Investigating C-4 sugar contamination of manuka honey and other New Zealand honey varieties using carbon isotopes

Isotopic characteristics (δ13C, δ15N, and δ18O) of honey from Bangladesh retail markets: Investigating sugar manipulation, botanical and geographical authentication

The study analyzed stable isotope composition (carbon, nitrogen, oxygen) of Bangladesh origin monofloral and multifloral honey for the first time to identify the C-4plant sugar adulteration, botanical and geographical differentiation. The C-4 sugar content (11.90 to 86.61%) using carbon isotope values of whole honey and protein extractidentified18% adulterated honeys.Whereas 82% honey have been detected as authentic with the δ13C ranges from -24.86 to -29.26‰ and the C-4 sugar values ranges from -6.75 to 5.67%. The chemometric approach using carbon and nitrogen isotopesvalues revealed discrimination among floral types of Bangladeshi authentic honeys indicating the influence of botanical source on isotopic composition. Canonical discriminant analysis (CDA) of C and N isotopes showed geographic distinction among Bangladeshi and overseas origin honeys. It is notable that the black seed honeys were correctly classified with the CDA analysis representing this type as unique Bangladesh brand as New Zealand manuka honey.

Fourier transform infrared spectroscopy and chemometrics for the rapid screening of economically motivated adulteration of honey spiked with corn or rice syrup

Due to its high price, increased consumption, and limited production, honey has been a main target for economically motivated adulteration (EMA). An approach combining Fourier-Transform infrared spectroscopy (FTIR) and chemometrics was evaluated to develop a rapid screening tool to detect potential EMA of honey with either rice or corn syrup. A single-class soft independent modeling of class analogy (SIMCA) model was developed using a diverse set of commercial honey products and an authentic set of honey samples collected at four different U.S. Department of Agriculture (USDA) honey sample collection locations. The SIMCA model was externally validated with a set of calibration-independent authentic honey, typical commercial honey control samples, and those spiked with rice and corn syrups in the 1-16% concentration range. The authentic honey and typical commercial honey test samples were correctly predicted with an 88.3% classification rate. High accuracy was found in predicting the rice and corn syrup spiked samples above the 7% concentration range, yielding 97.6% and 94.8% correct classification rates, respectively. This study demonstrated the potential for a rapid and accurate infrared and chemometrics method that can be used to rapidly screen for either rice or corn adulterants in honey in less than 5 min.

Regional and global perspectives of honey as a record of lead in the environment

Honey from Apis mellifera is a useful and inexpensive biomonitor for mapping metal distributions in urban centers. The sampling resolution of a biomonitoring survey (e.g., city versus global scale) determines which geochemical processes are reflected in the results. This study presents Pb isotopic compositions and metal concentrations in honey from around the world, sampled at varying resolutions: honey from Canada (n = 21), the United States (n = 111), Belgium (n = 25), and New Zealand (n = 10), with additional samples from Afghanistan, Brazil, Cuba, Germany, Liberia, Taiwan, and Turkey. Honey was sampled at high resolution in two uniquely different land-use settings (New York Metro Area and the Hawaiian island of Kaua'i), at regional-scale resolution in eastern North America (including the Great Lakes region), and Pb isotopic compositions of all samples were compared on a global scale. At high sampling resolution, metal concentrations in honey reveal spatially significant concentration gradients: in New York City, metals associated with human activity and city infrastructure (e.g., Pb, Sb, Ti, V) are more concentrated in honey collected within the city compared to honey from upstate New York, and metal concentrations in honey from Kaua'i suggest polluting effects of nearby agricultural operations. At lower resolution (regional and global scales), lead isotopic compositions of honey are more useful than metal concentrations in revealing large-scale Pb processes (e.g., the enduring legacy of global leaded gasoline use throughout the twentieth century) and the continental origin of the honey. Lead isotopic compositions of honey collected from N. America (especially from the eastern USA) are more radiogenic (²⁰⁶Pb/²⁰⁷Pb: 1.132-1.253, ²⁰⁸Pb/²⁰⁶Pb: 2.001-2.129) compared to European honey, and honey from New Zealand, which has the least radiogenic isotopic compositions measured in this study (²⁰⁶Pb/²⁰⁷Pb: 1.077-1.160, ²⁰⁸Pb/²⁰⁶Pb: 2.090-2.187). Thus, biomonitoring using honey at different resolutions reflects differing processes and, to some extent, a honey terroir defined by the Pb isotopic composition. The data presented here provide important (and current) global context for future studies that utilize Pb isotopes in honey. Moreover, this study exhibits community science in action, as most of the honey was collected by collaborators around the world, working directly with local apiarists and hobby beekeepers.

Achieving Food Authenticity and Traceability Using an Analytical Method Focusing on Stable Isotope Analysis

High-value agricultural products are characterized by the geographical conditions of the production areas such as climatic and soil conditions. These products are protected by the geographical indication (GI) protection system, which has been introduced in more than 100 countries. Because GI products are expensive in the market, products are often mislabeled as GI. Thus, there is an urgent need for the development of analytical methods that enable the tracing of geographical origins of food materials. Stable isotope analysis is used to trace the geographical origin of food materials. In this study, we review the applications for tracing the geographical origin of agricultural products (especially rice, beef, and honey) focusing on an analytical method for analyzing stable isotopes (δD, δ13C, δ15N, δ18O, and δ34S).

Sugar Profiling of Honeys for Authentication and Detection of Adulterants Using High-Performance Thin Layer Chromatography

Honey adulteration, where a range of sugar syrups is used to increase bulk volume, is a common problem that has significant negative impacts on the honey industry, both economically and from a consumer confidence perspective. This paper investigates High-Performance Thin Layer Chromatography (HPTLC) for the authentication and detection of sugar adulterants in honey. The sugar composition of various Australian honeys (Manuka, Jarrah, Marri, Karri, Peppermint and White Gum) was first determined to illustrate the variance depending on the floral origin. Two of the honeys (Manuka and Jarrah) were then artificially adulterated with six different sugar syrups (rice, corn, golden, treacle, glucose and maple syrup). The findings demonstrate that HPTLC sugar profiles, in combination with organic extract profiles, can easily detect the sugar adulterants. As major sugars found in honey, the quantification of fructose and glucose, and their concentration ratio can be used to authenticate the honeys. Quantifications of sucrose and maltose can be used to identify the type of syrup adulterant, in particular when used in combination with HPTLC fingerprinting of the organic honey extracts.

Compositional identification and authentication of Chinese honeys by 1H NMR combined with multivariate analysis

Honey authentication has been becoming more and more important and necessary to the honey producers, the consumers and the market regulatory authority due to its favorite organoleptic and healthy properties, high value and increasing export but prevalent falsification practice for economic motivation in China and the potential health risk of adulterated honey. In this study, we obtained the spectral profiles of 90 authentic and 75 adulterated Chinese honey samples by means of high resolution nuclear magnetic resonance (NMR) spectroscopy, and 65 kinds of major and minor components in honey were identified and quantified from their NMR spectra. Combining with the multivariate statistical analyses including principal component analysis (PCA), linear discriminant analysis (LDA), and orthogonal partial least squared-discriminant analysis (OPLS-DA), the discrimination models were successfully established to identify the adulterated honeys from the authentic ones with an accurate rate of 97.6%. Furthermore, the corresponding volcano plot was used to screen out 8 components including proline, xylobiose, uridine, β-glucose, melezitose, turanose, lysine and an unknown component, which are responsible for the differentiation between the authentic and adulterated honeys and will help to control Chinese domestic honey market.

Determination of honey adulteration with beet sugar and corn syrup using infrared spectroscopy and genetic-algorithm-based multivariate calibration

BACKGROUND

Fourier transform infrared spectroscopy (FTIR) equipped with attenuated total reflectance accessory was used to determine honey adulteration. Adulterated honey samples were prepared by adding corn syrup, beet sugar and water as adulterants to the pure honey samples in various amounts. The spectra of adulterated and pure honey samples (n = 209) were recorded between 4000 and 600 cm^-1 wavenumber range.

RESULTS

Genetic-algorithm-based inverse least squares (GILS) and partial least squares (PLS) methods were used to determine honey content and amount of adulterants. Results indicated that the multivariate calibration generated with GILS could produce successful models with standard error of cross-validation in the range 0.97-2.52%, and standard error of prediction between 0.90 and 2.19% (% w/w) for all the components contained in the adulterated samples. Similar results were obtained with PLS, generating slightly larger standard error of cross-validation and standard error of prediction values.

CONCLUSION

The fact that the models were generated with several honey samples coming from various different botanical and geographical origins, quite successful results were obtained for the detection of adulterated honey samples with a simple Fourier transform infrared spectroscopy technique. Having a genetic algorithm for variable selection helped to build somewhat better models with GILS compared with PLS. © 2018 Society of Chemical Industry.

Authenticity and geographic origin of global honeys determined using carbon isotope ratios and trace elements

Honey is the world's third most adulterated food. The addition of cane sugar or corn syrup and the mislabelling of geographic origin are common fraudulent practices in honey markets. This study examined 100 honey samples from Australia (mainland and Tasmania) along with 18 other countries covering Africa, Asia, Europe, North America and Oceania. Carbon isotopic analyses of honey and protein showed that 27% of commercial honey samples tested were of questionable authenticity. The remaining 69 authentic samples were subject to trace element analysis for geographic determination. One-way ANOVA analysis showed a statistical difference (p < 0.05) in trace element concentrations of honey from Australian regions and different continents. Principal component analysis (PCA) and canonical discriminant analysis (CDA) coupled with C5.0 classification modelling of honey carbon isotopes and trace element concentrations showed distinct clusters according to their geographic origin. The C5.0 model revealed trace elements Sr, P, Mn and K can be used to differentiate honey according to its geographic origin. The findings show the common and prevalent issues of honey authenticity and the mislabelling of its geographic origin can be identified using a combination of stable carbon isotopes and trace element concentrations.

Adulteration Identification of Commercial Honey with the C-4 Sugar Content of Negative Values by an Elemental Analyzer and Liquid Chromatography Coupled to Isotope Ratio Mass Spectroscopy

According to the AOAC 998.12 method, honey is considered to contain significant C-4 sugars with a C-4 sugar content of >7%, which are naturally identified as the adulteration. However, the authenticity of honey with a C-4 sugar content of <0% calculated by the above method has been rarely investigated. A new procedure to determine δ(13)C values of honey, corresponding extracted protein and individual sugars (sucrose, glucose, and fructose), δ(2)H and δ(18)O values, sucrose content, and reducing sugar content of honey using an elemental analyzer and liquid chromatography coupled to isotope ratio mass spectroscopy, was first developed to demonstrate the authenticity of honey with a C-4 sugar content of <0%. For this purpose, 800 commercial honey samples were analyzed. A quite similar pattern on the pentagonal radar plot (isotopic compositions) between honey with -7 < C-4 sugar content (%) < 0 and 0 < C-4 sugar content (%) < 7 indicated that honey with -7 < C-4 sugar content (%) < 0 could be identified to be free of C-4 sugars as well. A very strong correlation is also observed between δ(13)C honey values and δ(13)C protein values of both honey groups. For the δ(18)O value, the C-4 sugar content (%) < -7 group has lower (p < 0.05) values (16.30‰) compared to other honey, which could be a useful parameter for adulterated honey with a C-4 sugar content (%) < -7. The use of isotopic compositions and some systematic differences permits the honey with a C-4 sugar content of <0% to be reliably detected. The developed procedure in this study first and successfully provided favorable evidence in authenticity identification of honey with a C-4 sugar content of <0%.

Linking soil, water, and honey composition to assess the geographical origin of argentinean honey by multielemental and isotopic analyses

The objective of this research was to investigate the development of a reliable fingerprint from elemental and isotopic signatures of Argentinean honey to assess its geographical provenance. Honey, soil, and water from three regions (Córdoba, Buenos Aires, and Entre Rı́os) were collected. The multielemental composition was determined by ICP-MS. δ(13)C was measured by isotopic ratio mass spectrometry, whereas the (87)Sr/(86)Sr ratio was determined using thermal ionization mass spectrometry. The data were analyzed by chemometrics looking for the association between the elements, stable isotopes, and honey samples from the three studied areas. Honey samples were differentiated by classification trees and discriminant analysis using a combination of eight key variables (Rb, K/Rb, B, U, (87)Sr/(86)Sr, Na, La, and Zn) presenting differences among the studied regions. The application of canonical correlation analysis and generalized procrustes analysis showed 91.5% consensus between soil, water, and honey samples, in addition to clear differences between studied areas. To the authors' knowledge, this is the first report demonstrating the correspondence between soil, water, and honey samples using different statistical methods, showing that elemental and isotopic honey compositions are related to soil and water characteristics of the site of origin.