Monitoring amino acids, organic acids, and ripening changes in Cheddar cheese using Fourier-transform infrared spectroscopy

Effect of the Bioprotective Properties of Lactic Acid Bacteria Strains on Quality and Safety of Feta Cheese Stored under Different Conditions

Lately, the inclusion of additional lactic acid bacteria (LAB) strains to cheeses is becoming more popular since they can affect cheese's nutritional, technological, and sensory properties, as well as increase the product's safety. This work studied the effect of Lactiplantibacillus pentosus L33 and Lactiplantibacillus plantarum L125 free cells and supernatants on feta cheese quality and Listeria monocytogenes fate. In addition, rapid and non-invasive techniques such as Fourier transform infrared (FTIR) and multispectral imaging (MSI) analysis were used to classify the cheese samples based on their sensory attributes. Slices of feta cheese were contaminated with 3 log CFU/g of L. monocytogenes, and then the cheese slices were sprayed with (i) free cells of the two strains of the lactic acid bacteria (LAB) in co-culture (F, ~5 log CFU/g), (ii) supernatant of the LAB co-culture (S) and control (C, UHT milk) or wrapped with Na-alginate edible films containing the pellet (cells, FF) or the supernatant (SF) of the LAB strains. Subsequently, samples were stored in air, in brine, or in vacuum at 4 and 10 °C. During storage, microbiological counts, pH, and water activity (aw) were monitored while sensory assessment was conducted. Also, in every sampling point, spectral data were acquired by means of FTIR and MSI techniques. Results showed that the initial microbial population of Feta was ca. 7.6 log CFU/g and consisted of LAB (>7 log CFU/g) and yeast molds in lower levels, while no Enterobacteriaceae were detected. During aerobic, brine, and vacuum storage for both temperatures, pathogen population was slightly postponed for S and F samples and reached lower levels compared to the C ones. The yeast mold population was slightly delayed in brine and vacuum packaging. For aerobic storage at 4 °C, an elongation in the shelf life of F samples by 4 days was observed compared to C and S samples. At 10 °C, the shelf life of both F and S samples was extended by 13 days compared to C samples. FTIR and MSI analyses provided reliable estimations of feta quality using the PLS-DA method, with total accuracy (%) ranging from 65.26 to 84.31 and 60.43 to 89.12, respectively. In conclusion, the application of bioprotective LAB strains can result in the extension of feta's shelf life and provide a mild antimicrobial action against L. monocytogenes and spoilage microbiota. Furthermore, the findings of this study validate the effectiveness of FTIR and MSI techniques, in tandem with data analytics, for the rapid assessment of the quality of feta samples.

Microbial trace based on PCR-DGGE to evaluate the ripening stage of minas artisanal cheeses from the Canastra microregion produced by different dairies

The Minas artisanal cheese from the Serra da Canastra (MAC-CM) microregion is a traditional product due to its production and ripening process. Artisanal chesses manufactured with raw cow's milk and endogenous dairy starters ("also known as pingo") have distinctive flavors and other sensory characteristics because of the unknown microbiota. The aim of this study was to evaluate the microbiota during 30 days of ripening, the physicochemical changes, and their relation in MACs produced in two different microregions located in the Serra da Canastra microregion through culture-dependent and culture-independent methods. The MACs were collected in the cities of Bambuí (MAC-CMB) and Tapiraí (MAC-CMT) in the Canastra microregion (n = 21). Cheeses uniqueness was demonstrated with the multivariate analysis that joined the microbiota and physicochemical characteristics, mainly to the proteolysis process, in which the MAC-CMT showed deeper proteolysis (DI -T0:14.18; T30: 13.95), while the MAC-CMB reached only a primary level (EI -T0:24.23; T30: 31.10). Abiotic factors were responsible for the differences in microbial diversity between the cheese farms. Different microbial groups: the prokaryotes, like Corynebacterium variabile, Lactococcus lactis, and Staphylococcus saprophyticus; and the eukaryotes, like Kluyveromyces lactis and Diutina catenulata dominated ripening over time. The microbial community and proteolysis were responsible for the predominance of volatile groups, with alcohols predominating in MAC-CMB and free fatty acids/acids and esters in MAC-CMT.

Chemometrics-driven monitoring of cheese ripening: a multimodal spectroscopic and scanning electron microscopy investigation

The integration of spectroscopic techniques with chemometrics offers a means to monitor quality changes in dairy products throughout processing and storage. This study employed Attenuated Total Reflectance-Mid-Infrared Spectroscopy (ATR-MIR) coupled with Independent Components Analysis (ICA), and 3D Front-Face Fluorescence Spectroscopy (FFFS) paired with Common Components and Specific Weight Analysis (CCSWA). The research focused on Cheddar cheeses aged for 1, 2, 3, and 5 years, alongside Comté cheeses aged for 6, 9, and 12 months. The adopted approach offered valuable insights into the intricate cheese aging process within the food matrix. The ICA proportions and CCSWA scores highlighted the significant impact of biochemical transformations during maturation on the aging process. The extracted independent components (ICs) revealed variations in the vibration modes of amides, lipids, amino acids, and organic acids, facilitating the distinction between different cheese age categories. Additionally, CCSWA outcomes identified age-related differences through shifts in tryptophan fluorescence characteristics as the cheeses aged. These results were consistent with the observed alterations in the microstructure of cheese samples over time, corroborated by Scanning Electron Microscopy (SEM) imagery. The introduced multimodal methodology serves as a significant asset for determining the ripening stage of various types of cheese, offering a detailed perspective of cheese maturation beneficial to the dairy industry and researchers.

Replacement of fat with highland barley β-glucan in zein-based cheese: Structural, rheological, and textual properties

Nowadays, few plant-based cheese provides satisfactory viscoelastic property like conventional cheese, promoting the application of zein. Our study prepared zein-based cheese containing different concentrations (0-30 %) of highland barley β-glucan (HBG) as a fat replacer. Increased HBG caused smaller and more uniform oil droplets in zein network. SAXS pattern implied Rg decreased from 0.936 nm to 0.567 nm with increased HBG concentration. The stretchability of Cheddar and Violife cheese was 23.69 cm and 6.72 cm, respectively, while that of zein-based cheese added with HBG was 7.76-16.47 cm. The melting behavior of zein-based cheese did not fully mimic Cheddar cheese, but those of HBG5 and HBG10 were more comparable than Violife cheese. Violife cheese lacked hardness and gumminess compared to Cheddar cheese, while more similarities in textural properties were observed between Cheddar and zein-based cheese added with 10 % HBG. Our results provide opportunities in creating meltable low-fat plant-based cheese.

Identifying Chemical Differences in Cheddar Cheese Based on Maturity Level and Manufacturer Using Vibrational Spectroscopy and Chemometrics

Cheese is a nutritious dairy product and a valuable commodity. Internationally, cheddar cheese is produced and consumed in large quantities, and it is the main cheese variety that is exported from Australia. Despite its importance, the analytical methods to that are used to determine cheese quality rely on traditional approaches that require time, are invasive, and which involve potentially hazardous chemicals. In contrast, spectroscopic techniques can rapidly provide molecular information and are non-destructive, fast, and chemical-free methods. Combined with partner recognition methods (chemometrics), they can identify small changes in the composition or condition of cheeses. In this work, we combined FTIR and Raman spectroscopies with principal component analysis (PCA) to investigate the effects of aging in commercial cheddar cheeses. Changes in the amide I and II bands were the main spectral characteristics responsible for classifying commercial cheddar cheeses based on the ripening time and manufacturer using FTIR, and bands from lipids, including β'-polymorph of fat crystals, were more clearly determined through changes in the Raman spectra.

Use of probiotic yeasts with biocontrol activity for fermentation of ewe's milk

BACKGROUND

There are sufficient scienctific studies that support the benefit that fermented dairy products produce in those who consume them. Traditionally, cow's milk has been the most commonly used milk but there is a growing interest in the development of new dairy products, substituting cow's milk with milk from other sources, as well as in the use of microorganisms in fermentation to replace artificial preservatives or treatments that may affect the chemical and organoleptic characteristics of the product. For these reasons, the aim of the present work was to understand the behavior of five potential probiotic yeasts during the fermentation of ewe's milk and to consider their potential use as biocontrol agents.

RESULTS

Saccharomyces cerevisiae 3 and Hanseniaspora osmophila 1056 provided the most promising kinetic parameters in the different salt, temperature and pH conditions tested in their technological characterization. The profiles of organic acids and volatile compounds after the fermentation period was noteworthy for contributing to the final aroma of the dairy product. Sensory analysis revealed the sour taste of all samples, and S. cerevisiae 3, Lachancea thermotolerans 1039, and H. osmophila 1056 stood out for an accentuated cheese flavor. In addition, all strains showed biocontrol activity; they reduced the mycelium of the mycotoxigenic molds.

CONCLUSION

Saccharomyces cerevisiae 3 and H. osmophila 1056 could be inoculated along with bacterial starters to provide a functional fermented beverage with improved flavor. These strains also have an added value as they act as biocontrol agents. © 2022 Society of Chemical Industry.

Validation of the Methods for the Non-Milk Fat Detection in Artificially Adulterated Milk with Palm Oil

Dairy products are among the most adulterated food products. Due to the current high price of milk fat, it has been replaced by low-cost oils, especially those oils that have the same fatty acid profile as milk fat. This study intends to confirm the lowest level of palm oil added to milk and validate various methods for detecting palm oil in milk, including gas chromatography, reverse-phase high performance liquid chromatography, and Fourier transform infrared. Different amounts of palm oil were prepared in the final liquid milk using five treatments of fresh milk cream and an emulsion of palm oil. The results of this study showed that the values of the saponification number decreased with the increase in the percentages of added palm oil. There was no decrease under the limits of the Egyptian standards until the addition of 50% palm oil. The iodine number is less sensitive than the saponification number in the detection of palm oil. Butyro refractometer reading is unable to detect the palm oil in milk. The fatty acid profile in milk determined by gas chromatography correlated well with the addition of palm oil. Furthermore, there is a positive relationship between the level of added palm oil and the β-sitosterol content as measured by reverse-phase high-performance liquid chromatography. There was no relationship between the behavior of the spectra resulting from Fourier transform infrared spectroscopy and the presence of palm oil.

Monitoring Turkish white cheese ripening by portable FT-IR spectroscopy

The biochemical metabolism during cheese ripening plays an active role in producing amino acids, organic acids, and fatty acids. Our objective was to evaluate the unique fingerprint-like infrared spectra of the soluble fractions in different solvents (water-based, methanol, and ethanol) of Turkish white cheese for rapid monitoring of cheese composition during ripening. Turkish white cheese samples were produced in a pilot plant scale using a mesophilic culture (Lactococcus lactis subsp. lactis, Lactococcus lactis subsp. cremoris), ripened for 100 days and samples were collected at 20-day intervals for analysis. Three extraction solvents (water, methanol, and ethanol) were selected to obtain soluble cheese fractions. Reference methods included gas chromatography (amino acids and fatty acid profiles), and liquid chromatography (organic acids) were used to obtain the reference results. FT-IR spectra were correlated with chromatographic data using pattern recognition analysis to develop regression and classification predictive models. All models showed a good fit (R_Pre ≥ 0.91) for predicting the target compounds during cheese ripening. Individual free fatty acids were predicted better in ethanol extracts (0.99 ≥ R_Pre ≥ 0.93, 1.95 ≥ SEP ≥ 0.38), while organic acids (0.98 ≥ R_Pre ≥ 0.97, 10.51 ≥ SEP ≥ 0.57) and total free amino acids (R_Pre = 0.99, SEP = 0.0037) were predicted better by using water-based extracts. Moreover, cheese compounds extracted with methanol provided the best SIMCA classification results in discriminating the different stages of cheese ripening. By using a simple methanolic extraction and collecting spectra with a portable FT-IR device provided a fast, simple, and cost-effective technique to monitor the ripening of white cheese and predict the levels of key compounds that play an important role in the biochemical metabolism of Turkish white cheese.

Evaluation of Portable Vibrational Spectroscopy Sensors as a Tool to Detect Black Cumin Oil Adulteration

Black cumin oil adulteration has become a concern because it has numerous health benefits and a high price. Therefore, a simple, non-destructive, and rapid method to identify adulterations in black seed oil is necessary to protect the quality of the oils. This study aimed to perform a non-invasive method to authenticate black cumin oil by portable FT-NIR, FT-MIR, and Raman spectrometers. Spectra were collected with portable devices and analyzed using Soft Independent Modelling of Class Analogy (SIMCA) to generate a classification model to identify pure black cumin oil and partial least squares regression (PLSR) to predict the adulterant levels. For confirmation, the fatty acid profile of the oils was determined by gas chromatography (GC). SIMCA and PLSR models provided a very high performance in detecting adulterated samples in all portable units. These portable units showed great potential for rapid and non-destructive monitoring to identify adulterated black cumin oils.

Monitoring the ripening attributes of Turkish white cheese using miniaturized vibrational spectrometers

Monitoring the ripening process by prevalent analytic methods is laborious, expensive, and time consuming. Our objective was to develop a rapid and simple method based on vibrational spectroscopic techniques to understand the biochemical changes occurring during the ripening process of Turkish white cheese and to generate predictive algorithms for the determination of the content of key cheese quality and ripening indicator compounds. Turkish white cheese samples were produced in a pilot plant scale and ripened for 100 d, and samples were analyzed at 20 d intervals during storage. The collected spectra (Fourier-transform infrared, Raman, and near-infrared) correlated with major composition characteristics (fat, protein, and moisture) and primary products of the ripening process and analyzed by pattern recognition to generate prediction (partial least squares regression) and classification (soft independent analysis of class analogy) models. The soft independent analysis of class analogy models classified cheese samples based on the unique biochemical changes taking place during the ripening process. partial least squares regression models showed good correlation (R_Pre = 0.87 to 0.98) between the predicted values by vibrational spectroscopy and the reference values, giving low standard errors of prediction (0.01 to 0.57). Portable and handheld vibrational spectroscopy units can be used as a rapid, simple, and in situ technique for monitoring the quality of cheese during aging and provide real-time tools for addressing deviations in manufacturing.

FT-MIR Analysis of Water-Soluble Extracts during the Ripening of Sheep Milk Cheese with Different Phospholipid Content

The purpose of this work was to study the suitability of the water-soluble extracts (WSE) of semi-hard sheep milk cheese for analysis by diffuse reflectance Fourier transform mid-infrared spectroscopy (FT-MIR) and the development of classification models using discriminant analysis and based on cheese age or phospholipid content. WSE was extracted from three types of sheep milk cheeses (full-fat, reduced-fat and reduced-fat fortified with lyophilized sweet sheep buttermilk) at various stages of ripening from six to 168 days and lyophilized. The first model used 1854–1381 and 1192–760 cm−1 regions of the first-derivative spectra and successfully differentiated samples of different age, based on changes in the water-soluble products of ripening biochemical events. The second model used the phospholipid absorbance spectral regions (3012–2851, 1854–1611 and 1192–909 cm−1) to successfully discriminate cheeses of markedly different phospholipid content. Cheese WSE was found suitable for FT-MIR analysis. According to the results, a fast and simple method to monitor cheese ripening based on water-soluble substances has been developed. Additionally, the results indicated that a considerable amount of phospholipids migrates to the cheese WSE and that FT-MIR can be a useful tool for their assessment.

Mid-Infrared Spectroscopy as a Valuable Tool to Tackle Food Analysis: A Literature Review on Coffee, Dairies, Honey, Olive Oil and Wine

Nowadays, food adulteration and authentication are topics of utmost importance for consumers, food producers, business operators and regulatory agencies. Therefore, there is an increasing search for rapid, robust and accurate analytical techniques to determine the authenticity and to detect adulteration and misrepresentation. Mid-infrared spectroscopy (MIR), often associated with chemometric techniques, offers a fast and accurate method to detect and predict food adulteration based on the fingerprint characteristics of the food matrix. In the first part of this review the basic concepts of infrared spectroscopy, sampling techniques, as well as an overview of chemometric tools are summarized. In the second part, recent applications of MIR spectroscopy to the analysis of foods such as coffee, dairy products, honey, olive oil and wine are discussed, covering a timespan from 2010 to mid-2020. The literature gathered in this article clearly reveals that the MIR spectroscopy associated with attenuated total reflection acquisition mode and different chemometric tools have been broadly applied to address quality, authenticity and adulteration issues. This technique has the advantages of being simple, fast and easy to use, non-destructive, environmentally friendly and, in the future, it can be applied in routine analyses and official food control.

Understanding the effect of milk composition and milking season on quality characteristics of chhana

The quality characteristics of chhana varied due to the milk composition (cow‐, buffalo‐, and mixed‐ milk) which in turn was affected by the milking season (summer and winter). Upon heating and acidification of milk samples water holding phenomena and denatured protein association within and with other components lead to variation in both macroscale properties (color, texture, and rheology) and molecular bonding patterns (FTIR character). Yield, lightness (L* value), textural firmness, and elastic modulus of chhana increased with increasing proportion of buffalo milk in mixed milk due to higher total solids and less moisture content in both the seasons. Total protein, fat, water, and interaction between them and extent of hydrogen bonding significantly affected the rheological and textural properties of chhana samples.

Chemometric analysis combined with FTIR spectroscopy of milk and Halloumi cheese samples according to species' origin

Food adulteration is an issue of major concern, as numerous foodstuffs and beverages do not follow their labeling. Our research interest is in the field of authenticity of dairy products and particularly cheese. Adulteration of dairy products is a well-known phenomenon, and there are numerous published studies specifically on the authenticity of cheese. In fact, substitution of a portion of fat and/or proteins, adulteration with milk of other species' origin, and mislabeling of ingredients are some of the main issues that the science of dairy products' authenticity is regularly facing. Discrimination of dairy products can be determined through several chemical or microbiological methods as presented in the literature. In addition, chemometric analysis is an important tool for interpretation of a huge load of measurements. The aim of this study is to discriminate between various milk samples, which is the primary ingredient of dairy products. Milk samples with different trademarks were analyzed. That data was combined with Halloumi cheese samples for chemometric discrimination of species' origin. The innovative point of this study is the fact that it is the first time that a research study related to dairy products includes Halloumi cheese which is a traditional Cypriot cheese, not well-studied until now. The first step of the methodology was the freeze-drying via lyophilization of the samples. Fourier transformed infrared spectroscopy (FTIR) was chosen for their chemical characterization. Moreover, interpretation of the measurements was carried out by chemometric analysis using SIMCA software. For this study, FTIR data combined with chemometrics have given a very good discrimination of the samples according to their species' origin. Chemometric methods such as PCA and OPLS-DA have been used with great success. In the future, this model will be studied regarding geographical origin of the samples.

Quantitative Identification of Adulterated Sichuan Pepper Powder by Near-Infrared Spectroscopy Coupled with Chemometrics

Sichuan pepper is a traditional and important flavoring of Chinese cuisine. It has attracted increasing interest in recent years owning to its unique taste and aroma. However, some cheap adulterants have been illegally found in Sichuan pepper powder in the market due to merchants trying to cut costs and gain an extra profit. In order to determine the compositions of Sichuan pepper powder quickly and effectively, a direct detection method using near-infrared (NIR) spectroscopy has been developed. 462 samples of adulterated Sichuan pepper powder mixed with different amounts of wheat bran, rice bran, corn flour, and rosin powder were studied. The NIR spectra data was studied using partial least squares (PLS) analysis. The method was found to be capable of predicting the compositions of adulterated Sichuan pepper powder. The determination coefficients of prediction set (Rp2) with the best pretreatments were 0.971 for Sichuan pepper powder, 0.948 for rice bran, 0.969 for wheat bran, 0.967 for corn flour, and 0.994 for rosin powder, respectively. The standard errors of prediction (SEP) were 2.81%, 2.38%, 3.19%, 2.46%, and 1.10%, respectively. The results showed that NIR spectroscopy with chemometrics is a rapid and nondestructive tool for the quantitative analysis of adulterated Sichuan pepper powder.

The feasibility of using near-infrared spectroscopy and chemometrics for untargeted detection of protein adulteration in yogurt: removing unwanted variations in pure yogurt

Untargeted detection of protein adulteration in Chinese yogurt was performed using near-infrared (NIR) spectroscopy and chemometrics class modelling techniques. sixty yogurt samples were prepared with pure and fresh milk from local market, and 197 adulterated yogurt samples were prepared by blending the pure yogurt objects with different levels of edible gelatin, industrial gelatin, and soy protein powder, which have been frequently used for yogurt adulteration. A recently proposed one-class partial least squares (OCPLS) model was used to model the NIR spectra of pure yogurt objects and analyze those of future objects. To improve the raw spectra, orthogonal projection (OP) of raw spectra onto the spectrum of pure water and standard normal variate (SNV) transformation were used to remove unwanted spectral variations. The best model was obtained with OP preprocessing with sensitivity of 0.900 and specificity of 0.949. Moreover, adulterations of yogurt with 1% (w/w) edible gelatin, 2% (w/w) industrial gelatin, and 2% (w/w) soy protein powder can be safely detected by the proposed method. This study demonstrates the potential of combining NIR spectroscopy and OCPLS as an untargeted detection tool for protein adulteration in yogurt.