1H HRMAS-NMR based metabolic fingerprints for discrimination of cheeses based on sensory qualities

Kandasamy, Sujatha; Yoo, Jayeon; Yun, Jeonghee; Kang, Han Byul; Seol, Kuk-Hwan; Ham, Jun Sang

doi:10.1016/j.sjbs.2020.04.043

Cited by 20 publications

(8 citation statements)

References 25 publications

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“…The OPLS-DA model’s degree of fit (R2) and prediction capacity (Q2) were used to distinguish DM samples with significant differences ( Bhumireddy, Rocchetti, Pallerla, Lucini, & Sripadi, 2021 ). Higher values closer to 1 indicated better predictability and interpretability ( Kandasamy et al, 2020 ). Here, the parameters of the models R2X, R2Y, and Q2 were 0.971, 0.969, and 0.911, respectively ( Fig.…”

Section: Resultsmentioning

confidence: 99%

Influence of heating temperatures and storage on the odor of duck meat and identification of characteristic odorous smell compounds

Zhao,

Zhang,

Wang

et al. 2024

Food Chemistry: X

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Section: Resultsmentioning

confidence: 99%

Influence of heating temperatures and storage on the odor of duck meat and identification of characteristic odorous smell compounds

Zhao,

Zhang,

Wang

et al. 2024

Food Chemistry: X

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“…PCA is an unsupervised classification model, which continuously reduces the dimensions of multi-dimensional data into several main components (PCs) to describe the characteristics of the original data to the furthest extent possible [ 24 ]. On the other hand, the PLS-DA model and OPLS-DA model are supervised classification models, which can maximize the differences between groups according to the predefined classification and achieve a better separation effect than PCA [ 25 ]. However, supervised analytical models may produce the phenomenon of overfitting [ 26 ].…”

Section: Methodsmentioning

confidence: 99%

Relationship between amniotic fluid metabolic profile with fetal gender, maternal age, and gestational week

Sun

Zhang

et al. 2021

BMC Pregnancy Childbirth

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Background Amniotic fluid (AF) provides vital information on fetal development, which is also valuable in identifying fetal abnormalities during pregnancy. However, the relationship between the metabolic profile of AF in the second trimester of a normal pregnancy with several maternal–fetal parameters remains poorly understood, which therefore limits its application in clinical practice. The aim of this study was to explore the association between the metabolic profile of AF with fetal gender, maternal age, and gestational week using an untargeted metabolomics method. Methods A total of 114 AF samples were analyzed in this study. Clinical data on fetal gender, maternal age, and gestational week of these samples were collected. Samples were analyzed by gas chromatography/time-of-flight-mass spectrometry (GC-TOF/MS). Principal component analysis(PCA), orthogonal partial least square discrimination analysis(OPLS-DA) or partial least square discrimination analysis (PLS-DA) were conducted to compare metabolic profiles, and differential metabolites were obtained by univariate analysis. Results Both PCA and OPLS-DA demonstrated no significant separation trend between the metabolic profiles of male and female fetuses, and there were only 7 differential metabolites. When the association between the maternal age on AF metabolic profile was explored, both PCA and PLS-DA revealed that the maternal age in the range of 21 to 40 years had no significant effect on the metabolic profile of AF, and only four different metabolites were found. There was no significant difference in the metabolic profiles of AF from fetuses of 17–22 weeks, and 23 differential metabolites were found. Conclusions In the scope of our study, there was no significant correlation between the AF metabolic profile and the fetal gender, maternal age and gestational week of a small range. Nevertheless, few metabolites appeared differentially expressed.

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“…In cheese production process, ripening acts as an essential step in the enhancement of flavor and texture characteristics for any cheese variety. Depending upon the degree of proteolytic activity, the microbiota involved in cheese ripening accumulates free amino acids that might be precursors in the production of BAs [ 3 , 10 , 15 ]. Both starter and non-starter LAB involved in the manufacturing process, and/or contaminating microflora in the production, and ripening environments reported widely to produce BAs.…”

Section: Introductionmentioning

confidence: 99%

“…The health concerns over the food safety and healthy lifestyle forced many Koreans to consume cheeses produced from domestic farms. It is difficult for domestic manufacturers to compete against imported cheeses on price and quality [ 15 , 20 ]. The high popularity and demand on these products drive the assessment of their quality and health safety related to the content of BAs.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Biogenic Amines in Different Cheese Varieties Obtained from the Korean Domestic and Retail Markets

et al. 2021

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To evaluate the safety and risk assessment of cheese consumption in the Republic of Korea, sixty cheese samples purchased from the farmstead and retails markets (imported) were analyzed for their biogenic amine (BA) contents. The BA profiles and quantities of eight amines (tryptamine, 2-phenylethylamine, putrescine, cadaverine, histamine, tyramine, spermidine, and spermine) were determined using high-performance liquid chromatography (HPLC). Spermine was the only amine detectable in all the samples. The BAs of fresh cheeses from both farmstead and retail markets were mostly undetectable, and comparatively at lower levels (<125 mg/kg) than ripened samples. Putrescine was undetectable in all the domestic ripened cheeses. The sum of BA levels in the imported ripened cheeses of Pecorino Romano (1889.75 mg/kg) and Grana Padano (1237.80 mg/kg) exceeds >1000 mg/kg, of which histamine accounts nearly 86 and 77% of the total levels, respectively. The tolerable limits of the potential toxic amines, histamine and tyramine surpassed in four and three imported ripened samples, respectively. Furthermore, the presence of potentiators (putrescine and cadaverine) together in samples even with a lower level of toxic amines alarms the risk in consumption. Therefore, adoption of strict hygienic practices during the entire chain of cheese production, along with obligatory monitoring and regulation of BA in cheeses seems to be mandatory to ensure the safety of the consumers.

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1H HRMAS-NMR based metabolic fingerprints for discrimination of cheeses based on sensory qualities

Cited by 20 publications

References 25 publications

Influence of heating temperatures and storage on the odor of duck meat and identification of characteristic odorous smell compounds

Influence of heating temperatures and storage on the odor of duck meat and identification of characteristic odorous smell compounds

Relationship between amniotic fluid metabolic profile with fetal gender, maternal age, and gestational week

Quantitative Analysis of Biogenic Amines in Different Cheese Varieties Obtained from the Korean Domestic and Retail Markets

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