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Nutrient digestibility and predicting the energy content of pig feeds
No full textWith 11 million slaughters per year, pigs are the most important production animal in Belgium. Feed is
the biggest cost factor in pig farming, especially the energy component. The aim of feed formulation
and production is to meet the nutrient requirements of pigs under the constraint of the available feed
ingredients (Chapter 1). Correct energy and nutrient evaluation is critical, especially given the increasing
amounts of fiber-rich co-products from human food production that are being included in pig feed.
Another difficulty is that feed digestibility and utilization depend on many factors related to either the
animal or to its growing conditions (Chapter 1). The net energy (NE) reflects best the true available
energy for pigs, but NE determination requires time-consuming and expensive in vivo digestibility
experiments. Potential methods to estimate NE in feeds include the use of tabular values of ingredients,
empirical models based on chemical parameters and/or the in vitro digestibility of organic matter and
near infrared spectroscopy (NIRS).
The following research objectives (Chapter 2) were defined:
• Study the interactions between fat and fiber level on nutrient digestibility and energy utilization
of pig feeds (Chapter 4)
• Evaluate the usefulness and accuracy of NIRS calibrations based on spectra from pig feed and
feces to predict their chemical composition as well as nutrient digestibility and NE (Chapter 5)
• Compare a) the use of feed tables, b) empirical models based on chemical and in vitro analyses
and c) NIRS calibrations based on feed and feces spectra for their accuracy in predicting feed
quality and more particularly NE, their applicability in practice and their limits (Chapter 6)
Data related to these objectives were gathered via three in vivo digestibility trials. In Chapter 3, the
protocol and details of the various methods used are described and justified. Main conclusions are: the
acid insoluble ash (AIA), that is naturally present in pig feeds, is reliable as marker to determine nutrient
digestibility via spot sampling of feces; AIA and TiO2 are equally reliable as external markers; the NE
of a feed increases with 0.0021 MJ per kg higher bodyweight; once-daily sampling and pooling feces
from two or three animals per pen is sufficient to determine in vivo digestibility.
The interactions between fiber-rich co-products and fat were investigated, as well as their possible
impact on nutrient digestibility and NE (Chapter 4). For this experiment, a low fiber (LF) and a high
fiber (HF) diet were formulated. From these two basal diets, 8 additional diets were derived by adding
20 or 40 g/kg of either pig fat or soy oil. Compared to LF diets, HF diets had a lower (P<0.05)
standardized digestibility for all nutrients except for NDF. However, higher fiber levels in the diet did
not affect the digestibility of the added fat. The standardized digestibility of fat in the HF diets with
added fat was higher (P<0.05) than that of the non-fat supplemented basal diet, whereas no significant
(P>0.05) differences in fat digestibility among the LF diets were observed. Increasing fat level appeared
to negatively affect the fat-free organic matter digestibility, in particular NDF. On the other hand, the
negative effect of fat addition on digestibility and NE was relatively small in comparison to the extra
energy added by the fat. Therefore, no special consideration should be given when adding extra fat to a
fiber-rich diet to meet pigs’ energy requirements.
For prediction of the chemical composition of pig feed and feces, as well as nutrient digestibility and
NE, the usefulness and accuracy of NIRS calibrations based on combined spectra were investigated
(Chapter 5). Near infrared spectroscopy appeared to accurately predict (residual prediction deviation,
RPD>3; R²>0.8) most organic components and moisture content of pig feed and freeze-dried feces. The
NE was better estimated using feed spectra than feces spectra, with a standard error of cross validation
(SECV) of 0.33 and 0.46 MJ/kg, respectively. Combining feed and feces spectra resulted in an overall
better estimation of the digestibility and NE, especially with merging (SECV=0.26 MJ/kg) and
subtracting (SECV=0.27 MJ/kg). Finally, this study highlighted the importance of the cross-validation
method when the dataset contains several feces spectra (alone or combined) from the same feed. Indeed,
cross-validation may lead to over-optimistic results when the group to be validated contains spectra that
are not independent.
The use of tabular values, empirical models and NIRS to estimate nutrient composition and NE were
compared (Chapter 6). This evaluation was based on 62 compound feeds, and 28 among them had known
ingredient composition. In addition to the accuracy of each approach, their applicability in practice and
practical limitations were compared. Feed tables predicted most chemical components accurately
(R²>0.90), with exception of crude ash, sugar, acid detergent lignin and moisture, the latter being
strongly underestimated (-16 g/kg). The standard error of estimate (SEE) for NE with tabular values
amounted to 0.29 MJ/kg. Using empirical models based solely on chemical parameters resulted in a SEE
of 0.21 MJ/kg. Incorporating in vitro digestibility resulted in a decrease of SEE to 0.18 MJ/kg. The SEE
of a NIRS calibration based on feed spectra alone resulted in a SEE of 0.33 MJ/kg, whereas the
combination of feed and feces spectra decreased this error to 0.26 MJ/kg. The use of feed tables allows
a cheap and fast estimation of the chemical composition and NE, but it is only suitable for feeds of
known and common ingredient composition and is not so accurate. The use of empirical models allows
to accurately estimate the NE of feeds even with unknown composition, but relies on quite expensive
and time-consuming analyses. Finally, NIRS calibration based on feed and feces spectra allows for a
fast estimation of NE, but is less precise than empirical models and requires a specific sample
preparation.
Finally, the general discussion, conclusions and recommendations are presented (Chapter 7), where the
results are discussed in depth and put into perspective. Important attention points are the limitation of
NIRS accuracy for evaluating compound feeds due to the complexity and heterogeneity of the matrix;
the error (0.033 MJ/kg) in the determination of the in vivo NE reference value due to sampling, animal
variation and laboratory analysis, which represents the maximum achievable accuracy for the predicting
models; and the practical limitation and applicability of each method. Future research could consider a
combination of estimation methods and it would be interesting to integrate the energy and protein (amino
acid) balance
Sponge-bed trickling filters for nitrogen removal from anaerobically treated sewage : mechanistic insights and practical experiences
No full textThe Latin American region still struggles with basic sanitation problems that developed nations have long surpassed. Hence, proper technologies should be considered for increasing sewage treatment coverage, entailing process robustness, operational simplicity, and low capital and operational expenditures. In this way, anaerobic sewage treatment has been widely applied in the region, mainly in Brazil, fulfilling a major role of organic carbon abatement. As an anaerobic process, intrinsic limitations thus exist concerning nitrogen removal. Among the consolidated post-treatment options, trickling filters have been extensively applied due to their remarkable effluent quality in terms of residual organic carbon removal.
Trickling filters are typically filled with rocks as a support material for the attached biomass growth (hereafter termed rock-bed trickling filters). Research has been done on improving the performance of such reactors for carbon and nitrogen removal by replacing rocks with a sponge-based support media, the so-called sponge-bed trickling filters (SBTFs). A core advantage of the SBTFs lies in the high capacity of biomass retention, allowing for the colonization of slow-growing bacteria, such as those involved in the nitrogen cycle. Moreover, implementing SBTFs reduces land requirements and possibly saves construction costs compared with rock-bed trickling filters, as secondary settlers can potentially be eliminated.
This doctoral research work focuses on the use of sponge-bed trickling filters for the post-treatment of anaerobic effluents. The overall goal is to establish highly efficient nitrogen removal, dealing with residual organic carbon and integrated with the abatement of dissolved gases in the anaerobic effluent. Demo-scale experimental studies are thus combined with mathematical modelling and simulation work.
Chapter 1 gives a general introduction, outlining consolidated technologies for the post-treatment of UASB reactor effluents. Research challenges are summarized considering the (i) design of SBTFs following anaerobic sewage treatment, (ii) the relevance of influent characteristics, (iii) the need for long-term experimental assessments, and (iv) nitrogen removal pathways at the core of this thesis, namely: conventional nitrification-denitrification and partial nitritation-anammox (PN/A). Additional autotrophic nitrogen removal processes are outlined based on the link with dissolved gases abatement (i.e., denitrifying anaerobic methane oxidation (DAMO) and sulfur-based denitrification (SBDN)). In Chapter 2, a literature review is carried out on the design and operation of trickling filters post-UASB reactors. Practical experiences are critically compiled to derive the most important design criteria and relevant influent characteristics to predict process performance for organic matter removal. An outlook is given on process configurations for improving nitrogen removal via heterotrophic denitrification or partial nitritation-anammox. Based on the consolidated design criteria, a demo-scale SBTF was built and operated under the scope of Chapter 3, which deals with the relevance of influent characteristics, most specifically inorganic carbon limitation during nitrogen conversions. A 300-day monitoring campaign showed that a lack of inorganic carbon impaired nitrification, and nitrite oxidizing bacteria (NOB) were less affected. Bicarbonate was added as a state variable to properly describe inorganic carbon limitation, and sigmoidal kinetics were applied. The resulting model was able to capture the overall experimental behaviour.
In Chapter 4, the developed model was used to mechanistically assess the effect of key reactor and kinetic parameters controlling nitrogen conversions in SBTFs in the long-term. A simulation study was performed considering the key reactor-specific parameters that influence the formation of nitrogen gas via heterotrophic denitrification or anammox process, identified via sensitivity analysis. The results support that the interplay between the oxygen transfer coefficient, external mass transfer resistance, biofilm thickness, and specific surface area of the sponge-based support media influences the optimum oxygen concentration to sustain ammonium oxidizing bacteria (AOB) activity without compromising anammox bacteria growth. Particular attention was paid to process start-up, which was identified as a primary bottleneck. Standalone biomass inoculation strategies for promoting a fast partial-nitritation anammox are ineffective if inhibitory oxygen levels remain at the biofilm-liquid interface. Effluent recirculation coupled to sewage by-pass led to a quick establishment of heterotrophic denitrification; however, it was limited at approximately 55% total nitrogen removal. Overall, high performance for both processes (i.e., heterotrophic and autotrophic) relies on particular reactor-specific parameters. In Chapter 5, a long-term experimental comparative study was performed in two SBTFs operating in parallel following a UASB reactor treating real sewage. Effluent recirculation to the top compartment of the SBTF showed a rapid increase in total nitrogen removal efficiency. Nevertheless, further supplying organic carbon via sewage by-pass was detrimental to AOB activity. Stepwise ventilation strategies decreased volumetric ammonium conversion rates; however, nitrate remained the main end-product throughout the monitoring period, meaning NOB repression was ineffective. The model developed under Chapter 3 was further used to gain process insight based on the observed experimental data. Results indicated that dissolved gases in the anaerobic effluent likely hampered AOB during restricted ventilation of the SBTF. Furthermore, under the observed temperature range, the long-term ingrowth of anammox bacteria tends to be constrained.
In Chapter 6, the fate of dissolved methane and H2S in the anaerobic effluent during nitrogen conversions in SBTFs was assessed. The developed model (Chapter 3) was expanded to account for stripping and biological conversion processes of dissolved methane and H2S. Simulations showed that nearly all gases were stripped from the anaerobic effluent at the top compartment of the SBTF. If a (partially) closed SBTF is applied, stripping is therefore decreased, and practically all methane and H2S were oxidized by methane oxidizing bacteria (MOB) and sulfide oxidizing bacteria (SOB), respectively. Nevertheless, total nitrogen removal efficiencies were impaired due to the competition for oxygen, which was generally lost by AOB. Simulations also did not sustain the occurrence of DAMO or SBDN. Further experimental tests with a closed SBTF fed with desorbed anaerobic effluents showed that nitrogen conversions are potentially better handled if methane and H2S are removed upfront.
In Chapter 7, the main findings are revised involving both mechanistic insights and practical experiences. Perspectives concerning practical implications and research needs are provided, and take-home messages conclude this thesis
CO2-assisted propane dehydrogenation over Pt-based catalysts : looking inside via in situ X-ray absorption spectroscopy
No full textPropylene is the basic raw material for the production of polypropylene, acrylonitrile, propylene oxide and other industrial products. Propane dehydrogenation (PDH) is an important synthesis route towards selective propylene production. It is an endothermic equilibrium-limited reaction, for which catalyst deactivation through carbon formation and sintering is an issue. Pt-based bimetallic catalysts are typically employed for this process as the addition of the promoter element leads to improved resistance to carbon formation and sintering.
The first part of this thesis investigates the potential applicability of CO2 in the feed along with propane as CO2-PDH. CO2 assists in shifting the equilibrium towards product formation through the reverse water gas shift reaction and suppresses carbon formation through the reverse Boudouard reaction. Three different promoter elements were explored and a strong correlation was established between the promoter’s potential to oxidation by CO2 and its activity towards CO2-PDH. The second part of this work looks into the potential benefit of an Al2O3 coating applied by Atomic Layer Deposition on Pt-Ga catalysts for PDH. Advanced characterization techniques, such as X-ray Absorption Spectroscopy, Small Angle X-ray Scattering, CO-DRIFTS, etc., were utilized to answer the research questions for both parts
Assessing, creating and using knowledge graph restrictions
No full textIn 2020 was het aantal digitale bytes 40 keer groter dan het aantal sterren in het waarneembare heelal. Toch wordt het beantwoorden van eenvoudige vragen met deze data bijna onmogelijk, omdat elke applicatie data een beetje anders opslaat en het niet duidelijk is wat wat is. Een oplossing voor dit probleem is dat data van verschillende applicaties worden gekoppeld aan hergebruikbare definities op het web. Juist daarvoor worden zogenaamde Kennisgrafen gebruikt. Maar Kennisgrafen hebben echter begrenzingen nodig om uit te drukken wat zinvolle verbindingen zijn tussen data, anders kun je met je auto trouwen of de lucht opdrinken. Bovendien vereist een vlotte gegevensuitwisseling tussen applicaties lokale beperkingen om de kwaliteit te waarborgen. Ook als twee applicaties dezelfde definitie van "een persoon" delen, heeft een webshop ook het adres van de persoon nodig om een bestelling af te leveren, maar een bier-rating app niet. Deskundige hebben ondersteuning nodig bij het hergebruiken van Kennisgrafen. Dit doctoraat onderzocht hoe deskundige kunnen worden ondersteund bij het beoordelen van begrenzingen en maken van beperkingen voor Kennisgrafen. Hoe begrenzingen en beperkingen kunnen worden gebruikt, werd aangetoond in een project voor het bewaren van sociale media met de Koninklijke Bibliotheek van België
Tools for bridging discovery proteomics and pandemic preparedness
No full textProteomics or the large-scale study of proteins is critical in the study of biological systems, because proteins mediate the metabolic and regulatory mechanisms of all living organisms. Liquid Chromatography coupled to Mass Spectrometry (LC-MS) has become the method of choice for the accurate identification and quantification of the protein complement. In recent years, label-free data-independent acquisition (DIA) quantification strategies have tremendously evolved, which makes them an attractive alternative over traditional data-dependent acquisition (DDA) methodologies. Unfortunately, the loosened mass selection criteria in DIA requires prior generation of exhaustive spectral libraries in DDA to extract peptides and proteins from the DIA data. In this dissertation, the use of machine learning algorithms that predict retention time and fragment ion intensity were explored as an alternative to experiment specific libraries. However, by lack of a single dataset covering the most commonly applied data acquisition strategies in proteomics, a comprehensive LFQ benchmark dataset, covering both DDA and DIA methodologies, on 6 different instrumental platforms was created to overcome this hurdle. As the SARS-CoV-2 pandemic drastically demonstrated the lack of pandemic preparedness, the use of LC-MS was explored as an orthogonal test procedure. For this, the previously developed predicted spectral library workflow was applied on DIA data of a small cohort of Covid-19 confirmed patient samples, followed by translating the target peptides and their corresponding fragment ions into a targeted multiple reaction monitoring (MRM) assay. Finally, an anti-peptide antibody approach was incorporated to improve the dynamic range and the repeatability of the quantification, while at the same time allowing the assay to be uncoupled from the viral transport medium
Interpreter-mediated police interviewing cum drafting : interpreters' access to and handling of the written record
No full textIn the Belgian judicial system, written police records are documents of paramount
importance. They constitute the textual representation of interviewees’ statements and
are further along in the criminal law process treated as actual representations of the
interaction during the police interview. Although text drafting is commonly the sole
responsibility of the recording police officers and usually performed in silence, in some
cases, interpreters are granted access to the text of the written record while it is being
drafted. Interpreters’ text access may be achieved in various ways: through police
officers’ computer screens or through police officers reading aloud while typing or what
they just have typed. Decisions interpreters make on handling their text access are bound
to have an impact on the final text of the written record. This dissertation aims at
describing various ways in which interpreters are granted text access and at analysing
how interpreters handle their text access. When having text access, interpreters may
decide to transfer their text access to interviewees by sight translating from the police
officer’s computer screen or by rendering the police officer’s reading turns. Granting
interviewees access to the text of the written record enables them to negotiate both
content and wording of that written record. It may allow them to detect errors and solve
problems, which may improve the quality and accuracy of the written record.
Interpreters however do not always transfer their text access to interviewees.
Interpreters’ text access to the computer screen is not often transferred to interviewees,
as interpreters seem reluctant to use the text on the screen as a source to initiate sight
translation sequences. When text access is explicitly granted by police officers reading
aloud when typing, interpreters are expected to render these reading or typing aloud
turns, making the content of these turns available to interviewees, allowing the latter to
negotiate the content and wording of the text. Interpreters however do not always render
these turns and are seen to involve themselves in the text negotiation and production
process. Failure to render these turns however denies the interviewee the opportunity to
negotiate the text, which may be detrimental to their case. Interpreters’ decisions on how
to handle their text access thus have a significant influence on the text drafting process
Electrophysiological markers of depression symptomatology and suicidality
No full textMajor Depressive Disorder (MDD) is a prevalent, severe, and debilitating psychiatric illness that can be described by a wide range of symptoms such as a persistent sad mood, a loss of experiencing pleasure, impaired concentration, and even suicidal behaviors. An accurate and rapid diagnosis of MDD is necessary to select appropriate treatment strategies in order to maximize a favorable clinical outcome and minimize the chances of a chronic- or recurrent illness course. Contemporary diagnostic tools such as self-report questionnaires, have been found to be inadequate for accurately screening depressed individuals and improving general clinical outcomes within at risk groups. Consequently, there is a great need for depression biomarkers and neuroimaging research has been dedicated to find such markers. Despite the great strides made by functional Magnetic Resonance Imaging (fMRI) studies to elucidate the neural underpinnings of depression symptoms, none of those discoveries have resulted in clinical diagnostic tools that can be applied in psychiatric hospitals. The primary reason for this discrepancy is related to the significant costs associated with MRI scanners, compelling hospitals to prioritize MRI use for the imaging of serious medical conditions such as cancer. Fortunately, the electroencephalogram (EEG) is a relatively cost-effective, accessible, and time-efficient neuroimaging tool that can be routinely applied for both the diagnosis and treatment of neuropsychiatric disorders. Nevertheless, studies that have investigated whether EEG markers of depression symptomatology and suicidality can serve as clinically usable biomarkers are either remarkably scarce or lack clinical validity. Therefore, the primary objective of this dissertation was to search for reliable and clinically valid electrophysiological markers of depression symptoms including suicide, based on robust findings from the extensive fMRI depression literature.
The study discussed in chapter 2 demonstrated how depressed patients with a recent history of suicide attempt or suffering from suicidal ideation, exhibit distinct spectral power topographical scalp distributions when compared to non-suicidal depressed controls. Moreover, these suicide-specific spectral power abnormalities were source localized within brain regions consistent with the neuroimaging literature concerning suicide, implying that EEG resting state spatial-frequency power characteristics could become a potential biomarker to assess suicide risk. In chapter 3, we attempted to replicate findings from prior fMRI functional connectivity studies that demonstrate how depressed patients exhibit hyper-connectivity between nodes of the Default Mode Network (DMN) and the subgenual Anterior Cingulate Cortex (sgACC), and may represent maladaptive rumination. We therefore tested the hypothesis whether this enhanced DMN–sgACC functional connectivity is present in the EEG resting state of depressed patients in remission (rMDD), and whether this DMN–sgACC hyper-connectivity signifies a vulnerability for future MDD episodes through its association with maladaptive rumination. Our EEG source-space functional connectivity analysis revealed that rMDD patients continue to exhibit enhanced connectivity between the Posterior Cingulate Cortex (PCC) and the sgACC when compared to matched healthy controls. In addition, this elevated PCC–sgACC connectivity had a significant positive association with maladaptive rumination, which was independent of rMDD patients’ current depression- and anxiety scores, denoting that elevated PCC–sgACC connectivity may be an electrophysiological marker that can identify individuals at risk for depression. Lastly, the study described in chapter 4 investigated whether the EEG resting state of currently depressed patients contained aberrant functional connectivity between nodes of the cognitive control network (CCN) and nodes of the affective network (AN), and whether this aberrant connectivity has potential as an electrophysiological diagnostic marker of MDD. Our analysis revealed how depressed patients have reduced functional connectivity between the CCN and AN when compared to healthy controls and this diminished CCN–AN connectivity is significantly correlated with MDD patients’ lifetime number of depression episodes, implying that attenuated CCN–AN connectivity may signify a recurrent illness course. Furthermore, aberrant CCN–AN connectivity seems promising as an electrophysiological diagnostic marker for depression since, a machine learning classifier was able to successfully identify 80% of depressed patients and 89.5% of healthy controls when the algorithm was solely trained on participants’ CCN–AN connectivity values.
Taken together, the scientific work discussed in this doctoral thesis suggest that the EEG is capable to translate the findings from fundamental neuroimaging depression research into promising electrophysiological markers that provide the clinical utility and validity, needed for use in the psychiatric practice
Biogeochemical cycles along an elevational transect in Rwenzori montane forests of Uganda
No full textIn his PhD research, Joseph Okello used an elevational gradient transect approach to unravel the effect of climate gradient and in situ short-term climate warming on carbon (C), nitrogen (N) and phosphorus (P) biogeochemistry in Rwenzori montane forests of Uganda. In the first objective, Joseph Okello studied aboveground C stocks, woody and litter productivity. In the second objective, he studied the effect of long-term climate gradient along elevation on soil and leaf C, N & P contents and subsequently investigated the response of soil C, N & P to in situ soil warming, achieved following soil mesocosms translocation down-slope. In the third objective, he investigated the temperature sensitivity of carbon dioxide (CO2) emission and response to in situ and lab-based warming. Here, Joseph specifically studied the heterotrophic soil CO2 emission rates and the temperature sensitivities (Q10) of heterotrophic soil CO2 emission rates. Finally in the fourth objective, he investigated the fluxes of methane (CH4) and nitrous oxide (N2O) along the elevational gradient under in situ and lab-based conditions. Generally the results indicated that montane forests store similar amounts of aboveground C along elevation and not per se less productive than lower elevation forests. Further, soil C, N and P increased with elevation. Climate warming undermined the climate mitigation potential of the soil by increasing soil organic matter turnover and reducing soil organic matter recalcitrance. Therefore, given the uniqueness of montane forests, their conservation should be prioritised