Saleem Asima, Sahar Amna, Pasha Imran, Shahid Muhammad
National Institute of Food Science and Technology (NIFSAT), Faculty of Food, Nutrition and Home Sciences (FFNHS), University of Agriculture, Faisalabad 38000, Pakistan.
Department of Food Engineering, Faculty of Agricultural Engineering and Technology, University of Agriculture, Faisalabad 38000, Pakistan.
Food Sci Anim Resour. 2022 Jul;42(4):672-688. doi: 10.5851/kosfa.2022.e29. Epub 2022 Jul 1.
The objective of this study was to explore the potential of front face fluorescence spectroscopy (FFFS) as rapid, non-destructive and inclusive technique along with multi-variate analysis for predicting meat adulteration. For this purpose (FFFS) was used to discriminate pure minced beef meat and adulterated minced beef meat containing (1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%) of chicken meat as an adulterant in uncooked beef meat samples. Fixed excitation (290 nm, 322 nm, and 340 nm) and fixed emission (410 nm) wavelengths were used for performing analysis. Fluorescence spectra were acquired from pure and adulterated meat samples to differentiate pure and binary mixtures of meat samples. Principle component analysis, partial least square regression and hierarchical cluster analysis were used as chemometric tools to find out the information from spectral data. These chemometric tools predict adulteration in minced beef meat up to 10% chicken meat but are not good in distinguishing adulteration level from 1% to 5%. The results of this research provide baseline for future work for generating spectral libraries using larger datasets for on-line detection of meat authenticity by using fluorescence spectroscopy.
本研究的目的是探索正面荧光光谱法（FFFS）作为一种快速、无损且全面的技术，并结合多变量分析来预测肉类掺假的潜力。为此，使用FFFS来区分纯牛肉末和掺假的牛肉末，掺假牛肉末中含有（1%、2%、3%、4%、5%、10%、20%、30%、40%、50%、60%、70%、80%、90%和100%）作为掺杂物的鸡肉，用于未煮熟的牛肉样本。使用固定激发波长（290 nm、322 nm和340 nm）和固定发射波长（410 nm）进行分析。从纯肉和掺假肉样本中获取荧光光谱，以区分纯肉样本和二元混合肉样本。主成分分析、偏最小二乘回归和层次聚类分析被用作化学计量工具，以从光谱数据中找出信息。这些化学计量工具可预测牛肉末中鸡肉掺假量高达10%，但在区分1%至5%的掺假水平方面效果不佳。本研究结果为未来工作提供了基线，即使用更大的数据集生成光谱库，以便通过荧光光谱法在线检测肉类的真实性。
