Food Quality and Sensory Science Department, Teagasc Food Research Centre, Ashtown, Dublin, Ireland.
Food Biosciences Department, Teagasc Food Research Centre, Ashtown, Dublin, Ireland.
Meat Sci. 2021 Jul;177:108491. doi: 10.1016/j.meatsci.2021.108491. Epub 2021 Mar 9.
The food industry has been slow in harnessing technological developments to expand opportunities and benefit the community. One such opportunity is in the application of proteolytic enzymes to the development of softer-textured meat products that require reduced mastication force, for those with impaired dentition, and reduced strength including older adults. Proteolytic enzymes haven't been fully explored for their potential in this area. Here a response surface methodology (RSM) was applied to model the interactive effects of sous-vide and papain application on texture, color, and cooking loss of meat. An innovative meat product formulation with a reduced toughness (120 min cooking sous-vide and 0.01 mg papain/100 g) was optimized and the technological performance of the formulation was validated. Bias values of the optimized model were in the range of 0.97 to 1.06, while accuracy factors for shear force values, chewiness, TPA hardness, cooking loss, color parameters ranged from 1.00 and 1.06, both of which metrics indicated the reliability of the resultant models.
食品行业在利用技术发展来扩大机会和造福社会方面一直进展缓慢。其中一个机会是在应用蛋白酶来开发质地更柔软的肉类产品,这些产品需要减少咀嚼力,适用于牙齿受损和力量较弱的人群,包括老年人。蛋白酶在这方面的潜力尚未得到充分探索。在这里,响应面法(RSM)被应用于模拟低温巴氏杀菌和木瓜蛋白酶应用对肉质、颜色和烹饪损失的交互影响。优化了一种具有降低韧性的创新肉类产品配方(120 分钟低温巴氏杀菌和 0.01 毫克木瓜蛋白酶/100 克),并验证了配方的技术性能。优化模型的偏差值在 0.97 到 1.06 之间,而剪切力值、咀嚼性、TPA 硬度、烹饪损失、颜色参数的准确度因子范围在 1.00 到 1.06 之间,这两个指标都表明了所得模型的可靠性。