Characterization of Vegetables by Stable Isotopic and Elemental Signatures

Differentiation of Transylvanian fruit distillates using supervised statistical tools based on isotopic and elemental fingerprint

BACKGROUND

The spirit drinks industry is one of the largest in the world. Fruit distillates require adequate analysis methods combined with statistical tools to build differentiation models, according to distinct criteria (geographical and botanical origin, producer's fingerprint, respectively). Over time a database of alcoholic beverage fingerprints can be generated, being very important for product safety and authenticity control.

RESULTS

To control the distillates' geographical origin, linear discriminant analysis (LDA) revealed that the cross-validation classification was correct for 88.2% of samples, but partial least squares discriminant analysis (PLS-DA) was slightly better suited for this purpose, with a correct classification rate of 91.2%. LDA effectiveness was proven for the trademark fingerprint differentiation, which was achieved at 93.5%, compared to 89.1% for PLS-DA. The principal predictors obtained by LDA were the same both for geographical origin and producer differentiation: B, δ¹³ C, Na, Cu, Ca and Be; highlighting the fact that in the production process of distillates each producer used fruits coming from the respective specific region. Through PLS-DA, some of the discrimination markers were the same for geographical origin and producer's identification, but others were completely specific: the rare earth elements Eu and Er only for geographical origin differentiation, and Cu solely as predictor for producer's identification. Regarding distillates' fruit variety, the correct discrimination rates of plum spirits from the rest were 84.2% for PLS-DA and 63% for LDA.

CONCLUSION

LDA and PLS-DA were suitable for differentiation models development of fruits spirits according to geographical region, producer and fruit variety based on isotopic and elemental fingerprint. © 2022 Society of Chemical Industry.

Isotopic and elemental characterization of Romanian pork meat in corroboration with advanced chemometric methods: A first exploratory study

In this study 93 pork meat samples (tenderloin) were analyzed via isotope ratios mass spectrometry (δ2H, δ18O, δ13C) and inductively coupled plasma - Mass spectrometry (55 elements). The meat samples are coming from Romania and abroad. Those from Romania are originating from conventional farms and yard rearing system. The analytical results in conjunction with linear discriminant analysis (LDA) and artificial neural networks (ANNs) were used to assess: The geographical origin, and animal diet. The most powerful markers which could differentiate pork meat samples concerning the geographical origin were δ18O, terbium, and tin. The results of chemometric models showed that, along with 13C signature, rubidium concentration, and a few rare earth-elements (lanthanum, and cerium) were efficient to discriminate animal diet in a percent of 97.8% (initial classification) and 94.6% (cross-validation), respectively. Some of predictors for feeding regime differentiation by using LDA were identified also to be the best markers to distinguish corn-based diet by using ANNs (δ13C, Rb, La).

Isotope chemometrics determines farming methods and geographical origin of vegetables from Yangtze River Delta Region, China

Shanghai city has encountered possible food fraud regarding the geographical mislabeling of vegetables for economic gain. A combination of δ¹³C, δ¹⁵N, δ²H and δ¹⁸O values and partial least squares discrimination analysis and support vector machine (SVM) methods were used for the first time to assess farming methods and determine the origin of vegetables from Shanghai city, Anhui and Zhejiang provinces. The results showed that 65.8% of Shanghai vegetables, 38.2% of Anhui vegetables and 23.6% of Zhejiang vegetables appeared to be grown using green or organic farming methods. The optimal discriminant model was obtained using SVM with a predictive accuracy of 100% for Shanghai vegetables. Zhejiang vegetables had a predictive accuracy of 91.7%, while it was difficult to distinguish Anhui vegetables from Shanghai or Zhejiang vegetables. Therefore, this study provided a useful method to identify vegetable farming methods and discriminate vegetables from Shanghai and Zhejiang.

Applications of emerging stable isotopes and elemental markers for geographical and varietal recognition of Romanian and French honeys

The research towards the identification of new authenticity markers is crucial to fight against fraudulent activities on honey, one of the top ten most falsified food commodities. This work proposes an association of stable isotopes and elemental content as markers for honey authentication, with respect to its floral and geographical origin. Emerging markers like isotopic signature of honey water alongside with carbon and hydrogen isotopic ratios of ethanol obtained from honey fermentation and Rare Earth Elements, were used to develop new recognition models. Thus, the efficiency of the discrimination potential of these emerging markers was discussed individually and in association. This approach proved its effectiveness for geographical differentiation (>98%) and the role of the emerging markers in these classifications was an essential one, especially of: (D/H)_I, δ²H, δ¹⁸O, La, Ce and Pr. Floral recognition was realized in a lower percentage revealing the suitability of these markers mainly for geographical classification.

Differentiation of tomatoes based on isotopic, elemental and organic markers

In this study, 41 tomato samples were investigated by means of stable isotope ratios (δ¹³C, δ¹⁸O and δ²H), elemental content, phenolic compounds and pesticides in order to classify them, according to growing conditions and geographical origin. Using investigated parameters, stepwise linear discriminant analysis was applied and the differences that occurred between tomato samples grown in greenhouses compared to those grown on field, and also between Romanian and abroad purchased samples were pointed out. It was shown that Ti, Ga, Te, δ²H and δ¹³C content were able to differentiate Romanian tomato samples from foreign samples, whereas Al, Sc, Se, Dy, Pb, δ¹⁸O, 4,4'-DDT could be used as markers for growing regime (open field vs. greenhouse). For the discrimination of different tomato varieties (six cherry samples and fourteen common sorts) grown in greenhouse, phenolic compounds of 20 samples were determined. In this regard, dihydroquercetin, caffeic acid, chlorogenic acid, rutin, rosmarinic acid, quercetin and naringin were the major phenolic compounds detected in our samples. The phenolic profile showed significant differences between cherry tomato and common tomato. The contents of the chlorogenic acid and rutin were significantly higher in the cherry samples (90.27-243.00 µg/g DW and 160.60-433.99 µg/g DW respectively) as compared to common tomatoes (21.30-88.72 µg/g DW and 24.84-110.99 µg/g DW respectively). The identification of dihydroquercetin is of particular interest, as it had not been reported previously in tomato fruit.

Traceability of fruits and vegetables

Food safety and traceability are nowadays a constant concern for consumers, and indeed for all actors in the food chain, including those involved in the fruit and vegetable sector. For the EU, the principles and legal requirements of traceability are set out in Regulation 178/2002. Currently however the regulation does not describe any analytical traceability tools. Furthermore, traceability systems for fruits and vegetables face increasing competition due to market globalization. The current challenge for actors in this sector is therefore to be sufficiently competitive in terms of price, traceability, quality and safety to avoid scandal and fraud. For all these reasons, new, flexible, cheap and efficient traceability tools, as isotopic analysis, DNA fingerprinting and metabolomic profiling coupled with chemometrics are needed.

Isotopic and elemental profiling alongside with chemometric methods for vegetable differentiation

In this study, three chemometric models for vegetables growing system (field versus greenhouse), geographical origin and species attribution using stable isotope (δ¹³C, δ¹⁸O, δ²H) and elemental fingerprints of 101 samples (54 squashes and 47 radishes) commercialized on Romanian market were developed. These models were constructed and validated through linear discriminant analysis. Initial validations of 94.4% and 83% were obtained for squash and radish growing systems, respectively, such that one squash and four radish samples declared to be grown in the field were attributed to the greenhouse group. For this purpose, the most powerful differentiation markers appeared to be Sn and δ¹³C for radishes, and Sn, Cu for squashes. Regarding the vegetable origin, four samples, initially considered to originate from Romania (95% for initial classification) were attributed to the foreign group in the cross-validation procedure (93.1%). Romanian radishes and squashes were characterized by a higher content of Na and Cu, respectively, compared with foreign samples, while the mean values for Zn, Sr, Zr and Co concentrations were found to be higher for the vegetables from abroad.

Bulk and compound-specific stable isotope ratio analysis for authenticity testing of organically grown tomatoes

Until now, there has been a lack of analytical methods that can reliably verify the authenticity of organically grown plants and derived organic food products. In this study, stable isotope ratio analysis of hydrogen (H, δ²H), carbon (C, δ¹³C), nitrogen (N, δ¹⁵N), oxygen (O, δ¹⁸O) and sulfur (S, δ³⁴S) was conducted along the tomato passata production process using organic and conventionally grown tomatoes from two Italian regions over two years. A gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) based method was developed and applied for analysis of C and N isotope ratios in amino acids derived from tomatoes. Of the bulk isotope ratios, δ¹⁵N was the most significant parameter for discriminating organic from conventional products. The classification power was improved significantly by compound-specific isotope analysis regardless of the production years and regions. We conclude that isotope analysis of amino acids is a novel analytical tool for complementing existing certification and control procedures in the organic tomato sector.