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

Castada, Hardy Z.; Hanas, Kaitlyn; Barringer, Sheryl A.

doi:10.3390/foods8020078

Cited by 43 publications

(32 citation statements)

References 82 publications

(117 reference statements)

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“…A reaction of one-step transesterification is effective in synthesizing lactones from hydroxylated FFAs [28]. These mechanisms heavily and quite positively affect the cheese flavor, since lactones are associated with very pronounced fruity notes, although they have been found to also contribute in cheese to the buttery character [59]. The synthesis of lactones leads to the release of αand β-lactones that are reported to be highly reactive and unstable, while γand δ-lactones are stable and have been identified in several dairy products.…”

Section: Lactonesmentioning

confidence: 99%

Volatile Flavor Compounds in Cheese as Affected by Ruminant Diet

et al. 2020

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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.

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Section: Lactonesmentioning

confidence: 99%

Volatile Flavor Compounds in Cheese as Affected by Ruminant Diet

et al. 2020

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“…Principal component analysis (PCA) is an orthogonal projection of the data onto a lower-dimensional space such that the variance of the projected data is maximized [52,53]. This method has been widely used in sensory analysis [54,55,56,57,58,59,60,61]. Furthermore, it is a core component of the internal and external preference mappings.…”

Section: Methodsmentioning

confidence: 99%

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

Sánchez

Domínguez-Soberanes

Escalona‐Buendía

et al. 2019

Foods

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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.

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“…Using selected ion scan mode, HCN was measured using the H 3 O + precursor ion to detect a protonated HCNH + at m/z 28 with a reaction rate, k, of 3.8 × 10 −9 cm 3 s −1 . SIFT-MS has recently been used for the headspace analysis of various compounds in different food (oil, cheese, and garlic) and breath matrices [29][30][31][32][33][34]. For the headspace detection of HCN using SIFT-MS, 0.100 g of Macadamia flowers, leaves, husks, or defatted nuts sample was weighed into individual 500 mL Schott bottles.…”

Section: Headspace Cyanide Analysis Using Sift-msmentioning

confidence: 99%

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

Castada

Liu

Barringer

et al. 2020

Foods

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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.

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

Cited by 43 publications

References 82 publications

Volatile Flavor Compounds in Cheese as Affected by Ruminant Diet

Volatile Flavor Compounds in Cheese as Affected by Ruminant Diet

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

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

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