Previous contributions highlighted the considerable potential of these analytical techniques for the detection and quantification of key constituents, such as aromatic amino acids, peptides, aromatic acids, carotenoids, alcohols, terpenoids and flavonoids in the food matrices. Additionally, promising results were obtained for the identification and characterization of different microorganism species such as fungus, bacterial strains and yeasts using these techniques combined with supervised and unsupervised pattern recognition techniques. In conclusion, this review summarized the cutting-edge applications of FTIR, NIR and Raman spectroscopy techniques equipped with multivariate statistics for food analysis and foodomics in the context of metabolomic fingerprinting and profiling.

Rapid Sensing: Hand-Held and Portable FTIR Applications for On-Site Food Quality Control from Farm to Fork.

Today, one of the world's biggest problems is the assurance of food integrity from farm to fork. Economically motivated food adulteration and food authenticity problems are increasing daily with considerable health and economic effects. Early detection and prevention of food integrity-related problems could be provided by the application of effective on-site food analysis technologies. FTIR spectroscopy coupled with chemometrics can be used for the rapid quality control of a wide variety of food products with fast, high-throughput, accurate and nondestructive analysis advantages. In particular, hand-held and portable FTIR instruments have the potential to surveil food quality and food safety in various critical segments of the food supply chain. In this review, we explore the abilities of hand-held and portable FTIR spectrometers combined with multivariate statistics to conduct a quality evaluation of various food products in terms of food adulteration and authenticity issues. An examination of the literature showed that comparable results were obtained based on detection limits, correlation coefficient (R2) values, standard error values and discrimination power by using both portable/hand-held FTIR spectrometers and benchtop FTIR spectrometers. In conclusion, this review highlights the potential usefulness of portable and hand-held FTIR spectrometers combined with chemometrics for maintaining the food quality through the presentation of various applications that may shed light for on-site food control at any point of the food supply chain.

Determination of the Antifungal, Antibacterial Activity and Volatile Compound Composition of Citrus bergamia Peel Essential Oil.

Safe and health-beneficial citrus oils can be employed as natural preservatives, flavorings, antioxidants, and as antibacterial and antifungal agents in a wide variety of food products. In this research, using GC−MS methodology, the major volatile composition of Citrus bergamia EO, obtained by hydro-distillation, was determined to consist of limonen (17.06%), linalool (46.34%) and linalyl acetate (17.69%). The molecular fingerprint was obtained using FTIR spectroscopy. The antibacterial effect of C. bergamia EO at different concentrations (0.5, 1, 2.5 and 5 µg/mL) was tested against different pathogen species (Salmonella typhimurium, Bacillus cereus, Staphylococcus aureus, Escherichia coli, Listeria monocytogenes), based on disc diffusion assay. The in vitro antifungal activity of C. bergamia EO oil against Aspergillus niger and Penicillium expansum was evaluated using agar disc diffusion assay. Clear inhibition zones were formed by C. bergamia EO against selected species of pathogens. Almost all of the concentrations were revealed to have antifungal activity against selected fungal pathogens. The highest inhibition rate of A. niger at 6 incubation days was 67.25 ± 0.35 mm with a 20 µL dose, while the growth in the control was 90.00 ± 0.00 mm. In addition, the highest inhibition rate of P. expansum was 26.16 ± 0.76 mm with a 20 µL dose, while the growth was 45.50 ± 2.12 mm in the control fungus. A higher antifungal effect of C. bergamia EO against P. expansum was obtained. It was observed that the growth of fungi was weakened with increasing concentrations (5, 10, 15 and 20 µL dose) of C. bergamia EO. Statistically significant (p < 0.05) results were obtained for the antibacterial and antifungal effects of C. bergamia EO. The findings from the research may shed light on the further use of C. bergamia EO obtained from peels in innovative food engineering applications in order to maintain food quality, food safety, and food sustainability.

Physical and biochemical characterization of dromedary milk as traditionally consumed by Bedouins.

Few studies were dedicated to characterizing the dromedary milk (DM) as consumed by Bedouins, mixed with a small amount of dromedary urine (DU). Therefore, this work aimed to reveal some physical and biochemical characteristics of the DM alone, and incorporated with DU at two different concentrations. pH, colour, Brix, fats, and minerals were evaluated with proteins and sugar content using FTIR; in addition to protein oxidation. The results showed that DM counts as a rich source of the nutritional element yet its proprieties were affected by the addition of DU. An important increase in colour, sugar, fat, and protein concentration with a remarkable augmentation in the pH, mineral content, and protein oxidation where the more urine is added the more milk proteins are oxidated as demonstrated by the characteristics showed in the two mixtures which will negatively affect DM therapeutical proprieties, especially the one related to proteins.

Quantification of the Geranium Essential Oil, Palmarosa Essential Oil and Phenylethyl Alcohol in Rosa damascena Essential Oil Using ATR-FTIR Spectroscopy Combined with Chemometrics.

Rosa damascena essential oil is an essential oil that has the greatest industrial importance due to its unique quality properties. The study used ATR-FTIR (attenuated total reflectance-Fourier transform infrared) spectroscopy coupled with chemometrics of PLSR (partial least squares regression) and PCR (principal component regression) for quantification of probable adulterants of geranium essential oil (GEO), palmarosa essential oil (PEO) and phenyl ethyl alcohol (PEOH). Hierarchical cluster analysis was performed to observe the classification pattern of Rosa damascena essential oil, spiked samples and adulterants. Rosa damascena essential oil was spiked with each adulterant at concentrations of 0-100% (v/v). Excellent R2 (regression coefficient) values (≥0.96) were obtained in all PLSR and PCR cross-validation models. The SECV (standard error of cross-validation) values ranged between 0.43 and 4.15. The lowest SECV and bias values were observed in the PLSR and PCR models, which were built by using the raw FTIR spectra of all samples. Hierarchical cluster analysis through Ward's algorithm and Euclidian distance had high potential to observe the classification pattern of all adulterated and authentic samples. In conclusion, the combination of ATR-FTIR spectroscopy with multivariate analysis can be used for rapid, cost-effective, easy, reliable and high-throughput detection of GEO, PEO and PEOH in Rosa damascena essential oil.

The famous Turkish rose essential oil: Characterization and authenticity monitoring by FTIR, Raman and GC-MS techniques combined with chemometrics.

There is a necessity for rapid, robust, easy, accurate and cost-effective methodologies for the quality control of essential oils from medicinal and aromatic plants. Rosa damascena essential oil is a high-value natural product with its unique quality properties and economic importance. This research evaluated the capability of Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy and gas chromatography-mass spectrometry (GC-MS) techniques combined with chemometrics for determination of the authenticity of R. damascena essential oil. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were successfully employed with 100% accuracy for discrimination of authentic R. damascena essential oil samples from fraudulent commercial samples. Consistent results were obtained by FTIR, Raman and GC-MS techniques. Two of twenty commercial samples were determined as authentic R. damascena essential oil samples using the three analytical techniques. Findings showed that FTIR and Raman spectroscopy combined with chemometrics could be used as reliable, robust, rapid, accurate and low-cost analytical techniques for quality evaluation of R. damascena essential oil.

Rapid Screening of Mentha spicata Essential Oil and L-Menthol in Mentha piperita Essential Oil by ATR-FTIR Spectroscopy Coupled with Multivariate Analyses.

Mentha piperita essential oil (EO) has high economic importance because of its wide usage area and health-beneficial properties. Besides health-beneficial properties, Mentha piperita EO has great importance in the flavor and food industries because of its unique sensory and quality properties. High-valued essential oils are prone to being adulterated with economic motivations. This kind of adulteration deteriorates the quality of authentic essential oil, injures the consumers, and causes negative effects on the whole supply chain from producer to the consumer. The current research used fast, economic, robust, reliable, and effective ATR-FTIR spectroscopy coupled chemometrics of hierarchical cluster analysis(HCA), principal component analysis (PCA), partial least squares regression (PLSR) and principal component regression (PCR) for monitoring of Mentha spicata EO and L-menthol adulteration in Mentha piperita EOs. Adulterant contents (Mentha spicata and L-menthol) were successfully calculated using PLSR and PCR models. Standard error of the cross-validation SECV values changed between 0.06 and 2.14. Additionally, bias and press values showed alteration between 0.06 and1.43 and 0.03 and 41.15, respectively. Authentic Mentha piperita was successfully distinguished from adulterated samples, Mentha spicata and L-menthol, by HCA and PCA analysis. The results showed that attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometrics could be effectively used for monitoring various adulterants in essential oils.

Rapid detection of green-pea adulteration in pistachio nuts using Raman spectroscopy and chemometrics.

BACKGROUND: Ground pistachio nut is prone to adulteration because of its high economic value and wide usage. Green pea is known as the main adulterant in frauds involving pistachio nuts. The present study developed a new, rapid, reliable and low-cost methodology by using a portable Raman spectrometer in combination with chemometrics for the detection of green pea in pistachio nuts. RESULTS: Three different methods of Raman spectroscopy-based chemometrics analysis were developed for the determination of green-pea adulteration in pistachio nuts. The first method involved the development of hierarchical cluster analysis (HCA) and principal component analysis (PCA), which differentiated authentic pistachio nuts from green pea and green pea-adulterated samples. The best classification pattern was observed in the adulteration range of 20-80% (w/w). In addition to classification methods, partial least squares regression (PLSR) and genetic algorithm-based inverse least squares (GILS) were also used to develop multivariate calibration models to determine quantitatively the degree of green-pea adulteration in grounded pistachio nuts. The spectral range of 1790-283 cm-1 was used in the case of multivariate data analysis. A green-pea adulteration level of 5-80% (w/w) was successfully identified by PLSR and GILS. The correlation coefficient of determination (R2 ) was determined as 0.91 and 0.94 for the PLSR and GILS analyses, respectively. CONCLUSION: A Raman spectrometer combined with chemometrics has a high capability with regard to the detection of adulteration in pistachio nuts, combined with low cost, strong reliability, a high level of accuracy, rapidity of analysis, and minimum sample preparation. © 2020 Society of Chemical Industry.

Detection of Orange Essential Oil, Isopropyl Myristate, and Benzyl Alcohol in Lemon Essential Oil by FTIR Spectroscopy Combined with Chemometrics.

Essential oils are high-valued natural extracts that are involved in industries such as food, cosmetics, and pharmaceutics. The lemon essential oil (LEO) has high economic importance in the food and beverage industry because of its health-beneficial characteristics and desired flavor properties. LEO, similar to other natural extracts, is prone to being adulterated through economic motivations. Adulteration causes unfair competition between vendors, disruptions in national economies, and crucial risks for consumers worldwide. There is a need for cost-effective, rapid, reliable, robust, and eco-friendly analytical techniques to detect adulterants in essential oils. The current research developed chemometric models for the quantification of three adulterants (orange essential oil, benzyl alcohol, and isopropyl myristate) in cold-pressed LEOs by using hierarchical cluster analysis (HCA), principal component regression (PCR), and partial least squares regression (PLSR) based on FTIR spectra. The cold-pressed LEO was successfully distinguished from adulterants by robust HCA. PLSR and PCR showed high accuracy with high R2 values (0.99-1) and low standard error of cross-validation (SECV) values (0.58 and 5.21) for cross-validation results of the raw, first derivative, and second derivative FTIR spectra. The findings showed that FTIR spectroscopy combined with multivariate analyses has a considerable capability to detect and quantify adulterants in lemon essential oil.

Detection of lard in butter using Raman spectroscopy combined with chemometrics.

There is a contentious need for robust and rapid methodologies for maintaining the authenticity of foods and food additives. The current paper presented a new Raman spectroscopy-based methodology for detection and quantification of lard in butter. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were successfully performed for the classification and discrimination of butter and lard-adulterated samples. Strong discrimination pattern was observed in the HCA analysis. Also, partial least squares regression and principal component regression (R2 = 0.99) were applied for quantification of lard in butter samples. Quite favorable prediction capabilities were observed in the cross-validation of PLS and PCR analysis for the adulteration levels between 0% and 100% lard fat (w/w). Raman spectroscopy coupled chemometrics was employed effectively for quantification of lard fat in butter fat samples with easy, robust, effective, low-cost and reliable application in the quality control of butter.

Determination and evaluation of in vitro bioaccessibility of added vitamin C in commercially available fruit-, vegetable-, and cereal-based baby foods.

Knowing the bioaccessibility of vitamin C in foodstuffs produced for infants and young children is necessary to determine their daily vitamin C intake. The purpose of the present study was to investigate the bioaccessibility of vitamin C in fruit-, vegetable-, and cereal-based baby foodstuffs by an in vitro digestion model at varying gastric pHs. The concentrations of measured vitamin C were higher than the declared amounts on their label. The bioaccessibility of vitamin C ranged from 10.4 to 43.4%, and from 0.4 to 19.2% in fruit- and vegetable-based baby foodstuffs (declared vitamin C fortified) at gastric pH 1.5 and 4, respectively. For cereal-based baby foodstuffs, the bioaccessibility ranged from 1.3 to 53.8%, and from 0.3 to 26.3% at gastric pH 1.5 and 4, respectively. As revealed in this research, the bioaccessibility of vitamin C in baby foodstuffs is very low in both gastric pH conditions.

Physicochemical, rheological, molecular, thermal and sensory evaluation of newly developed complementary infant (6-24 months old) foods prepared with quinoa (Chenopodium quinoa Willd.) flour.

The aim of the current work was to evaluate the physicochemical, rheological, molecular, thermal and sensory properties of complementary food (CF) formulations prepared with quinoa (Chenopodium quinoa Willd.) flour (QF). It was observed that QF addition significantly affected the physicochemical and rheological properties of CF formulations, resulting in higher protein and crude fiber, but lower total sugar contents and increased storage (G') and loss (G″) modulus values. The glass transition temperature decreased due to QF addition. The FTIR spectra revealed the presence of aromatic amino acids derived from QF. GC, GC-MS and GC-O analyses revealed the presence of 50 aroma and 23 aroma-active compounds, among which aldehydes, alcohols and ketones were the most prevalent group of compounds. The formulation with 8% QF received the highest sensory scores. QF could be used to improve the physicochemical, rheological, thermal and sensory properties of CF products.

Chemical Fingerprinting of Seeds of Some Salvia Species in Turkey by Using GC-MS and FTIR.

Six species of Salvia seeds cultivated and grown in Cumra/Konya (Turkey) were evaluated using headspace gas chromatography mass spectroscopy (GC-MS) and Fourier transform infrared spectroscopy-attenuated total reflectance (FTIR-ATR) combined chemometrics of hierarchical cluster analysis (HCA) and principal component analysis (PCA). The major volatile compounds in the Salvia species are determined as n-hexanal (present in seven samples), sabinene (present in three samples), α-pinene (present in 13 samples), α-thujone (present in four samples), borneol (present in 11 samples), linalyl acetate (present in 10 samples), ß-pinene (present in 13 samples), camphene (present in 13 samples), α-thujene (present in four samples), 2,4(10)-thujadien (present in two samples), ß-myrcene (present in seven samples), limonen (present in 12 samples), 1,8-cineole (eucalyptol) (present in 13 samples) and camphor (present in nine samples). The most abundant (%) volatile compounds among all were detected as α-pinene, camphene, ß-pinene and eucalyptol. For the first time, chemometrics of HCA and PCA is applied to FTIR and GC-MS data. The classification of all samples is performed on the basis of their chemical similarities and differences.

A rapid ATR-FTIR spectroscopic method for classification of gelatin gummy candies in relation to the gelatin source.

Gelatin is widely used in gummy candies because of its unique functional properties. Generally, porcine and bovine gelatins are used in the food industry. FTIR-ATR combined with chemometrics analysis such as hierarchical cluster analysis (HCA) (OPUS Version 7.2 software), principal component analysis (PCA) (OPUS Version 7.2 software) and partial least squares-discriminant analysis (PLS-DA) (Matlab R2017b) were used for classification and discrimination of gelatin gummy candies related to their gelatin source. The spectral region between 1734 and 1528 cm-1 was selected for chemometric analysis. The potential of FTIR spectroscopy for determination of bovine and porcine source in gummy candies was examined and validated by a real-time polymerase chain reaction (PCR) method. Twenty commercial samples were tested by developed ATR-FTIR methodology and RT-PCR technique, mutually confirming and supporting results were obtained. Gummy candies were classified and discriminated in relation to the bovine or porcine source of gelatin with 100% success without any sample preparation using FTIR-ATR technique.

A survey of free glutamic acid in foods using a robust LC-MS/MS method.

An effective and simultaneous liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was used with the aim of quantifying monosodium glutamate (MSG) in foodstuffs, such as chips, taste cubes, sauces and soups. The results were linear (R2 = 1), with very low LOD and LOQ values, 1.0 µg/kg, 5.0 µg/kg, respectively. Excellent repeatability and reproducibility were also achieved. This highly sensitive and robust LC-MS/MS technique was applied successfully for the detection and quantification of MSG in a wide variety of foodstuffs. MSG contents ranged from 0.01 g/100 g to 15.39 g/100 g in food samples. Importantly, determination of free glutamic acid in the daily diet could also prevent various side effects associated with consumption of excess free glutamic acid.

A rapid ATR-FTIR spectroscopic method for detection of sibutramine adulteration in tea and coffee based on hierarchical cluster and principal component analyses.

Sibutramine may be illicitly included in herbal slimming foods and supplements marketed as "100% natural" to enhance weight loss. Considering public health and legal regulations, there is an urgent need for effective, rapid and reliable techniques to detect sibutramine in dietetic herbal foods, teas and dietary supplements. This research comprehensively explored, for the first time, detection of sibutramine in green tea, green coffee and mixed herbal tea using ATR-FTIR spectroscopic technique combined with chemometrics. Hierarchical cluster analysis and PCA principle component analysis techniques were employed in spectral range (2746-2656cm-1) for classification and discrimination through Euclidian distance and Ward's algorithm. Unadulterated and adulterated samples were classified and discriminated with respect to their sibutramine contents with perfect accuracy without any false prediction. The results suggest that existence of the active substance could be successfully determined at the levels in the range of 0.375-12mg in totally 1.75g of green tea, green coffee and mixed herbal tea by using FTIR-ATR technique combined with chemometrics.

Detection of l-Cysteine in wheat flour by Raman microspectroscopy combined chemometrics of HCA and PCA.

l-Cysteine is deliberately added to various flour types since l-Cysteine has enabled favorable baking conditions such as low viscosity, increased elasticity and rise during baking. In Turkey, usage of l-Cysteine as a food additive isn't allowed in wheat flour according to the Turkish Food Codex Regulation on food additives. There is an urgent need for effective methods to detect l-Cysteine in wheat flour. In this study, for the first time, a new, rapid, effective, non-destructive and cost-effective method was developed for detection of l-Cysteine in wheat flour using Raman microscopy. Detection of l-Cysteine in wheat flour was accomplished successfully using Raman microscopy combined chemometrics of PCA (Principal Component Analysis) and HCA (Hierarchical Cluster Analysis). In this work, 500-2000cm-1 spectral range (fingerprint region) was determined to perform PCA and HCA analysis. l-Cysteine and l-Cystine were determined with detection limit of 0.125% (w/w) in different wheat flour samples.

Prediction of peroxide value in omega-3 rich microalgae oil by ATR-FTIR spectroscopy combined with chemometrics.

Our work explored, for the first time, monitoring peroxide value (PV) of omega-3 rich algae oil using ATR-FTIR spectroscopic technique. The PV of the developed method was compared by that obtained by standard method of Association of Official Analytical Chemists (AOAC). In this study, peak area integration (PAI), Partial Least Squares Regression (PLSR), and Principal Component Regression (PCR) were used as the calibration techniques. PV obtained by the AOAC method and by FTIR-ATR technique were well correlated considering the peak area related to trans double bonds and chemometrics techniques of PLSR and PCR. Calibration model was established using the band with a peak point at 966cm-1 (990-940cm-1) related to CH out of plane deformation vibration of trans double bond. Algae oil oxidation could be successfully quantified using PAI, PLSR and PCR techniques. Additionally, hierarchical cluster analysis was performed and significant discrimination was observed coherently with oxidation process.