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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Data from: Quantitative visual soil observation for visual soil evaluation on dairy farms
Leeuwen, M.W.J. van; Schols, Anne ; Quik, C. - \ 2019
dairy farm - soil quality assessment - visual soil evaluation
Quantitative visual observations were collected for two studies on dairy farms in the Netherlands. Data were collected following the same methodology (Van Leeuwen et al., 2018) based on Visual Soil Assessment of Shepherd (2009).
Successful Engagement of Practitioners and Software Engineering Researchers: Evidence From 26 International Industry-Academia Collaborative Projects
Garousi, Vahid ; Shepherd, David C. ; Herkiloglu, Kadir - \ 2019
IEEE Software (2019). - ISSN 0740-7459 - 1 p.
applied research - experience report - Industry-academia collaborations - lessons learned

There has been a recent push to increase the practical relevance and impact of software engineering (SE) research. Even though many practitioners and researchers agree that this change is desirable, only some concrete actions have been taken in the community so far. In this paper, we present our experience in a large number of collaborative research projects (26 projects) which have had practical (industrial) impact. These projects have been conducted in several different countries, have focused on different SE topics (e.g., testing, software maintenance, and documentation), and have spanned over different domains (e.g., embedded software, defense and telecom, robotics). We characterize the industrial needs, contributions, and impacts of the projects. Furthermore, via a participant-observation research approach, the authors analyze their diary reflections recorded during the projects and synthesize their experience into a set of seven lessons learned on how to conduct successful industry-academia collaborations. Our hope is that the evidence and experience provided by our example projects would motivate SE practitioners and researchers to engage more on collaborative projects.

Characterizing industry-academia collaborations in software engineering: evidence from 101 projects
Garousi, Vahid ; Pfahl, Dietmar ; Fernandes, João M. ; Felderer, Michael ; Mäntylä, Mika V. ; Shepherd, David ; Arcuri, Andrea ; Coşkunçay, Ahmet ; Tekinerdogan, Bedir - \ 2019
Empirical Software Engineering 24 (2019)4. - ISSN 1382-3256 - p. 2540 - 2602.
Anti-patterns - Best practices - Challenges - Empirical study - Evidence - Industry-academia collaborations - Patterns - Software engineering

Research collaboration between industry and academia supports improvement and innovation in industry and helps ensure the industrial relevance of academic research. However, many researchers and practitioners in the community believe that the level of joint industry-academia collaboration (IAC) projects in Software Engineering (SE) research is relatively low, creating a barrier between research and practice. The goal of the empirical study reported in this paper is to explore and characterize the state of IAC with respect to industrial needs, developed solutions, impacts of the projects and also a set of challenges, patterns and anti-patterns identified by a recent Systematic Literature Review (SLR) study. To address the above goal, we conducted an opinion survey among researchers and practitioners with respect to their experience in IAC. Our dataset includes 101 data points from IAC projects conducted in 21 different countries. Our findings include: (1) the most popular topics of the IAC projects, in the dataset, are: software testing, quality, process, and project managements; (2) over 90% of IAC projects result in at least one publication; (3) almost 50% of IACs are initiated by industry, busting the myth that industry tends to avoid IACs; and (4) 61% of the IAC projects report having a positive impact on their industrial context, while 31% report no noticeable impacts or were “not sure”. To improve this situation, we present evidence-based recommendations to increase the success of IAC projects, such as the importance of testing pilot solutions before using them in industry. This study aims to contribute to the body of evidence in the area of IAC, and benefit researchers and practitioners. Using the data and evidence presented in this paper, they can conduct more successful IAC projects in SE by being aware of the challenges and how to overcome them, by applying best practices (patterns), and by preventing anti-patterns.

Fertilizer response and nitrogen use efficiency in African smallholder maize farms
Ichami, Stephen M. ; Shepherd, Keith D. ; Sila, Andrew M. ; Stoorvogel, Jetse J. ; Hoffland, Ellis - \ 2019
Nutrient Cycling in Agroecosystems 113 (2019)1. - ISSN 1385-1314 - p. 1 - 19.
Kenya - Meta-analysis - Nitrogen - Soil responsiveness - Spatial variability

Improving fertilizer recommendations for farmers is essential to increase food security in smallholder landscapes. Currently, blanket recommendations are provided across agro-ecological zones, although fertilizer response and nutrient use efficiency by maize crop are spatially variable. We aimed to identify factors that could help to refine fertilizer recommendation by analyzing the variability in fertilizer response (FR) and the agronomic nitrogen use efficiency (N-AE). A literature search for on-farm studies across Kenya and Sub-Sahara Africa (SSA), excluding Kenya, yielded 71 publications. The variability in FR was studied using a meta-analysis whereas key factors that influence FR and N-AE were studied with linear regression models. On average, the FR was 2, but it varied considerably from 1 to 28.5 (excluding outliers). In SSA, 18% of the plots were non-responsive plots with an FR < 1. The main factors affecting N-AE for Kenya were P-Olsen, silt content, soil pH, clay and rainfall, whereas only soil pH, exchangeable K and texture were important for SSA. However, our study indicates that available data on soil, climate and management factors could explain only a small part (< 33%) of the variation in FR and N-AE. Soil pH, P-Olsen, silt content, and rainfall had significant but low levels of power in explaining variation in FR and N-AE. Our findings indicate that strategies to refine fertilizer recommendation should include information on soil types and soil properties.

Probabilistic Assessment of Investment Options in Honey Value Chains in Lamu County, Kenya
Wafula, J. ; Karimjee, Y. ; Malava, G. ; Muchiri, C. ; Koech, G. ; Leeuw, J. de; Nyongesa, J. ; Shepherd, K. ; Luedeling, E. - \ 2018
Frontiers in Applied Mathematics and Statistics 4 (2018)Article 6. - ISSN 2297-4687 - 11 p.

Designing and implementing biodiversity-based value chains can be a complex undertaking, especially in places where outcomes are uncertain and risks of project failure and cost overruns are high. We used the Stochastic Impact Evaluation (SIE) approach to guide the Intergovernmental Authority on Development (IGAD) on viable investment options in honey value chains, which the agency considered implementing as an economic incentive for communities along the Kenya-Somalia border to conserve biodiversity. The SIE approach allows for holistic analysis of project cost, benefit, and risk variables, including those with uncertain and missing information. It also identifies areas that pose critical uncertainties in the project. We started by conducting a baseline survey in Witu and Awer in Lamu County, Kenya. The aim of the survey was to establish the current farm income from beekeeping as a baseline, against which the prospective impacts of intervention options could be measured. We then developed an intervention decision model that was populated with all cost, benefit and risk variables relevant to beekeeping. After receiving training in making quantitative estimates, four subject-matter experts expressed their uncertainty about the proposed variables in the model by specifying probability distributions for them. We then used Monte Carlo simulation to project decision outcomes. We also identified variables that projected decision outcomes were most sensitive to, and we determined the value of information for each variable. The variable with the highest information value to the decision-maker in Witu was the honey price. In Awer, no additional information on any of the variables would change the recommendation to invest in honey value chains in the region. The analysis demonstrates a novel and comprehensive approach to decision-making for different stakeholders in a project where decision outcomes are uncertain.

Introduction
Detecting macroecological patterns in bacterial communities across independent studies of global soils
Ramirez, Kelly S. ; Knight, Christopher G. ; Hollander, Mattias de; Brearley, Francis Q. ; Constantinides, Bede ; Cotton, Anne ; Creer, Si ; Crowther, Thomas W. ; Davison, John ; Delgado-Baquerizo, Manuel ; Dorrepaal, Ellen ; Elliott, David R. ; Fox, Graeme ; Griffiths, Robert I. ; Hale, Chris ; Hartman, Kyle ; Houlden, Ashley ; Jones, David L. ; Krab, Eveline J. ; Maestre, Fernando T. ; McGuire, Krista L. ; Monteux, Sylvain ; Orr, Caroline H. ; Putten, Wim H. van der; Roberts, Ian S. ; Robinson, David A. ; Rocca, Jennifer D. ; Rowntree, Jennifer ; Schlaeppi, Klaus ; Shepherd, Matthew ; Singh, Brajesh K. ; Straathof, Angela L. ; Bhatnagar, Jennifer M. ; Thion, Cécile ; Heijden, Marcel G.A. van der; Vries, Franciska T. de - \ 2018
Nature Microbiology 3 (2018). - ISSN 2058-5276 - p. 189 - 196.
The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential ‘indicator’ taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.
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.
The environmental, socioeconomic, and health impacts of woodfuel value chains in Sub-Saharan Africa : A systematic map
Sola, Phosiso ; Cerutti, Paolo Omar ; Zhou, Wen ; Gautier, Denis ; Iiyama, Miyuki ; Schure, Jolien ; Chenevoy, Audrey ; Yila, Jummai ; Dufe, Vanessa ; Nasi, Robert ; Petrokofsky, Gillian ; Shepherd, Gill - \ 2017
Environmental Evidence 6 (2017)1. - ISSN 2047-2382
Africa - Charcoal - Consumption - Firewood - Forests - Fuelwood - Livelihoods - Production - Trade - Woodlands
Background: In Sub-Saharan Africa (SSA), the production and use of woodfuel remains an important socio-economic activity with more than 70% of the population relying on woodfuel as their primary household energy source. Despite their socio-economic significance, woodfuel value chains are often viewed negatively due to their association with detrimental health and environmental impacts. However, the lack of sound evidence and limited understanding of the role of contextual factors in influencing the various impacts of woodfuel value chains have prevented the formulation of properly guided policy interventions. Thus the objective of this systematic map is to provide a comprehensive review of the environmental, socio-economic, and health impacts of woodfuel value chains across SSA. Methods: The search strategy for this review map was defined in a peer-reviewed protocol and refined by iterative testing. Search strings were composed of population, intervention, and location terms and combined using Boolean operators. The bibliographic databases Web of Science, Scopus, and CAB Abstracts were used as the main sources of literature for this review, and a total of 4728 results were initially retrieved. Following title and abstract screening, 659 entered full text screening. Critical appraisal of 219 articles led to the exclusion of studies that did not set meet quality criteria for this map, resulting in a final total of 131 articles for inclusion in data extraction and analysis. Results: From the 131 included articles, 152 individual studies were identified during data extraction. Studies came from 26 of the 49 Sub Saharan African countries, with a particular preponderance of articles published in the last 10 years. Critical appraisal found significant weaknesses in the experimental design of woodfuel value chain studies with the exception of health impact studies, which frequently utilized controls or other relevant comparators. Findings suggest that woodfuel value chains have environmental, socioeconomic and health consequences with the frequent presence of trade-offs. The reporting of contextual factors in the studies challenge the widespread perception of deforestation as being directly caused by bush fires, overgrazing and woodcutting. Instead, agricultural expansion (which often includes forest clearing) and pre-existing biophysical factors were the most frequently cited factors in shaping environmental outcomes. Conclusions: This systematic map suggests that there are environmental, socioeconomic and health consequences associated with woodfuel value chains in Sub-Saharan Africa. However, the literature also shows a weak and geographically limited evidence base to justify the above claims. We argue that policy formulation processes targeting woodfuels in SSA require more solid, coherent and broad body of knowledge, especially for such a vital sector in rural economies. Thus, there is an urgent need to design and undertake research using robust methodologies, at appropriate scales that further takes into account the interrelationships between environmental and socio-economic outcomes in order to generate substantial and reliable evidence for informed policy formulation.
Grazing lands in Sub-Saharan Africa and their potential role in climate change mitigation: What we do and don't know
Milne, E. ; Aynekulu, E. ; Bationo, A. ; Batjes, N.H. ; Boone, R. ; Conant, R. ; Davies, J. ; Hanan, N. ; Hoag, D. ; Herrick, J.E. ; Knausenberger, W. ; Neely, C. ; Njoka, J. ; Ngugi, M. ; Parton, B. ; Paustian, K. ; Reid, K. ; Said, M. ; Shepherd, K. ; Swift, D. ; Thornton, P. ; Williams, S. ; Miller, S. ; Nkonya, Ephraim - \ 2016
Environmental Development 19 (2016). - ISSN 2211-4645 - p. 70 - 74.
In 2014, the USAID project ‘Grazing lands, livestock and climate resilient mitigation in Sub-Saharan Africa’ held two workshops, hosted by the Colorado State University, which brought together experts from around the world. Two reports resulted from these workshops, one an assessment of the state of the science, and the other an inventory of related activities in the region to date.. In this short communication we summarize the main points of the first report – The state of the science (Milne and Williams, 2015). A second report is in preparation.
The future of phosphorus in our hands
Shepherd, J.G. ; Kleemann, Rosanna ; Bahri-Esfahani, Jaleh ; Hudek, Lee ; Suriyagoda, Lalith ; Vandamme, Elke ; Dijk, K.C. van - \ 2016
Nutrient Cycling in Agroecosystems (2016). - ISSN 1385-1314 - p. 281 - 287.
Conceptual model - Food security - P balance calculation tool - P conceptual model - Phosphorus paradox - Young Scientist Workshop

We live in a global phosphorus (P) system paradox. P access is becoming increasingly limiting, leading to food insecurity but at the same time an over-application or abundance of P in many agricultural and urban settings is causing environmental degradation. This has been recognised in the academic literature and at regulatory levels, but swift action and multi-level cooperation of all stakeholders is required to ensure the economically, environmentally and socially responsible use of P. To provide foundations for future cooperation, a conceptual model describing the elements of P need, P availability and P use in different systems and at different scales was developed during the Young Scientists Workshop in P Week 2014 in Montpellier, France. Here we describe our extended conceptual model and a theoretical P balance calculation tool for describing multi-scale P balances and imbalances to impartially advise all stakeholders on more sustainable P use across the world.

Map-based estimates of present carbon stocks of grazing lands in Sub-Sahara Africa
Batjes, N.H. ; Milne, E. ; Williams, S. - \ 2015
In: Grazing Lands, Livestock and Climate Resilient Mitigation in Sub-Saharan Africa: The State of the Science United States Agency for International Development (USAID) - p. 31 - 33, 97-100.
This report is a detailed review, synthesis, and analysis of the current “state of the science” concerning the potential for carbon sequestration in grazing lands through improved land management practices in Sub-Saharan Africa (SSA). It aims to provide an up-to-date assessment of the science of C sequestration from improved land management, including the current levels of uncertainty, major gaps in knowledge and data, areas for near term research and development, major determinants of sequestration potential, and current and potential scientific monitoring tools. The report firstly gives an overview of current grazing lands in SSA (Chapter 1) and explores the major determinants of C sequestration in grass/rangeland systems (Chapter 2). It then considers current research work on C impacts of grazing land management systems (Chapter 3). Available measurement techniques are summarized in Chapter 4 and a map based approach is then used in Chapter 5 to estimate present C stocks in grazing lands in SSA. This is followed by Chapter 6 which looks at available modeling techniques and Chapter 7 which presents a model based estimate of C sequestration potential in grass/rangelands in SSA. The final chapter (Chapter 8) provides a synthesis of the report’s findings. > Authors of the respective chapters: Eleanor Milne · Stephen Williams · Andre Bationo · Robin Reid · David Swift · Rich Conant · Niall Hanan · Constance Neely · Ermias Aynekulu · Keith D. Shepherd · Niels Batjes · Randall Boone
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.
Endline report – Indonesia, Good Shepherd Sisters MFS II country evaluations
Kusters, C.S.L. ; Wieriks, M. ; Dwi Andari, B. ; Suprobo, N. ; Priyahita, W. ; Sihombing, R.R. ; Rokhmatulloh, S.W. ; Rosita, I. - \ 2015
Wageningen : Centre for Development Innovation, Wageningen UR (Report / Wageningen UR, Centre for Development Innovation CDI-15-036) - 80
capacity - capacity building - organizational development - organizations - development projects - indonesia - south east asia - asia - capaciteit - capaciteitsopbouw - organisatieontwikkeling - organisaties - ontwikkelingsprojecten - indonesië - zuidoost-azië - azië
This report presents the findings of the endline of the evaluation of the organisational capacity component of the MFS II country evaluations. The focus of this report is Indonesia, GSS. The format is based on the requirements by the synthesis team and NWO/WOTRO. The endline was carried out in 2014. The baseline was carried out in 2012.
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.
Prevalence of genetic disorders in dog breeds: a literature review
Wirth, J. - \ 2015
Wageningen : Wetenschapswinkel van Wageningen UR (318 ) - ISBN 9789461738899 - 18 p.
Genetic disorders are common in dogs and in the media it is reported that genetic disorders are more frequent in pedigree dogs than in look-a-likes or in mixed-breed dogs. Here, we consider pedigree dogs as purebred dogs (i.e. matching a breed-specific morphology) with a registered and certified pedigree, whereas look-a-likes dogs are dogs without a certification. Thus, look-a-likes may be non-pure bred or purebred but lacking the supporting evidence. Dutch experts have indicated that more than 40 percent of purebred dogs in the Netherlands suffer from genetic disorders. Uncertainty about the validity of such indications, and if pedigree dogs are at increased risk of genetic disorders, together with societal concerns about the well-being of (pedigree) dogs, incited a Wageningen UR Science Shop project commissioned by the Dutch animal protection foundation Dier&Recht. Genetic disorders are heterogeneous in aetiology and manifestations across dog breeds, which complicates studying them. One feasible approach is to study specific disorders in pre-selected breeds only, as a model for the complex reality. This report, as part of this project’s products, provides a scientific literature overview on prevalence data for two genetic disorders (hip dysplasia and elbow dysplasia) in the German Shepherd and the Rottweiler in various countries including the Netherlands. The prevalence data assembled and compared in this study are based on results of screening programs published from national and international Kennel Clubs and Veterinarian Associations. In both breeds, the disease prevalence for hip dysplasia (HD), ranging from 10-46% in European and non -European countries, was remarkably variable, with a substantial proportion of the population at risk in, for example, Finland (33-46%). In the Netherlands, the prevalence for HD reported for both breeds (10-18%) was intermediate compared to that in other European countries (8-46%). Different methodology and scoring systems for HD are used in screening programs, whereas interpretations of radiographs to determine the HD grade, and the quality of databases, are critical factors. Methodological differences between studies make a valid comparison between studies difficult. The results for elbow dysplasia (ED) are similar regarding the high variation in prevalence among different countries (7-65%). However, the ED condition is estimated to be at least twice as prevalent in Rottweilers (40-60%) than in German Shepherds (20%). Yet, in the Netherlands, the estimated ED prevalence in both breeds is low (7-14%). This literature search found no data that allowed to test if the subcategory of look-a-likes are less affected by the specific genetic disorders HD and ED than pedigree dogs. Earlier studies have indicated that purebred dogs are more at risk of genetic disorders than mixed breed dogs, but this need not be the case for every disorder-dog breed combination. The detection of subtle differences in the prevalence of genetic disorders, for example between pedigree dogs and look-a-likes, require data that are presently unavailable as look-a-likes and mixed breeds are not nationally monitored for ED and HD.
Prevalence and co-occurrence of hip dysplasia and elbow dysplasia in Dutch pure-bred dogs
Lavrijsen, I.C.M. ; Heuven, H.C.M. ; Meij, B.P. ; Theyse, L.F.H. ; Nap, R.C. ; Leegwater, P.A.J. ; Hazewinkel, H.A.W. - \ 2014
Preventive Veterinary Medicine 114 (2014)2. - ISSN 0167-5877 - p. 114 - 122.
german-shepherd dogs - uk labrador retrievers - bernese mountain dog - canine hip - control program - cost-analysis - inheritance - osteochondrosis - heritability - breeds
Hip as well as elbow dysplasia (HD, ED) are developmental disorders leading to malformation of their respective joints. For a long time both disorders have been scored and targeted for improvement using selective breeding in several Dutch dog populations. In this paper all scores for both HD and ED, given to pure bred dogs in the Netherlands from 2002 to 2010, were analyzed. Heritabilities and correlations between HD and ED were calculated for the 4 most frequently scored breeds. Heritabilities ranged from 0.0 to 0.37 for HD related traits (FCI-score, osteoarthritis, congruity, shape and laxity (Norberg angle); FCI: Federation Cynologique Internationale) and from 0.0 to 0.39 for ED related traits (IEWG score, osteoarthritis, sclerosis and indentation; IEWG: International Elbow Working Group). HD related traits showed high genetic and residual correlations among each other but were only to a minor extent correlated with ED related traits, which also showed high correlations among each other. Genetic correlations were higher than residual correlations. Phenotypic and genetic trends since 2001 for the four most scored breeds were slightly positive but decreasing overtime, indicating that selection over the past decade has not been effective. (C) 2014 Published by Elsevier B.V.
De Hollandse Herder: verwantschap en inteelt
Oldenbroek, J.K. ; Windig, J.J. ; Scholten, I. - \ 2013
Zeldzaam huisdier 38 (2013)3. - ISSN 0929-905X - p. 8 - 9.
hollandse herder - hondenrassen - dierveredeling - genetische bronnen van diersoorten - zeldzame rassen - dutch shepherd - dog breeds - animal breeding - animal genetic resources - rare breeds
De SZH heeft de Hollandse Herder tot ras van het jaar 2013 gekozen. Een van de redenen is dat er binnen dit oorspronkelijke Nederlandse hondenras in de fokkerij veel aandacht aan het voorkomen van inteelt wordt besteed. De resultaten van dit beleid zijn door het Centrum voor Genetische Bronnen Nederland (CGN) geanalyseerd.
Soil heterogeneity and soil fertility gradients in smallholder agricultural systems of the east african highlands
Tittonell, P.A. ; Muriuki, A. ; Klapwijk, C.J. ; Shepherd, K.D. ; Coe, R. ; Vanlauwe, B. - \ 2013
Soil Science Society of America Journal 77 (2013)2. - ISSN 0361-5995 - p. 525 - 538.
western kenya - resource-allocation - organic-matter - management - maize - variability - quality - productivity - indicators - tropics
Heterogeneity in soil fertility in these smallholder systems is caused by both inherent soil-landscape and human-induced variability across farms differing in resources and practices. Interventions to address the problem of poor soil fertility in Africa must be designed to target such diversity and spatially heterogeneity. Data on soil management and soil fertility from six districts in Kenya and Uganda were gathered to understand the determinants of soil heterogeneity within farms. Analysis of the variance of soil fertility indicators across 250 randomly selected farms (i.e., 2607 fields), using a mixed model that considered site, sampling frame, farm type, and field as random terms, revealed that the variation in soil organic C (6.5–27.7 g kg-1), total N (0.6–3.0 g kg-1), and available P (0.9–27 mg kg-1) was mostly related to differences in the inherent properties of the soils across sites (50 to 60% of total variance). Exchangeable K+ (0.1–1.1 cmol(+) kg-1), Ca2+ (1.5–14.5 cmol(+) kg-1), Mg2+ (0.6–3.7 cmol(+) kg-1), and pH (5.1–6.9) exhibited larger residual variability associated with field-to-field differences within farms (30 to 50%). Soil fertility indicators decreased significantly with increasing distance from the homesteads. When this variable was included in the model, the unexplained residual variances—associated with soil heterogeneity within farms—were 38% for soil C; 32% for total N; 49% for available P; 56, 49, and 38% for exchangeable K+, Ca2+ and Mg2+, respectively; and 49% for the pH. In allocating nutrient resources, farmers prioritized fields they perceived as most fertile, reinforcing soil heterogeneity. Categorization of fields within a farm with respect to distance from the homestead, and soil fertility classes as perceived by farmers, were identified as entry points to target soil fertility recommendations to easily recognizable, distinct entities.
The Identification and Interpretation of Differences in the Transcriptomes of Organically and Conventionally Grown Potato Tubers
Dijk, J.P. van; Cankar, K. ; Hendriksen, P.J.M. ; Beenen, H.G. ; Zhu, M. ; Scheffer, S.J. ; Shepherd, L.V.T. ; Steward, D. ; Davies, H.V. ; Leifert, C. ; Wilkockson, S.J. ; Gruden, K. ; Kok, E.J. - \ 2012
Journal of Agricultural and Food Chemistry 60 (2012)9. - ISSN 0021-8561 - p. 2090 - 2101.
gene-expression data - nutritional quality - safety assessment - dna-microarray - wheat - mapman - foods - vegetables - responses - genome
In the European integrated research project SAFEFOODS, one of the aims was to further establish the potential of transcriptomics for the assessment of differences between plant varieties grown under different environmental conditions. Making use of the knowledge of cellular processes and interactions is one of the ways to obtain a better understanding of the differences found with transcriptomics. For the present study the potato genotype Santé was grown under both organic and conventional fertilizer, and each combined with either organic or conventional crop protection, giving four different treatments. Samples were derived from the European project QualityLowInputFood (QLIF). Microarray data were analyzed using different statistical tools (multivariate, principal components analysis (PCA); univariate, analysis of variance (ANOVA)) and with pathway analysis (hypergeometric distribution (HGD) and gene set enrichment analysis (GSEA)). Several biological processes were implicated as a result of the different treatments of the plants. Most obvious were the lipoxygenase pathway, with higher expression in organic fertilizer and lower expression in organic crop protection; the starch synthase pathway, with higher expression in both organic crop protection and fertilizer; and the biotic stress pathway, with higher expression in organic fertilizer. This study confirmed that gene expression profiling in combination with pathway analysis can identify and characterize differences between plants grown under different environmental conditions
The process of setting micronutrient recommendations: a cross-European comparison of nutrition-related scientific advisory bodies
Timotijevic, L. ; Barnett, J. ; Brown, K. ; Shepherd, R. ; Fernandez-Celemin, L. ; Domolki, L. ; Ruprich, J. ; Dhonukshe-Rutten, R.A.M. ; Sonne, A.M. ; Hermoso, M. ; Koletzko, B. ; Frost-Andersen, L. ; Timmer, A. ; Raats, M.M. - \ 2011
Public Health Nutrition 14 (2011)4. - ISSN 1368-9800 - p. 716 - 728.
folic-acid - health-policy - risk - science - perspectives - expertise - politics - context - trial
Objective - To examine the workings of the nutrition-related scientific advisory bodies in Europe, paying particular attention to the internal and external contexts within which they operate. Design - Desk research based on two data collection strategies: a questionnaire completed by key informants in the field of micronutrient recommendations and a case study that focused on mandatory folic acid (FA) fortification. Setting - Questionnaire-based data were collected across thirty-five European countries. The FA fortification case study was conducted in the UK, Norway, Denmark, Germany, Spain, Czech Republic and Hungary. Results - Varied bodies are responsible for setting micronutrient recommendations, each with different statutory and legal models of operation. Transparency is highest where there are standing scientific advisory committees (SAC). Where the standing SAC is created, the range of expertise and the terms of reference for the SAC are determined by the government. Where there is no dedicated SAC, the impetus for the development of micronutrient recommendations and the associated policies comes from interested specialists in the area. This is typically linked with an ad hoc selection of a problem area to consider, lack of openness and transparency in the decisions and over-reliance on international recommendations. Conclusions - Even when there is consensus about the science behind micronutrient recommendations, there is a range of other influences that will affect decisions about the policy approaches to nutrition-related public health. This indicates the need to document the evidence that is drawn upon in the decisions about nutrition policy related to micronutrient intake
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