A sense of ginger fraud: prevalence and deconstruction of the China

npj Science of Food volume 6, Article number: 51 (2022) Cite this article

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As an important spice, ginger has been widely distributed in the Chinese and the European Union (EU) markets, the two largest trading areas, in various forms. The ginger supply chain between China and the EU is long and complex, providing opportunities for fraudsters to deceive consumers. However, limited attention has been given to food fraud in ginger, and there is a lack of research on this topic. In this review, ginger was used as an example for interpreting the fraud issues within low-priced and high-trade volume spice products. This review aims to summarize the open access information from food and food fraud databases, literature, and stakeholders about ginger fraud, and to map, deconstruct and analyse the food fraud vulnerability in the supply chain. In addition, potential testing strategies to detect ginger fraud were also discussed. The investigation of food fraud databases, a semi-structured literature review and online interviews with stakeholders revealed that adulteration is the major fraud type in ginger products. And the most vulnerable ginger products are ground ginger and finely processed ginger. The ginger supply chain from China to the EU comprises nine stages and is medium vulnerable to food fraud, both in regard to opportunities and motivational drivers. To ensure the integrity of the ginger supply chain, there is a need to apply fraud vulnerability tools in the companies of the industry. In addition, screening and confirmatory techniques based on the characteristics of ginger should be utilised for monitoring fraud issues in the supply chain.

Food fraud is generally defined as one of the behaviours that deceive consumers for financial gain1. Food fraud types include but are not limited to, adulteration, substitution, addition, tampering or misrepresentation of food, food ingredients or food packing; or false and/or misleading statements made about a product2. Food fraud has troubled the food industry throughout history3. The 2008 melamine-contaminated milk powder scandal in China and the 2013 horsemeat scandal in the European Union (EU) shed light on the problem again and highlighted that food fraud is a vital topic that has been greatly overlooked by the food industry for many years4,5. Food fraud can cause economic and reputational damages to food companies and the associated industry, in addition, some fraud incidents have resulted in serious public health risks such as allergies and poisoning6,7. The reported food fraud scandals not only caused significant financial losses to the food industry and brought about food safety or public risk events but also reduced consumers’ confidence in brands.

The spice industry is one of the top three industries prone to food fraud8. Although only consumed in small quantities, spices play a significant role in the food industry as it is an important ingredient in a huge variety of foods and beverages. Its unique position in the food industry, complex supply chain and high price by weight make spice highly vulnerable to food fraud9. In addition, the time it takes from harvest to the consumption of spice can be years; further decreasing the transparency of the spice supply chain10. Nowadays, more research is being conducted on food fraud issues in the spice industry, especially on developing analytical techniques for spice authentication11. Nevertheless, limited research has focused on summarizing the fraud issues of a specific spice, as well as the intricacies of spice supply chain networks and the fraud risk factors hidden therein. In addition, low-priced and high trade volume spices receive limited attention compared with expensive spices such as saffron and vanilla. In 2018, a review by Galvin-King et al.12 gave a general insight into the spice supply chain and looked at the type and effect of fraud in spices and herbs. This review created a need for further research on the topic; especially focused on specific spices.

From a global perspective, the EU is one of the largest consumption areas of spice13. Nearly 95% of the EU's imports of spices come from developing countries, while China is the EU's largest spice trading partner that mainly supplies ginger and capsicums14. Among all spices circulated worldwide, ginger is a representative of the low-priced and high trade volume spice products because of its mass trade volume and wide application in foods. Ginger is one of the most common spices used for flavouring dishes in China, and it is also one of the most important spices exported to the European market because of the huge import volumes14,15. In 2018, the import volume of ginger (in all forms) was 127,259 tonnes, ranking first in the import of spices and herbs from developing countries, moreover, China accounted for almost 45% of ginger supplies from developing countries to the EU16.

However, even though ginger, especially ground ginger, has been labelled at high risk of food fraud according to the Food Fraud Risk Information17, fraud issues in ginger products have not been investigated and summarized. The overall situation regarding ginger fraud remains unclear. Moreover, the current understanding of the ginger supply chain from China to the EU is still the general impression of the traditional system of the spice supply chain18. The hidden issues in the opaque ginger supply chain limit the ability of stakeholders to guarantee the authenticity of this important spice. Therefore, it is necessary to provide a general summary of food fraud issues in ginger products and to map, deconstruct and analyse the supply chain based on the current information. This paper aims to summarize the open access data in the food fraud databases and the literature about ginger fraud, comprehend the structure of the China-EU ginger supply chain to identify the most vulnerable nodes and propose potential technical solutions that can be used to mitigate ginger fraud. This review can be used as an example for the spice industry as a solution to the fraud issue in many other low-price high trade volume spices.

An investigation of food fraud databases, a semi-structured literature search, online interviews with key stakeholders and a food fraud vulnerability assessment was performed to identify ginger products with fraud concerns, explore associated fraud issues, and map the ginger supply chain between China and the EU.

The databases, as described in Supplementary Table 1 related to food and food fraud cases were investigated to summarize the information about ginger and ginger fraud issues. The specific keyword, "ginger", was used to search for information related to ginger and ginger fraud to ensure all types of ginger products were included while searching. The information generated from the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) and Tridge were about the latest price, production, export and import volume of ginger in China and the EU. The Food and Feed Safety Alerts Portal (RASFF Portal), Food Fraud Risk Information, Decernis Food Fraud Database, Food Adulteration Incidents Registry, Recalls, Market Withdrawals, and Safety Alerts and Medical Information System (MEDISYS) were screened for ginger fraud issues covering all fraud types and all publication years. A total of 32 cases of ginger fraud were found in the food fraud databases and summarized by product types, databases, fraud types and detailed issues.

For the semi-structured literature search, Web of Science, Scopus, and Google Scholar were used as databases to source relevant articles written in the English language, covering all publication years up to 2021. During the process, specific keywords, and the combination of these keywords with Boolean operators were included. For the search strategy to obtain information related to ginger supply chains, the following search string was used within all fields of the databases: "spice" OR "ginger" AND "supply chain" OR "supply chain network" AND "map" OR "diagram" OR "model". For the search strategy of fraud issues related to ginger, the following search string was used within all fields of the databases: "ginger" AND "fraud" OR "adulteration" OR "unapproved processing" OR "undeclared processing" OR "mislabelling" OR "misrepresentation".

The above-mentioned keywords of ginger fraud were selected from the "CWA 17369: Authentic and fraud in the feed and food chain – Concepts, terms and definitions" standard published by the European Committee for Standardization and the detailed definition of the keywords are as fellow: adulteration is the intentional addition of inferior materials in foods, even non-food adulterants, to increase profit margins; misrepresentation/mislabelling refer to when the label is not in accordance by the actual food product characteristics; unapproved/undeclared processing is intentionally improving perceived quality or covering the deficiencies of food products19,20. During the search processing, the inclusion and exclusion criteria (Table 1) were used to determine if the articles were pertaining to the primary research aims. Governmental websites were also used to search for ginger supply chain and ginger fraud issues using the above-mentioned keywords. A total of 13 relevant articles including five government papers were found and formed the basis of the ginger supply chains data. The references of 13 relevant articles can be found in Supplementary Table 2. A total of 31 relevant articles related to ginger fraud that fit the inclusion and exclusion criteria were found and summarized.

Online interviews with stakeholders were conducted to validate the accuracy of the information obtained from the literature and the food fraud databases. In addition, the information acquired during the interviews were used as supplementary information for the results generated from the investigation of food fraud databases and semi-structured literature search. This step aims to eliminate the potential cognition gaps between the real industry, researchers (literature) and organizations/authorities (food fraud databases). A total of five stakeholders (i.e., three processors, one exporter and one trader) from three actor groups in the ginger supply chain were requested to participate in a 30-min online interview. All interviewees’ positions were quality assurance managers, two from China and three from the EU. The interviews were conducted online in English and Chinese, depending on the nationality of the interviewees, in three steps. First, the aim and major content of the interview were explained. Second, the interviewees were requested to introduce themselves and basic information about their companies. Third, the interviewees were requested to answer questions about their ginger products, supply chains and potential fraud risk factors. The full interview questions that were used in step three are shown in Supplementary Table 3. The interviewees and their affiliated companies were treated anonymously, while all original materials used in the interview process were treated confidentially and would not be published in any form. The interviews served as validation and supplementation. Therefore, the collected information is presented as a complement along with inferences drawn from the food fraud databases and the literature as a whole.

After mapping the ginger supply chain based on the information obtained from semi-structured literature search and online interview with supply chain stakeholders, the food fraud vulnerability of the supply chain was assessed to gain a better understanding of the supply chain from a fraudulent perspective. The food fraud vulnerability of the ginger supply chain from China to the EU was determined by using the free online food fraud vulnerability assessment tool, developed by the non-profit SSAFE organization in partnership with Wageningen University, VU University Amsterdam1. This is a science-based food fraud vulnerability self-assessment questionnaire consisting of 50 questions to evaluate the three key elements of food fraud vulnerability: Opportunities, Motivations and Control measures. Each question has three optional answers describing low, medium, and high vulnerability situations of the associated indicator. For the indicators from Opportunities and Motivations, answers with scores 1, 2 and 3 reflected a low, medium, and high vulnerability level, respectively. For the indicators from Control measures, the answers with the scores 1, 2 and 3 reflected a high, medium, and low vulnerability, respectively. The questions used in this study were pre-selected and slightly modified based on the available information acquired from food fraud databases, semi-structured literature search and online interview with stakeholders before being further used. The results were determined by the highest frequency of perceived vulnerability for all stages/indicators/elements. The frequency was determined by the following Eq. (1):

Where Fi is the frequency of score i (i = 1, 2, 3), Xij is the number of observations which get the score i in the j stages/indicators/elements, Yj is the total number of the observation in the j stages/indicators/elements.

Ginger (Zingiber officinale) is one of the most commonly used spices21. Because of its unique flavour and potential health benefits to the human body and brain, ginger is widely used as a spice and traditional medicine22. The unique flavour of ginger makes it suitable to be used for various food products such as vegetables, confectionery, soft and alcoholic beverages, pickles, and biscuits. Ginger can be used in numerous forms, such as fresh, dried, grounded, pickled, preserved, and crystallized. The harvest time of ginger rhizomes depends on their intended use. For fresh, preserved, or pickled ginger, young and immature ginger is primarily used as it is juicy, with a mild taste and has a thin skin23. The content of fibre and volatile organic compounds of ginger continues to increase with age24. Therefore, for dried ginger, it is best to use mature rhizomes, which have a sufficient aroma, flavour and pungency25. In addition, the ideal type of ginger for cooking is ginger harvested eight to nine months after planting because the content of volatile organic compounds and pungent compounds reach a maximum of about nine months after planting26. In this section, the ginger products with food fraud concerns were summarized from the literature and food fraud databases and classified according to the degree of processing (Table 2).

The search results from the food fraud databases in Table 3 indicate that the amount of information in the different databases was uneven. Food fraud issues in ginger products could only be found in three of five databases: 20 reports in the RASFF portal, two reports in Food Fraud Risk Information and 10 reports in the Decernis Food Fraud Database. Almost all information in the databases was related to adulteration and unapproved processing or undeclared processing, except one entry about the misrepresentation of geographical origin listed in the Food Fraud Risk Information and two cases about the misrepresentation of production system claims in the Decernis Food Fraud Database. In addition, processed ginger products, such as pickled ginger, preserved ginger, and sliced ginger, were the most common products recorded in the food fraud databases. In the RASFF portal, the type of ginger products, their adulterants and notifying countries were described. The information from the Decernis Food Fraud Database is more specific where the reason for adulteration, date, location, and reference can be found. Although ginger has been labelled at high risk of food fraud in the Food Fraud Risk Information, there is only a statement and no detailed information and case studies mentioned to substantiate the risk assignment.

The search results from the Web of Science, Scopus and Google Scholar (as shown in Table 4) indicates that most of the literature mentioned ginger adulteration, while some articles also gave examples of adulterants27,28,29, however, only a few articles directly focussed on the description or the detection of ginger fraud and the type of ginger products was also not described in detail in the articles30,31. In most cases, ginger adulteration is only used as an example in other food fraud studies12,27. In addition, misrepresentation/mislabelling of ginger and unapproved/undeclared processing of ginger were less common in the literature, only three out of 31 studies indicated these fraud issues31,32,33.

The search results of the databases and the literature led to the same conclusions, adulteration, misrepresentation/mislabelling and unapproved/undeclared processing appeared in two information sources. Yet the details of information related to the adulteration of ginger products were quite different as can be seen in Table 5. Adulteration of ginger products is the most crucial problem in the ginger industry which has been mentioned 50 out of 65 times in all results. In the food fraud databases, incidences of adulteration were reported as the addition of unapproved food additives (undeclared sweetener and undeclared preservative) to improve the flavour and shelf life of processed ginger34. However, in the literature results, the adulteration of ginger was related to the addition of other powdered materials to increase the bulk weight of ground ginger35. The search results from food fraud databases and literature showed that the unapproved processing of ginger involved the use of sulphur smoke and the addition of colorants which were mentioned nine out of 65 times in all results. For both sources, misrepresentation/mislabelling of ginger included fraudulent geographical origin and production system claims (only mentioned five out of 65 times in all results). According to the answers from the interviewees, it is the industry's consensus that ground ginger is more vulnerable to food fraud, especially by adulteration with foreign material. This is consistent with the findings from the literature search results.

The results of the food fraud databases showed that food fraud in ginger, a low-priced and high-trade volume spice product, is not only an example in the literature but a real-world issue. The discrepancy between the search results of the food fraud database and the literature may be either because there is less adulterated ground ginger in the actual market compared with fine processed ginger, or the limited technology available together with no/restricted market monitoring means that the adulteration of ground ginger remains hidden. These two possible reasons may have contributed to the limited reports of adulterated ground ginger in the food fraud databases, in contrast to the high proportion (but undetailed information) of adulterated ground ginger in all literature.

The complexity and transparency of a supply chain or indeed a network is an important characteristic that helps to determine where fraud risks exist. Therefore, it is pivotal to map and deconstruct the Chinese and the EU ginger market and to identify critical nodes along the chain.

The information about the ginger markets in China and the EU was obtained from the Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) as well as Tridge. The basic scheme of the ginger supply network from China to the EU was generated from 13 articles including five government reports (Supplementary Table 1) related to ginger or spice supply chains. The information acquired from interviews, including the role of the companies, their upper and lower actor groups, their knowledge of the ginger supply network and fraud issues, was used to validate the information obtained from the 13 articles and the supply chain actor groups. The actor groups in the supply chain were connected according to the flow of products from one actor group to the next. In addition, the supply chain was divided into different stages to reduce the complexity of the whole network based on the classification method of the "Guidance on authenticity of herbs and apices industry best practice on assessing and protecting culinary fries herbs and spices" released by British Retail Consortium, Food and Drink Federation and Seasoning and Spice Association36. The associated fraud issues at each stage of the supply chain were also identified based on this Guidance.

The demand for ginger is growing annually and is expected to increase in the coming years16. In 2019, exported ginger (uncrushed or unground) amounted to US$ 849.5 million, and the total export of crushed or ground ginger was US$ 81.5 million16. Based on the export value, the top five exporting countries of ginger are China, the Netherlands, Thailand, Peru, and India. China is the main producing and exporting country of ginger and has more than a 50% share of the global export market. China's ginger exports in 2019 amounted to US$ 508.3 million, with an export volume of 490,500 tones37. Moreover, almost 80% of all suppliers from developing countries to the EU are Chinese suppliers. Among all ginger products exported from China, almost 90% are in uncrushed/unground (whole) forms, while only 10% are crushed or ground products16. Ginger production in China has been mechanized, which makes it more competitive than any suppliers. Some provinces in China, such as Shandong, Hebei, Liaoning and Fujian, are known as the main origins of ginger16.

In 2018, the import value of ginger worldwide amounted to US$ 826.4 million, with an import volume of 645,700 tonnes37. For the EU, most of the ginger is imported from other countries, especially developing countries. In 2018, more than 70% of imported ginger in the EU came from developing countries16. The Netherlands is the largest importer and marketer of ginger in the EU, where the import volume of ginger has grown significantly16. Germany is the second largest importer of ginger in the EU, with an import volume of 22,600 tonnes in 2018. Nearly 90% of Germany's ginger product imports come from developing countries38. Italy, Spain and France are medium-sized importers of ginger in the EU and their main supplier is China16.

The ginger supply network between China and the EU follows a traditional system. The key actor groups in the ginger supply network are presented in Fig. 1. They are farmers, collectors, processors, agents, exporters, wholesalers, retailers, food manufacturers, food service operators, business-to-business (B-to-B) companies, seasoning companies, packaging companies and consumers. From farmers in China to the final consumers in the EU, the ginger supply network can be divided into nine stages according to the classification method of the Guidance on Authenticity of Herbs and Spices36. The nine stages are primary production, local collection, local processing, local market, local consumer, international trade, EU processing, EU market and EU consumer. The structure and the food fraud vulnerability of the supply chain were analysed by the stages to gain a better understanding of the supply chain from a fraudulent perspective.

Note. Each solid small rectangle represents an actor group, each dotted big rectangle represents a stage (from Stage I to Stage IX), and the arrow direction represents the flow of products from one actor group to the next.

A modification of the SSAFE FFVA tool was applied to assess the fraud vulnerability of each stage and the whole chain with indicators from the tool. The tool was developed as a self-assessment tool for food business operators. However, in the current study the tool was modified to allow a ‘bird's eye view’ evaluation, i.e. as a third-party tool instead of a tool for a food business operator. The modification of the tool was based on the acquired information from the literature, the databases, and the interviews with stakeholders. The available information from the previous sections includes specific products, detailed fraud issues, potential adulterants, available techniques, the number of historical cases, etc. Therefore, only indicators related to the above-mentioned information were used in this study. Some food fraud factor/indicators of the SSAFE self-assessment FFVA tool focus on the company-specific food business environment. However, these factor/indicators cannot be used at the aggregated level for the ‘bird's eye’ approach and were omitted in the current study. These inapplicable factor/indicators are listed in Supplementary Table 6. It is important to note that the indicators from the Control measures were all excluded from the assessment as the indicators belonged to the list of inapplicable indicators. The applicable fraud factor/indicators were related to potential threats, represented by food fraud factor/indicators in the Opportunities and Motivations key element groups; therefore, the fraud vulnerability of the ginger supply chain was discussed from two perspectives, opportunities related vulnerability and motivations related vulnerability. The applicable fraud factor/indicators were further divided into the factor/indicators for each stage and the factor/indicators for the whole chain based on the targeting objects of the fraud factor/indicator questions (Table 6 and Table 7). The factor/indicators applied to each stage all belonged to the key element Opportunities including technical opportunities and opportunities in time and space. Whereas the factor/indicators applied to the whole supply chain were from the key elements Opportunities and Motivations. The consequence of the selected ‘bird's eye approach’ is that the level of vulnerability is determined by the threats in the chain only. In practice these can be mitigated, at least to some extent, by appropriate control measures but this will depend on priorities and capabilities of individual food business operators.

The assessment of the opportunities-related vulnerability of the chain was conducted by accessing the opportunities-related vulnerability of each stage using stage-targeted fraud factor/indicators (Table 6) and combined with the whole chain targeted factor/indicators (Table 7) to have the overall opportunities-related vulnerability of the whole chain. The assessment of motivations-related vulnerability of the chain was conducted using the fraud factor/indicators in Table 7. The opportunities and motivations related vulnerability of the nine stages and the whole chain are described below.

The primary production stage of the food supply chain includes agricultural activities, aquaculture and other similar processes related to raw food materials39. Regarding the ginger supply chain, activities in this stage related to the harvest, handling, and storage of fresh ginger before it moves to either processing or distribution. At this stage, farmers may use acid wash ginger or use sulphur smoke ginger (unapproved/undeclared processing) to improve the appearance of the ginger, as reported on social media40,41. Such fraudulent activities do not require advanced technology, methods and/or facilities suggesting the factor/indicator ‘Availability of technology and knowledge to commit food fraud on final products’ is high vulnerability (Table 6 - Question 1 - Answer option 3 - score 3). Unapproved/undeclared processing of ginger is easily identified by the abnormal odour and colour of ginger, therefore, the fraud factor/indicator ‘Detectability of food fraud in final products’ is low vulnerability (Table 6 - Question 2 - Answer option 1 - score 1)42. This fraudulent behaviour was reported by the media, but it is less common in China recently, hence the ‘Historical evidence of fraud in final products’ is assigned a medium vulnerability level (Table 6 - Question 3 - Answer option 2 – score 2). Altogether, the frequency of all three factor/indicators is equal, no highest frequency and corresponding vulnerability can be determined at this stage.

For the local collection stage (Stage II) of the supply network, the collectors purchase ginger from farmers and rarely process the ginger. At this stage, collectors do not process ginger, the factor/indicator ‘Availability of technology and knowledge to commit food fraud on final products’ is not applicable at this stage. However, unapproved/undeclared processing of ginger may already happen at the primary production stage (Stage I), and it is still easy to be noticed. Therefore, the factor/indicator ‘Detectability of food fraud in final products’ is low vulnerability (Table 6 – Question 2 – Answer option 1 – score 1). In addition, there is no information about the ‘Historical evidence’ at this stage. However, one common issue at this stage is the loss of traceability43. The main reason for this loss at the local collection stage might be due to the lack of traceability standards between farmers and collectors44. Paper-based systems are widely implemented for food traceability across the whole food industry45. While such systems are cheap they can lack accuracy in the recording and storage of data44. Robust digital systems for traceability are more expensive to implement, operate and maintain46. For smallholder ginger farmers who live in remote districts, it is difficult and costly to implement and apply such advanced systems for traceability. Based on the available information, the opportunities related vulnerability at this stage cannot be determined.

Local processors obtain fresh ginger from local collectors on a regional basis. At Stage III, local processors may perform some basic processing, such as cleaning, sterilization packing and grinding or fine process into other form47. Adulteration may occur at this stage when ginger is ground into powder or processed into other forms43. Fraudsters may add inferior material to ground ginger to increase its weight or they may add unauthorized ingredients to enhance certain qualities of ginger for profit29. For instance, adding powdered beans to ground ginger to increase weight and adding Sudan dyes for a more vibrant colour48,49. Because simple/basic technologies and methods are available, and no specialist facilities are required, to adulterate the materials/products, the ‘Availability of technology and knowledge to commit food fraud on final products’ is high (Table 6 – Question 1 – Answer option 3 – score 3). In addition, from the previous investigation of the literature and food fraud databases, even though the fraud issues in ginger are not as common as in expensive spices, adulteration is the main issue that usually happened during ginger processing and there is a lack of robust techniques for detecting ginger adulteration. Hence, the factor/indicator ‘Detectability of food fraud in final products’ is high vulnerability and the factor/indicator ‘Historical evidence of fraud in final products’ is medium (Table 6 – Question 2 – Answer option 3 - score 3, Table 6 – Question 3 – Answer option 2 - score 2). To sum up, the opportunities related vulnerability at the local processing stage is high because the high vulnerability has the highest frequency.

There are four actor groups within the local market stage (Stage IV); the wholesaler, retailer, food manufacturer and food service operators. The common fraud issue at this stage is deliberate misrepresentation/mislabelling36. For ginger products, deliberate misrepresentation can be around the geographical origin or production system claims50,51. This fraudulent issue does not require advanced technologies, methods, facilities and/or knowledge because no additional processing is needed on ginger. Therefore, the factor/indicator ‘Availability of technology and knowledge to commit food fraud on final products’ is high vulnerability (Table 6 – Question 1 – Answer option 3 - score 3). Although some studies has been conducted to identify the misrepresentation/mislabelling issues in ginger products, those methods usually need advanced equipment and trained analysts are needed for its detection52. Moreover, such laboratory tests are usually expensive and time-consuming. Based on the description of ‘Detectability of food fraud in final products’, the vulnerability related to this factor/indicator is medium (Table 6 – Question 2 – Answer option 2 – score 2). According to the results of the literature and food fraud databases, there are limited cases/documentations (five statements), hence, the fraud factor/indicator ‘Historical evidence of fraud in final products’ is medium vulnerability (Table 6 – Question 3 – Answer option 2 - score 2). To that end, the opportunities relate vulnerability at this stage is medium because the medium vulnerability has the highest frequency.

At Stage VI, the ginger products from China are transported to the EU. Exporters and agents are working as an intermediary between the Chinese market and the EU market. According to the Guidance on Authenticity of Herbs and Spices36, the purchase of low-grade materials and the occurrence of mislabelling often happen at this stage in the herb and spice industry supply chain. The main fraud issue at this stage is the same as that at the local market stage. Consequently, the factor/indicators for this stage, including ‘Availability of technology and knowledge to commit food fraud on final products’, ‘Detectability of food fraud in final products’ and ‘Historical evidence of fraud in final products’ have the same vulnerability as the local market stage which were high, medium, and medium vulnerability, respectively. According to an interview with EU processors, to prevent food fraud, they only trade with exporters and agents who are trustworthy and have long-term partnerships. However, this cooperation model may lead to the EU processors being over-dependent on their exporters and agents. One of the interviewees from an EU spice company stated that all information about their purchase of ginger products came from their Chinese agents. Therefore, excessive reliance on agents or exporters creates fraud vulnerability at the international trade stage. To sum up, the opportunities related vulnerability at this stage is medium since the medium vulnerability has the highest frequency.

The EU processors group of Stage VII is one of the most significant actor groups within the ginger supply chain network. Most of the ginger products in the EU market come from the EU processors. In addition to the basic processing such as cleaning, sterilization and grinding, the EU processors may further process ginger into other ginger products, for instance, pickled ginger, preserved ginger, and crystalized ginger depending on the companies. Like local processors in China, adulteration of ground ginger is still the main fraud issue at this stage, such as adding spent ginger to ground ginger53. Therefore, the EU processing stage has the same opportunities related vulnerability as the Local processing stage, which is high vulnerability. In addition, all interviewees at this stage claimed that they had confirmed the authenticity of their products and believed that the fraud issues they knew always came from other actor groups in the ginger supply chain. However, the questions related to food fraud may touch on the sensitivities of potential offenders, therefore, we presumed the interviewees might answer the questions in a more reserved or socially acceptable way. This behaviour is consistent with the ‘alien conspiracy theory’, which describes that crime as a problem from outside parties, rather than a part of the own direct environment/society54.

Stage VIII consists of six actor groups that directly sell ginger products to EU consumers. At this stage, the fraud vulnerability would be knowingly placing mislabelled products on the market43. Therefore, the same in the local market, the opportunities related vulnerability at this stage is medium.

At Stage V and Stage IX of the spice supply chain, local (Chinese) and EU consumers receive the final products circulating within the entire supply chain network. At these stages, it is likely that the products may already be tampered with if it has been vulnerable to food fraud at earlier stages of the network55.

The nine stages of the ginger supply chain from China to the EU and corresponding opportunities and motivations related vulnerability have been compiled in Fig. 2. The low, medium, and high vulnerability respectively corresponded to green, orange, and red colours for better visualization. The overall opportunities related vulnerability of the chain based on the results of nine stages is medium to high vulnerability because medium and high vulnerability have the same frequency. The local processing and EU processing have high opportunities related vulnerability compared with other stages. According to the theoretical framework of the FFVA tool, more robust internal hard controls should be applied at these two stages to counterweigh the high vulnerability in opportunities1.

Note: Number 1, 2 and 3 reflected a low, medium, and high vulnerability level.

In addition to the indicators targeting each stage, five additional Opportunities related indicators for the whole were also considered. The raw material (raw ginger) of the whole supply chain is consistent, therefore the factor/indicators related to raw material were considered based on the whole supply chain. For the factor/indicator ‘The complexity of committing food fraud on raw materials’, the physical status of raw ginger is in line with the description of Table 7 – Question 1 - Answer option 1 – score 1, which is low vulnerability. As discussed in the primary stage, the unapproved/undeclared processing of raw ginger does not require advanced technology/knowledge and can be easily noticed by odour and colour, therefore, the factor/indicator ‘Availability of technology and knowledge to commit food fraud raw materials’ is high vulnerability (Table 7 – Question 2 – Answer option 3 - score 3) and the factor/indicator ‘Detectability of food fraud in raw materials’ is low vulnerability (Table 7 – Question 3 – Answer option 1 - score 1). The factor/indicator ‘Historical evidence’ for the raw ginger is less common, consequently, this factor/indicator is medium vulnerability (Table 7 – Question 5 – Answer option 2 - score 2). For the factor/indicator ‘Transparency of the supply chain network’, the information from 13 relevant articles used to map the ginger supply chain indicated that the ginger supply chain is not fully transparent, there is a lack of research on the structure of the chain. Accordingly, the ‘Transparency of the supply chain network’ is medium vulnerability (Table 7 – Question 4 – Answer option 2 – score 2). To bring the factor/indicators targeting each stage and the indicator targeting the whole chain together, the overall opportunities related vulnerability of the whole ginger supply chain from China to the EU is medium since the medium vulnerability has the highest frequency.

For the motivations-related vulnerability, all six motivations-related indicators are targeting the whole supply chain. Regarding the factor/indicator ‘Economic situation of the raw materials’, the ginger products fit the description of medium vulnerability (Table 7 – Question 6 – Answer option 2 – score 2) i.e., stable prices but the supply of raw materials are not readily available and export bans on raw materials exist in a few countries. The price of ginger is stable compared with expensive spices which have big price fluctuations, such as black pepper56. However, the export ban existing in a few countries makes ginger is not readily available all the time57. For the factor/indicator ‘Valuable components or attributes of products’, the ginger products fit the description of high vulnerability (Table 7 – Question 7 – Answer option 3 – score 3), i.e., the value of materials/products is greatly determined by its composition, way of production and/or origin. The factor/indicator ‘Corruption level in the country’ is low to medium vulnerability, since the corruption index is medium (66) for China and low for top import countries (Netherlands 8, Germany 10). The vulnerability of the factor/indicator ‘Economic conditions branch of the industry’ is low because the ginger industry is operating in a growing market according to Tridge (Table 7 – Question 9 – Answer option 1 – score 1). The information from Tridge also indicated that the factor/indicator ‘Price asymmetries’ is medium vulnerability since the price of ginger is different in some regions and countries (Table 7 – Question 10 – Answer option 2 – score 2). The last factor/indicator ‘Historical evidence branch of the industry’ was determined by fraud prevalence in ginger in previous section, there is well-known and documented evidence of fraudulent activity across the ginger supply chain. Therefore, the ‘Historical evidence branch of the industry’ is high vulnerability. In conclusion, the motivations related vulnerability of the ginger supply chain is medium vulnerability due to the high frequency of the medium vulnerability.

According to the Global Food Safety Initiative (GFSI) guidelines, two key elements are needed to mitigate the risk of food fraud, food fraud vulnerability assessment and control plan58. Until now there is no food fraud vulnerability assessment has been conducted on the ginger supply chain from China to the EU. In addition, based on the search results from the literature, as an key element of the control plan, laboratory-based detection techniques for ginger fraud issues are not well-developed. Limited research has been conducted on the detection of known adulterants in ginger products and the new emerging adulterants keep increasing the length of the adulterants list of ginger products. The development of robust detection techniques and the transfer from the laboratory to the real industry is still on the way. Therefore, the available food fraud vulnerability assessment tools and possible detection techniques will be discussed in this section.

In the previous section, a modified food fraud vulnerability assessment tool (i.e., SSAFE FFVA) was applied to have a general impression of the food fraud vulnerability in the ginger supply chain. However, it is necessary to apply the fraud vulnerability assessment tools in the spice companies to reveal the real situation of the supply chain. Besides the SSAFE FFVA tool59 used in this study, various other food fraud vulnerability assessment tools have been developed to determine fraud risks of companies within supply chains. Examples include the vulnerability assessment and critical control points (VACCP), food fraud mitigation guidance60, CARVER plus shock method61, NSF fraud protection model62 and the food fraud initial screening model (FFIS)63. In principle, the above-mentioned food fraud vulnerability assessment tools do not provide specific mitigation techniques for ginger fraud, as indeed is the case for most commodities and ingredients but they provide the possibility to find vulnerable points along with the ginger supply chain network. However bespoke risk assessment tools are required as has been shown in the case of beef fraud64.

In this study, the investigation in the literature indicated a lack of appropriate detection techniques for ginger fraud. The robust detection technique is one of the key elements in the control plan to mitigate food fraud. Therefore, in this section, ginger authentication in practice and potential detection techniques will be discussed to have a general impression on possible technical solution to ginger fraud.

According to interviews with stakeholders, to ensure the authentication and safety of their ginger products, some technical control measures have been taken on the raw material and the final products of ginger. For the raw material, undeclared bleaching and SO2 addition can be detected using wet chemistry. In terms of detecting the adulteration of ginger products, especially in the ground form, there are several problems with the current control measures. An interviewee stated that traditional wet chemistry is costly for companies and DNA profiling for spice adulteration does not work properly. The public databases for DNA analysis are not valid and lack verification. In addition, some processing of ginger may destroy DNA making profiling inaccurate. Therefore, more accurate, low-cost, and efficient techniques need to be developed to address the real-life fraud issues in ginger.

Although studies on ginger authentication are limited, many techniques have been applied for the characterization of ginger (Table 8). Techniques used for characterization can also be used for authentication, because of the ability to distinguish the differences between groups of samples. Most of the characterization of ginger is based on the main active constituents in ginger, including volatile organic compounds and non-volatile pungent compounds which attribute to the unique flavour of ginger products65,66,67.

Previous studies on ginger characterization provide the possibility to explore different analytical techniques to detect ginger fraud. In addition, the limitation of current methods for ginger authentication in practice creates a need to develop better techniques. According to a database of food ingredient fraud and economically motivated adulteration generated by Moore et al. (2012), chromatography, vibrational spectroscopy, mass spectrometry and DNA-based analyses were the most common approaches applied. These analytical tools can be further divided into confirmatory methods and screening techniques. The principle of confirmatory techniques for spice adulteration is mainly based on the identification of specific markers of the spice, such as adulterants and specific chemical constituents (Galvin-King et al., 2018). The application of screening techniques for spice adulteration are characterized as being rapid, low cost and non-destructive. Both confirmatory and screening techniques could be applied to detect adulteration in ginger products.

Based on the principle of confirmatory techniques, certain adulterants in ginger products and some characteristic compounds in ginger can be used as specific markers in detecting ginger fraud. For the adulteration of processed ginger products, illegal dyes, unauthorized preservatives, and undeclared sweeteners are the most used adulterants. Researchers have demonstrated that these adulterants can successfully be detected by some techniques, such as high-performance thin-layer chromatography-mass spectrometry and thin layer chromatography68,69. These confirmatory techniques are characterised as being more labour intensive, costly, and accurate as opposed to screening techniques.

Screening techniques can be powerful tools for non-targeted analysis to detect ginger adulteration. In practice, they are applied to flag suspect products which can then be further investigated with the more accurate confirmatory methods. For ground ginger, like many spices, the list of adulterants could be endless70. Some non-targeted screening methods are more suitable for rapid quality testing. For instance, near-infrared (NIR) spectroscopy has been used to distinguish pure black pepper powder from adulterated pepper samples mixed with black pepper husk, papaya seeds, pinheads and chili powder71. Although still in the early stages of development and practical application, the advantages of non-targeted screening techniques on food fraud will make them one of the most suitable tools in combating ginger fraud.

One of the main aims of this review was to summarize the open access data about ginger fraud from the food fraud databases and the published literature. A second aim was to map the structure of the ginger supply network from China to the EU to identify the most vulnerable nodes along the chain and to propose analytical approaches that can be taken to detect and help mitigate fraud. Figure 2 from the Section: The ginger supply chain network: from China to the EU indicated that the overall opportunities and motivations related vulnerability of the ginger supply chain from China to the EU is medium vulnerability. The figure also indicated a difference in the vulnerability at different stages. To prevent food fraud, technical control measures should be applied at different stages. The undeclared/unapproved processing issue at the primary production stage can be detected very easily by the observation of odors and colour and wet chemistry. For monitoring the local market, international trade and EU market stages, isotope ratio mass spectrometry and elemental analysis can be used as an effective authentication technique to detect misrepresentation/mislabeling of geographical origin/production system claims despite the high cost72,73. For the adulteration of ground ginger and processed ginger at local processing and EU processing stages, the various potential techniques mentioned in the section: Potential ginger authentication techniques can be the analytical solutions in the future. According to the statements of the stakeholders, the current analytical control measures do not meet their expectations (as described in the section: Ginger authentication in practice). Therefore, the development of more promising and less costly analytical techniques is needed.

As a typical low-priced and high trade volume spice product, this is the study to investigate the food fraud prevalence in ginger products from the perspective of the supply chain. However, certain limitations of this study should be considered. First, there were only five participants for the stakeholder interviews, limiting the information from stakeholders and representing their perspectives. Second, only English literature and food fraud databases were used in this study. This could cause the omission of the food fraud information reported in other languages. Third, only open access information in the food fraud databases was included in this study. Despite these limitations, the current results still provide a good understanding of food fraud in the supply chain of ginger products and provide possible analytical solutions for detecting food fraud in the ginger supply chain from China to the EU.

Food fraud is a constant threat to the spice industry. The results of the food fraud databases and the literature indicate that ginger fraud is a threat that has not been well investigated by researchers, especially the adulteration issues of ground ginger. Even though adulteration in ginger was widely reported in the literature, the available detection techniques, specifically focussed on ginger fraud, are limited. In addition, by mapping the ginger supply chain from a fraudulent perspective, the opportunities and motivation related vulnerability of the ginger supply chain was considered to be at a medium with the processing stages identified as the most vulnerable nodes along the chain. Confirmatory and screening techniques based on ginger characteristics analysis should be applied and developed in the future. In summary, attention should be given not only to extremely high valuable spice products, but also to spice products marketed at lower prices and sold in high trade volumes.

The authors declare that all data supporting the findings of this study are available within the article and its supplementary information files.

van Ruth, S. M., Huisman, W. & Luning, P. A. Food fraud vulnerability and its key factors. Trends Food Sci. Technol. 67, 70–75 (2017).

Article Google Scholar

Spink, J. & Moyer, D. C. Defining the public health threat of food fraud. J. Food Sci. 76, 157–163 (2011).

Article Google Scholar

Johnson, R. Food fraud and ‘economically motivated adulteration’ of food and food ingredients. in Congressional Research Report R 43358 (2014).

Madichie, N. O. The European ‘horsemeat scandal’: A welcome opportunity for the halal supply chain? J. Cust. Behav. 14, 63–82 (2015).

Article Google Scholar

Xiu, C. & Klein, K. K. Melamine in milk products in China: Examining the factors that led to deliberate use of the contaminant. Food Policy 35, 463–470 (2010).

Article Google Scholar

Charlebois, S., Juhasz, M., Foti, L. & Chamberlain, S. Food fraud and risk perception: Awareness in Canada and projected trust on risk-mitigating agents. J. Int. Food Agribus. Mark. 29, 1–18 (2017).

Article Google Scholar

Visciano, P. & Schirone, M. Food frauds: Global incidents and misleading situations. Trends Food Sci. Technol. 114, 424–442 (2021).

Article CAS Google Scholar

Bindt, V. Costs and benefits of the food fraud vulnerability assessment in the Dutch food supply chain. (Wageningen University, 2016).

Silvis, I. C. J., van Ruth, S. M., van der Fels-Klerx, H. J. & Luning, P. A. Assessment of food fraud vulnerability in the spices chain: An explorative study. Food Control 81, 80–87 (2017).

Article Google Scholar

Székács, A., Wilkinson, M. G., Mader, A. & Appel, B. Environmental and food safety of spices and herbs along global food chains. Food Control 83, 1–6 (2018).

Article Google Scholar

Haughey, S. A., Galvin-King, P., Ho, Y. C., Bell, S. E. J. & Elliott, C. T. The feasibility of using near infrared and Raman spectroscopic techniques to detect fraudulent adulteration of chili powders with Sudan dye. Food Control 48, 75–83 (2015).

Article CAS Google Scholar

Galvin-King, P., Haughey, S. A., Montgomery, H. & Elliott, C. T. The rapid detection of sage adulteration using Fourier transform infra-red (FTIR) spectroscopy and chemometrics. J. AOAC Int 102, 354–362 (2019).

Article CAS PubMed Google Scholar

Herms, S. Investment opportunities in the Ethiopian: Spices sub-sector. https://www.rvo.nl/ (2015).

Centre for the Promotion of Imports from developing countries. Which requirements should spices or herbs comply with to be allowed on the European market? https://www.cbi.eu/ (2018).

Hinsbergh, G. Van. The top 10 most common herbs and spices used to flavor Chinese food. China Highlights https://www.chinahighlights.com/travelguide/chinese-food/herbs-and-spices.htm (2020).

Centre for the Promotion of Imports from developing countries. The European market potential for dried ginger. https://www.cbi.eu/ (2019).

Authentic Food. Food fraud risk information. https://trello.com/b/aoFO1UEf/food-fraud-risk-information (2017).

Centre for the Promotion of Imports from developing countries. The spices and herbs market in the EU. http://www.greenfoodec.eu/documents/The_spices_and_herbs_market_in_the_EU.pdf (2009).

McGrath, T. F. et al. What are the scientific challenges in moving from targeted to non-targeted methods for food fraud testing and how can they be addressed? – Spectroscopy case study. Trends Food Sci. Technol. 76, 38–55 (2018).

Article CAS Google Scholar

European Committee for Standardization. CWA 17369: Authenticity and fraud in the feed and food chain - Concepts, terms, and definitions. https://www.cencenelec.eu/ (2019).

White, B. Ginger: An overview. American Family Physician https://www.aafp.org/afp/2007/0601/p1689.html#:~:text=Ginger (2007).

Ali, B. H., Blunden, G., Tanira, M. O. & Nemmar, A. Some phytochemical, pharmacological and toxicological properties of ginger (Zingiber officinale Roscoe): A review of recent research. Food Chem. Toxicol. 46, 409–420 (2008).

Article CAS PubMed Google Scholar

Shahrajabian, M. H., Sun, W. & Cheng, Q. Clinical aspects and health benefits of ginger (Zingiber officinale) in both traditional Chinese medicine and modern industry. Acta Agric. Scand. Sect. B Soil Plant Sci. 69, 546–556 (2019).

CAS Google Scholar

Shukurova, M. K., Asikin, Y., Chen, Y., Kusano, M. & Watanabe, K. N. Profiling of volatile organic compounds in wild indigenous medicinal ginger (Zingiber barbatum wall.) from Myanmar. Metabolites 10, 248 (2020).

Article CAS PubMed Central Google Scholar

Simonyan, K. J., Ehiem, J. C., Eke, A. B., Adama, J. C. & Okpara, D. A. Some physical properties of ginger varieties. J. Appl. Agric. Res. 5, 73–79 (2013).

Google Scholar

FAO. Ginger value chain study in Nueva Vizcaya, Philippines. (2019).

Parvathy, V. A. et al. DNA barcoding to detect chilli adulteration in traded black pepper powder. Food Biotechnol. 28, 25–40 (2014).

Article CAS Google Scholar

Zhu, H. & Zhao, M. Study on the microscopic identification of the adulterated plant origin powdered seasonings. Discourse J. Agric. Food Sci. 2, 264–269 (2014).

Google Scholar

Mohiuddin, A. K. Health hazards with adulterated spices: Save the "onion tears". J. Soc. Serv. Welf. 1, 11–16 (2019).

Google Scholar

Salmon, C. N. A. et al. Characterisation of cultivars of Jamaican ginger (Zingiber officinale Roscoe) by HPTLC and HPLC. Food Chem. 131, 1517–1522 (2012).

Article CAS Google Scholar

Wu, C. Y. et al. Impact of sulphur fumigation on the chemistry of ginger. Food Chem. 239, 953–963 (2018).

Article CAS PubMed Google Scholar

Rafi, M., Lim, L. W., Takeuchi, T. & Darusman, L. K. Simultaneous determination of gingerols and shogaol using capillary liquid chromatography and its application in discrimination of three ginger varieties from Indonesia. Talanta 103, 28–32 (2013).

Article CAS PubMed Google Scholar

Nair, K. P. P. The biotechnology of ginger. in The Agronomy and Economy of Turmeric and Ginger 375–400 (2013).

European Commission. RASFF portal. https://webgate.ec.europa.eu/rasff-window/portal/?event=SearchForm&cleanSearch=1 (2020).

Rathmell, C. Adulteration of spices. Spectroscopol https://www.spectropol.pl/images/APP/App-Note-Adulteration-of-Spices.pdf (2016).

BRC-FDF-SSA. Guidance on authenticity of herbs and spices. Food and Drink Federation 1–19 http://www.brc.org.uk/downloads/Guidance_on_Authenticity_of_Herbs_and_Spices_June_2016.pdf (2016).

Tridge. Spices; ginger. Tridge https://www.tridge.com/ (2020).

CBI Ministry of Foreign Affairs. CBI Product Factsheet: Dried ginger in Europe. https://www.cbi.eu/ (2015).

Commission for Environmental Cooperation. Specific guidance for different sectors of the food supply chain on how to measure food loss and waste. http://www.cec.org/flwm/sector/primary-production/ (2021).

Bhattacharya, A. B. Beware of adulteration: Ginger being washed by acid to make it shiny, 6 godowns raided in Delhi. The logical India https://thelogicalindian.com/news/ginger-adulteration-delhi/ (2017).

Yi, Z. 60% of ginger in Xi’an treated with sulfur. Global Times https://www.globaltimes.cn/content/578611.shtml (2019).

Lou, T. et al. Monitoring, exposure and risk assessment of sulfur dioxide residues in fresh or dried fruits and vegetables in China. Food Addit. Contam. - Part A Chem. Anal. Control. Expo. Risk Assess. 34, 918–927 (2017).

Article CAS PubMed Google Scholar

Galvin-King, P., Haughey, S. A. & Elliott, C. T. Herb and spice fraud; the drivers, challenges and detection. Food Control 88, 85–97 (2018).

Article CAS Google Scholar

Aung, M. M. & Chang, Y. S. Traceability in a food supply chain: Safety and quality perspectives. Food Control 39, 172–184 (2014).

Article Google Scholar

Folinas, D., Manikas, I. & Manos, B. Traceability data management for food chains. Br. Food J. 108, 622–633 (2006).

Article Google Scholar

Karippacheril, T. G., Rios, L. D. & Srivastava, L. Global markets, global challenges: Improving food safety and traceability while empowering smallholders through ICT. in ICT in Agriculture (Updated Edition): Connecting Smallholders to Knowledge, Networks, and Institutions (2017).

Centre for the Promotion of Imports from developing countries. Exporting value-added spices and herbs. https://www.cbi.eu/ (2018).

Terouzi, W. & Oussama, A. Evaluation of Ginger adulteration with beans using Attenuated Total Reflectance Fourier Transform Infrared spectroscopy and multivariate analysis. Int. J. Eng. Appl. Sci. 3, 257627 (2016).

Google Scholar

Ma, M., Luo, X., Chen, B., Su, S. & Yao, S. Simultaneous determination of water-soluble and fat-soluble synthetic colorants in foodstuff by high-performance liquid chromatography-diode array detection-electrospray mass spectrometry. J. Chromatogr. A 1103, 170–176 (2006).

Article CAS PubMed Google Scholar

Hemmes, M. Brazil and Peru compete with China on ginger quality, not on price. Fresh Plaza https://www.freshplaza.com/article/2008911/brazil-and-peru-compete-with-china-on-ginger-quality-not-on-price/ (2017).

Shafie, F. A. & Rennie, D. Consumer perceptions towards organic food. Procedia - Soc. Behav. Sci. 49, 360–367 (2012).

Article Google Scholar

Šelih, V. S., Šala, M. & Drgan, V. Multi-element analysis of wines by ICP-MS and ICP-OES and their classification according to geographical origin in Slovenia. Food Chem. 153, 414–423 (2014).

Article PubMed Google Scholar

Abdo, M. T., El-Ahmady, S. H. & Gad, H. A. Quality control and long-term stability study of ginger from different geographical origins using chemometrics. J. Sci. Food Agric. 101, 3429–3438 (2021).

Article CAS PubMed Google Scholar

Kleemans, E. Theoretical perspectives on organized crime. (2014).

Soon, J. M. & Liu, X. Chinese consumers’ risk mitigating strategies against food fraud. Food Control 115, 107298 (2020).

Article Google Scholar

Sabu, S. S. & Kuruvila, A. Price instability in black pepper: A comparative analysis of preliberalisation and post-liberalisation periods. J. Trop. Agric. 54, 41–49 (2016).

Google Scholar

Raj Dahal, B. & Rijal, S. Ginger value chain analysis: A case of smallholder ginger production and marketing in hills of central Nepal. Agric. Sci. Technol. 12, 31–36 (2020).

Google Scholar

GFSI. Tackling Food Fraud through Food Safety Management Systems. Global Food Safety Initiative 1–10 https://mygfsi.com/wp-content/uploads/2019/09/Food-Fraud-GFSI-Technical-Document.pdf (2018).

SSAFE. Food fraud vulnerability assessment tool. https://www.ssafe-food.org/our-projects/ (2020).

USP. Food fraud mitigation guidance. (2016).

FDA. CARVER plus Shock method. https://www.fda.gov/food/food-defense-programs/carver-shock-primer (2009).

NSF. NSF fraud protection model. https://www.nsf.org/consulting/food/food-fraud (2020).

Spink, J., Moyer, D. C. & Speier-Pero, C. Introducing the Food Fraud Initial Screening model (FFIS). Food Control 69, 306–314 (2016).

Article Google Scholar

Robson, K., Dean, M., Haughey, S. A. & Elliott, C. T. The identification of beef crimes and the creation of a bespoke beef crimes risk assessment tool. Food Control 126, 107980 (2021).

Article Google Scholar

Li, X. et al. Analysis of the volatile compounds associated with pickling of ginger using headspace gas chromatography - ion mobility spectrometry. Flavour Fragr. J. 34, 485–492 (2019).

Article CAS Google Scholar

Yudthavorasit, S., Wongravee, K. & Leepipatpiboon, N. Characteristic fingerprint based on gingerol derivative analysis for discrimination of ginger (Zingiber officinale) according to geographical origin using HPLC-DAD combined with chemometrics. Food Chem. 158, 101–111 (2014).

Article CAS PubMed Google Scholar

Yan, H. et al. Rapid and practical qualitative and quantitative evaluation of non-fumigated ginger and sulfur-fumigated ginger via Fourier-transform infrared spectroscopy and chemometric methods. Food Chem. 341, Part 1 (2021).

Article Google Scholar

Mishra, M. K. Detection of adulterants in spices through chemical method and thin layer chromatograpghy for forensic consideration. 6, 8824–8827 (2016).

Rani, R., Medhe, S. & Srivastava, M. M. HPTLC–MS based method development and validation for the detection of adulterants in spices. J. Food Meas. Charact. 9, 186–194 (2015).

Article Google Scholar

Dhanya, K. & Sasikumar, B. Molecular maker based adulteration detection in traded food and agricultural commodities of plant origin with special reference to spices. Curr. Trends Biotechnol. Pharm. 4, 454–489 (2010).

CAS Google Scholar

Wilde, A. S., Haughey, S. A., Galvin-King, P. & Elliott, C. T. The feasibility of applying NIR and FT-IR fingerprinting to detect adulteration in black pepper. Food Control 100, 1–7 (2019).

Article CAS Google Scholar

Longobardi, F. et al. Discrimination of geographical origin of lentils (Lens culinaris Medik.) using isotope ratio mass spectrometry combined with chemometrics. Food Chem. 188, 343–349 (2015).

Article CAS PubMed Google Scholar

Geana, I. et al. Geographical origin identification of Romanian wines by ICP-MS elemental analysis. Food Chem. 138, 1125–1134 (2013).

Article CAS PubMed Google Scholar

An, K. et al. Comparison of different drying methods on Chinese ginger (Zingiber officinale Roscoe): Changes in volatiles, chemical profile, antioxidant properties, and microstructure. Food Chem. 197, 1292–1300 (2016).

Article CAS PubMed Google Scholar

Parthasarathy, V. A., Chempakam, B. & Zachariah, T. J. Chemistry of spices. Chem Spices. https://doi.org/10.4327/jsnfs1949.32.267 (2008).

Huang, B., Wang, G., Chu, Z. & Qin, L. Effect of oven drying, microwave drying, and silica gel drying methods on the volatile components of ginger (Zingiber officinale Roscoe) by HS-SPME-GC-MS. Dry. Technol. 30, 248–255 (2012).

Article CAS Google Scholar

Yu, Y., Huang, T., Yang, B., Liu, X. & Duan, G. Development of gas chromatography-mass spectrometry with microwave distillation and simultaneous solid-phase microextraction for rapid determination of volatile constituents in ginger. J. Pharm. Biomed. Anal. 43, 24–31 (2007).

Article CAS PubMed Google Scholar

Li, X. et al. Analysis of the volatile compounds associated with pickling of ginger using headspace gas chromatography - ion mobility spectrometry. Flavour Fragr. J. 34, 485–492 (2019).

Article CAS Google Scholar

Pang, X., Cao, J., Wang, D., Qiu, J. & Kong, F. Identification of ginger (Zingiber officinale Roscoe) volatiles and localization of aroma-active constituents by GC-olfactometry. J. Agric. Food Chem. 65, 4140–4145 (2017).

Article CAS PubMed Google Scholar

Zhan, K., Wang, C., Xu, K. & Yin, H. Analysis of volatile and non-volatile compositions in ginger oleoresin by gas chromatography-mass spectrometry. Chinese J. Chromatogr. (Se Pu) 26, 692–696 (2008).

CAS Google Scholar

Yin, X. et al. Label-free proteomic analysis to characterize ginger from China and Ghana. Food Chem. 249, 1–7 (2018).

Article CAS PubMed Google Scholar

Asamenew, G. et al. Characterization of phenolic compounds from normal ginger (Zingiber officinale Rosc.) and black ginger (Kaempferia parviflora Wall.) using UPLC–DAD–QToF–MS. Eur. Food Res. Technol. 245, 653–665 (2019).

Article CAS Google Scholar

Zhao, X., Ao, Q., Du, F., Zhu, J. & Liu, J. Surface characterization of ginger powder examined by X-ray photoelectron spectroscopy and scanning electron microscopy. Colloids Surf. B. Biointerfaces. 79, 494–500 (2010).

Article CAS PubMed Google Scholar

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The authors gratefully acknowledge all the companies for their participation in the study. This work was supported by China Scholarship Council (grant agreement No. 201903250123) and the EU-China-Safe project (http://www.euchinasafe.eu/) which is funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 727864. Any opinions, findings and conclusions or recommendations expressed in this material are that of the authors and the European Commission does not accept any liability in this regard.

Food Quality & Design Group, Wageningen University & Research, P.O. Box 17, 6700 AA, Wageningen, The Netherlands

Qing Han, Sara W. Erasmus & Saskia M. van Ruth

Institute for Global Food Security, Biological Sciences, 19 Chlorine Gardens, Queen's University Belfast, BT9 5DL, Belfast, Northern Ireland, UK

Qing Han, Christopher T. Elliott & Saskia M. van Ruth

School of Food Science and Technology, Faculty of Science and Technology, Thammasat University, 99 Mhu 18, Pahonyothin Road, Khong Luang, Pathum Thani 12120, Thailand

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Q.H.: Conceptualization; investigation; methodology; resources; and writing – original draft, review & editing. S.W.E.: Supervision; validation; writing – review & editing. C.T.E.: Supervision; writing – review & editing. S. M. v. R.: Conceptualization; project administration; resources; supervision; validation; writing – review & editing; and funding acquisition.

Correspondence to Saskia M. van Ruth.

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Han, Q., Erasmus, S.W., Elliott, C.T. et al. A sense of ginger fraud: prevalence and deconstruction of the China-European union supply chain. npj Sci Food 6, 51 (2022). https://doi.org/10.1038/s41538-022-00166-y

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