Linking microbial contamination to food spoilage and food waste: the role of smart packaging, spoilage risk assessments, and date labeling

Ensuring a safe and adequate food supply is a cornerstone of human health and food security. However, a significant portion of the food produced for human consumption is wasted annually on a global scale. Reducing harvest and postharvest food waste, waste during food processing, as well as food waste at the consumer level, have been key objectives of improving and maintaining sustainability. These issues can range from damage during processing, handling, and transport, to the use of inappropriate or outdated systems, and storage and packaging-related issues. Microbial growth and (cross)contamination during harvest, processing, and packaging, which causes spoilage and safety issues in both fresh and packaged foods, is an overarching issue contributing to food waste. Microbial causes of food spoilage are typically bacterial or fungal in nature and can impact fresh, processed, and packaged foods. Moreover, spoilage can be influenced by the intrinsic factors of the food (water activity, pH), initial load of the microorganism and its interaction with the surrounding microflora, and external factors such as temperature abuse and food acidity, among others. Considering this multifaceted nature of the food system and the factors driving microbial spoilage, there is an immediate need for the use of novel approaches to predict and potentially prevent the occurrence of such spoilage to minimize food waste at the harvest, post-harvest, processing, and consumer levels. Quantitative microbial spoilage risk assessment (QMSRA) is a predictive framework that analyzes information on microbial behavior under the various conditions encountered within the food ecosystem, while employing a probabilistic approach to account for uncertainty and variability. Widespread adoption of the QMSRA approach could help in predicting and preventing the occurrence of spoilage along the food chain. Alternatively, the use of advanced packaging technologies would serve as a direct prevention strategy, potentially minimizing (cross)contamination and assuring the safe handling of foods, in order to reduce food waste at the post-harvest and retail stages. Finally, increasing transparency and consumer knowledge regarding food date labels, which typically are indicators of food quality rather than food safety, could also contribute to reduced food waste at the consumer level. The objective of this review is to highlight the impact of microbial spoilage and (cross)contamination events on food loss and waste. The review also discusses some novel methods to mitigate food spoilage and food loss and waste, and ensure the quality and safety of our food supply

Evaluating reuse of nontraditional water sources in agriculture and food production utilizing a scientometrics approach

Climate change is proving to be detrimental for agriculture and food production by depleting natural resources such as irrigation water. Researchers and growers are turning to alternative sources of irrigation water. Growers are potentially willing to accept nontraditional sources, provided they meet the chemical and microbial standards of existing sources. To help identify research gaps and suggest future research directions, a thorough analysis of existing literature needed to be done. The aim of this study was to categorize and analyze existing research on water reuse found on the Web of Science database using a scientometrics approach. The publication dataset comprising 3072 titles, published between 1990 and 2022, was analyzed for keywords and co-occurrence of commonly used phrase groups. The global and year-wise trends in publications were mapped and graphed to identify which countries were actively researching water reuse and whether the number of publications were progressing significantly per year. The highly cited publications were also analyzed for their content to understand what differentiated them from the other publications. Our results indicated that the numbers of publications have increased considerably over the years from 1990 to 2022 with a potential to further increase by 2060, indicating a growing interest in the area of water reuse. The global distribution of publications indicated that researchers across the globe have identified this as a potential future strategy and are actively working to understand various aspects of water reuse in agriculture and food production by using experimental and modeling based study methods. The current focus is on reclaimed water and roof harvested rainwater with other prospective sources being investigated. The findings indicate that a multidisciplinary approach is required to understand the multifaceted aspects of reusing nontraditional water sources as irrigation water for food crops. Based on our study, we suggest that collaborations between academic research, agricultural industries and government agencies could lead to the integration of nontraditional water sources as irrigation water, helping to alleviate the negative effects of climate change

Importance of artificial intelligence in evaluating climate change and food safety risk

Climate change is considered primarily as a human-created phenomenon that is changing the way humans live. Nowhere are the impacts of climate change more evident than in the food ecosphere. Climate-induced changes in temperature, precipitation, and rain patterns, as well as extreme weather events have already started impacting the yield, quality, and safety of food. Food safety and the availability of food is a fundamental aspect of ensuring food security and an adequate standard of living. With climate change, there have been increasing instances of observed changes in the safety of food, particularly from a microbiological standpoint, as well as its quality and yield. Thus, there is an urgent need for the implementation of advanced methods to predict the food safety implications of climate change (i.e., future food safety issues) from a holistic perspective (overall food system). Artificial Intelligence (AI) and other such advanced technologies have, over the years, permeated many facets of the food chain, spanning both farm- (or ocean-) to-fork production, and food quality and safety testing and prediction. As a result, these are perfectly positioned to develop novel models to predict future climate change-induced food safety risks. This article provides a roundup of the latest research on the use of AI in the food industry, climate change and its impact on the food industry, as well as the social, ethical, and legal limitations of the same. Particularly, this perspective review stresses the importance of a holistic approach to food safety and quality prediction from a microbiological standpoint, encompassing diverse data streams to help stakeholders make the most informed decisions