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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    Optimizing rates and sources of nutrient input to mitigate nitrogen, phosphorus, and carbon losses from rice paddies
    Ding, Wencheng ; He, Ping ; Zhang, Jiajia ; Liu, Yingxia ; Xu, Xinpeng ; Ullah, Sami ; Cui, Zhenling ; Zhou, Wei - \ 2020
    Journal of Cleaner Production 256 (2020). - ISSN 0959-6526
    Enhanced-efficiency fertilizer - Greenhouse gas - Manure N - N threshold - Nutrient loss - Straw return

    Decreasing nutrient losses from excessive synthetic fertilizer inputs is the direct and valid way to address low nutrient use efficiency and the related environmental consequences. Here, we established a comprehensive database of nitrogen (N), phosphorus (P), and carbon (C) losses from rice paddy fields in China, which we used to evaluate fertilization-induced losses and the impact of environmental factors, and to mitigate losses by adopting alternative fertilization options and setting input thresholds. Our results showed that most N-loss pathways had exponential increases with additional N input. In average, 23.8% of the N applied was lost via NH3 (16.1%), N2O (0.3%), leaching (4.8%), and runoff (2.6%). Total P loss was approximately 2.7% of the input, composed of leaching (1.3%) and runoff (1.4%). C lost as CH4 accounted for 4.9% of the organic C input. A relative importance analysis indicated that climate or soil variation rather than fertilizer rate was the dominant factor driving N and P leaching, and CH4 emissions. Based on the sensitivity of multiple N-loss pathways to N fertilization, we propose upper thresholds for N inputs of 142–191 kg N ha−1 across four rice types, which would avoid dramatic increases in N losses. Compared to conventional chemical fertilization, alternative fertilization options had diverse performances: enhanced-efficiency N fertilizer reduced N loss rate by 7.8 percent points and the global warming potential (GWP, considering N2O and CH4 emissions) by 28.8%; combined manure and chemical N fertilizer reduced N loss rate by 9.0 percent points but increased the GWP by 56.9%; straw return had no effect on total N loss but almost doubled the GWP. Using nutrient sources most appropriate to site-specific conditions is demonstrated as a robust way to decrease nutrient losses. Setting nutrient input thresholds would also contribute to the mitigation of environmental pollution, especially in regions with poor fertilization recommendation systems.

    Eight grand challenges in socio-environmental systems modeling
    Elsawah, Sondoss ; Filatova, Tatiana ; Jakeman, Anthony J. ; Kettner, Albert J. ; Zellner, Moira L. ; Athanasiadis, Ioannis N. ; Hamilton, Serena H. ; Axtell, Robert L. ; Brown, Daniel G. ; Gilligan, Jonathan M. ; Janssen, Marco A. ; Robinson, Derek T. ; Rozenberg, Julie ; Ullah, Isaac I.T. ; Lade, Steve J. - \ 2020
    Socio-Environmental Systems Modelling 2 (2020). - ISSN 2663-3027
    Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling purpose, many SES modelers also realize that involvement of stakeholders and experts is fundamental to support social learning and decision-making processes for achieving improved environmental and social outcomes. The contribution of this paper lies in identifying and formulating grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. Eight challenges are delineated: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. These challenges limit our ability to effectively use SES modeling to provide the knowledge and information essential for supporting decision making. Whereas some of these challenges are not unique to SES modeling and may be pervasive in other scientific fields, they still act as barriers as well as research opportunities for the SES modeling community. For each challenge, we outline basic steps that can be taken to surmount the underpinning barriers. Thus, the paper identifies priority research areas in SES modeling, chiefly related to progressing modeling products, processes and practices.
    Natural attenuation of chlorinated ethenes in hyporheic zones : A review of key biogeochemical processes and in-situ transformation potential
    Weatherill, John J. ; Atashgahi, Siavash ; Schneidewind, Uwe ; Krause, Stefan ; Ullah, Sami ; Cassidy, Nigel ; Rivett, Michael O. - \ 2018
    Water Research 128 (2018). - ISSN 0043-1354 - p. 362 - 382.
    Biogeochemistry - Biotransformation - Chlorinated ethenes - Heterogeneity - Hyporheic zone - Natural attenuation
    Chlorinated ethenes (CEs) are legacy contaminants whose chemical footprint is expected to persist in aquifers around the world for many decades to come. These organohalides have been reported in river systems with concerning prevalence and are thought to be significant chemical stressors in urban water ecosystems. The aquifer-river interface (known as the hyporheic zone) is a critical pathway for CE discharge to surface water bodies in groundwater baseflow. This pore water system may represent a natural bioreactor where anoxic and oxic biotransformation process act in synergy to reduce or even eliminate contaminant fluxes to surface water. Here, we critically review current process understanding of anaerobic CE respiration in the competitive framework of hyporheic zone biogeochemical cycling fuelled by in-situ fermentation of natural organic matter. We conceptualise anoxic-oxic interface development for metabolic and co-metabolic mineralisation by a range of aerobic bacteria with a focus on vinyl chloride degradation pathways. The superimposition of microbial metabolic processes occurring in sediment biofilms and bulk solute transport delivering reactants produces a scale dependence in contaminant transformation rates. Process interpretation is often confounded by the natural geological heterogeneity typical of most riverbed environments. We discuss insights from recent field experience of CE plumes discharging to surface water and present a range of practical monitoring technologies which address this inherent complexity at different spatial scales. Future research must address key dynamics which link supply of limiting reactants, residence times and microbial ecophysiology to better understand the natural attenuation capacity of hyporheic systems.
    Biomonitoring of fluoride pollution with gladiolus in the vicinity of a brick kiln field in Lahore, Pakistan
    Ullah, Kifayat ; Saeed Ahmad, S. ; Nauman Ahmad, M. ; Khan, Sardar ; Urooj, Rabail ; Shahid Iqbal, M. ; Zia, Afia ; Ahmad Khan, N. - \ 2016
    Fluoride 49 (2016)3. - ISSN 0015-4725 - p. 245 - 252.
    Biomonitoring - Brick kilns - Fluoride - Gladiolus - Pakistan - South Asia

    Although there are thousands of small-scale, poorly regulated brick kilns in rural areas of South Asia their impact on local agricultural crops is largely unknown. The impact of fluoride on crops in a brick kiln area in the Northern Punjab Region of Pakistan was investigated. Fluoride accumulation, leaf necrosis, and reduced corm diameter and weight were found in the brick kiln area in two cultivars of Gladiolus that have been widely used as biomonitors in Europe. The rate of increase in leaf injury of the sensitive Gladiolus cultivar was greatest at all sites when the temperature was lower and there was a high relative humidity of 60–75%. The necrotic leaf tip lengths of the indicator plants correlated very well with their fluoride concentrations. The fluoride accumulation was directly proportional to the Fluoride Injury Index, although a higher injury index was observed with the fluoride-sensitive cultivar Lavendell Puff compared to the fluoride-tolerant cultivar Flower Song. These results suggest that injury to sensitive crops from fluoride may occur in other brick kiln areas in South Asia, and that Gladiolus plants could be used as a cost-effective biomonitor for further investigation in this region.

    Effects of seasonal variations on physicochemical properties and concentrations of faecal coliform in river Kabul
    Javed, Faryal ; Ahmed, Muhammad Nauman ; Shah, Hamid Ullah ; Iqbal, Muhammad Shahid ; Wahid, Abdul ; Ahmad, Sheikh Saeed - \ 2014
    World Applied Sciences Journal 29 (2014)1. - ISSN 1818-4952 - p. 142 - 149.
    Climate change - Developing countries - Drinking water - Risk assessment - South Asia

    Physicochemical properties of water pH, EC and TDS has relationship with total coliform count, total bacterial count and E. coli in terms of seasonal variations. It had been observed the highest values of TCC, TBC and fecal coliform was significantly higher in July as compare to April and December, Because the monsoon floods in river Kabul carries more pollutants from nearby fields. All these factors contribute in deteriorating the drinking water quality of study area. pH has positive effect on the growth and persistence of E.coli. Similarly, EC and TDS have influence on transport and fate of these faecal coliform. E. coli is extensively used as indicator organism for faecal contamination of water. The disease risk due to waterborne pathogens is directly related to the concentration of waterborne pathogens in surface and drinking water. This pathogen concentration is influenced by extreme precipitation and floods. More pathogens enter the surface water when floods flush ineffectively treated sewage and manure into surface waters and increase concentrations. As future extreme precipitation and flood frequencies are expected to increase due to climate change, it is essential to better understand the relationship between extreme precipitation, flooding and the concentration of waterborne pathogens in the surface waters. Water managers can then prepare for possible increased health risk in these situations.

    Estimation of grassland biomass and nitrogen using MERIS data
    Ullah, G. ; Si, Y. ; Schlerf, M. ; Skidmore, A.K. ; Shafique, M. ; Iqbal, I.A. - \ 2012
    International Journal of applied Earth Observation and Geoinformation 19 (2012)1. - ISSN 0303-2434 - p. 196 - 204.
    terrestrial chlorophyll index - band-depth analysis - red edge position - vegetation indexes - aboveground biomass - hyperspectral data - branta-leucopsis - broad-band - canopy - quality
    This study aimed to investigate the potential of MERIS in estimating the quantity and quality of a grassland using various vegetation indices (NDVI, SAVI, TSAVI, REIP, MTCI and band depth analysis parameters) at a regional scale. Green biomass was best predicted by NBDI (normalised band depth index) and yielded a calibration R2 of 0.73 and a Root Mean Square Error (RMSE) of 136.2 g m-2 (using an independent validation dataset, n = 30) compared to a much higher RMSE obtained from soil adjusted vegetation index SAVI (444.6 g m-2). Nitrogen density was also best predicted by NBDI and yielded a calibration R2 of 0.51 and a RMSE of 4.2 g m-2 compared to a relatively higher RMSE obtained from MERIS terrestrial chlorophyll index MTCI (6.6 g m-2). For the estimation of nitrogen concentration (%), band depth analysis parameters showed poor R2 of 0.21 and the results of MTCI and REIP were statistically non-significant (P > 0.05). It is concluded that band depth analysis parameters consistently showed higher accuracy than vegetation indices, suggesting that band depth analysis parameters could be used to monitor grassland condition over time at regional scale.
    Using a genetic algorithm as an optimal band selector in the mid and thermal infrared (2.5-14 µm) to discriminate vegetation species
    Ullah, S. ; Groen, T.A. ; Schlerf, M. ; Skidmore, A.K. ; Nieuwenhuis, W. ; Vaiphasa, C. - \ 2012
    Sensors 12 (2012)7. - ISSN 1424-8220 - p. 8755 - 8769.
    spectral discrimination - reflectance - spectroscopy - emissivity - imagery - leaves - identification - spectrometry - regression - plants
    Genetic variation between various plant species determines differences in their physio-chemical makeup and ultimately in their hyperspectral emissivity signatures. The hyperspectral emissivity signatures, on the one hand, account for the subtle physio-chemical changes in the vegetation, but on the other hand, highlight the problem of high dimensionality. The aim of this paper is to investigate the performance of genetic algorithms coupled with the spectral angle mapper (SAM) to identify a meaningful subset of wavebands sensitive enough to discriminate thirteen broadleaved vegetation species from the laboratory measured hyperspectral emissivities. The performance was evaluated using an overall classification accuracy and Jeffries Matusita distance. For the multiple plant species, the targeted bands based on genetic algorithms resulted in a high overall classification accuracy (90%). Concentrating on the pairwise comparison results, the selected wavebands based on genetic algorithms resulted in higher Jeffries Matusita (J-M) distances than randomly selected wavebands did. This study concludes that targeted wavebands from leaf emissivity spectra are able to discriminate vegetation species.
    An accurate retrieval of leaf water content from mid to thermal infrared spectra using continuous wavelet analysis
    Ullah, S. ; Skidmore, A.K. ; Naeem, M. ; Schlerf, M. - \ 2012
    Science of the Total Environment 437 (2012). - ISSN 0048-9697 - p. 145 - 152.
    remote-sensing imagery - hyperspectral data - mu-m - spatial heterogeneity - reflectance data - transform - vegetation - leaves - classification - compression
    Leaf water content determines plant health, vitality, photosynthetic efficiency and is an important indicator of drought assessment. The retrieval of leaf water content from the visible to shortwave infrared spectra is well known. Here for the first time, we estimated leaf water content from the mid to thermal infrared (2.5-14.0µm) spectra, based on continuous wavelet analysis. The dataset comprised 394 spectra from nine plant species, with different water contents achieved through progressive drying. To identify the spectral feature most sensitive to the variations in leaf water content, first the Directional Hemispherical Reflectance (DHR) spectra were transformed into a wavelet power scalogram, and then linear relations were established between the wavelet power scalogram and leaf water content. The six individual wavelet features identified in the mid infrared yielded high correlations with leaf water content (R 2=0.86 maximum, 0.83 minimum), as well as low RMSE (minimum 8.56%, maximum 9.27%). The combination of four wavelet features produced the most accurate model (R 2=0.88, RMSE=8.00%). The models were consistent in terms of accuracy estimation for both calibration and validation datasets, indicating that leaf water content can be accurately retrieved from the mid to thermal infrared domain of the electromagnetic radiation.
    Nutritional Systems Biology of Fat : integration and modeling of transcriptomics datasets related to lipid homeostasis
    Ohid Ullah, M. - \ 2012
    Wageningen University. Promotor(en): Michael Muller, co-promotor(en): Guido Hooiveld. - S.l. : s.n. - ISBN 9789461733818 - 158
    vetzuren - genexpressie - lipidenmetabolisme - obesitas - transcriptomica - statistische analyse - wiskundige modellen - fatty acids - gene expression - lipid metabolism - obesity - transcriptomics - statistical analysis - mathematical models

    Fatty acids, in the form of triglycerides, are the main constituent of the class of dietary lipids. They not only serve as a source of energy but can also act as potent regulators of gene transcription. It is well accepted that an energy rich diet characterized by high intakes of dietary fat is linked to the dramatic increase in the prevalence of obesity in both developed and developing countries in the last several decades. Obese individuals are at increased risk of developing the metabolic syndrome, a cluster of metabolic abnormalities that ultimately increase the risk of developing vascular diseases and type 2 diabetes. Many studies have been performed to uncover the role of fatty acids on gene expression in different organs, but integrative studies in different organs over time driven by high throughput data are lacking. Therefore, we first aimed to develop integrative approaches on the level of individual genes but also pathways using genome-wide transcriptomics datasets of mouse liver and small intestine that are related to fatty acid sensing transcription factor peroxisome proliferator activated receptor alpha (PPARα). We also aimed to uncover the behavior of PPARαtarget genes and their corresponding biological functions in a short time series experiment, and integrated and modeled the influence of different levels of dietary fat and the time dependency on transcriptomics datasets obtained from several organs by developing system level approaches.

    We developed an integrative statistical approach that properly adjusted for multiple testing while integrating data from two experiments, and was driven by biological inference. By quantifying pathway activities in different mouse tissues over time and subsequent integration by partial least squares path model, we found that the induced pathways at early time points are the main drivers for the induced pathways at late time points. In addition, using a time course microarray study of rat hepatocytes, we found that most of the PPARα target genes at early stage are involved in lipid metabolism-related processes and their expression level could be modeled using a quadratic regression function. In this study, we also found that the transcription factorsNR2F, CREB, EREF and RXR might work together with PPARα in the regulation of genes involved in lipid metabolism. By integrating time and dose dependent gene expression data of mouse liver and white adipose tissue (WAT), we found a set of time-dose dependent genes in liver and WAT including potential signaling proteinssecreted from WAT that may induce metabolic changes in liver, thereby contributing to the pathogenesis of obesity.

    Taken together, in this thesis integrative statistical approaches are presented that were applied to a variety of datasets related to metabolism of fatty acids. Results that were obtained provide a better understanding of the function of the fatty acid-sensor PPARa, and identified a set of secreted proteins that may be important for organ cross talk during the development of diet induced obesity.

    An Integrated Statistical Approach to Compare Transcriptomics Data Across Experiments : A Case Study on the Identification of Candidate Target Genes of the Transcription Factor PPARa
    Ohid Ullah, M. ; Müller, M.R. ; Hooiveld, G.J.E.J. - \ 2012
    Bioinformatics and Biology Insights 6 (2012). - ISSN 1177-9322 - p. 145 - 154.
    An effective strategy to elucidate the signal transduction cascades activated by a transcription factor is to compare the transcriptional profiles of wild type and transcription factor knockout models. Many statistical tests have been proposed for analyzing gene expression data, but most tests are based on pair-wise comparisons. Since the analysis of microarrays involves the testing of multiple hypotheses within one study, it is generally accepted that one should control for false positives by the false discovery rate (FDR). However, it has been reported that this may be an inappropriate metric for comparing data across different experiments. Here we propose an approach that addresses the above mentioned problem by the simultaneous testing and integration of the three hypotheses (contrasts) using the cell means ANOVA model. These three contrasts test for the effect of a treatment in wild type, gene knockout, and globally over all experimental groups. We illustrate our approach on microarray experiments that focused on the identification of candidate target genes and biological processes governed by the fatty acid sensing transcription factor PPARa in liver. Compared to the often applied FDR based across experiment comparison, our approach identified a conservative but less noisy set of candidate genes with same sensitivity and specificity. However, our method had the advantage of properly adjusting for multiple testing while integrating data from two experiments, and was driven by biological inference. Taken together, in this study we present a simple, yet efficient strategy to compare differential expression of genes across experiments while controlling for multiple hypothesis testing
    Economic contribution of participatory agroforestry program to poverty alleviation: a case from Sal forests, Bangladesh
    Islam, K.K. ; Hoogstra, M.A. ; Ullah, M.O. ; Sato, N. - \ 2012
    Journal of Forestry Research 23 (2012)2. - ISSN 1007-662X - p. 323 - 332.
    In the Forest Department of Bangladesh, a Participatory Agroforestry Program (PAP) was initiated at a denuded Sal forests area to protect the forest resources and to alleviate poverty amongst the local poor population. We explored whether the PAP reduced poverty and what factors might be responsible for poverty alleviation. We used three poverty measurement methods: the Head Count Index, the Poverty Gap Index and the Foster-Greer-Thorbecke index to determine the extent poverty reduction. We used a linear regression model to determine the possible differences among factors in poverty reduction. Data were collected through semi-structured questionnaires and face to face interviews within the study area. PAP proved effective at poverty alleviation, considerably improving the local situation. The linear regression model showed that PAP output explained the income differences in poverty reduction. Participants identified bureaucracy and illegal money demands by forest department officials, an uncontrolled market system, and underdeveloped road infrastructure as the main obstacles to reduction of poverty. Overall, PAP is quite successful in alleviating poverty. So this program might be of interest at other degraded forest areas as a tool to alleviate poverty.
    Identifying plant species using mid-wave infrared (2.5-6µm) and thermal infrared (8-14µm) emissivity spectra
    Ullah, S. ; Schlerf, M. ; Skidmore, A.K. ; Hecker, C. - \ 2012
    Remote Sensing of Environment 118 (2012)4. - ISSN 0034-4257 - p. 95 - 102.
    salt-marsh vegetation - hyperspectral data - biomass estimation - reflectance - discrimination - indexes - imagery - leaves - classification - spectroscopy
    Plant species discrimination using remote sensing is generally limited by the similarity of their reflectance spectra in the visible, NIR and SWIR domains. Laboratory measured emissivity spectra in the mid infrared (MIR; 2.5µm-6µm) and the thermal infrared (TIR; 8µm-14µm) domain of different plant species, however, reveal significant differences. It is anticipated that with the advances in airborne and space borne hyperspectral thermal sensors, differentiation between plant species may improve. The laboratory emissivity spectra of thirteen common broad leaved species, comprising 3024 spectral bands in the MIR and TIR, were analyzed. For each wavelength the differences between the species were tested for significance using the one way analysis of variance (ANOVA) with the post-hoc Tukey HSD test. The emissivity spectra of the analyzed species were found to be statistically different at various wavebands. Subsequently, six spectral bands were selected (based on the histogram of separable pairs of species for each waveband) to quantify the separability between each species pair based on the Jefferies Matusita (JM) distance. Out of 78 combinations, 76 pairs had a significantly different JM distance. This means that careful selection of hyperspectral bands in the MIR and TIR (2.5µm-14µm) results in reliable species discrimination.
    Chemical composition, rumen degradability, protein utilization and lactation response to selected tree leaves as substitute of cottonseed cake in the diet of dairy goats
    Khan, N.A. ; Habib, G. ; Ullah, G. - \ 2009
    Animal Feed Science and Technology 154 (2009)3-4. - ISSN 0377-8401 - p. 160 - 168.
    tannin-containing leaves - condensed tannins - hydrolyzable tannins - digestion - supplements - nutrition - sheep - forages - growth - straw
    The aim of this study was to investigate the potential of leaves from Grewia oppositifolia (G. oppositifolia) and Ziziphus mauritiana (Z. mauritiana) as a crude protein (CP) supplements to low quality diets of goats in Pakistan. Chemical composition and CP degradability of the tree leaves were compared with cottonseed cake (CSC). The CP content of the supplements ranged from 141 to 269 g/kg dry matter (DM). Contents of total phenols and condensed tannins (CT) were higher (P
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