Merkx Donny W H, Swager Andries, van Velzen Ewoud J J, van Duynhoven John P M, Hennebelle Marie
Unilever Food Innovation Centre, Bronland 14, 6708 WH Wageningen, The Netherlands.
Laboratory of Food Chemistry, Wageningen University & Research, Bornse Weilanden 9, 6708 WG Wageningen, The Netherlands.
Antioxidants (Basel). 2021 Feb 15;10(2):287. doi: 10.3390/antiox10020287.
Food emulsions with high amounts of unsaturated fats, such as mayonnaise, are prone to lipid oxidation. In the food industry, typically accelerated shelf life tests are applied to assess the oxidative stability of different formulations. Here, the appearance of aldehydes at the so-called onset time, typically weeks, is considered a measure for oxidative stability of food emulsions, such as mayonnaise. To enable earlier assessment of compromised shelf-life, a predictive model for volatile off-flavor generation is developed. The model is based on the formation kinetics of hydroperoxides, which are early oxidation products and precursors of volatile aldehydes, responsible for off-flavor. Under accelerated shelf-life conditions (50 °C), hydroperoxide (LOOH) concentration over time shows a sigmoidal curvature followed by an acceleration phase that occurs at a LOOH-concentration between 38-50 mmol/kg, here interpreted as a critical LOOH concentration (CC). We hypothesize that the time at which CC was reached is related to the onset of aldehyde generation and that the characterization of the LOOH-generation curvature could be based on reaction kinetics in the first days. These hypotheses are tested using semi-empirical models to describe the autocatalytic character of hydroperoxide formation in combination with the CC. The Foubert function is selected as best describing the LOOH-curvature and is hence used to accurately predict onset of aldehyde generation, in most cases within several days of shelf-life. Furthermore, we find that the defining parameters of this model could be used to recognize antioxidant mechanisms at play.
含有大量不饱和脂肪的食品乳剂,如蛋黄酱,容易发生脂质氧化。在食品工业中,通常采用加速保质期试验来评估不同配方的氧化稳定性。在此,在所谓的起始时间(通常为数周)出现的醛类物质被视为食品乳剂(如蛋黄酱)氧化稳定性的一种衡量标准。为了能够更早地评估保质期缩短的情况,开发了一种挥发性异味产生的预测模型。该模型基于氢过氧化物的形成动力学,氢过氧化物是挥发性醛类的早期氧化产物和前体,会导致异味产生。在加速保质期条件(50°C)下,氢过氧化物(LOOH)浓度随时间呈S形曲线,随后在LOOH浓度为38 - 50 mmol/kg之间出现加速阶段,在此将其解释为临界LOOH浓度(CC)。我们假设达到CC的时间与醛类产生的起始时间相关,并且LOOH产生曲线的特征可以基于最初几天的反应动力学。使用半经验模型来测试这些假设,以结合CC描述氢过氧化物形成的自催化特性。福贝尔函数被选为最能描述LOOH曲线的函数,因此被用于准确预测醛类产生的起始时间,在大多数情况下,在保质期的几天内即可预测。此外,我们发现该模型的定义参数可用于识别所起作用的抗氧化机制。