Resumo

SALINAS LABRA, Sara et al. Development and validation of a visual pattern for evaluating beef meat color in Mexico. Rev. mex. de cienc. pecuarias [online]. 2020, vol.11, n.2, pp.479-497.  Epub 23-Out-2020. ISSN 2448-6698.  https://doi.org/10.22319/rmcp.v11i2.5181.

This study aimed to develop a visual scale for beef color evaluation. A total of 1,165 loins were analyzed 24 h postmortem in four slaughterhouses in Mexico. In each sample, it was determined color using a visual pattern and a spectrophotometer (CIELAB scale), taking a photograph of each loin. Seven categories were identified using the visual method (from very light red to very dark red), and the instrumental color variables (L*, a*, b*, C*, and h*) were used to create prediction models for the visual categories. The scale was constructed using L* as the sole predictor, as this model explained > 90 % of the observed variation. The pattern was illustrated with photos of the samples with an L* value within the 95 % confidence interval of the mean in each category, from very light red (48.1 <L*<48.8) to very dark red (32.7 <L*<33.4). The total color difference between the categories fluctuated between 2.8 and 5.5, which suggests that these are distinguishable with the naked eye. A trained sensory panel and a consumer panel, through tests, validated the scale. Trained panelists correctly rated the samples in 92.6 % of the evaluations. In meat with dark-cutting (DC) appearance, the trained panelists had 100 % hits, and the consumer panelists 85.3 %. The proposed visual pattern is supported by instrumental measurements and proved to be technically feasible for the evaluation of color in beef by trained personnel and consumers.

Palavras-chave : Beef; Bovine; Quality; Color; Visual; Instrumental; Pattern.