PhD, EngD and MSc by research theses (SWEE)

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  • ItemOpen Access
    Supply chain management for a policy-led transition from fossil fuels to renewable energy: contributions to Indonesia's national energy roadmap.
    (Cranfield University, 2023-05) Widya Yudha, Satya; Longhurst, Philip; Tjahjono, Benny
    The growing awareness of global warming has resulted in the need for more sustainable energy production. Facilitating the transition from fossil fuels to renewable energy sources necessitates a thorough examination of the energy sector, starting from the identification and analysis of the current energy regime, understanding the energy potentials, and ultimately moving towards the analysis of the preferred clean energy. The ultimate goal of this research is to propose comprehensive yet feasible strategies for policy recommendations as well as to facilitate and accelerate the transition from fossil fuel to renewable energy sources, by incorporating the supply chain management principle, using Indonesia’s energy sector as the framework. This research is divided into a series of research starting with PESTLE and stakeholder analysis of the energy fossil sector in Indonesia and then followed by that of the renewable energy sector. Following these identifications, these stakeholders are then involved in recounting the renewable energy sector as well as determining the most suitable renewable energy in Indonesia, through qualitative approaches. In this research, geothermal energy is selected as the most suitable renewable energy in Indonesia. Following this, the research continued to illustrate the complex nature of geothermal development in Indonesia through model conceptualization by employing the System Dynamics (SD) modelling technique. The SD model visualized the whole process, elements, and stakeholders that are incorporated within the geothermal system, including some of the most important factors that can act as key enablers in geothermal development such as geothermal investment, infrastructure, upstream data, environmental aspects, incentive, pricing, permit, and public acceptance. The research is continued by employing the supply chain principles and combining them with the transition framework, through a Multi-Level Perspective (MLP). The MLP model showcases the interaction between three levels, namely the socio-technical landscape, regime, and niche innovations as well as the transition pathways from fossil fuel to renewable energy. In this study, the main keys to the transition depend heavily on many aspects such as incentives and schemes. This research provides novelties that consist of (1) MLP new data, where it is not just a framework, (2) a new method, where it selects, links, and synthesizes different methods from PESTLE, Stakeholders analysis, SD, MLP into a toolkit that can be used a reference model for other transition cases and (3) transferability, where the research is transferrable to other sustainable transition problems where policy-led development and implementation have relevance such as the digitalization of hospitals, sustainable tourism, etc. This research could be beneficial for the stakeholders and it has high credibility in terms of data source. This research is strongly relevant to international agreements that can accelerate the energy transition.
  • ItemOpen Access
    New insights into drinking water treatment, storage and distribution systems using Flow Cytometry.
    (Cranfield University, 2022-09) Palazzo, Francesca; Hassard, Francis; Jarvis, Peter
    Excessive microbial regrowth in drinking water distribution systems (DWDS) signifies compromised biostability. In chlorinated DWDS, diminished chlorine residual and substantially elevated water age or transit times can pose risks to water safety. This study delves into microbial community dynamics within DWDS by analysing samples from 119 service reservoirs and 41 water towers across various water sources for six months (March-September 2021). Using Flow Cytometry (FCM) to directly measure microbial populations, surface water exhibited 4-10 times higher microbial loading compared to groundwater and mixed sources. Among these sites, two distinct microbial water quality compliance events (detection of culturable coliform bacteria) were identified through FCM data, each presenting different microbial trends. Factors influencing regrowth in DWDS, notably water age and free chlorine, were scrutinized. Elevated intact cell counts were noted with chlorine levels <0.50 mg/L and water ages surpassing 4 days. Multiple linear regression highlighted temperature as the prime factor affecting cell counts variability in surface and mixed waters. For groundwaters, water age was significant, likely due to decreased disinfectant residuals and minimal treatment of these sources. The Bray-Curtis similarity index, derived from FCM fingerprints, emerged as a potential metric for detecting biological instability in drinking water microbiomes. The findings underscore the necessity of optimally managed DWDS and emphasize the significance of maintaining chlorine levels, especially at higher water ages and temperatures – particularly relevant considering climate change. Through FCM and its fingerprint analysis, a more detailed view of DWDS dynamics is attainable, promoting possibility for enhanced system control. The implications of this research offering potential for safeguarding public health, ensuring consistent water quality, and pathways for more resilient and sustainable water distribution practices. As a prospective direction for future research, machine learning models could be developed to predict and classify microbial community dynamics in DWDS using the rich dataset provided by FCM fingerprints.
  • ItemOpen Access
    Strategies for controlling nucleation and crystal growth in membrane distillation crystallisation.
    (Cranfield University, 2023-06) Ouda, Alaa Samir; McAdam, Ewan; Bajón Fernández, Yadira
    Membrane distillation crystallisation (MDC) is a promising technology that can address the primary restriction of regulating supersaturation rate in conventional crystallisation technologies, thus affording good control over nucleation and crystal growth. The supersaturation rate (R’) was used as a key parameter to govern the onset of nucleation (induction time) instead of irreversible flux decline, which is typically used in previous MDC studies. In this work, in-line turbidimetry enabled the precise determination of the induction time and metastable zone width (MSZW), which have been correlated to the supersaturation rate for a detailed characterisation of the nucleation kinetics and growth mechanism. The supersaturation at which nucleation occurred was measured within the interfacial boundary layer and bulk solution to differentiate between two scaling mechanisms (crystal adhesion or deposition) associated with the underlying nucleation mechanism based on classical nucleation theory. This allowed the MDC to decouple surface scaling from bulk nucleation at specific MSZW regions where the achieved crystallisation trajectory could balance between crystal quality and reduced membrane scaling. The increased supersaturation rate independent of the boundary layer enabled the transition towards a homogeneous nucleation mechanism where scaling is minimised, which aligns with classical nucleation theory but contradicts previous MDC studies. The consistent and reproducible nucleation kinetics obtained in this study while controlling multiple supersaturation factors suggested crystallisation to be inherently scalable, which is a unique facet compared to conventional crystallisers. Furthermore, the ability to sustain the supersaturation profile following nucleation enabled the system to reposition the crystallisation trajectory close to the MSZW threshold, providing high potential for nucleation kinetic control while regulating crystal size, size distribution and yield. Therefore, the kinetic framework established in this work offers advanced control over the nucleation mechanism and growth phase, which can be employed to fulfil commercial requirements for zero liquid discharge and more valuable crystalline products.
  • ItemOpen Access
    Structural fatigue assessment and optimisation of offshore wind turbine jacket foundations.
    (Cranfield University, 2023-08) Marjan, Ali; Huang, Luofeng; Hart, Phil
    Offshore Wind Turbine (OWT) is an expensive type of renewable energy system, and there is a continuous effort to lower the capital and operational costs. Jacket foundations are increasingly used in offshore wind due to their relatively light weight and adaptability in deep waters. However, the contemporary jacket designs are based on conservative practices from the oil and gas industry. There is still substantial room to optimise the jacket designs for offshore wind usage. This research aims to generate innovative jacket designs by applying a topology optimisation algorithm. The research demonstrates the use of advanced computational techniques to improve existing designs by enhancing structural integrity and fatigue life whilst reducing the mass. The research presents a comprehensive investigation of different parameters and design modifications that impact the design life of an existing jacket. An OC4 jacket foundation is employed, modelled in industrial software from DNV, and transformed into a super element model. The time-series loads obtained from Bladed are used to assess fatigue damages experienced during the foundation's service life. Furthermore, the research presents a topology optimisation method to retrofit an existing jacket foundation design by finding the optimum load path on the structure to enhance fatigue life and lower costs. The jacket's structural optimisation is performed by considering its dynamic response while adhering to the relevant international design standards. In particular, time-domain fatigue simulations were performed to assess the structural integrity of the topology- optimised jacket for the first time. As a result, a range of optimised models with various thickness and diameter options are presented, which are shown to be rational and verify the optimisation procedure. The research contributes a unique integrated topology optimisation framework, dynamic analysis, and time-domain fatigue simulations using industry-standard software tools, and achieved a mass reduction of 35.2% and simultaneously realized a 37.2% better fatigue life compared to the baseline model. The overall environmental load calculation, optimisation procedure and results provide useful practicalities for designing offshore wind turbine foundations and potentially facilitate the relevant industry's structural integrity and cost reduction.
  • ItemOpen Access
    Developing novel bioinformatics tools and pipelines for working with reference genomes and large sets of resequenced genomes.
    (Cranfield University, 2022-01) Kurowski, Tomasz Janusz; Mohareb, Fady R.
    Both reference genomes assembled for individual species and large, publicly maintained sets of resequenced genomes are of immense value to researchers. The former represent important milestones for research involving the species of interest and serve as ostensibly static points of reference for other data, while the latter serve as catalogues of genetic variation, enabling researchers to place their own data in a wider context. However, maintaining sets of resequenced genomes and ensuring their integrity as they undergo updates to match any new releases of their reference genome poses certain computational challenges, as does manipulating and comparing those large sets of genomes in general. This work reports on the detection and correction of significant errors which were introduced into resequenced tomato data in the course of updating them to a new version. It also introduces Tersect, a low-level utility optimized for manipulating and comparing large sets of resequenced genomic data, as well as Tersect Browser, a Web application which uses the high performance of Tersect, coupled with a higher-level indexing and precomputation scheme to allow for interactive comparison of large sets of resequenced genomes, giving biologists a tool capable of generating visualisations of genetic distance and phylogenetic relationships based on whole-genome sequence data from hundreds of genomes in seconds rather than hours.
  • ItemOpen Access
    Enhanced bio-minerals production using catalysts to accelerate resource recovery in wastewater treatment plants.
    (Cranfield University, 2023-01) Colston, Robert; Soares, Ana; Stephenson, Tom
    The biomineralisation mechanisms of five known bio-struvite producing microbes have been established and their ability to recover said biomineral from synthetic solutions and sludge dewatering liquors has been trialled. There is a lack of evidence and knowledge how these microbes perform in open culture conditions and the impact encapsulating media has on their ability to remove and recover orthophosphate as bio-struvite. In this PhD thesis, these microorganisms (Brevibacterium antiquum, Bacillus pumilus, Halobacterium salinarum, Idiomarina loihiensis, Myxococus xanthus) were investigated initially, this was streamlined into investigating encapsulated cultures of B. antiquum and B. pumilus in wastewaters under open culture conditions. The inoculation of all five microbes in source-separated urine in open culture conditions showed growth rates as high as 0.18 1/h and high nucleic acid proportions >80% within 24 hours of incubation. An orthophosphate removal of up to 70% was achieved by B. antiquum inoculations and was increased to 100% when magnesium was increased to a 1:1, P:Mg. Encapsulated cultures of B. pumilus were incubated B4.1 growth media, the removal of orthophosphate and chemical oxygen demand was equal to suspended cell inoculations of B. pumilus. In pure culture and open culture sludge dewatering liquors, encapsulated cultures of B. pumilus and B. antiquum, removed 55% and 70% of the initial orthophosphate over 24 hours respectively. The minimal difference in orthophosphate removal between pure and open culture conditions indicates that encapsulation provided an environmental advantage to the selected microbes to out compete the native species within the open culture sludge dewatering liquors. Suspended cell inoculations into open culture sludge dewatering liquors did not remove any more orthophosphate than non-inoculated controls. In continuous reactors fed by open culture sludge dewatering liquors orthophosphate removal for both encapsulated microbes averaged between 20% and 30%, at phosphorus loading rates of 0.4 kg P/m³ .d and 0.6 kg P/m³ .d. Supplementing a carbon source to the equivalent of 150 mg sCOD/L and increasing the ratio of P:Mg to 1:1.5, achieved an orthophosphate removal of 96% on average by encapsulated B. antiquum. Bio-struvite recovered from all open culture wastewaters was euhedral, prismatic and tabular and was typically coated in a secondary abiotic calcium phosphate. Micropollutant analysis showed the recovered minerals were below international heavy metal limits and were absent from faecal coliforms, pharmaceuticals and other micropollutants for fertilisers. Potential end users and consumers from the public and industry showed a strong willingness to use and eat produce grown from recycling derived fertilisers. There remains to be optimisation of the biomineralisation technique to improve the efficiency of recovery and streamline the operational set up, however the data collected in this PhD strongly supports the development of this technique into industry and will satisfy a growing need for circular economies and closing the nutrient loop.
  • ItemOpen Access
    Enhancing bioremediation efficiency of acidic wetlands contaminated with crude oil.
    (Cranfield University, 2023-03) Jumbo, Raphael Butler; Jiang, Ying; Bortone, Imma; Coulon, Frederic
    Crude oil exploration and exploitation has significantly impacted the Niger Delta, Nigeria wetlands and its ecosystems. Studies suggest that acidification is ongoing with several acid forming and acid tolerant microbes identified in the Niger Delta wetlands. The efficient remediation of the crude oil contaminants in the acidified wetlands is the only alternative left to the Niger Delta for effective ecological restoration of the environment. In this research, different combinations of bioremediation strategies were investigated to enhance the remediation of simulated crude oil contaminated acidic wetlands similar to the Nigeria Niger Delta wetlands contamination conditions. A series of mesocosm experiments subjected to wetland condition and a combination of treatments were evaluated as follows: for biostimulation experiment, Food waste anaerobic digestate (FWAD), and Tween 80 surfactant were individually added to the mesocosms at 10%, 20% and 30% w/w respectively with soil in the mesocosm experiments. For bioaugmentation experiments, mesocosms were enriched with Pseudomonas aeruginosa, Bacillus subtilis, or microbes indigenous to the crude oil spiked soil. Sequel to the results of these experiments, an optimised combination of FWAD (30% w/w) plus Tween 80 (30% w/w), Tween 80 (30% w/w) plus indigenous microbes, and digestate (30% w/w) plus Tween 80 (30% w/w) plus indigenous microbes were investigated. For each set of the experiments, pristine soil, acidified soil, and crude oil spiked acidified soil were maintained as controls. Total petroleum hydrocarbon (TPH) contents, soil basal respiration, and soil microbial communities’ dynamics were measured over 112 days of the experiments. For the biostimulation experiment, the FWAD and Tween 80 each at 30% (w/w) resulted in the highest petroleum hydrocarbons degradation (> 87% removal in 49 days). Augmentation with indigenous microbes enhanced the extent of degradation of the petroleum hydrocarbons (up to 80% in 49 days). For the optimised combined strategies, digestate (30% w/w) plus Tween 80 (30% w/w) plus indigenous microbes resulted in degradation of the hydrocarbons by > 98%. The correlation between basal respiration, microbial community and hydrocarbons showed that the more the biogenic CO₂ produced by the relevant microbial community, the faster the rate of the hydrocarbons degradation. Gram positive bacteria were the dominant microbial group in the FWAD, Tween 80 surfactant, indigenous microbes, and combined digestate (30% w/w) plus Tween 80 (30% w/w) plus indigenous microbe mesocosms. This research has demonstrated that acidified wetlands contaminated by petroleum hydrocarbons can be effectively remediated using low carbon biomaterials and indigenous microbial consortia. This conclusion was further confirmed by the more than 90% maize germination and undetectable bioavailable hydrocarbons recorded at the end of the experiment in these mesocosms. Potential exists for further studies in low carbon remediation of weathered hydrocarbons contaminants in various types of wetlands and sediments using FWAD, Tween 80 surfactant, and indigenous microbes.
  • ItemOpen Access
    Development of efficient data management and analytics tools for Intelligent sanitation network design.
    (Cranfield University, 2023-05) Jiang, Yirui; Tran, Trung Hieu; Williams, Leon
    According to the World Health Organisation, billions of people lack access to basic sanitation facilities and services, resulting in estimated 2.9 million cases of diseases and 95,000 deaths each year. This is because poor planning, design, maintenance, and access in traditional sanitation networks. Nowadays, intelligent sanitation systems leveraging the Internet of Things (IoT) technology can provide efficient and sustainable services, incorporating sensors, hardware, software, and wireless communication. Furthermore, advanced data analytics tools combined with the intelligent sanitation systems can provide a deeper insight into operations, make informed decisions, and enhance user experience, thereby improving sanitation services. The thesis provides a comprehensive review of literature on intelligent sanitation systems from both academic and industrial perspectives, with the objective of identifying recent advances, research gaps, opportunities, and challenges. Existing solutions for intelligent sanitation are fragmented and immature due to a lack of a unified framework and tool. To address these issues, the thesis introduces a generalised Sanitation-IoT (San-IoT) framework to manage sanitation facilities and a standardised Sanitation-IoT-Data Analytics (San-IoT-DA) tool to analyse sanitation data. The framework and tool can serve as a foundation for future research and development in intelligent sanitation systems. The San-IoT framework can enhance the connectivity, operability, and management of IoT-based sanitation networks. The San-IoT-DA tool is designed to standardise the collection, analysis, and management of sanitation data for providing efficient data processing and improving decision making. The feasibility of the proposed framework and tool was evaluated on a case study of the Cranfield intelligent toilet. The San-IoT framework has the potential to enable system monitoring and control, user health monitoring, user behaviour analysis, improve water usage efficiency, reduce energy consumption, and facilitate decision-making among global stakeholders. The San-IoT-DA tool can detect patterns, identify trends, predict outcomes, and detect anomalies. The thesis offers valuable insights to practitioners, academics, engineers, policymakers, and other stakeholders on leveraging IoT and data analytics to improve the efficiency, accessibility, and sustainability of the sanitation industry.
  • ItemOpen Access
    An agent-based model for improving museum design to enhance visitor experience.
    (Cranfield University, 2022-11) Ji, Yijing; Tran, Trung Hieu; Simon, Jude; Williams, Leon
    Museum experience is a multi-layered journey including ontological, sensory, intellectual, aesthetic, and social aspects. In recent years, the museum sector has faced a number of challenges in terms of the need to enhance the potential of the experience while maintaining authenticity and credibility. For public science communication in museums, exhibition is an important medium for connecting exhibits and visitors, and as such, the study of visitors' senses and behaviours under impact of various museum layout designs has become an important research direction. The purpose of this study is to explore the recall of visitors' memories in the exhibition space by integrating images, echoes and tactile senses, and then transform memories and interactions into their own experience and knowledge base. The impact of spatial design and other design elements on visitors' memories is also explored. We have conducted Agent-based simulation, by setting up virtual visitors, exhibition spaces and artefact based on real gallery spaces, as a time-saving and cost-saving method to improve exhibition interactivity and content coherence. Meanwhile, through the simulation of this novel way, visitors can observe and predict the interactive experience between visitors and the exhibition, so as to improve the curatorial team's research on tourist behaviour and spatial design scheme. Next, the simulated data on visitors' memory recall behaviour is compared with the actual observed data to explore the authenticity of visitors' behaviour in the simulated museum. The impact of this study is by integrating a variety of shared understandings between curators, exhibition management and participants, drawing on diverse information based on experience, practice and simulation. It seeks to provide future museum- oriented practitioners, particularly in small and medium-sized museum exhibition spaces, with a novel perspective and approach to observing or predicting the experience of visitors' sensory interactions within an exhibition. Furthermore, at the same time as enhancing the visitor’s exhibition experience, the content of exhibition story is fully transformed into its own knowledge accumulation.
  • ItemOpen Access
    Numerical modelling of bipolar plate in pem fuel cells to analyse the pressure drop in various channels and development of a novel geometry of the bipolar plate.
    (Cranfield University, 2022-09) Jayabal, Jayvassanth; Verdin, Patrick G.; Nabavi, Sayed Ali
    This work centres on comprehending and elevating the performance of Proton Exchange Membrane (PEM) hydrogen fuel cells, with a specific emphasis on minimizing pressure drop in the bipolar plate. Fuel cell efficiency hinges upon core factors, including electrochemical reaction, temperature, and pressure management. Notably, pressure drop within the fuel cell plays a pivotal role in determining overall efficiency and power output. The study aims to tackle the pressing issue of pressure drop, primarily manifested in the bipolar plate, profoundly affecting the fuel cell's output power. Researchers have pursued ground-breaking designs to curtail pressure drop and augment power output. However, certain advanced designs pose challenges in fabrication, leading to a research gap impeding the development of efficient models. To bridge this gap, the study proposes a novel and straightforward bipolar plate design, demanding minimal external power and eliminating the need for intricate geometries. Furthermore, apart from pressure drop, fuel cell inefficiencies are compounded by obstacles like inadequate meshing and porosity integrity of the end plates. Consequently, costly platinum and gold-plated end plates are often deployed to achieve superior output performance. The research reveals that velocity variations influence pressure within existing models, furnishing valuable insights for attaining improved efficiencies in fuel cells. The work presents a comprehensive analysis of PEM fuel cells, with particular attention to the bipolar plate's design and its ramifications on pressure drop. The proposed novel geometry aims to enhance fuel cell performance while addressing challenges linked to complex designs. The research findings offer valuable recommendations for optimizing fuel cell efficiencies, thereby contributing to the advancement of clean energy technologies.
  • ItemOpen Access
    Design and performance analysis of concentrated photovoltaic cooling.
    (Cranfield University, 2023-01) Ibrahim, Khalifa Aliyu; Luk, Patrick Chi-Kwong; Kahagala Gamage, Upul
    The use of solar energy as a global energy source has increased over the past two decades. Photovoltaic cells, which utilise the sun to generate electricity, are a promising alternative to fossil fuels that contribute to climate change. However, the high intensity of concentrated solar radiation can cause overheating in photovoltaic cells, reducing their efficiency and power output. Researchers worldwide are improving cooling in concentrated photovoltaic cells (CPV) to enhance temperature uniformity and improve power output. Previous studies have demonstrated that pulsating flow can effectively enhance heat transfer in various fields, including electronics, mechanical engineering, and medicine. In this research, three flow patterns (continuous flow, uniform pulsating flow, and bio-inspired pulsating flow) were studied in both simulation and experimental designs. Two cooling designs were considered: the conventional design (C- Design) and the parallel design with baffles (W-B) and without baffles (Wout-B). With the implementation of 30 pulses per minute bio-inspired pulsating flow a reduction of 1.96% in solar cell temperature was observed when compared to continuous flow. This reduction in temperature was consistently observed across a range of flow rates from 0.5 to 2.5 L/m, employing the parallel Wout-B design. Notably, the bio-inspired pulsating flow shows better performance in comparison to uniform pulsating flow, as well as the conventional designs with continuous flow and uniform pulsating flow, resulting in notable improvements in cooling efficiency of 1.22%, 2.14%, and 4.00%, respectively. In terms of a direct comparison, the implementation of uniform pulsating flow in the parallel Wout-B design exhibited a maximum cooling improvement of 0.74% when contrasted with continuous flow. Furthermore, when assessing uniform pulsating flow against the C-design with uniform pulsating flow in the parallel Wout-B design, a noteworthy enhancement of 0.93% was observed. Remarkably, the C-design with uniform pulsating flow demonstrated a superior effectiveness of 1.90% when compared to the C-design with continuous flow.
  • ItemOpen Access
    Optimising polyacrylamide (PAM) spray application to mitigate the agronomic effects of Soil Crust.
    (Cranfield University, 2022-07) Arpano, Silvia; Simmons, Robert W.; Deeks, Lynda K.
    The Leafy greens industry provides micronutrient-rich fresh produce at an affordable price. To meet the demand, multiple short crop cycles per year are seeded and harvested, for example, the summer spinach cycle can be as short as 21 days with 4 to 6 crop cycles in a season, in the UK. However, this high input/output agronomic system has a negative impact on other provisioning and regulating ecosystem services (ES). The primary soil-related ES that are affected are sequestration of soil carbon, crop production and water storage. The intensive soil management strategy promotes on-field loss of soil organic matter, which reduces soil resilience to erosive forces and contributes to the formation of capping and sealing. Soil capping and sealing inhibits seedling emergence, which reduces crop productivity. Within the rapid management cycle of leafy greens production there is limited time to incorporate soil amendments to offset the loss of SOM. This research explores the use of polyacrylamides (PAMs) as a soil surface amendment within this cropping system. Polyacrylamides are molecules with a long carbon backbone characterised by areas of different electric charge density. This trait allows them to bind to polar substance (e.g. water, soil colloids, soils organic matter). They are excellent flocculants and have been used for decades in furrow-irrigated crops to mitigate soil erosion and increase water infiltration. Besides flocculating particles in free-flowing water, PAMs have also been found to bind and protect soil aggregates by being adsorbed into aggregates and stabilising them. In combination, these two properties of PAMs have the potential to mitigate the agronomic effects of soil capping and sealing, including reducing emergence impedance, reducing splash contamination, and promoting water infiltration. However, PAMs are very hygroscopic and can be difficult to work with at concentrations above 500 ppm in water. This research investigated a new PAM broadcast system, using a Dual-Fluid nozzle which mixes PAM and water outside of the hydraulic system. The effect of PAMs on soil and crops were measured in a laboratory experiment and in five field trials on two crops, coriander and spinach. The metrics measured included soil crust, soil moisture, emergence and final yield quantity and quality. The results of the research have shown the efficacy of PAM within commercial leafy greens crops. The application of PAM was associated with earlier emergence in coriander, that lead to higher biomass per plant and it also increased the emergence count in spinach, leading to an overall higher yield (47- 39% for plots treated with 80 kg ha⁻¹ of PAM and 80kg ha⁻¹ PAM+Ca respectively). The amount of soil splash, and therefore potential for contamination of the product, was also reduced (24, 41 and 59% decrease in splash detached soil from plots treated with 40, 80 and 120 kg ha⁻¹ PAM respectively compared to the control). An economic appraisal based on the field data, also determined that PAM could be economically viable within the commercial cropping system and identified future improvements.
  • ItemOpen Access
    Influence of bioremediation on the chemical and nutritional composition of produce from crude oil-polluted sites.
    (Cranfield University, 2015-12) Odukoya, Johnson Oluwaseun; Sakrabani, Ruben
    The influence of crude oil-contaminated and remediated sites on agrifood production is not clearly understood. To address this knowledge gap, the research was divided into two stages involving: (1) assessment of the efficiency of two bioremediation strategies to support hydrocarbons degradation as well as agrifood production with the initial analysis of the experimental materials, and (2) evaluation of the effect of different crude oil remediation intervention values (CRIV) on selected vegetables (Brassica juncea, Brassica oleracea, Lactuca sativa and two different cultivars of Solanum lycopersicum). Results from the first stage showed that the crude oil used had a pristane/phytane ratio of 0.98 (within the 0.8 – 3.0 range of most crude oils), higher concentrations of C₁₀ – C₁₄, C₁₅ – C₂₀ and C₂₁ – C₂₇ alkanes than the C₂₈ – C₃₆ alkanes including higher concentrations of two of the US EPA priority pollutant polycyclic aromatic hydrocarbons (PAHs) - phenanthrene and anthracene. Four treatments were prepared in which weekly tillage enhanced the degradation of C₁₅ – C₂₀ and C₂₁ - C₂₇ alkanes in the Remediation by Enhanced Natural Attenuation (RENA) treatment. The two bioremediation strategies (RENA and bioaugmentation) enhanced PAHs degradation compared with the remediation-study control treatment while only RENA application among the two approaches supported the growth of B. juncea. Although there was no statistical significant difference (p > 0.05) between the major dietary mineral contents of samples from the various treatments compared with the control treatment samples, RENA application affected the Cr, Zn and Pb contents. Meanwhile, the Ca/P (> 1.0) and Na/K (< 0.60) ratios of all the harvested samples imply that they provide a good source of these minerals for bone formation and would not contribute to high blood pressure. The crude oil used also deterred the attack of juvenile caterpillars of cabbage white butterfly. Findings from the second stage revealed that the yield of the green leafy vegetables including one of the selected tomato cultivars (Micro-Tom), was in most cases impaired at CRIV ≥ 3,000 mg/kg total petroleum hydrocarbon (TPH). Compared with the control treatment samples’ composition, crude oil stress at 10,000 mg/kg TPH enhanced the concentration ODUKOYA, Johnson O. Cranfield University PhD Thesis of K, Mn and crude protein of B. oleracea and L. sativa as well as the sucrose, total sugars, total phenolics and total flavonoids contents of the latter vegetable. Sucrose was also only detected in M82 tomato cultivar samples from the crude oil-containing treatments. The Cd content of B. oleracea, Pb contents of: L. sativa and M82 tomato harvested samples were all below the FAO/WHO Codex Alimentarius Commission 2015 recommended maximum levels. However, tartaric acid was only detected in B. oleracea and L. sativa samples from the 10,000 mg/kg TPH treatment as well as in M82 tomato cultivar samples from the treatment involving CRIV of 5,000 mg/kg TPH. Generally, the yield of these crops in response to crude oil contamination varied in which B. juncea had the least tolerance to crude oil stress among the green leafy vegetables tested. Most of the quality parameters in the two tomato cultivars were not affected by CRIV between 750 - 5,000 mg/kg TPH with p-xylene having the greatest toxic potential among the VOCs emitted from the 5,000 mg/kg TPH treatment. The research findings, under the experimental conditions, indicated the effectiveness of RENA for the degradation of low molecular weight PAHs and its agricultural benefits. They also suggest that crude oil-contaminated sites at ≤ 3,000 mg/kg TPH present a similar growing environment to a clean site for agrifood production and the possibility that crude oil stress at 10,000 mg/kg TPH could enhance crop quality. Nonetheless, the contribution of bio- accumulated PAHs in these crops to the food chain demands further investigation.
  • ItemOpen Access
    Effects of organic matter additions on the soil microbial population and associated stoichiometry in horticultural systems.
    (Cranfield University, 2023-01) Hasler, Rachel; Pawlett, Mark; Harris, Jim A.
    Organic matter addition influences soil function (respiration/ decomposition) and community structure (PLFA/ NLFA community profiles) which result in changes to the provision of soil derived ecosystem services. Additions of organic matter to gardens (e.g. composts, mulches, soil conditioners) is a widespread practice both globally and in the UK. Research on the long-term cumulative impact of annual additions to UK gardens is limited. A field trial, set-up in 2007, at the Royal Horticultural Society’s Wisley Gardens site, was used to examine the changes to soil chemical, physical and biological soil quality indicators following 12 years of different soil organic matter additions. Additions varied in carbon-to-nitrogen ratios (C/N), physical structure and macro/ micro-nutrient profiles. The amendments used in the trial included composted bark, bracken, stable manure, garden compost, spent mushroom growing compost, peat, fertiliser (rate adjusted each year to meet plant growth requirements) and controls; no organic matter addition and no plant sown, no organic matter addition and plant sown. Lab studies were designed following analyses of amendment legacy effects in field trial plots to further examine the effects of addition on microbiological indicators of soil function, health and quality. Reviewing long term chemical and physical data from the field trial highlighted significant effects of organic matter additions on soil micro- and macro-nutrients. Recommendations for garden industry were made from the findings and include the need for labelling standards for compost material packaging to reduce unwanted environmental impacts of use. Organic matter treatment to clay-loam textured soil significantly increased microbial respiration and shifted microbial community structure. The effects were distinct and dependent on composition of the organic matter applied. The horticultural sector has outlined targets for reducing the impact of garden practise on drivers of climate change. This study aligns with literature which seeks to understand common practise in order to improve economic and environmental sustainability.
  • ItemOpen Access
    IOT enabled greenhouse automatic control system for energy efficiency optimization.
    (Cranfield University, 2022-02) Faniyi, Beatrice; Luo, Jerry; Luk, Patrick Chi-Kwong
    Agricultural greenhouses provide optimal conditions for plant growth, but they consume an excessive amount of energy, making energy the second-largest expense after labour costs. Most of the energy is used for heating, which is a major contributor to the high energy demand of the system. Precise and timely control technology can help reduce energy costs and increase profitability. The integration of IoT into greenhouses is a new development in smart agriculture that has the potential to optimise energy use. Various methods exist for optimising energy use in greenhouses, including the use of phase change materials, efficient greenhouse construction designs, and control systems. However, smart automatic control systems are an efficient method that has not been explored enough. Understanding the control algorithm and its proper implementation for use in the greenhouse control system is critical for energy optimisation. This thesis makes three main contributions to greenhouse temperature control. First, a dynamic, physics-based model of greenhouse temperature was optimised to be adaptable for greenhouses equipped with IoT hardware. Second, two control algorithms were implemented in simulation to regulate the system to the grower's desired temperature, while four other control algorithms were implemented to evaluate their energy minimization capability. Results showed that the MPC controller was the best controller in terms of energy savings. Nevertheless, for small to medium greenhouse operators who may have limited resources, relatively simple on-off control algorithm is cost-effective. Finally, the study demonstrates that an IoT-based control system can optimise the energy use in the greenhouse. The use of IoT technology has the capacity to overcome the greenhouse energy management problem with a distribution control system aided by cloud computing. This study demonstrates the potential of IoT-based control systems to save energy and improve greenhouse efficiency by reducing delays and increasing control effectiveness.
  • ItemOpen Access
    Application of artificial neural networks in the design of drainage systems in data-poor areas.
    (Cranfield University, 2022-06) Ellafi, Murad; Simmons, Robert W.; Deeks, Lynda K.
    Drainage has been identified as an often-neglected component of irrigated agriculture in arid and semi-arid areas. Even though it is accepted that drainage is often necessary to prevent waterlogging and salinity impacting productivity in irrigated agriculture, it is typically ignored when planning future irrigation schemes. Only 5 – 10% of the total irrigated land in Least Developed Countries (LDCs) that requires drainage is currently drained (compared to 25 – 30% in developed countries). This is partly due to a fundamental lack of spatially and temporally coherent datasets containing key input parameters for drainage models, local expertise and the high cost of drainage installation. Drainage simulation models can provide reliable predictions of multi-component systems to evaluate drainage system design over long periods (1 – 100 years). This study evaluated existing drainage simulation models (i.e. DRAINMOD, SWAP, ADAPT, RZWQM2, EPIC, WaSim and HYDRUS-1D) for their suitability to be applied in data-poor arid and semi-arid regions. Based on a selection criteria, the most applicable model for drainage design in arid and semi-arid areas was DRAINMOD. DRAINMOD, an agricultural drainage simulation model, is a versatile and readily available model that can be used to evaluate alternative drainage system designs. DRAINMOD requires several key inputs, including saturated hydraulic conductivity (Ksat), reference evapotranspiration (ET0) and the Electrical Conductivity of a saturated soil Extract (ECe). In LDCs, measuring these parameters is expensive and time-consuming. In addition, existing historic datasets are often spatially and temporally limited. Therefore, indirect approaches are needed to overcome incomplete data records that restrict drainage designs. This thesis evaluates the feasibility of applying indirect methods, with a focus on developing and validating the use of artificial neural networks (ANNs) using available historic measured datasets. The study data draws on the drainage design for Hammam Agricultural Project (HAP) and Eshkeda Agricultural Project (EAP), located in the south of Libya, north of the Sahara Desert. Soil texture, bulk density, field capacity, and wilting point were used to develop ANNs to predict Ksat which were significantly more accurate compared to widely adopted Pedotransfer functions (PTFs) such as Rosetta3. To calculate the daily ET0, average monthly maximum and minimum air temperature were used to develop ANNs. Arithmetic Averaging of Neighbouring Stations (AANS), MODAWEC and Era5-Land were among the indirect methods applied to predict ET0. Landsat 5 Surface Reflectance bands and the derived salinity indices were applied to develop ANNs to estimate ECe. The accuracy of the predicted values of Ksat, ET0 and ECe were evaluated by using statistical parameters such as coefficient of determination (R²), mean square error (MSE), and root mean square error (RMSE). The predicted Ksat and ET0 values were input to DRAINMOD to design drainage systems in EAP and HAP as compared to the optimum design based on measured data. The design focused on how accurately the predicted values were able to estimate drain spacing, relative yield, irrigation depth, and drainage discharge. The key findings showed that the accuracy of predicting Ksat greatly impacted predicting the optimum drain spacing and the associated relative yield. Accurate prediction of the optimum spacing between drains will reduce the overall cost by ensuring that the drains are not spaced too closely, but also lowers the risk of raising the water table and negatively impacting the yield by preventing the drains being installed on too wider a spacing. In addition, precisely predicting ET0 is essential to quantify the irrigation water requirement and drainage discharge. Finally, predicting soil salinity using remote sensing data can be used as an early warning tool to monitor irrigated lands affected by salinity, evaluate the performance of existing drainage systems, and indicate areas that need improvement. Future research recommendations identified by this research include the need for (1) critical evaluation of the accuracy of using ANNs and other machine learning approaches to predict other input parameters required for drainage design such as the water retention curve, depth of impermeable layer, hourly or daily rainfall, and initial water table depth. (2) development and validation of ANNs and other machine learning approaches that can predict Ksat, ET0, and ECe on a national level (Libya) and/or regional level (Middle East and North Africa) to overcome the challenge of incomplete data records that restrict drainage designs.
  • ItemOpen Access
    Full chain analysis of nitrogen use efficiency in rice-livestock systems in Uruguay: identifying opportunities for optimizing N management.
    (Cranfield University, 2022-11) Castillo Velazquez, Jesus; Kirk, Guy; Haefele, Stephan M.
    Traditionally the rice crop in Uruguay rotates with pastures for direct livestock grazing. This rotation has allowed a constant rice yield increase of 90 kg ha⁻¹ yr⁻¹ over the past 50 years, with yields averaging 8.4 Mg ha⁻¹ in the last decade. Relatively little nitrogen (N) fertilizer is added (80 kg ha⁻¹ yr⁻¹) and the system shows no sign of soil degradation. By contrast, the livestock component is conducted extensively with mostly (75-80%) unimproved pastures, with low animal productivity (100 kg liveweight ha⁻¹ yr⁻¹). This thesis is concerned with how the system N balance is sustained at regional and national scales and if it can be maintained in the future. The objectives were to quantify the N balance (all N inputs – outputs), N surplus (all N inputs – N removed in food products) and N use efficiency (NUE = N in food products / all N inputs) of different rice-livestock- pasture rotations across Uruguay over time. Because historical records of N inputs and outputs are available at regional and national scales, it was possible to assess the whole system in the long term at a farm-gate level. The DNDC model was parameterised with data from a rice long-term experiment and used to compliment the regional N balance data. Results showed a very high average NUE (55–60%) with N balances around neutrality (-6 to +5 kg N ha⁻¹ yr⁻¹) and low N surplus (20 kg N ha⁻¹ yr⁻¹). These values were worse where pastures have been replaced by other cash-crops or rotations shortened. However, there is an opportunity to intensify the system, maintaining the good N balance by improving the livestock component with improved pastures and higher stocking rates to improve N cycling. Results showed the rice-livestock system of Uruguay is a model mixed farming system with several decades of integration.
  • ItemOpen Access
    Study on incentive mechanisms of smes crowdsourcing contest innovation.
    (Cranfield University, 2021-02) Zhu, Binxin; Williams, Leon; Lighterness, Paul
    Dealing with insufficient resources is a common challenge yet practical reality for many project managers working within SMEs. With the rise of Web 2.0, crowdsourcing contest innovation (CCI) it is now possible for project managers to use online platforms as a way to collaborate with external agents to fill this resource gap and thus improve innovation. This research uses agent-based modelling to prognosticate the efficacy of crowdsourcing contest innovation with a particular focus on the project manager ‘seeker’ within an SME initiating competitive crowdsourced contest teams made up of individual ‘solver’ participants. The contribution of knowledge will benefit the open innovation community to better understand the main motivational incentives to obtain maximum productivity of a team with limited project management resources. In pursuit of this, the social exchange theory is challenged, this thesis explores the motivation factors that influence solvers to participate in SMEs CCI from the perspectives of benefit perception and cost perception. The results found that non-material factors such as knowledge acquisition and sharing, reputation can stimulate solvers to participate in SMEs CCI more than material (physical money) rewards. Meanwhile, risks such as intellectual property risks and waste of resources are significant participation obstacles. Based on this, the principal- agent theory is used to design the models of team collaboration material incentive mechanism, dynamic reputation incentive mechanism and knowledge sharing incentive mechanism, and the performance of each incentive mechanism is analysed. At last, according to the principles of sample selection, Zbj.com, the China’s most successful crowdsourcing platform of which the main clients are SMEs, is chosen as the research object, and the effectiveness of the incentive mechanisms designed in this thesis is verified. It is found that the material and non-material incentives have been partially applied on the platform, and the explicit, implicit and synergistic effects of incentives are preliminarily achieved. According to the research results, it is suggested that the guarantee measures of the incentive mechanisms should be further developed, such as optimising pricing services and refining task allocation rules.
  • ItemOpen Access
    A pcr-based method for SARS-COV-2 variant detection in wastewater.
    (Cranfield University, 2022-06) Caetano Souza, Karina; Yang, Zhugen; McAdam, Ewan
    The COVID-19 outbreak, caused by the SARS-CoV-2 virus, rapidly evolved into a worldwide pandemic, as declared by World Health Organization on 11th March 2020. The continued spread since early 2020 has resulted in many variants of this virus. Most mutations found along its genome are known as single nucleotide polymorphisms (SNPs) where only one base pair is mutated. Current real-time qualitative polymerase chain reaction (RT-qPCR) protocols, so called gold-standard method, are used to confirm if a person is positive or negative for the virus. There is a lack of available technology for rapid identification of variants. In order to identify the presence of a viral variant it is necessary to perform sequencing. Sequencing is expensive and may take hours to days to complete. Due to its cost, sequencing is widely unavailable in most countries. Even in countries where sequencing is available, like the UK, the number of samples sequenced are less than 10% of total cases due to extremely high cost. Wastewater-based epidemiology (WBE) is a novel approach that would help monitor and possibly revert the current health crisis. It has been reported the presence of SARS-CoV-2 RNA in faeces of infected individuals. This makes it possible to detect and monitor SARS-CoV-2 in wastewater samples, providing a health status report of the population within the catchment. To this context, WBE also enables to monitor the dissemination of variants for early warning of the outbreak within the defined population. In this project, a RT-qPCR method was developed targeting unique SNPs of SARS-CoV-2. This assay uses two probes, both targeting the same sequence, one with the SNP and the other non- SNP. These mutations are found in the N-gene of SARS-CoV-2 viral RNA, a conserved region that contains unique SNPs specific to each variant for differentiation. By using two probes, binding competition occurs, and the differentiation is done by observing an earlier detection with the SNP probe (~6 cycles). In addition to this, this method can be coupled with a melt curve analysis for further confirmation. Currently, there is a lack of available technology for rapid identification of variants of concern within the community. This assay can be implemented for routine WBE. By developing a SNP-PCR assay to detect specific variants of concern using WBE, it would be possible to accurately detect variants. This information provides a comprehensive health report on the population that could possibly help revert the current health crisis.
  • ItemOpen Access
    Impacts of irrigation heterogeneity on sugarcane yields, energy and water use in sub-saharan Africa.
    (Cranfield University, 2023-12) Banda, Mavuto Muhammad; Knox, Jerry W.; Hess, Tim M.
    Sugarcane is an economically strategic crop in Sub-Saharan Africa (SSA), underpinning the rural livelihoods and economies of many SSA countries. Despite its economic importance, yield trends in the region have been declining by an average of 0.03 t/ha per year over the last 60 years. However, total cane production has been increasing by an average of one million tonnes per year over the same period – an indication that the increase in total cane production has largely been due to an overall expansion in cultivated area. However, this situation is not sustainable in the long-term since land availability is limited. Whilst irrigation has the potential to improve yields, production in SSA is typically characterised by poor irrigation management practices as evidenced by high levels of irrigation water use, low irrigated yields and low water productivities. Understanding the impacts of future climate variability and drought risk on the reliability of irrigation and identifying appropriate technology and management options to improve yields, water and energy use and productivity are key challenges facing the agricultural sector in SSA. Impacts of irrigation non- uniformity on cane yields, water and energy use in SSA were identified as key research gaps in this study. Thus, the aim of this research was to evaluate the agronomic, environmental and economic impacts of irrigation non-uniformity on sugarcane production in SSA. Initially, a benchmarking study was conducted to identify opportunities to improve cane yields and water productivity and reduce irrigation water and energy use. Biophysical crop, water balance and economic modelling approaches were then integrated to simulate cane yield response to water, the impacts of irrigation non- uniformity and the relative cost and benefits of improving irrigation uniformity. Cane yields were modelled for varying water applications and irrigation uniformity using the DSSAT Canegro model coupled with a water balance model. The relative financial costs and benefits of implementing different interventions to improve irrigation management were then evaluated using a spreadsheet-based economic model. The results showed that there were opportunities to improve the performance of irrigated cane production in SSA – currently characterised by lower-than- expected yields – ranging between 83.9 and 108.9 t/ha, high irrigation water uses and lower than potential water productivity – ranging between 5.0 and 7.8 kg/m³. It was also established that improving irrigation uniformity leads to improved cane yields, reduced irrigation water and energy use. It was also established that on average a percentage improvement in irrigation uniformity could improve yields by 0.2 – 0.5 t/ha and could reduce irrigation and energy use by 3%. These potential yield improvements (due to improved irrigation uniformity) coupled with a reduction in water and energy use resulted in increased revenues of between 23,300 and 70,900 MK/ha (c£18 – 65/ha) and a reduction in irrigation-related costs by 3,700 MK/ha (c £3/ha). Overall, the research has provided new valuable insights into the impacts of irrigation heterogeneity on cane yields and addressed existing knowledge gaps relating to how existing irrigation management practices in the sugarcane industry in SSA can be improved, without the need for transformational shifts to precision irrigation technologies. The findings provide the basis for improving cane yields, irrigation water and energy use and productivity in both commercial and smallholder cane production across SSA. It is, thus, recommended that there is a need for farmers to always operate irrigation with improved level of irrigation uniformity while ensuring proper irrigation scheduling approaches. The implementation of irrigation uniformity improvement interventions and adopting correct irrigation scheduling methods would likely reduce irrigation water use, improve yield average at field level which in turn will improve water productivity and reduce energy requirements for irrigation. The improvement of water productivity and reduction of irrigation water use and energy requirements would maximise crop yield benefits from irrigation and reduce irrigation operation costs, respectively.