Use of energy-dispersive X-ray fluorescence combined with chemometric modelling to classify honey according to botanical variety and geographical origin

Graphical Discrimination of New Zealand Honey from International Honey Using Elemental Analysis

This study investigated the potential of utilising the elemental fingerprinting of honey to differentiate New Zealand (NZ) honey from that of international origin. Twenty elements were analysed by ICP-MS in 352 honeys from 34 various countries. Of these, 323 honeys (245 New Zealand honeys, 78 international) and two subsets of data (NZ and European origin, n = 306, and, NZ and Denmark/Germany, n = 280) were visualised using principal component analysis (PCA). For the NZ/Europe subset, 42.2% of data was explained in the first two principal components. Statistical classification rules were also derived using linear discriminant analysis (LDA) and decision tree analysis. Various combinations of elements were explored for classification, considering the effect of soil-derived elements and those from anthropogenic sources. A high degree of accuracy (at least 90%) for the characterisation of New Zealand honey was observed for all statistical models, showing the robustness of these analyses. When using decision tree analysis to distinguish New Zealand samples from international samples, a tree with five terminal nodes (using Cs, Ba and Rb) was created with 92.4% accuracy. This work has demonstrated that elemental fingerprints of honey are a promising tool for categorising New Zealand honey from other geographical locations.

XRF analysis searching for fingerprint elemental profile in south-eastern Sicily tomatoes

The implementation of analytical techniques able to certify food quality and origin in a fast and non-destructive way is becoming a widespread need in the agri-food sector. Among the physical non-destructive techniques, X-ray fluorescence (XRF) spectrometry is often used to analyze the elemental composition of biological samples. In this study, X-ray fluorescence (XRF) elemental profiles were measured on tomato samples belonging to different geographical areas in Sicily (Italy). The purpose of this investigation was aiming to establish a protocol for in-situ measurement and analysis able to provide quality assessment and traceability of PGI agri-food products, specifically sustaining health safety and self qualifying bio-chemical signature. In detail, sampling was performed in one of the most tomato productive area of south-eastern Sicily (Pachino district), characterised by a relative higher amount of Organic Carbon and Cation Exchange Capacity, and compared with samples from other growing areas of Sicily, falling in Ragusa province and Mt. Etna region. Experimental data were analyzed in the framework of multivariate analysis by using principal component analysis and further validated by discriminant analysis. The results show the presence of specific elemental signatures associated to several characterizing elements. This methodology establishes the possibility to disentangle a clear fingerprint pattern associated to the geographical origin of an agri-food product.

Development and shelf-life assessment of soft-drink with honey

This scientific work describes research that aims to determine the physicochemical parameters of homogenized honey and its safety indicators based on the determination of toxic metals and radionuclides. A series of experimental studies were conducted to develop and study recipes for honey water based on different types of honey collected in the Lviv region of Ukraine, namely acacia, buckwheat, sunflower, coriander, goldenrod, linden, and weeds. According to the results of experiments, it was found that the studied honey meets all the requirements presented in the standard for natural honey. And the results obtained to determine the dry matter content and pH allowed to blend different types of honey and get honey drinks, which will expand the range of non-carbonated products, which is very popular, especially in summer, and drink this drink during the year. To prolong the shelf life of honey drinks, it is recommended to add citric acid in an amount of 1% by weight of the drink and sodium benzoate as a preservative in an amount of 0.1%. The quality of the obtained honey water samples was assessed using organoleptic evaluation and physicochemical parameters. The resulting beverages have good organoleptic characteristics and can be offered for products in the industry.

Detection of syrup adulterants in manuka and jarrah honey using HPTLC-multivariate data analysis

High-Performance Thin-Layer Chromatography (HPTLC) was used in a chemometric investigation of the derived sugar and organic extract profiles of two different honeys (Manuka and Jarrah) with adulterants. Each honey was adulterated with one of six different sugar syrups (rice, corn, golden, treacle, glucose and maple syrups) in five different concentrations (10%, 20%, 30%, 40%, and 50% w/w). The chemometric analysis was based on the combined sugar and organic extract profiles’ datasets. To obtain the respective sugar profiles, the amount of fructose, glucose, maltose, and sucrose present in the honey was quantified and for the organic extract profile, the honey’s dichloromethane extract was investigated at 254 and 366 nm, as well as at T (Transmittance) white light and at 366 nm after derivatisation. The presence of sugar syrups, even at a concentration of only 10%, significantly influenced the honeys’ sugar and organic extract profiles and multivariate data analysis of these profiles, in particular cluster analysis (CA), principal component analysis (PCA), principal component regression (PCR), partial least-squares regression (PLSR) and Machine Learning using an artificial neural network (ANN), were able to detect post-harvest syrup adulterations and to discriminate between neat and adulterated honey samples. Cluster analysis and principal component analysis, for instance, could easily differentiate between neat and adulterated honeys through the use of CA or PCA plots. In particular the presence of excess amounts of maltose and sucrose allowed for the detection of sugar adulterants and adulterated honeys by HPTLC-multivariate data analysis. Partial least-squares regression and artificial neural networking were employed, with augmented datasets, to develop optimal calibration for the adulterated honeys and to predict those accurately, which suggests a good predictive capacity of the developed model.

Feasibility study on the use of elemental profiles to authenticate aromatic rice: the case of Basmati and Thai rice

Among the thousands of existing rice varieties, aromatic rice has increasingly attracted consumer’s preference in recent years. Within aromatic rice, Basmati, cultivated in some regions in Pakistan and India, is highly demanded. Other aromatic rice, cultivated in specific regions, for instance in Thailand (commonly referred to as Jasmine Thai rice), are also highly appreciated by consumers. In this work, the elemental profiles of commercially available rice samples (17 Basmati, 11 Thai, and 7 Long Grain rice) were determined by energy-dispersive X-ray fluorescence (ED-XRF) spectroscopy. The mass fractions of P, Cl, S, K, Fe, Cu, and Zn were significantly different (95% confidence interval) between Basmati and Thai rice and between Thai and Long Grain rice; only Cl, S, and Zn were significantly different between Basmati and Long Grain rice. Multivariate evaluation of the results combining soft independent modelling by class analogy (SIMCA) and partial least square discriminant analysis (PLS-DA) allowed the correct classification (true positives) of 94.1, 85.6, and 100% of the Basmati, Long Grain, and Thai rice, respectively. The specificity (true negatives) of Basmati, Long Grain, and Thai was 94.4, 82.1, and 100%, respectively.

Are the elemental fingerprints of organic and conventional food different? ED-XRF as screening technique

Research has been conducted the last years to assess whether organically grown food is chemically different from produce of conventional agriculture and which markers are appropriate to discriminate between them. Most articles focus on one single food commodity, produced under strict controlled organic farming conditions, leaving open the question whether the difference would be seen when applied to the same commodity under different growing conditions. In this work 118 organic and 151 conventional samples of commercially available paprika powder, cinnamon, coffee, tea, chocolate, rice, wheat flour, cane sugar, coconut water, honey and bovine milk were characterised for their elemental composition using energy dispersive X-ray fluorescence. Resulting profiles were analysed using univariate and multivariate statistical techniques. Organic samples of a given commodity clustered together and were separated from their conventional counterparts. Differences in the elemental composition of food, could be used to develop statistical models for verifying the agronomical production system.

Investigation of inorganic elemental content of honey from regions of North Island, New Zealand

Determination of geographical origin of honey is important to consumers to confirm authenticity. This study investigated the elemental fingerprint of 181 honey samples collected from apiary sites in six regions of North Island, New Zealand to determine if differences were observed due to region of collection or land use surrounding the hive (e.g. agricultural, rural, urban). Using principal component analysis, soil related elements (Ca, K, Mg, Mn, Na) provided 75.2% discrimination of samples in the first two principal components. Overall, low concentrations of heavy metals were observed; lead was present in close proximity to highly trafficked roads (28.1% of samples; 9.50-76.5 µg kg^-1) and cadmium was primarily present in honey collected from agricultural land in the Waikato (<51.6 µg kg^-1). The use of an elemental fingerprint of New Zealand honey may be advantageous to determine the geographical origin compared to honey produced from other countries.

Discrimination of Tunisian Honey by Mineral and Trace Element Chemometrics Profiling

The concentrations of 19 chemical elements have been determined in 36 honey samples of different botanical (wildflower, eucalyptus, eucalyptus red flowers, prickly pears, lemon blossom, thyme, almond, rosemary and jujube) honeys from the three geographical areas of Tunisia (Sidi Bouzid, Nabeul and Sfax) using inductively coupled plasma mass spectrometry (ICP-MS). The aim of this work was to use the multielement analysis together with chemometric tools to verify the botanical and the geographical origin of honeys. The correlation on the basis of mineral element content between the honey samples and their botanical and/or geographical origins was in some measure achieved. The data collected on the samples were also used to evaluate the nutritional quality and the potential health risks associated with elements via consumption of the Tunisian honey. According to the results obtained, the intake of essential elements was small, and the potential health risks associated with toxic or potentially toxic elements via consumption of this food were overall insignificant.

Honey authenticity: analytical techniques, state of the art and challenges

Honey is a high-value, globally consumed, food product featuring a high market price strictly related to its origin. Moreover, honey origin has to be clearly stated on the label, and quality schemes are prescribed based on its geographical and botanical origin. Therefore, to enhance food quality, it is of utmost importance to develop analytical methods able to accurately and precisely discriminate honey origin. In this study, an all-time scientometric evaluation of the field is provided for the first time using a structured keyword on the Scopus database. The bibliometric analysis pinpoints that the botanical origin discrimination was the most studied authenticity issue, and chromatographic methods were the most frequently used for its assessment. Based on these results, we comprehensively reviewed analytical techniques that have been used in honey authenticity studies. Analytical breakthroughs and bottlenecks on methodologies to assess honey quality parameters using separation, bioanalytical, spectroscopic, elemental and isotopic techniques are presented. Emphasis is given to authenticity markers, and the necessity to apply chemometric tools to reveal them. Altogether, honey authenticity is an ever-growing field, and more advances are expected that will further secure honey quality.

Quality, composition and health-protective properties of citrus honey: A review

Citrus honey is one of the most important monofloral honeys produced and consumed worldwide. This honey has pleasant sensorial characteristics, which include light color and typical aroma and flavor. Besides that, several constituents such as minerals, phenolic and volatile compounds, amino acids, sugars, enzymes, vitamins, methylglyoxal and organic acids are found in citrus honey. Moreover, potential biological properties have been associated with citrus honey. All these factors make it highly desired by consumers, increasing its market value, which can stimulates the practice of fraud. Also, citrus honey is susceptible to contamination and to inadequate processing. All these factors can compromise the quality, safety and authenticity of citrus honey. In this sense, this review aims to update and to discuss, for the first time, the data available in the literature about the physicochemical and the sensorial characteristics, composition, health properties, contamination, authenticity and adulteration of citrus honey. With this background, we aim to provide data that can guide future researches related to this honey.

Use of elemental profiles to verify geographical origin and botanical variety of Spanish honeys with a protected denomination of origin

Honey with Protected Denomination of Origin (PDO) could be an attractive target for fraudsters. Elemental profiles by Energy Dispersive-X Ray Fluorescence were processed by multivariate methods to classify 183 PDO honeys produced in three regions of Spain (Liébana, Granada, Tenerife). Additional honey samples (18) produced in a fourth region without PDO (El Bierzo) separated well from the PDO clusters. The manganese content was a discriminant marker of Liébana PDO and El Bierzo, that could also be differentiated from each other. Within each region, distinct clusters revealed differences between dark vs light varieties, multi- vs uni-floral honey and producers of the same PDO. The developed models were validated with 131 samples produced outside the PDO regions and El Bierzo. The proposed classification approach could be implemented as a fast screening tool to support pollen analysis in honey authentication. The reduced number of observations in some light honey models affected their performance.

Feasibility study about the use of element profiles determined by ED-XRF as screening method to authenticate coconut sugar commercially available

Financial gain is a main driver for committing food fraud and replacement of ingredients with cheaper alternatives is an easy way to do it. Coconut sugar is becoming popular as an alternative to beetroot or cane sugar due to its high mineral content and lower glycaemic index. As its market price is about twice as high as that of conventional sugar, coconut sugar may become target to fraudulent manipulation. The present work explores the feasibility of using energy-dispersive X-ray fluorescence as a screening tool to verify its authenticity. Mass fractions of P, Cl, S, K, Ca, Fe, Cu, Br, Rb, and Sr determined in eleven coconut, ten cane, and one beetroot sugar samples, purchased in Belgian, Spanish, Polish, and Italian supermarkets were used for discriminating the different sugars. On average, the mass fractions of all the mentioned elements were higher in coconut than in cane and beetroot sugars. Multivariate analysis of the elemental fingerprint by Soft Independent Modelling of Class Analogies was used for authentication purposes. Models constructed were characterised by zero false positives; three coconut sugars (27%) could not be classified as such, neither as cane sugars.