Multi-element Fingerprints Research Articles

Geographical specificity of fatty acid and multi-element fingerprints of soybean in northern China

Soybean is an important food crop in China. Recently, crops cultivated in specific geographical locations have started attracting high prices. Therefore, developing a technique to identify the geographical origin of a crop is crucial to prevent fraud. In this work, we measured the contents of five fatty acids and 17 elements in soybean samples produced in Heilongjiang, the Inner Mongolia Autonomous Region, Jilin and Liaoning using gas chromatography and inductively coupled plasma mass spectrometry. Correlation analysis, principal component analysis and cluster analysis were used to identify the relationship between the metabolic fingerprint and the geographical location. Our results showed a significant correlation between the contents of fatty acids and geographical origin. Principal component analysis provided a preliminary classification of all variables. Hierarchical clustering, based on heat maps, showed that all samples could be classified based on their geographical origins. The model established by partial least squares discriminant analysis showed 89.9% predictive ability, further proving that the 14 classification indexes, comprising fatty acids and elements, could be used as molecular fingerprints to identify and distinguish soybean samples from four different production areas. Besides, pairs of soybean sample fingerprints from the four provinces were compared, and the differences in fatty acid and element contents between the provinces were explained based on the climatic environment and soil distribution. In conclusion, our method of classifying and confirming soybean production areas through fatty acid and multi-element fingerprints can potentially be used for identifying soybean of similar origins.

Assuring food safety and traceability of polished rice from different production regions in China and Southeast Asia using chemometric models

A novel strategy combining elemental analysis-isotopic ratio mass spectrometry (EA-IRMS) and inductively plasma coupled mass spectrometry (ICP-MS) analysis with chemometric data-processing was applied to differentiate polished rice from different growing regions in China with rice imported from Southeast Asia (Thailand and Malaysia). Seven stable isotope ratios (i.e. δ13C, δ15N, δ2H, δ18O, 87/86Sr, 207/206Pb and 208/207Pb) and 25 multielemental concentrations (Na, Ca, Fe, Zn, Rb, Ag, and Cd, etc.) were assayed and used to establish principal component analysis (PCA) and step-wise linear discriminant analysis (LDA) modeling to determine the rice's geographical origin. The prediction accuracies were cross-validated, and “blind sample” tests were all higher than 90.0% for rice samples from different production areas in China and 85.0% for rice imported from Southeast Asia, respectively. The high level of geographical traceability when combining stable isotope and multielement fingerprints with chemometric data-processing provides a promising tool to assure the origin of Chinese polished rice. This authentication method protects premium rice brands, combats commercial fraud, and quickly locates the origin of contaminated Cd rice to add verifiable food safety measures for consumers.

Elemental analysis of sea cucumber from five major production sites in China: A chemometric approach

Geographic origin of sea cucumber is topic of interest for both consumers and producers since the prices of sea cucumber vary largely according to their geographic origins. It is currently important that a scientific technique should be developed for determining geographic origin as a mean to detect fraudulent labeling. We have therefore developed a technique to classify the geographic origin of sea cucumber based on elemental analysis combined with the statistical analysis. In this study, a total of 39 elements contents of sea cucumber from five major production regions in China were determined to evaluate their applicability in the origin traceability of sea cucumber. Pattern recognition techniques including principal component analysis (PCA) and linear discriminate analysis (LDA) were applied to evaluate their performance in terms of classification or predictive ability. Thirty six elements in sea cucumber samples of different regions showed significant differences (p < 0.05), which proved that the elemental composition was an effective tool for distinguishing different origins of sea cucumber. Classification of sea cucumber using PCA did not give satisfactory results. The LDA gave an overall correct classification rate of 94.1% and cross-validation rate of 88.2%. These results demonstrated the usefulness of multi-element fingerprints as indicators for authenticating the geographical origin of sea cucumber in China.

Quality Characterization of Japanese Medicinal Paeoniae Radix by Metallomic Analysis.

Paeoniae Radix is one of the crude drugs frequently used in traditional Japanese medicine (Kampo medicine). It takes abundant labor and time to cultivate Paeonia lactiflora for medicinal use; high production cost is one of the main reasons why the domestic production of Paeoniae Radix is decreasing in Japan. To promote the production of Paeoniae Radix, we focused on Paeonia cultivars that produce commercially valuable flowers and investigated their possibility for medicinal use. We prepared 28 batches of peony roots derived from P. lactiflora, which were cultivated in Japan; 4 batches were crude drug samples, and 24 batches were cultivar roots. The elements contained in these samples were measured using inductively coupled plasma (ICP)-MS. The obtained data were then analyzed by principal component analysis (PCA) and back propagation artificial neural network (BPANN) analysis. No significant differences were found between the profiles of elements contained in crude drugs and cultivar roots. However, PCA results indicated a high similarity of the multielement fingerprints of crude drugs. Using the PCA results, we also assessed visible cluster trends and found that 5 batches of cultivars also showed fingerprints related to those of crude drugs. We certified this classification by BPANN. From the perspective of metallomics, our findings suggest that these 5 batches of Paeonia cultivars could be alternatives to crude drugs.

Using Mineral Elements to Authenticate the Geographical Origin of Yak Meat

Labeling systems for niche market food products is becoming increasingly important to address expectations. Yak meat is green product from natural extensive rangeland on Qinghai-Tibetan plateau. A trace technique is essential for consumers to know the origin of yak meat. In the current study, mineral fingerprints were investigated for their potential to classify yak meat according to geographical origin. The concentration of more than 50 mineral contents in 24 yak meat samples from three regions on Qinghai-Tibetan plateau were analyzed by ICP-MS. Multivariate statistical analyses were used to identify the most relevant indicators of origin. Seven elements (Na, As, Ni, Se, Rb, Cd and Ti) were selected for further routine analyses based on the significant origin differences (P<0.05). The three minerals (Se, Rb, Ti) were selected by statistics analysis and established discriminant model for yak meat traceability. Linear discriminate analysis gave an overall correct classification rate of 91.7% and cross-validation rate of 87.5%. These results demonstrate the usefulness of multi-element fingerprints as indicators for authenticating the geographical origin of yak meat.

The effectiveness of multi‐element fingerprints for identifying the geographical origin of wheat

SummaryTotally 270 wheat samples with ten genotypes of 2010/2011, 2011/2012 and 2012/2013 from three regions were collected, and the multi‐elemental compositions (Mg, Al, Ca, Mn, Fe, Cu, Zn, As, Sr, Mo, Cd, Ba, Pb) were analysed with high‐resolution inductively coupled plasma mass spectrometry (HR‐ICP‐MS). Multiway analysis of variance was employed to investigate the influences of region, genotype, harvest year and their interactions on all elements. The contribution rates of variances were computed, and the results showed that the elements of Mn, Sr, Mo and Cd were closely related to region explaining 34.2%, 39.6%, 35.0% and 78.8% of the total variation, respectively. The genotype contributed most for the variation of Ba, accounting for 27.3%, and the other elements were affected by the harvest year. Mn, Sr, Mo and Cd can be used for establishing the robust discriminant model with the correct classification rate of 98.5% to identify the geographical origin of wheat.

Effects of sediment, seawater, and season on multi-element fingerprints of Manila clam (Ruditapes philippinarum) for authenticity identification

The objective of this study was to select suitable elements which reflect the link with geographical origin while are less affected by season to build robust discriminant models for the protection of Jiaozhou Bay clam by the multi-element fingerprinting technique. Manila clam (Ruditapes philippinarum), sediment, and seawater samples were collected from three major clam producing areas of China (Jiaozhou Bay, Nantong coast, and Dalian coast) in May and September 2014. The concentrations of 25 elements (Na, Mg, Al, etc.) were determined in all the samples. The data obtained was analyzed by analysis of variance, Pearson correlation, a radar plot, and stepwise linear discriminant analysis. The results demonstrated that the models built on five elements (Mg, Cd, Sn, Ba, Ce) are correlated with geographical origin and independent of seasonal variations, and can be used to completely differentiate Jiaozhou Bay clams from the samples from Nantong and Dalian.

Establishment of a methodology for identifying Paeoniae Radix based on metallomic analysis

We aimed to establish a methodology for identifying Paeonia samples based on metallomic analysis. We prepared 66 batches of samples (16 batches of crude drugs and 50 batches of cultivars, comprising 64 batches of Paeonia lactiflora and 2 batches of P. veitchii) collected from Japan and China (Inner Mongolia and elsewhere) between 1996 and 2008. P. lactiflora samples were genetically classified into white peony root (WPR) type and red peony root (RPR) type. Up to 47 elements were measured by inductively coupled plasma-mass spectrometry, and RPR type crude drug samples contained up to five times as much calcium as the others. Principal component analysis (PCA) of the multi-element fingerprints obtained suggested that P. veitchii, which grows wild, were distinguishable from the other cultivated P. lactiflora samples. This was confirmed perfectly by soft independent modeling of class analogy (SIMCA). The PCA of the fingerprints of P. lactiflora crude drug samples also suggested that it was possible to classify them by production area (Japan, Inner Mongolia, and China excluding Inner Mongolia) and genetic type (RPR and WPR types). They were also classified 100 % to the predicted class by SIMCA in both cases. These analyses were successful among the samples whose collection dates varied. This simple metallomic method is an efficient approach for verifying the complex origin of Paeoniae Radix.

Effects of Wheat Origin, Genotype, and Their Interaction on Multielement Fingerprints for Geographical Traceability

The objective of this study was to investigate the effects of origin, genotype, and their interaction on multielement fingerprints in wheat kernels to provide theoretical basis for geographical traceability. Ten varieties were grown in three different regions of China during the 2010-2011 growing seasons. The concentrations of 10 elements (Na, Mg, Ca, V, Mn, Fe, Cu, Zn, Mo, and Ba) were determined in 90 wheat kernel samples and 30 provenance soil samples. Multiway analysis of variance results demonstrated that both origin and genotype had significant influences on the content of each element, and their interaction had significant influences on the contents of Mn, Fe, Cu, Zn, Mo, and Ba. The elements Na, Ca, Fe, Zn, and Mo were associated with origin, and Mg, Mn, Cu, and Ba were related to genotype. Na, Ca, Fe, Zn, and Mo were proved to be good indicators to discriminate wheat geographical origin.

A retail market study of organic and conventional potatoes (Solanum tuberosum): mineral content and nutritional implications

Whether or not all foods marketed to consumers as organic meet specified standards for use of that descriptor, or are nutritionally different from conventional foods, is uncertain. In a retail market study in a Western US metropolitan area, differences in mineral composition between conventional potatoes and those marketed as organic were analysed. Potatoes marketed as organic had more copper and magnesium (p < 0.0001), less iron (p < 0.0001) and sodium (p < 0.02), and the same concentration of calcium, potassium and zinc as conventional potatoes. Comparison of individual mineral concentrations between foodstuffs sold as organic or conventional is unlikely to establish a chemical fingerprint to objectively distinguish between organic and conventional produce, but more sophisticated chemometric analysis of multi-element fingerprints holds promise of doing so. Although statistically significant, these differences would only minimally affect total dietary intake of these minerals and be unlikely to result in measurable health benefits.

Multi-element analysis for determining the geographical origin of mutton from different regions of China

Elemental fingerprints were investigated for their potential to classify mutton samples according to their geographical origin. The concentration of 25 element contents in 99 mutton samples from three pastoral regions and two agricultural regions of China were analysed by ICP-MS. Multivariate statistical analysis including principal component analysis (PCA) and linear discriminate analysis (LDA) were used for this purpose. Twenty-one elements (Be, Na, Al, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Ag, Sb, Ba, Tl, Pb, Th and U) in de-fatted mutton showed significant differences ( p < 0.05). LDA gave an overall correct classification rate of 93.9% and cross-validation rate of 88.9%. Furthermore, mutton samples from agricultural regions and pastoral regions were differentiated with 100% accuracy. These results demonstrate the usefulness of multi-element fingerprints as indicators for authenticating the geographical origin of mutton in China.

Dealing with outliers and censored values in multi-element geochemical data – a visualization approach using XmdvTool

Dealing with geochemical data also means coping with their underlying limitations that are related to sampling, analytical techniques, and other characteristics of the data. This paper discusses the issue of data cleaning, using a regional geochemical dataset of 6 heavy metals in glacial till. Interactive data manipulation techniques provided in the freeware visualization system XmdvTool were used for exploring both metal concentrations reported as under the detection limit, and high or extreme values (outliers) in the dataset. The proposed integrated visual evaluation (IVE) approach for selective removal of outliers outperformed simple removal of the highest concentrations of metals, showing that existing spatial multi-element fingerprints in data could be recognized and preserved by IVE. The uniqueness of visualization is in simultaneous display of both multivariate and spatial information. Being simple and interactive, integrated visual evaluation can be recommended as a valuable complementary tool in cleaning and analysing multi-element geochemical data.

Temporal and spatial variability in elemental composition of otoliths: implications for determining stock identity and connectivity of populations

Interannual variability in elemental composition of otoliths may confound spatial interpretations. The elemental fingerprints of otoliths of juvenile fish were determined for fish collected from 12 to 15 estuaries in each of three consecutive recruitment years to determine temporal variation in otolith chemistry for each estuary. It was also examined whether there is overlap in elemental fingerprints of fish collected in different years and from different estuaries that may confound subsequent spatial comparisons. Significant differences in otolith chemistry were found among years for individual elements (lithium, manganese, strontium, and barium) and for multi-element fingerprints. Some estuaries showed large variation in multi-element fingerprints among years, whereas others showed little variation among years. There was some overlap of elemental fingerprints of different estuaries, but these were not always for fish collected in the same year. The significant spatial and temporal variation in elemental fingerprints meant that it was possible to confound spatial differences with temporal differences. Therefore, if the natal estuary of the adults is to be determined, a library of elemental fingerprints needs to be built up over time for each estuary rather than a single year-class of juveniles being used as the elemental fingerprint for a number of year-classes of adults.