Serment-Moreno Vinicio, Fuentes Claudio, Torres José Antonio, Welti-Chanes Jorge
Tecnológico de Monterrey, Escuela de Ingenierías y Ciencias, Centro de Biotecnología FEMSA, Eugenio Garza Sada 2501 Sur, Col. Tecnológico, 64849, Monterrey, NL, México.
Statistics Dept., Oregon State Univ., 54 Kidder Hall, Corvallis, OR, 97331, U.S.A.
J Food Sci. 2017 Aug;82(8):1885-1891. doi: 10.1111/1750-3841.13783. Epub 2017 Jun 20.
A recently proposed Gompertz model (GMPZ) approach describing microbial inactivation kinetics by high-pressure processing (HPP) incorporated the initial microbial load (N ) and lower microbial quantification limit (N ), and simplified the dynamic effects of come-up time (CUT). The inactivation of Listeria innocua in milk by HPP treatments at 300, 400, 500, and 600 MPa and pressure holding times (t ) ≤10 min was determined experimentally to validate this model approach. Models based on exponential, logistic-exponential, and inverse functions were evaluated to describe the effect of pressure on the lag time (λ) and maximum inactivation rate (μ ), whereas the asymptote difference (A) was fixed as A = log (N /N ). Model performance was statistically evaluated and further validated with additional data obtained at 450 and 550 MPa. All GMPZ models adequately fitted L. innocua data according to the coefficient of determination (R ≥ 0.95) but those including a logistic-exponential function for μ (P) were superior (R ≥ 0.97). These GMPZ versions predicted that approximately 597 MPa is the theoretical pressure level (P ) at which microbial inactivation begins during CUT, mathematically defined as λ (P = P ) = t , and matching the value observed on the microbial survival curve at 600 MPa. As pressure increased, predictions tended to slightly underestimate the HPP lethality in the tail section of the survival curve. This may be overseen in practice since the observed microbial counts were below the predicted log N values. Overall, the modeling approach is promising, justifying further validation work for other microorganisms and food systems.
最近提出的一种通过高压处理(HPP)描述微生物失活动力学的冈珀茨模型(GMPZ)方法纳入了初始微生物负荷(N)和较低的微生物定量限(N),并简化了升压时间(CUT)的动态影响。通过实验确定了在300、400、500和600 MPa的HPP处理以及保压时间(t)≤10分钟条件下无害李斯特菌在牛奶中的失活情况,以验证该模型方法。评估了基于指数函数、逻辑斯蒂 - 指数函数和反函数的模型,以描述压力对滞后时间(λ)和最大失活率(μ)的影响,而渐近线差异(A)固定为A = log(N /N)。对模型性能进行了统计评估,并使用在450和550 MPa下获得的额外数据进行了进一步验证。根据决定系数(R≥0.95),所有GMPZ模型都能很好地拟合无害李斯特菌的数据,但那些包含μ(P)的逻辑斯蒂 - 指数函数的模型表现更优(R≥0.97)。这些GMPZ版本预测,约597 MPa是理论压力水平(P),在升压时间期间微生物失活开始于此,数学上定义为λ(P = P)= t,并且与在600 MPa下微生物存活曲线上观察到的值相符。随着压力增加,预测往往会略微低估存活曲线尾部的HPP致死率。由于观察到的微生物计数低于预测的log N值,这在实际中可能被忽略。总体而言,该建模方法很有前景,证明了对其他微生物和食品系统进行进一步验证工作的合理性。