Advancements in Predictive Microbiology: Integrating New Technologies for Efficient Food Safety Models.

Predictive microbiology is a rapidly evolving field that has gained significant interest over the years due to its diverse application in food safety. Predictive models are widely used in food microbiology to estimate the growth of microorganisms in food products. These models represent the dynamic interactions between intrinsic and extrinsic food factors as mathematical equations and then apply these data to predict shelf life, spoilage, and microbial risk assessment. Due to their ability to predict the microbial risk, these tools are also integrated into hazard analysis critical control point (HACCP) protocols. However, like most new technologies, several limitations have been linked to their use. Predictive models have been found incapable of modeling the intricate microbial interactions in food colonized by different bacteria populations under dynamic environmental conditions. To address this issue, researchers are integrating several new technologies into predictive models to improve efficiency and accuracy. Increasingly, newer technologies such as whole genome sequencing (WGS), metagenomics, artificial intelligence, and machine learning are being rapidly adopted into newer-generation models. This has facilitated the development of devices based on robotics, the Internet of Things, and time-temperature indicators that are being incorporated into food processing both domestically and industrially globally. This study reviewed current research on predictive models, limitations, challenges, and newer technologies being integrated into developing more efficient models. Machine learning algorithms commonly employed in predictive modeling are discussed with emphasis on their application in research and industry and their advantages over traditional models.

Closing the loop: A framework for tackling single-use plastic waste in the food and beverage industry through circular economy- a review.

The escalating threat of plastic pollution necessitates urgent and immediate action, particularly within the food and beverage (F&B) industry, a significant contributor to single-use plastic waste (SUP). As the global population surges, so does the consumption of single-use plastics in the F&B sector, perpetuating a linear economy model characterized by a 'take, make, use, dispose' approach. This model significantly exacerbates plastic waste issues, with projections indicating an alarming increase in plastic outputs by 2050 if current practices continue. Against this backdrop, the circular economy presents a viable alternative, with its emphasis on resource retention, recovery, and the extension of product lifecycles. This study delves into the problems posed by single-use plastics, introduces the circular economy as a sustainable model, and explores effective strategies for the recycling and reuse of plastic waste within this framework. By examining the environmental impact of SUP in the F&B sector and advocating for the adoption of circular economy principles, this paper underscores a critical pathway towards sustainable solutions in the battle against plastic pollution. In conclusion, the transition to a circular economy, underpinned by global collaboration and the proactive implementation of supportive policies, is imperative for reducing the environmental footprint of single-use plastics and fostering a sustainable future.