Analysis of Conventional and Biodegradable Microplastics in Solid Sample Matrices: A Contribution to Method Standardization

Microplastics are the new emerging pollutants ubiquitously detectable in aquatic and terrestrial ecosystems. Fate and behavior as well as ecotoxicity are of increasing environmental concern particularly in sediments and soils as natural sinks. For a global environmental risk assessment reliable and easy to apply analytical methods are mandatory to obtain comparable data. This is based on the isolation of microplastics out of the solid sample matrices prior to instrumental detection. Thus, this study provides a validated approach for density separation, which emerged from a comparative study using different salt solutions to isolate conventional and for the first time biodegradable microplastics from different solid sample matrices, i.e., sand, artificial soil, and compost. Four solutions (water, sodium chloride, sodium hexametaphosphate and sodium bromide) of different densities were applied followed by oxidizing digestion. Finally, the impact of the procedures on size and surface properties of microplastics was tested. Dependent on the sample matrix, highest recovery rates of 87.3-100.3 % for conventional polymers and 38.2–78.2 % for biodegradable polymers were determined with sodium bromide. It could be shown that the type of solid sample matrix influences the recovery rates and has to be considered when choosing a sample preparation technique.

Assessing Multiplex Tiling PCR Sequencing Approaches for Detecting Genomic Variants of SARS-CoV-2 in Municipal Wastewater

Monitoring the genomic characteristics of the SARS-CoV-2 virus circulating in a population can shed important insights into epidemiological aspects of the COVID-19 outbreak. Sequencing every clinical patient sample in a highly populous area is a difficult feat, and thus sequencing SARS-CoV-2 RNA in municipal wastewater offers great promise to augment genomic surveillance by characterizing a pooled population sample matrix, particularly during an escalating outbreak.

Targeted analysis of phenolic compounds by LC-MS v1

Cell-wall-bound (CWB) aromatics such as ferulate and p-coumarate play important physiological roles in plant development and response to stresses. Their presence also poses some challenges and opportunities during processing of plant biomass in various agro-industrial applications. To this end, we have developed a robust high-throughput reversed-phase liquid chromatography mass spectrometry method for quantifying CWB phenolic compounds. The method showed excellent linearity (R2 = ≥0.999) and intraday retention time repeatability (≤ 0.31 %RSD) for ferulate and p-coumarate. The limits of detection and quantitation for these analytes were ≤ 39 nM and 130 nM, respectively. Furthermore, there was very little effect of the CWB sample matrix on the retention times of the analytes and analyte percent recoveries from the CWB sample matrix was ≥83.91%.

Full Workflows for the Analysis of Gas Chromatography—Ion Mobility Spectrometry in Foodomics: Application to the Analysis of Iberian Ham Aroma

Gas chromatography—ion mobility spectrometry (GC-IMS) allows the fast, reliable, and inexpensive chemical composition analysis of volatile mixtures. This sensing technology has been successfully employed in food science to determine food origin, freshness and preventing alimentary fraud. However, GC-IMS data is highly dimensional, complex, and suffers from strong non-linearities, baseline problems, misalignments, peak overlaps, long peak tails, etc., all of which must be corrected to properly extract the relevant features from samples. In this work, a pipeline for signal pre-processing, followed by four different approaches for feature extraction in GC-IMS data, is presented. More precisely, these approaches consist of extracting data features from: (1) the total area of the reactant ion peak chromatogram (RIC); (2) the full RIC response; (3) the unfolded sample matrix; and (4) the ion peak volumes. The resulting pipelines for data processing were applied to a dataset consisting of two different quality class Iberian ham samples, based on their feeding regime. The ability to infer chemical information from samples was tested by comparing the classification results obtained from partial least-squares discriminant analysis (PLS-DA) and the samples’ variable importance for projection (VIP) scores. The choice of a feature extraction strategy is a trade-off between the amount of chemical information that is preserved, and the computational effort required to generate the data models.

Study on the removal of interferences for the determination of ⁸⁷Sr/⁸⁶Sr isotopic ratio in petroleum drill-hole water samples using isotope dilution – inductively coupled plasma mass spectrometry (ID – ICP-MS)

87Sr/86Sr isotopic ratio is one of the useful tools that can authenticate the original source of the natural products from the earth-created and/or geological processes. However, the effect of interferences in petroleum drill-holes water sample such as thickness of sample matrix or isotopic signal of 87Rb might cause the low precision of 87Sr/86Sr determination using quadrupole inductively coupled plasma spectrometry (ICP-MS). The elimination of these mentioned effects was thus studied by using the ion - exchange chromatography. Calcium in sample matrix was separated on anionite column (Bio-Rad AG1-X8 resin) in methanol medium with the high efficiency while rubidium wasremoved from strontium on cation exchange resin (Bio-Rad AG50-X8) with strontium recovery over 99%. The isotope dilution technique with 86Sr - enriched isotopic standard solution was used for the control of separation process. The 87Sr/86Sr isotopic ratio was thus determined using ICP-MS with the signal correction by a strontium isotopic ratio standard reference material (NIST SRM 987).

Influence of Sample Matrix on Determination of Histamine in Fish by Surface Enhanced Raman Spectroscopy Coupled with Chemometric Modelling

Histamine fish poisoning is a foodborne illness caused by the consumption of fish products with high histamine content. Although intoxication mechanisms and control strategies are well known, it remains by far the most common cause of seafood-related health problems. Since conventional methods for histamine testing are difficult to implement in high-throughput quality control laboratories, simple and rapid methods for histamine testing are needed to ensure the safety of seafood products in global trade. In this work, the previously developed SERS method for the determination of histamine was tested to determine the influence of matrix effect on the performance of the method and to investigate the ability of different chemometric tools to overcome matrix effect issues. Experiments were performed on bluefin tuna (Thunnus thynnus) and bonito (Sarda sarda) samples exposed to varying levels of microbial activity. Spectral analysis confirmed the significant effect of sample matrix, related to different fish species, as well as the extent of microbial activity on the predictive ability of PLSR models with R2 of best model ranging from 0.722–0.945. Models obtained by ANN processing of factors derived by PCA from the raw spectra of the samples showed excellent prediction of histamine, regardless of fish species and extent of microbial activity (R2 of validation > 0.99).

Quantification of Fructans in Bioethanol Stillage Based On a Simplified Analytical Method

Bioethanol stillage, the main by-product of industrial bioethanol production, is a potential substrate for fructans. However, the determination and quantification of fructans in such complex sample matrices is still a challenge for the corresponding analytics to be overcome in order to allow for the identification and utilisation of such unused fructan sources. Especially a possible utilisation or rather the corresponding process development requires appropriate analytics first. Thus, this paper aims to illuminate the basics of fructan quantification in stillage and the corresponding challenges particularly arising with widely used HPLC-RID systems. On this basis, a new approach for fructan quantification is presented based on such HPLC-RID systems allowing for a reliable and especially simple fructan determination in bioethanol stillage for comparably high sample throughput. The developed method performs fructan quantification by determination of fructose and glucose equivalents after a targeted acidic hydrolysis adapted to the respective sample matrix. By means of two different stationary phases, the problem of limited resolution in case of HPLC-RID is overcome and thus measurement errors are reduced. The approach towards the adapted analytical method can be transferred easily to comparable complex sample matrices.