Modelling irrigation and fertiliser use for chlorophyll production

Chlorophyll is a natural coloring extract used extensively in the food and pharmaceutical industries. In Europe, most chlorophyll is produced commercially from rainfed grassland production in eastern England. This paper describes a biogeochemical modeling study to assess the potential yield benefits associated with switching from rainfed to irrigated production. The research is in response the impacts of recent summer droughts on yield coupled with risks regarding climate change, rainfall reliability and long-term viability of rainfed production. The Denitrification-Decomposition model was calibrated and validated using multiple field data (n = 47) from 2000 to 2009 for a tall fescue grass (Festuca arundinacea) to simulate a range of irrigation and fertilizer management regimes on yield (annual and individual yield per cut). For chlorophyll production, a schedule combining 300 mm year−1 irrigation with 300 kg N ha−1 was shown to provide the highest average yield (an uplift of +62% above current levels). Switching from rainfed to irrigated production could also potentially halve (54%) current levels of fertilizer application. The implications for reducing environmental impacts from nitrate leaching are discussed

Assessment of AquaCrop Model in the Simulation of Seed Yield and Biomass of Italian Ryegrass

Given that the optimal sowing rate and inter-row spacing of Italian ryegrass raised for seed have not been determined, the objective of this research was to assess the effect of crop density on biomass and seed yields under different climate conditions, applying the AquaCrop model. The data came from experiments conducted under moderate continental climate conditions at Stitar (Serbia) and Mediterranean climate conditions at Cukurova (Turkey). At Stitar, there were three different inter-row spacings (high (Sd), medium (Sm), and low (Sw) crop densities), while at Cukurova there was only high crop density (Sn). In the calibration process, the initial canopy cover, canopy expansion and maximal canopy cover were adapted to each crop density, while the other conservative parameters were adjusted to correspond to all climate conditions. Calibration results showed a very good match between measured and simulated seed yields; the values of the coefficient of determination (0.922). The biomass simulationwas very good for Cukurova (R2=0.97), but somewhat poorer for Stitar (R2=0.72). Other statistical indicators were high such as Willmott index of agreement of both the calibrated and validated data sets, for both study areas >0.916 and normalized root mean square error (NRMSE) in the range from 9%–18%. The AquaCrop model was found to be more reliable for Italian ryegrass biomass and seed yield predictions under mild winter climate conditions, with adequate water supply, compared to moderate climate and water shortage conditions

Development of a transmission model for gastro-intestinal nematode infections in cattle

Gastro-intestinal nematodes (GIN) are one of the great threats for farmed ruminants worldwide. Mathematical models that simulate the dynamics of GIN infections have great potential to provide improved understanding of parasite epidemiology under altered conditions and to underpin the development of alternative parasite control strategies. In chapter 1, first the general epidemiology of GIN in ruminants is discussed to provide insight in the dynamics and underlying drivers of the host-parasite interaction. Host immunity, weather and farm management are shown to be significant drivers of parasite epidemiology. The second part of chapter 1 discusses the evolution of both hosts and parasites during the past half century, the expected trends to come and the underlying drivers of these anticipated changes. Finally, the value of transmission models to improve our understanding of parasite epidemiology under changing conditions and to facilitate the development of control strategies is discussed. Key terms encountered in the field of parasitic disease modelling are explained and the development process of these models is given. An overview of the available models for GIN infections in ruminants provides insights into the needs for this field of research. The overall objective of this PhD project was to develop a generic framework for a mechanistic transmission model that simulates the parasitic phase of the GIN lifecycle in farmed ruminants. Further, facilitation of the collection of pasture larval count data, a key input parameter, was explored. Chapter 2 quantifies the main life history traits of the parasitic phase for O. ostertagi and Cooperia oncophora through systematic review and meta-analysis and assesses the potential influences associated with the effect of immunity on these traits. The main parameters determining parasite density during the parasitic phase are the larval establishment rate or pre-adult mortality, the hypobiosis rate, adult mortality and female fecundity. A systematic review was performed covering studies from 1962 to 2007, in which helminth-naïve calves were artificially infected with O. ostertagi and/or C. oncophora. The database was further extended with results of unpublished trials conducted at the Laboratory for Parasitology of Ghent University, Belgium. Overall inverse variance weighted estimates were computed for each of the traits through random effects models. To our knowledge, this systematic review is the first to summarize the available data on the main life history traits of the parasitic phase of O. ostertagi and C. oncophora and provides novel estimates for the parameterization of life cycle-based transmission models. Chapter 3 presents a flexible model framework (GLOWORM-PARA) developed for the parasitic phase of GINs infecting ruminants. The framework can be applied to a range of GIN species and is parameterised and thoroughly validated for first season grazing calves infected by two species that are of major importance in cattle, i.e. O. ostertagi and C. oncophora. To our knowledge, no previous attempt has been made to model C. oncophora. For O. ostertagi, GLOWORM-PARA incorporates important improvements to the existing models such as data-driven parameterisation of the rate of acquisition of immunity based on cumulative exposure and the incorporation of host grazing behaviour. Both the parameterisation and validation of these models were backed by extensive datasets obtained from various sources and acquired over decades of parasitological research. This represents the most comprehensive and thorough validation of GIN models to date. The model was able to generate the general patterns of faecal egg counts seen in first season grazing cattle throughout the grazing season. The estimation of the immune response rate from field observations was preferred over fitting the immune response rate to get meaningful predictions of acquired immunity. Linear regression of predictions against observations showed that incorporating host grazing behaviour resulted in an important improvement of model performance and is therefore likely to be important in the transmission of GIN. Assessing levels of pasture larval contamination is frequently used to study the population dynamics of the free-living stages of parasitic nematodes of livestock and the abundance of infective larvae (L3) on pasture is an important input parameter for GLOWORM-PARA. Direct quantification of L3 on herbage is the most applied method to measure pasture larval contamination, but herbage collection remains labour intensive. Chapter 4 compares two different sampling methods in terms of pasture larval count results and time required to sample, to assess the amount of variation in larval counts at the level of sample plot, pasture and season, respectively and to calculate the required sample size to assess pasture larval contamination with a predefined precision using random plots across pasture. Chapter 5 discusses the results and limitations of this work along with opportunities for future research. The integration of GLOWORM-PARA with a complementary model which simulates the free-living stages of GINs, GLOWORM-FL, should lead to a full life cycle based model in further research. To improve the link between the free-living and the parasitic phase, future research needs to assess the daily faecal production based on easy-to-use predictors such as body weight. The incorporation of a component that models grass growth can provide the needed complexity to account for different farm management situations and to underpin meaningful larval infection rates. Several questions remain concerning the implementation of transmission models as site-specific decision support tools for nematode control. A proposed approach to achieve better and more applied modelling is to gradually refine generic models with the needed amount of biological detail. Obtaining relevant and realistic parameter estimates and integrating these in generic models might be a good step to achieve the right balance between generality and specificity. Efforts to facilitate data quality and collection should be encouraged, as this is fundamental to make progress and underpins the future implementation of models. Future research should also focus on how to improve knowledge transfer to the end-users and to identify user-needs

Provision of soil information for biophysical modelling

This thesis is concerned with the generation of a framework for addressing soil data needs, specifically for biophysical modelling. The soil system is an important ecosystem actor, supporting most of the worlds' food production and being the major terrestrial carbon stocks, thereby information about it is crucial for management and policy making. To provide this information, it is important to deliver information of the highest possible quality; thus the need to define guidelines to standardise, not only the methodologies, but the minimum requirements that information must meet. In this project, providing soil data is addressed in two ways. The first scenario investigates the use of soil information to predict other soil properties, using pedotransfer function (PTFs). In the second scenario, it is assumed that the end-user does not have extra information about the soil properties at a specific location. In this case, the use of existing soil maps is a traditional solution, thus a framework for generating maps at national/continental scale, using digital soil mapping (DSM) techniques, is proposed

Evaluation of risk based microbiological criteria for Campylobacter in broiler carcasses in Belgium using TRiMiCri

Campylobacteriosis is the most frequently reported foodborne zoonosis worldwide. Consumer´s exposure to Campylobacter might be reduced by establishing a microbiological criterion (MC) for Campylobacter on broiler meat. In the present study two possible approaches were evaluated, using the freely available software tool for risk based microbiological criteria TRiMiCri (http://tools.food.dtu.dk/trimicri). The first approach was the traditional one that implies a microbiological limit (ML-MC) and the second one which is based on the relative risk estimate (RRL-MC). The analyses were based on Campylobacter quantitative data collected from 28 Campylobacter positive bathes processed in 6 Belgian broiler slaughterhouses. To evaluate the performance of ML-MC, n=6, different c (0,1,2) and m (100,1 000,10 000) were used. Results showed that more than 90% of Campylobacter positive batches were not complying with strict ML criteria based on the m=100 for all applied combination of c. The RRL approach requires a baseline risk which was estimated based on the Campylobacter baseline data collected in Belgium in 2008. Approximately 60% of evaluated Campylobacter positive batches account for higher risk than the baseline risk. For both approaches, application of less stringent criteria results in lower percentage of NC and higher minimum relative residual risks (MRRR; it refers to the change in risk when all batches are sampled and all NC batches undergo treatment that effectively eliminates Campylobacter so they are replaced by zero risk batches). It was also observed that the number of samples (n) had little effect on risk estimates. Additionally, the results from ML-MC and RRL-MC follow the same curve when plotting percentage of NC against MRRR. However, for RRL-MC the percentage of NC batches and MRRR was lower and higher, respectively. To conclude, obtained results indicate that TRiMiCri is a useful and user friendly tool to make a risk based decision on the choice of the MC

Consideration of Abiotic Natural Resources in Life Cycle Assessments

The book contains a collection of articles dealing with how the extraction of mineral resources can be considered in environmental analyses such as Life Cycle Assessment (LCA). The consumption of resources, e.g., metals, is increasing strongly worldwide. This is associated with more energy use; environmental pollution; and social, economic, and political consequences. An increase is also expected for the coming decades. At the same time, modern products and technologies, even in the field of renewable energies, require a large number of critical raw materials. A crucial question here is the exhaustibility of natural resources. What is the relevance of resource depletion today? Must a geological shortage of metals be expected in the foreseeable future? How could such a thing be considered in the LCA of products and weighed against other environmental aspects? The articles in question have been written over the past three years by leading experts in both geology and environmental sciences and show the breadth of the controversial discussion