Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Fast and nondestructive method for leaf level chlorophyll estimation using hyperspectral LiDAR
    Nevalainen, O. ; Hakala, T. ; Suomalainen, J.M. ; Mäkipää, R. ; Peltoniemi, M. ; Krooks, A. ; Kaasalainen, S. - \ 2014
    Agricultural and Forest Meteorology 198-199 (2014). - ISSN 0168-1923 - p. 250 - 258.
    supercontinuum laser source - vegetation indexes - reflectance spectra - precision agriculture - canopy reflectance - red edge - airborne - model - spectroscopy - validation
    We propose an empirical method for nondestructive estimation of chlorophyll in tree canopies. The first prototype of a full waveform hyperspectral LiDAR instrument has been developed by the Finnish Geodetic Institute (FGI). The instrument efficiently combines the benefits of passive and active remote sensing sensors. It is able to produce 3D point clouds with spectral information included for every point, which offers great potential in the field of environmental remote sensing. The investigation was conducted by using chlorophyll sensitive vegetation indices applied to hyperspectral LiDAR data and testing their performance in chlorophyll estimation. The amount of chlorophyll in vegetation is an important indicator of photosynthetic capacity and stress, and thus important for monitoring of forest condition and carbon sequestration on Earth. Performance of chlorophyll estimation was evaluated for 27 published vegetation indices applied to waveform LiDAR collected from ten Scots pine shoots. Reference data were collected by laboratory chlorophyll concentration analysis. The performance of the indices in chlorophyll estimation was determined by linear regression and leave-one-out cross-validation. The chlorophyll estimates derived from hyperspectral LiDAR linearly correlate with the laboratory analyzed chlorophyll concentrations, and they are able to represent a range of chlorophyll concentrations in Scots pine shoots (R2 = 0.88, RMSE = 0.10 mg/g). Furthermore, they are insensitive to measurement scale as nearly the same values of vegetation indices were measured in natural setting while scanning the whole canopy and from clipped shoots re-measured with hyperspectral LiDAR in laboratory. The results indicate that the hyperspectral LiDAR instrument has the potential to estimate vegetation biochemical parameters such as the chlorophyll concentration. The instrument holds much potential in various environmental applications and provides a significant improvement over single wavelength LiDAR or passive optical systems for environmental remote sensing.
    Genomic prediction based on data from three layer lines using non-linear regression models
    Huang, H. ; Windig, J.J. ; Vereijken, A. ; Calus, M.P.L. - \ 2014
    Genetics, Selection, Evolution 46 (2014). - ISSN 0999-193X - 11 p.
    dairy-cattle breeds - dimensionality reduction - gaussian kernel - accuracy - traits - values - validation - selection - pedigree - plant
    Background - Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. Methods - In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. Results - When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Conclusions - Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional occurrence of large negative accuracies when the evaluated line was not included in the training dataset. Furthermore, when using a multi-line training dataset, non-linear models provided information on the genotype data that was complementary to the linear models, which indicates that the underlying data distributions of the three studied lines were indeed heterogeneous.
    Fusion of pan-tropical biomass maps using weighted averaging and regional calibration data
    Ge, Y. ; Avitabile, V. ; Heuvelink, G.B.M. ; Wang, J. ; Herold, M. - \ 2014
    International Journal of applied Earth Observation and Geoinformation 31 (2014). - ISSN 0303-2434 - p. 13 - 24.
    remotely-sensed imagery - land-cover datasets - multisensor data - forest biomass - carbon-dioxide - sensing data - soil maps - classification - deforestation - validation
    Biomass is a key environmental variable that influences many biosphere–atmosphere interactions. Recently, a number of biomass maps at national, regional and global scales have been produced using different approaches with a variety of input data, such as from field observations, remotely sensed imagery and other spatial datasets. However, the accuracy of these maps varies regionally and is largely unknown. This research proposes a fusion method to increase the accuracy of regional biomass estimates by using higher-quality calibration data. In this fusion method, the biases in the source maps were first adjusted to correct for over- and underestimation by comparison with the calibration data. Next, the biomass maps were combined linearly using weights derived from the variance–covariance matrix associated with the accuracies of the source maps. Because each map may have different biases and accuracies for different land use types, the biases and fusion weights were computed for each of the main land cover types separately. The conceptual arguments are substantiated by a case study conducted in East Africa. Evaluation analysis shows that fusing multiple source biomass maps may produce a more accurate map than when only one biomass map or unweighted averaging is used.
    Nutrient-rich foods, cardiovascular diseases and all-cause mortality: the Rotterdam study
    Streppel, M.T. ; Sluik, D. ; Yperen, J. van; Geelen, A. ; Hofman, A. ; Franco, O.H. ; Witteman, J.C.M. ; Feskens, E.J.M. - \ 2014
    European Journal of Clinical Nutrition 68 (2014). - ISSN 0954-3007 - p. 741 - 747.
    nutritional quality index - physical-activity - dietary pattern - elderly-people - women - risk - questionnaire - validation - cohort
    Background/Objectives: The nutrient-rich food (NRF) index assesses nutrient quality of individual food items by ranking them according to their nutrient composition. The index reflects the nutrient density of the overall diet. We examined the associations between the NRF9.3 index—a score on the basis of nine beneficial nutrients (protein, fiber, vitamins and minerals) and three nutrients to limit (saturated fat, sugar and sodium)—incidence of cardiovascular disease (CVD) events and all-cause mortality. Subjects/Methods: A total of 4969 persons aged 55 and older from the Rotterdam Study, a prospective cohort study in the Netherlands, were studied. First, all foods were scored on the basis of their nutrient composition, resulting in an NRF9.3 score on food item level. Subsequently, they were converted into individual weighted scores on the basis of the amount of calories of each food item consumed by the subjects and the total energy intake. The hazard ratios (HRs) of the NRF9.3 index score were adjusted for age, gender, body mass index, smoking history, doctor-prescribed diet, alcohol consumption and education. Results: Food groups that contributed most to the NRF9.3 index score were vegetables, milk and milk products, fruit, bread and potatoes. A high NRF9.3 index score was inversely associated with all-cause mortality (HR Q4 versus Q1: 0.84 (95% confidence interval: 0.74, 0.96)). Associations were stronger in women than in men. The NRF9.3 index score was not associated with incidence of CVD. Conclusion: Elderly with a higher NRF9.3 index score, indicating more beneficial components and/or less limiting components, had a lower risk of all-cause mortality. Consuming a nutrient-dense diet may improve survival
    Rapid analysis of Delta-9-tetrahydrocannabinol in hair using direct analysis in real time ambient ionization orbitrap mass spectrometry
    Duvivier, W.F. ; Beek, T.A. van; Pennings, E.J.M. ; Nielen, M.W.F. - \ 2014
    Rapid Communications in Mass Spectrometry 28 (2014)7. - ISSN 0951-4198 - p. 682 - 690.
    synthetic cannabinoids - cocaine - drugs - identification - capabilities - metabolites - validation - samples - abuse
    RATIONALE - Forensic hair analysis methods are laborious, time-consuming and provide only a rough retrospective estimate of the time of drug intake. Recently, hair imaging methods using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) were reported, but these methods require the application of MALDI matrix and are performed under vacuum. Direct analysis of entire locks of hair without any sample pretreatment and with improved spatial resolution would thus address a need. METHODS - Hair samples were attached to stainless steel mesh screens and scanned in the X-direction using direct analysis in real time (DART) ambient ionization orbitrap MS. The DART gas temperature and the accuracy of the probed hair zone were optimized using ¿-9-tetrahydrocannabinol (THC) as a model compound. Since external contamination is a major issue in forensic hair analysis, sub-samples were measured before and after dichloromethane decontamination. RESULTS - The relative intensity of the THC signal in spiked blank hair versus that of quinine as the internal standard showed good reproducibility (26% RSD) and linearity of the method (R2¿=¿0.991). With the DART hair scan THC could be detected in hair samples from different chronic cannabis users. The presence of THC was confirmed by quantitative liquid chromatography/tandem mass spectrometry. Zones with different THC content could be clearly distinguished, indicating that the method might be used for retrospective timeline assessments. Detection of THC in decontaminated drug user hair showed that the DART hair scan not only probes THC on the surface of hair, but penetrates deeply enough to measure incorporated THC. CONCLUSIONS - A new approach in forensic hair analysis has been developed by probing complete locks of hair using DART-MS. Longitudinal scanning enables detection of incorporated compounds and can be used as pre-screening for THC without sample preparation. The method could also be adjusted for the analysis of other drugs of abuse.
    Evaluation of preformance of Predictive Models for Deoxynivalenol in Wheat
    Fels, H.J. van der - \ 2014
    Risk Analysis 34 (2014)2. - ISSN 0272-4332 - p. 380 - 390.
    fusarium mycotoxins - winter-wheat - validation
    The aim of this study was to evaluate the performance of two predictive models for deoxynivalenol contamination of wheat at harvest in the Netherlands, including the use of weather forecast data and external model validation. Data were collected in a different year and from different wheat fields than data used for model development. The two models were run for six preset scenarios, varying in the period for which weather forecast data were used, from zero-day (historical data only) to a 13-day period around wheat flowering. Model predictions using forecast weather data were compared to those using historical data. Furthermore, model predictions using historical weather data were evaluated against observed deoxynivalenol contamination of the wheat fields. Results showed that the use of weather forecast data rather than observed data only slightly influenced model predictions. The percent of correct model predictions, given a threshold of 1,250 µg/kg (legal limit in European Union), was about 95% for the two models. However, only three samples had a deoxynivalenol concentration above this threshold, and the models were not able to predict these samples correctly. It was concluded that two- week weather forecast data can reliable be used in descriptive models for deoxynivalenol contamination of wheat, resulting in more timely model predictions. The two models are able to predict lower deoxynivalenol contamination correctly, but model performance in situations with high deoxynivalenol contamination needs to be further validated. This will need years with conducive environmental conditions for deoxynivalenol contamination of wheat.
    A high-throughput method for GMO multi-detection using a microfluidic dynamic array
    Brod, F.C.A. ; Dijk, J.P. van; Voorhuijzen, M.M. ; Dinon, A.Z. ; Guimarães, L.H.S. ; Scholtens, I.M.J. ; Arisi, A.C.M. ; Kok, E.J. - \ 2014
    Analytical and Bioanalytical Chemistry 406 (2014)5. - ISSN 1618-2642 - p. 1397 - 1410.
    genetically-modified maize - real-time pcr - polymerase-chain-reaction - modified organisms - reference molecules - quantitative pcr - screening-assay - digital pcr - zea-mays - validation
    The ever-increasing production of genetically modified crops generates a demand for high-throughput DNAbased methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis byDNA basedmethods, which is the use of a microfluidic dynamic array as a high throughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.
    Global water resources affected by human interventionss and climate change
    Haddeland, I. ; Heinke, J. ; Biemans, H. ; Eisner, S. ; Florke, M.F. ; Hanasaki, N. ; Konzmann, M. ; Ludwig, F. - \ 2014
    Proceedings of the National Academy of Sciences of the United States of America 111 (2014)9. - ISSN 0027-8424 - p. 3251 - 3256.
    integrated model - bias correction - surface-water - validation - fluxes - scheme
    Humans directly change the dynamics of the water cycle through dams constructed for water storage, and through water withdrawals for industrial, agricultural, or domestic purposes. Climate change is expected to additionally affect water supply and demand. Here, analyses of climate change and direct human impacts on the terrestrial water cycle are presented and compared using a multimodel approach. Seven global hydrological models have been forced with multiple climate projections, and with and without taking into account impacts of human interventions such as dams and water withdrawals on the hydrological cycle. Model results are analyzed for different levels of global warming, allowing for analyses in line with temperature targets for climate change mitigation. The results indicate that direct human impacts on the water cycle in some regions, e.g., parts of Asia and in the western United States, are of the same order of magnitude, or even exceed impacts to be expected for moderate levels of global warming (+2 K). Despite some spread in model projections, irrigation water consumption is generally projected to increase with higher global mean temperatures. Irrigation water scarcity is particularly large in parts of southern and eastern Asia, and is expected to become even larger in the future.
    Skill of a global seasonal streamflow forecasting system, relative roles of initial conditions and meteorological forcing
    Yossef, N.C. ; Winsemius, H. ; Weerts, A.H. ; Beek, R. van; Bierkens, M.F.P. - \ 2013
    Water Resources Research 49 (2013)8. - ISSN 0043-1397 - p. 4687 - 4699.
    united-states - hydrological model - water-resources - climate-change - discharge - predictability - availability - prediction - validation - balances
    We investigate the relative contributions of initial conditions (ICs) and meteorological forcing (MF) to the skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCRaster Global Water Balance. Potential improvement in forecasting skill through better climate prediction or by better estimation of ICs through data assimilation depends on the relative importance of these sources of uncertainty. We use the Ensemble Streamflow Prediction (ESP) and reverse ESP (revESP) procedure to explore the impact of both sources of uncertainty at 78 stations on large global basins for lead times upto 6 months. We compare the ESP and revESP forecast ensembles with retrospective model simulations driven by meteorological observations. For each location, we determine the critical lead time after which the importance of ICs is surpassed by that of MF. We analyze these results in the context of prevailing hydroclimatic conditions for larger basins. This analysis suggests that in some basins forecast skill may be improved by better estimation of initial hydrologic states through data assimilation; whereas in others skill improvement depends on better climate prediction. For arctic and snowfed rivers, forecasts of high flows may benefit from assimilation of snow and ice data. In some snowfed basins where the onset of melting is highly sensitive to temperature changes, forecast skill depends on better climate prediction. In monsoonal basins, the variability of the monsoon dominates forecasting skill, except for those where snow and ice contribute to streamflow. In large basins, initial surface water and groundwater states are important sources of skill.
    Making Sense of Agrobiodiversity, Diet, and Intensification of Smallholder Family Farming in the Highland Andes of Ecuador
    Oyarzun, P.J. ; Borja, R.M. ; Sherwood, S. ; Parra, V. - \ 2013
    Ecology of Food and Nutrition 52 (2013)6. - ISSN 0367-0244 - p. 515 - 541.
    nutrition - biodiversity - food - agriculture - validation - diversity - stability - recall - health - crops
    Methods are needed for helping researchers and farmers to interactively describe and analyze local practices in search of opportunities for improving health, environment, and economy. The authors worked with smallholder family farmers in five Andean villages in Ecuador to apply participatory four-cell analysis (PFCA) in characterizing agrobiodiversity. Margelef and Shannon indices examined ecological richness and evenness, and a simplified 24-hour dietary recall characterized food consumption. Cross-analysis tested interactions among agrobiodiversity, farm size, and diet. Overall trends appeared to work against sustainable intensification, with notable heterogeneity and positive deviance found in the practices of relatively smaller enterprises, representing a potential resource for sustainable intensification. The suite of methods was determined useful for initiating researcher-farmer explorations of promising innovation pathways.
    Factors influencing assessment quality in higher vocational education
    Baartman, L. ; Gulikers, J.T.M. ; Dijkstra, A. - \ 2013
    Assessment & Evaluation in Higher Education 38 (2013)8. - ISSN 0260-2938 - p. 978 - 997.
    assessing professional competence - argument-based approach - validity - validation - performance
    The development of assessments that are fit to assess professional competence in higher vocational education requires a reconsideration of assessment methods, quality criteria and (self)evaluation. This article examines the self-evaluations of nine courses of a large higher vocational education institute. Per course, 4–11 teachers and 3–10 students participated. The purpose of this article is to critically examine the quality of assessment in higher vocational education, to identify critical factors influencing assessment quality and to study whether self-evaluation leads to concrete points for improvement. Results show that strong points are fitness for purpose, comparability and fairness. Weak points are reproducibility of decisions and development of self-regulated learning. Critical factors are the translation of competences into assessment criteria to be used in daily lessons and the involvement of the work field. The self-evaluations generated many points for improvement, but not all were translated into actions. Altogether, this article provides a rich picture of assessment quality in higher education and identifies quality aspects that need improvement, (partly) confirming other research on current assessment methods.
    Application of gas chromatography–(triple quadrupole) massspectrometry with atmospheric pressure chemical ionization for thedetermination of multiclass pesticides in fruits and vegetables
    Cherta, L. ; Portoles, T. ; Beltran, J. ; Pitarch, E. ; Mol, J.G.J. ; Hernandez, F. - \ 2013
    Journal of Chromatography. A, Including electrophoresis and other separation methods 1314 (2013). - ISSN 0021-9673 - p. 224 - 240.
    solid-phase extraction - residue analysis - multiresidue method - organic pollutants - quechers method - gc-ms - validation - ms/ms - water
    A multi-residue method for the determination of 142 pesticide residues in fruits and vegetables has been developed using a new atmospheric pressure chemical ionization (APCI) source for coupling gas chromatography (GC) to tandem mass spectrometry (MS). Selected reaction monitoring (SRM) mode has been applied, acquiring three transitions for each compound. In contrast to the extensive fragmentation typically obtained in classical electron ionization (EI), the soft APCI ionization allowed the selection of highly abundant protonated molecules ([M+H](+)) as precursor ions for most compounds. This was favorable for both sensitivity and selectivity. Validation of the method was performed in which both quantitative and qualitative parameters were assessed using orange, tomato and carrot samples spiked at two levels, 0.01 and 0.1mg/kg. The QuEChERS method was used for sample preparation, followed by a 10-fold dilution of the final acetonitrile extract with a mixture of hexane and acetone. Recovery and precision were satisfactory in the three matrices, at both concentration levels. Very low limits of detection (down 0.01µg/kg for the most sensitive compounds) were achieved. Ion ratios were consistent and identification according to EU criteria was possible in 80% (0.01mg/kg) to 96% (0.1mg/kg) of the pesticide/matrix combinations. The method was applied to the analysis of various fruits and vegetables from the Mediterranean region of Spa
    Identification of drug metabolites in human plasma or serum integrating metabolite prediction, LC–HRMS and untargeted data processing.
    Jacobs, P.L. ; Ridder, L.O. ; Ruijken, M. ; Rosing, H. ; Jager, N.G.L. ; Beijnen, J.H. ; Bas, R.R. ; Dongen, W.D. van - \ 2013
    Bioanalysis 5 (2013)17. - ISSN 1757-6180 - p. 2115 - 2128.
    ionization mass-spectrometry - preclinical safety - major metabolite - in-vivo - disposition - excretion - pharmacokinetics - inhibitor - annotation - validation
    Background: Comprehensive identification of human drug metabolites in first-in-man studies is crucial to avoid delays in later stages of drug development. We developed an efficient workflow for systematic identification of human metabolites in plasma or serum that combines metabolite prediction, high-resolution accurate mass LC–MS and MS vendor independent data processing. Retrospective evaluation of predictions for 14 14C-ADME studies published in the period 2007–January 2012 indicates that on average 90% of the major metabolites in human plasma can be identified by searching for accurate masses of predicted metabolites. Furthermore, the workflow can identify unexpected metabolites in the same processing run, by differential analysis of samples of drug-dosed subjects and (placebo-dosed, pre-dose or otherwise blank) control samples. To demonstrate the utility of the workflow we applied it to identify tamoxifen metabolites in serum of a breast cancer patient treated with tamoxifen. Results & Conclusion: Previously published metabolites were confirmed in this study and additional metabolites were identified, two of which are discussed to illustrate the advantages of the workflow.
    Sensitivity analysis and calibration of the Modified Universal Soil Loss Equation (MUSLE) for the upper Malewa Catchment, Kenya
    Odongo, V.O. ; Onyando, J.O. ; Mutua, B.M. ; Oel, P.R. van; Becht, R. - \ 2013
    International Journal of Sediment Research 28 (2013)3. - ISSN 1001-6279 - p. 368 - 383.
    sediment rating curves - uncertainty analysis - hydrologic-models - river catchment - erosion - yield - delivery - runoff - validation - greece
    Simulation models are widely used for studying physical processes such as surface runoff, sediment transport and sediment yield in catchments. Most models need case-specific empirical data for parameterization before being applied especially in regions other than the ones they have been developed. Sensitivity analysis is usually performed to determine the most influential factors of a model so that they can be prioritized for optimization. In this way uncertainties in model outputs can be reduced considerably. This study evaluates the commonly used modified universal soil loss equation (MUSLE) model used for sediment yield simulation for the case of the upper Malewa catchment in Kenya. The conceptual factors of the model are assessed relative to the hydrological factors in the model. Also, the sensitivity of the model to the choice of the objective function in calibration is tested. The Sobol' sensitivity analysis method was used for evaluating the degree of sensitivity of the conceptual and hydrological factors for sediment yield simulations using the MUSLE model. Nash-Sutcliffe Efficiency (NSE) and the modified Nash-Sutcliffe Efficiency (NSEm) are used to test the sensitivity of the model to the choice of the objective function and robustness of model performance with sediment data measured from upper Malewa catchment, Kenya. The results indicate that the conceptual factors are the most sensitive factors of the MUSLE model contributing about 66% of the variability in the output sediment yield. Increased variability of sediment yield output was also observed. This was attributed to interactions of input factors. For the upper Malewa catchment calibration of the MUSLE model indicates that the use of NSEm as an objective function provides stable results, which indicates that the model can satisfactorily be applied for sediment yield simulations.
    Receptor-based high-throughput screening and identification of estrogens in dietary supplements using bioaffinity liquid-chromatography ion mobility mass spectrometry
    Aqai, P. ; Gómez Blesa, N. ; Major, H. ; Pedotti, P. ; Varani, L. ; Ferrero, V.E.V. ; Haasnoot, W. ; Nielen, M.W.F. - \ 2013
    Analytical and Bioanalytical Chemistry 405 (2013)29. - ISSN 1618-2642 - p. 9427 - 9436.
    ms-binding assays - multi-residue method - anabolic-steroids - lc-ms - nutritional supplements - chemical derivatization - native marker - contamination - transporter - validation
    A high-throughput bioaffinity liquid chromatography-mass spectrometry (BioMS) approach was developed and applied for the screening and identification of recombinant human estrogen receptor a (ERa) ligands in dietary supplements. For screening, a semi-automated mass spectrometric ligand binding assay was developed applying 13C2,15¿N-tamoxifen as non-radioactive label and fast ultra-high-performance–liquid chromatography–electrospray ionisation–triple-quadrupole-MS (UPLC-QqQ-MS), operated in the single reaction monitoring mode, as a readout system. Binding of the label to ERa-coated paramagnetic microbeads was inhibited by competing estrogens in the sample extract yielding decreased levels of the label in UPLC-QqQ-MS. The label showed high ionisation efficiency in positive electrospray ionisation (ESI) mode, so the developed BioMS approach is able to screen for estrogens in dietary supplements despite their poor ionisation efficiency in both positive and negative ESI modes. The assay was performed in a 96-well plate, and all these wells could be measured within 3 h. Estrogens in suspect extracts were identified by full-scan accurate mass and collision-cross section (CCS) values from a UPLC-ion mobility-Q-time-of-flight-MS (UPLC-IM-Q-ToF-MS) equipped with a novel atmospheric pressure ionisation source. Thanks to the novel ion source, this instrument provided picogram sensitivity for estrogens in the negative ion mode and an additional identification point (experimental CCS values) next to retention time, accurate mass and tandem mass spectrometry data. The developed combination of bioaffinity screening with UPLC-QqQ-MS and identification with UPLC-IM-Q-ToF-MS provides an extremely powerful analytical tool for early warning of ERa bioactive compounds in dietary supplements as demonstrated by analysis of selected dietary supplements in which different estrogens were identified.
    Evaluation of food and nutrient intake assessment using concentration biomarkers in European adolescents from the Healthy Lifestyle in Europe by Nutrition in Adolescence study
    Vandevijvere, S. ; Geelen, A. ; Gonzalez-Gross, M. ; Veer, P. van 't; Dallongeville, J. ; Mouratidu, T. ; Dekkers, A. ; Börnhorst, C. ; Breidenassel, C. - \ 2013
    The British journal of nutrition 109 (2013)4. - ISSN 0007-1145 - p. 736 - 747.
    serum cholesteryl esters - n-3 fatty-acids - dietary-intake - energy-intake - additional measurements - micronutrient intake - biochemical markers - adipose-tissue - vitamin-c - validation
    Accurate food and nutrient intake assessment is essential for investigating diet–disease relationships. In the present study, food and nutrient intake assessment among European adolescents using 24 h recalls (mean of two recalls) and a FFQ (separately and the combination of both) were evaluated using concentration biomarkers. Biomarkers included were vitamin C, ß-carotene, DHA+EPA, vitamin B12 (cobalamin and holo-transcobalamin) and folate (erythrocyte folate and plasma folate). For the evaluation of the food intake assessment 390 adolescents were included, while 697 were included for the nutrient intake assessment evaluation. Spearman rank and Pearson correlations, and validity coefficients, which are correlations between intake estimated and habitual true intake, were calculated. Correlations were higher between frequency of food consumption (from the FFQ) and concentration biomarkers than between mean food intake (from the recalls) and concentration biomarkers, especially for DHA+EPA (r 0·35 v. r 0·27). Most correlations were higher among girls than boys. For boys, the highest validity coefficients were found for frequency of fruit consumption (0·88) and for DHA+EPA biomarker (0·71). In girls, the highest validity coefficients were found for fruit consumption frequency (0·76), vegetable consumption frequency (0·74), mean fruit intake (0·90) and DHA+EPA biomarker (0·69). After exclusion of underreporters, correlations slightly improved. Correlations between usual food intakes, adjusted for food consumption frequency, and concentration biomarkers were higher than correlations between mean food intakes and concentration biomarkers. In conclusion, two non-consecutive 24 h recalls in combination with a FFQ seem to be appropriate to rank subjects according to their usual food intake
    Practical Experiences with an Extended Screening Strategy for Genetically Modified Organisms (GMOs) in Real-Life Samples
    Scholtens-Toma, I.M.J. ; Laurensse, E. ; Molenaar, B. ; Zaaijer, S. ; Gaballo, H.M.S. ; Boleij, P.A. ; Bak, A. ; Kok, E.J. - \ 2013
    Journal of Agricultural and Food Chemistry 61 (2013)38. - ISSN 0021-8561 - p. 9097 - 9109.
    modified maize - reference molecules - quantitation - validation
    Nowadays most animal feed products imported into Europe have a GMO (genetically modified organism) label. This means that they contain European Union (EU)-authorized GMOs. For enforcement of these labeling requirements, it is necessary, with the rising number of EU-authorized GMOs, to perform an increasing number of analyses. In addition to this, it is necessary to test products for the potential presence of EU-unauthorized GMOs. Analysis for EU-authorized and -unauthorized GMOs in animal feed has thus become laborious and expensive. Initial screening steps may reduce the number of GMO identification methods that need to be applied, but with the increasing diversity also screening with GMO elements has become more complex. For the present study, the application of an informative detailed 24-element screening and subsequent identification strategy was applied in 50 animal feed samples. Almost all feed samples were labeled as containing GMO-derived materials. The main goal of the study was therefore to investigate if a detailed screening strategy would reduce the number of subsequent identification analyses. An additional goal was to test the samples in this way for the potential presence of EU-unauthorized GMOs. Finally, to test the robustness of the approach, eight of the samples were tested in a concise interlaboratory study. No significant differences were found between the results of the two laboratories.
    Measuring fast-temporal sediment fluxes with an analogue acoustic sensor: a wind tunnel study
    Poortinga, A. ; Minnen, J. van; Keijsers, J.G.S. ; Riksen, M.J.P.M. ; Goossens, D. ; Seeger, K.M. - \ 2013
    PLoS ONE 8 (2013)9. - ISSN 1932-6203
    eolische processen - sediment - windtunnels - meettechnieken - aeolian processes - sediment - wind tunnels - measurement techniques - inland drift-sand - aeolian transport - erosion - velocity - cloud - soil - validation - efficiency - intensity - saltation
    In aeolian research, field measurements are important for studying complex wind-driven processes for land management evaluation and model validation. Consequently, there have been many devices developed, tested, and applied to investigate a range of aeolian-based phenomena. However, determining the most effective application and data analysis techniques is widely debated in the literature. Here we investigate the effectiveness of two different sediment traps (the BEST trap and the MWAC catcher) in measuring vertical sediment flux. The study was performed in a wind tunnel with sediment fluxes characterized using saltiphones. Contrary to most studies, we used the analogue output of five saltiphones mounted on top of each other to determine the total kinetic energy, which was then used to calculate aeolian sediment budgets. Absolute sediment losses during the experiments were determined using a balance located beneath the test tray. Test runs were conducted with different sand sizes and at different wind speeds. The efficiency of the two traps did not vary with the wind speed or sediment size but was affected by both the experimental setup (position of the lowest trap above the surface and number of traps in the saltation layer) and the technique used to calculate the sediment flux. Despite this, good agreement was found between sediment losses calculated from the saltiphone and those measured using the balance. The results of this study provide a framework for measuring sediment fluxes at small time resolution (seconds to milliseconds) in the field.
    In aeolian research, field measurements are important for studying complex wind-driven processes for land management evaluation and model validation. Consequently, there have been many devices developed, tested, and applied to investigate a range of aeolian-based phenomena. However, determining the most effective application and data analysis techniques is widely debated in the literature. Here we investigate the effectiveness of two different sediment traps (the BEST trap and the MWAC catcher) in measuring vertical sediment flux. The study was performed in a wind tunnel with sediment fluxes characterized using saltiphones. Contrary to most studies, we used the analogue output of five saltiphones mounted on top of each other to determine the total kinetic energy, which was then used to calculate aeolian sediment budgets. Absolute sediment losses during the experiments were determined using a balance located beneath the test tray. Test runs were conducted with different sand sizes and at different wind speeds. The efficiency of the two traps did not vary with the wind speed or sediment size but was affected by both the experimental setup (position of the lowest trap above the surface and number of traps in the saltation layer) and the technique used to calculate the sediment flux. Despite this, good agreement was found between sediment losses calculated from the saltiphone and those measured using the balance. The results of this study provide a framework for measuring sediment fluxes at small time resolution (seconds to milliseconds) in the field.
    An evaluation of WRF's ability to reproduce the surface wind over complex terrain based on typical circulation patterns.
    Jiménez, P.A. ; Dudhia, J. ; González-Rouco, J.F. ; Montávez, J.P. ; Garcia-Bustamante, E. ; Navarro, J. ; Vilà-Guerau de Arellano, J. ; Munoz-Roldán, A. - \ 2013
    Journal of Geophysical Research: Atmospheres 118 (2013)14. - ISSN 2169-897X - p. 7651 - 7669.
    regional climate model - cluster-analysis - quality-assurance - mesoscale model - united-states - variability - validation - reanalysis - classification - simulation
    [1] The performance of the Weather Research and Forecasting (WRF) model to reproduce the surface wind circulations over complex terrain is examined. The atmospheric evolution is simulated using two versions of the WRF model during an over 13¿year period (1992 to 2005) over a complex terrain region located in the northeast of the Iberian Peninsula. A high horizontal resolution of 2km is used to provide an accurate representation of the terrain features. The multiyear evaluation focuses on the analysis of the accuracy displayed by the WRF simulations to reproduce the wind field of the six typical wind patterns (WPs) identified over the area in a previous observational work. Each pattern contains a high number of days which allows one to reach solid conclusions regarding the model performance. The accuracy of the simulations to reproduce the wind field under representative synoptic situations, or pressure patterns (PPs), of the Iberian Peninsula is also inspected in order to diagnose errors as a function of the large-scale situation. The evaluation is accomplished using daily averages in order to inspect the ability of WRF to reproduce the surface flow as a result of the interaction between the synoptic scale and the regional topography. Results indicate that model errors can originate from problems in the initial and lateral boundary conditions, misrepresentations at the synoptic scale, or the realism of the topographic features.
    Lipids from yeasts and fungi: Tomorrow's source of Biodiesel?
    Meeuwse, P. ; Sanders, J.P.M. ; Tramper, J. ; Rinzema, A. - \ 2013
    Biofuels Bioproducts and Biorefining 7 (2013)5. - ISSN 1932-104X - p. 512 - 524.
    solid-state fermentation - fatty-acid production - gamma-linolenic acid - sugar-beet pulp - mortierella-isabellina - oleaginous fungi - chemostat model - scale-up - validation - cultures
    In the search for new transport fuels from renewable resources, biodiesel from microbial lipids comes into view. We have evaluated the lipid yield and energy use of a process for production of biodiesel from agricultural waste using lipid-accumulating yeast and fungi. We included different bioreactors for submerged and solid-state fermentation in our evaluation. Using existing kinetic models, we predict lipid yields on substrate between 5% and 19% (w/w), depending on the culture system. According to the same models, improvement of the yield to 25–30% (w/w) is possible, for example by genetic modifi cation of the micro-organisms. The net energy ratio of the non-optimized systems varies between 0.8 and 2.5 MJ produced per MJ used; energy use for pre-treatment and for oxygen transfer are most important. For the optimized systems, the net energy ratio increases to 2.9–5.5 MJ produced per MJ used, which can compete very well with other biofuels such as bioethanol or algal biodiesel. This shows that, although quite some work still has to be done, microbial lipids have the potential to be tomorrow’s source of biodiesel. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd
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