Swiss Cheese Flavor Variability Based on Correlations of Volatile Flavor Compounds, Descriptive Sensory Attributes, and Consumer Preference

Description of Ewiss cheese, a new ewe milk cheese processed by Swiss cheese manufacturing techniques: Microbiological, physicochemical, and sensory aspects

Typically, Swiss-type cheese is made from cow milk. However, in the present work an attempt to expand the sheep supply chain and product offering in this field was made by developing a new type of cheese using Swiss-type cheese technology. The cheese was manufactured under industrial conditions, and fermentations were carried out using freeze-dried commercial starters that are traditionally used in the production of Swiss cheese. Two experimental "Ewiss cheese" (EC) products were produced using raw milk (RM) and pasteurized milk (PM), respectively. Fourteen microbial groups were investigated by plate counts from curd until ripened cheeses. According to microbiological analyses, no statistically significant differences were found between the 2 productions with respect to the group of lactic acid bacteria (LAB). The curds were mainly characterized by mesophilic LAB cocci (7.45 log10 cfu/g in RM-EC and 7.33 log10 cfu/g in PM-EC). However, at the end of the ripening period (9 mo), the cheeses exhibited a higher presence of mesophilic LAB rods. Undesired microbiological groups were found only in the curd of raw milk cheese in the range of 104 to 105 cfu/g, but they were reaching undetectable levels by plate count in the cheese at the end of ripening. The RM-EC and PM-EC were characterized by 76% and 68% of DM, respectively. These cheeses contained 29.30% and 34.36% of protein, and 51.31% and 50.38% of fat, respectively. Textural analysis showed differences in terms of hardness, chewiness, and gumminess between the experimental cheeses and Swiss cheese sold on the market. These differences could be attributed to the higher protein content of ewe milk. The main fatty acids in the cheeses were palmitic acid, myristic acid, oleic acid, and capric acid. Among the organic acids, RM-EC had higher concentrations of lactic acid, whereas PM-EC was higher in propionic acid. The ewe cheeses emitted 46 volatile compounds, including acids, aldehydes, ketones, esters, alcohols, and other compounds. The PM-EC was characterized by the main compounds of Swiss-type cheese: acetic acid, butyric acid, ethyl butyrate, ethyl caproate, propanoic acid, and tetramethylpyrazine. Sensory evaluation showed that the new dairy products were generally appreciated, and PM-EC was the most preferred by the judges. This research has enabled the development of new ewe milk products, which could stimulate the valorization of a sector that has been long neglected and still has a large margin of improvement.

Production of a Cheese-Like Aroma via Fermentation of Plant Proteins and Coconut Oil with the Basidiomycetes Cyclocybe aegerita and Trametes versicolor

Cheese is one of the most common dairy products and is characterized by its complex aroma. However, in times of climate change and resource scarcity, the possibility to mimic the characteristic cheese-like aroma from plant-based sources is in demand to offer alternatives to cheese. Accordingly, the production of a natural cheese-like aroma via fermentation of four plant-based proteins and coconut oil with basidiomycetes has been addressed. Mixtures of soy and sunflower protein with coconut oil (15 g/L) have shown the formation of a cheese-like aroma after 72 and 56 h after fermentation with Cyclocybe aegerita and Trametes versicolor, respectively. Isovaleric acid, butanoic acid, ethyl butanoate, 1-octen-3-ol, and various ketones were identified as the key odorants. Similarities to typical cheeses were observed by the principal component analysis. Overall, the finding offered an approach to a sustainable production of a natural cheese-like aroma from a plant source, thus contributing to the development of cheese alternatives.

Analysis of Volatile Compounds in Processed Cream Cheese Models for the Prediction of "Fresh Cream" Aroma Perception

Controlling flavor perception by analyzing volatile and taste compounds is a key challenge for food industries, as flavor is the result of a complex mix of components. Machine-learning methodologies are already used to predict odor perception, but they are used to a lesser extent to predict aroma perception. The objectives of this work were, for the processed cream cheese models studied, to (1) analyze the impact of the composition and process on the sensory perception and VOC release and (2) predict "fresh cream" aroma perception from the VOC characteristics. Sixteen processed cream cheese models were produced according to a three-factor experimental design: the texturing agent type (κ-carrageenan, agar-agar) and level and the heating time. A R-A-T-A test on 59 consumers was carried out to describe the sensory perception of the cheese models. VOC release from the cheese model boli during swallowing was investigated with an in vitro masticator (Oniris device patent), followed by HS-SPME-GC-(ToF)MS analysis. Regression trees and random forests were used to predict "fresh cream" aroma perception, i.e., one of the main drivers of liking of processed cheeses, from the VOC release during swallowing. Agar-agar cheese models were perceived as having a "milk" odor and favored the release of a greater number of VOCs; κ-carrageenan samples were perceived as having a "granular" and "brittle" texture and a "salty" and "sour" taste and displayed a VOC retention capacity. Heating induced firmer cheese models and promoted Maillard VOCs responsible for "cooked" and "chemical" aroma perceptions. Octa-3,5-dien-2-one and octane-2,3-dione were the two main VOCs that contributed positively to the "fresh cream" aroma perception. Thus, regression trees and random forests are powerful statistical tools to provide a first insight into predicting the aroma of cheese models based on VOC characteristics.

A machine learning method for juice human sensory hedonic prediction using electronic sensory features

This study proposed a method that combines fused electronic sensory analysis technology with artificial neural network to predict the human sensory hedonic of fruit juice. Quantitative descriptive analysis (QDA) and the scoring test method were utilized for human sensory evaluation. The first step involved modeling the fused e-sensory features with human sensory attributes, followed by establishing a fitting model of human sensory attributes and acceptance. The R2 and RMSE values obtained were 0.77 and 0.42 (QDA method), and 0.63 and 0.63 (scoring test method). Finally, the relationship between the fusion e-sensory features and the human sensory hedonic was established. Model-1 achieved an R2 of 0.95 and an RMSE of 0.04, while model-2 achieved an R2 value of 0.88 and an RMSE value of 0.21. This study demonstrates the potential of fusing e-sensory technologies to replace human senses, which may lead to the development of devices with simultaneous multiple senses.

Identification of Corrosive Volatile Compounds Found in the Headspace of Chicken Noodle Soup Retorted in Metal Cans

This study investigated the development of volatile compounds in the headspace of canned chicken noodle soup (and sought to develop appropriate testing methods). The primary objective of this study was to identify compounds in the soup that were responsible for the initiation of the corrosion in the cans. The long-term goal of these studies is to develop an efficient method to investigate how headspace volatile compounds in foods could cause corrosion defects in metal cans and how these could be corrected without undermining the quality and safety of the food. To determine and to evaluate the volatile compounds in the canned soups, selected ion flow tube-mass spectrometry (SIFT-MS) was used. The coatings of the tested cans were carefully stripped off and analyzed using this SIFT-MS method. High levels of sulfur-containing volatile compounds and organic acids were detected in both the soups and the coatings. It was concluded that during the retorting of the sealed cans filled with chicken soup, sulfur-containing volatile compounds formed and entered the headspace of the tested cans and interacted with the coating, leading to the formation of blackened stains.

Mitigation of undesirable volatile aroma compounds in kefir by freeze drying and vacuum evaporation

Commercial kefir was recently found to be effective in curing recurrent Clostridioides difficile infection when consumed alongside antibiotic treatment. However, kefir products have limited acceptance among Western consumers due to their characteristic flavor and texture. Plain, unsweetened commercial kefir with 1% milkfat was subjected to vacuum evaporation and freeze-drying processes to assess the effect on volatile organic compound concentration, sensory quality, and microbial viability. Vacuum evaporation and freeze-drying both significantly decreased the concentration of 26 out of 27 volatiles in the kefir (p < 0.05), by an average of 61%. Vacuum evaporation exhibited an apparent greater reduction than freeze-drying in the concentrations of the ketones and aldehydes, while freeze-drying showed a more noticeable reduction in the concentrations of the acids, alcohols, and esters. While lowering the concentration of volatiles did not significantly improve the average consumer acceptance of commercial kefir, both treatments showed differences in the range of acceptability responses. Both treatments also produced a small but significant reduction in the concentrations of Lactobacillus and Lactococcus species present.

Impact of LAB from Serpa PDO Cheese in Cheese Models: Towards the Development of an Autochthonous Starter Culture

Serpa is a protected designation of origin (PDO) cheese produced with raw ewes' milk and coagulated with Cynara cardunculus. Legislation does not allow for milk pasteurization and starter culture inoculation. Although natural Serpa's rich microbiota allows for the development of a unique organoleptic profile, it also suggests high heterogeneity. This raises issues in the final sensory and safety properties, leading to several losses in the sector. A possible solution to overcoming these issues is the development of an autochthonous starter culture. In the present work, some Serpa cheese Lactic acid bacteria (LAB)-isolated microorganisms, previously selected based on their safety, technological and protective performance, were tested in laboratory-scale cheeses. Their acidification, proteolysis (protein and peptide profile, nitrogen fractions, free amino acids (FAA)), and volatiles generation (volatile fatty acids (VFA) and esters) potential was investigated. Significant differences were found in all parameters analyzed, showing a considerable strain effect. Successive statistical analyses were performed to compare cheese models and Serpa PDO cheese. The strains L. plantarum PL1 and PL2 and the PL1 and L. paracasei PC mix were selected as the most promising, resulting in a closer lipolytic and proteolytic profile of Serpa PDO cheese. In future work, these inocula will be produced at a pilot scale and tested at the cheese level to validate their application.

Evolution of Volatile Compounds during Ripening and Final Sensory Changes of Traditional Raw Ewe’s Milk Cheese “Torta del Casar” Maturated with Selected Protective Lactic Acid Bacteria

In traditional soft ripened cheeses made with raw milk, the use of protective cultures is infrequent. In the present work, the effect of selected (for their activity against Listeria monocytogenes) protective cultures of Lactocaseibacillus casei 116 and Lactococcus garvieae 151 was evaluated, on the evolution of volatile compounds throughout the ripening and on the final sensory characteristics of traditional soft ripened “Torta del Casar” cheese. For this, both strains were separately inoculated in raw cheeses and ripened for 90 days. The selected LAB strains did not affect physicochemical parameters, including texture and color of the ripened cheeses. However, they could have a positive effect on the aroma, for the generation of methyl branched acids and for the reduction in compounds derived from β-oxidation of fatty acids. Thus, these protective cultures, in addition to contributing to their safety, could improve quality of the ripened cheeses.

Physiological roles of hydrogen sulfide in mammalian cells, tissues and organs

H2S belongs to the class of molecules known as gasotransmitters, which also includes nitric oxide (NO) and carbon monoxide (CO). Three enzymes are recognized as endogenous sources of H2S in various cells and tissues: cystathionine g-lyase (CSE), cystathionine β-synthase (CBS) and 3-mercaptopyruvate sulfurtransferase (3-MST). The current article reviews the regulation of these enzymes as well as the pathways of their enzymatic and non-enzymatic degradation and elimination. The multiple interactions of H2S with other labile endogenous molecules (e.g. NO) and reactive oxygen species are also outlined. The various biological targets and signaling pathways are discussed, with special reference to H2S and oxidative posttranscriptional modification of proteins, the effect of H2S on channels and intracellular second messenger pathways, the regulation of gene transcription and translation and the regulation of cellular bioenergetics and metabolism. The pharmacological and molecular tools currently available to study H2S physiology are also reviewed, including their utility and limitations. In subsequent sections, the role of H2S in the regulation of various physiological and cellular functions is reviewed. The physiological role of H2S in various cell types and organ systems are overviewed. Finally, the role of H2S in the regulation of various organ functions is discussed as well as the characteristic bell-shaped biphasic effects of H2S. In addition, key pathophysiological aspects, debated areas, and future research and translational areas are identified A wide array of significant roles of H2S in the physiological regulation of all organ functions emerges from this review.

Volatile fingerprint of food products with untargeted SIFT-MS data coupled with mixOmics methods for profile discrimination: Application case on cheese

Volatile organic compounds (VOCs) emitted by food products are decisive for the perception of aroma and taste. The analysis of gaseous matrices is traditionally done by detection and quantification of few dozens of characteristic markers. Emerging direct injection mass spectrometry technologies offer rapid analysis based on a soft ionisation of VOCs without previous separation. The recent increase of selectivity offered by the use of several precursor ions coupled with untargeted analysis increases the potential power of these instruments. However, the analysis of complex gaseous matrix results in a large number of ion conflicts, making the quantification of markers difficult, and in a large volume of data. In this work, we present the exploitation of untargeted SIFT-MS volatile fingerprints of ewe PDO cheeses in a real farm model, using mixOmics methods allowing us to illustrate the typicality, the manufacturing processes reproducibility and the impact of the animals' diet on the final product.

Comparative Analysis and Development of a Flavor Fingerprint for Volatile Compounds of Vegetable Soybean Seeds Based on Headspace-Gas Chromatography-Ion Mobility Spectrometry

Evaluating the volatile compounds and characteristic fingerprints of the core cultivars of vegetable soybean would provide useful data for improving their aroma in the breeding programs. The present study used headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to evaluate the volatile compounds of vegetable soybean seeds at a specific growth stage. In total, 93 signal peaks were identified, 63 compounds qualitatively, with 14 volatile flavor compounds providing multiple signals. The 63 volatile compounds consisted of 15 esters, 15 aldehydes, 13 alcohols, 15 ketones, one acid, and four other compounds. The peak intensity of most of the volatile compounds varied greatly between the core cultivars. The alcohols and aldehydes determined the basic volatile flavor of the vegetable soybean seeds. Volatile flavors were determined by their respective esters, ketones, or other components. Characteristic fingerprints were found in some core vegetable soybean cultivars. Four cultivars (Xiangdou, ZHE1754, Zhexian 65018-33, and Qvxian No. 1) had pleasant aromas, because of their higher content of 2-acetyl-1-pyrroline (2-AP). A principal component analysis (PCA) was used to distinguish the samples based on the signal intensity of their volatile components. The results showed that the composition and concentration of volatile compounds differed greatly between the core cultivars, with the volatile flavor compounds of soybeans being determined by the ecotype of the cultivar, the direction of breeding selection, and their geographical origin. Characteristic fingerprints of the cultivars were established by HS-GC-IMS, enabling them to be used to describe and distinguish cultivars and their offspring in future breeding studies.

Relationship between Sensory Attributes, (Dis) Liking and Volatile Organic Composition of Gorgonzola PDO Cheese

Blue-veined cheese tends to polarize the consumers' affective responses due to its strong flavor. This study aims to: (i) explore the consumers' sensory perceptions and liking of Gorgonzola PDO cheese; (ii) identify the sensory drivers of acceptance for Gorgonzola in the function of the cheese style; (iii) characterize them by the volatile organic compounds (VOCs); and (iv) explore the relationships of the VOCs with sensory perception and liking. Six samples of Gorgonzola cheese differing in style (sweet vs. piquant), aging time (70-95 days), and production process (artisanal vs. industrial) were evaluated by 358 subjects (46% males, 18-77 years) using liking and Rate-All-That-Apply (RATA) tests. The cheese VOCs were measured by SPME/GC-MS. Liking was significantly higher for the sweet cheese than for the piquant cheese and for the artisanal cheese than for the industrial samples. Penalty Analysis showed that 'creamy', 'sweet', 'nutty', and 'salty' were significant drivers of liking while the 'soapy' and 'ammonia' flavors turned out to be drivers of disliking. Fifty-three VOCs were identified. Regression models revealed the significant highest associations between the VOCs and 'ammonia', 'pungent', 'soapy', and 'moldy' flavors. A good association was also found with the consumers' liking. The identification of the sensory drivers of (dis) liking and their relationship with the VOCs of Gorgonzola opens up a new understanding of the consumers' blue-veined cheese preferences.

A Review on the General Cheese Processing Technology, Flavor Biochemical Pathways and the Influence of Yeasts in Cheese

Cheese has a long history and this naturally fermented dairy product contains a range of distinctive flavors. Microorganisms in variety cheeses are an essential component and play important roles during both cheese production and ripening. However, cheeses from different countries are still handmade, the processing technology is diverse, the microbial community structure is complex and the cheese flavor fluctuates greatly. Therefore, studying the general processing technology and relationship between microbial structure and flavor formation in cheese is the key to solving the unstable quality and standardized production of cheese flavor on basis of maintaining the flavor of cheese. This paper reviews the research progress on the general processing technology and key control points of natural cheese, the biochemical pathways for production of flavor compounds in cheeses, the diversity and the role of yeasts in cheese. Combined with the development of modern detection technology, the evolution of microbial structure, population evolution and flavor correlation in cheese from different countries was analyzed, which is of great significance for the search for core functional yeast microorganisms and the industrialization prospect of traditional fermented cheese.

Formation of 3-Methylbutanal and 3-Methylbutan-1-ol Recognized as Malty during Fermentation in Swiss Raclette-Type Cheese, Reconstituted Milk, and de Man, Rogosa, and Sharpe Broth

This work aimed to determine the formation over time of 3-methylbutanal and 3-methylbutan-1-ol recognized as malty during the manufacture of Raclette-type cheese and the fermention of reconstituted skim milk, and filter-sterilized MRS broth. Using dynamic headspace-vacuum transfer in trap extraction followed by gas chromatography coupled with mass spectrometry-olfactometry (DHS-VTT-GC-MS-O) as a screening method for the malty compounds, five compounds (2-methylpropanal, 2- and 3-methylbutanal, and 2- and 3-methylbutan-1-ol) were identified as potential compounds causing the malty aroma in starter culture development and Raclette-type cheeses. Focus on compounds having a predominant sensorial effect (3-methylbutanal and 3-methylbutan-1-ol), spikings of leucine, ¹³C-labeled leucine, α-ketoisocaproic acid, and α-ketoglutaric acid provided a better understanding of their formation pathway. This study highlighted the discrepancies in the formation of 3-methylbutanal and 3-methylbutan-1-ol between the growth media; namely, despite the presence of free leucine available in MRS and the addition of an excess, no increase of the target compounds was observed. The concentration of these compounds in MRS increased only when α-ketoglutaric acid or α-ketoisocaproic acid was added, and a preference for the pathway to α-hydroxyisocaproic acid instead of 3-methylbutanal was shown. In addition, a formation of 3-methylbutanal when the bacteria were not yet active was observed when spiking α-ketoisocaproic acid, which potentially indicates that this part of the metabolism could take place extracellularly. These results could potentially unveil other, not-yet-identified reactants, directly influencing the production of compounds responsible for the malty aroma in Raclette cheese.

Determination of changes in the microbial and chemical composition of Țaga cheese during maturation

Țaga cheese is a traditional Romanian smear-ripened cheese made from bovine milk and identified with the name of the village and caves where it is produced. As no previously reported microbiological and chemical studies have been undertaken on this product, this research aimed to investigate the microbiological and biochemical characteristics which ensure the uniqueness of Țaga cheese during the ripening process, to inform producers as to key quality determinants. Cheese samples, consisting of retail blocks, were collected on days 2, 5, 12, 18, and 25 of the ripening process. The evolution of lactic microbiota during the production and maturation of traditional cheeses involves isolating lactic acid microorganisms present in cheese. Cheese samples were analyzed for pH, fat, NaCl, fatty acids, and volatile compounds. The microbial ecosystem naturally changes during the maturation process, leading to variation in the microorganisms involved during ripening. Our results show that specific bacteria were identified in high levels during the entire ripening process and may be responsible for milk fat lipolysis contributing directly to cheese flavor by imparting detailed fatty acid flavor notes, or indirectly as precursors formation of other flavor compounds.

Physical, Nutritional, and Sensory Properties of Cheese Obtained from Goats Fed a Dietary Supplementation with Olive Leaves

Simple Summary

This study aims to investigate the effects of cheese obtained from goats fed a dietary supplementation with olive leaves. Thirty Saanen goats were allocated into two groups, (1) a control group that received a standard diet, and (2) an experimental group whose diet was supplemented with olive leaves. The results suggest a positive role of olive leaves in improving the cheese fatty acids composition and oxidative stability during ripening. Moreover, there were several variations in the development of volatile flavor compounds, even if no changes were evidenced in the sensory properties.

Abstract

The aim of this study is to evaluate the physical, nutritional, and sensory properties of cheese obtained from goats fed a dietary supplementation with olive leaves (OL). Thirty Saanen goats were randomly allocated into two groups of 15 goats each, (1) a control group fed with a standard diet (CG), and (2) an experimental group (EG) fed an OL-enriched diet. The trial lasted for 30 days. The milk of each group was then collected and used to produce Caciotta cheese, which was analyzed at the beginning and at the end of the ripening period (60 days). The results showed a positive effect of dietary OL supplementation in improving the fatty acid profiles due to the significant increase of unsaturated fatty acids, mostly α-linolenic acid (C18:3 n-3), with the consequent reduction of the ω-6/ω-3 ratio, a condition commonly associated with an increased health functionality of food products. Moreover, improved oxidative stability was observed in cheese during ripening, a presumable consequence of the transfer into the milk of dietary bioactive compounds, mainly polyphenols of high biological value, and credited as a marked antioxidant potential. Furthermore, reduced lipolytic action was observed in 60-day ripened cheese, even if no significant changes in sensory properties were evidenced.

Metabolomics for Evaluating Flavor-Associated Metabolites in Plant-Based Products

Plant-based diets (PBDs) are associated with environmental benefits, human health promotion and animal welfare. There is a worldwide shift towards PBDs, evident from the increased global demand for fresh plant-based products (PBPs). Such shifts in dietary preferences accompanied by evolving food palates, create opportunities to leverage technological advancements and strict quality controls in developing PBPs that can drive consumer acceptance. Flavor, color and texture are important sensory attributes of a food product and, have the largest influence on consumer appeal and acceptance. Among these, flavor is considered the most dominating quality attribute that significantly affects overall eating experience. Current state-of-art technologies rely on physicochemical estimations and sensory-based tests to assess flavor-related attributes in fresh PBPs. However, these methodologies often do not provide any indication about the metabolic features associated with unique flavor profiles and, consequently, can be used in a limited way to define the quality attributes of PBPs. To this end, a systematic understanding of metabolites that contribute to the flavor profiles of PBPs is warranted to complement the existing methodologies. This review will discuss the use of metabolomics for evaluating flavor-associated metabolites in fresh PBPs at post-harvest stage, alongside its applications for quality assessment and grading. We will summarize the current research in this area, discuss technical challenges and considerations pertaining to sampling and analytical techniques, as well as s provide future perspectives and directions for government organizations, industries and other stakeholders associated with the quality assessment of fresh PBPs.

A Deep Learning Method for Yogurt Preferences Prediction Using Sensory Attributes

During the development of innovative products, consumer preferences are the essential factors for yogurt producers to improve their market share. A high-performance prediction method will be beneficial to understand the intrinsic relevance between preferences and sensory attributes. In this study, a novel deep learning method is proposed that uses an autoencoder to extract product features from the sensory attributes scored by experts, and the sensory features acquired are regressed on consumer preferences with support vector machine analysis. Model performance analysis, hedonic contour mapping, and feature clustering were implemented to validate the overall learning process. The results showed that the deep learning model can vouch an acceptable level of accuracy, and the hedonic mapping reflected could supply a great help for producers’ product design or modification. Finally, hierarchical clustering analysis revealed that for all three brands of yogurts, low temperature (4 °C) storage for no more than 4 weeks can promise the highest consumer preferences.

Cyanogenesis in Macadamia and Direct Analysis of Hydrogen Cyanide in Macadamia Flowers, Leaves, Husks, and Nuts Using Selected Ion Flow Tube-Mass Spectrometry

Macadamia has increasing commercial importance in the food, cosmetics, and pharmaceutical industries. However, the toxic compound hydrogen cyanide (HCN) released from the hydrolysis of cyanogenic compounds in Macadamia causes a safety risk. In this study, optimum conditions for the maximum release of HCN from Macadamia were evaluated. Direct headspace analysis of HCN above Macadamia plant parts (flower, leaves, nuts, and husks) was carried out using selected ion flow tube-mass spectrometry (SIFT-MS). The cyanogenic glycoside dhurrin and total cyanide in the extracts were analyzed using HPLC-MS and UV-vis spectrophotometer, respectively. HCN released in the headspace was at a maximum when Macadamia samples were treated with pH 7 buffer solution and heated at 50 °C for 60 min. Correspondingly, treatment of Macadamia samples under these conditions resulted in 93%-100% removal of dhurrin and 81%-91% removal of total cyanide in the sample extracts. Hydrolysis of cyanogenic glucosides followed a first-order reaction with respect to HCN production where cyanogenesis is principally induced by pH changes initiating enzymatic hydrolysis rather than thermally induced reactions. The effective processing of different Macadamia plant parts is important and beneficial for the safe production and utilization of Macadamia-based products.

Volatile Flavor Compounds in Cheese as Affected by Ruminant Diet

Extensive research has been conducted concerning the determination and characterization of volatile compounds contributing to aroma and flavor in cheese. Considerable knowledge has been accumulated on the understanding of the mechanisms through which these compounds are formed during ripening, as well as on the optimization of the methodological approaches which lead to their detection. More recently, particular attention has been given to the aromatic properties of milk and cheeses obtained from lactating dairy ruminants fed experimental diets, characterized, for instance, by the addition of trace elements, natural supplements, or agricultural by-products rich in bioactive compounds. The purpose of this review is to summarize the major families of volatile compounds most commonly found in these types of dairy products at various ripening stages, describing in greater detail the role of animal diet in influencing the synthesis mechanisms most commonly responsible for cheese flavor determination. A large number of volatile compounds, including carboxylic acids, lactones, ketones, alcohols, and aldehydes, can be detected in cheese. The relative percentage of each compound depends on the biochemical processes that occur during ripening, and these are mainly mediated by endogenous enzymes and factors of bacterial origin whose function can be strongly influenced by the bioactive compounds taken by animals with the diet and released in milk through the mammary gland. Further evaluations on the interactions between volatile compounds and cheese matrix would be necessary in order to improve the knowledge on the synthesis mechanisms of such compounds; in addition to this, more should be done with respect to the determination of synergistic effects of flavor compounds, correlating such compounds to the aroma of dairy products.

"Cheese: Technology, Compositional, Physical and Biofunctional Properties:" A Special Issue

The objective of the present editorial to critical synopsize articles that make up the Special Issue “Cheese: Technology, Compositional, Physical and Biofunctional Properties.” The published research papers are multidisciplinary studies which refer to some of the most important sub-topics of Cheese Science and Technology. They present the results of experimental studies and analyses that can be further exploited by academia and cheese producers.

Liking Product Landscape: Going Deeper into Understanding Consumers' Hedonic Evaluations

The use of graphical mapping for understanding the comparison of products based on consumers’ perceptions is beneficial and easy to interpret. Internal preference mapping (IPM) and landscape segmentation analysis (LSA) have successfully been used for this propose. However, including all the consumers’ evaluations in one map, with products’ overall liking and attributes’ perceptions, is complicated; because data is in a high dimensional space some information can be lost. To provide as much information as possible, we propose the liking product landscape (LPL) methodology where several maps are used for representing the consumers’ distribution and evaluations. LPL shows the consumers’ distribution, like LSA, and also it superimposes the consumers’ evaluations. However, instead of superimposing the average overall liking in one map, this methodology uses different maps for each consumer’s evaluation. Two experiments were performed where LPL was used for understanding the consumers’ perceptions and compared with classic methodologies, IPM and cluster analysis, in order to validate the results. LPL can be successfully used for identifying consumers’ segments, consumers’ preferences, recognizing perception of product attributes by consumers’ segments and identifying the attributes that need to be optimized.