The combined effect of temperature and moisture (or water activity) on the rate of nutrients loss and other deteriorative chemical reactions in foods has been primarily studied in relation to drying. In long foods storage, changes in their temperature and/or moisture content are much slower and never as dramatic, but their effect can be similar in kind. Reported degradation reactions in foods mostly followed first- or other fixed-order kinetics. Hence, their progress under dynamic conditions primarily depends on the varying rate constant. Perhaps the most economic way to describe the rate constant’s variations pattern and magnitude is a two-parameter temperature-dependence model whose two coefficients are moisture dependent, each described by another two-parameter model, which brings the total number of adjustable parameters to four. Such a flexible model is the two-parameter exponential temperature-dependence term, a simpler substitute to the Arrhenius equation, whose two parameters’ moisture dependencies are also described by two similar exponential terms. This model’s flexibility is demonstrated with computer simulations of chemical degradation under varying temperature and moisture conditions. Testing a large number of products stored for long times by the traditional methods to determine a reaction’s kinetic parameters and their temperature and moisture dependencies can create logistic problems. Theoretically, they can be avoided by estimating the kinetic parameters directly from several successive concentration determinations during a single dynamic storage experiment whereby the monitored temperature and moisture are allowed to vary arbitrarily. The principle is demonstrated with simulated data having no or very small errors. However, its practical implementation might not be effective if the experimental concentration measurements have a substantial scatter.

温度和水分（或水分活度）对食物中营养物质流失速率和其他恶化的化学反应的综合影响已被初步研究与干燥有关。在长时间的食物存储中，温度和/或水分含量的变化要慢得多，而且从未如此剧烈，但其效果可能相似。据报道，食品中的降解反应主要遵循第一阶或其他固定阶动力学。因此，它们在动态条件下的进展主要取决于变化的速率常数。描述速率常数变化模式和幅度的最经济的方法可能是一个两参数温度依赖性模型，该模型的两个系数与湿度有关，每个系数都由另一个两参数模型描述，这将可调参数的总数增加到四个。这种灵活的模型是两参数指数温度相关项，它是Arrhenius方程的简单替代，其两个参数的湿度相关性也由两个相似的指数项来描述。通过在不同温度和湿度条件下进行化学降解的计算机模拟，可以证明该模型的灵活性。用传统方法测试大量长时间存储的产品以确定反应的动力学参数及其温度和湿度依赖性会产生逻辑问题。从理论上讲，可以通过在单个动态存储实验中直接从几个连续的浓度确定值中直接估算动力学参数来避免这些问题，从而允许所监视的温度和湿度任意变化。用没有误差或误差很小的模拟数据证明了该原理。但是，如果实验浓度测量值具有较大的分散性，则其实际实施可能无效。