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

Explainable machine learning for predicting the geographical origin of Chinese Oysters via mineral elements analysis

The traceability of geographic origin is essential for guaranteeing the quality, safety, and protection of oyster brands. However, the current outcomes of traceability lack credibility as they do not adequately explain the model's predictions. Consequently, we conducted a study to evaluate the efficacy of utilizing explainable machine learning combined with mineral elements analysis. The study findings revealed that 18 elements have the ability to determine regional orientation. Simultaneously, individuals should pay closer attention to the potential risks associated with oyster consumption due to the regional differences in essential and toxic elements they contain. Light gradient boosting machine (LightGBM) model exhibited indistinguishable performance, achieving flawless accuracy, precision, recall, F1 score and AUC, with values of 96.77%, 96.43%, 98.53%, 97.32% and 0.998, respectively. The SHapley Additive exPlanations (SHAP) method was used to evaluate the output of the LightGBM model, revealing differences in feature interactions among oysters from different provinces. Specifically, the features Na, Zn, V, Mg, and K were found to have a significant impact on the predictive process of the model. Consistent with existing research, the use of explainable machine learning techniques can provide insights into the complex connections between important product attributes and relevant geographical information.

Seasonal variations of heavy metals in seawater and integrated poly-cultured scallop Chlamys farreri in Ailian Bay, northern China

Seasonal variations of heavy metals in integrated poly-cultured scallops and seawater from Ailian Bay, northern China were analyzed to reveal the potential factor in bioaccumulation of metals in scallop Chlamys farreri. Results showed that heavy metals (Cu, Zn, As, Cd, Cr, Pb and Hg) in seawater were much below the maximum permissible limits and showed no seasonal changes, but were consistent with the growing period of the poly-cultivated kelp. The content of Zn in scallop tissues was highest with an average value of 88.35 ± 11.50 mg/kg, and Hg content was lowest (0.046 ± 0.025 mg/kg). The accumulation of Cu, As, Cd and Hg in scallops presented a significant seasonal change, and they were closely correlated with the physicochemical quality instead of heavy metals in seawater. Cadmium provided 88.9 % of the total hazard index for adults and 72.2 % for children. Arsenic should also be paid more attention in the risk assessment of human health.

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), a Useful Tool in Authenticity of Agricultural Products' and Foods' Origin

Fraudulent practices are the first and foremost concern of food industry, with significant consequences in economy and human's health. The increasing demand for food has led to food fraud by replacing, mixing, blending, and mislabeling products attempting to increase the profits of producers and companies. Consequently, there was the rise of a multidisciplinary field which encompasses a large number of analytical techniques aiming to trace and authenticate the origins of agricultural products, food and beverages. Among the analytical strategies have been developed for the authentication of geographical origin of foodstuff, Inductively Coupled Plasma Mass Spectrometry (ICP-MS) increasingly dominates the field as a robust, accurate, and highly sensitive technique for determining the inorganic elements in food substances. Inorganic elements are well known for evaluating the nutritional composition of food products while it has been shown that they are considered as possible tracers for authenticating the geographical origin. This is based on the fact that the inorganic component of identical food type originating from different territories varies due to the diversity of matrix composition. The present systematic literature review focusing on gathering the research has been done up-to-date on authenticating the geographical origin of agricultural products and foods by utilizing the ICP-MS technique. The first part of the article is a tutorial about food safety/control and the fundaments of ICP-MS technique, while in the second part the total research review is discussed.

The Pattern of Rare Earth Elements Like a Possible Helpful Tool in Traceability and Geographical Characterization of the Soil-Olive System (Olea europaea L.)

The identification of a product, with its geographical origin, is a guaranty of the value of the foodstuff and protection from potential fraud. Extra virgin olive oil is produced or marketed as a single variety or a blend of two or more cultivars, often of different geographic origins. Therefore, to study a possible link between the soil and olive oil, we accounted crucial to analyse the behaviour of olive of different cultivars. We studied Rare Earth Elements (REE) amounts and their relationship to trace their distribution from soil to the olive pulp (Olea europea L.). The results obtained pointed out that the different cultivars of Olea did not drive significant differences in reciprocal ratios of REE in the uptake from the soil up to olive (except for Eu). However soil-plant Rare Earth relationships depend exclusively on the soil REE composition. This method can be the starting point to enforcing the laws, in fact, it is important to develop analytical methods to measure the authenticity of the samples, and to verify the geographical origin even when olive oil is blended.

Intra-regional classification of Codonopsis Radix produced in Gansu province (China) by multi-elemental analysis and chemometric tools

Multi-elemental analysis is widely used to identify the geographical origins of plants. The purpose of this study was to explore the feasibility of combining chemometrics with multi-element analysis for classification of Codonopsis Radix from different producing regions of Gansu province (China). A total of 117 Codonopsis Radix samples from 7 counties of Gansu province were collected. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of 28 elements (³⁹ K, ²⁴ Mg, ⁴⁴Ca, ²⁷Al, ¹³⁷Ba, ⁵⁷Fe, ²³Na, ⁸⁸Sr, ⁵⁵Mn, ⁶⁶Zn, ⁶⁵Cu, ⁸⁵Rb, ⁶¹Ni, ⁵³Cr, ⁵¹ V, ⁷Li, ²⁰⁸Pb, ⁵⁹Co, ⁷⁵As, ¹³³Cs, ⁷¹ Ga, ⁷⁷Se, ²⁰⁵Tl, ¹¹⁴Cd, ²³⁸U, ¹⁰⁷Ag, ⁴Be and ²⁰²Hg). Among macro elements, ³⁹ K showed the highest level, whereas ²³Na was found to have the lowest content value. Micro elements showed the concentrations order of: ⁸⁸Sr > ⁵⁵Mn > ⁶⁶Zn > ⁸⁵Rb > ⁶⁵Cu. Among trace elements, ⁵³Cr and ⁶¹Ni showed higher content and ⁴Be was not detected in all samples. Intra-regions differentiation was performed by principal component analysis (PCA), cluster analysis (CA) and supervised learning algorithms such as linear discriminant analysis (LDA), k-nearest neighbors (k-NN), support vector machines (SVM), and random forests (RF). Among them, the RF model performed the best with an accuracy rate of 78.79%. Multi-elemental analysis combined with RF was a reliable method to identify the origins of Codonopsis Radix in Gansu province.

Multi-element signature of cuttlefish and its potential for the discrimination of different geographical provenances and traceability

The measurement and analysis of fifty-two elements by quadrupole inductively coupled plasma mass spectrometry (Q-ICP-MS) and direct mercury analysis were applied to origin discrimination of Italian traditional cuttlefish (Chioggia, Venice lagoon) from Mediterranean and Atlantic samples. A total 68 specimens were analyzed in triplicates to generate 204 mass spectra profiles which were statistically processed by different chemometric techniques. Loading weights from principal component analysis as input for linear discriminant analysis (LW-LDA), stepwise-LDA (S-LDA) and variable influence of projection-partial least square discriminant analysis (VIP-PLS-DA) were used to classify samples while retaining the lowest possible number of key variables. VIP-PLS-DA was found to be the best variable selection-discriminant tool combo since the selected Na-Co-B-K-Cd-V-U-Rb-Ni-Ba-Cu-As-Sr-Mn-Mo-Li-Ca-Mg-Se-Bi-Cs-P-Y elemental pattern allowed the samples to be classified with 100% sensitivity, specificity and accuracy.

Advances in Troubleshooting Fish and Seafood Authentication by Inorganic Elemental Composition

The demand for fish and seafood is growing worldwide. Meanwhile, problems related to the integrity and safety of the fishery sector are increasing, leading legislators, producers, and consumers to search for ways to effectively protect themselves from fraud and health hazards related to fish consumption. What is urgently required now is the availability of reliable, truthful, and reproducible methods assuring the correspondence between the real nature of the product and label declarations accompanying the same product during its market life. The evaluation of the inorganic composition of fish and seafood appears to be one of the most promising strategies to be exploited in the near future to assist routine and official monitoring operations along the supply chain. The present review article focuses on exploring the latest scientific achievements of using the multi-elemental composition of fish and seafood as an imprint of their authenticity and traceability, especially with regards to the geographical origin. The scientific literature of the last 10 years focusing on the analytical determination and statistical elaboration of elemental data (alone or in combination with methodologies targeting other compounds) to verify the identity of fishery products is summarized and discussed.

Hyperaccumulation of cadmium by scallop Chlamys farreri revealed by comparative transcriptome analysis

Cadmium (Cd) is a hazardous environmental contaminant, which has a serious effect on the ecosystem, food safety and human health. Scallop could accumulate high concentration of Cd from the environment and has been regarded as a Cd hyper-accumulator. In this work, we investigated the antioxidative defense, detoxification and transport of Cd in the kidneys of scallops by transcriptome analysis. A total of 598 differentially expressed genes including 387 up-regulated and 211 down-regulated ones were obtained during Cd exposure, and 46 up-regulated and 260 down-regulated ones were obtained during depuration. Cadmium exposure could cause oxidative stress in the kidneys, which was particularly shown in the pathways involved in proteasome and oxidative phosphorylation. The mRNA expression of 5 metallothionein (MT) genes were overexpressed under Cd exposure and significantly decreased during Cd depuration, which played a vital role in Cd chelation and detoxification. The expression of divalent metal transporter (DMT) genes were down-regulated insignificantly during accumulation and depuration of Cd, which suggested that the DMT played little roles in Cd transport in scallops. A positive relationship in the expression of the zinc transporter (ZIP6 and ZIP1) genes with Cd exposure and depuration was observed, which confirmed its important role for Cd uptake in the kidneys of scallops. 26S proteasome activities and MT expression were Cd-dependent. This study supplied the important reference on the hyperaccumulation of Cd by scallops and identified some effective bioindicators for the environmental risk assessment.

Use of mineral multi-elemental analysis to authenticate geographical origin of different cultivars of tea in Guizhou, China

BACKGROUND

The geographical origin of tea (Camellia sinensis) can be traced using mineral elements in its leaves as fingerprints. However, the role that could be played by soil mineral elements in the geographical authentication of tea leaves has been unclear. In this study, 22 mineral elements in 73 pairs of tea leaves and soils from three regions (Pu'an, Duyun, and Liping) in Guizhou, China, were determined using inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectrometry (ICP-AES). The mineral element concentrations were processed by multivariate statistical analysis, including one-way analysis of variance (ANOVA), correlation analysis, principal component analysis (PCA), and stepwise linear discriminant analysis (S-LDA).

RESULTS

Based on a one-way ANOVA, tea leaves and soils with different origins possessed unique mineral element fingerprints. Sixteen mineral element concentrations in tea leaves were significantly correlated with those in soils (P < 0.05). The geographical origins of tea leaves were effectively differentiated using the 16 correlated mineral elements combined with PCA. The S-LDA model offered a 100% differentiation rate, and six indicative elements (phosphorus, Sr, U, Pb, Cd, and Cr) were selected as important fingerprinting markers for the geographic traceability of tea leaves. The accurate discrimination rate of geographical origin was unaffected by the cultivars of tea in the S-LDA model.

CONCLUSIONS

Mineral elements in soils played an important role in the geographical authentication of tea leaves. Mineral elemental concentrations with significant correlations between tea leaves and soils could be robust, and could be used to trace the geographical origins of tea leaves. © 2020 Society of Chemical Industry.