Determination of the total volatile basic nitrogen (TVB-N) content in pork meat using hyperspectral fluorescence imaging

Authors: LEE, HOONSOO - Us Forest Service (FS); Kim, Moon; LEE, WANG-HEE - Chungnam National University; CHO, BYOUNG-KWAN - Chungnam National University

Submitted to: Sensors and Actuators B: Chemical
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/15/2017
Publication Date: 12/16/2017
Citation: Lee, H., Kim, M.S., Lee, W., Cho, B. 2017. Determination of the total volatile basic nitrogen (TVB-N) content in pork meat using hyperspectral fluorescence imaging. Sensors and Actuators B: Chemical. 259:532-539.

Interpretive Summary: The total volatile basic nitrogen (TVB-N) content of meats reflects tissue decomposition and has long been used as an indicator of freshness. Conventional chemistry-based methods of measuring TVB-N are time-consuming, labor-intensive, and sample-destructive procedures. Although alternate quantitative measurement methods using visible and near-infrared spectroscopy and imaging techniques for non-destructive assessment of TVB-N have been investigated, no previous studies have utilized hyperspectral fluorescence imaging for the task. In this investigation, hyperspectral fluorescence images of pork loin samples were acquired using high-intensity ultraviolet excitation light and analyzed to develop a model for predicting the TVB-N content and visualizing its distribution in the meat. A high correlation between measured fluorescence intensities and TVB-N content was found, suggesting that hyperspectral fluorescence techniques have potential for use by the meat industry as rapid and non-destructive alternatives to conventional methods of assessing TVB-N as part of efforts to ensure meat quality and safety for consumers.

Technical Abstract: The total volatile basic nitrogen (TVB-N) content of meats is a key factor in measuring meat quality; however, conventional chemical methods for measuring TVB-N contents are time-consuming, labor-intensive, and are destructive procedures. The objective of this study is therefore to investigate the possibility of using hyperspectral fluorescence imaging techniques to determine TVB-N contents in pork meat. Thus, high-intensity light-emitting diodes at 365 nm were employed to acquire hyperspectral fluorescence images of the excitation. Prediction algorithms based on partial least squares (PLS) analysis and least squares support vector machines (LS-SVM) were developed. The coefficient of determination for the prediction data set (Rp2) and the standard error of prediction (SEP) of the optimal LS-SVM model for determining the TVB-N content were 0.967 and 1.902%, respectively. This study showed that visualization of the TVB-N distribution for the optimal model was useful for the spatial interpretation of the sample, and so we could conclude that fluorescence hyperspectral imaging exhibits potential for the rapid measurement of TVB-N contents in meats.