School of Agriculture, Food and Ecosystem Sciences - Theses

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    Application of New and Emerging Technologies to Assess Rice Quality and Sensory Perception by Consumers
    Aznan, Aimi Athirah ( 2023-07)
    Rice is a staple food for over half of the world's population. The selections of commercial rice in the market resulted from the diversity of rice quality preferences by consumers. Besides, demographic factors such as cultural background, urbanisation, and socioeconomic status may change rice quality preferences over time. Hence, rice breeders and producers need to actively assess the best rice quality attributes that suit the demands. However, the traditional methods to evaluate rice quality are commonly tedious, time-consuming, costly and non-portable. Besides, the conventional descriptive and consumer acceptance tests based on conscious responses are likely prone to bias, expensive, time-consuming and require a dedicated laboratory sensory to conduct the sensory sessions. Therefore, new methods to assess rice quality and sensory perceptions using artificial intelligence (AI) subdivision technologies might be beneficial to overcome these disadvantages. Integrating digital sensors, computer vision, biometrics, and machine learning technologies could offer new approaches to assess rice quality and consumer perception of rice using rapid methods. This research aimed to develop rice quality assessment methods using digital sensors, computer vision, biometrics and machine learning to assess the aromas, physicochemical quality and consumer perceptions towards different types of rice. The project was divided into three main scopes to assess raw and cooked rice physicochemical quality, consumer perception of uncooked rice, cooked rice and packaging and detection of rice adulteration. This study used different types of commercial rice bought from the local markets in Australia. The rice samples consisted of regular white rice (e.g., long, medium and short-grain rice), organic, and unpolished rice from different market segments and provenances. The wide selection of rice is essential to the study since various types of rice are consumed by diverse cultural backgrounds to cook different kinds of dishes worldwide. In this study, digital, chemical and aroma fingerprints of rice were obtained using digital sensing devices such as the smartphone camera, near-infrared (NIR) spectrometer and electronic nose (e-nose). The fingerprints were used as inputs to develop machine learning models to classify different types of rice and predict the aromas, physicochemical quality, consumer perceptions, and rice adulteration levels. Furthermore, biometrics responses were used to obtain subconscious responses to assess their relationship with self-reported responses and different types of rice samples. Findings from this research are expected to contribute to the scientific knowledge of the relationship between digital, chemical and aroma fingerprinting with consumer perceptions towards different types of rice quality. Besides, the proposed method to classify different kinds of rice quality and predict rice quality attributes, consumer perceptions and adulteration levels using the integration of digital sensors, computer vision and machine learning showed high prediction accuracy (classification model: accuracy > 90%; regression model: R > 0.94). The proposed methods using the new and emerging technologies described in this study will lead the rice industry towards applying the rapid technique at a lower cost to assess rice quality compared to the traditional method.
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    Effect of green roof design configuration and climate on rainfall retention, evapotranspiration, and plant drought stress
    Lubaina ( 2023-04)
    Urbanisation significantly alters the hydrological cycle through creation of impervious surfaces and removal of vegetation. Besides creating large volumes of stormwater runoff which degrades urban stream ecosystems and water sources, impervious surfaces reduce infiltration of rainfall and therefore water availability for remaining vegetation. Sustainable and resilient stormwater management techniques are required to mitigate the impacts of stormwater runoff and compensate for the loss of vegetation in cities. Green roofs are a promising green infrastructure technology with the potential to deliver these ecosystem services, however, gaps in our understanding of how they should be designed is preventing widespread uptake. Green roof substrates are typically shallow due to building weight-loading restrictions and therefore have limited water storage for reducing runoff and sustaining vegetation. Species typically used on green roofs are limited to those with the ability to survive harsh environmental conditions, such as succulent species. However, selecting plants with high water use, combined with drought resistance, such as non-succulent species, and planting at higher density in deeper substrates may improve green roof rainfall retention without substantially increasing plant drought stress. Where substrate depth cannot be increased, mimicking processes we observe in natural systems, such as redirecting rainfall towards vegetation in semi-arid banded systems, has significant potential to both increase rainfall retention and reduce plant drought stress. Climate is the primary driver of green roof performance, specifically the supply of and demand for water from the atmosphere, which in turn determines evapotranspiration, rainfall retention and plant drought stress. Ideally, by understanding the interaction of substrate depth, plant density (water use) and redistribution of water resources on green roofs, it should be possible to determine the most suitable green roof configuration for different climates, and therefore remove the key barrier to widespread green roof installation. In this thesis, I aimed to achieve this understanding through a combination of controlled experiments and water balance modelling. Firstly, a glasshouse experiment was used to understand how increasing substrate depth and plant density, as well as their interaction, impacted plant water use, drought stress and rainfall retention. Due to COVID-19 disruptions, only the first well-watered phase could be completed, after which the experiment had to be terminated without measuring water use and drought stress under water-deficit. Therefore, I used an established green roof water balance model to simulate performance under water deficit conditions. Pre-existing functions describing the plant species’ drought response were combined with well-watered plant crop factors (Kc) calculated from ET measured during the experiment, to estimate rainfall retention and the incidence of plant drought stress. Contrary to my initial hypotheses, increasing plant density did not result in a proportional increase in plant water use, even when substrate depth was doubled. Importantly, this indicated little gain in retention performance by increasing plant density. Using a water balance model to extend these findings to include performance under water deficit, I showed that rainfall retention was very high, regardless of substrate depth and plant density, as plants in the glasshouse had a very high crop factor and therefore rates of water use. With a high crop factor, all treatments from the glasshouse simulated in the model depleted the substrate water quickly, resulting in greater retention, but also significant plant drought stress. In this model, the indicator of drought stress in plants on each day of the rainfall simulation was when the depth of water (millimeter) in the substrate at the end of any given day reached zero. Importantly, increasing substrate depth showed no significant benefit to either rainfall retention or plant drought stress. Overall, planting in shallower substrates at a lower density optimised green roof performance when measured and simulated in a temperate climate. Secondly, a rainfall simulation experiment using green roof modules was conducted to understand the effect of plant density and redistribution of rainfall (runoff zones) on rainfall retention, plant water use and drought stress. In this experiment, drought stress in plants was indicated by midday leaf water potential (MegaPascal). Again, planting at a lower density (10 plants per module, approximately half the module area planted) achieved high rainfall retention and most importantly, plants experienced lower drought stress than fully-planted modules (18 plants per module). Furthermore, using runoff zones to direct rainfall towards plants also reduced plant drought stress. However, the runoff zones also created preferential flow pathways and shaded the substrate surface, both of which were the likely cause of lower rainfall retention, despite the observed reduction in plant drought stress. Although, reducing plant density showed the most effective way of achieving high rainfall retention and lower drought stress, there are other ways of increasing substrates' water retention and holding capacity, such as using water retention additives to increase water available for more densely planted green roofs which would improve the ecological, environmental, and social benefits of a green roofs. While redirecting rainfall showed promising approach, further work is required to improve their design to find the optimal method to redirect more water to plants and improve the coverage of plants on green roofs. Finally, using results from both experiments, I developed and validated a new green roof water balance model to simulate long-term green roof rainfall retention and plant performance in two contrasting climates (temperate vs semi-arid climates). Green roofs showed high rainfall retention in both temperate and semi-arid climates, regardless of substrate depth, plant density and presence/ absence of runoff zones. Even unplanted roofs showed high retention in both climates, showing that evaporation is the major component of evapotranspiration and therefore a primary driver of rainfall retention. In this experiment, midday leaf water potential was used to indicate the maximum water stress experienced by plants during the day and therefore plant drought stress. Therefore, I modified the water balance model used in the first experiment, by using the relationship between midday leaf water potential (MegaPascal) and substrate water content (S) to estimate plant drought stress. As expected, green roofs in semi-arid climates had significantly greater plant drought stress (more negative water potential) as compared with those in temperate climates, with no observed benefit in rainfall retention, despite increased substrate depth. Hence, a substrate depth of 150 millimeter could achieve optimal retention in both temperate and semi-arid climates. Increasing substrate depth, plant density and the use of runoff zones was less important for improving rainfall retention than climate. The modeled results also highlight that an unplanted roof is equally good for stormwater management alone, as it can achieve similar rates of rainfall retention as compared to a planted roof. However, keeping in mind the ecological, environmental, and social benefits of vegetated green roofs with good plant coverage, it is not recommended that practitioners install non-vegetated green roofs. Overall, the results showed that green roofs perform very well for rainfall retention, in both temperate climates with a large proportion of small rainfall events, and semi-arid climates with an annually low rainfall depth. However, only one plant species was evaluated in my thesis, which would have impacted on these results as the plants were high-water using species that could effectively dry out substrates after rainfall and also tolerate drought stress in dry substrates. The design of green roofs for good plant coverage and survival in semi-arid climates is likely to be more challenging than constructing in temperate climates in real conditions due to the risk of plant death where drought periods are more severe and prolonged. In this case, it is likely to be preferrable to plant low water using succulent species. In both temperate and semi-arid climates, green roof substrate depth did not necessarily need to be deeper than 150 mm, as the increase in rainfall retention was minimal and plant drought stress could not alleviate beyond this depth. Installing runoff zones is a promising approach to changing how water is distributed on green roofs and have the capacity to reduce plant drought stress. However, they can also promote preferential flow pathways minimising the water storage capacity of substrates and decreasing the evaporation from surface of substrates underneath their structure and therefore, reducing rainfall retention. Hence, reconsideration the design for such runoff zones could be a potential avenue of future research. In the end, the practical output of this research suggests that green roofs with lower plant density such as 1 plant per 0.1 square meter and substrate depth such as 150 millimeter can effectively retain rainfall in temperate and semi-arid climates. While in temperate climates, higher water using plant species can be used, it is recommended that in semi-arid climates, green roofs are planted with low water using species such as succulents to support vegetation cover on green roofs. This means that even when green roof plant cover reduces over time, green roofs will still have high performance for rainfall retention.
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    The effects of fire and landscape structure on animal communities, species, and connectivity
    Zylinski, Simeon ( 2023-04)
    The loss and fragmentation of habitat associated with land use change is the primary driver of global biodiversity declines. Changes to fire regimes that alter habitat suitability also threaten a range of animal taxa. Fire has been increasingly recognised as an important ecological process and is now used to manage fire-prone landscapes around the world, but important questions remain about the effects of fire regimes on animals, especially in fragmented landscapes. The aim of this thesis is to determine the influence of landscape structure (the composition and configuration of landscape elements) on animals in heathy woodlands in southern Australia in terms of fire, fragmentation, and interactions between them. First, I explored post-fire growth stage and land use together as components of landscape structure and assessed their relative and interacting effects on mammal communities. I used camera traps to collect mammal presence-absence data in 2019-20 and analysed it using ordination and linear modelling. I found that land cover composition was the primary influence on community composition. The composition of the fire mosaic had a secondary, weaker effect and one that may change depending on land cover composition. Second, I explored habitat structure as a mechanism by which fire regimes may affect mammal species, using a species activity index derived from the same camera trap data. Post-fire growth stage (a categorical representation of time since fire) was not a direct predictor of any species’ activity levels, but some habitat structure attributes were linked to certain growth stages and were therefore a mediating influence on animals. Finally, I assessed how the growth stages influence functional connectivity for a litter-dwelling skink. I used genetic data, landscape resistance modelling, and circuit theory-based mapping to find the relative connectivity of land use types and growth stages. Functional connectivity varied little with growth stage, with the primary influence on connectivity being the matrix of pasture and forestry plantation. Overall, I did not find direct effects of growth stage on animal communities, species, or connectivity. However, less obvious effects such as the composition of the fire mosaic beyond the site-scale and indirect effects through habitat structure are important to consider in future fire management. The extent of native heathy woodland was also vital for native mammal communities and functional connectivity; remaining native vegetation must be protected and expanded for the best outcomes for native diversity and species persistence.
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    Dietary strategies to adapt to, and mitigate, climate change in sheep
    Prathap, Pragna ( 2023-04)
    Climate change and associated global warming are major menaces to the Australian sheep industry. In addition to being susceptible to the harmful effects of climate change, sheep actively contribute to it through the release of methane (CH4) into the atmosphere. The aim of this thesis was to test and identify suitable feed additives that can reduce enteric CH4 emission and improve the thermoregulatory responses, rumen and digestive functions that were impaired by heat stress in sheep. In the first experiment, sheep were exposed to 3 different durations of heat stress (1 day, 3 days and 5 days; 28 to 38oC and 40 to 60% relative humidity; RH) with thermoneutral being the control (18 to 21oC and 45 to 55% RH) and observed variations in the rumen fermentation profile and rumen microbiota. The following two studies had three different groups of sheep based on the diet; wheat based diet (WD), Bioprotect treated wheat based diet (BD) and maize based diet (MD). Sheep experienced 3 consecutive periods of varying temperature and feeding levels. Period 1 (P1) consisted of 1.7xmaintenance energy (MF) feeding level and thermoneutral conditions (18 to 21oC and 40 to 50% RH). During period 2 (P2) sheep were fed at 1.7xMF level and were exposed to heat stress (28 to 40oC and 30 to 50% RH). During period 3 (P3) sheep were held under heat stress and fed at 2.0xMF level. In the fourth experiment, sheep were supplemented with two different dosages of a sugarcane derived polyphenol (0.25PG and 1PG) and tested for their enteric CH4 mitigation potential and production responses. To explain differences in the enteric CH4 production and ascertain the influence of Polygain on rumen microbiota 16s rRNA sequencing was also explored. The final experiment reported in this thesis studied the effect of an essential oil mix, Agolin, on enteric CH4 reduction and production variables in growing lambs. Results from this thesis demonstrated that short duration heat waves particularly, 3 and 5 days of heat stress, can significantly reduce total and individual rumen volatile fatty acid (VFA) concentrations and alter the VFA profile and rumen microbial diversity indices and richness of certain microbes of second cross lambs. Treating wheat with Bioprotect can partially alleviate the effects of heat stress on the thermoregulatory responses of sheep. As Bioprotect works as a rumen bypass feed by promoting the digestion of starch and protein in the small intestine, animals experience less metabolic heat from rumen fermentation. This enables the sheep to have better body temperature control. Bioprotect can also reduce enteric CH4 from sheep without hampering diet digestibility and dry matter intake (DMI). Polygain feeding reduced CH4 emissions without compromising average daily gain (ADG) or DMI. The highest CH4 reduction (49% reduction). was achieved from the lowest dosage of Polygain (0.25% PG) used in the study. Agolin was also successful in reducing CH4 emissions from sheep. Sheep fed Agolin showed a 27% reduction in CH4 without reducing DMI or ADG. The findings from the work reported in this thesis are novel as most of the work covered in the thesis is pioneering research in the sheep industry. However, it is important to conduct follow up research over longer durations and with larger sample sizes for policymaking if these feeding strategies are to be adopted.
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    Landscape-scale disturbance history and the dynamics of the conifer taxa of Bidoup–Nuiba National Park, Vietnam
    Nguyen, Thiet Van ( 2023-03)
    Tropical forests are complex and poorly understood ecosystems. In recent decades large-scale, long-term forest dynamics plots have been providing important insights into basic demographic processes such as recruitment, growth, and mortality. However, this information offers little insight into long-term forest dynamics and the role of infrequent disturbances that may occur at the scale of decades to centuries. Understanding how species-rich tropical forests will respond to global change requires understanding these long-term dynamics. Dendroecology, the study of tree rings, has provided the foundation for understanding forest dynamics in temperate forests in the northern hemisphere and parts of the southern hemisphere. It has been little applied in the tropics where most tree species do not have annual growth rings. The overarching aim of this study was to better understand the ecology and dynamics of Vietnam’s Central Highlands, and, in particular, the rich conifer taxa that are found there. To address this, my thesis involves the application of dendroecological approaches to: (1) reconstruct historical fire regimes in the Central Highlands of Vietnam; (2) understand the historical dynamics of Pinus kesiya forests and (3) the spatial and temporal patterns of recruitment and growth of the endemic conifer taxa in mixed conifer-angiosperm forests, and (4) identify angiosperm species with significant potential for future tree-ring based studies. A detailed reconstruction of how disturbances have varied across the Central Highlands landscape over recent centuries will provide important insights into the response of these forests to past disturbances and climate variability, as well as potential future trajectories of development under a changing climate. My thesis presents one of the most comprehensive reconstructions of fire in tropical forests using tree rings of Pinus kesiya in the Bidoup Nuiba National Park (BNNP) in the Central Highlands of Vietnam. A tree ring-based fire reconstruction showed that fire occurrence increased after 1900 and was highly correlated with climate indices (ENSO and PDSI) during the period 1900 – 1960. However, after 1964 the relationship between climate and fire disappeared due to the overwhelming pressure of human ignition sources, which have effectively eliminated climate as a factor limiting fire in these landscapes. While climate change is seen as a potential driver of changing fire regimes in many parts of the world, the role of local human populations may be equally or more important in shaping them. A detailed history of fire in these forests provides a baseline against which recent and future changes can be assessed. Dendrochronological analysis also indicated that extreme droughts, fire, and canopy disturbance have been associated with tree regeneration, growth, and canopy recruitment for centuries. The age distributions of Pinus dalatensis, Keteleeria evelyniana and Fokienia hodginsii show a distinct pulse of recruitment during the 1750s and during the period 1800-1850 that consistently coincided with extreme regional droughts. Periods of sudden and sustained growth release amongst these endemic conifers were associated with regional mega-droughts in the late 18th and 19th centuries. Results from superposed epoch analysis between Palmer Drought Severity Index and discrete tree release events indicated that extreme droughts and abrupt changes in moisture availability may have contributed to increased canopy disturbance rates and tree-level mortality. The effects of drought on tree growth were typically recorded in the tree rings 1-5 years after the drought event. This indicated that extreme drought conditions may drive large-scale canopy disturbances in BNNP. My results also confirmed that growth releases occurred within ~5 years of recorded fire events. This relationship between growth releases and fire events is consistent over 250 years of tree-ring records (1770-2020). Finally, my thesis demonstrated that a number of the angiosperm tree species occur in BNNP have significant potential for tree-ring studies. This is the first study to systematically examine the potential of a large number of angiosperm species for dendrochronological study in Vietnam. Demographic information derived from tree-rings of angiosperms could provide well-dated, long-term data that complements the tree-ring record from the conifers at BNNP. This would further advance our understanding of forest dynamics and the impacts of climate change in these species-rich tropical landscapes.
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    Phenolic Profile and Potential of Chicory and Lucerne to Ameliorate Heat Stress in Broilers
    Iqbal, Yasir ( 2023-03)
    There has been a global aggregate increase in meat production over recent decades. Driving this increase has been an increase in poultry production, which due to its efficiency is also displacing other meat sources such as beef. However, these fast-growing broilers are more susceptible to heat stress and significant reduction in productivity of poultry birds has been observed with the advent of frequent heat waves and increase in environmental temperature in the recent decades. Initially, antibiotic growth promoters were applied to improve productivity of poultry. With increased understanding about antibiotic resistance, there has been a drive to search for alternative strategies that could effectively improve poultry performance without the use of antibiotics. Increasingly there is an interest in compounds grown by plants (phytochemicals) that have antimicrobial properties. Polyphenols are among the most diverse class of phytochemicals that are expressed by plants to confer a range of biological activities. Owing to the biological properties, they have been used as nutritional supplements, natural product-based drugs and/or ingredients in different food, feed and cosmetic formulations for a long time and have been part of disease control strategies since the ancient times. The health benefits of polyphenols are credited to their strong antioxidant potential and the ability to scavenge free radicals and reactive oxygen species. Therefore, this project explored polyphenolic profiles of six plants (chicory, lucerne, narrow leaf plantain, white clover, perennial ryegrass and tall fescue), quantified their major polyphenol compounds and determined their antioxidant potential. Results indicated the presence of 56 polyphenols in lucerne, 29 in chicory, 27 in white clover, 25 in narrow leaf plantain, 15 in perennial ryegrass and 14 in tall fescue. Based on the higher diversity of polyphenols, chicory and lucerne were selected to assess their suitability for inclusion in broiler feed. As a first step, chicory and lucerne were subjected to gastrointestinal digestion and cecal fermentation in an in vitro model of the broiler gut and the effects on antioxidant capacity and bioaccessibility of chicory and lucerne polyphenols were studied. Furthermore, the production of gas and short chain fatty acids, and changes in microbiota composition were also studied following in vitro cecal fermentation of chicory and lucerne. The results indicated that chicory and lucerne favoured the growth of beneficial bacteria and suppressed the growth of pathogens. The most important finding was that chicory and lucerne suppressed growth of Clostridium genus that contains major pathogens of poultry. Hence, chicory and lucerne exerted a positive influence in regulating microbiota changes during cecal fermentation in an in vitro model of broiler gut. Further, chicory and lucerne improved short chain fatty acids production that help to improve gut health and microbial environment. This could have beneficial effects on broiler health and productivity. Based on the findings of in vitro experimentation, chicory and lucerne were supplemented in broiler’s feed to further investigate their beneficial effects and potential to ameliorate the adverse effects of heat stress on gastrointestinal tract, production performance and meat quality of broilers. Heat stress reduced the organ weight, plasma vitamin C, transepithelial electrical resistance and villus height of ileum and jejunum. The broilers in the experiment displayed increased parameters of heat stress such as elevated rectal temperature and respiration rate. This was supported by increased haematological changes such as reduced blood pCO2, TCO2, HCO3, haematocrit and haemoglobin under heat stress. The increased indices of heat stress adversely affected health and productivity as heat stressed broilers showed a considerable decreased in slaughter weight. Additionally heat stress increased lipid oxidation (TBARs) of breast muscle, which is associated with lower quality meat, increased drip loss and reduced shelf life. Chicory and lucerne supplementation partially ameliorated the effects of heat stress on broiler production. Broilers fed lucerne showed higher average daily weight gain and lower FCR indicating an overall improvement in growth rate. Chicory reduced the physiological responses to heat stress and ameliorated negative influence of heat stress on haematological parameters through reduction of blood HCO3. Furthermore, chicory and lucerne increased jejunal and ileal villous height and ileal transepithelial electrical resistance when supplemented together. Chicory and lucerne also favoured the growth of beneficial Faecalibacterium and reduced pathogenic Clostridium. Further, drip loss and lipid oxidation (TBARs) of breast muscle was reduced with chicory and lucerne supplementation. Collectively these data indicated that chicory and lucerne improved broiler growth rates, most likely due to improved digestive capacity through improved mucosal growth, upregulation of positive bacteria and inhibition of pathogenic bacteria. The addition of chicory and lucerne to the diets reduced parameters of heat stress, indicating resilience to production under warmer conditions. Furthermore, it was apparent that chicory and lucerne reduces oxidative stress, which had a positive effect on meat quality.
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    A glimpse into land-use futures: Simulating socioeconomic pathways within a temporally recursive, land-use explicit computable general equilibrium model
    Cantele, Matthew ( 2023-03)
    Equilibrium models are frequently employed to examine the potential impacts of economic, energy, and trade policies as well as form the foundation of most integrated assessment models. Most equilibrium models are best classified as policy-change models, suitable for examining the impact of specific trade-related policies at a single point in time. Several improvements to these models are necessary in order to create a more useful tool within the larger context of a coupled model framework, namely the way land is represented and the quality of underlying economic data. In the first chapter we provide an introduction to equilibrium models, their use within integrated assessment models, and an overview of the modeling framework. In Chapter 2 we extract data from 10 years of published equilibrium models, focusing on how these models have been extended beyond their economic origins. The results indicate that there is greater spatial coverage of high income countries compared to low income countries, with notable gaps in Central America, Africa, the Middle East, and Central Asia. We also find a high degree of aggregation within production inputs and sectoral outputs, particularly within the context of global socioeconomic scenarios. Within Chapter 3 we develop a novel, recursive dynamic land-use explicit computable general equilibrium model using the most recent economic and land-use data available to build confidence in the model's ability to predict land-use change under different socioeconomic trajectories. We integrate several major methodological advances including representation of land in biophysical flows and implementation of an endogenous land supply. We collect and harmonize economic data for 232 countries to develop historical trajectories from 2011 through 2020. We find that land-use predicted by the model is highly sensitive to the choice of land supply elasticity as well as magnitude of labor supply shock. This work highlights the importance of conducting hindcasting runs in order to compare model outputs with the historical record prior to moving on to more ambitious long-term simulations. In Chapter 4 we simulate a long-term, global socioeconomic scenario known as a Shared Socioeconomic Pathway. Here we simulate the dynamics-as-usual Shared Socioeconomic Pathway 2 with the model developed in Chapter 3. We begin this work by recalculating GDP trajectories according to the most recent demographic scenarios and growth projections. We then carry out 43 sequential shocks at two-year intervals from 2014 until 2100 using the new GDP and population trajectories. We find that our land-use results are largely consistent with publicly available outputs from other prominent integrated assessment modeling teams, with the added benefit of reproducibility. At a regional level our model predicts considerable expansion of pasturelands in sub-Saharan African as a function of extreme GDP and demographic growth. We also predict a rapid increase in trade between OECD/EU countries and low-income countries within sub-Saharan Africa and South Asia. In Chapter 5 we provide a summary of the key results for each chapter and dedicate a section to some of the methodological challenges faced. Here we also discuss insights gained as well as identify where future work is necessary.
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    Pathogenicity and early detection of Verticillium dahliae and V. albo-atrum in potatoes in Australia
    Shin, Mee-Yung ( 2023-04)
    Verticillium wilt is a vascular wilt disease of potatoes primarily caused by the soilborne ascomycete fungi, Verticillium dahliae Kleb. and V. albo-atrum Reinke & Berthold. Verticillium wilts are amongst the most economically devastating crop diseases worldwide as they detrimentally impact crop yield and quality as well as exponentially increase pre- and post- planting management costs. Verticillium dahliae is widespread across potato growing fields in south-eastern Australia whilst, to date, V. albo-atrum has only been detected in Victoria and Tasmania. Verticillium wilt is an exceedingly challenging disease to control due to the broad host range of the causal pathogens and their long-term persistence in soil in the absence of a susceptible host. There are no curative measures available once Verticillium spp. have invaded plant tissues. As such, early detection is a critical component of an effective management strategy for Verticillium wilt, as it can facilitate growers to take actions that can prevent or significantly restrict disease expansion. Non-destructive early detection methods may involve machine- based technologies coupled with machine learning modelling, but initial validation trials are yet to be conducted in potato in controlled conditions. Glasshouse trials were conducted to assess early (2 to 5 weeks after inoculation) infection and colonisation by V. dahliae using visual symptom assessment, tissue colonisation assays, and RT-qPCR DNA quantification of the amount of V. dahliae present in the infected stems. Visible symptoms of Verticillium wilt first occurred in plants of the moderately resistant cultivar Denali and the susceptible cultivar Russet Burbank at two weeks after infection, and tissue colonisation assays showed that the lower stems, crowns, and upper root tissues of plants of both cultivars were extensively colonised within these two weeks. RT-qPCR also showed the quantity of V. dahliae DNA generally increased in the lower stems and crown tissue each week after infection in Russet Burbank plants. This confirmed that V. dahliae was pathogenic and highly virulent in potato plants within two weeks of infection. Furthermore, this study showed that quantitative disease resistance or tolerance is likely to occur in Denali and further studies are required to confirm the type of resistance. Visual symptom severity progressed more slowly in Denali and by the conclusion of the trials, the mean symptom severity was 39% and 75% for Denali and Russet Burbank respectively. Despite this, both cultivars were observed to be extensively colonised within two weeks. During Trial 1, the mean quantity of V. dahliae DNA was significantly different (P = 0.004) and was 0.56 pg/ul and 2.23 pg/ul in Denali and Russet Burbank respectively. Conversely, during Trial 2, the mean quantity of V. dahliae DNA was not significantly different (P = 0.106) and was 1.51 pg/ul and 2.25 pg/ul respectively. Glasshouse trials to assess early infection and colonisation by V. albo-atrum were also conducted using visual symptom assessment, tissue colonisation assays, plant physiological measurements, and visible near-infrared (Vis-NIR) spectroscopy. Symptoms of Verticillium wilt were not observed during at any time during the trials. Although roots, stolons, and crowns were observed to be extensively colonised in inoculated plants, stem colonisation was not observed in 69 out of 140 plants. Multifactorial analyses showed that infected and uninfected plants could be visually grouped at two weeks after inoculation using Vis-NIR. Vis- NIR measurements alongside stem, root, and crown infection, were the best indicators of infection within plants. These results showed that V. albo-atrum is pathogenic in potato but has low virulence within five weeks of infection. These trials justified the merit of conducting further investigations into the use of NIR spectroscopy and NIR modelling for the early detection of infection of potatoes by the more pathogenic V. dahliae. Two artificial neural network (ANN) models were developed using the raw absorbance values within the 1596-2396 nm light spectral range as inputs to predict photosynthetic rate, transpiration rate, and stomatal conductance (Model 1), as well as predict whether Denali and Russet Burbank plants were infected or not infected by V. dahliae (Model 2). The results showed high accuracy for Model 1 (R = 0.89 using all samples from Trial 1) with a deployment accuracy of R = 0.76 using all samples from Trial 2. High accuracy was also obtained for Model 2 using all samples from Trial 1 (94%) with a deployment accuracy of 84% using samples from Trial 2. The results showed that V. dahliae presence could correctly be identified in potato plants two days after infection without any visible symptoms present in plants. These novel ANN model types show high potential in introducing a cost-effective, efficient, and user- friendly means for growers to detect Verticillium wilt before symptoms occur. Overall, this study demonstrated that pathogenic and virulent strains of Verticillium spp. are active within plant tissues within 2 weeks of infection and that machine-based technologies and machine learning modelling can be used for the early detection of Verticillium wilt of potatoes in Australia.
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    Exploring legume protein derivatives for enhanced essential element bioaccessibility
    Zhang, Yianna Yi ( 2023-03)
    Essential element dyshomeostasis is a tenacious nutritional risk factor underlying the pathophysiology of numerous diseases in humans. A fundamental cause is the inadequacy of elemental bioaccessibility from dietary sources, especially plant-based foods. Out of the essential dietary elements, iron (Fe) and zinc (Zn) are among the broader class of micronutrients whose deficiencies affect approximately one-third of people worldwide. Oral supplementation is the first line of therapy being both accessible and affordable. However, conventional elemental salt supplements often create an imbalance between low bioaccessibility and toxic overload within the body, leading to adverse side effects and unknown safety with cumulative exposure. Some food-derived biomolecules possess physicochemical properties that may be utilised to enhance elements’ solubility, and hence bioaccessibility during digestion for improved absorption. As such, the current investigation explored the potential properties of legume-derived protein products that may enhance the bioaccessibility of Fe and Zn. The study began by extracting water- and NaCl-soluble protein fractions from three Australian-grown pulses (pea, lupin and faba), with their effects on fortified Fe and Zn bioaccessibility examined using an in vitro simulated gastrointestinal model. Both promotive and inhibitory effects were observed depending on the fraction and protein source, as well as the digestion state. Lupin and faba salt extracts enhanced Fe(II) and Zn small intestinal solubility under fed and fasted digestion states, respectively. Meanwhile, water-soluble pea proteins showed the greatest potential to solubilise Fe(III), mostly during gastric digestion. Subsequent to the preliminary study, pea protein extract was selected to be subjected to bioprocessing approaches involving either enzymatic hydrolysis (protease, phytase, or both) or inoculated fermentation (Lactobacillus plantarum) to enhance its potential as carrier of Fe(III) or Zn during small intestinal digestion. All treatments involving phytase were effective at enhancing Fe(III) solubility during small intestinal digestion, whereas all treatments involving protease were able to enhance Zn solubility only under the fed state of digestion. This reflected differences in the binding behaviour between Fe(III) and Zn with the proteins during digestion, indicating that they be investigated separately. Focusing on iron as the most commonly deficient micronutrient, the third study characterised the properties of the soluble Fe(III)-binding peptides potentially responsible for the enhanced solubility observed in the previous chapters. The unpurified hydrolysate was found to bind 5.3 mg of soluble iron/g of powder. The Fe(III)-binding peptides that were separated using IMAC-Fe(III) and characterised using LC-MS/MS were found to be rich in Glu, Asn, Lys and Leu, and low in sulfur-containing amino acids Met & Cys. Further bioinformatics analyses identified 15 novel peptides (< 1.5 kDa) that were suitable for enhancing Fe(III) bioaccessibility based on their abundance, chelation score, isoelectric point and hypo-allergenicity. Although pea protein hydrolysates were able to enhance Fe(III) bioaccessibility in the previous studies, its poor overall bioaccessibility can lead to increased iron levels in the lower gut, underscoring a need to examine their effects on the gut microbiota. The final study investigated the effects of iron fortification with and without pea protein fractions (intact and hydrolysate) on both small and large intestinal bioaccessibility, using the INFOGEST gastrointestinal model with colonic fermentation using a human faecal culture. Following 24 h of fermentation, all treatments involving iron fortification saw a decline in within-species diversity, relative increases in members of Proteobacteria and a loss of Lactobacilliaceae. Fortification of the hydrolysate was found to reverse the intact protein’s inhibitory effects on small intestinal iron solubility, but led to a decline in total short-chain fatty acids (SCFAs), and significant increases in Proteobacteria comparable to that found in the iron salt control. Meanwhile, the fortified intact protein saw an increase in SCFAs and in the butyrate-producing family Propionibacteriaceae. This thesis addresses the critical role of legume protein fractions as modulators of fortified iron/zinc bioaccessibility, challenging ways to overcome their reputation as absorption inhibitors. It expands extant knowledge on how properties of legume peptides that bind to iron and/or zinc can be associated with promotive or inhibitory effects on iron/zinc bioaccessibility during digestion, as well as diverging effects on the gut microbiota. Outcomes of the study prompts that further research on ways of improving legume proteins’ digestibility may assist to promote fortified Fe and Zn bioaccessibility.
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    The effect of in vitro manure nitrogen composition and lignite application on dairy cattle manure ammonia emission
    SONG, YUMENG ( 2022-09)
    The major objectives of the master study were to estimate the urinary nitrogen (UN) to faecal nitrogen (FN) ratio from sampled dairy cattle, to quantify the effectiveness of lignite application on reducing ammonia (NH3) emission and to establish the relationships between dairy cattle manure NH3 emission, nitrogen (N) isotope fractionation (delta-15N), the N to phosphorus (P) and N to potassium (K) ratios in diverse manure property and environmental conditions. The in vitro manure incubation system was conducted to explore the manure daily changes, daily NH3 emission and the effect of lignite application on reducing NH3 emission. The UN to FN ratios were approximately 1 to 1, calculated via the N balance study. Total 600 g reconstructed manure was put into each incubation system to achieve a manure UN to FN ratio of 1 to 1 for CT and CT+L, and 2 to 1 for 2U1F and 2U1F+L. Further, 250 g lignite powder was added into CT+L and 2U1F+L and mixed with manure. Acid traps were settled to collect emitted NH3 emission. A total of 15 g manure sample and 15 mL of acid sample were collected daily from each incubation system and stored frozen (-20 degrees centigrade). The daily NH3 emission in the non-lignite group decreased with incubation days while it increased with days in the lignite group. The major NH3 emission occurred in the first 7 days in the non-lignite group and in the last 10 days in the lignite group. There was a weak relationship between temperature and daily NH3-N emission (R2 = 0.30, P <= 0.05). The cumulative NH3-N emission of 2 UN to 1 FN ratio (2U1F) treatment was 45.8% higher than control (CT) treatment in non-lignite groups, while it of 2U1F with lignite application (2U1F + L) was 100% higher than CT with lignite application (CT + L). The lignite application reduced the cumulative NH3-N emission by 87.5% compared to CT and CT + L treatments and 82.9% compared to 2U1F and 2U1F + L treatments. The manure delta-15N from the CT and 2U1F treatments increased with incubation days (R2 = 0.85 and 0.91, respectively; P <= 0.001). However, there was no relationship between manure delta-15N from the CT + L, 2U1F + L treatments and incubation day (R2 = 0.07 and 0.08, respectively; P <= 0.001). The manure N to P ratio decreased with incubation days (R2 = 0.81, 0.73, 0.81, and 0.84 in CT, 2U1F, CT + L, and 2U1F + L treatment, respectively; P <= 0.001). There was a weak relationship between manure N to K ratio and incubation days found in CT treatment (R2 = 0.28, P <= 0.001), while manure N to K ratio decreased with incubation days in the other three treatments (R2 = 0.70, 0.79, and 0.90 in 2U1F, CT + L, and 2U1F + L treatment, respectively; P <= 0.001). Overall, the master studies showed that manure delta-15N could not be used as an accurate biomarker to estimate NH3 emission in relatively low NH3 concentrations (R2 = 0.02, P <= 0.001) while the N to P ratio was better to use (R2 = 0.85, P <= 0.001). The manure delta-15N outperformed to be the best biomarker to estimate NH3 emission in relatively high NH3 concentrations (R2 = 0.83, P <= 0.001). The lignite application was an effective method to reduce NH3 emissions. However, further study is required to investigate the maximum absorption ability of lignite for improving the application in livestock industries.