Optical scattering in beef steak to predict tenderness using hyperspectral imaging in the VIS-NIR region

Abstract

The objective of this research is to develop a non-destructive method for predicting cooked beef tenderness using optical scattering of light on fresh beef muscle tissue. A hyperspectral imaging system (k = 496-1,036 nm) that consists of a CCD camera and an imaging spectrograph, was used to acquire beef steak images. The hyperspectral image consisted of 120 bands with spectral intervals of 4.54 nm. Sixty-one fresh beef steaks, including 44 strip loin and 17 tenderloin cuts, were collected. After imaging, the steaks were cooked and Warner-Bratzler shear (WBS) force values were collected as tenderness references. The optical scattering profiles were derived from the hyperspectral images and fitted to the modified Lorentzian function. Parameters, such as the peak height, full scattering width at half maximum (FWHM), and the slope around the FWHM were determined at each wavelength.Stepwise regression was used to identify 7 key wavelengths and parameters. The parameters were then used to predict the WBS scores. The model was able to predict WBS scores with an R = 0.67. Optical scattering implemented with hyperspectral imaging shows limited success for predicting current status of tenderness in beef steak.

Quality classification of cooked, sliced turkey hams using NIR hyperspectral imaging system

“…It was successfully implemented for predicting beef tenderness (Cluff et al, 2008;Peng and Wu, 2008), classification and prediction of marbling, colour, texture and exudation, drip loss, pH in pork (Qiao et al, 2007a,b,c), contaminants and tumor detection in chicken (Lawrence et al, 2004;Nakariyakul and Casasent, 2004;Park et al, 2006) and assessment of water and fat contents in fish fillets (ElMasry and Wold, 2008).…”

Selection of feature wavelengths for developing multispectral imaging systems for quality, safety and authenticity of muscle foods-a review

“…Visible and near infrared (Vis/NIR) hyperspectral imaging (400e1000 nm) has also been widely applied to determine the tenderness of meats. Seven key wavelengths (501, 510, 646, 651, 927, 1005 and 1023 nm) were identified by SR to predict WBSF scores of fresh beef (Cluff et al, 2008). Similarly, for prediction of beef WBSF, the MLR model was based on the selected eight wavelengths (485, 524, 541, 645, 700, 720, 780 and 820 nm) by SR and gave R cv ¼ 0.91 .…”

Optical Methods and Techniques for Meat Quality Inspection

“…The authors defined SSF ≤ 205.8 N as tender meat,SSF between 205.8 and 254.8 N as intermediate,and SSF > 254.8 N as tough meat. In a similar study, a hyperspectral imaging system (496 to 1036 nm) was used to measure the tenderness of beef (Cluff et al, 2008). The authors reported fitting the optical scattering profiles obtained from the hyperspectral images using a modified Lorentzian function.…”