Upadhyay Neelam, Jaiswal Pranita, Jha Shyam Narayan
Dairy Technology Division, ICAR-National Dairy Research Institute, Karnal, 132001 India.
Agricultural Structures and Environmental Control Division, ICAR-Central Institute of Postharvest Engineering and Technology (CIPHET), Ludhiana, 141004 India.
J Food Sci Technol. 2016 Oct;53(10):3752-3760. doi: 10.1007/s13197-016-2353-2. Epub 2016 Oct 28.
Ghee forms an important component of the diet of human beings due to its rich flavor and high nutritive value. This high priced fat is prone to adulteration with cheaper fats. ATR-FTIR spectroscopy coupled with chemometrics was applied for determining the presence of goat body fat in ghee (@1, 3, 5, 10, 15 and 20% level in the laboratory made/spiked samples). The spectra of pure (ghee and goat body fat) and spiked samples were taken in the wavenumber range of 4000-500 cm. Separated clusters of pure ghee and spiked samples were obtained on applying principal component analysis at 5% level of significance in the selected wavenumber range (1786-1680, 1490-919 and 1260-1040 cm). SIMCA was applied for classification of samples and pure ghee showed 100% classification efficiency. The value of R was found to be >0.99 for calibration and validation sets using partial least square method at all the selected wavenumber range which indicate that the model was well developed. The study revealed that the spiked samples of goat body fat could be detected even at 1% level in ghee.
由于酥油具有浓郁的风味和高营养价值,它构成了人类饮食的重要组成部分。这种高价脂肪容易被掺入较便宜的脂肪。采用衰减全反射傅里叶变换红外光谱(ATR-FTIR)结合化学计量学方法来测定酥油中山羊体脂的存在情况(在实验室制备/加标的样品中,添加水平为1%、3%、5%、10%、15%和20%)。在4000 - 500厘米波数范围内采集了纯品(酥油和山羊体脂)及加标样品的光谱。在选定的波数范围(1786 - 1680、1490 - 919和1260 - 1040厘米)内,以5%的显著性水平进行主成分分析,得到了纯酥油和加标样品的分离聚类。采用软独立建模类比法(SIMCA)对样品进行分类,纯酥油的分类效率为100%。在所有选定的波数范围内,使用偏最小二乘法,校准集和验证集的R值均大于0.99,这表明模型构建良好。该研究表明,即使在酥油中添加1%的山羊体脂样品也能被检测到。