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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Mapping topsoil organic carbon concentrations and stocks for Tanzania
Kempen, Bas ; Dalsgaard, Soren ; Kaaya, Abel K. ; Chamuya, Nurdin ; Ruiperez Gonzalez, Maria ; Pekkarinen, Anssi ; Walsh, Markus G. - \ 2019
Geoderma 337 (2019). - ISSN 0016-7061 - p. 164 - 180.
Tanzania is one of the countries that has embarked on a national programme under the United Nations collaborative initiative on Reducing Emissions from Deforestation and forest Degradation (REDD). Tanzania is currently developing the capacity to enter into a carbon monitoring REDD+ regime. In this context spatially representative soil carbon datasets and accurate predictive maps are important for determining the soil organic carbon pool. The main objective of this study was to model and map the SOC stock for the 0–30-cm soil layer to provide baseline information for REDD+ purposes. Topsoil data of over 1400 locations spread throughout Tanzania from the National Forest Monitoring and Assessment (NAFORMA), were used, supplemented by two legacy datasets, to calibrate simple kriging with varying local means models. Maps of SOC concentrations (g kg−1) were generated for the 0–10-cm, 10–20-cm, 20–30-cm, 0–30-cm layers, and maps of bulk density and SOC stock (kg m−2) for the 0–30-cm layer. Two approaches for modelling SOC stocks were considered here: the calculate-then-model (CTM) approach and the model-then-calculate approach (MTC). The spatial predictions were validated by means of 10-fold cross-validation. Uncertainty associated to the estimated SOC stocks was quantified through conditional Gaussian simulation. Estimates of SOC stocks for the main land cover classes are provided. Environmental covariates related to soil and terrain proved to be the strongest predictors for all properties modelled. The mean predicted SOC stock for the 0–30-cm layer was 4.1 kg m−2 (CTM approach) translating to a total national stock of 3.6 Pg. The MTC approach gave similar results. The largest stocks are found in forest and grassland ecosystems, while woodlands and bushlands contain two thirds of the total SOC stock. The root mean squared error for the 0–30-cm layer was 1.8 kg m−2, and the R2-value was 0.51. The R2-value of SOC concentration for the 0–30-cm layer was 0.60 and that of bulk density 0.56. The R2-values of the predicted SOC concentrations for the 10-cm layers vary between 0.46 and 0.54. The 95% confidence interval of the predicted average SOC stock is 4.01–4.15 kg m−2, and that of the national total SOC stock 3.54–3.65 Pg. Uncertainty associated with SOC concentration had the largest contribution to SOC stock uncertainty. These findings have relevance for the ongoing REDD+ readiness process in Tanzania by supplementing the previous knowledge of significant carbon pools. The soil organic carbon pool makes up a relatively large proportion of carbon in Tanzania and is therefore an important carbon pool to consider alongside the ones related to the woody biomass. Going forward, the soil organic carbon data can potentially be used in the determination of reference emission levels and the future monitoring, reporting and verification of organic carbon pools.
Understanding root, tuber, and banana seed systems and coordination breakdown : a multi-stakeholder framework
Bentley, Jeffery W. ; Andrade-Piedra, Jorge ; Demo, Paul ; Dzomeku, Beloved ; Jacobsen, Kim ; Kikulwe, Enoch ; Kromann, Peter ; Kumar, P.L. ; McEwan, Margaret ; Mudege, Netsayi ; Ogero, Kwame ; Okechukwu, Richardson ; Orrego, Ricardo ; Ospina, Bernardo ; Sperling, Louise ; Walsh, Stephen ; Thiele, Graham - \ 2018
Journal of Crop Improvement 32 (2018)5. - ISSN 1542-7528 - p. 599 - 621.
Bananas and plantains - root crops - seed security - seed systems - tuber crops - vegetatively propagated crops (VPC)

Vegetatively propagated crop (VPC) seed tends to remain true to varietal type but is bulky, often carries disease, and is slow to produce. So VPC seed needs to be handled differently than that of other crops, e.g., it tends to be sourced locally, often must be fresh, and it is less often sold on the market. Hence, a framework was adapted to describe and support interventions in such seed systems. The framework was used with 13 case studies to understand VPC seed systems for roots, tubers, and bananas, including differing roles and sometimes conflicting goals of stakeholders, and to identify potential coordination breakdowns when actors fail to develop a shared understanding and vision. In this article, we review those case studies. The framework is a critical tool to (a) document VPC seed systems and build evidence; (b) diagnose and treat coordination breakdown and (c) guide decision-makers and donors on the design of more sustainable seed system interventions for VPCs. The framework can be used to analyze past interventions and will be useful for planning future VPC seed programs.

Genetic covariance components within and among linear type traits differ among contrasting beef cattle breeds
Doyle, Jennifer L. ; Berry, Donagh P. ; Walsh, Siobhan W. ; Veerkamp, Roel F. ; Evans, Ross D. ; Carthy, Tara R. - \ 2018
Journal of Animal Science 96 (2018)5. - ISSN 0021-8812 - p. 1628 - 1639.
Beef - Breeds - Cattle - Type traits

Linear type traits describing the skeletal, muscular, and functional characteristics of an animal are routinely scored on live animals in both the dairy and beef cattle industries. Previous studies have demonstrated that genetic parameters for certain performance traits may differ between breeds; no study, however, has attempted to determine if differences exist in genetic parameters of linear type traits among breeds or sexes. Therefore, the objective of the present study was to determine if genetic covariance components for linear type traits differed among five contrasting cattle breeds, and to also investigate if these components differed by sex. A total of 18 linear type traits scored on 3,356 Angus (AA), 31,049 Charolais (CH), 3,004 Hereford (HE), 35,159 Limousin (LM), and 8,632 Simmental (SI) were used in the analysis. Data were analyzed using animal linear mixed models which included the fixed effects of sex of the animal (except in the investigation into the presence of sexual dimorphism), age at scoring, parity of the dam, and contemporary group of herd-date of scoring. Differences (P < 0.05) in heritability estimates, between at least two breeds, existed for 13 out of 18 linear type traits. Differences (P < 0.05) also existed between the pairwise within-breed genetic correlations among the linear type traits. Overall, the linear type traits in the continental breeds (i.e., CH, LM, SI) tended to have similar heritability estimates to each other as well as similar genetic correlations among the same pairwise traits, as did the traits in the British breeds (i.e., AA, HE). The correlation between a linear function of breeding values computed conditional on covariance parameters estimated from the CH breed with a linear function of breeding values computed conditional on covariance parameters estimated from the other breeds was estimated. Replacing the genetic covariance components estimated in the CH breed with those of the LM had least effect but the impact was considerable when the genetic covariance components of the AA were used. Genetic correlations between the same linear type traits in the two sexes were all close to unity (≥0.90) suggesting little advantage in considering these as separate traits for males and females. Results for the present study indicate the potential increase in accuracy of estimated breeding value prediction from considering, at least, the British breed traits separate to continental breed traits.

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.
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.
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.
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