Fingerprinting Approach Research Articles

Analysis of sediment accessibility and availability concepts based on sediment connectivity throughout a watershed

AbstractThe identification of the degree of linkage between sediment source and sink areas and also the channel network allows for prioritizing areas for sediment control measures at the watershed scale. The present study was therefore planned to investigate sediment connectivity based on structural and functional aspects. To that end, the index of connectivity (IC) and sediment delivery ratio (SDR), respectively, were calculated based on the approaches of Borselli, Cassi, & Torri (2008) and a sediment contribution area (SCA) representing structural and functional sediment indices of connectivity. Results showed that high structural connectivity in an area does not necessarily result in high transportation of sediment, since structural connectivity only reflects the potential for sediment transfer between specific source and sink areas. We name this potential movement as sediment accessibility. Meanwhile, high functional sediment connectivity occurs only where soil erosion processes are actively eroding sediment, and consequently we name this condition as sediment availability. Therefore, four sediment connectivity states can occur: (a) sediment availability and sediment accessibility (SASA); (b) sediment availability and sediment inaccessibility (SASIA); (c) sediment unavailability and sediment accessibility (SUASA); and (d) sediment unavailability and sediment inaccessibility (SUASIA). From the application of this concept in the Taham representative watershed in Zanjan Province, Iran, there was a consistency between both structural and functional connectivity in seven subwatersheds within the study area, with one exception with higher sediment availability than sediment accessibility. Such information in combination with a sediment fingerprinting approach assists managers to plan appropriate approaches for achieving the desired sediment (dis)connectivity.

Stable isotope imprint of hypogene speleogenesis: Lessons from Austrian caves

Hypogene speleogenesis involves the formation of solution-enlarged permeability structures driven by ascending water acquiring its acidity from deep-seated sources. This process occurs in a wide range of geological settings and in different lithologies. Although hypogene speleogenesis has received increasing attention in the last two decades, the identification of former hypogene activity in caves remains challenging, unless unambiguous morphological, mineralogical and/or hydrogeological evidence is available. Here, we document that geochemical analyses (mainly stable oxygen and carbon isotopes) of cave wall rock samples may fill this methodological gap and provide a useful tool to identify hypogene karstification through geochemical fingerprinting of water-rock interaction.Stable isotope profiles of a comprehensive set of wall rock cores from eight hypogene caves in Austria in both limestone and dolomite settings were investigated. Alteration halos typically a few centimeters wide and characterized by up to 12‰ and 15‰ depletion in δ13C and δ18O, respectively, were identified in limestone and calcite marble caves. Besides isotopic alteration, bleaching and/or staining of the wall rock was observed due to oxidizing conditions of the paleowater. No isotopic change of the wall rock was identified in hypogene caves carved in dolomite, which may be attributed to low Ca/Mg ratios of the paleowater and/or aggressive fluids leading to fast wall rock retreat. On the other hand, dedolomitization was observed in some wall rocks implying the presence paleowaters with elevated Ca/Mg ratios. Similarly to dolomitic caves, no isotopic alteration front was observed in a cave formed by sulfuric acid speleogenesis. A likely explanation is the high rate of wall rock retreat outpacing the rate of isotope exchange in the wall rock. Our study also shows that water-rock interaction during epigene speleogenesis does not lead to isotopic halos.This geochemical fingerprinting approach offers a powerful tool to test the hypogene origin of caves and may provide additional insights into the temperature and provenance of the paleowater and the source(s) of its dissolved inorganic carbon.

Screening the Q-markers of TCMs from RA rat plasma using UHPLC-QTOF/MS technique for the comprehensive evaluation of Wu-Wei-Wen-Tong Capsule.

The appropriate selection of quality marker (Q-marker) for performing the comprehensive quality evaluation of traditional Chinese medicines (TCMs) has much more significance. Wu-Wei-Wen-Tong Capsule (WWWTC), a TCMs prescription, is mainly utilized to treat rheumatoid arthritis (RA) in China. However, the comprehensive quality control for WWWTC has not been achieved because of lacking system analysis for the Q-marker. In this study, a dual wavelength, 203 and 270 nm, was selected based on the feature of 15 Q-markers, and a reliable UHPLC-UV fingerprinting approach was established, achieving the comprehensive quality evaluation of WWWTC. First, we identified 91 prototypes in rat plasma after administering a set amount of WWWTC by using UHPLC-QTOF/MS technique and selected them as the candidate Q-markers. Next, based on the "five principles" of Q-marker selection, 15 absorbed components among them including coumarin, cinnamic acid, cinnamaldehyde, cinnamic alcohol, and 2-methoxycinnamaldehyde derived from Monarch medicine of Cmnamomi Mmulus; epimedin C, icariin, baohuoside I, and anhydroicaritin derived from Monarch medicine Epimedii Folium; germacrone, the sesquiterpene compound in Minister medicine Rhizoma Wenyujin Concisum; pachymic acid, the tetracyclic triterpenoid acids in Assistant medicine Poria; baicalin, baicalein, wogonin, and wogonoside in Guide medicine Scutellariae Radix, respectively, were seriously chosen as the Q-markers, indicating preferable pharmacological effect on RA, characterization of transitivity and traceability as well as measurable components in WWWTC. The effective and meaningful strategy displayed a unique perspective for the exploration of Q-markers in the quality evaluation and further ensured efficacy and safety of the TCMs.

C‐CNNLoc: Constrained CNN for robust indoor localization with building boundary

To enable accurate and reliable indoor localization in a multi-building environment, a novel constrained convolutional neural network (CNN)-based indoor localization system (C-CNNLoc) is proposed using WiFi fingerprinting approach. The proposed network has a sequential structure that firstly classifies a building, followed by estimating the user's location coordinate within the pre-detected building. Furthermore, the location accuracy is improved by introducing a new loss function that incorporates a penalty term associated with the building boundary. Experimental results illustrate that the proposed method outperforms the existing solutions on the average distance error. The gain comes from that the approach tailored to a multi-building indoor localization with the sequential structure is prone to successfully correct outliers, that is, predicted location coordinates that lie outside the buildings.

Fast in-line bottom-up analysis of monoclonal antibodies: Toward an electrophoretic fingerprinting approach.

For their characterization and quality control, monoclonal antibodies are frequently analyzed at the bottom-up level to generate specific fingerprints that can be used to tackle post-translational modifications or ensure production consistency between lots. To circumvent time-consuming and labor-intensive off-line sample preparation steps, the implementation of integrated methodologies from sample preparation to separation and detection is highly valuable. In this perspective, capillary zone electrophoresis appears as a choice technique since the capillary can subsequently be used as a vessel for sample preparation and electrophoretic discrimination/detection of the reaction products. Here, a fast in-line methodology for the routine quality control of mAbs at the bottom-up level is reported. Simultaneous denaturation and reduction (pretreatment step) were conducted with RapiGest® surfactant and dithiothreitol before in-line tryptic digestion. Reactant mixing was realized by transverse diffusion of laminar flow profile under controlled temperature. In-line digestion was carried out with a resistant trypsin to autolysis. The main parameters affecting the digestion efficiency (trypsin concentration and incubation conditions) were optimized to generate mAb electrophoretic profiles free from trypsin interferences. An acidic MS-compatible BGE was used to obtain high resolution separation of released peptides and in-line surfactant cleavage. The whole methodology was performed in less than two hours with good repeatability of migration times (RSD = 0.91%, n = 5) and corrected peak areas (RSD = 9.6%, n = 5). CE-fingerprints were successfully established for different mAbs and an antibody-drug conjugate.

Forensic analytical approach for hydrocarbon fingerprinting in soil vapor samplings: Example of a residential neighborhood in Brazil

Conventional analytical methods determine the concentration of compounds used to estimate the presence of environmental contamination capable of posing risk to human and ecological receptors. While these target analytes help regulators and environmental professional identify and manage potentially harmful conditions, these compounds can be generated by many natural and anthropogenic (man-made) sources and conventional methods alone fail to compositionally differentiate subsurface sources of contamination in complex environments. This case study demonstrates the advantage of using both conventional and forensic testing methods to accurately identify the source(s) of volatile hydrocarbon contamination in soil vapor samples for the development of an accurate conceptual site model in a neighbourhood near industrial facilities in Rio de Janeiro State, Brazil. The goal of this study was to differentiate potential impacts from a local steelmaking plant from fugitive hydrocarbons associated with more generic human activity in urban settings. This case study demonstrated the advantage of constructing chemical fingerprints from conventional volatile organic compound (VOC) method TO 15 and a forensic volatile hydrocarbon method using an enhanced version of method TO 15 (PIANO). The chemical fingerprints of vapor samples collected from subsurface soil gas and sewers were analysed and compared to laboratory reference samples. These data determined that the VOCs detected in neighbourhood soil vapor samples were associated with fugitive petroleum products migrating in the sewer pipelines and not with the steelmaking wastes emplaced near the residential area. This article discusses the forensic data and chemical signatures that support these findings, and the use of environmental forensic techniques to evaluate environmental data associated with complex scenarios, involving multiple contamination sources.

Stable isotopes of amino acids indicate that soil decomposer microarthropods predominantly feed on saprotrophic fungi

AbstractSoil microarthropods are essential for nutrient cycling in forest ecosystems as they are integral components of decomposer food webs. They channel carbon and nutrients from leaf litter and roots to higher trophic levels; however, knowledge on the relative importance of different channels and on their variation with forest type is lacking. Although the importance of root‐derived inputs for sustaining soil food webs is increasingly recognized, the pathways by which they are channeled to higher trophic levels are little understood. For the channeling, ectomycorrhizal fungi may play a significant role, but until now methods allowing to separate the contribution of ectomycorrhizal and saprotrophic fungi to the nutrition of soil animal communities are lacking. Using dual analysis of 15N and 13C in amino acids (AAs), we investigated trophic positions and basal resources of two major groups of soil microarthropods, Collembola and Oribatida, in beech and spruce forests in Germany. By applying a 13C fingerprinting approach and Bayesian mixing models, we separated in a first step the relative contribution of bacteria, fungi, and plants to the nutrition of soil microarthropods. As fungi were identified as the major food source, in a second step we attempted to separate the contribution of ectomycorrhizal vs. saprotrophic fungi. For the first time, we provide direct evidence that soil microarthropods mainly rely on saprotrophic fungi, whereas ectomycorrhizal fungi are consumed by only few species. While trophic niches of Collembola and Oribatida species generally varied little between beech and spruce forests, plant detritus as basal resource of soil microarthropods was somewhat more important in beech forests, whereas in spruce forests microbial resources dominated. Overall, the dual analysis of carbon and nitrogen in AAs provided insight into food web structure of soil microarthropods in unprecedented detail, and for the first time allowed to estimate the relative importance of mycorrhizal and saprotrophic fungi for soil food web nutrition, a long‐standing riddle in soil food web ecology. The technique provides the perspective for a comprehensive understanding of the trophic structure and energy channeling in soil food webs.

A critical zone observatory dedicated to suspended sediment transport: The meso‐scale Galabre catchment (southern French Alps)

AbstractThe 20 km2 Galabre catchment belongs to the French network of critical zone observatories (OZCAR; Gaillardet et al., Vadose Zone Journal, 2018, 17(1), 1–24). It is representative of the sedimentary lithology and meteorological forcing found in Mediterranean and mountainous areas. Due to the presence of highly erodible and sloping badlands on various lithologies, the site was instrumented in 2007 to understand the dynamics of suspended sediments (SS) in such areas. Two meteorological stations including measurements of air temperature, wind speed and direction, air moisture, rainfall intensity, raindrop size and velocity distribution were installed both in the upper and lower part of the catchment. At the catchment outlet, a gauging station records the water level, temperature and turbidity (10 min time‐step). Stream water samples are collected automatically to estimate SS concentration‐turbidity relationships, allowing quantification of SS fluxes with known uncertainty. The sediment samples are further characterized by measuring their particle size distributions and by applying a low‐cost sediment fingerprinting approach using spectrocolorimetric tracers. Thus, the contributions of badlands located on different lithologies to total SS flux are quantified at a high temporal resolution, providing the opportunity to better analyse the links between meteorological forcing variability and watershed hydrosedimentary response. The set of measurements was extended to the dissolved phase in 2017. Both stream water electrical conductivity and major ion concentrations are measured each week and every 3 h during storm events. This extension of measurements to the dissolved phase will allow progress in understanding both the origin of the water during the events and the partitioning between particulate and dissolved fluxes of solutes in the critical zone. All data sets are available at https://doi.osug.fr/public/DRAIXBLEONE_GAL/index.html.

OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach

In recent years, fingerprint-based positioning has gained researchers’ attention since it is a promising alternative to the Global Navigation Satellite System and cellular network-based localization in urban areas. Despite this, the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions constitutes a high entry barrier for studies. As an effort to overcome this barrier and foster new research efforts, this paper presents OutFin, a novel dataset of outdoor location fingerprints that were collected using two different smartphones. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 reference points. Each site is different in terms of its visibility to the Global Navigation Satellite System and reference points’ number, arrangement, and spacing. Before OutFin was made available to the public, several experiments were conducted to validate its technical quality.

Elucidating intra-storm variations in suspended sediment sources using a Bayesian fingerprinting approach

There is an increasing need for reliable information on the origin of fine-grained sediment transported by river systems, but critically, at temporal scales that reflect the timing and pattern of sediment mobilization and delivery in response to effective precipitation events. Temporal variability is likely to be more pronounced in steep mountainous catchments. Accordingly, the main objective of this study was to investigate the temporal variability of sediment sources during and between flood events, in a mountainous catchment in Iran, using a geochemical fingerprinting approach and Bayesian un-mixing model. Potential sediment sources were classified as either tributary sub-basin spatial end members or individual source types represented by surface soils and channel banks. A total of 34 geochemical elements, elemental ratios and weathering indices were measured as potential tracers on a total of 155 samples, including 40 target samples collected across the hydrographs of four flood events at the overall catchment outlet. Virtual mixture tests, used to compare the computed source estimates with known source mixtures, revealed better fits in the case of spatial, rather than source type apportionment. The Bayesian un-mixing model results revealed pronounced intra-storm variations in the relative contributions from both the spatial sources and source types, but with Quaternary surface soils and channel banks being dominant at different stages of the hydrographs. For all the suspended sediment samples collected throughout the three small to medium size events, the Babazid, middle upstream sub-catchment, was the major (84%–99%) sediment source while for the largest sampled event, suspended sediment samples predominantly (>98%) originated from the Kalkoshan, the most southern sub-catchment. By investigating both spatial sources and source types, temporal variations in the dominant sources were revealed. Quaternary geology and channel banks were identified as the main sediment sources. By combining instantaneous suspended sediment loads through the sampled flood events (across all floods) and using the corresponding source proportions derived from the MixSIR un-mixing model, channel banks and channel bank and surface soils generated 2911 kg and 34,171 kg of suspended sediment, respectively. Whilst the use of spatial source end members is practical in medium-size drainage basins, integration with estimates of sediment source type contributions is more informative to managers in selecting relevant sediment mitigation methods. The intra-storm results underscore the need to manage sediment loss from both surface soils and channel banks.

Differences in New Zealand Hop Cultivars Based on Their Unique Volatile Compounds: An Integrated Fingerprinting and Chemometrics Approach.

Hop aroma characteristics originate from hop essential oils, which have complex chemical profiles that remain poorly understood, particularly for New Zealand hops. The aim of this study was to determine volatile compounds that distinguish New Zealand hop cultivars. Untargeted fingerprinting methods based on headspace gas chromatography mass spectrometry (GC-MS) were used to analyse nine hop cultivars. A total of 61 volatile compounds were identified as compounds that differentiated the commercial hop varieties using advanced chemometrics and feature selection techniques. Similarities in volatile composition were found between Wakatu, Wai-iti™ and Kohatu®, which are rich in alcohols. Another grouping was found between Waimea™ and Nelson Sauvin™, where ketones and esters were commonly found. Rakau™ was distinct from the other eight cultivars, distinguished by 2-methylbutyl 3-methylbutanoate and methanethiol hexanoate. Riwaka™ contained the greatest number of discriminating volatile compounds when compared to other cultivars, which was dominated by terpenoids, such as geranyl 2-methylbutanoate, perillene and D-limonene. The chemical fingerprinting approach successfully identified volatile compounds that had not been previously found in New Zealand hop cultivars and that discriminated the commercial cultivars. The data obtained in the present study further extend the knowledge of New Zealand hops and will help facilitate targeted breeding.

Critical evaluation of ambient mass spectrometry coupled with chemometrics for the early detection of adulteration scenarios in Origanum vulgare L

Nowadays, most of the screening methods in food manufacturing are based on spectroscopic techniques. Ambient Mass Spectrometry is a relatively new field of analytical chemistry which has proven to offer similar speed and ease-of-use when compared to other fingerprinting techniques, alongside the advantages of good selectivity, sensitivity and chemical information. Numerous applications have been explored in food authenticity, based either on the target detection of adulteration markers or, less frequently, on the development of multivariate classification models. The aim of the present work was to evaluate and compare the capabilities of Direct Analysis in Real Time (DART) and Atmospheric Solid Analysis Probe (ASAP) Mass Spectrometry (MS) for the high-throughput authenticity screening of commercial herbs and spices products. The gross addition of bulking material to dried Mediterranean oregano was taken as case study. First, a pilot sample set, constituted by authentic dried oregano, olive leaves (a frequently reported adulterant) and mixtures thereof at different levels (i.e. 10, 20, 30 and 50% w/w) was used. Each sample was fingerprinted by both ambient-MS techniques. After appropriate pre-processing, the whole mass spectra were used for the subsequent multivariate data analysis. Soft Independent Modelling of Class Analogy was adopted as classification algorithm and the model was challenged with both new authentic oregano and in-house prepared blends. To the best of our knowledge, this is the first report of DART-MS and ASAP-MS used in full scan mode and coupled to chemometric modelling as rapid fingerprinting approach for food authentication. Although both the techniques provided satisfactory results, ASAP-MS clearly showed greater potential, leading to reproducible, diagnostic feature-rich mass spectra. For this reason, ASAP-MS was further tested under a more convoluted scenario, where the training and validation sets were enlarged with additional authentic oregano samples and a wider range of adulterant species, respectively. Overall good results were achieved, with 93% model predictive accuracy, and screening detection capability estimated between 5−20% (w/w) addition, depending on the adulterant considered with the only exception of majorana. Investigation of Q residuals could highlight the statistically-relevant chemical markers which could be tentatively annotated by coupling the ASAP probe with a high resolution mass analyser. The results from the validation study confirmed the great potential of ASAP-MS in combination with chemometrics as fast MS-based screening solution and demonstrated its feasibility for classification model building.

Non-targeted fingerprinting approach for rapid quantification of mustard oil adulteration with linseed oil: An economically motivated adulteration

Mustard oil (MO) is a popular edible oil and an essential component of the Indian diet due to its characteristic flavor and pungency. Recently, “Economically motivated adulteration (EMA),” a type of oil fraud, becomes an evolving threat to consumers. In the present work, MO adulteration with Linseed oil (LSO) was analyzed using attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy. Based on spectral information of adulterated samples, exploratory method such as Principal component analysis (PCA) and classification method like Linear discriminant analysis (LDA) were employed that correctly classified adulterated samples, providing an accurate classification of 100 %. Furthermore, quantitative methods like Principal component regression (PCR) and partial least square regression (PLSR) were used to compare raw, first, and second derivatives of three selected optimized spectral regions to obtain the best model. The PLSR model for the first derivative of optimized spectral region II (1800 to 600 cm−1) showed excellent precision and accuracy ability in predicting adulterated samples with high R2 (0.999), RPD (63.42) and low standard error values (RMSECV; 0.216 v/v, RMSEP; 0.167 v/v and RE%; 3.45). Therefore, our results showed that the optimized statistical model has the potential to rapidly detect LSO adulteration in MO as low as 0.5 % v/v.

PhenoGMM: Gaussian Mixture Modeling of Cytometry Data Quantifies Changes in Microbial Community Structure.

Microbial flow cytometry can rapidly characterize the status of microbial communities. Upon measurement, large amounts of quantitative single-cell data are generated, which need to be analyzed appropriately. Cytometric fingerprinting approaches are often used for this purpose. Traditional approaches either require a manual annotation of regions of interest, do not fully consider the multivariate characteristics of the data, or result in many community-describing variables. To address these shortcomings, we propose an automated model-based fingerprinting approach based on Gaussian mixture models, which we call PhenoGMM. The method successfully quantifies changes in microbial community structure based on flow cytometry data, which can be expressed in terms of cytometric diversity. We evaluate the performance of PhenoGMM using data sets from both synthetic and natural ecosystems and compare the method with a generic binning fingerprinting approach. PhenoGMM supports the rapid and quantitative screening of microbial community structure and dynamics.IMPORTANCE Microorganisms are vital components in various ecosystems on Earth. In order to investigate the microbial diversity, researchers have largely relied on the analysis of 16S rRNA gene sequences from DNA. Flow cytometry has been proposed as an alternative technology to characterize microbial community diversity and dynamics. The technology enables a fast measurement of optical properties of individual cells. So-called fingerprinting techniques are needed in order to describe microbial community diversity and dynamics based on flow cytometry data. In this work, we propose a more advanced fingerprinting strategy based on Gaussian mixture models. We evaluated our workflow on data sets from both synthetic and natural ecosystems, illustrating its general applicability for the analysis of microbial flow cytometry data. PhenoGMM supports a rapid and quantitative analysis of microbial community structure using flow cytometry.

Using different size fractions to source fingerprint fine-grained channel bed sediment in a large drainage basin in Iran

Sediment fingerprinting in data sparse regions, such as the mountainous areas of Iran, is more suited to a confluence-based sample design wherein tributary sub-basins are characterised by sediment samples using different size fractions. Our objective was therefore to fingerprint spatial source contributions to the < 37 and 37–63 µm fractions of fine-grained channel bed sediment samples collected in a large erodible mountainous river basin in Iran based on a number of statistical and machine learning approaches. Geochemical elements were measured in channel bed surface drape sediments from seven sub-basins and in delivered sediments from the basin outlet. A Bayesian mass balance model (modified MixSIR) was applied to apportion sub-basin spatial sources with four composite signatures selected using the different statistical approaches. For the < 37 and 37–63 µm fractions, the signatures all indicated that sub-basins 3 (Andajroud; 46.7%) and 7 (Ninehroud; 36.8%) were the dominant spatial sources of the fine-grained bed drape sediment samples, respectively, identifying the most active erosional zones spatially. The statistical error between known and predicted spatial source contributions using virtual mixture tests for both size fractions demonstrated the importance of using multiple different composite fingerprints to decrease the model prediction uncertainties. Despite the difficult terrain in such data sparse areas, the source fingerprinting approach provides a basis for assembling new evidence which, in turn, is of interest to scientists and managers alike.

Adoption of improved cassava varieties in Nigeria: Insights from DNA fingerprinting versus self-reporting varietal identification approaches

Much of the empirical studies on crop varietal adoption in Sub-Saharan Africa relied on self-reported adoption in farm-household surveys, which is prone to measurement errors. In addition, farmers’ perceptions of consumption-related varietal traits in adoption studies has received limited attention compared with production-related traits. Using DNA-based and self-reported adoption measures, we analyze the adoption of improved cassava varieties (ICVs) with a focus on the extent of varietal misidentification, the sensitivity of the drivers of adoption to varietal misidentification and the role of farmers’ perceptions of biofortification trait in adoption decisions. We find that the adoption rate of ICVs is relatively high using both DNA-based and self-reported adoption measures, but there is notable misclassification in varietal adoption. We find that the mismatch in DNA-based and self-reported adoption measures leads to some variation in the factors that influence the likelihood and intensity of adoption of ICVs. This suggests that appropriate varietal identification helps in better understanding of the drivers of adoption. In addition, we find that despite the observed varietal misclassification, farmers’ perceptions of biofortification trait is significantly correlated with the probability and intensity of adoption of ICVs using both DNA-based and self-reported varietal identification. This suggests that inclusion of biofortification trait in cassava matters for both the likelihood and extent of adoption of ICVs. The latter lends credence to the emerging policy interests in breeding programs for biofortified crops to address hidden hunger in Nigeria.

Reactivity of particulate element concentrations: apportionment assessment of suspended particulate matter sources in the Upper Rhône River, France

Suspended particulate matter (SPM) transport through rivers is a major vector of nutrients and pollutants to continental shelf areas. To develop efficient sediment management strategies, there is a need to obtain quantitative information on SPM sources. For many years, the geochemical properties of SPM have been commonly used as tracers to identify sediment sources. In large watersheds, with numerous sources, the expected alteration of tracers during their transport requires that their reactivity be taken into account. To overcome this issue, we tested the use of major and trace element signatures in the residual fraction of SPM, using two different extraction methods. This original fingerprinting approach was applied to the Upper Rhône River basin (~20,000 km2) in order to assess the respective SPM contributions of its main five tributaries (Arve, Ain, Fier, Guiers, and Bourbre Rivers) for contrasted hydrological conditions (base flow periods, flood events and dam flushing). By incorporating element concentrations previously corrected from particle size distribution in a mixing model coupled to Monte Carlo simulations, we estimated the associated uncertainties of the SPM contributions from each tributary. The relative SPM contributions obtained using this fingerprinting approach were compared with those calculated with a 1-D hydro-sedimentary model. The use of element concentrations, such as Zn, P, Cu, Pb, Mn, or Sr, in the total fraction of SPM as conservative fingerprinting properties was not suitable, since they are mainly bound (> 50%) to reactive carrier phases. By using Ba, Ni, Fe, Mg, Cu, Sr, and V concentrations in the SPM residual fraction, the apportionment modeling of SPM sources was successfully assessed. The fingerprinting approach showed that, in base flow conditions, SPM originated mainly from the Arve River. During dam flushing event, the fingerprinting approach consistently estimated that re-suspended sediments came from the Arve River, while the 1-D hydro-sedimentary model estimated a proportion of re-suspended sediment originating within the Rhône River. This original fingerprinting approach highlighted the relevance of using geochemical properties in the non-reactive fraction of SPM in order to obtain reliable information on spatial sources of SPM in a large river basin. This methodology opens up promising perspectives to better track SPM sources in highly reactive environments such as estuaries/delta or in historical sediment archives.

Exploration of the potential of different analytical techniques to authenticate organic vs. conventional olives and olive oils from two varieties using untargeted fingerprinting approaches

Authentication of organic olives and olive oils is of growing interest due to the marked development of organic olive agriculture worldwide. In this study, the potential of using the untargeted volatile fingerprinting of organic and conventional olives obtained with a low-cost and fast methodology based on headspace ultraviolet ion mobility spectrometry (HS-UV-IMS) was investigated for first time. The results showed the suitability of the optimised method since a 94.39% success rate of classification of olives samples was achieved. However, this HS-UV-IMS device did not provide good results for olive oil samples and so two different and more powerful analytical techniques (HS-gas chromatography coupled to IMS with tritium source (HS-GC-IMS) and capillary electrophoresis coupled to UV detector (CE-UV)) were employed respectively to analyse the volatile fingerprinting and the polar compounds extracted from organic and conventional olive oils from two varieties and harvests. It was found that both devices could provide good classification results, above 93.20%, if an adequate number of samples (n > 50) from a single harvest was used. However, it was demonstrated that CE-UV is the best option since it provided more robust classification results over years (95.76%) in comparison with HS-GC-IMS (75.16%). An improvement in classification percentages of HS-GC-IMS data was observed when samples from two harvests were separated into Picual (98.73%) and Hojiblanca (98.78%) variety sets. HS-GC-mass spectrometry with a single quadruple (HS-GC-MS) was employed to contrast the results obtained for the volatile fraction of olive and olive oils with HS-UV-IMS and HS-GC-IMS devices. Also, up to 12 compounds were identified in olive and olive oil samples using HS-GC-MS but only the 3-hexenyl acetate was able to differentiate organic and conventional olive oils.

Channel erosion dominates sediment sources in an agricultural catchment in the Upper Yangtze basin of China: Evidence from geochemical fingerprints

A sediment fingerprinting approach was applied to identify dominant sediment sources in an area where soil conservation measures (i.e. terracing) had been carried out on steep, intensively cultivated lands but the outcome was unknown. The wider purpose was to provide scientific evidence to inform decisions on where erosion control and sediment mitigation strategies could be further targeted. Geochemical fingerprints were used to quantify sediment contributions from three potential sources, i.e. surface soil under cropland and woodland land use, and channel banks, in a managed small catchment in the Upper Yangtze River basin in southwestern China. In parallel, artificial mixtures with known source proportions were evaluated to examine the effects of grain size selection (<125 µm and < 63 µm) on the accuracy of modeled source contributions. Source apportionment results suggest that materials originating from incised and actively eroding channel banks were the most important source of sediment, which contribute over 80% of sediment to the catchment outlet. Sediment inputs from cropland (10–20%) and woodland (<10%) areas as a result of surface erosion were less important, since effective soil conservation measures have been implemented in this catchment. Although apportionment of sampled sediment provided comparable results for both coarser (<125 µm) and fine (<63 µm) size fractions, the artificial mixture results indicated that unmixing the coarse fraction alone could yield poor agreement between modeled source contributions and actual source proportions. The mean absolute error (MAE) for the coarse fraction mixtures ranged between 8.8% and 19.6%, with a mean of 13.6%, compared to the values of 4.0–7.4%, with a mean of 5.2% for the fine fractions. The results of this study highlight that channel bank materials constitute a significant fraction of suspended sediment exports in a heavily managed agricultural catchment, suggesting that future conservation works should be focused on drivers of erosion from this particular source type. Herein, it is surmised that reworking of legacy valley fill deposits is tempering the downstream benefits (e.g. reduced siltation) of recent upslope soil conservation, an important message for policy makers. The findings of this work also emphasize the methodological need to take account of potential uncertainties associate with source apportionments when using specific particle size fractions in fingerprinting studies.

Evaluation of FRET X for Single-Molecule Protein Fingerprinting

Single-molecule protein identification is a novel, as of yet unrealized concept with potentially ground-breaking applications in biological research. We propose a method called FRET X (Forster Resonance Energy Transfer via DNA eXchange) fingerprinting, in which the FRET efficiency is read out between exchangeable dyes on protein-bound DNA docking strands, and accumulated FRET efficiency values constitute the fingerprint for a protein. To evaluate the feasibility of this approach, we simulated fingerprints for hundreds of proteins using a coarse-grained lattice model and experimentally demonstrated FRET X fingerprinting on a system of model peptides. Measured fingerprints are in agreement with our simulations, corroborating the validity of our modeling approach. In a simulated complex mixture of >300 human proteins of which only cysteines, lysines and arginines were labeled, a support vector machine was able to identify constituents with 95% accuracy. We anticipate that our FRET X fingerprinting approach will form the basis of an analysis tool for targeted proteomics.