Abstract：Hyperspectral scattering techniques were used to predict beef pH, tenderness(i.e. WBSF: Warner-Bratzler Shear Force) and color parameters. Thirty-three fresh strip loin cuts were collected from 2-day postmortem carcass. After capturing scattering images and measuring pH values, the samples were vacuum packaged and aged to seventh day, then their color parameters (L*, a*, b*) and WBSF were measured as references. The optical scattering profiles were extracted from the hyperspectral images and fitted to the Lorentzian distribution (LD) function with three parameters. LD parameters, such as the peak height, full scattering width at half maximum (FWHM) and the scattering asymptotic were calculated at individual wavelength. Stepwise regression was used to determine optimal combinations of wavelengths for each of parameters. The optimal combinations were then used to establish multi-linear regression (MLR) models to predict the beef attributes. The full cross validation method was used to examine the performance of models. The models were able to predict beef WBSF with RCV=0.86, and with the SECV (the standard error of cross validation) of 11.7 N, 91% classification accuracy could be obtained. Two-day pH values with RCV=0.86, SECV=0.07 and color parameters (L*, a*, b*) with RCV of 0.92, 0.90 and 0.88, with the SECV of 0.90, 1.34 and 0.41 were obtained respectively. This research provided available technique for the development of multispectral system, which could be implemented online to determine beef steaks color and tenderness.
Key words：Beef quality;Hyperspectral scattering imaging;Lorentzian distribution function;Multi-linear regression
[1] SUN Bao-zhong，MA Ai-jin，YANG Xi-bo(孙宝忠，马爱进，杨喜博). Food and Nutrition in China(中国食物与营养)，2002，(5)：15. [2] Leroy B，Lambotte S，Dotreppe O，et al. Meat Science，2003，66：45. [3] Liu Y L，Lyon B G，Windham W R，et al. Meat Science，2003，65：1107. [4] Andrés S，Silva A，Pereira A L，et al. Meat Science，2007，73(3)：217. [5] Prieto N，Andrés S，Giráldez F J，et al. Meat Science，2008，79：692. [6] Park B，Chen Y R，Hruschka W R，et al. Journal of Animal Science，1998，76：2115. [7] Rodbotten R，Nilsen B N，Hildrum K I. Food Chemistry，2000，69：427. [8] Gowen A A，O’Donnell C P，Cullen P J，et al. Trends in Food Science & Technology，2007，18：590. [9] Kim I，Kim M S，Chen Y R，et al. Transaction of the ASAE，2004，47(5)：1785. [10] Park B，Windham W R，Lawrence K C，et al. Biosystems Engineering，2007, 96(3)：323. [11] Mehl P M，Chen Y R，Kim M S，et al. Journal of Food Engineering，2004，61：67. [12] MA Ben-xue, YING Yi-bin，RAO Xiu-qin，et al(马本学，应义斌，饶秀勤，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2009，29(6)：1611. [13] Xing J，Saeys W，De Baerdemaeker. Computers and Electronics in Agriculture，2007，56(1)：1. [14] Masry G E，Wang N，Sayed A E，et al. Journal of Food Engineering，2007，81(1)：98. [15] Liu Y，Chen Y R，Kim M S，et al. Journal of Food Engineering，2007，81(2)：412. [16] Qiao J，Wang N，Ngadi M O，et al. Meat Science，2007，76：1. [17] Qiao J，Wang N，Ngadi M O，et al. Journal of Food Engineering，2007，83：10. [18] Naganathan W K，Grimes L M，Subbiah J，et al. Computers and Electronics in Agriculture，2008，64(2)：225. [19] Lu R，Peng Y. Biosystems Engineering，2006，93 (2)：161. [20] Peng Y，Lu R. Transactions of the ASABE，2006，49(1)：269. [21] Peng Y，Lu R. Post Harvest Biology and Technology，2008，48：52. [22] Xia J J，Weaver A，Gerrard D E，et al. Sens. & Instrument Food Qual，2008，2：75. [23] Cluff K，Naganathan G K，Subbiah J，et al. Sens. & Instrument Food Qual，2008，2：189. [24] Peng Y K，Wu J H. In：ASABE Annual International Meeting，Paper No.080004，July 2008.
