Kandasamy Sujatha, Yoo Jayeon, Yun Jeonghee, Kang Han Byul, Seol Kuk-Hwan, Ham Jun-Sang
Animal Products Research and Development Division, National Institute of Animal Science, Rural Development Administration, Wanju 55365, Republic of Korea.
Saudi J Biol Sci. 2020 Jun;27(6):1446-1461. doi: 10.1016/j.sjbs.2020.04.043. Epub 2020 May 11.
In this study, the H HRMAS-NMR (High-resolution Magic Angle Spinning-Nuclear Magnetic Resonance) spectra of 52 cheese samples obtained from the South Korean dairy farms were evaluated for their metabolic profiling and intensities associating with the sensory qualities. The NMR profiles displayed a broad range of compounds comprising amino acids, carbohydrates, organic acids, and phospholipids. Afterwards, the cheese samples were categorized into three groups (more likeness - G1, moderate likeness - G2, less likeness - G3), in relating to their sensory scores. The NMR data of the samples were later investigated through multivariate statistical tools to define the variations in metabolic fingerprints of every cheese sample and their intensities hailing in individual sensory groups. The unsupervised PCA employing all cheese samples unveiled the uniqueness in metabolite profiles of the brown and cheddar type cheeses (outliers). Moreover, Gouda and other types of cheeses displayed samples positioning in respective of their metabolite profiles. The pairwise comparison of sensory groups in the supervised models perceived better separation in OPLS-DA than PLS-DA. The corresponding VIP (PLS-DA) and loading (OPLS-DA) plots revealed amino acids and organic acids (lactate, citrate) as significant variables. The discrimination of G 1 Gouda type of cheeses against G 2 and G 3 was highly associated with their citrate levels. Further investigation using heatmaps displayed clear differentiation between each sensory group in terms of the levels of amino acids, lactate, citrate, phospholipids, and glycerol, conveying these variations are likely due to proteolytic and metabolic processes in cheese ripening. This study concluded that H HRMAS-NMR metabolite profile of the Korean cheeses is consistence with their sensory qualities. Further, the candidate metabolites identified in this study confers their potential application as biomarkers in cheese industries for faster and effective validation of sensory characteristics.
在本研究中，对从韩国奶牛场采集的52个奶酪样品的高分辨率魔角旋转核磁共振（H HRMAS-NMR）光谱进行了评估，以分析其代谢谱以及与感官品质相关的强度。核磁共振谱显示出广泛的化合物，包括氨基酸、碳水化合物、有机酸和磷脂。之后，根据奶酪样品的感官评分将其分为三组（相似度较高 - G1、相似度中等 - G2、相似度较低 - G3）。随后，通过多变量统计工具对样品的核磁共振数据进行研究，以确定每个奶酪样品代谢指纹的变化及其在各个感官组中的强度。使用所有奶酪样品进行的无监督主成分分析（PCA）揭示了棕色奶酪和切达干酪类型奶酪（异常值）代谢物谱的独特性。此外，高达干酪和其他类型的奶酪根据其代谢物谱显示出样品的分布情况。在监督模型中，感官组的成对比较显示，正交偏最小二乘法判别分析（OPLS-DA）比偏最小二乘法判别分析（PLS-DA）具有更好的分离效果。相应的变量重要性投影（VIP，PLS-DA）图和载荷图（OPLS-DA）显示氨基酸和有机酸（乳酸、柠檬酸）是显著变量。G1组高达干酪类型与G2组和G3组的区分与其柠檬酸盐水平高度相关。使用热图进行的进一步研究表明，在氨基酸、乳酸、柠檬酸、磷脂和甘油水平方面，各感官组之间存在明显差异，表明这些差异可能是由于奶酪成熟过程中的蛋白水解和代谢过程所致。本研究得出结论，韩国奶酪的H HRMAS-NMR代谢物谱与其感官品质一致。此外，本研究中鉴定出的候选代谢物具有作为生物标志物在奶酪行业中快速有效验证感官特性的潜在应用价值。
