The Australian grains industry is fundamental to the overall agricultural sector, comprising one of Australia’s largest category of food exports. Over recent decades, the grains industry has faced challenges. Its total factor productivity growth has slowed due to factors such as climate change, extreme weather events, declining research, development and extension, and slower adoption of new technologies. This has been coupled with greater competition in Australia’s main grain export markets. In order to increase productivity and maintain international competitiveness, greater and better-targeted investments in research, development and extension and market intelligence are required. Equilibrium Displacement Models (EDMs) are useful for estimating the net benefits of agricultural RD&E and the distribution of these benefits along the value chain, enabling an evaluation of different research investments. This thesis develops three EDMs, one for each main agroecological region in Australia—the Western, Southern and Northern regions. Combined together, these models provide a stylised representation of the Australian grains industry and can be applied to assist investment decisions by RD&E funders and other parties seeking to boost the profitability of various parts of Australia’s grains industry. Eight hypothetical RD&E investment scenarios are modelled for each region, depicted by one per cent exogenous parallel shifts in the relevant market supply and demand curves associated with each region. Under each investment scenario for each region, both the change in total economic surplus as well as the welfare changes in each of the different industry sectors are estimated. It is found that, overall, the size of the total economic benefits is determined largely by the size of the market in which the RD&E investment takes place, with a high gross revenue market generating higher overall returns. Additionally, the size of the innovating market also impacts the distribution of benefits, as the larger the gross value of this market, the greater its share of total benefits received. The results generally suggest that producers receive a greater share of benefits from on-farm research than from off-farm research. They also receive comparably large shares from export market research and promotion. Differences in results are also observed between the three regions. Due to regional differences in supply chain characteristics, any particular RD&E investment scenario will affect each region differently. Stochastic sensitivity analysis is also conducted for the uncertain market parameter values specified in the base model. Using the set of EDMs to generate information that better informs agricultural research, development and extension investment decisions and industry actions, can ultimately boost the economic role and performance of Australia’s grains industry.

Climate change is adversely affecting global food production. Reduced crop yields and increasing food demands are presenting new challenges for developing resilient crop varieties. Legume plant soybean is an important food crop next to cereals. Soybean is a rich source of high-quality vegetable oils, protein, nutraceuticals, and it is widely cultivated across the globe for both human and animal consumption. According to the Australian oilseed federation, soybean cultivation strengthens regional economies and contributes to 2.5 billion dollars of the Australian oilseed industry. To breed better soybean crops, a study of light and temperature perception is important, as these events control the process of flowering which is the first step towards total seed production. On the molecular level, light and temperature signal control is a complex process mediated by a network of photoreceptors and transducers. One such transducer is Phytochrome Interacting Factor 4 (PIF4). It is involved in the perception of external environmental stimuli to integrate the information of daily light and temperature fluctuations with the internal physiology of plants. PIF4 has been studied in the model plant Arabidopsis thaliana, but knowledge about its counterparts in soybean is limited. To understand the function of PIF4 in soybean, an integrated genomics, molecular, and functional characterization approach was employed. The genomic analysis show that there are seven active copies of PIF4 gene in the genome of the cultivated soybean (Glycine max). The seven soybean PIF4 genes have evolved at different time points during the soybean genome duplication events, and phylogeny is suggestive of the existence of a conserved PIF4 clade (PIF4 I), which includes Arabidopsis PIF4 and a clade that groups only the PIF4s of legumes (PIF4II). To assess the gene expression patterns of soybean PIF4s during variable photoperiods and temperature conditions, quantitative RT-PCR was performed. Quantitative RT-PCR results showed that three PIF4s belonging to the PIF4I clade (i.e. GmPIF4a, GmPIF4b, and GmPIF4c) had conserved PIF4 like expression (consistent with Arabidopsis pif4) in inductive photoperiod (short day; SD), whereas two soybean PIF4s belonging to the PIF4II clade (i.e. GmPIF4f and GmPIF4g) exhibited reduced to nil sensitivity to short-days. The mRNA transcript levels of three PIF4s were elevated at 35-degree centigrade as compared to 25-degrees centigrade in short days. In non-inductive photoperiod (long day; LD), all soybean PIF4s were responsive to extended light phase suggesting their functional role in long photoperiods. Further, no significant transcript variation was observed at elevated temperatures in long days, except one PIF4, which expressed at higher levels at 30-degrees centigrade as compared to 25-degrees centigrade. Mining of previously published RNA sequencing data obtained from leaf samples of a short-day soybean cultivar (Bragg) undergoing floral transition showed that one of the PIF4s was differentially regulated with high differences in transcript read values on consecutive short days. This soybean PIF4 was designated as GmPIF4b. GmPIF4b was functionally characterized using ectopic expression in Arabidopsis, mutant complementation in Arabidopsis pif4-101 mutants and gene over-expression in the soybean cultivar, Bragg. Ectopic expression of GmPIF4b in Arabidopsis resulted in elongated hypocotyls and early flowering responses suggesting the function of GmPIF4b in hypocotyl elongation and flowering responses. Arabidopsis pif4-101 mutant contains a mutation in the exon-5 of pif4 gene. This mutant is characterized by shorter hypocotyls and a compact rosette size. Complementation of GmPIF4b in Arabidopsis pif4-101 mutant partially rescued the short hypocotyl and compact rosette phenotypes of pif4-101 mutant. The results were suggestive of both conservation and divergence of GmPIF4b. To gain insights into the function of GmPIF4b in soybean, constitutive overexpression of GmPIF4b in soybean (Bragg) was undertaken. Constitutive overexpression resulted in decreased plant height, reduced leaf surface area, decline in total number of branches per plant, and early flowering in transgenic soybean plants as compared to the wild type. Quantitative RT-PCR was performed to study the transcript levels of soybean florigens; GmFT2a and GmFT5a in the transgenic plants (over expressing GmPIF4b). The transcript levels of GmFT2a and GmFT5a were significantly elevated in transgenic lines compared to the wild type. Late maturing soybean varieties, such as Bragg, can terminate flowering in sub-optimal photoperiods. To study the effect of GmPIF4b over-expression on termination of flowering, transgenic soybean plants (over expressing GmPIF4b) grown in short days were transitioned to non-inductive photoperiod (for 10 long days) at full bloom stage. Interestingly, wild type Bragg plants terminated flowers and produced less pods. Transgenic plants did not terminate their reproductive activity and gave rise to a higher number of pods per plant. To study the dynamics of GmPIF4b protein, immunoblot analysis was undertaken. The results showed that on protein level, GmPIF4b follows a strict diurnal expression pattern under both long and short days, suggesting the involvement of biological clock in regulating GmPIF4b protein expression. Chromatin immunoprecipitation was performed to study the protein-DNA interaction of GmPIF4b protein with the promoters of soybean florigens GmFT2a and GmFT5a. The results suggested that GmPIF4b interacts with the promoters of GmFT2a in short-day treated plants, whereas it interacts with the promoter of GmFT5a in a photoperiod insensitive manner. PIF4 is shown to be involved in nitrate assimilation and phosphate acquisition pathways. Soybeans plants were treated with nitrates or orthophosphates under inductive short days to analyse the GmPIF4b gene expression by RT-PCR. The results showed that the application of nitrates and orthophosphates can affect the levels of GmPIF4b transcript and can modulate the expression pattern of soybean floral identity marker gene, GmAP1. Hence, the outcome of this study can contribute towards developing climate-resilient varieties for the future.

Increasing the biomass yield of perennial forage crops remains a crucial factor underpinning the profitability of grazing industries, and therefore is a priority for breeding programs. The rate of genetic gain for dry matter yield (DMY) in forage crops is likely to be increased with the development and application of genomic selection (GS) strategies. However, realising the full potential of GS will require an increase in the amount of phenotypic data and the rate at which it is collected. Phenotyping remains a critical bottleneck in the implementation of GS in forage species. Current assessment of DMY in forage crop breeding includes visual scores, sample clipping and mowing of plots, which are often costly and time-consuming. New ground and aerial-based platforms equipped with advanced sensors offer opportunities for fast, non-destructive and low-cost, high-throughput phenotyping (HTP) of plant growth, development and yield in a field environment. This thesis aimed to develop, validate and deploy sensor-based non-destructive aerial, and ground-based HTP platforms to estimate DMY of perennial ryegrass plants in-field. Firstly, calibration and validation of aerial and ground based HTP platforms were developed to provide a non-destructive method to accurately estimate perennial ryegrass height and DMY. Secondly, the thesis compared a range of traits alone and in combination to demonstrate sensor based DMY estimation. Thirdly, this study demonstrated the application of combining normalised difference vegetative index (NDVI) from multispectral imaging and ultrasonic sonar estimates of plant height to estimate the seasonal distribution of DMY of 48,000 perennial ryegrass plants. Fourthly, the study discussed the application of developed platforms and data processing workflow which allows for an increase in the accuracy of genomic breeding values prediction in GS. Calibration and validation results indicated that plant height measurements from ultrasonic sonar and light detection and ranging (LiDAR) sensors showed the potential to measure plant height with consistent repeatability under controlled conditions and in field trials. NDVI demonstrated the capability for non-destructive DMY estimation of individual ryegrass spaced planted and sward plots. However, DMY estimation from NDVI saturates as the biomass increases. The combination of plant height and NDVI was found to improve the DMY prediction accuracy by up to 10%. This was achieved by combining NDVI and plant height with a simple multiplication combination (NDVI multiply by plant height), with the possibility to further improve the accuracy by combining the parameters in different models. This thesis assesses further the feasibility of combining NDVI from multispectral imaging and ultrasonic sonar estimates of plant height to estimate DMY of single plants in a large perennial ryegrass breeding program. Results demonstrated that the best prediction models of DMY of spaced-planted perennial ryegrass plants come from the multiplicative combination of NDVI and plant height (NDVIsq_PH). The K-fold and random split cross-validation findings imply that the combination of NDVI and plant height improved prediction accuracy over the use of NDVI and plant height alone. This yielded an accuracy of the coefficient determination of DMY estimation of more than 0.63 and root mean square error (RMSE) for fresh herbage yield, and dry herbage yield was less than 33 gram per plant and 8 gram per plant, respectively across multiple growing seasons. Therefore, to assess the application of combining NDVI and plant height for accurate DMY, a computational workflow was developed for image acquisition, data processing and analysis of spaced-planted perennial ryegrass plants. Fifty advanced breeding lines and commercial cultivars represented by a total of 48,000 individual plants were used to develop and validate the computation workflow for DMY prediction across three growing seasons. Combining NDVI and plant height of individual plants was a robust method to enable HTP of DMY estimation in a large population of ryegrass breeding. Similarly, the plot-level model indicated good to high-correlation between the predicted and measured DMY across three seasons with coefficient determination between 0.19- 0.81 and root RMSE values ranging from 0.09-0.21 kilogram per plot. The model was further validated using a combined regression of the three seasonal harvests. This study will have a significant contribution to the wide application of sensor technologies in forage research and plant breeding.

Soil microbial organisms are involved in many soil processes including nutrient cycling, impacting on soil quality and health. Anthropogenic activities such as nutrient addition influence soil ecosystems and soil environment. It is widely known that the contribution of urease inhibitors (UI) e.g. N-(n-butyl) thiophosphoric triamide (NBPT) and nitrification inhibitors (NIs) e.g. 3, 4-dimethylpyrazole phosphate (DMPP) in reducing N losses is associated with urea hydrolysis (and ammonia volatilization) and ammonia oxidization processes, respectively. However, little attention has been given to the understanding of the effect of NBPT on nitrification and urease producing microbes. Further, although the effects of NIs on ammonia oxidizers have been studied, there is limited information on how they influence non-targeted microbes or the newly discovered complete ammonia oxidizers (comammox Nitrospira). Some studies have reported that targeting mitigation of N losses through one pathway of the nitrogen cycle may lead to losses in another pathway. Therefore, the use of a combination of mitigation measures was suggested including combining UIs and NIs. Limited bio-molecular studies have investigated the effect of combined UIs and NIs on the soil N cycling microbes. In an incubation study on five soils from different parts of Victoria, Australia, using the terminal restriction fragment length polymorphisms (T-RFLP) and quantitative polymerase chain reaction (qPCR) techniques, we reported that the abundances of ammonia-oxidizing bacteria (AOB) and complete ammonia oxidizers (comammox Nitrospira), but not ammonia-oxidizing archaea (AOA), were significantly influenced by the application of NBPT, DMPP, and DMPP + NBPT. The structures and community composition of both AOA and AOB were influenced by NBPT, DMPP, or their combination. AOA, AOB, and comammox Nitrospira clade B might be significant contributors to nitrification in the studied soils. However, the contribution and responses of these microbes to nutrients, UI, or NI could be controlled by soil properties like soil pH. This study for the first time provided some new knowledge about ureolytic microbes and complete ammonia oxidizers (comammox Nitrospira) as influenced by NBPT and DMPP. However, there is a need for more information on how to develop a dual inhibitor compound whose individual compounds will work together effectively to target both hydrolysis and nitrification processes. It is also important to understand how comammox Nitrospira responds to different UI and NIs or their combinations, and the suitable rates of application of the UIs, NIs or their combinations for effective inhibition of comammox Nitrospira. Further, more studies have concentrated on understanding the molecular mechanisms of inhibition of ammonia oxidation by the NIs in short-term laboratory and field experiments. However, little is known about the effect of DMPP on soil enzyme activities, N cycling microbes (involved in nitrification and denitrification), or non-targeted microbes in soil following a production period in repeated chemical fertilizer and NI application regimes. Such a study has great implications for soil quality and health. Microbial communities were analyzed using Illumina sequencing and qPCR, from soil sampled 1 week after harvesting from a 4.5-year field experiment with repeated application of urea (U), urea + DMPP (UE) at 40, 80 and 120 kg N/ha. This analysis revealed that the AOB gene abundance increased as the N application rate increased (from 0 to 120 kg N/ha). The use of DMPP significantly reduced AOB and nirK gene copy numbers compared to urea alone at an application rate of 120 kg N/ha. There was no effect on the abundance of either ammonia-oxidizing archaea (AOA), comammox Nitrospira clade A and B, nosZ, or bacterial 16S rRNA genes. The community composition of AOB and AOA changed with N addition and use of DMPP while increasing the N application rate only changed the composition of AOB. Potential nitrification rates increased after the addition of N at 80 and 120 kg N/ha. There was no significant treatment effect on the relative abundance of total bacteria at the phylum level, indicating no residual effects of urea and DMPP at different rates on the non-targeted microbes. This experiment demonstrated that the application of N (with or without DMPP) at lower than 120 kg N/ha would not result in a significant impact on soil archaeal or bacterial ecology. Repeated application or overuse of chemical fertilizer can lead to environmental issues like soil acidification. The temporal effects of NBPT on soil ureolytic and ammonia-oxidizing microbes, crop yield, and nitrogen use efficiency (NUE) following repeated applications are not well understood. A perennial ryegrass (Lolium perenne L.) experimental site, received fertilizer treatments of urea applied alone at 40 kg N/ha and 80 kg N/ha or urea applied with NBPT (as Green Urea NV at 40 kg N/ha) in respective plots that had received the same treatments since 2014. The qPCR analysis of soil samples collected on a weekly basis for 45 days confirmed that the abundance of ureolytic microbes was higher in control (CK) compared to all N treatments on all sampling days, which was associated with changes in soil pH. Despite the reduced soil pH following repeated applications of urea with NBPT, ureC gene copy numbers were significantly reduced in the NBPT treatment plots applied at 40 kg N/ha compared to those in urea alone applied at the same rate. NBPT had no significant effect on the abundance of ammonia oxidizers. However, increasing the urea application rate significantly increased the abundance of ammonia-oxidizing bacteria (AOB) and complete ammonia oxidizers (comammox Nitrospira clade B). NBPT had no significant effect on pasture dry matter (DM) yield, N-uptake, or NUE. Increasing N application rate significantly increased pasture DM yield and N-uptake but this did not influence the pasture NUE. From the two field experiments, this thesis confirmed that repeated application of urea with NBPT or DMPP led to changes in soil physiochemical properties which included decreasing soil pH, and this controlled the response of soil microbes to chemical inhibitor applications. In both experiments with repeated applications, it was confirmed that AOB could be major players to nitrification in acidic soils with repeated chemical fertilizer applications with UI or NI. Future work should consider understanding the interaction between plants and soil microbial communities especially around the rhizosphere and how these may influence the efficacy of UI and NI on a short and long-term basis. Also, there is a need in the future to investigate how the inhibitor compounds and enzyme activities in different soils change following the application of these inhibitor compounds.

Beer and sparkling water are popular carbonated beverages within consumers as it can be evidenced by an important growth in terms of volume sales around the world. Although they are both composed of carbon dioxide (CO2), this gas is produced in different forms and the drinks present distinct performance in terms of their sensory and physicochemical characteristics. The most important factors that determine quality and consumer acceptability in all carbonated beverages are the visual aspects such as colour, bubble morphometry and dynamics and foam-related parameters as these create the first impression when consumers select the products. Currently, consumers are in a constant search for more premium or high-quality products, which has put pressure in their respective industries to remain relevant in the market. Available methods to assess physical and chemical parameters in carbonated beverages to assess quality tend to be costly, time-consuming and not reliable. Therefore, there is then a need to develop automatic, more reliable, accurate and affordable quality assessment techniques. From the sensory analysis perspective, traditional consumer tests to assess products acceptability are primarily focused on subjective conscious responses from participants which contribute a reduced amount of information, which many times it can be bias. Traditional methods to tap into the autonomic nervous system response from consumers, which is unconscious, are invasive and had not been implemented in the assessment of beer and sparkling water, which can complement and enhance objective and meaningful information for consumers from the physiological and emotional responses to these products. This research was focused on the development of novel techniques such as an automatic robotic pourer integrated with remote sensing to measure the physical dynamics of foamability and bubbles coupled with CO2, alcohol and pouring temperature to add chemical analysis. The data analysis included an artificial intelligence (AI) approach by using computer vision algorithms and machine learning modelling. The objective from these measurements was to assess color, bubble and foam-related parameters in both beer and carbonated water. Near-infrared (NIR) spectroscopy was used to obtain the chemical fingerprinting of the products and to analyze their relationship with foamability and bubble related measurements. Furthermore, an electronic nose was developed using nine gas sensors to assess aromas and beer quality to enhance the chemical (non-contact) analysis from the robotic pourer. Additionally, a new integrated system to assess consumer acceptability using a novel bio-sensory computer application (App) coupled with video and thermal cameras was developed to obtain biometric responses such as heart rate, face temperature, gaze fixations and facial expressions. This new App was used on panelists assessing different products considered in this research. The information gathered from these new techniques allowed to create different machine learning (ML) models with high accuracy (R>0.8) to classify beers according to their liking and physicochemical intrinsic characteristics. Likewise, different ML models based on regression algorithms were created using the data obtained from the robotic pourer, electronic nose, and NIR spectroscopy data to predict the products intensity of sensory descriptors, consumers acceptability and chemometry to assess beer quality. The results obtained from this research showed to be accurate, reliable, rapid and affordable tools that can be applied to the growing industries related to beverages production to monitor and increase product quality to compete in the international market.

Soybean (Glycine max L.) is one of the major crop plants since its seeds contain high levels of oil and protein. In addition, soybean’s unique ability in fixing nitrogen makes it a key plant for sustainable agriculture due to the increasing cost of nitrogen fertilizers caused by continuing depletion of petroleum. The demand for improvement of soybean yield has been rapidly growing due to the plant’s high nutritional values and its significance in sustainable agriculture. Flowering is a major step in plant life cycles as it plays crucial roles in reproductive success. Late flowering under favourable conditions allow plants to maximize their vegetative growth, which ultimately leads to improved seed production, whilst early flowering allows plants to secure their progenies under adverse growth environments. Comparative analysis of flowering genes between Arabidopsis and soybean has revealed conservation of most flowering genes. However, functions of most flowering genes in soybean are still unknown. Therefore, investigation of soybean flowering genes is expected to provide insight into flowering mechanisms of soybean. Plant genetic transformation is an important tool to improve agricultural traits and investigate functions of genes. Since reported success in soybean genetic transformation has been limited to inferior-breeding cultivars, development of stable transformation systems for commercial soybean cultivars will provide a new solution to meet the ever-increasing demand for soybean. In the present study, transformation systems for commercial cultivars of soybean were developed using the Agrobacterium-mediated transformation method. Transgenic soybean plants (cv. Bragg) containing yellow fluorescence protein (YFP) and herbicide resistant gene (bar) were produced using half-seed transformation method. Shoot elongation efficiency was increased (6 fold) by addition of phenolic compound inhibitors [adenine hemisulfate (40mg/L) and PVP 40,000 (500 mg/L)] during shoot elongation, resulting in improvements in the growth of transgenic shoots. Total 23 independent T0 putative transgenic lines were produced and herbicide resistance was confirmed via basta brush test (100mg/L glufosinate). Total two basta resistance lines exhibited YFP expression in leaves. Stable expressions of transgenes were observed in T1 and T2 generations. The roles of soybean LFY homolog (Glyma.06G163600.1) in flowering initiation was confirmed in this study. LEAFY gene (LFY) is one of floral meristem identity genes and plays essential roles in flowering. In soybean, two LFY homologs (Glyma.04G202000.1 and Glyma.06G163600.1) are annotated and they show high sequence similarity (Glyma.04G202000.1: 73.4% and Glyma.06G163600.1: 69.5%) with Arabidopsis LFY (AtLFY). Furthermore, soybean LFY homologs have two conserved DNA-binding domains (N- and C-domains). The expression levels of both soybean LFY homologs gradually increased in flowering inductive conditions and Glyma.06G163600.1(GmLFY1) showed a higher expression than Glyma.04G202000.1 (GmLFY2). These high sequence conservation and expression patterns of soybean LFY homologs suggested GmLFY genes may have roles in flowering initiation. Ectopic expression of GmLFY1 in transgenic Arabidopsis and tobacco plants induced early flowering phenotypes. Moreover, up-regulations of genes (AP1, SOC1 and LFY) involved in flowering were also detected in transgenic plants. These results suggest that GmLFY1 may regulate flowering time via the conserved process as in Arabidopsis. Besides, tissue-specific GUS expressions on sepals were detected in flowers of transgenic tobacco plants (GmLFY1::GUS), indicating that GmLFY1 is also involved in flower development. The ageing pathway is one of the identified flowering genetic pathways and the miR156-miR172 module plays major roles in this process via repression of their target genes. In this study, expression patterns of soybean miR156 and miR172 (gma-miR156a, gma-miR172a) in vegetative and reproductive developments were confirmed. Expression of gma-miR156a was higher than that of gma-miR172a in the vegetative developmental stage and it decreased with ageing. On the other hand, expression of gma-miR172a was elevated under flowering inductive conditions. These expression patterns of soybean miR156a and miR172a genes suggest that they may be involved in the developmental process. Ectopic expression of gma-miR156a in transgenic tobacco plants caused significant delays in flowering initiation with extended juvenile developmental traits (round shape of leaves). In contrast, transgenic tobacco plants overexpressing gma-miR172a exhibited early flowering phenotypes with adult traits on leaves (narrow shape). Significant down-regulations of miR156 target genes (SPL transcription factor family) and miR172 target genes (AP2-like genes) were detected in transgenic tobacco plants. These results showed that gma-miR156a and gma-miR172a may regulate ageing process via repressions of their target genes. In the present study, transgenic commercial soybean cultivar (cv. Bragg) was produced using the Agrobacterium-mediated method. In addition, this study provided evidence of conserved roles of GmLFY1, gma-miR156a and gma-miR172a in flowering and plant developments via heterologous expressions in transgenic Arabidopsis and tobacco plants. GmLFY1 is involved in floral meristem development and initiation of flowering. gma-miR156a is responsible for juvenile developments via repression of SPL transcription factor family. In contrast, gma-miR172a plays major roles in adult developmental phase by down-regulations of its target genes. These results will provide new insights on the genetic improvement of soybean.

To date, no studies have accounted for the effects of the yield and/or price risks that will occur over a run of years on the profitability of investing in ameliorating subsoil constraints within a cropping system. While addressing subsoil constraints is likely to increase grain yield, the key economic question for a grower is whether the income from extra grain produced covers the extra costs of ameliorating the subsoil. The focus of this thesis was the likely profit and risk of investing in ameliorating subsoil constraints. Investment costs and annual activity gross margins for a set rotation were used to estimate the economic performance of subsoil amelioration. The marginal change to the gross margin as a result of subsoil amelioration was assessed using partial discounted cashflow budgets. Risk analysis was used to assess the effect of price and yield variability on the mean and variance of outcomes from an investment in ameliorating subsoil constraints in cropping. This study shows an investment in subsoil amelioration was more profitable on average than an alternative investment earning 6% (real). The size of the expected extra yield benefits and longevity of these benefits are the most important factors for a grower to consider when assessing the likely merit (return and risk) of investing in subsoil amelioration in their own situations.

Milk fat globules (MFGs) are spherical structures comprising a neutral lipid core that is surrounded by a three-layer membrane. This MFG membrane is of nutritional benefit for infants and adult consumers. Individual variation in the size of MFGs is observed within a herd of the same breed, and this milk production trait, if selected for through breeding programs, could be exploited for a more targeted milk production for specific technological streams. For example, large MFGs are desirable for butter making, whereas small MFGs are preferred for cheese making and direct consumption due to improved sensory properties and increased relative abundance of the beneficial membrane material. The initial experiment of this work aimed to determine how much the average MFG size is affected by on-farm and animal related factors within a herd subjected to the same diet and environmental conditions. Milk fat globule size of the whole herd was repeatedly measured over a one-year period and the effects of these parameters were estimated using a linear mixed effect model. This analysis showed that stage of lactation, parity and milk yield can affect MFG size, while the impact of fat yield, concentrate intake and number of milkings per day was limited. However, the individual variation within the herd outweighed the effect of individual factors, supporting the possibility of a genetically determined regulation of MFG size. Based on the data collected for the first experimental chapter, cows were selected for the second and third experiment, which aimed to characterise the small and large MFG phenotypes through an in-depth lipidomics analysis. This analysis included the characterisation of the fatty acid (FA) profile of the MFG core by gas chromatography and the identification of the whole milk lipidome through targeted liquid chromatography tandem mass spectrometry. The analysis of the MFG core FA profile revealed that the cows with the small MFG (SMFG) phenotype produced milk with higher proportions of unsaturated FAs compared to large MFG (LMFG) cows. This was related to an increased uptake of preformed FAs with a chain length of 18 or more carbons, which are sourced directly from the diet or from lipid mobilisation. This characteristic of the SMFG group could potentially lead to the production of milk with an improved nutritional profile. The results of the third experiment present the most extensive milk lipidomic analysis in the literature to date, with 301 detected lipid species. The results also revealed, for the first time, a potential role for ether phosphatidylethanolamine (ePE) in the regulation of MFG size, showing a higher relative abundance of ePE in the milk from LMFG cows. Ether PEs can reduce the fluidity of biological membranes and are predicted to promote lipid droplet fusion. The milk from SMFG cows, on the other hand, contained higher total phosphatidylcholine (PC) to PE ratios and a higher relative abundance of unsaturated PC species, both attributes that are predicted to prevent lipid droplet fusion. In the final experiment of this thesis an in vitro model using cells purified from raw milk and grown on permeable membrane supports was established, which offers the potential to test some of the novel findings of this thesis in future experiments.

Controlling and managing environmental conditions is crucial to avoid hyperthermia and heat stress, and hence to successful poultry production and welfare. Heat stress (HS) is one of the most important environmental factors challenging poultry production globally. The detrimental effects of HS on broilers range from reduced growth rate to decreased poultry meat quality. Increasingly, there has been a focus on the use of nutritional supplements as a cost effective HS amelioration strategy. The use of antioxidants such as selenium, vitamin E and polyphenols to improve productivity via reduced levels of oxidative stress in tissues when broiler chickens were exposed to cyclic HS. Another molecule of interest is the osmolyte betaine, which is accumulated in cells under osmotic stress, but also has properties as a methyl donor and antioxidant. The principal findings were that cyclic HS impaired growth performance and physiological responses as increased respiratory rate and rectal temperature caused alteration in blood haematology as pCO2 reduced and blood pH increased which could lead to impaired product quality. While supplementation of betaine improved growth performance, including improved final body weight and this effect was observed irrespective of HS or additional antioxidants supplementation where it had no impact on blood haematology. The effects of HS and betaine were investigated on meat quality and it was found that HS reduced moisture content, increased lipid oxidation and reduced myofibril degradation, indicating reduced post-mortem proteolysis. This indicates worsening of meat quality as increased lipid oxidation reduces shelf life and myofibrillar degradation is important for the meat tenderisation process. When supplemented betaine was distributed to the breast muscle, and corresponded to improvements in meat quality. This was evidenced by reduced drip loss, lipid oxidation and reduction of Evans Blue dye (EBD) concentration in the breast muscle. Most importantly, supplementation of betaine reduced EBD concentration in vital organs such as kidney and ileum, indicating that betaine could have protective effects under HS. Furthermore, supplementation of betaine improved intestinal and breast muscle structure, including improved villous length and increased muscle fibre diameters which contribute to better growth performance and meat quality. Betaine supplementation was also performed against or with selenium, vitamin E or polyphenols. In general, selenium and vitamin E did not have additive effects on growth, whereas some benefits were iv observed for preventing lipid oxidation. The use of polyphenols improved growth rates to levels seen with betaine, indicating that they may also be useful nutritional agents for the amelioration of HS. Many studies have investigated the effects of the mentioned additives individually, but limited studies are available that whether the combination of them at different ages could ameliorate the negative effects of HS. This thesis aimed to investigate the effects of betaine alone or in combination with antioxidants on growth performance, meat quality and involved mechanisms to provide a better understanding on HS and betaine effects. In conclusion, betaine is a promising additive that can partially ameliorate HS effects. Despite of positive effects of antioxidants on meat quality, the additional effects of antioxidants warrant further investigation, particularly with respect to shelf life and oxidation.

Premium international goods are sought after by quality-concerned Chinese consumers who are increasingly turning towards cross-border e-Commerce and social media platforms with the expectation to avoid local food safety scares. Online retail of foreign brands however, does not guarantee protection against fraud. Counterfeit products are now commonly placed and are marketed equally besides the genuine items exposing consumers to vulnerabilities and heightening their perceived risk prior to purchase. Products are forensically scrutinised on multiple levels of security and further judged on authenticity. Australian Small-to-Medium Enterprises (SMEs), which make up 97% of all Australia’s workforce, are not well represented in the encouraged export trade opportunities as they fear export pathways that are increasingly complicated and changing. Compounding the problem is SMEs limited investment funds to upscale with expensive anti-counterfeiting solutions that may not clearly deliver on counterfeiting deterrent effectiveness and appropriateness to build consumer’s ‘initial trust’. This paper seeks to shed light on three key principles of the food counterfeiting phenomenon. Firstly, to map literature on food fraud, packaging counterfeiting with a focus on deceptive counterfeiting operations and tactics. Secondly, to investigate the unique trust relationship formation between risk adverse consumers and emerging, unfamiliar SME brands. Finally, the research will appraise anti-counterfeiting responses, from two perspectives: technological and design-driven, with a primary focus on cost-effective deterrent strategies catering to SMEs. Design/methodology/approach – A Mixed Methods approach was adopted to integrate the Participatory Action Research (PAR) methodology and co-creation strategies to later inform the larger online survey, triangulating the overall findings through qualitative and quantitative studies. Comparisons were made between Consumer and Industry insights as well as a cross-cultural study between Australia (low risk) and China (high risk) representing diverse levels of Risk Societies. The three studies investigated trust influences and drivers of Security Elements applied to food packaging founded on Technology and/or Design applications. The studies consisted of: (1) a Qualitative Multivariate Analysis, identifying the 5 Design-Driven Influencing Factors (DDIFs), (2) an Anti-Counterfeiting Workshop Model testing 30 security elements through the Case Study methodology, and finally (3) a Quantitative Online Study comparing two populations trust propensities and expectations of security elements on food packaging. Overall, the research identified that consumers acceptance of anti-counterfeiting elements can be strongly influenced by DDIFs that are appropriate for the food category (Fitted), multiple authenticity checks (Layered), connected to the country of origin (Identity Links), presents a reward attraction (User-Purposed), and technologies use a holistic design (Embedded). Design-Driven elements were identified as strong applicable to SME needs and were perceived as strong deterrent hurdles against counterfeiting threats. Future research is needed in developing education for designers to become the trust design guardians for the expansion and protection of the Australian food exporting industry.

The increasing prevalence of antibiotic resistance genes (ARGs) in environmental settings and their potential acquisition by human and animal pathogens have become a global public health concern in the 21st century. The use of antibiotics in livestock industry and the enrichment of ARGs in animal manure and arable soils have engendered the concern that recycling of manure onto agricultural land could disseminate antimicrobial resistance to crops/vegetables, which might represent a potential route for migration of environmental ARGs from farm to fork. However, the pathways for transmission of ARGs from soil to plant remain unclear. Growing evidence points to the pivotal role of the environmental factors in influencing the prevalence of ARGs in the natural environment, while our understanding of the ecological and evolutionary environmental factors that contribute to the development and dissemination of antibiotic resistance in natural environment is lacking. It is imperative to decipher the diversity, prevalence, and environmental determinants of antibiotic resistance before we could design management approaches to control the transmission of environmental resistomes. A soil microcosm incubation experiment was conducted to compare the effects of poultry, cattle and swine manures spiked with or without the antibiotic tylosin on the temporal changes of soil ARGs. The high-throughput quantitative PCR detected a total of 185 unique ARGs (out of 295 targeted genes) among all the soil samples. The diversity and abundance of ARGs significantly increased following manure application. The level of antibiotic resistance gradually decreased over time in all the manured soils but was still significantly higher in the soils treated with swine and poultry manures than in the untreated soils after 130 days’ incubation. Tylosin-amended soils consistently showed higher abundances of ARGs than soils treated with manure only, suggesting a strong selection pressure of antibiotic-spiked manure on soil ARGs. The relative abundance of ARGs had significantly positive correlations with integrase and transposase genes, indicative of horizontal transfer potential of ARGs in the manure and tylosin treated soils. A glasshouse pot experiment explored the impacts of manure fertilization on the incidence of ARGs in the plant-associated microbiomes. Rhizosphere and phyllosphere microbiomes of cherry radish harbored significantly higher diversity and abundance of ARGs than root endophytic microbiomes. Manure application significantly increased the abundance of ARGs in the rhizosphere and phyllosphere, but not in the root endosphere, which is the edible part of cherry radish. Soil and plant microbiomes changed dramatically after manure applications. The bacterial abundance was the most important factor modulating the distribution patterns of soil and plant resistomes after accounting for multiple drivers. For the pot experiment of lettuce, rhizosphere soil samples harbored the most diverse ARGs compared with other components of lettuce. Comparing with cattle manure, poultry manure had a stronger impact on lettuce resistomes, reflecting by the significant increase of ARGs in rhizosphere, root endophyte and phyllosphere in the poultry manure treatment. Moreover, the overlaps of ARGs between lettuce tissues and soil were identified to propose two potential transmission routes (internal and external pathway) of ARGs from manured soils to different compartments of lettuce. A field survey experiment investigated the abundance, diversity and environmental determinants of ARGs in ocean and river beach soils. A total of 61 soil samples were collected from ocean and river beaches, which are hotspots for human activities and platforms for potential transmission of environmental ARGs to human pathogens. A total of 110 ARGs conferring resistance to eight major categories of antibiotics were detected. The core resistome including all the abundant and prevalent ARG subtypes was identified, which accounted for 66.9% of the total abundance of ARGs. The relative abundances of ARGs were significantly correlated with salinity-related properties including electrical conductivity and concentrations of sodium and chloride. Random forest analysis and structural equation modeling revealed that salinity was the most important factor modulating the distribution patterns of beach soil ARGs after accounting for multiple drivers. These findings suggest that beach soil is a rich reservoir of ARGs, and that salinity is a predominant factor shaping the distribution patterns of soil resistome. Overall, this research provided solid evidence that manure application may result in a significant increase of ARGs in agricultural soil and different parts of vegetables. The shared ARGs in the soil-plant system suggested a potential route of ARGs transfer from manure/soil to vegetables and highlighted the potential threats to human health by consuming raw vegetables grown in manure-amended soils. Soil salinity has been identified as the most important environmental factor in shaping the ARGs in beach soil environments, highlighting the importance of understanding the environmental stresses that maintain the environmental ARGs and developing effective strategies to minimize the dissemination of ARGs.

Stagnation of rice yield over last few decades is a major concern for food security, especially in Asia. A large part of the yield increase in food crops has come from breeding for abiotic and biotic stresses and responsiveness to nutrients. However, next step of change in rice yield should target improving photosynthetic capacity, better utilising the major inputs of sunlight and/or carbon dioxide. C4 species are efficient in utilising both sunlight and carbon dioxide and therefore, engineering or breeding of C4 like traits into C3 crop plants are major pathways to increase the yield potential. Reduced interveinal spacing or enhanced leaf vein density is known to be a primary prerequisite for C4 evolution. This study is carried out to identify the potential high vein density candidates in Sri Lankan traditional rice germplasm and rice from different regions of origin and further screened for variation in their other anatomical and physiological mechanisms that are associated with enhanced photosynthesis and crop production. We have successfully identified high vein density candidates in this study and investigated their changes of leaf vein density for exogenous application of Phytohormone, Brassinosteroid (Brassinolide), a Brassinosteroid inhibitor (Brassinazole) and Auxin (Indole-3-butyric acid), and for abiotic stress; elevated carbon dioxide levels, elevated temperature and water limited conditions to identify regulatory mechanism of leaf vein density. This study is providing insight to underpin regulatory mechanism of rice leaf vein density and further, pave a foundation to develop C4 like rice to meet future food demand while mitigating the impact of climate change.