Prediction of beef palatability from colour, marbling and surface texture features of longissimus dorsi

A review of the development and use of video image analysis (VIA) for beef carcass evaluation as an alternative to the current EUROP system and other subjective systems

“…To verify and calibrate the existing commercial rib surface VIA systems at different quartering positions or on carcasses with different trim specifications would require software changes and a comprehensive validation experiment. Interestingly, recent research involving VIA technology applied to the meat surface seems to have focused more on predicting meat eating quality rather than LMY% (Jackman, Sun, & Allen, 2010;Jackman, Sun, Du, & Allen, 2009;Tan, 2004;Zheng, Sun, & Tan, 2008). …”

Applications of Computer Vision for Assessing Quality of Agri-food Products: A Review of Recent Research Advances

“…Also, Jackman et al measurements as an accurate model to determine surface color, marbling, and wavelet texture features with an accuracy of 90%. Moreover, an alternative grayscale (Jackman et al, 2010a) and a broad range of colors and marbling fat features were combined with high magnification images to develop surface texture features with good results. Based on these experiments, the results showed that linear models proved to be better than non-linear models.…”

“…Especially, prediction of beef palatability by Jackman et al (2008Jackman et al ( , 2009aJackman et al ( , 2009bJackman et al ( , 2009cJackman et al ( , 2009dJackman et al ( , 2010aJackman et al ( , 2010b has affected the grading of beef by United States Department of Agriculture (Jackman et al, 2011). …”

Hyperspectral imaging of ribeye muscle on hanging beef carcasses for tenderness assessment

“…In addition, robust hyperspectral image analysis algorithms are needed to improve the accuracy and repeatability of tenderness assessment. Only a few image features such as the gray level co-occurrence matrix, wavelet, and Gabor features, have been used for beef and pork tenderness evaluation (Konda Naganathan et al, 2008a,b;Jackman et al, 2009aJackman et al, , 2010Barbin et al, 2013). Additional feature sets need to be evaluated for their ability to discriminate tenderness.…”