Nuin Maider, Alfaro Begoña, Cruz Ziortza, Argarate Nerea, George Susie, Le Marc Yvan, Olley June, Pin Carmen
AZTI-Tecnalia, Txatxarramendi Ugartea z/g, Bizkaia, Spain.
Int J Food Microbiol. 2008 Oct 31;127(3):193-9. doi: 10.1016/j.ijfoodmicro.2008.04.010. Epub 2008 Apr 30.
Kinetic models were developed to predict the microbial spoilage and the sensory quality of fresh fish and to evaluate the efficiency of a commercial time-temperature integrator (TTI) label, Fresh Check(R), to monitor shelf life. Farmed turbot (Psetta maxima) samples were packaged in PVC film and stored at 0, 5, 10 and 15 degrees C. Microbial growth and sensory attributes were monitored at regular time intervals. The response of the Fresh Check device was measured at the same temperatures during the storage period. The sensory perception was quantified according to a global sensory indicator obtained by principal component analysis as well as to the Quality Index Method, QIM, as described by Rahman and Olley [Rahman, H.A., Olley, J., 1984. Assessment of sensory techniques for quality assessment of Australian fish. CSIRO Tasmanian Regional Laboratory. Occasional paper n. 8. Available from the Australian Maritime College library. Newnham. Tasmania]. Both methods were found equally valid to monitor the loss of sensory quality. The maximum specific growth rate of spoilage bacteria, the rate of change of the sensory indicators and the rate of change of the colour measurements of the TTI label were modelled as a function of temperature. The temperature had a similar effect on the bacteria, sensory and Fresh Check kinetics. At the time of sensory rejection, the bacterial load was ca. 10(5)-10(6) cfu/g. The end of shelf life indicated by the Fresh Check label was close to the sensory rejection time. The performance of the models was validated under fluctuating temperature conditions by comparing the predicted and measured values for all microbial, sensory and TTI responses. The models have been implemented in a Visual Basic add-in for Excel called "Fish Shelf Life Prediction (FSLP)". This program predicts sensory acceptability and growth of spoilage bacteria in fish and the response of the TTI at constant and fluctuating temperature conditions. The program is freely available at http://www.azti.es/muestracontenido.asp?idcontenido=980&content=15&nodo1=30&nodo2=0.
建立了动力学模型，用于预测鲜鱼的微生物腐败和感官品质，并评估一种商业时间 - 温度积分器（TTI）标签Fresh Check®监测保质期的效率。养殖大菱鲆（Psetta maxima）样本用PVC薄膜包装，分别储存在0、5、10和15摄氏度下。定期监测微生物生长和感官特性。在储存期间，在相同温度下测量Fresh Check装置的响应。根据主成分分析获得的全局感官指标以及Rahman和Olley [Rahman, H.A., Olley, J., 1984. Assessment of sensory techniques for quality assessment of Australian fish. CSIRO Tasmanian Regional Laboratory. Occasional paper n. 8. Available from the Australian Maritime College library. Newnham. Tasmania]描述的质量指数法（QIM）对感官感知进行量化。发现这两种方法在监测感官品质损失方面同样有效。将腐败细菌的最大比生长速率、感官指标的变化率以及TTI标签颜色测量的变化率建模为温度的函数。温度对细菌、感官和Fresh Check动力学有类似影响。在感官拒收时，细菌负荷约为10⁵ - 10⁶ cfu/g。Fresh Check标签指示的保质期结束时间接近感官拒收时间。通过比较所有微生物、感官和TTI响应的预测值和测量值，在波动温度条件下验证了模型的性能。这些模型已在一个名为“鱼类保质期预测（FSLP）”的Excel Visual Basic插件中实现。该程序可预测鱼类中腐败细菌的感官可接受性和生长以及TTI在恒定和波动温度条件下的响应。该程序可从http://www.azti.es/muestracontenido.asp?idcontenido=980&content=15&nodo1=30&nodo2=0免费获取。
