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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Climate change and the vulnerability of electricity generation to water stress in the European Union
Behrens, P. ; Vliet, M.T.H. van; Nanninga, T. ; Walsh, B. ; Rodrigues, J.F.D. - \ 2017
Nature Energy 2 (2017). - ISSN 2058-7546
Thermoelectric generation requires large amounts of water for cooling. Recent warm periods have led to curtailments in generation, highlighting concerns about security of supply. Here we assess EU-wide climate impacts for 1,326 individual thermoelectric plants and 818 water basins in 2020 and 2030. We show that, despite policy goals and a decrease in electricity-related water withdrawal, the number of regions experiencing some reduction in power availability due to water stress rises from 47 basins to 54 basins between 2014 and 2030, with further plants planned for construction in stressed basins. We examine the reasons for these pressures by including water demand for other uses. The majority of vulnerable basins lie in the Mediterranean region, with further basins in France, Germany and Poland. We investigate four adaptations, finding that increased future seawater cooling eases some pressures. This highlights the need for an integrated, basin-level approach in energy and water policy.
Mapping and monitoring soil organic carbon in Africa’s cropland biome
Walsh, M.G. ; Leenaars, J.G.B. - \ 2017
Soil nutrient maps of Sub-Saharan Africa : assessment of soil nutrient content at 250 m spatial resolution using machine learning
Hengl, Tomislav ; Leenaars, Johan G.B. ; Shepherd, Keith D. ; Walsh, Markus G. ; Heuvelink, Gerard B.M. ; Mamo, Tekalign ; Tilahun, Helina ; Berkhout, Ezra ; Cooper, Matthew ; Fegraus, Eric ; Wheeler, Ichsani ; Kwabena, Nketia A. - \ 2017
Nutrient Cycling in Agroecosystems 109 (2017)1. - ISSN 1385-1314 - p. 77 - 102.
Africa - Machine learning - Macro-nutrients - Micro-nutrients - Random forest - Soil nutrient map - Spatial prediction
Spatial predictions of soil macro and micro-nutrient content across Sub-Saharan Africa at 250 m spatial resolution and for 0–30 cm depth interval are presented. Predictions were produced for 15 target nutrients: organic carbon (C) and total (organic) nitrogen (N), total phosphorus (P), and extractable—phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), iron (Fe), manganese (Mn), zinc (Zn), copper (Cu), aluminum (Al) and boron (B). Model training was performed using soil samples from ca. 59,000 locations (a compilation of soil samples from the AfSIS, EthioSIS, One Acre Fund, VitalSigns and legacy soil data) and an extensive stack of remote sensing covariates in addition to landform, lithologic and land cover maps. An ensemble model was then created for each nutrient from two machine learning algorithms—random forest and gradient boosting, as implemented in R packages ranger and xgboost—and then used to generate predictions in a fully-optimized computing system. Cross-validation revealed that apart from S, P and B, significant models can be produced for most targeted nutrients (R-square between 40–85%). Further comparison with OFRA field trial database shows that soil nutrients are indeed critical for agricultural development, with Mn, Zn, Al, B and Na, appearing as the most important nutrients for predicting crop yield. A limiting factor for mapping nutrients using the existing point data in Africa appears to be (1) the high spatial clustering of sampling locations, and (2) missing more detailed parent material/geological maps. Logical steps towards improving prediction accuracies include: further collection of input (training) point samples, further harmonization of measurement methods, addition of more detailed covariates specific to Africa, and implementation of a full spatio-temporal statistical modeling framework.
BASICS Nigeria : Building an Economically Sustainable, Integrated Cassava Seed
Walsh, Stephen - \ 2017
Centre for Development Innovation
BENEFIT Partnership – 2016 Annual Report : Bilateral Ethiopian-Netherlands Effort for Food, Income and Trade Partnership
Alemu, Dawit ; Tesfaye, Seblewengel ; Koomen, I. ; Ayana, Amsalu ; Walsh, Stephen ; Elias, Eyasu ; Vonk, R.B. ; Terefe, Geremew ; Schrader, T. ; Getaw, Helen ; Becx, G.A. ; Blomne Sopov, M. - \ 2017
Centre for Development Innovation (CDI report CDI-17-005)
The influence of service employees and other customers on customer unfriendliness : a social norms perspective
Albrecht, Arne K. ; Walsh, Gianfranco ; Brach, Simon ; Gremler, Dwayne D. ; Herpen, Erica van - \ 2017
Journal of the Academy of Marketing Science 45 (2017)6. - ISSN 0092-0703 - p. 827 - 847.
Customer to customer influence - Descriptive norm - Identification - Injunctive norm - Social influence - Unfriendliness

This research investigates the influence that social sources in the service environment exert on customer unfriendliness. Drawing on social norms theory, the authors demonstrate that descriptive norms (i.e., what most people are perceived to be doing in a certain situation), in the form of unfriendliness by service employees and fellow customers, predicts customers’ unfriendliness toward employees. Injunctive norms (i.e., beliefs about which behaviors are approved by important others) and identification with fellow customers exert moderating effects. Specifically, strong injunctive norms can buffer the effect of descriptive norms. Furthermore, fellow customers influence a customer’s unfriendliness only if he or she identifies either very strongly or very weakly with them. By clarifying the role of norms in service encounters, this study provides insights on when unfriendly customer behavior is likely to occur. Managerial implications for companies who want to diminish customer unfriendliness are discussed.

Programme on Integrated Seed Sector Development in Ethiopia : 2015 Annual report
Walsh, Stephen ; Thijssen, M.H. - \ 2016
Centre for Development Innovation (Report CDI-16-012 ) - 45 p.
seeds - seed production - agroindustrial sector - entrepreneurship - businesses - development - ethiopia - zaden - zaadproductie - agro-industriële sector - ondernemerschap - bedrijven - ontwikkeling - ethiopië
The programme on Integrated Seed Sector Development in Ethiopia aims to strengthen the development of a vibrant, market-oriented and pluralistic seed sector in the country, where quality seed of superior varieties is available and affordable for a larger number of farmers, thereby contributing to food security and economic development in Ethiopia. The programme is a joint effort of Bahir Dar University, Haramaya University, Hawassa University, Mekelle University, Oromia Seed Enterprise, the Ethiopian Seed Association and Centre for Development Innovation of Wageningen UR. Partners include governmental organizations at federal, regional and local level, non-governmental organizations, development organizations, and seed businesses operating at different scales. The programme is funded by the Directorate General for International Cooperation through the Embassy of the Kingdom of the Netherlands in Addis Ababa.
Preface
Pereira, Paulo ; Ferreira, Antonio J.D. ; Sarah, Pariente ; Cerdà, Artemi ; Walsh, Rory ; Keesstra, Saskia - \ 2016
Journal of Soils and Sediments 16 (2016)11. - ISSN 1439-0108 - p. 2493 - 2499.
Taxonomy of the order Mononegavirales : update 2016
Afonso, Claudio L. ; Amarasinghe, Gaya K. ; Bányai, Krisztián ; Bào, Yīmíng ; Basler, Christopher F. ; Bavari, Sina ; Bejerman, Nicolás ; Blasdell, Kim R. ; Briand, François Xavier ; Briese, Thomas ; Bukreyev, Alexander ; Calisher, Charles H. ; Chandran, Kartik ; Chéng, Jiāsēn ; Clawson, Anna N. ; Collins, Peter L. ; Dietzgen, Ralf G. ; Dolnik, Olga ; Domier, Leslie L. ; Dürrwald, Ralf ; Dye, John M. ; Easton, Andrew J. ; Ebihara, Hideki ; Farkas, Szilvia L. ; Freitas-Astúa, Juliana ; Formenty, Pierre ; Fouchier, Ron A.M. ; Fù, Yànpíng ; Ghedin, Elodie ; Goodin, Michael M. ; Hewson, Roger ; Horie, Masayuki ; Hyndman, Timothy H. ; Jiāng, Dàohóng ; Kitajima, Elliot W. ; Kobinger, Gary P. ; Kondo, Hideki ; Kurath, Gael ; Lamb, Robert A. ; Lenardon, Sergio ; Leroy, Eric M. ; Li, Ci Xiu ; Lin, Xian Dan ; Liú, Lìjiāng ; Longdon, Ben ; Marton, Szilvia ; Maisner, Andrea ; Mühlberger, Elke ; Netesov, Sergey V. ; Nowotny, Norbert ; Patterson, Jean L. ; Payne, Susan L. ; Paweska, Janusz T. ; Randall, Rick E. ; Rima, Bertus K. ; Rota, Paul ; Rubbenstroth, Dennis ; Schwemmle, Martin ; Shi, Mang ; Smither, Sophie J. ; Stenglein, Mark D. ; Stone, David M. ; Takada, Ayato ; Terregino, Calogero ; Tesh, Robert B. ; Tian, Jun Hua ; Tomonaga, Keizo ; Tordo, Noël ; Towner, Jonathan S. ; Vasilakis, Nikos ; Verbeek, Martin ; Volchkov, Viktor E. ; Wahl-Jensen, Victoria ; Walsh, John A. ; Walker, Peter J. ; Wang, David ; Wang, Lin Fa ; Wetzel, Thierry ; Whitfield, Anna E. ; Xiè, Jiǎtāo ; Yuen, Kwok Yung ; Zhang, Yong Zhen ; Kuhn, Jens H. - \ 2016
Archives of Virology 161 (2016)8. - ISSN 0304-8608 - p. 2351 - 2360.

In 2016, the order Mononegavirales was emended through the addition of two new families (Mymonaviridae and Sunviridae), the elevation of the paramyxoviral subfamily Pneumovirinae to family status (Pneumoviridae), the addition of five free-floating genera (Anphevirus, Arlivirus, Chengtivirus, Crustavirus, and Wastrivirus), and several other changes at the genus and species levels. This article presents the updated taxonomy of the order Mononegavirales as now accepted by the International Committee on Taxonomy of Viruses (ICTV).

Minimum Information about a Biosynthetic Gene cluster
Medema, M.H. ; Kottmann, Renzo ; Yilmaz, Pelin ; Cummings, Matthew ; Biggins, J.B. ; Blin, Kai ; Bruijn, Irene De; Chooi, Yit Heng ; Claesen, Jan ; Coates, R.C. ; Cruz-Morales, Pablo ; Duddela, Srikanth ; Düsterhus, Stephanie ; Edwards, Daniel J. ; Fewer, David P. ; Garg, Neha ; Geiger, Christoph ; Gomez-Escribano, Juan Pablo ; Greule, Anja ; Hadjithomas, Michalis ; Haines, Anthony S. ; Helfrich, Eric J.N. ; Hillwig, Matthew L. ; Ishida, Keishi ; Jones, Adam C. ; Jones, Carla S. ; Jungmann, Katrin ; Kegler, Carsten ; Kim, Hyun Uk ; Kötter, Peter ; Krug, Daniel ; Masschelein, Joleen ; Melnik, Alexey V. ; Mantovani, Simone M. ; Monroe, Emily A. ; Moore, Marcus ; Moss, Nathan ; Nützmann, Hans Wilhelm ; Pan, Guohui ; Pati, Amrita ; Petras, Daniel ; Reen, F.J. ; Rosconi, Federico ; Rui, Zhe ; Tian, Zhenhua ; Tobias, Nicholas J. ; Tsunematsu, Yuta ; Wiemann, Philipp ; Wyckoff, Elizabeth ; Yan, Xiaohui ; Yim, Grace ; Yu, Fengan ; Xie, Yunchang ; Aigle, Bertrand ; Apel, Alexander K. ; Balibar, Carl J. ; Balskus, Emily P. ; Barona-Gómez, Francisco ; Bechthold, Andreas ; Bode, Helge B. ; Borriss, Rainer ; Brady, Sean F. ; Brakhage, Axel A. ; Caffrey, Patrick ; Cheng, Yi Qiang ; Clardy, Jon ; Cox, Russell J. ; Mot, René De; Donadio, Stefano ; Donia, Mohamed S. ; Donk, Wilfred A. Van Der; Dorrestein, Pieter C. ; Doyle, Sean ; Driessen, Arnold J.M. ; Ehling-Schulz, Monika ; Entian, Karl Dieter ; Fischbach, Michael A. ; Gerwick, Lena ; Gerwick, William H. ; Gross, Harald ; Gust, Bertolt ; Hertweck, Christian ; Höfte, Monica ; Jensen, Susan E. ; Ju, Jianhua ; Katz, Leonard ; Kaysser, Leonard ; Klassen, Jonathan L. ; Keller, Nancy P. ; Kormanec, Jan ; Kuipers, Oscar P. ; Kuzuyama, Tomohisa ; Kyrpides, Nikos C. ; Kwon, Hyung Jin ; Lautru, Sylvie ; Lavigne, Rob ; Lee, Chia Y. ; Linquan, Bai ; Liu, Xinyu ; Liu, Wen ; Luzhetskyy, Andriy ; Mahmud, Taifo ; Mast, Yvonne ; Méndez, Carmen ; Metsä-Ketelä, Mikko ; Micklefield, Jason ; Mitchell, Douglas A. ; Moore, Bradley S. ; Moreira, Leonilde M. ; Müller, Rolf ; Neilan, Brett A. ; Nett, Markus ; Nielsen, Jens ; O'Gara, Fergal ; Oikawa, Hideaki ; Osbourn, Anne ; Osburne, Marcia S. ; Ostash, Bohdan ; Payne, Shelley M. ; Pernodet, Jean Luc ; Petricek, Miroslav ; Piel, Jörn ; Ploux, Olivier ; Raaijmakers, Jos M. ; Salas, José A. ; Schmitt, Esther K. ; Scott, Barry ; Seipke, Ryan F. ; Shen, Ben ; Sherman, David H. ; Sivonen, Kaarina ; Smanski, Michael J. ; Sosio, Margherita ; Stegmann, Evi ; Süssmuth, Roderich D. ; Tahlan, Kapil ; Thomas, Christopher M. ; Tang, Yi ; Truman, Andrew W. ; Viaud, Muriel ; Walton, Jonathan D. ; Walsh, Christopher T. ; Weber, Tilmann ; Wezel, Gilles P. Van; Wilkinson, Barrie ; Willey, Joanne M. ; Wohlleben, Wolfgang ; Wright, Gerard D. ; Ziemert, Nadine ; Zhang, Changsheng ; Zotchev, Sergey B. ; Breitling, Rainer ; Takano, Eriko ; Glöckner, Frank Oliver - \ 2015
Nature Chemical Biology 11 (2015)9. - ISSN 1552-4450 - p. 625 - 631.

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.

A Case Study of a Decision Support System on Mango Fruit Maturity
Walsh, K.B. ; Subedi, P. ; Tijskens, L.M.M. - \ 2015
Acta Horticulturae 1091 (2015). - ISSN 0567-7572 - p. 195 - 204.
Mango fruit maturity can be difficult to determine from external attributes. Assessment of parameters of fruit on tree (dry matter, internal flesh colour) relevant to estimation of fruit maturity was undertaken with a handheld (near infrared spectroscopic) system. Measurement error on dry matter was low (typical RMSEP 0.6% DM). Repeated measurements on the same individual fruit from 78 different blocks across two farms demonstrated that each piece of fruit was on a similar, but individual, maturation trajectory, with a time offset. The offset was presumably related to date of pollination or environmental conditions around the fruit (e.g., inner or outer canopy). A non-linear indexed regression model, coupled with the use of a ‘biological shift factor’, was used to describe the time series data. Estimated biological shift factors were larger for dry matter than flesh colour, indicative of an earlier change in dry matter, albeit at a lower rate. Differences between blocks within a farm and between two farms were small, indicating the maturation processes were independent of local conditions. This technique could be used to trace the source of variation within a block (e.g., to location in canopy or plant water status), towards the goal of reducing this variation, leading to crops of greater uniformity.
Soil property maps of Africa at 250 m resolution
Kempen, B. ; Hengl, T. ; Heuvelink, G.B.M. ; Leenaars, J.G.B. ; Walsh, M.G. ; Macmillan, R.A. ; Mendes de Jesus, J.S. ; Shepherd, K. ; Sila, A. ; Desta, L.T. ; Tondoh, J.E. - \ 2015
Geophysical Research Abstracts 17 (2015). - ISSN 1029-7006 - 1 p.
Vast areas of arable land in sub-Saharan Africa suffer from low soil fertility and physical soil constraints, and
significant amounts of nutrients are lost yearly due to unsustainable soil management practices. At the same
time it is expected that agriculture in Africa must intensify to meet the growing demand for food and fiber the
next decades. Protection and sustainable management of Africa’s soil resources is crucial to achieve this. In
this context, comprehensive, accurate and up-to-date soil information is an essential input to any agricultural or
environmental management or policy and decision-making model.
In Africa, detailed soil information has been fragmented and limited to specific zones of interest for decades.
To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was
established in 2008. AfSIS builds on recent advances in digital soil mapping, infrared spectroscopy, remote
sensing, (geo)statistics, and integrated soil fertility management to improve the way soils are evaluated, mapped,
and monitored. Over the period 2008–2014, the AfSIS project has compiled two soil profile data sets (about
28,000 unique locations): the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site (new soil samples)
database — the two data sets represent the most comprehensive soil sample database of the African continent to
date. In addition a large set of high-resolution environmental data layers (covariates) was assembled.
The point data were used in the AfSIS project to generate a set of maps of key soil properties for the
African continent at 250 m spatial resolution: sand, silt and clay fractions, bulk density, organic carbon, total
nitrogen, pH, cation-exchange capacity, exchangeable bases (Ca, K, Mg, Na), exchangeable acidity, and Al
content. These properties were mapped for six depth intervals up to 2 m: 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm,
60-100 cm, and 100-200 cm. Random forests modelling was used to relate the soil profile observations to a set
covariates, that included global soil class and property maps, MODIS imagery and a DEM, in a 3D mapping
framework. The model residuals were interpolated by 3D kriging, after which the kriging predictions were added
to the random forests predictions to obtain the soil property predictions.
The model predictions were validated with 5–fold cross-validation. The random forests models explained
between 37% (exch. Na) and 85% (Al content) of the variation in the data. Results also show that globally
predicted soil classes help improve continental scale mapping of the soil nutrients and are often among the most
important predictors.
We conclude that the first mapping results look promising. We used an automated modelling framework
that enables re-computing the maps as new data becomes arrives, hereby gradually improving the maps. We
showed that global maps of soil classes and properties produced with models that were predominantly calibrated
on areas with plentiful observations can be used to improve the accuracy of predictions in regions with less
plentiful data, such as Africa.
Impacts of prescribed fire on soil loss and soil quality : An assessment based on an experimentally-burned catchment in central Portugal
Shakesby, Richard A. ; Martins Bento, Celia ; Ferreira, Carla S.S. ; Ferreira, António J.D. ; Stoof, C.R. ; Urbanek, Emilia ; Walsh, Rory P.D. - \ 2015
Catena 128 (2015). - ISSN 0341-8162 - p. 278 - 293.
Central Portugal - Prescribed fire - Soil degradation - Soil erosion - Wildfire

Prescribed (controlled) fire has recently been adopted as an important wildfire-fighting strategy in the Mediterranean. Relatively little research, however, has assessed its impacts on soil erosion and soil quality. This paper investigates hillslope-scale losses of soil, organic matter and selected nutrients before and after a 'worst-case scenario' prescribed fire in a steep, shrub-vegetated catchment with thin stony soil in central Portugal. Comparison is made with soil erosion measured: (1) on a nearby hillslope burned by wildfire and monitored at the hillslope scale and (2) on long-unburned terrain at small-plot, hillslope- and catchment-scales. Hillslope-scale pre- and post-fire soil erosion was recorded over periods of 6weeks to 5months for (1) 9.5months pre-fire and 27months post-fire in the prescribed fire catchment, and (2) c. 3years post-fire at the wildfire site. Organic matter content, pH, total N, K2O, P2O5, Ca2+ and Mg2+ were measured in the eroded sediment and in pre- and post-prescribed fire surface soil. Results indicate that: (1) both the prescribed fire and the wildfire caused expected marked increases in erosion compared with unburned terrain; and (2) the hillslope-scale post-prescribed fire soil losses (up to 2.41tha-1yr-1) exceeded many reported plot-scale post-prescribed fire and post-wildfire erosion rates in the Mediterranean. As a comparison, post-fire erosion for both fire types was less than that caused by some other forms of common soil disturbance (e.g. types of tillage) and even that on undisturbed shrubland in low rainfall areas of the region. Total estimated post-prescribed fire particulate losses of organic matter and nutrients represent only 0.2-2.9% of the content in the upper 2cm of soil, suggesting only a modest fire effect on soil quality, although this may reflect in part a lack of extreme rainfall events following the fire. The longer-term implications for soil conservation of repeated prescribed fire in the Mediterranean are explored and future research priorities identified.

Harvesting quality, Where to start?
Tijskens, L.M.M. ; Schouten, R.E. ; Walsh, K.B. ; Zadravec, P. ; Unuk, T. ; Jacob, S. ; Okello, R.C.O. - \ 2015
In: Acta Horticulturae International Society for Horticultural Science (Acta Horticulturae ) - ISBN 9789462610965 - p. 269 - 276.
Acids - Biological variation - Dry matter content - Fruit size - Sugars

Size increase (expressed as diameter) of four apple cultivars in five seasons during about 130 days before harvest, was analysed with a simple first order production mechanism. All variation in diameter among individual fruit could be attributed to the same origin (development stage or biological age), with explained parts (R2 adj) of more than 98%. The same general behaviour of diameter development was observed in two tomato cultivars whose fruits where grown at two different temperatures. These data were also analysed using the same model with explained parts (R2 adj) of about 90%. Converting diameter into volume (assuming a perfect sphere), the usually observed asymmetrical sigmoidal behaviour was obtained, frequently described in growth modelling with the Richard's curve. A similar sigmoidal behaviour was also observed in the accumulation of dry matter (DM), as measured with NIR technology in growing mangoes. The cubic root of these data on DM could be analysed using the same model formulation, including the variation between individual fruit, with R2 adj well over 90%. Accumulation of DM ends at harvest, so the mechanism of DM production can very well define the final level of DM obtained in harvested fruit. Since sugars and DM are strongly related (e.g., conversion of starch into sugars, Brix values), a very similar mechanism could govern the accumulation of sugars. Destructively measured data on sugars were collected in nectarines, showing indeed a very similar overall behaviour and variation. This indicates that growth (diameter, mass) and quality increase (DM, sugars) could be described by a very similar mechanism, providing the first tools in the quest to harvest quality.

The KnownLeaf literature curation system captures knowledge about Arabidopsis leaf growth and development and facilitates integrated data mining
Szakonyi, D. ; Landeghem, S. van; Baerenfaller, K. ; Baeyens, L. ; Blomme, J. ; Casanova-Saéz, R. ; Bodt, S. De; Esteve-Bruna, D. ; Fiorani, F. ; Gonzalez, N. ; Grønlund, J. ; Immink, R.G.H. ; Jover-Gil, S. ; Kuwabara, A. ; Muñoz-Nortes, T. ; Dijk, A.D.J. van; Wilson-Sánchez, D. ; Buchanan-Wollaston, V. ; Angenent, G.C. ; Peer, Y. Van de; Inzé, D. ; Micol, J.L. ; Gruissem, W. ; Walsh, S. ; Hilson, P. - \ 2015
Current Plant Biology 2 (2015). - ISSN 2214-6628 - p. 1 - 11.
The information that connects genotypes and phenotypes is essentially embedded in research articles written in natural language. To facilitate access to this knowledge, we constructed a framework for the curation of the scientific literature studying the molecular mechanisms that control leaf growth and development in Arabidopsis thaliana (Arabidopsis). Standard structured statements, called relations, were designed to capture diverse data types, including phenotypes and gene expression linked to genotype description, growth conditions, genetic and molecular interactions, and details about molecular entities. Relations were then annotated from the literature, defining the relevant terms according to standard biomedical ontologies. This curation process was supported by a dedicated graphical user interface, called Leaf Knowtator. A total of 283 primary research articles were curated by a community of annotators, yielding 9947 relations monitored for consistency and over 12,500 references to Arabidopsis genes. This information was converted into a relational database (KnownLeaf) and merged with other public Arabidopsis resources relative to transcriptional networks, protein–protein interaction, gene co-expression, and additional molecular annotations. Within KnownLeaf, leaf phenotype data can be searched together with molecular data originating either from this curation initiative or from external public resources. Finally, we built a network (LeafNet) with a portion of the KnownLeaf database content to graphically represent the leaf phenotype relations in a molecular context, offering an intuitive starting point for knowledge mining. Literature curation efforts such as ours provide high quality structured information accessible to computational analysis, and thereby to a wide range of applications. DATA: The presented work was performed in the framework of the AGRON-OMICS project (Arabidopsis GRO wth Network integrating OMICS technologies) supported by European Commission 6th Framework Programme project (Grant number LSHG-CT-2006-037704). This is a data integration and data sharing portal collecting all the all the major results from the consortium. All data presented in our paper is available here. https://agronomics.ethz.ch/.
Mapping Soil Properties of Africa at 250 m resolution: random forest significantly improve current predictions
Hengl, T. ; Heuvelink, G.B.M. ; Kempen, B. ; Leenaars, J.G.B. ; Walsh, M.G. ; Shepherd, K.D. ; Sila, A. ; Macmillan, R.A. ; Mendes de Jesus, J.S. ; Tamene, L. ; Tondoh, J.E. - \ 2015
PLoS One 10 (2015)6. - ISSN 1932-6203
continental-scale - maps - classification - surveillance - management - models - carbon - trees
80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008–2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management—organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15–75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological knowledge from data rich countries to countries with limited soil data.
The perceived impact of the National Health Service on personalised nutrition service delivery among the UK public
Fallaize, R. ; Macready, A.L. ; Butler, L.T. ; Ellis, J.A. ; Berezowska, A. ; Fischer, A.R.H. ; Walsh, M.C. ; Gallagher, C. ; Stewart-Knox, B.J. ; Kuznesof, S. ; Frewer, L.J. ; Gibney, M.J. ; Lovegrove, J.A. - \ 2015
British Journal of Nutrition 113 (2015)8. - ISSN 0007-1145 - p. 1271 - 1279.
nutrigenomics - communication - disease - information - consumer - medicine - intervention - acceptance - knowledge - attitudes
Personalised nutrition (PN) has the potential to reduce disease risk and optimise health and performance. Although previous research has shown good acceptance of the concept of PN in the UK, preferences regarding the delivery of a PN service (e.g. online v. face-to-face) are not fully understood. It is anticipated that the presence of a free at point of delivery healthcare system, the National Health Service (NHS), in the UK may have an impact on end-user preferences for deliverances. To determine this, supplementary analysis of qualitative data obtained from focus group discussions on PN service delivery, collected as part of the Food4Me project in the UK and Ireland, was undertaken. Irish data provided comparative analysis of a healthcare system that is not provided free of charge at the point of delivery to the entire population. Analyses were conducted using the ‘framework approach’ described by Rabiee (Focus-group interview and data analysis. Proc Nutr Soc 63, 655-660). There was a preference for services to be led by the government and delivered face-to-face, which was perceived to increase trust and transparency, and add value. Both countries associated paying for nutritional advice with increased commitment and motivation to follow guidelines. Contrary to Ireland, however, and despite the perceived benefit of paying, UK discussants still expected PN services to be delivered free of charge by the NHS. Consideration of this unique challenge of free healthcare that is embedded in the NHS culture will be crucial when introducing PN to the UK.
Atlantic flatfish fisheries
Walsh, S.J. ; Diaz de Astarloa, J.M. ; Poos, J.J. - \ 2015
In: Flatfishes: Biology and Exploitation, 2nd edition / Gibson, R.N., Nash, R.D.M., Geffen, A.J., van der Veer, H.W., West Sussex : John Wiley (Fish and Aquatic resources series 16) - ISBN 9781118501191 - p. 346 - 394.
The perceived impact of the National Health Service on personalised nutrition delivery in the UK
Fallaize, R. ; Macready, A.L. ; Butler, L.T. ; Ellis, J.A. ; Berezowska, A. ; Fischer, A.R.H. ; Walsh, M. ; Gallagher, C. ; Stewart-Knox, B. ; Kuznesof, S. ; Frewer, L.J. ; Gibney, M. ; Lovegrove, J.A. - \ 2014
In: Book of abstracts of the 11th NuGOweek nutrigenomics of foods. - Wageningen Academic Publishers - p. 129 - 129.
The Nutrition Researcher Cohort (NRC) was launched at the 10th NuGOweek 2013 and represents a new generation research platform. Thereby, each individual provides and owns her/his selfquantification data on her/his health data using various gadgets and/or clinical analysis. The NRC approach is thus in a stepping-stone ‘development phase’ for a new way to merge observational research, personal health empowerment, (nutritional) intervention studies and preventive healthcare with the goal to become a globally accepted standard. Thereby, the NRC aims to renew the relationship between research and healthcare. Participants actively take part in research studies, by monitoring their health status themselves, instead of being passive data-and-blood-donating humans. In addition, participants will have a direct health benefit from participating in research by personalized health information and advice based on their personal data. We here present the first results of the initiation study, which included metabolomics and metabolite profiling of Dried Blood Spots (DBS) of finger prick blood, accomplished by five participating laboratories. Furthermore, all participants were asked to enter self-quantification data on food intake, anthropometrics, age, blood pressure, glucose response and several more. In total, about 300 metabolites were identified and relatively or absolutely quantified using LC-MS/MS and GC-MS. In addition, four trace elements were determined using total-reflection X-ray fluorescence analysis. Metabolite profiles will be connected to self-quantification data, anthropometrics and food intake. Thereof, first examples of visualization will be presented. The final aim is to provide personal advice on health, lifestyle and diet. As the NRC is a ‘crowd or citizen science’ initiative, any lab is invited to participate in optimizing and supplying DiY sampling (e.g. DBS, mucosal swaps) and analytics, metabolomics, data visualization and interpretation or other relevant methods. If you like to become a contributing participant entering your own health data, please check our website http://nrc.dbnp.org.
SoilGrids1km— global soil information based on automated mapping
Hengl, T. ; Mendes de Jesus, J.S. ; Macmillan, R.A. ; Batjes, N.H. ; Heuvelink, G.B.M. ; Carvalho Ribeiro, E.D. ; Samuel Rosa, A. ; Kempen, B. ; Leenaars, J.G.B. ; Walsh, M.G. ; Ruiperez Gonzalez, M. - \ 2014
PLoS One 9 (2014)8. - ISSN 1932-6203
global land areas - organic-carbon - resolution - climate - world - maps - interpolation - database - models
Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg-1), soil pH, sand, silt and clay fractions (%), bulk density (kg m-3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha-1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is highly automated and flexible, increasingly accurate predictions can be generated as new input data become available. SoilGrids1km are available for download via http://soilgrids.org under a Creative Commons Non Commercial license.
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