Department of Biosystems and Agricultural Engineering, 524 South Shaw Lane (ORCID: https://orcid.org/0000-0002-5553-5841 [B.P.M.]), Michigan State University, East Lansing, Michigan 48824, USA.
Department of Food Science and Human Nutrition, 469 Wilson Road, Michigan State University, East Lansing, Michigan 48824, USA.
J Food Prot. 2021 Jan 1;84(1):47-57. doi: 10.4315/JFP-20-221.
Prior efforts to model bacterial thermal inactivation in and on low-moisture foods generally have been based on isothermal and iso-moisture experiments and have rarely included dynamic product and process variables. Therefore, the objective of this study was to test appropriate secondary models to quantify the effect of product temperature, product moisture, and process humidity on thermal inactivation of Salmonella Enteritidis PT30 on pistachios subjected to dynamic dry- or moist-air heating. In-shell pistachios were inoculated with Salmonella Enteritidis PT30, equilibrated in controlled-humidity chambers (to target water activities [aw] of 0.45 or 0.65), and in some cases, subjected to a presoak treatment prior to heating in a laboratory-scale, moist-air convection oven at multiple combinations (in duplicate) of dry bulb (104.4 or 118.3°C) and dew point (∼23.8, 54.4, or 69.4°C) temperatures, with air speed of ∼1.3 m/s. Salmonella survivors, pistachio moisture content, and aw were quantified at six time points for each condition, targeting cumulative lethality of ∼3 to 5 log. The resulting data were used to estimate parameters for five candidate secondary models that included combinations of product temperature, product moisture, aw, and/or process dew point (coupled with a log-linear primary model). A model describing the D-value as a function of temperature and dew point fit the data well (root mean squared error [RMSE] = 0.86 log CFU/g); however, adding a term to account for dynamic product moisture improved the fit (RMSE = 0.83 log CFU/g). In addition, product moisture content yielded better model outcomes, as compared with aw, particularly in the case of the presoaked pistachios. When validated at the pilot scale, the model was conservative, always underpredicting the experimental log reductions. Both dynamic product moisture and process humidity were critical factors in modeling thermal inactivation of Salmonella in a low-moisture product heated in an air-convection system.
先前在低水分食品中对细菌热失活动力学的建模工作通常基于等温及等湿实验，很少包含动态产品和工艺变量。因此，本研究旨在测试合适的二级模型，以量化产品温度、产品水分和工艺湿度对经动态干或湿空气加热的带壳开心果中肠炎沙门氏菌 PT30 的热失活动力学的影响。将肠炎沙门氏菌 PT30 接种到带壳开心果中，在控湿室中平衡（目标水活度 [aw] 为 0.45 或 0.65），在某些情况下，在实验室规模的湿空气对流烘箱中加热前进行预浸泡处理，在多个组合（一式两份）下，用干球（104.4 或 118.3°C）和露点（23.8、54.4 或 69.4°C）温度，空气速度约为 1.3 m/s。对每种条件下的六个时间点进行沙门氏菌存活数、开心果水分含量和 aw 的定量检测，目标累计致死率为3 至 5 对数级。用所得数据来估计包含产品温度、产品水分、aw 和/或工艺露点的五个候选二级模型的参数（与对数线性一级模型结合）。描述 D 值作为温度和露点函数的模型很好地拟合了数据（均方根误差 [RMSE] = 0.86 log CFU/g）；然而，添加一个项来解释动态产品水分可改善拟合度（RMSE = 0.83 log CFU/g）。此外，与 aw 相比，产品水分含量可得出更好的模型结果，尤其是在带预浸泡的开心果的情况下。在中试规模验证时，该模型较为保守，始终低估实验的对数减少值。在空气对流系统中加热低水分产品时，动态产品水分和工艺湿度都是沙门氏菌热失活动力学建模的关键因素。
