Prediction of texture in different beef cuts applying image analysis technique

Abstract

Purpose

Measuring texture parameters are time consuming and expensive; it is necessary to develop an efficient and rapid method to evaluate them. Image analysis can be a useful tool. The purpose of this paper is to predict texture parameters in different beef cuts applying image analysis techniques.

Design/methodology/approach

Samples were analyzed by scanning electron microscopy. Texture parameters were analyzed by instrumental, image analysis techniques and by Warner–Bratzler shear force.

Findings

Significant differences (p<0.05) were obtained for image and instrumental texture features. Higher amount of porous were observed in freeze dried samples of beef cuts from Gluteus Medius and semintendinosus muscles. A linear trend with a linear correlation was applied for instrumental and image texture. High correlations were found between image and instrumental texture features. Instrumental parameters showed a positive correlation with image texture feature.

Originality/value

This research suggests that the addition of image texture features improves the accuracy to predict texture parameter. The prediction of quality parameters can be performed easily with a computer by recognizing attributes within an image.

Citation

Pieniazek, F., Roa Andino, A. and Messina, V. (2018), "Prediction of texture in different beef cuts applying image analysis technique", British Food Journal, Vol. 120 No. 8, pp. 1929-1940. https://doi.org/10.1108/BFJ-12-2017-0695