Food Stability Simulation

The 2030 agenda stated food security with Sustainable Development Goal (SDG) 3 "good health and well-being" and SDG 2 "zero hunger." Access to safe, nutritious food is essential for food security and imperative to protect public health. In recent years, chemical hazards in food have raised consumer concerns. Additionally, recent food scandals have increased consumer demand for food safety. There is a need to integrate food conservation processes with food processing that aims to extend shelf life, even with scarce technical resources, facilities, and equipment. It is nearly impossible to control every component of an entire process, so the real challenge is controlling different influential dynamics like rancidity, texture changes, moisture fluctuations, staling, browning, and microbial spoilage. It is very important to ensure that food is safe and acceptable for consumption, and the shelf life for which this is maintained is a key component of product design and hygiene. Consumer acceptance will be affected by changes in the sensory and nutritional properties of food products. For health and safety reasons, food must be consumed within a certain period; here a "use by" or "best before" date is required. Generally, a best-before date is applicable to foods whose deterioration affects consumer acceptance but does not affect health and safety. Depending on the type of deterioration the product undergoes, the "use-by" or "best-before" dates are overstated. During real-time testing, the best-before dates mentioned in the products are verified. However, it is not suitable to use real-time testing for improving packed food products with a longer shelf life. The shelf life of those items can be estimated by accelerated stability testing. Analysis of accelerated shelf life test (ASLT) applies to any process of deterioration that can be quantitatively expressed by an Arrhenius relationship. Keeping products at high temperatures, humidity, or light intensity is typically required to ensure the quality of the product. Various conditions and times are used to inspect products following storage. In some cases, testing beyond routine quality control may be necessary. Statistical and mathematical tools are used in predictive modeling to find relationships between intrinsic, extrinsic, and implicit factors. Also, it examines how it behaves under different combinations of intrinsic and extrinsic factors. Based on these calculations, a predictive shelf life is estimated. In this chapter, methods based on linear kinetic models and recent non-linear ones are reviewed. In conclusion, this significant area of accelerated shelf-life testing is explored in an attempt to suggest future directions. Moreover, it discusses what expectations one should have when developing novel practical and reliable tools that are applicable in the industrial process.