## 1 Introduction
When there is available time and space for the maintenance or operation of units, it is possible to adapt a life distribution model to the components over a long period, until the product's warranty time or even until the end of its life under normal stress conditions. However, when it is impossible to collect sufficient data and, at the same time, a study of the behavior of units under stress conditions (temperature, pressure, electric voltage, humidity, vibration, strength and friction) is sought, then it is necessary to subject some units to increasing levels of stress for a short period of time so that expected failures can be adjusted to a life distribution model. Predicting the failure rate at high stress levels significantly reduces both the experimental time and the minimum necessary sample size of units. However, it is necessary to set the stress correctly at high levels, and the models that bridge the gap between high stress and normal stress are called acceleration models. The next move is to integrate the parameters of life distribution models into models describing the stress effect on the units. The most popular of these are the Arrhenius and Eyring models, and the selection of the most appropriate model that adjusts the data as a result of the units being subjected to stress is statistically estimated by applying either traditional regression (least squares) or, more precisely, by the maximum likelihood estimation (MLE) [17]. Regarding food packaging films, a fatigue cyclic stretching test has only been applied to a nanocellulose hydrogel for refrigerated chicken preservation; nevertheless, the study involved only the presentation of data for different hydrogel compositions, without any attempt to model fatigue behavior [18]. On the contrary, numerous studies have applied fatigue tests to investigate the thermal reliability of thin films that are used as coatings [19] or as parts of electronics packages and devices [20; 21; 22; 23; 24] using the reliability testing method [22] or the finite element numerical analysis method [20; 21; 23; 24]. Fatigue models for metallic thin films are typically based either on the stress-cycle curve, in the case of high-cycle fatigue [21], or the Coffin-Manson equation, in the case of low-cycle fatigue [20], although other models--such as the strain envelope evolution model combined with critical fracture strain, in the case of a polyimide thin film [22]; the Engelmaier model, in the case of a film bulk acoustic resonator filter [23]; or the modified Basquin law for non-zero mean stress, in the case of inorganic coatings [19]--have been proposed. The aim of this study was to evaluate the degradation--fatigue model of several starch biodegradable film treatments and examine the best fit distribution for regression analysis using the elongation level, break cycle and exact break time as fixed factors. Secondly, it tried to obtain better insight into the way that explanatory variables may influence the log tensile quotient (logarithm of the tensile strength to the corresponding break cycle (log[ts/bc])) through the employment of a multiple regression analysis using the forward selection of the most important variables to enter the model at a 0.05 probability level of significance. This combination of two response variables is attempted for the first time in this field. Finally, it should be addressed that it is the first time in the literature that this degradation model is applied on packaging materials.