Food authenticity and the interactions with human health and climate change

Abstract

Food authenticity and fraud, as well as the interest in food traceability have become a topic of increasing interest not only for consumers but also for the research community and the food manufacturing industry. Food authenticity and fraud are becoming prevalent in both the food supply and value chains since ancient times where different issues (e.g., food spoilage during shipment and storage, mixing decay foods with fresh products) has resulted in foods that influence consumers health. The effect of climate change on the quality of food ingredients and products could also have the potential to influence food authenticity. However, this issue has not been considered. This article focused on the interactions between consumer health and the potential effects of climate change on food authenticity and fraud. The role of technology and development of risk management tools to mitigate these issues are also discussed. Where applicable papers that underline the links between the interactions of climate change, human health and food fraud were referenced.

Keywords:

• Fraud
• health
• climate change
• sustainability
• technology

Introduction

Food adulteration and fraud events covers a wide range of disruptions in the food supply and value chains (Esteki et al. 2019). These disruptions include events linked with food authenticity, provenance, mislabeling, cross-contamination, and fraud. Different terminologies and words have been used to characterize and define a wide range of common incidents related to food adulteration and fraud (Manning and Soon 2016; Spink and Moyer 2011; Spink et al. 2016, Spink, Moyer, and Speier-Pero 2016; Danezis et al. 2010; Cuadros-Rodríguez et al. 2016; Davidson et al. 2017).

Food fraud and adulteration, where the purpose of the intentional fraud ranges from personal retaliation and economic gain to ideological objectives (e.g., food crime and food terrorism) have been reported in detail in the scientific literature and mass media (e.g., radio, television, internet, newspapers) (Spink and Moyer 2011; Spink et al. 2016, Spink, Moyer, and Speier-Pero 2016; Bannor et al. 2023; SSAFE 2020; Spink 2019).

Nowadays, consumers not only demand information about the nutritive or health value of foods but also on other issues intimately connected with the authenticity, adulteration, and fraud of food (Bannor et al. 2023; Danezis et al. 2010; Cuadros-Rodríguez et al. 2016; Spink 2019). For example, issues linked with food adulteration and fraud have been considered critical for the development of legislation, regulations, and food standards in different countries (Manning and Soon 2016; Bannor et al. 2023; Danezis et al. 2010; Cuadros-Rodríguez et al. 2016; Esteki et al. 2019; Visciano and Schirone 2021).

Food ingredients and products have been susceptible to different degrees of adulteration or mislabeling from ancient Rome (Bush 2002), through the Middle Ages to present times (Coley et al. 2011; Moore et al. 2012; Esteki et al. 2019; van Ruth et al. 2017, van Ruth et al. 2018).

The several examples in the scientific literature and mass media illustrated the occurrence of these historical events, including the adulteration of foods subjected to spoilage (e.g., fungal contamination) during transport and storage by mixing fresh food into a spoilt food lot (Manning and Soon 2016; Folinas et al. 2006; Olsen and Borit 2018; Esteki et al. 2019). Where the substitution of expensive ingredients and products with low quality ones from unknown sources, and the addition of foreign materials (e.g., coloring or masking agents) are specific examples reported in the literature (van Ruth et al. 2017, van Ruth et al. 2018).

Overall, food adulteration and fraud have dominated different events that directly or indirectly affect either consumers health, or even causing their death (Coley et al. 2011; Moore et al. 2012; Estekiet al. 2019). Specifically, the addition of melamine to infant formula in China, or the horse meat scandal in Europe, are examples of these disruptions that affect the trust and wellbeing of consumers (Xiu and Klein 2010; Moore et al. 2012; Aung and Chang 2014; Yang et al. 2019).

It has been estimated that between 5 and 9% of the global world food trade are adulterated (Giannakas and Yiannaka 2023). However, the scientific literature has showed a reality that is of high concern for both consumers and the food industry. For example, it has been reported that at least 80% of the Italian extra virgin olive oil has been adulterated with low quality vegetable oils, while 74% of the seafood sold in sushi restaurants and 18% of the seafood sold in grocery stores were mislabeled in the US market (Giannakas and Yiannaka 2023). More importantly, the total cost of food fraud for the food manufacturing industry is estimated to be around US$ 30 to 40 billion per year (approximately $AU 2 to 3 billion in Australia alone) (Brooks et al. 2021; Giannakas and Yiannaka 2023). In addition to the economic impact of food adulteration causes to the food manufacturing industry, food fraud has been also linked to criminal activity where organized crime has been directly involved in this process (Spink and Moyer 2011; Spink et al. 2016; Spink et al. 2016; Spink et al. 2017; SSAFE 2020; Spink 2019; GFSI 2014, 2018; Elliott, 2014).

This article focused on the interactions between consumer health and the potential effects of climate change on food authenticity and fraud. The role of technology and development of risk management tools to mitigate these issues are also discussed. Where applicable papers that underline the links between the interactions of climate change, human health and food fraud were referenced.

How are food adulteration and fraud defined?

Food authenticity and fraud are terms that incorporates the deliberate and intentional substitution, addition, tampering, or misrepresentation of food ingredients and products, including the false or misleading declaration made about a given food (Nychaset al. 2016; Spink and Moyer 2011; Spink et al. 2016; Spink et al. 2016; Spink et al. 2017; SSAFE 2020; Spink 2019; GFSI 2014, 2018; Robson et al. 2021). Nonetheless, there is no consensus around the use of a specific terminology. However, there is a worldwide agreement that food fraud is associated with the intentional act carried out for financial gain (Avery 2014). The US Pharmacopeial Convention defined food fraud as any food ingredient that is subjected to a deceitful addition of a non-authentic substance, removal, or replacement of authentic ingredients without the knowledge of the consumer for the economic gain of the producer or seller (Nychas et al. 2016; Johnson 2014; Robson et al. 2021).

For example, milk can be diluted with either water to increase the volume or with starch to increase the concentration of solids. In the same way, honey has been adulterated with different sugars, either by adding them directly to the product or by overfeeding sugar to the bees. These practices have resulted in a decrease in consumer trust in the nutritional and healthy properties of this product (Fakhlaie et al. 2020; Brooks et al. 2021; Spink and Moyer 2011, Danezis et al. 2010; Cuadros-Rodríguez et al. 2016; Davidson et al. 2017).

As defined above, the practice of intentional adulteration is directly linked with economical motives, including the imitation of a food ingredient or product as part of a business strategy, or as a tactic to increase the quantity of the food produced, or as a strategy to increase the sales (Spink and Moyer 2011; Danezis et al. 2010; Cuadros-Rodríguez et al. 2016; Davidson et al. 2017; Fakhlaie et al. 2020). The intentional adulteration of foods in not only associated with a business or marketing strategy. For example, Varghese and Ramamoorthy (2023) noted that the increase in the use of organic and inorganic colorants is linked with the increase in the consumption of packaged foods, particularly in developing countries like India. The same authors highlighted that this can be associated with the need for a food company to satisfy food demand due to the fast-growing population, or to make a maximum profit from food products (Varghese and Ramamoorthy 2023).

The mix of spoiled fresh produce with unspoiled or products of higher quality, or the addition of either natural or chemical dyes to enhance the attractiveness of the food to the consumers are also examples of intentional adulteration (Varghese and Ramamoorthy 2023). The use of rotten ingredients and the addition of toxic substances (e.g., unauthorized dyes, harmful preservatives), the misbranding and altering the manufacturing and expiring dates, as well as alterations of the list or mislabeling ingredients with similar ones are all common examples of food adulteration in the supply and value chains (Spink and Moyer 2011, Danezis et al. 2010; Cuadros-Rodríguez et al. 2016; Davidson et al. 2017; Fakhlaie et al. 2020; Varghese and Ramamoorthy 2023).

Other type of adulteration may include the addition of inexpensive, unhealthy, or low-quality ingredients, often inorganic materials (e.g., sand, dust, clay, mud, and pebbles) to increase the weight of the product – these could compromise consumer health and wellbeing (Sai et al. 2021; Bannor et al. 2023 Spink and Moyer 2011, Danezis et al. 2010; Cuadros-Rodríguez et al. 2016; Davidson et al. 2017).

Consumers and the food manufacturing industry are also concerned with the non-intentional cross-contamination of foods that might increase the prevalence of food allergies or other health issues along the supply and value chains (Galvin-King et al. 2018; Johnson 2014; Sharma et al. 2017; Robson et al. 2021; Fakhlaei et al. 2020). Unintentional adulteration might include the addition of hormones, and chemical substances such as calcium carbide (e.g., acetylene gas) or ethylene to hasten the ripening of fruits, commonly utilized by the farmers. An example of this, is the use of carbide to accelerate mango ripeness in order to meet market demands in a short period of time (Varghese and Ramamoorthy 2023).

Implications of food fraud on consumer health and wellbeing

Food adulteration and fraud not only have an economical effect but also an impact on the nutritional value of the food and ultimately human health (Carcea et al. 2009; Karippacheril et al. 2017; Manning and Soon, 2016; Fan et al. 2021). Adulterated foods (e.g., milk adulterated with melamine; olive oil adulterated with inexpensive vegetable oils) can be highly harmful to the consumer, as they may contain toxic substances that lead to health issues, such as causing nutritional deficiencies, kidney or liver disorders (Spink and Moyer 2011; Spink et al. 2016, Spink et al. 2016; Spink et al. 2017; SSAFE 2020; Spink 2019; GFSI 2014, 2018). The presence of non-declared allergens in foods, intentionally or unintentionally, is also an important aspect issue that can affect consumers health (Ellis et al. 2012; Ellis et al. 2015; Brooks et al. 2017; Fritsche 2018; Spink et al. 2016; Spink 2019; Cozzolino 2015, 2019; Callao and Ruisánchez 2018; Power and Cozzolino 2020; Amaral et al. 2021; Astill et al. 2019; Sai et al. 2021; Visciano and Schirone 2021).

In this context, prevention and increase awareness about food fraud will make consumers more alert about health hazards. For example, the addition of melamine to powder milk in China in July 2008 had produced disastrous outcomes for consumers. Melamine, a flame-retardant used in the furniture industry as a plastic namely melamine-formaldehyde resin, had been added to increase the amount of nitrogen, and therefore the apparent protein content in the powdered milk and powdered infant formula (Spink and Moyer). It was estimated that more than 300,000 children suffered from kidney failure, of which 50,000 babies were hospitalized in a critical condition where six infants died because of kidney stones (Friel et al. 2020). It is important to remark that the use of melamine in food is not approved by the World Health Organization (WHO) or any national authorities (Friel et al. 2020). Although the case of melamine is one of the most notorious, several other cases have been reported as having a direct effect on the health of consumers worldwide (Friel et al. 2020; Brooks et al. 2021). In the same way, the dilution of milk by the addition of water was responsible of causing more than 10 deaths in China due to protein malnutrition and nephrotoxicity (Spink and Moyer 2011).

Verifying the authenticity of food is not only critical in reducing the negative effects on consumer health (Amaral et al. 2021; Astill et al. 2019) but also in maintaining a brand reputation. Recent food safety and security issues in Europe (e.g., beef contaminated with horse meat) (Madichie 2015), the case of powder milk contaminated with melamine in China, have shown that misbranded, or even fake foods represent a substantial danger to the health and safety of consumers (Amaral et al. 2021; Astill et al. 2019).

In addition to health issues, wellbeing aspects such as religious believes also become of great importance to the consumers. An example of this is the growing efforts to develop traceability systems of the Halal process and the intricacies of this process along the entire supply and value chain (Nakyinsige et al. 2012). Although food fraud is typically associated with the selling of inferior or mislabeled food products, selling foods that do not meet secular or religious requirements can also be considered as an example of a more subtle case of adulteration (Nakyinsige et al. 2012; Rejeb 2018). The adulteration (e.g., mislabeling, cross-contamination) of Halal foods with Haram (forbidden) items has been a growing issue in Muslim and non-Muslim countries (Rejeb 2018). For Muslims, it is not only the food that needs to be Halal, but the whole supply chain from production to consumption needs to be pure and certified (Rejeb 2018; Voak 2021). Halal certification and traceability provides recognition of the quality and safety of a product through the concept of halal tayyib that is implemented throughout the entire supply chain, from farm to fork (Rejeb 2018; Voak 2021). The process of certification and traceability includes good animal husbandry practices, transparent pre-slaughter management and slaughtering process, as well as post-slaughter management practices (Yaacob et al. 2018; Zainalabidin et al. 2019; Azimi et al. 2020).

In particular, meat adulteration is also unacceptable in other religious groups (e.g., Buddhism, Hinduism, Jainism, Judaism) as well as with consumers concerned with the inclusion of certain animal products due to animal welfare or environmental reasons, or with both vegetarians and vegans. For some consumers, there are specific days when the eating of some foods is prohibited by religious beliefs such as Jews may not eat meat on the Sabbath, Catholics may not eat red meat on Fridays, nor on Ash Wednesday and Good Friday where the latter applies to the age of Catholics over the age of 14.

The potential effect of climate change on food adulteration

For producers to be financially rewarded they should follow sustainable production guidelines and protocols that will be supported by robust monitoring and verification systems (Amaral et al. 2021; Astill et al. 2019; Chandra et al. 2017). Consequently, robust monitoring and verification systems are needed to provide with a credible and compelling evidence of the environmental and social benefits derived from the application of regenerative and sustainable practices in agri-food systems (Ahearn et al. 2016; Primrose et al. 2010; Poore and Nemecek 2018; Whitfield et al. 2018; García-Oliveira et al. 2022). Although monitoring and verification systems will provide evidence about the different management systems and practices that assure carbon sequestration, animal welfare, nutritional and functional properties of foods, they are not widely implemented by the agri-food production industries (Ahearn et al. 2016; Primrose et al. 2010; Poore and Nemecek 2018; Whitfield, Challinor, and Rees 2018; García-Oliveira et al. 2022). For example, the Australian Government throughout the Australian Competition and Consumer Commission (ACCC) is increasingly acting against businesses who use greenwashing terms to dishonestly promote their products as environmentally friendly or green. In this regards, the ACCC has the task of advising businesses to guarantee that claims are confirmed by robust and trustworthy scientific information, transparency in the information across the food supply chains, as well as the utilization and implementation of reliable certification protocols and systems (Ahearn et al. 2016; Primrose et al. 2010; Poore and Nemecek 2018; Whitfield et al. 2018; García-Oliveira et al. 2022; Australian Competition and Consumer Commission 2022). Advances in the knowledge and practical experience within the regenerative agri-food systems will create new opportunities for market innovation to drive growth and competitiveness within the sustainable foods industry (Ahearn et al. 2016; Primrose et al. 2010; Poore and Nemecek 2018; Whitfield et al. 2018; García-Oliveira et al. 2022). These will provide with new challenges to guarantee the authenticity of agri-food systems.

The effect of climate change has been mainly associated with its impact on crop productivity (e.g., yield) and less on its effects on food safety and security (Gregory et al. 2005; Gregory 2010; Gutteridge 2018). Both climate change and natural disasters affect agriculture and food production systems in several ways. These effects stretch from direct impact on crop production, such as yield; to changes in the market by influencing food prices or determining disruptions on the supply chain thereby making the demand higher than the supply, adding pressure on the food chain making it more susceptible to food fraud (Gregory et al. 2005; Gregory 2010; DaMatta et al. 2010; Gutteridge 2018).

Extreme climate events comprising of floods, heat waves, droughts, and wildfires are directly or indirectly affecting food production systems (Gregory et al. 2005; Gregory 2010). A wide range of studies have reported on the frequency, intensity and duration of extreme weather events (e.g., increased temperature, precipitation) on global warming (e.g., increase in CO2, increase sea levels, land degradation) and their direct effects on food production (e.g., crop yield, grain and fruit composition and quality) (Williams et al. 1995; Ainsworth et al. 2008; Rouphael et al. 2018; Bisbis et al. 2018).

It has been reported the influence of climate change on wild fishing, seafood and aquaculture production as well as marine biodiversity has been reviewed by Lemasson et al. (2019). Similarly, the effect of high ambient temperatures on the incidence of dark cuts in beef cattle has been reported (Gregory 2010). Kadim et al. (2004) have also reported an increase in the proportion of dark cuts in meat from the US and Oman. Godde et al. (2021) reviewed the evidence of climate change on the livestock food supply chain and noted that it would have a profound effect on animal products in terms of the quantity (food security), nutritional quality, safety, sensory appeal, price and social acceptability.

Climate change is affecting the agri-food systems where different events are having a considerable influence on food security as well as on the nutritional composition of commodities and foods. Studies have suggested the use of the term “climate-smart food systems” to address and analyze the complexity and challenges connected with the current and future trends in climate change that will modulate food sustainability (Gregory et al. 2005; DaMatta et al. 2010; Gutteridge 2018). Despite the influences of climate change on agri-food systems, and its impact on the chemical, functional and nutritional properties of food, the extent of the direct and indirect effects of climate change on food authenticity and fraud have not been fully evaluated. More effort should be put into better understanding the influence and impact of climate change on the incidence of food fraud. Figure 1 illustrates the relationship between food fraud, climate change, production systems and human health.

Figure 1. The relationship between food fraud/adulteration, climate change, agri-production systems and human health.

Consequences of food adulteration in the food supply and value chains

In the scientific literature, the adulteration of food, particularly with the intent of fraud, is considered a persistent battle between the “science of deception” with the “science of detection” (Shears 2008). Regardless of recent advances in food science (e.g., new methods, techniques), chemistry, physics, the fraudsters always find deceptive means to scam the consumer and circumvent current detection methods (Ruiz-Altisent et al. 2010).

The COVID pandemic, regional wars and climate change have caused disruptions in the supply and value chains and have alerted consumers about issues associated with food security, food sustainability as well as food authentication and fraud (Aung and Chang 2014; Montgomery et al. 2020; Laborde et al. 2021; Fan et al. 2021; Udmale et al. 2020; Brooks et al. 2021). Therefore, both food authenticity and fraud, as well as the interest in food traceability have become a topic of increasing interest not only for the consumers but also for the research community and the food manufacturing industry (Godfrey 2019; Dabbene et al. 2014; van Ruth et al. 2018).

Food products and agricultural commodities are not exempt from challenges related to adulteration, fraud, or mislabeling (Galvin-King et al. 2018; Huck et al. 2016). As defined above, adulteration and fraud can be solely the addition of cheap chemicals or food waste products (e.g., dilution or addition) like the addition of foreign materials, the dilution or addition of water (Galvin-King et al. 2018; Huck et al. 2016). High-quality or premium ingredients are the most frequent foods that can be replaced with cheaper or counterfeit materials, which influence their nutritive value, functionality, and composition of the food (Galvin-King et al. 2018). Food adulteration can also trigger a wide range of disruptions in the supply and value chains, creating fear among the consumers of high-quality foods (Galvin-King et al. 2018). Food products of high economic value, such as premium food products, are frequently the target of adulteration and fraud. The scientific literature has described that the disruptors involved in the process of food adulteration can be defined as a type of modern terrorists (Aung and Chang 2014; Charlebois et al. 2017; Fox et al. 2018; Kleemans 2014). They proceed ahead of enforcement authorities and in some cases have succeeded in using terrorist devices by overcoming public authorities and even the research community (Aung and Chang 2014; Charlebois et al. 2017; Fox et al. 2018; Kleemans 2014).

Guaranteeing the authenticity of foods has become a priority for the manufacturing food industry and consumers, as well as by governments and authorities (Carcea et al. 2009; Robson et al. 2021; Medina et al. 2019). Currently, consumers require accurate and comprehensive information about food products. This has become more prevailing as indicated by the increased number of reported cases associated with either intentional or unintentional adulteration of food (Carcea et al. 2009; Ellis et al. 2015; Brooks et al. 2017; Fritsche 2018; Spink et al. 2016; Spink 2019; Cozzolino 2015, 2019; Callao and Ruisánchez 2018; Power and Cozzolino 2020).

Regardless of the implementation of strict regulations and labeling protocols by various regulatory authorities and governments, both food authenticity and fraud remain of international concern for the food manufacturing industry (Carcea et al. 2009; Ellis et al. 2015; Brooks et al. 2017; Fritsche 2018; Spink et al. 2016; Spink 2019; Cozzolino 2015; Callao and Ruisánchez 2018; Power and Cozzolino 2020). Several researchers have highlighted and presented the current state of the art of the different technologies and methods available to guarantee the authenticity of a food. A wide range of applications and approaches (i.e., different methods and techniques, food matrices), including the incorporation of the internet of things (IoT), machine learning (ML), AI have been utilized to target food authentication, adulteration, fraud and even provenance in different food products (Ellis et al. 2015; Brooks et al. 2017; Fritsche 2018; Spink et al. 2016; Spink 2019; Cozzolino 2015; Callao and Ruisánchez 2018; Power and Cozzolino 2020; McGrath et al. 2018; Oliveira, Cruz-Tirado, and Barbin 2019; Riedl, Esslinger, and Fauhl-Hassek 2015).

Food fraud in the supply and value chains – some examples

Foods of great economic value are the ones that are usually subjected to food adulteration or fraud. They include premium grains (Giannetti et al. 2016; Psodorov et al. 2015; Ratnasekhar et al. 2021; Saa et al. 2019), honey (Rachineni et al. 2022; Fakhlaei et al. 2020), spices (e.g., saffron, oregano, pepper) (Dhanya and Bhas 2010; Rubert et al. 2016; Wilde et al. 2019; Wielogorska et al. 2018), meat (Camin et al. 2007; Camin et al. 2017; Rady and Adedeji 2018), milk, olive oil (Pastor et al. 2020; Casadei et al. 2021; Pereira et al. 2021), and wine (Ranaweera et al. 2021) to mention a few (Kamal and Karoui 2015; Astill et al. 2019; Amaral 2021; Alewijn et al. 2016; Lim et al. 2018; Liu et al. 2023). However, each of these foods present with their unique technical challenges to verify their authenticity. Some examples of adulteration are briefly described in Table 1 and in the section below. Fruit juices can be adulterated by watered down before the addition of artificial coloring and sweetener to make them appear more concentrated. Olive oil is a premium food frequently subjected to adulteration, where its origin and quality is usually targeted. It has been reported that up to 80% of Italian olive oil is fake (Casadei et al. 2021; Pereira et al. 2021). Pure olive oil can be mixed with other vegetable oils such as canola or sunflower oil. Olive oil of lesser quality can be sold as virgin or extra virgin (Casadei et al. 2021; Pereira et al. 2021). The adulteration of spices (e.g., oregano, saffron) is also considered one of the most ancient example of food fraud in the food supply chain (Anibal et al. 2009; Black et al. 2016; Schaarschmidt et al. 2018; Oliveira et al. 2019). Coffee is another commodity food that is commonly adulterated (e.g., high-quality beans mixed with low-quality beans) or intentionally mislabeled (Toci et al. 2016; Flores-Valdez et al. 2020; de Carvalho et al. 2023). Another commonly food that is extensively adulterated is honey. Honey can be adulterated by the addition of different ingredients including maple syrup, corn syrup, antibiotics and even heavy metals (Rachineni et al. 2022; Fakhlaei et al. 2020). Fish mislabeling has also become very popular in certain countries where a recent US study has found that up to one in five pieces of seafood had been mislabeled (Pappalardo and Ferrito 2015; Power and Cozzolino 2020).

Table 1. Examples of food fraud and sources of adulteration in different high value foods as reported by different authors.

Food	Adulteration, mislabeling with	Reference
Olive oil	Addition of cheap oils, mislabeling	Casadei et al. (2021); Pereira et al. (2021)
Meat	Mislabeling of species, cuts, cross-contamination with other species, addition of water	Camin et al. (2007); Camin et al. (2017); Rady and Adedeji (2018)
Coffee	Addition of sawdust, leaves, mixture with different species	Toci et al. (2016)
Milk	Addition of urea, melamine	Xiu and Klein (2010)
Honey	Addition of sugars and syrups	Rachineni et al. 2022; Fakhlaei et al. 2020
Wine	Mislabeling, addition of methanol, dilution with water	Chandra et al. (2017); Chapman et al. (2019); Ranaweera et al. (2021)

As milk has become more common in Asian markets, adulteration through the addition of contaminants such as urea, caustic soda and melamine has been common (Xiu and Klein 2010). Adulteration of grapes and wines is also an important issue (Chandra et al. 2017; Chapman et al. 2019; Ranaweera et al. 2021). Blending different varieties without legal declaration, adding chemicals (e.g., methanol) or mixing in low-quality wine to deceive the consumer into believing the product is of higher quality is common practice (Chandra et al. 2017; Chapman et al. 2019; Ranaweera et al. 2021).

Meat adulteration has driven concerns among consumers and in the meat supply and value chain regarding food and consumer safety. For example, the horsemeat (‘horsegate’) scandal of 2013 that occurred in UK, France and Sweden (Brooks et al. 2017; Boyacı et al. 2014; Rady and Adedeji 2018; Hassoun et al. 2020) or the adulteration of beef and pork meat, and products (e.g., minced meat, burgers patties, sausages) with donkey, goat and water buffalo meats in South Africa (Cawthorn et al. 2013). Walker and collaborators (2013) wrote an interesting report on the history of the substitution of meat with other species in the UK – they note as early as 1886 sick horses were shipped to Europe to be slaughtered and returned to the UK as sausages and timed meat. Issues such as meat species substitution are a major problem for the meat industry worldwide, concerning not only changes in the nutrition and composition value but also economic and safety issues (some of the horse meat was found to be contaminated with phenylbutazone – a drug commonly used on horses) since they cannot be easily detected by visual inspection of the meat (Boyacı et al. 2014; Rady and Adedeji 2018; Hassoun et al. 2020). In response to the horsegate scandal, the Department for Environment, Food and Rural Affairs and the UK Food Standards Agency has established a series of recommendations addressing the weakness of the value chain, and the implementation of a task force to assure the integrity of the food supply network, suggesting measurements on how to address these issues in the meat value chain (Brooks et al. 2018; Food Crime Newsletter 2020).

Food fraud, and specifically food adulteration is not only associated with the alteration of the nutritional value or composition of the food due to the change of ingredients or products but also with the false claims about the system of production. For example, a food can be claimed to be an organic product where non-organic ingredients were used can be sold as organic. This form of adulteration has been reported in the grain industry (Liu et al. 2023) and in the horticulture and fresh produce market (Pandiselvam et al. 2022). Table 1 provides with a summary of some highly value foods and the types of adulteration as reported in the scientific literature.

Challenges and opportunities – the role of technology and data analytics to target food authenticity

The increasing focus on food adulteration and fraud by both consumers and the food manufacturing industry, has determined several opportunities and challenges. For example, the analysis as well as monitoring of food authenticity issues have provided opportunities for new technologies such as those that embrace the digital era (e.g., blockchain, the utilization of sensing technologies) (Ruiz-Garcia et al. 2009; Kamble et al. 2020) and the Internet of things (IoT) as well as foster the development of new strategies or systems to monitor food adulteration (Fritsche 2018; Moore et al. 2012; Cavanna et al. 2018; Cortés et al. 2019). Targeting food authenticity and fraud requires a new approach in terms of the type of analysis required and the interpretation of the results (Cavanna et al. 2018; Moore et al. 2012; Serazetdinova et al. 2019; Cortés et al. 2019) in addition, to better understand the whole food system (e.g., farm to fork). The inclusion of information from other sources such as those associated with food functionality and type of ingredients, consumers choices, market information will be of importance.

The delay in the adoption of new technologies and data analytics by the food manufacturing industry, regulatory authorities, and routine quality control laboratories are some major concerns. The implementation and selection of agile and modern analytical methods, combined with the use of data analytics such as machine learning tools, including challenges associated with sampling, the definition of what is considered an authentic sample, among other issues, are still not well defined or understood. Furthermore, the utilization of technology and data analytics in addressing food adulteration and fraud is hindered by the lack of training or education, not only at the practical level but also at the academic level where the need to have highly skilled and qualified staff is essential.

Most of the analytical techniques utilized to assure and monitor food authenticity and fraud are considered non-target in nature, however, the vast amount of research and the wide range of practical and successful examples in this field have indicated their potential to be utilized as routine quality control methods (Rubert et al. 2016; Saa et al. 2019; Saeys et al. 2019; Wielogorska et al. 2018; Wilde et al. 2019; Cavanna et al. 2018). Traditional methodologies or analytical approaches currently in use are comparatively more expensive, time-consuming, and require highly specialized instrumentation and skilled operators (Cavanna et al. 2018). Therefore, the incorporation of sensing technologies where less consumables and less time in sample preparation are required, have become more attractive as they can be a more time and cost-effective analysis per sample.

It is a given that the use of digital and sensing technologies to assess the authenticity of foods at distribution centers will become important to assure compliance with quality control and regulatory systems (Beć and Huck 2019; Beć et al. 2020). Testing agricultural commodities and food at the collection point (e.g., distribution centers; market) minimizes possible deterioration and damage to the food during transportation to the more traditional analytical or quality control laboratories. Moreover, the advent of sensing technologies eliminates the need for expensive and time-consuming analyses utilized along the food supply and value chains to guarantee quality and authenticity.

These technologies are highly depended on operator expertise as obtaining reliable results with high accuracy requires specialized knowledge. In this respect providing training for individuals in the food supply and value chain will be useful. Current developments in portable devices have also provided new tools that collect multi-dimensional and complex data. The integration of data transfer systems into different devices would enable remote data storage and so maintain records for food fraud (Esteki et al. 2019). Sensors have proven useful for monitoring most of the different steps of the supply and value chains (from gate to plate). The incorporation of sensing technologies, IoT, blockchain, throughout the entire food value chain provides numerous benefits, such as increasing productivity, safety, consumer confidence, enhancing the transparency of the food systems.

Managing the risks associated with food fraud in the value chain

As manufacturer and consumer awareness of food authenticity and fraud increases, companies choose to make use of food fraud mitigation strategies to manage the risk to their business. These strategies consist of a set of procedures adopted to protect a food product and its raw materials from intentional adulteration (Manning and Soon 2016; BRCGS 2022). In addition to reducing the likelihood of fraudulent attacks, the objectives of food fraud mitigation strategies are to minimize the impact of fraud on the company, protect a company’s brand reputation, and instill trust among customers by demonstrating reasonable precautions to reduce the risk of fraud occurring in the food supply chain (Ahmed and Al-Mahmood 2023).

Global standards such as the Global Food Safety Initiative (GFSI) require food companies to have systems in place which minimize the risk of purchasing fraudulent raw materials and ensure all products sold are authentic with respect to their ingredient specification or product descriptions and claims (Spink 2019; BRCGS 2022). Within the food trade industry, many food production companies invest in obtaining certifications from quality programs endorsed by GSFI such as BRC, FSSC 22000 and IFS (FSSC 2018; IFS 2018; BRCGS 2022; Popping et al. 2022). These GFSI-compliant certifications are generally accepted as an international quality and safety benchmark for food commerce and over 65% of the global food trade industry uses these guidelines (Spink 2019). It is crucial for companies to obtain this certification to be a supplier for some food companies and retailers, especially international partners.

Food fraud mitigation strategies typically consist of two systems that operate in conjunction with HACCP (Hazard Analysis Critical Control Point), namely VACCP (Vulnerability Analysis Critical Control Point) and TACCP (Threat Analysis Critical Control Point). To this end, HACCP relates to unintentional adulteration of food products with microbial, physical or chemical hazards focusing on the prevention of foodborne illness (BRCGS 2022; Popping et al. 2022). Both TACCP and VACCP are classified as intentional adulteration, however, VACCP focuses on economically motivated fraud, while TACCP is driven by human behavioral factors such as retaliation or ideological beliefs (BRCGS 2022; Popping et al. 2022). GFSI requires food companies to have separate documented proof of each of these systems, including a thorough vulnerability assessment for the two food fraud mitigation systems (Popping et al. 2022).

Vulnerability assessments apply horizon-scanning techniques to identify opportunities for fraud in the supply chain (Popping et al. 2022). A documented vulnerability assessment study should include information surrounding the significant risk factors in the supply chain, including the significant risks outlined in Figure 2 (Popping et al. 2022). After identifying potential risks in the supply chain, risks are given quantitative scores. Typically, FSSC 22000 and IFS schemes use a likelihood versus severity matrix to generate scores, while BRCGS modified the same matrix to include the profitability of a specific fraud (FSSC 2018; IFS 2018; BRCGS 2022; Popping et al. 2022). After the hazards are quantified, they can be ranked, and a company can focus on controlling the most significant risks of fraud to their food manufacturing site. Control measures include assurance processes such as thorough supplier vetting or testing schemes to verify the authenticity of incoming raw materials (BRCGS 2022; Popping et al. 2022).

Figure 2. A summary of food fraud risks factors typically encountered in the food supply chain.

Though the use of vulnerability assessments can be extremely valuable in providing insight into the enterprise risks associated with the food production industry, it is subjective and highly dependent on the level of collective expertise in the food fraud task force and the quality of information gathered during horizon scanning. This process has been streamlined through the release of the SSAFE (Safe Supply of Affordable Food Everywhere) tool, which makes use of a set of questions to aid in the process of generating a vulnerability assessment that meets GFSI standards (Popping et al. 2022). Similarly, artificial intelligence such as large language models or deep learning models could also potentially be implemented to aid food manufacturing companies in generating more comprehensive vulnerability assessments in the future. Instead of investing in the appointment of a food fraud task force, companies would subscribe to big data packages consisting of information on commodity prices, food fraud incident reports and current economic affairs as training data for artificial intelligence models. This would be more time effective and allow human resources to shift their focus to the development of effective risk management strategies for only the prominent risks highlighted by AI (Figure 3).

Figure 3. A brief overview of the process of developing a food fraud mitigation strategy (adapted from Spink et al. 2019).

Concluding remarks

The prevalence of food authenticity and fraud in the food supply and value chains has increased the incidence of health issues and even dead among consumers. Other aspects of consumers wellbeing (e.g., religious believes) can also be influenced by the prevalence of food authenticity and fraud.

Detecting and monitoring food authenticity and fraud requires the incorporation of technology and data analytics into the food supply and value chain. Understanding the background of these new sensing technologies has become essential for the interpretation of the different data processing and analytics tools. A growing number of research groups and to a lesser extent the food manufacturing industry, have embraced the utilization of sensing technologies to monitor food authenticity and fraud. The extent to which results from food fraud analysis using these noninvasive technologies and data analytics are repeatable using traditional biological or biochemical procedures as verification is of paramount importance in judging the reliability of the application of these technologies as well as ensuring public and authority acceptance thereof.

Climate change and its direct effects on the chemical composition and nutritive value of commodities and food ingredients will influence food origin and provenance, and consequently the prevalence of food fraud. This effect is not yet well understood or evaluated in the context of food safety and security. Understanding food fraud and its relationship with climate change and human health is beyond the analysis of a single element, compound, or event. This process requires a systems approach that should incorporate multidisciplinary teams.

A close collaboration between researchers, compliance authorities, industry and consumers is critical for the implementation and understanding of systems of monitoring and verification protocols that can help to better understand the close relationships between climate change, sustainability, and health. Targeting food fraud in the context of changes in climate and production systems will require the development of decision-management tools that should better understand the whole food supply and value chain.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Internal University of Queensland Institutional funds.