Geographical discrimination of honeys through antioxidant capacity,mineral content and colour

The assessment of geographical origin of honey is economically important for producers and consumers as every region may present particular quality characteristics. In this study, honeys from the seven different regions of Buenos Aires province (Argentina) were characterised by their antioxidant capacity (DPPH, FRAP), total phenolic content (TPC), mineral composition, colour and ash. Honeys showed significant differences among their antioxidant capacity (DPPH), ash, colour and mineral content (P ≤ 0.05). Besides, a good antioxidant activity and low amounts of Cu and Zn (<1.0–1.5 and 0.7–1.8 mg kg^?1, respectively) were found in the samples. Significant Pearson's correlations (P ≤ 0.05) among the different parameters were found. Moreover, the linear discriminant analysis allowed the classification of honeys in their original groups with a prediction success of 98%. The present results suggest that honeys could be correctly classified by their geographical origin through their TPC, colour, ash and mineral concentrations.     

Characterisation of Serbian unifloral honeys according to their physicochemical parameters

The characterisation of three unifloral Serbian honeys (acacia, sunflower and linden) was carried out based on some common physicochemical parameters (water content, electrical conductivity, free acidity, optical rotation and pH). A total of 201 honey samples, collected during the 2009 harvesting season, were analysed. Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to highlight the data structure and to find the relationships between the physicochemical parameters and the botanical origin of honey. The variables that best discriminated the samples were electrical conductivity (ranging from 0.10 to 0.76 mS/cm), free acidity (ranging from 7.80 to 42.70 meq/kg) and pH (ranging from 3.17 to 5.85). LDA resulted in a classification model with a high predictive power, allowing further assessment of unknown samples of the three unifloral honeys. Determination of geographic origin of acacia honey samples based on physicochemical properties and chemometrics was attempted.     

Classification of the floral origin of Uruguayan honeys by chemical and physical characteristics combined with chemometrics

This study reports both the chemical and physical characterization of honey samples produced in Uruguay and the classification of honeys by floral origin using chemometrics. Moisture (M), pH, electric conductivity (EC), hydroxymethyl-2-furaldehyde and colour composition were analysed. As well as composition, classification of honey samples from different floral origins namely pasture (n=6), Eucalyptus spp. (n=6), Citrus spp. (n=5), Baccharis spp. (n=5), multifloral (n=2) and others (n=6) was attempted using principal component analysis and linear discriminant analysis. All the honey samples were found to meet the international specifications for the chemical parameters evaluated. The EC, M and pH were the variables that explain the classification of honey samples according to floral origin. More than 80% of the samples belonging to pasture, Citrus spp. and Baccharis spp. honeys were correctly classified according to its floral origin. Further studies are needed in order to investigate the effect of other floral and geographical (region) to provide a robust model to classify honey samples.     

近红外光谱分析技术在花生原产地溯源中的应用

采用近红外光谱结合化学计量学方法对不同省份来源的花生样品进行溯源研究。首先花生近红外光谱通过标准正态变换加去趋势化预处理降噪、主成分分析降维和小波转换降噪降维两种处理,然后结合线性判别分析、贝叶斯判别分析和k最近邻分析3种判别模型对不同省份来源地花生进行判别。通过分析最优判别组合结果表明,小波转换结合k最近邻分析对花生产地分类效果最好,原始正确分类率为100.0%;交叉验证正确分类率为55.9%。初步实现了花生产地判别,但模型的性能仍有待提高。     

Antioxidant properties and phenolic content of sulla (Hedysarum spp.) honeys from Southern Italy

The geographical origin greatly influences the qualitative and nutraceutical characteristics of honey. In this study, a total of twenty‐four sulla honeys from eight different geographical areas of Southern Italy have been examined for total phenolic content (Folin–Ciocalteu method), antioxidant activity (FRAP and DPPH assays), colour intensity (ABS₄₅₀), and identification and quantification of phenolic acids (RP‐HPLC/UV‐VIS method). The total phenolic content ranged from 47.9 (Potentino honeys) to 248.3 mg GAE per kg honey (Penisola Sorrentina honeys). The antioxidant activity ranged from 47.06% (Basso Pollino honeys) to 88.25% (Penisola Sorrentina honeys), and from 98.26 μM Fe (II) (Potentino honeys) to 786.53 μm Fe (II) (Tarantino honeys) for DPPH and FRAP assays, respectively. Major phenolic acids identified in analysed samples were gallic, caffeic and ferulic acids. Correlations between the parameters analysed were statistically significant (P < 0.05). The results of the study showed that the parameters studied are greatly affected by the peculiarities of their production area.     

Geographical discrimination of honeys by using mineral composition and common chemical quality parameters

Sixty honey samples from six different production zones of the provinces of Salamanca, Zamora and Cáceres (western Spain) were analysed for 13 common legal physicochemical parameters and 17 mineral elements (13 cations and four anions) in order to test for their geographical classification. Application of linear stepwise discriminant analysis to a number of variables made of a selection of analytical results and their simple mathematical functions allowed, firstly, discrimination between honeys from all six zones and, secondly, discrimination between honeys from the three zones of the province of Salamanca. The most discriminant variables selected for the six zones were 10 in number, a combination of three physicochemical parameters and nine elements, with a result of 91.38% of correctly classified samples; for the three zones of the province of Salamanca, regarded with special interest in our study, six variables were selected (made of eight elements) with a result of 97.07% of correctly classified samples. © 2000 Society of Chemical Industry     

Characterization and classification of Thymus capitatus (L.) honey according to geographical origin based on volatile compounds,physicochemical parameters and chemometrics

Greek thyme honeys (Thymus capitatus L.) were characterized and classified according to geographical origin based on the determination of volatile compounds and physicochemical parameters using MANOVA and Linear Discriminant Analysis. Forty two thyme honey samples were collected during the harvesting period in 2011 from 5 different regions in Greece known to produce thyme honey of good quality. The analysis of volatile compounds was performed by Headspace Solid Phase Microextraction coupled to Gas chromatography/Mass spectroscopy. Forty seven volatile compounds were identified and semi-quantified. Physicochemical analysis included the determination of pH, free, lactonic and total acidity, electrical conductivity, moisture, ash, lactonic/free acidity ratio and color parameters: L*, a*, b*. Using 9 volatile compounds and 11 physicochemical parameters the honey samples were satisfactorily classified according to geographical origin using volatile compounds (64.3% correct prediction), physicochemical parameters (92.7% correct prediction), and the combination of both (92.9% correct prediction).     

A potentiometric electronic tongue for the discrimination of honey according to the botanical origin. Comparison with traditional methodologies: Physicochemical parameters and volatile profile

The effectiveness of a potentiometric electronic tongue, made of various metals and metallic compounds was evaluated for the differentiation of honey in three different states: raw, liquefied and pasteurized. Principal component analysis (PCA) and a neural network showed that potentiometric electrodes seem useful to classify honey by its botanical origin, though they do not seem capable of discrimination between applied thermal treatments. The same was observed in the samples for physicochemical parameters and volatile compounds analysed with PCA. Au, Cu and Ag electrodes were more decisive in the discrimination of honey. A remarkable correlation (PLS analysis) between the electronic tongue and the physicochemical parameters was found, the best results being for color Pfund (r² = 0.958), L^∗ (r² = 0.935) and diastase activity (r² = 0.926). The correlation with volatile compounds was much weaker, though this improved for specific characteristic compounds in each monofloral variety. Thus, this is a good starting point for the development of new systems focused on the honey sector.     

Botanical discrimination and classification of honey samples applying gas chromatography/mass spectrometry fingerprinting of headspace volatile compounds

A validated method for the discrimination and classification of honey samples performing GC/MS fingerprinting of headspace volatile compounds was developed. Combined mass spectra of honey samples originated from different plants and geographical regions of Greece were subjected to orthogonal partial least squares-discriminant analysis™ (OPLS™-DA), soft independent modelling of class analogy (SIMCA), and OPLS™-hierarchical cluster analysis (OPLS™-HCA). Analyses revealed an excellent separation between honey samples according to their botanical origin with the percentage of misclassification to be as low as 1.3% applying OPLS™-HCA. Fragments (m/z) responsible for the observed separation were assigned to phenolic, terpenoid, and aliphatic compounds present in the headspace of unifloral honeys. On the other hand, a variable classification for citrus and thyme honeys according to their geographical origin could be achieved. Results suggested that the developed methodology is robust and reliable for the botanical classification of honey samples, and the study of differences in their chemical composition.     

蜂蜜用葡萄糖溶液掺假的近红外光谱检测

为实现蜂蜜用葡萄糖溶液掺假的快速检测,利用近红外光谱技术(NIRS)对真假蜂蜜样本进行了研究。121个真蜂蜜样本中取8个分别按5%、10%、15%、20%、25%、30%、35%、45%、55%和65%的质量比掺假,共得80个掺假样本。不同光谱预处理方法的模型结果表明最佳预处理方法为自归一化加一阶微分(真假判别)和中心化加一阶微分(掺假量分析)。利用CARS(Competitive adaptive reweighted sampling)法筛选变量,PLS-LDA模型对真假蜂蜜的判别准确率为100%,PLS模型对掺假量定量分析的交互验证均方差为3.137 7,预测均方差为2.980 0。结果表明NIRS能实现蜂蜜用葡萄糖掺假的检测。     

Simplex lattice mixture design approach on the rheological behavior of glucomannan based salep-honey drink mixtures: An optimization study based on the sensory properties

The rheological properties of salep drink sweetened with different honeys were measured using a controlled-stress rheometer. Mixture design experiments were used to study the effect of interactions among pine, flower and highland honeys on the rheological properties of salep-honey drink mixture (SHDM) samples. In addition, product optimization was carried out using the ridge analysis to determine the optimum mixture proportions based on sensory properties of SHDM samples. Flower honey was the component showing the highest effect on the consistency coefficient values of SHDM samples. The preference of panelists was more prominent for the SHDM samples including the higher concentrations of highland honey with respect to odour and overall preference parameters. Optimum values of pine, flower and highland honeys in the mixture were found to be 0–85%, 0–40% and 15–100%, respectively, with respect to sensory properties. In addition, ridge analysis results revealed that the SHDM should include 65% highland honey, 35% pine honey and no flower honey to obtain the maximum overall preference score (7.24). The consistency coefficient and flow behavior index values of the sample to get maximum overall preference score (7.24) were predicted to be 3.650 Pa sⁿ and 0.435, respectively.     

Application of a statistical approach to the classification of honey by geographic origin

Forty eight honeys from the La Rioja region of Spain were analysed to establish their quality. Fourteen legally required parameters of quality control were measured. Samples were obtained from two geographic areas of production: Valley and Sierra. These areas present different agroclimatic conditions and, thus, different flora. Classification of these honeys according to their geographic origin was achieved by applying multivariate statistical analysis to the chemical and physical data. Acidity (free acidity and pH), mineral content (electrical conductivity and ash) and factors related to degree of freshness (hydroxymethylfurfural and diastatic activity), were found to be the most important features for classification. Determination of the geographic origin of a La Rioja honey (Valley or Sierra) was possible with 83% accuracy using only these legally required quality control parameters; pollen studies were not necessary to achieve this objective.     

Characterisation of the geographical origin of Western Greek virgin olive oils based on instrumental and multivariate statistical analysis

In this work, measurements of free acidity, peroxide content, spectrophotometric parameters, chlorophyll content, phenol, sterol, fatty acid and triacylglycerol composition, were carried out on samples of virgin olive oils (VOOs) coming from four different Greek Ionian islands, i.e. Zakynthos, Kefalonia, Lefkada and Kerkyra. An analysis of variance (ANOVA) highlighted statistically significant differences (p < 0.01) in the values of 26 analytical parameters amongst the VOOs produced in the four different geographical regions but a post-hoc test showed that no variable was able to distinguish all four origins. Analogously, a Principal Component Analysis (PCA) showed a modest grouping of VOOs according to geographical origin except for Kerkyra samples which were more distinct from others. Applying discriminant function analysis (DFA) a good separation of the four geographical groups was achieved with classification and prediction abilities equal to 97.7% and 95.3%, respectively. Moreover, the analysis of the standardised coefficients showed that the fatty acids and triacylglycerols were the most discriminant variables. This last outcome was confirmed by comparison of the prediction performances obtained applying DFA on four subdatasets containing fatty acids (69.8%), triacylglycerols (76.7%), sterols (62.8%), and remaining parameters (65.1%) together, respectively. As the results showed, the multidisciplinary approach that combines different types of analytical determinations improved the discrimination of geographical origin for Greek virgin olive oils.     

基于主成分分析及聚类分析的不同产地冬枣品质特性分析

通过测定采自5 个主产区冬枣的18 个品质指标,基于多重比较、相关性分析、主成分分析、聚类分析和Fisher判别分析对不同产地冬枣品质进行评价并筛选特征指标。继而根据不同地域冬枣的特征指标,探讨其对冬枣产地溯源的可行性。结果表明：主成分分析综合得分结果表明新疆和田和山东沾化是冬枣的优势产区;结合聚类分析将18 项品质指标简化为可溶性固形物、钾、锰、单果质量、硬度、乙醇、色泽和含水量8 项具有代表性的特征指标;Fisher判别分析显示8 个特征指标可作为5 个冬枣主产区产地溯源的品质指标,且对冬枣产地整体正确判别率为100.0%,交叉检验正确判别率为97.2%。本研究为不同产地冬枣品质评价和核心品质指标的确定提供了依据,在冬枣的产地溯源中具有重要意义。     

Impact of botanical source and processing conditions on physicochemical properties and antioxidant activity of honey in the northern part of Thailand

Phenolics, melissopalynological analysis, and selected physicochemical characteristics could differentiate floral honey origin. Botanical sources (longan, multifloral and Manuka) had more pronounced effect on honey properties than processing conditions. The conductivity was related to ash content and colour of honey. Total sugar, fructose and glucose content in all samples were not significantly different. Melissopalynological analysis was used to verify the botanical source of honey samples. Predominant pollen was identified. Results characterising antioxidant properties (DPPH radicals, hydroxyl radicals, and carbon-centred radicals scavenging activity) were confirmed via both Electron Spinning Resonance and oxygen radical absorbance capacity (ORAC). They showed that only hydroxyl radicals scavenging activity and ORAC were significantly different. Type and amount of phenolics in honey samples identified using HPLC could differentiate botanical source. Gallic acid and kaempferol were potential marker phenolics for longan honey. Multivariate statistical analysis allowed discrimination of honey from different botanical sources based on their phenolic profiles.     

Flavonoids in Meliponinae honeys from Venezuela related to their botanical, geographical and entomological origin to assess their putative anticataract activity

 Honey was collected from 24 stinglessbee nests in Venezuela. The flavonoid compounds in the phenolic extracts were analysed and related to the botanical, geographical and entomological origin of the honey. Honeys produced in savannas were richer in flavonoids compared with honeys from the forests. It was found that phenolic extracts of honey of the same geographical origin had similar flavonoid profiles, whereas the same could not be said of honeys of the same entomological origin, although the botanical origin of the samples was variable. It is proposed that analysis of stinglessbee honey eyedrops in terms of their flavonoid content can be used as a basis of authenticating and controlling for their geographical origin. Received: 28 July 1997     

Pattern recognition analysis on nutritional profile and chemical composition of edible bird’s nest for its origin and authentication

Authenticity of food is of great importance to ensure food safety and quality, and to protect consumer rights. A rapid and accurate method for authentication of edible bird’s nest (EBN) was proposed by using nutritional profile and chemical composition, and pattern recognition analysis. The authentication of EBN includes identification and classification of EBN by production origin (houses or caves), species origin (Aerodramus fuciphagus or Aerodramus maximus) and geographical origin (Peninsular Malaysia or East Malaysia) based on their active compositional content. Three pattern recognition methods, principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA), were employed to develop classification models for authentication of EBN origins. Compared to PCA and HCA, LDA is more accurate and efficient in distinguishing EBN by different production, species, and geographical origins, having classification ability of 100% and prediction ability of 92% as validated by cross-validation method. The key chemical markers for production origin differentiation are total phenolic content, zinc, valine, and calcium, while for species origin discrimination are sialic acid, serine, phenylalanine and valine, and for geographical origin differentiation are arsenic and mercury. The findings suggest that nutritional and chemical profiles combined with pattern recognition analysis are promising strategy for rapid authentication of EBN and its products.     

Characterization of honeys by their botanical and geographical origins based on physico-chemical properties and chemo-metrics analysis

Honey, because of its nutritional and medicinal values, is in high demand and has become one of the important commodities. However, the issue of its quality and authenticity remain as important factors in consumption and marketing of honey. To assess the possibility of discriminating honeys by their geographical and botanical origins; 30 fresh honey samples of different botanical and geographical origins were collected and their major physico-chemical properties such as: total dissolved sugar (TDS), total ash, sugar profile, acidity, metallic ions and electric conductivity (EC) were investigated. The data was subjected to different chemo-metric (Hierarchical Cluster, Principal components and stepwise discriminant) analysis. Among the 23 characters used in the analysis; only 11 (TDS, EC, acidity, total ash, colour, and some specific metallic ions) characters have showed significant variations among different origin honeys. According to the stepwise discriminant analysis; 11 variables confirmed the grouping of the honey samples into four cluster groups based on their botanical and geographical origins. The clustering of the honeys associated with dominant plant source & climatic conditions of their origins. The study generally revealed the successful discrimination of honeys into their botanical and geographical provenances using fewer physico-chemical characters supported with melissopalynological data through applying suitable chemo-metric analysis.     

Differentiation of saffron from four countries by mid-infrared spectroscopy and multivariate analysis

Mid-infrared spectroscopy combined with multivariate analysis has been applied for the discrimination of 250 saffron samples from Greece (40 samples), Iran (87 samples), Italy (60 samples) and Spain (63 samples). The infrared spectra of saffron filament samples and their organic extracts were recorded. Principal component analysis was applied to different spectral regions. Then the principal components were used as variables in discriminant analysis. The best discriminatory approach was achieved in the spectral region 2000–700 cm⁻¹. The spectral region responsible for the differentiation of Italian samples is in the region of carbonyl group around 1746 cm⁻¹. The spectral region at around 1600 cm⁻¹ and the band at 1670 cm⁻¹ are responsible for the differentiation of samples from the remaining countries. From the original grouped cases, 93.6% were correctly classified. The correct classification rates for saffron samples from Greece, Iran, Italy and Spain were 90.0, 89.5, 96.7 and 98.4%, respectively. The combination of infrared spectroscopic technique with multivariate analysis is a rapid and ambient method to discriminate saffron samples in terms of geographical origin.     

Pattern of pH and electrical conductivity upon honey dilution as a complementary tool for discriminating geographical origin of honeys

Seven physicochemical parameters (water content, ash, water activity, free, lactone and total acidity, pH and electrical conductivity) were analyzed in 19 nectar honeys of different floral origin and from several regions of Argentina. In addition, the pattern of electrical conductivity and pH upon honey dilution were also studied with increasing honey concentration, the pH values decreased exponentially. The dependence of specific electrical conductivity (κ) on honey concentration was characterized by a maximum at a κ value (κ_max) corresponding to a dry solids of honey concentration of 30–35% (w/w). For a given geographical region, ash and acidity values were useful for discriminating honeys of different floral origins. The most adequate parameters for discriminating honeys of different geographical origin were those which described the patterns of pH and electrical conductivity with changes of honey concentration.