Preliminary investigation into the prediction of indicators of beef spoilage using Raman and Fourier transform infrared spectroscopy. (June 2023)

• Record Type: Journal Article
• Authors: Liu, Qingsen; Dong, Pengcheng; Fengou, Lemonia-Christina; Nychas, George-John; Fowler, Stephanie Marie; Mao, Yanwei; Luo, Xin; Zhang, Yimin
• Is Part Of: Meat science. Volume 200(2023)
• Publication Date: 2023-06
• Subjects: Raman spectra -- FT-IR spectra -- TVB-N -- Rapid prediction -- Beef spoilage; Meat -- Periodicals; Meat industry and trade -- Periodicals; Viande -- Périodiques; Viande -- Industrie -- Périodiques; Meat; Meat industry and trade; Periodicals; 641.36
• DOI: 10.1016/j.meatsci.2023.109168
• Languages: English
• ISSNs: 0309-1740

Abstract

Abstract: The objective of this study was to assess the potential to predict the microbial beef spoilage indicators by Raman and Fourier transform infrared (FT-IR) spectroscopies. Vacuum skin packaged (VSP) beef steaks were stored at 0 °C, 4 °C, 8 °C and under a dynamic temperature condition (0 °C ∼ 4 °C ∼ 8 °C, for 36 d). Total viable count (TVC) and total volatile basic nitrogen (TVB-N) were obtained during the storage period along with spectroscopic data. The Raman and FTIR spectra were baseline corrected, pre-processed using Savitzky-Golay smoothing and normalized. Subsequently partial least squares regression (PLSR) models of TVC and TVB-N were developed and evaluated. The root mean squared error (RMSE) ranged from 0.81 to1.59 (log CFU/g or mg/100 g) and the determination coefficient (R 2 ) from 0.54 to 0.75. The performance of PLSR model based on data fusion (combination of Raman and FT-IR data) is better than that based on Raman spectra and similar to that of FT-IR. Overall, Raman spectroscopy, FT-IR spectroscopy, and a combination of both exhibited a potential for the prediction of the beef spoilage.