Intra-regional classification of grape seeds produced in Mendoza province (Argentina) by multi-elemental analysis and chemometrics tools

The feasibility of the application of chemometric techniques associated with multi-element analysis for the classification of grape seeds according to their provenance vineyard soil was investigated. Grape seed samples from different localities of Mendoza province (Argentina) were evaluated. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of twenty-nine elements (Ag, As, Ce, Co, Cs, Cu, Eu, Fe, Ga, Gd, La, Lu, Mn, Mo, Nb, Nd, Ni, Pr, Rb, Sm, Te, Ti, Tl, Tm, U, V, Y, Zn and Zr). Once the analytical data were collected, supervised pattern recognition techniques such as linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), k-nearest neighbors (k-NN), support vector machine (SVM) and Random Forest (RF) were applied to construct classification/discrimination rules. The results indicated that nonlinear methods, RF and SVM, perform best with up to 98% and 93% accuracy rate, respectively, and therefore are excellent tools for classification of grapes.Fil: Canizo, Brenda Vanina. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales. Laboratorio de Química Analítica para Investigación y Desarrollo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Escudero, Leticia Belén. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales. Laboratorio de Química Analítica para Investigación y Desarrollo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Pérez, María Belén. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales. Laboratorio de Química Analítica para Investigación y Desarrollo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Pellerano, Roberto Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Wuilloud, Rodolfo German. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentin

Multielemental analysis in nanoplasmas of isolated particles in an optical trap

Single particle characterization still constitutes a challenge to contemporary chemical analysis. Considerable effort worldwide is being devoted to conceive experimental strategies providing detection capabilities compatible with the extremely low mass of micro- and nano-particles and the ability to determine the chemical composition of the individual entities. The notion of using optical levitation to trap individual particles was demonstrated in the past century. Recently we have proposed the multielemental analysis of individual nanoparticles in optical traps using LIBS. In this lecture, the fundamentals of optical trapping of nanoparticles in air will be presented. The specific excitation and ionization processes leading to efficient optical detection and an analysis of the photon emission efficiency will be discussed. Finally, some limiting factors involved in our approach and prospective directions for improvement will be presented.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Is it really organic? Authenticity testing of organic plant products using elemental and isotopic fingerprinting

The commercial market for high-value plant products is steadily increasing. Consumers are willingly paying premium prices for plants that originate from specific geographical regions or are produced according to certain agricultural management practices. This has significantly enhanced the market shares of organically grown plant products but has simultaneously increased the risk of food adulteration and fraudulent activities. Consequently, sophisticated analytical principles are currently being developed to enable discrimination of organic and conventional plants and ensure compliance with the regulations of organic agriculture. Some of the most promising principles for organic authentication are based on atomic spectroscopy which encompasses several analytical techniques suitable for analysis of the elemental and isotopic composition of plants (1). Analytical discrimination of organic and conventional plant products relies on an expectation of systematic differences in agricultural management practices. Thus, it has been hypothesized that the prohibition of pesticides and synthetically produced fertilizers in organic agriculture is reflected in the chemical composition of plants. This hypothesis was recently tested in a Danish research project called OrgTrace, in which analytical methods for elemental and isotopic fingerprinting were developed and combined with multivariate statistics for authenticity testing of organic crops (2-4). The unique experimental design of OrgTrace included numerous plant species grown either organically or conventionally at several geographical locations differing in soil type, climate etc. Furthermore, year-to-year variation was assessed by inclusion of two growth years. Results from the OrgTrace project will be presented at the seminar. Recently, the international research project AuthenticFood was initiated. In AuthenticFood novel analytical procedures will be tested and combined to enable authentication of selected organic plant products before and after processing of these. The main research hypotheses and methodologies of AuthenticFood will be presented

Classification of cowpea beans using multielemental fingerprinting combined with supervised learning

Multielemental compositions (Ag, As, Ba, Be, Cd, Cs, Co, Cr, Cu, Mo, Ni, Pb, Sb, Se, Sn, Sr, Tl, Rb, V, and Zn) of 106 cowpea bean samples belonging to different varieties collected from the province of Corrientes in Argentina were determined using inductively coupled plasma mass spectrometry (ICP-MS). Based on the multielemental data, five supervised learning techniques, namely, linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), k nearest neighbors (k-NN), random forest (RF), and support vector machine (SVM) with radial basis function Kernel, were computed aiming at building classification models that allow one to predict the botanical variety of the samples based on their element profiles. The best classification performance was obtained by SVM with 93% accuracy rate. The model developed through this method enabled the correct separation of the samples into the five cowpea varieties investigated, where 100% sensitivity was achieved for most of the predicted classes. Thus, SVM was the algorithm selected for the classification of the cowpea beans according to their botanical variety. Multielemental determination coupled with supervised pattern recognition techniques have proved to be an interesting approach for differentiating a diverse range of cowpea genotypes. This study has contributed toward generalizing the use of multielemental fingerprinting as a promising tool for testing the authenticity of cowpea beans on a global scale.Fil: Pérez Rodríguez, Michael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Gaiad, José Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Hidalgo, Melisa Jazmin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Avanza, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Pellerano, Roberto Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentin

LIBS detection of atoms and molecules in nanoplasmas of levitated particles

Single particle characterization still constitutes a challenge to contemporary chemical analysis. Considerable effort worldwide is being devoted to conceive experimental strategies providing detection capabilities compatible with the extremely low mass of micro- and nano-particles and the ability to determine the chemical composition of the individual entities. The notion of using optical levitation to trap individual particles was demonstrated in the past century. Recently we have proposed the multielemental analysis of individual nanoparticles in optical traps using LIBS. In this lecture, the fundamentals of optical trapping of nanoparticles in air will be presented. The specific excitation and ionization processes leading to efficient optical detection and an analysis of the photon emission efficiency will be discussed. Finally, some limiting factors involved in our approach and prospective directions for improvement will be presentedUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Fingerprint analysis of biological samples using ICP-MS and IR-MS

Atomic spectroscopy based analytical techniques can generate fingerprints encompassing the vast majority of elements found in the periodic table as well as ratios of their stable isotopes. These highly multivariate fingerprints have laid the foundation of many recent studies within environmental, geological, agricultural and food science. Inductively coupled plasma-optical emission spectroscopy (ICP-OES) and ICP-mass spectrometry (ICP-MS) still dominate multi-elemental analyses of biological samples while stable isotopes of the light mass elements H, C, N, O and S are measured by isotope ratio-mass spectrometry (IR-MS). However, it has recently been shown that rather unexplored analytical methods such as semi-quantitative ICP-MS and compound-specific isotope analysis (CSIA) can generate novel information suitable for evaluating the authenticity of plant based food products (1-3). Most plant based studies using atomic spectroscopy have focused on the essential nutrients: B, Mg, P, S, K, Ca, Mn, Fe, Ni, Cu, Zn, Mo and selected heavy metals such as Cd and Pb (4). However, plants contain traces of most of the periodic table, which can be measured by semi-quantitative ICP-MS (1-2). This represents a fast method for elemental fingerprinting in the mass range 7Li to 238U, but the accuracy suffers from the simplified calibration procedure that this technique is based on. The combination of semi-quantitative ICP-MS and multivariate statistics (chemometrics) efficiently minimize this problem and constitute a promising tool for authentication of plant products according to their geographical origin and production form (2). Stable isotope analysis complements elemental fingerprinting by targeting specific biological processes and their impact on the isotopic plant composition. This has recently proven valuable for authenticating organically grown plant products – especially when focusing on selected isotope pairs in plant derived compounds such as 18O/16O in NO3- using CSIA (3). Cases of novel atomic spectroscopy based food authentications will be presented at the conference

Using ICP-OES and SEM-EDX in biosorption studies

We have compared the analytical results obtained by inductively coupled plasma optical emission spectroscopy (ICP-OES) and by scanning electron microscopy with an energy dispersive X-ray analytical system (SEM-EDX) in order to explore the mechanism of metal ions biosorption by biomass using two independent methods. The marine macroalga Enteromorpha sp. was enriched with Cu(II), Mn(II), Zn(II), and Co(II) ions via biosorption, and the biosorption capacity of alga determined from the solution and biomass composition before and after biosorption process was compared. The first technique was used to analyze the composition of the natural and metal-loaded biomass, and additionally the composition of the solution before and after biosorption. The second technique was used to obtain a picture of the surface of natural and metal ion-loaded macroalgae, to map the elements on the cell wall of dry biomass, and to determine their concentration before and after biosorption. ICP-OES showed a better precision and lower detection limit than EDX, but SEM-EDX gave more information regarding the sample composition of Enteromorpha sp. Both techniques confirmed that biosorption is a surface phenomenon, in which alkali and alkaline earth metal ions were exchanged by metal ions from aqueous solution

Localized Quantitative Analysis of Polymeric Films through Laser Ablation–Inductively Coupled Plasma Mass Spectrometry

The present work shows, for the first time, the application of laser ablation connected to inductively coupled plasma mass spectrometry (LA-ICP-MS) to the localized quantitative analysis of inclusions in polymeric industrial films. The multielemental mapping capabilities of LA-ICP-MS has allowed to chemically examine unique defects appeared during the plastic processing. This analytical tool is perfectly suited to detect elements such as Al, Mg, Zr, Ti, Cr, P, Pb, Sb, Zn, and Si in those inclusions. A method for multielemental quantitative analysis of these defects has been developed in the present work. The profiling for more than 100 different defects in three samples has demonstrated that more than 50% of these inclusions contain aggregates of some of the aforementioned elements. Therefore, the distribution of elements used as additives or present in catalysts must be carefully controlled during the production of polymeric films in order to avoid degradation in their performance.Funding acquisition M.B. and J.L.T. Authors wish to thank to Total Research and Technology and to the Spanish Ministry of Science, Innovation and Universities for the financial support (project ref. PGC2018-100711-B-I100)

Sexual dimorphism in the multielemental stoichiometric phenotypes and stoichiometric niches of spiders

Nutritional limitations may shape populations and communities of organisms. This phenomenon is often studied by treating populations and communities as pools of homogenous individuals with average nutritional optima and experiencing average constraints and trade-offs that influence their fitness in a standardized way. However, populations and communities consist of individuals belonging to different sexes, each with specific nutritional demands and limitations. Taking this into account, we used the ecological stoichiometry framework to study sexual differences in the stoichiometric phenotypes, reflecting stoichiometric niches, of four spider taxa differing in the hunting mode. The species and sexes differed fundamentally in their elemental phenotypes, including elements beyond those most commonly studied (C, N and P). Both species and sexes were distinguished by the C:N ratio and concentrations of Cu, K and Zn. Species additionally differed in concentrations of Na, Mg and Mn. Phosphorous was not involved in this differentiation. Sexual dimorphism in spiders’ elemental phenotypes, related to differences in their stoichiometric niches, suggests different nutritional optima and differences in nutritional limitation experienced by different sexes and species. This may influence the structure and functioning of spider populations and communities