Proactive systems for early warning of potential impacts of natural disasters on food safety: Climate-change-induced extreme events as case in point

Modernization of digital food safety control

Foodborne illness remains a pressing global issue due to the complexities of modern food supply chains and the vast array of potential contaminants that can arise at every stage of food processing from farm to fork. Traditional food safety control systems are increasingly challenged to identify these intricate hazards. The U.S. Food and Drug Administration's (FDA) New Era of Smarter Food Safety represents a revolutionary shift in food safety methodology by leveraging cutting-edge digital technologies. Digital food safety control systems employ modern solutions to monitor food quality by efficiently detecting in real time a wide range of contaminants across diverse food matrices within a short timeframe. These systems also utilize digital tools for data analysis, providing highly predictive assessments of food safety risks. In addition, digital food safety systems can deliver a secure and reliable food supply chain with comprehensive traceability, safeguarding public health through innovative technological approaches. By utilizing new digital food safety methods, food safety authorities and businesses can establish an efficient regulatory framework that genuinely ensures food safety. These cutting-edge approaches, when applied throughout the food chain, enable the delivery of safe, contaminant-free food products to consumers.

Making food systems more resilient to food safety risks by including artificial intelligence, big data, and internet of things into food safety early warning and emerging risk identification tools

To enhance the resilience of food systems to food safety risks, it is vitally important for national authorities and international organizations to be able to identify emerging food safety risks and to provide early warning signals in a timely manner. This review provides an overview of existing and experimental applications of artificial intelligence (AI), big data, and internet of things as part of early warning and emerging risk identification tools and methods in the food safety domain. There is an ongoing rapid development of systems fed by numerous, real-time, and diverse data with the aim of early warning and identification of emerging food safety risks. The suitability of big data and AI to support such systems is illustrated by two cases in which climate change drives the emergence of risks, namely, harmful algal blooms affecting seafood and fungal growth and mycotoxin formation in crops. Automation and machine learning are crucial for the development of future real-time food safety risk early warning systems. Although these developments increase the feasibility and effectiveness of prospective early warning and emerging risk identification tools, their implementation may prove challenging, particularly for low- and middle-income countries due to low connectivity and data availability. It is advocated to overcome these challenges by improving the capability and capacity of national authorities, as well as by enhancing their collaboration with the private sector and international organizations.

Food retail environments, extreme weather, and their overlap: Exploratory analysis and recommendations for U.S. food policy

Extreme weather events are increasing in frequency and severity due to climate change, yet many of their impacts on human populations are not well understood. We examine the relationship between prior extreme weather events and food environment characteristics. To do so, we conduct a U.S. county-level analysis that assesses the association between extreme weather events and two common food retail environment dimensions. Overall, we find a relationship between higher levels of historic extreme weather exposure and lower food availability and accessibility. In addition, we find heterogeneity in association across the distribution of the number of extreme weather events and event type. Specifically, we find that more localized extreme weather events are more associated with a reduction of access and availability than broad geographic events. Our findings suggest that as extreme weather events amplify in intensity and increase in frequency, new approaches for mitigating less acute and longer-term impacts are needed to address how extreme weather may interact with and reinforce existing disparities in food environment factors. Furthermore, our research argues that integrated approaches to improving vulnerable food retail environments will become an important component of extreme weather planning and should be a consideration in both disaster- and food-related policy.

Food systems and rural wellbeing: challenges and opportunities

The future wellbeing of billions of rural people is interconnected with transforming food systems for equity, nutrition, environmental sustainability, and resilience. This article tackles three blind spots in the understanding of rural poverty and vulnerability: the narrow focus on extreme poverty and hunger that hides a much wider set of inequalities and vulnerabilities, insufficient recognition of the diversity of rural households, and an inadequate appreciation of the impact of rapid structural changes in markets, the physical environment, and the political economic context. A better understanding of these areas is necessary for imagining a new policy landscape that can align progress on rural poverty alleviation with a wider transformation of food systems. The article provides a framework for assessing the dynamics of rural wellbeing and food systems change. It looks at the viability of small-scale farming and the diversification of livelihood options needed to overcome rural poverty and inequality. The analysis suggests that the future prosperity of rural areas will depend on policy reforms to address market failures in the food system, which currently work against equity, good nutrition and sustainability. Investments will also be needed to enable rural economies to capture greater value from the food system, particularly in the midstream of food distribution, processing and services. The likely future scale and nature of rural poverty and inequality is such that improved social protection and humanitarian relief schemes that support those in crisis or being left behind will still be essential.

The Evolution and Influencing Factors of Total Factor Productivity of Grain Production Environment: Evidence from Poyang Lake Basin, China

The total factor productivity (hereafter TFP) of grain production is important to achieve balanced development, while environmental factors are an important part of TEP. In order to explore the characteristics and patterns of the temporal and spatial evolution of the environmental total factor productivity (hereafter ETFP), the Malmquist-Luerberger index, and the spatial autoregressive panel (SAR panel) model were adopted to analyze the evolutionary rules and the influencing factors of ETFP. In this study, we took Poyang Lake, one of China’s main grain production areas, as a study area, and carried out empirical research based on grain production statistical data. The results show that: (1) ETFP shows a growth trend with the increase of grain production from 2001 to 2017, and a great potential for improvement exists. Moreover, from the perspective of time sequence evolution and decomposition of ETFP, which belongs to the dual-track driver of environmental technical efficiency and environmental technological progress, relevant technologies play an important role in promoting the improvement of TEFP; (2) Given that the objective conditions of gain production remain unchanged, the fact that the urbanization rate and average annual rainfall have a negative effect on ETFP, the explanatory variables such as the business scale per worker, the proportion of grain growing population, industrial agglomeration, the proportion of grain sown area and the average annual temperature all play a positive role. Among the variables, the business scale per worker and the proportion of grain growing population significantly affect ETFP at the 1% level. The average annual rainfall, industrial agglomeration and the proportion of grain sown area significantly affect the ETFP at the 5% level. The average annual temperature significantly affects the ETFP at the 10% level.

Agriculture Development, Pesticide Application and Its Impact on the Environment

Pesticides are indispensable in agricultural production. They have been used by farmers to control weeds and insects, and their remarkable increases in agricultural products have been reported. The increase in the world's population in the 20th century could not have been possible without a parallel increase in food production. About one-third of agricultural products are produced depending on the application of pesticides. Without the use of pesticides, there would be a 78% loss of fruit production, a 54% loss of vegetable production, and a 32% loss of cereal production. Therefore, pesticides play a critical role in reducing diseases and increasing crop yields worldwide. Thus, it is essential to discuss the agricultural development process; the historical perspective, types and specific uses of pesticides; and pesticide behavior, its contamination, and adverse effects on the natural environment. The review study indicates that agricultural development has a long history in many places around the world. The history of pesticide use can be divided into three periods of time. Pesticides are classified by different classification terms such as chemical classes, functional groups, modes of action, and toxicity. Pesticides are used to kill pests and control weeds using chemical ingredients; hence, they can also be toxic to other organisms, including birds, fish, beneficial insects, and non-target plants, as well as air, water, soil, and crops. Moreover, pesticide contamination moves away from the target plants, resulting in environmental pollution. Such chemical residues impact human health through environmental and food contamination. In addition, climate change-related factors also impact on pesticide application and result in increased pesticide usage and pesticide pollution. Therefore, this review will provide the scientific information necessary for pesticide application and management in the future.

Overview of the Potential Impacts of Climate Change on the Microbial Safety of the Dairy Industry

Climate change is expected to affect many different sectors across the food supply chain. The current review paper presents an overview of the effects of climate change on the microbial safety of the dairy supply chain and suggest potential mitigation strategies to limit the impact. Raw milk, the common raw material of dairy products, is vulnerable to climate change, influenced by changes in average temperature and amount of precipitation. This would induce changes in the microbial profile and heat stress in lactating cows, increasing susceptibility to microbial infection and higher levels of microbial contamination. Moreover, climate change affects the entire dairy supply chain and necessitates adaptation of all the current food safety management programs. In particular, the review of current prerequisite programs might be needed as well as revisiting the current microbial specifications of the receiving dairy products and the introduction of new pretreatments with stringent processing regimes. The effects on microbial changes during distribution and consumer handling also would need to be quantified through the use of predictive models. The development of Quantitative Microbial Risk Assessment (QMRA) models, considering the whole farm-to-fork chain to evaluate risk mitigation strategies, will be a key step to prioritize actions towards a climate change-resilient dairy industry.

Assessment of the Heavy Metal Accumulation of Various Green Vegetables Grown in Nevşehir and their Risks Human Health

This study aimed to investigate the accumulation of heavy metal in five different leafy green vegetables grown in 10 different agricultural lands in the province of Nevşehir, Turkey, and determine the human health risks that may arise as a result the consumption of such metals. The heavy metal concentrations found in the soil samples taken from the agricultural lands were as follows: manganese (Mn) > lead (Pb) > arsenic (As) > nickel (Ni) > copper (Cu) > cadmium (Cd). These concentrations were found to be well above the permitted limits imposed by the World Health Organization/Food and Agricultural Organization (WHO/FAO) and the United States Environmental Protection Agency (USEPA). Also, particularly the concentrations of Pb and As were found to be dangerous levels in the soil. According to their accumulation in the vegetables, the detected heavy metal concentrations were listed as Mn > Zn > Cu > Ni > As > Cd. The estimated daily intake amount of the heavy metals was also found to be higher than the limits determined by FAO/WHO. Furthermore, the target hazard quotient of the metals was Mn > As > Cu > Zn > Ni > Cd > Pb. It was found to be > 1 for the sampling areas, except for Cd and Pb. As a result of the study, it was determined that almost all of the annual heavy metal intake amount that the population living in this region should receive was met as a result of the consumption of leafy vegetables grown in the stations designated for this study. It is vital to effectively monitor the heavy metal in the soil and vegetables to reduce metal concentrations in the studied area and to investigate its effects on human health. By doing so, acute and chronic health problems due to the heavy metal exposure in this region can be prevented.

Impact of Climate on Food Security in Mainland China: A New Perspective Based on Characteristics of Major Agricultural Natural Disasters and Grain Loss

Under the background of global warming, China has experienced frequent natural disasters that have seriously affected grain production in recent decades. Based on historical documents from 1978-2014, we explored the spatio-temporal variation of five major kinds of natural disasters and grain losses in China using statistical techniques: the Mann-Kendall (MK) test, social network analysis (SNA), and geographic information system (GIS) tools. The disaster intensity index (Q) clearly showed the variation of natural disasters; all of China experienced a significant increasing trend at an annual scale, reaching its peak (27.77%) in 2000. The step change points in floods, droughts, hail, and low-temperature events began to occur in 1983, 1988, 1988, 1992, respectively, while no obvious trend was detected for typhoon activity from 2001 to 2014. Drought and flood were the most serious types of disaster over the last four decades, accounting for more than 50% of total grain losses. Eight major provinces were identified with severe grain losses: Heilongjiang, Shandong, Henan, Hebei, Anhui, Sichuan, Jiangsu, Hunan, and Hubei. Five studied natural disaster types were identified throughout the seven physical geographical regions. Spatial distribution for the different disaster types showed significant geographical distribution characteristics. Natural disasters gradually became more diverse from north to south. Droughts, hail, and low-temperature disasters were randomly distributed throughout China; flood and typhoon disasters exhibited significant spatial auto-correlation and clustering patterns. Finally, in accordance with the intensity of natural disaster, the annual grain losses at the provincial scale initially increased (ranging from 0.14 million to 3.26 million tonnes in 1978-2000), and then decreased after 2000 (ranging from 3.26 million to 1.58 million tonnes in 2000-2014). The center of gravity of grain losses gradually moved northward. These results emphasize that developing different strategies for disaster prevention and mitigation programs in the major grain producing areas (e.g., Heilongjiang, Shandong, and Henan) are critical and important to China's food security.

Mycotoxin Contamination of Beverages Obtained from Tropical Crops

This review is mainly centered on beverages obtained from tropical crops, including tea, nut milk, coffee, cocoa, and those prepared from fruits. After considering the epidemiological data found on the matrices above, the focus was given to recent methodological approaches to assess the most relevant mycotoxins. Aspects such as singularities among the mycotoxin and the beverage in which their were found, and the economic effects and repercussions that the mycotoxin-tainted ingredients have on the beverage industry were pointed out. Finally, the burden of their consumption through beverages, including risk and health effects on humans, was addressed as well.

Heavy metals (Pb, Cd, Cu, Zn, Ni, Co) in leafy vegetables collected from production sites: their potential health risk to the general population in Shiraz, Iran

Heavy metal contamination of vegetables is a great public health concern. One hundred samples of spinach, dill, cilantro, and cress from the production sites of Shiraz, Iran, and its outskirts were, therefore, examined for lead (Pb), cadmium (Cd), copper (Cu), zinc (Zn), nickel (Ni), and cobalt (Co) content. The potential health risks of these metals to local residents via the consumption of leafy vegetables were also estimated. The mean concentrations of Pb, Cd, Cu, Zn, Ni, and Co were 3.21, 0.28, 4.55, 40.44, 3.11, and 1.86 mg/kg dry weight, respectively. The Pb level exceeded the permissible limit of 0.3 mg/kg in 44.7% of vegetable samples. The other elements were, however, within FAO/WHO standards. The estimated daily intake (EDI) of Pb, Cd, Cu, Zn, Ni, and Co from leafy vegetables was 0.10, 0.01, 0.14, 1.26, 0.10, and 0.06 μg/kg body weight/day, respectively. At the mean and 97.5 percentile levels, all health risk index (HRI) values were less than the safe limit (< 1). Thus, within the area this study was focused on, leafy vegetables did not make a major contribution to the dietary intake of the elements which could be mainly attributed to the low vegetable consumption by the study population (20 g/day). Nevertheless, the lead content of the vegetables should be viewed with some concern. Regular monitoring of heavy metal contamination of foodstuff is recommended to control the sources of contaminants in the food chain.

Emerging risks identification on food and feed - EFSA

The European Food Safety Authority's has established procedures for the identification of emerging risk in food and feed. The main objectives are to: (i) to carry out activities aiming at identifying, assessing and disseminating information on emerging issues and ensure coordination with relevant networks and international organisations; (ii) promote the identification of data sources and data collection and /or data generation in prioritised emerging issues; and the (iii) evaluate of the collected information and identify of emerging risks. The objective(s) of the Standing Working Group on Emerging Risks (SWG-ER) is to collaborate with EFSA on the emerging risks identification (ERI) procedure and provide strategic direction for EFSA work building on past and ongoing projects related to EFSA ERI procedure. The SWG-ER considered the ERI methodologies in place and results obtained by EFSA. It was concluded that a systematic approach to the identification of emerging issues based on experts' networks is the major strength of the procedure but at present, it is mainly focused on single issues, over short to medium time horizons, no consistent weighting or ranking is applied and clear governance of emerging risks with follow-up actions is missing. The analysis highlighted weaknesses with respect to data collection, analysis and integration. No methodology is in place to estimate the value of the procedure outputs in terms of avoided risk and there is urgent need for a communication strategy that addresses the lack of data and knowledge uncertainty and addresses risk perception issues. Recommendations were given in three areas: (i) Further develop a food system-based approach including the integration of social sciences to improve understanding of interactions and dynamics between actors and drivers and the development of horizon scanning protocols; (ii) Improve data processing pipelines to prepare big data analytics, implement a data validation system and develop data sharing agreements to explore mutual benefits; and (iii) Revise the EFSA procedure for emerging risk identification to increase transparency and improve communication.

Vulnerability of global food production to extreme climatic events

It is known that the frequency, intensity or duration of the extreme climatic events have been changing substantially. The ultimate goal of this study was to identify current vulnerabilities of global primary food production against extreme climatic events, and to discuss potential entry points for adaptation planning by means of an explorative vulnerability analysis. Outcomes of this analysis were demonstrated as a composite index where 118 country performances in maintaining safety of food production were compared and ranked against climate change. In order to better interpret the results, cluster analysis technique was used as a tool to group the countries based on their vulnerability index (VI) scores. Results suggested that one sixth of the countries analyzed were subject to high level of exposure (0.45-1), one third to high to very high level of sensitivity (0.41-1) and low to moderate level of adaptive capacity (0-0.59). Proper adaptation strategies for reducing the microbial and chemical contamination of food products, soil and waters on the field were proposed. Finally, availability of data on food safety management systems and occurrence of foodborne outbreaks with global coverage were proposed as key factors for improving the robustness of future vulnerability assessments.

Modelling climate change impacts on mycotoxin contamination

Projected climate change effects will influence primary agricultural systems and thus food security, directly via impacts on yields, and indirectly via impacts on its safety, with mycotoxins considered as crucial hazards. Mycotoxins are produced by a wide variety of fungal species, each having their own characteristics and requirements. The geographic distribution of toxigenic fungi reflects their ecological needs, with thermophilic fungi prevalent at lower latitudes and psychrophiles at the higher latitudes. A resulting gradient of mycotoxin contamination has been repeatedly stressed. Changes in climatic conditions will lead to shifts in the fungal population and the mycotoxin patterns. In general, climate change is expected to increase mycotoxin contamination of crops, but due to the complexity of mycoflora associated to each crop and its interaction with the environment, it appears rash to draw conclusions without specific studies. Very recently first quantitative estimations of impacts of climate change on mycotoxin occurrence have been made. Two studies each applied models of different disciplines including climate projection, crop phenology and fungal/mycotoxin prediction to cereals cultivated in Europe. They were followed by a case study on climate change effects on Alternaria moulds and their mycotoxins in tomato. Results showed that DON contamination of wheat grown in Europe was, in general, expected to increase. However, variation was large, and in some years and some regions a decrease in DON contamination was expected. Regarding aflatoxin contamination of maize grown in Europe, an increase was estimated, mainly in the +2 °C scenario. Two main research gaps were identified related to the (limited) number of existing quantitative models taking into account climate change and their validation in limited areas. Efforts are therefore mandatory to be prepared for future changes and challenges on model validation and limited mycotoxin-crop combinations.

Adaptation and mitigation options to manage aflatoxin contamination in food with a climate change perspective

Understanding the impact of climate change remains vital for food safety and public health. Of particular importance is the influence of climatic conditions on the growth of Aspergillus flavus and production of their toxins. Nevertheless, little is known about the actual impact of climate change on the issue. Setting up of relevant measures to manage the impact has therefore become a daunting task especially in developing nations. Therefore, this study aimed at providing adaptation and mitigation options to manage this risk with a special focus on Kenya where cases of aflatoxicosis have been recurrent. We used a systematic literature review of review and research articles, with limited searching but systematic screening to explore available qualitative and quantitative data. Projections from the data, showed that on average, a 58.9% increase of aflatoxin contamination in the Central and Western parts and a decrease of 44.6% in the Eastern and Southern parts is expected but with several possible scenarios. This makes the impact of climate change on aflatoxin contamination in Kenya complex. To protect the public and environment from the negative impact, a regulatory framework that allows for an integrated management of aflatoxins in a changing climate was proposed. The management practices in the framework are divided into agronomic, post-harvest and institutional levels. Given the multiple points of application, coordination amongst stakeholders along the chain is fundamental. We therefore proposed a complimentary framework that allows the food safety issues to be addressed in an integrated manner while allowing for transparent synergies and trade-offs (in implementing the measures). A policy-oriented foresight should be carried out to provide policy based evidence for the applicability of the proposed adaptation and mitigation measures.

Modelling of fire count data: fire disaster risk in Ghana

Stochastic dynamics involved in ecological count data require distribution fitting procedures to model and make informed judgments. The study provides empirical research, focused on the provision of an early warning system and a spatial graph that can detect societal fire risks. It offers an opportunity for communities, organizations, risk managers, actuaries and governments to be aware of, and understand fire risks, so that they will increase the direct tackling of the threats posed by fire. Statistical distribution fitting method that best helps identify the stochastic dynamics of fire count data is used. The aim is to provide a fire-prediction model and fire spatial graph for observed fire count data. An empirical probability distribution model is fitted to the fire count data and compared to the theoretical probability distribution of the stochastic process of fire count data. The distribution fitted to the fire frequency count data helps identify the class of models that are exhibited by the fire and provides time leading decisions. The research suggests that fire frequency and loss (fire fatalities) count data in Ghana are best modelled with a Negative Binomial Distribution. The spatial map of observed fire frequency and fatality measured over 5 years (2007–2011) offers in this study a first regional assessment of fire frequency and fire fatality in Ghana.