Albrecht Antonia, Mittler Maureen, Hebel Martin, Waldhans Claudia, Herbert Ulrike, Kreyenschmidt Judith
Institute of Animal Science, University of Bonn, Katzenburgweg 7-9, 53115 Bonn, Germany.
Research and Transfer Center, Anhalt University of Applied Sciences, Hubertus 1a, 06366 Köthen, Germany.
Foods. 2021 Nov 9;10(11):2740. doi: 10.3390/foods10112740.
The high perishability of fresh meat results in short sales and consumption periods, which can lead to high amounts of food waste, especially when a fixed best-before date is stated. Thus, the aim of this study was the development of a real-time dynamic shelf-life criterion (DSLC) for fresh pork filets based on a multi-model approach combining predictive microbiology and sensory modeling. Therefore, 647 samples of ma-packed pork loin were investigated in isothermal and non-isothermal storage trials. For the identification of the most suitable spoilage predictors, typical meat quality parameters (pH-value, color, texture, and sensory characteristics) as well as microbial contamination (total viable count, spp., lactic acid bacteria, , Enterobacteriaceae) were analyzed at specific investigation points. Dynamic modeling was conducted using a combination of the modified Gompertz model (microbial data) or a linear approach (sensory data) and the Arrhenius model. Based on these models, a four-point scale grading system for the DSLC was developed to predict the product status and shelf-life as a function of temperature data in the supply chain. The applicability of the DSLC was validated in a pilot study under real chain conditions and showed an accurate real-time prediction of the product status.
鲜肉的高度易腐性导致销售和消费周期短，这可能会导致大量食物浪费，尤其是在标明固定保质期的情况下。因此，本研究的目的是基于预测微生物学和感官建模相结合的多模型方法，开发一种用于新鲜猪里脊肉的实时动态保质期标准（DSLC）。为此，在等温及非等温储存试验中对647个真空包装猪里脊肉样本进行了研究。为了确定最合适的腐败预测指标，在特定的调查点分析了典型的肉质参数（pH值、颜色、质地和感官特性）以及微生物污染情况（总活菌数、假单胞菌属、乳酸菌、热杀索丝菌、肠杆菌科）。使用修正的Gompertz模型（微生物数据）或线性方法（感官数据）与阿伦尼乌斯模型相结合进行动态建模。基于这些模型，开发了一种用于DSLC的四点量表分级系统，以根据供应链中的温度数据预测产品状态和保质期。DSLC的适用性在实际供应链条件下的试点研究中得到了验证，结果表明该系统能够准确实时预测产品状态。
