The palatability of beef has been investigated with digital imaging systems on numerous previous occasions. In the current study, a novel approach was applied using high magnification imaging to develop surface texture features and an alternative colour space greyscale to express muscle surface texture. An automatic segmentation method was applied to develop colour and marbling features and best regression model subsets were selected automatically with genetic algorithms. Results indicated that accurate modelling of beef acceptability with regression models was possible with r(2) up to 0.95. Modelling of acceptability using high magnification images proved more successful than modelling with low magnification images. Linear models performed well compared to non-linear models. Other sensory measurements particularly TPA hardness were more difficult to model, although an accurate model of juiciness was developed. Addition of non-linear terms did not give large improvements except for juiciness. (C) 2009 Elsevier Ltd. All rights reserved.