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A comparative study of sterols in milk fat of different Indian dairy animals based on chemometric analysis

机译:基于化学计量分析的不同印度乳制品乳脂甾醇对比研究

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In this study, sterols in milk fat of cow, goat, buffalo and camel were analyzed for their variability across different season and species. A GC-MS-SIM (gas chromatography- mass spectrometry-single ion monitoring mode) method was developed for accurate determination of sterols through the selection of correct set of target and reference ions in different time windows. The simple and rapid method enabled accurate analysis of sterols without subjecting them to derivatization. The sterols characterized in milk fat included cholesterol, lathosterol, desmosterol, lanosterol and dihydrolanosterol. Species compared to season had a pronounced effect on variability of sterols. Among the different species, goat milk contained the highest cholesterol level (325.18 mg 100 g(-1)fat) while minor sterols were most abundant in buffalo milk (20.62 mg 100 g(-1)fat). The content of minor sterols: lanosterol, lathosterol, desmosterol and dihydrolanosterol in milk of different animals varied from 5.94 to 9.11, 3.01 to 7.50, 0.60 to 2.77 & 0.57 to 1.25 mg 100 g(-1)fat respectively. Chemometric statistical approaches consisting of principal component analysis and hierarchical cluster analysis (PCA and HCA) were used to process the data. PCA was a suitable approach to find out the similarity and differences between different species and accounted for 96.6% of total variability in data. However, the variation based on season could not be explained well by PCA. HCAcould suitably classify the milch animals into four clusters based on sterol content.
机译:在这项研究中,分析了牛奶脂肪的甾醇,在不同季节和物种中分析了牛奶脂肪,山羊,水牛和骆驼的变异性。开发了GC-MS-SIM(气相色谱 - 质谱 - 单离子监测模式)方法,用于精确测定甾醇通过选择正确的靶标和不同时间窗口的参考离子。简单快捷的方法使能够准确分析甾醇而不使它们衍生化。甾醇特征在牛奶脂肪包括胆固醇,载体甾醇,Desmosterol,Lanterol olol和二氢醇甾醇。与季节相比的物种对甾醇的可变性具有明显的影响。在不同的物种中,山羊牛奶含有最高的胆固醇水平(325.18mg 100g(-1)脂肪),而幼甾醇在水牛牛奶中最丰富(20.62mg 100g(-1)脂肪)。次要甾醇的含量:不同动物牛奶中的Lanterol醇,乳甾醇,Desmosterol和二氢甲苯醇醇分别从5.94〜9.11,3.01至7.50,0.60〜2.77&0.57至1.25mg 100g(-1)脂肪。由主成分分析和分层集群分析(PCA和HCA)组成的化学计量统计方法来处理数据。 PCA是一种合适的方法,可以了解不同物种之间的相似性和差异,并占数据总变异的96.6%。然而,基于季节的变体无法通过PCA良好解释。 HCACALL适当地将孤子动物分为四种簇,基于甾醇含量。

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