Resumen: Visual assessment is regarded as the gold standard to evaluate meat colour shelf-life, but it is costly and time consuming. To address this issue, this paper aims to evaluate the number of consumers and days of display that are necessaries in order to assess the colour shelf-life of meat, presented with different methods, all using images. Photographs of thirty-six lamb steaks were taken just after cutting (day 0) and on each of the following days until the 14th day of display under standardized conditions. Images were presented in three different manners: 1) with days of display and animals in random order (Random); 2) days of display in sequential and animals in random order (Sequential); and, 3) days of display and animals in sequential order (Animal); they were presented to 211 consumers who evaluated visual acceptability on a 9-point scale. At day zero, visual acceptability scores were the highest in Animal, followed by Sequential, and then by the Random (P <.05) method. Scores decreased over time for all methods tested (P <.05). The Random method presented the highest standard deviation; however, an increase in standard deviation among consumers along days of display was observed for all methods tested (P <.05). Shelf-life determined by regression varied according to the method of presentation (7.83, 7.00 and 7.54 days for Random, Sequential and Animal, respectively). A minimum number of 4 day points before and 4 day points after neutral scores had been reached (scores = 5.0) were necessary in order to obtain a robust model. The minimum number of required consumers (a = 0.05; d = 0.1 and ß = 0.2 or 0.1) varied according to methodology: it was 81 to 109 consumers for Random, 69 to 92 for Sequential, and 55 to 74 for Animal. Our study indicates that an optimal number of days and evaluators can be calculated depending on the manner of sample presentation. These findings should be taken into account in further studies that aim to balance data reliability with the cost involved in meat colour analyses. Idioma: Inglés DOI: 10.1016/j.foodres.2019.03.036 Año: 2019 Publicado en: Food Research International 121 (2019), 387-393 ISSN: 0963-9969 Factor impacto JCR: 4.972 (2019) Categ. JCR: FOOD SCIENCE & TECHNOLOGY rank: 11 / 139 = 0.079 (2019) - Q1 - T1 Factor impacto SCIMAGO: 1.44 - Food Science (Q1)