Intensive livestock production systems, such as cattle feedlots, play an important role in meeting the increasing global demand for animal products, driven by a growing population and increasing affluence. These intensive systems account for a significant proportion (~39%) of global atmospheric ammonia (NH3), which is released from the large amounts of manure generated. In cattle feedlots, the loss of NH3 represents about 75% of the excreted nitrogen (N) in the manure and this has important implications for environmental pollution. Consideration of management strategies to reduce this loss provides potential to obtain N enriched manures that can be used as fertilizer. A number of mitigation techniques have been shown to reduce NH3 loss from manure. These include: acidifying agents and urease inhibitors (both requiring frequent reapplication), dietary manipulation (can affect animal productivity) and manure compaction and covering (only applicable to stockpiled manure). Lignite (brown coal) has a demonstrated capacity to suppress NH3 emission from manure by 30-66% and is seen as a more effective, practical and potentially long lasting option. Lignite’s ability to effectively reduce the loss of NH3 from manure has been credited to its pH, cation exchange capacity (CEC), pH buffer capacity and labile carbon (C) content. However, we do not fully understand what the actual capacity for N retention by lignite is, or the main mechanisms by which lignite retains N, and how these are influenced by the properties of the lignite and changes in the environmental conditions when lignite is mixed with other materials (such as manure). Also, the impact of lignite on the quality of the manure during deposition, storage, processing (such as composting) and land application, has not been studied. The objectives of this study were to: (i) characterize different lignite materials for their capacity for nitrogen retention, and to understand the mechanisms of N retention; (ii) determine how lignite amendment of manure affects the composting process under both field and laboratory conditions by monitoring changes in biochemical parameters and gaseous emissions that occur during composting, and (iii) determine the C and N mineralization from non composted and composted manure applied to soil and how this is influenced by lignite. The capacity for N retention by lignite, and the mechanisms of N retention were determined by characterizing five lignites sourced from Victorian brown coal deposits. The chemical properties that were examined for each lignite (e.g. pH, total and labile C, forms of C, pH buffering capacity, CEC, etc.) were related to its ammonium (NH4+) adsorption capacity as a function of pH and also to the biological immobilization of N in the lignite. The properties of the lignites, their capacity for NH4+ adsorption and the immobilization of N, were determined through a series of laboratory experiments involving SEM, 13C NMR spectroscopy, sample digestion and extraction, batch adsorption isotherms techniques, and controlled environment incubations. Lignite’s impact on composting of manure was assessed under field (windrow) conditions to determine the benefits under typical industry scale management processes. The mechanisms by which lignite affected composting of manure was determined under laboratory (in-vessel) conditions. Changes in biochemical parameters (e.g. N forms, organic matter and pH), emissions of NH3 and greenhouse gases (GHG), as well as compost maturity indices, were monitored. Lignite’s effect on C and N mineralization from manure (non-composted and composted) when applied to soil, was determined through a laboratory incubation experiment which monitored CO2 evolution (as a measure of C mineralized) and changes in NH4+ and NO3- concentration in soil (as a measure of N mineralized) over a period of 40 days. The mechanism by which lignite retains N was found to be mainly through pH dependent adsorption of NH4+ on exchange sites of deprotonated carboxyl groups. The maximum NH4+ adsorption capacity (Qmax) increased up to 3 fold when pH was increased from 3.6 to ~7. Biological immobilization of N was insignificant (e.g. maximum of 0.1 mg N g-1 lignite) compared to NH4+ adsorption on exchange sites (e.g. highest Qmax of 25.6 mg NH4+-N g-1 lignite at pH ~7). These findings suggest lignite’s ability to suppresses NH3 from manure occurs by i) initially favouring the formation of NH4+ over NH3 due to the acidic pH of the lignite, and ii) deprotonation of more carboxyl groups with continuous deposition of alkaline manure leading to increased CEC of the lignite and increased retention of NH4+. Amending manure with lignite did not inhibit the composting of manure. The addition of lignite suppressed the emission of NH3 from manure during both field windrow (by 45%) and laboratory in-vessel (by 35-54%) composting. Lignite addition reduced the emissions of GHGs (12-23% for CO2, 58-72% for N2O and 52-59% for CH4) during in-vessel composting. However, during windrow composting, addition of lignite caused the emissions of GHGs to increase (41% for CO2, 136% for N2O, and from -5.0 mg kg-1 initial dry matter (DMi) day-1 in the manure only to 9.8 mg kg-1 DMi day-1 for CH4). The higher emissions of CH4 and N2O were presumed to be due to anaerobic pockets that developed within the lignite treated windrow resulting from the small particle size of the lignite, and facilitated by the largely passive aeration method (unlike the forced aeration for in-vessel composting) used during the windrow composting. For the in-vessel composting, lignite addition to manure increased the organic matter (OM) and N contents of the final compost by 10-19 and 28-38% respectively, and also the germination index, a measure of compost maturity, (from 71% to 90-113%). These changes were not observed under windrow composting conditions likely due to the passive aeration method used. In addition, the effect of lignite in the windrow compost may have differed to that in the in-vessel systems because i) the mode of manure collection using large scale field equipment meant that the lignite content of the manure was estimated based upon that applied but could have been less due to some being left on the pen surface, and ii) the source of soil used in the cattle pens was quite alkaline (pH 8.8) which may have reduced the lignite pH effect. Lignite addition to the manure suppressed microbial activity (soil respiration) which reduced the mineralization of C from the manure when applied to soil, more noticeably when the manure was composted. Over a 40-day incubation period, with non-composted manure application rates of 30 and 60 t ha-1 soil, the C mineralized was 26.4 to 27.8% for manure only, and with lignite amendment it was 16.3 to 21.4%. The corresponding C mineralized in the composted manure was 12.4 to 14.1% and 3.5 to 6.5%. The addition of lignite had a mixed effect on N mineralized from manure when applied to soil. The N mineralized was significantly higher in the non-composted manure amended with Loy Yang lignite (10.4 to 13.5% for 30 and 60 t ha-1) than with Bacchus Marsh lignite (4.1 to 9.8%) and non-composted manure only (3.2 to 8.7%). For composted manure, there was no significant difference between N mineralized in the manure only (4.8 to 6.7%) and the lignite treatments (2.5 to 7.8%). Results presented in this study, for the first time, show the dominant N retention mechanism by lignite in manure, its influence on biochemical changes and gaseous emissions during manure composting under both laboratory and field conditions, and finally how the lignite impacts nutrient mineralization from non-composted and composted manure when applied to soil. In conclusion, this study shows lignite’s capacity to mitigate the emissions of both NH3 and GHGs from manure under optimum composting conditions. Hence, in intensive livestock production systems, lignite has the ability to improve the agronomic value of the large volumes of manure generated and reduce the environmental pollution associated with livestock production and manure management. Lignite addition to manure, especially when composted, has the potential to increase soil OM and improve long term soil health due to the inhibitory effect of lignite on C mineralization from manure. The findings of this study provide the option for the use of lignite as a tool for sustainable livestock production in intensive livestock industry.

Antimicrobial resistance (AMR) has become a global issue for human and animal health and welfare. It narrows down the choice of antimicrobials to treat infections and increases the costs of treatment. Effective antimicrobial stewardship is critical to ensure antimicrobials are used appropriately. Monitoring the antimicrobial resistance genes (ARGs) in bacteria is one of the important parts of antimicrobial stewardship. Bacteria in animal faeces harbor various ARGs. The traditional culture-based approaches to detect ARGs in the faecal bacteria are limited to the culturable bacteria, which only represent a small fraction of the faecal microbiome. The culture-independent approaches, such as high-throughput qPCR (HT-qPCR) and the next generation sequencing, bypass the limitation of culture and allow us to characterise the ARG profiles of the total bacterial community. These approaches have been widely used to detect and quantify ARGs in the faecal microbiomes of animals in various countries, but few of such studies have been done in Australia. In this project, faecal samples were collected from foals, calves, chickens and pigs, raised in commercial farms. The foals and chickens had no history of antimicrobial treatment. Calves were expected to have low chance being exposed to antimicrobials and only the pigs might be medicated. ARGs of the major antimicrobial classes, mobile genetic elements (MGEs) and metal resistance genes (MRGs) in the faecal samples were detected and quantified using a HT-qPCR array. The faecal microbiomes were determined by amplifying the V3-V4 region of the bacterial 16S rRNA gene and sequencing the amplicons on an Illumina platform. In addition, environmental swabs were collected from the chicken and pig farms and the microbiome and ARGs profiles of the swab samples were analysed to determine whether the environmental sampling could be used to study ARGs in animals raised intensively on a large scale. Overall, tetracycline resistance genes (tet) encoding ribosomal protection proteins and macrolide resistance genes (mef and erm) were the dominant ARGs in the faecal samples regardless of the animal species. The high level of these genes could be explained by the predominance of the potential bacterial hosts, such as Bacteroides spp., in the faecal microbiomes. The ubiquitous presence of the tet and mef/erm genes in animals suggested these genes are persistent and are not necessarily associated with the antimicrobial usage. On the other hand, the faecal samples had very low level of extended spectrum beta lactamase genes, blaCMY and blaCTX-M, carbapenems resistance gene cphA, fluoroquinolones resistance gene qnrB and virginiamycin resistance gene vatE, which suggested animals with low antimicrobial exposure had low risk of carrying ARGs that confer resistance to antimicrobials of high clinical concern. Manure belt swabs collected in the cage chicken sheds were appropriate to study ARGs associated with caged poultry. However, the floor swabs in the chicken and pig farms did not reflect the ARG profiles of the animal faeces due to insufficient biomass for DNA extraction or great changes in the microbiome composition compared to the faeces. In conclusion, this project showed that HT-PCR is an efficient method to screen a range of ARGs in complex samples. Analysis of ARG profile of animals without antimicrobial exposure set the baseline of presence and abundance of ARGs in animal faeces. Diverse ARGs detected in these animals suggests the persistence of ARGs in faecal microbiome. The results are useful for future studies investigating whether the current antimicrobial use practices can select and enrich pre-existing ARGs in farm animals.

Lentil is one of the important pulse crops in the world; however, its production is threatened by economically important diseases. Two of the devastating seedborne diseases of this crop, across the world and in Australia, are Ascochyta blight, caused by Ascochyta lentis, and Botrytis grey mould, caused by Botrytis cinerea and Botrytis fabae. Lack of genetically diverse sources of disease resistance in cultivated lentil varieties has increased dependence on fungicides to control these diseases. However, still, huge production losses are recorded worldwide as overuse of fungicides has resulted in the pathogen adaptation by mutations leading to their resistance and a reduction of fungicides efficiency. Therefore, there is a dire need for the development of an environmentally friendly physical method to be implemented in the integrated disease management scheme in pulse crops, including lentil. Microwave radiation is a sustainable and environmentally safe technology for food and agricultural processing. Its use for thermal treatment has shown great potential for sterilisation of food material as well as eradication of pests and pathogens from agricultural commodities. However, its potential in the grain industry and the control of related pathogens have not been fully explored, probably due to the concerns related to the resulting grain quality. Additionally, the indirect use of microwave, as a source for processing gas to produce non-thermal plasma followed by treatment of the seeds with the plasma, has recently gained a lot of attention. Therefore, the present study aimed to develop a thermal or non-thermal process, based on microwave radiation, to disinfect lentil seeds from its seed borne pathogens. The potential of a microwave multi mode cavity with a turntable for the eradication of AB of lentil seeds at different seed moisture contents, microwave powers, and exposure times was evaluated. This process was assumed to be like the industrial scale microwave system, with a conveyor belt, in terms of heat uniformity and efficiency of pathogen control. It was proven that the pathogen could be removed faster at higher seed moisture content; however, the seed viability was also more susceptible to microwave radiation at the higher seed moisture content (19% wet based). Infected seed percentage (IS%) reduced from 17% to 8.9%, at a seed moisture content of 9.1%, by applying a 100% power level (maximum 1100 W) for 51 s without a significant seed germination loss. Nevertheless, seed vigour (measured by electrical conductivity) was negatively affected by these process parameters. Investigation of heat uniformity in this process showed that the difference between hot and cold spots could reach as high as 50 C, which may account for the seed vigour loss before completing the eradication of the pathogen. To improve heat uniformity, a microwave fluidised bed was designed and manufactured. The efficiency of this process, in the eradication of seed borne Botrytis grey mould of lentil seeds, was firstly evaluated by investigation of the effective factors, including microwave power, exposure time, air temperature and seed moisture content with responses of IS%, seed germination, seed vigour, seeds bed temperature, and moisture loss. The results showed that a 30% reduction in IS% could be achieved by applying microwave power of 300 W and air temperature of 60 C or microwave power of 400 W and air temperature of 50 C for 10 min at the seed moisture content of 18%, without a significant reduction in seed viability and vigour. The temperature history, measured at two points in the fluidised bed using fibre optic probes, showed that the difference between hot and cold spot did not exceed 5 C. It confirmed that there was a very good heat uniformity in the microwave fluidised bed process. Evaluation of the effect of factors in the previous study showed that exposure time was an effective factor in reducing the IS%, while it did not have a significant effect on seed germination. To determine whether more reduction of the IS% could be achieved at prolonged exposure time, IS% reduction was examined in a drying experiment in the microwave fluidised bed dryer at the same process parameters as the previous experiment. The drying kinetics and time saving, compared with the conventional fluidised bed, were also studied. The results confirmed that the same reduction of the IS% occurred, and therefore increasing exposure time did not improve the reduction of the infected seeds; however, it proved to be a very effective drying process (more than 54% reduction in the drying time). It means that the greatest reduction in infected seeds occurred during the first 10 min of the process. The reason for not having more reduction in IS% after a specific time could be the very fast desiccation of the pathogen during the treatments, which increased its thermal resistance and subsequently the minimum power, or temperature required for its eradication. The seeds, which were dried in the previous experiment, were evaluated for any quality changes by examining their antioxidant enzyme activities, cooking quality, and their macronutrient using Fourier transform infrared (FTIR) micro spectroscopy. It was concluded that there was no significant quality deterioration in the most efficient process parameters (400 W & 50 C). In conclusion, there is great potential for microwave disinfection of lentil seeds under the condition where the hot spot is controlled so as not to harm the seed quality. It could be achieved by microwave assisted drying with at least a 54% reduction in the drying time compared with conventional fluidised bed drying. One hundred percent eradication might not be achieved, but it can be considered as part of an integrated disease management process in lentil crops, with the ultimate goal of reducing initial fungicide application for seed treatment and later applications for the crop. However, there might be concerns over the heat tolerance of different grains and different batches of the same grain, which was the reason for considering the non-thermal treatment with microwave plasma. Finally, the non thermal process of plasma, created from a microwave source, was examined for its potential in the eradication of Botrytis grey mould from lentil seeds. Non thermal plasma is the fourth state of the matter produced by energizing a gas and consists of various reactive species including atoms, ions, and radicals, which is a very promising non chemical method of seed disinfection with a growth enhancement effect. Two modes of treatment were considered: direct argon plasma at low power (400 W); and treatment with the afterglow of the air or air and argon plasma (10 s and 100 s) followed by holding the seeds in the trapped processed gas for 5 min to 24 h. There was a 41% reduction in the infected seed percentage (IS%) after 100 s of treatment with the afterglow of air plasma following by 24 h holding and a 32.3% reduction occurred when they were treated by 30% air and 70% argon plasma for 10 s and 60 min holding time. No significant change was observed in antioxidant enzyme activities of the treated seeds, except for triggering of catalase activity after 24 h of holding time. However, lentil seeds colour changed towards redness and yellowness after prolonged treatment time (400 s) or holding time (24 h). Therefore, the afterglow of microwave plasma or plasma processed air could be further explored as a great tool for the disinfection of grains, without any negative effect on their viability. Overall, both microwave fluidised bed and the afterglow of microwave plasma were able to reduce the seed-borne Botrytis grey mould of lentil seeds without any adverse effect on the seed viability. Microwave fluidesed bed would be useful when drying and disinfection are simultaneously desirable as the disinfection was just achievable at high seed moisture content with very fast drying of the seeds. However, the disinfection of dry lentil seeds was possible using the treatment with the afterglow of the plasma. Therefore, plasma treatment could be further explored for the treatment of other grains and their related pathogens if the dry seeds need to be disinfected.

ABSTRACT Some farms remain in the ownership of one family for several generations and others do not. This study is about family farms in Australia used for growing crops, running beef cattle and sheep, or operating with a mix of these activities. Why and how has the same family operated a farm for generations and why and how do other such family farms cease to continue in the same ownership? This work investigates the question of inter-generational succession of family farm businesses in the context in which there are three main aims of owners of family farm business. The definition of the three main aims is to provide adequately for retirement; pass on to heirs a farm that has reasonable prospects of being a sound economic proposition and financially viable and has potential for future improvements in productivity and growth of wealth for the farming child or children, provide a share of resources for the non–farming children that they consider being adequately commensurate with their entitlement and that they are content with that share. There is a large body of work about farm management economics and business growth. Rarely does farm management literature document the process of succession, or investigate, develop and report theory about the many factors that contribute to enabling a farm to remain in the ownership of one family. Studies that concentrate on the human, technical or the economic elements of farm management overlook the question of succession. Usually studies focusing on succession are unburdened by the complexities of farm economics. Knowing how and why farm families manage to ‘farm for generations’, or fail to do so, remains the domain of the farm families and their stories about attempted inter-generational succession. A mix of research methods was used to investigate the question of inter-generational succession of family farming businesses, in the context of farm economic theory and theory about the growth of the firm. Surveys of farmers and agricultural professionals and case studies of the farm succession experiences of families have been documented. The possibilities open for farm families discussed and an analysis of historical records of farm firms has been undertaken. Explorations of the options facing some current farming businesses and what they would need to do now to achieve successful succession have been used to illuminate the research questions about inter-generational succession. Central to the question of farm succession are the attitudes and attributes, experiences and actions of the owner-managers who run farm businesses. The real situations of farm owners, family members and managers, who have been through or will go through succession, have been investigated in this study. A pilot survey through an advisor network provided an assessment of over 6,000 of the 52,000-broad acre family farms in Australia. The case study method was used to analyse and contrast attributes, attitudes and actions of sixteen family businesses; half of these family businesses will continue farming, half will not do so. The historical records of 100 case study businesses were explored and their stories of succession documented. Succession analysis and planning was done for five current family farm operations facing up to succession. In 2016, 48 per cent of the 52,000-broad-acre farm businesses in Australia had an annual gross value of sales of $230,000, or less. There is no likelihood that farms with such low annual income will achieve the three main aims of succession. Most of the owners of broad-acre family farm businesses do not have a succession plan, do not intend to develop a succession plan for their business and do not have the scale to achieve the three main aims. For those farm businesses that have adequate scale, this alone will not ensure there will be a business for the next generation that has reasonable prospects of being a sound economic proposition and financially viable and has potential for future improvements in productivity and growth of wealth for the farming child or children. Farm families cannot achieve the three main aims of succession unless the business generates economic returns and annual cash flows and builds wealth at a level and consistency above the average for the district and the industry. Farm businesses must farm well, over a long time, for the three aims of succession to be achievable and for succession hopes and plans to become reality. Most broad-acre farm families in Australia cannot aspire to achieve the three main aims. The reasons are many and complex ranging from the economics and finance of farming to the scale and medium-term profitability of the business, to planning and intent, and the always-complex interpersonal relationships of families. This is of course as it must be. How else can the family farms that achieve succession grow, to be able to pass on the farm to family decades hence?

Climate variability and extreme climate events such as heat waves, droughts, extreme precipitation and frost occurrences are increasingly challenging the agricultural systems in Australia and globally. Despite this, the majority of the previous climate change studies have focused on the influence of average climate change on agricultural systems, which risks underestimating the impacts of climatic changes. In south eastern (SE) Australia, climate variability has increased in recent decades accompanying an increased frequency and severity of extreme climate events such as heat waves and droughts. The objective of this research was to investigate the impacts of changing climate variability and extreme climate events on pasture systems in SE Australia using biophysical modelling and controlled experimental approaches. Year to year variability in pasture yields has many consequences on the key management decisions such as stocking rates and the timing of the reproductive cycle. Changes to the pasture growth patterns were investigated at five sites in SE Australia ranging from medium rainfall, warm temperate climate at Wagga Wagga in southern New South Wales to high rainfall, cool temperate climate at Elliott in Tasmania using DairyMod biophysical software over the period 1960-2015. Across the sites, winter production has increased, spring pasture growth has decreased and year to year yield variability during autumn and spring seasons has increased in the most recent period (2002-2015) compared to 1988-2001. Increased number of days with water and temperature limitation together with increased spring and summer soil moisture deficit are in line with the simulated changes in pasture growth patterns, suggesting that adaptations such as incorporating deep rooting and heat tolerant species should be prioritized to stabilize pasture production. The year to year variability in pasture yield was better explained when extreme climate indices were used in combination with climate averages, as compared with climate average alone. Extreme climate indices together with the average climate variables explained more yield variability at the medium rainfall sites (eg. Wagga Wagga R2=0.89) than high rainfall sites (eg. Elliott R2=0.70) indicating that medium rainfall sites are more sensitive to the changes in rainfall distribution and high temperatures. Increased occurrences of dry months, wet months during the winter and spring, number of hot days above 30 C and the duration of hot days in a year decreased pasture yields highlighting the importance of considering extreme climate events in future climate change studies on agricultural systems. El-Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are two major rainfall drivers that influence rainfall variability in Australia and their phases reach the peak during the spring season which is the major pasture growing season in SE Australia. Each driver has a dry and hot phase (El-Nino and IOD(+)) and a cool and wet phase (La-Nina and IOD(-)). The influence of these phases individually and in combination were investigated on simulated annual pasture production from 1950-2015 in five sites in SE Australia. In dry and hot phases of both of ENSO and IOD (El-Nino and IOD(+)), lower pasture production was simulated, while the phases responsible for the wet and cool climate increased the yield. When combined ENSO-IOD phases were examined, the highest yields resulted when the La-Nina phases coincided with IOD(-) or neutral, whilst the El-Nino with IOD(+) phases led to the lowest yields. Forecast analysis revealed that the effects of climate driver phases emerge at the end of winter, but this is not a sufficient lead time for making important pasture management decisions. Therefore, further studies are warranted to increase the forecast ability of each climate driver phase to use them in agriculture decision making. Climate models project increased frequency of extreme climate events in SE Australia in the future. A controlled environmental experiment was conducted to investigate growth and physiological responses of four summer active temperate perennial pasture species to consecutive 7-day heat and drought stresses. Exposure of perennial ryegrass, tall fescue, cocksfoot and chicory to consecutive moderate (30/20 C, day/night) and severe (35/25 C, day/night) heat and drought stress revealed that all the species can acclimate to moderate combined heat and drought stress by maintaining the physiological functions such as photosynthesis, maximum photochemical efficiency of photosystem II, cell membrane permeability and relative leaf water content. However, chicory was the only species that maintained the above physiological processes under consecutive severe heat and drought stresses while all grass species decline to the minimum values. Plants that were irrigated showed cooler canopies than non-irrigated plants during high temperature treatments and this transpirational cooling mitigated the impacts of heat stress in all species. Leaf temperature data measured using infrared images during the experiment were used to validate the leaf energy budget equation and the calculated leaf temperatures (using the energy budget) were used to model heat stress impacts on perennial ryegrass in DairyMod model. The leaf temperature calculation incorporates the interaction of air temperature and soil water through the feedback effects of transpiration through stomata. The simulations run with calculated leaf temperatures predicted the observed reduction of photosynthesis accurately while air temperature simulations overestimated the actual impacts under moderate temperature, indicating that leaf temperature more accurately represents the environment under which plants are grown under heat stress rather than air temperature. Further, the DairyMod high temperature stress recovery function (T sum) for perennial ryegrass was parameterized using measured data of the experiment. The findings demonstrated that simulations of DairyMod can be improved using leaf temperature and parameterizing heat stress recovery functions. In conclusion, this research highlighted that the climate variability and extreme events have changed the pasture growth patterns in SE Australia in the recent period (2002-2015) therefore, climate variability and extreme climate events need to be fully considered in the future climate change studies. Chicory may be a more adapted pasture species in temperate livestock areas where extreme summer heat and moisture stresses limit summer feed supply. Leaf temperature modelling improves the heat stress simulations in the DairyMod model and this approach can also be used in other crop simulation models to improve high temperature stress modelling. Future research should aim to identify the plant traits and key metabolic processes in Chicory that confer greater heat stress tolerance and what other species would have similar traits. Future research on climate change impacts should also aim to determine critical combinations of extreme events that would result in tipping points for farming systems.

Nigeria is an agrarian economy with over seventy percent of the population engaged in agriculture. However, the nation depends heavily on food imports. Nigerian food producers are predominantly resource-constrained poor farmers, who are the most food insecure. Nigerian agriculture is chiefly conducted to meet household food requirement but is gradually transitioning to semi-subsistence agriculture. Agriculture was once the mainstay of Nigeria. The Nigerian agricultural sector was abandoned for the oil sector in the early 1970s. This neglect has negative consequences on the country’s agriculture. Presently, Nigerian agriculture is characterized by low performance. Nigeria, once a net food exporter has become a net food importer. With a view to enhancing the performance of Nigeria farmers, improved technologies have been developed and disseminated to farmers. In spite of this, there is food insecurity and poverty intensification in the country. This raises the questions whether or not farmers are adopting these technologies and the efficacy of these technologies in enhancing farmer performance and alleviating poverty in the country. Yam is a significant crop in Nigeria. It is a highly prized crop in the country. It has sociocultural, medicinal, nutritional and economic value. It is nutritionally superior to comparable crops including sweet potato and taro. Notwithstanding, yam farmers in Nigeria are performing poorly. Yam production in Nigeria is mainly impeded by high cost, unavailability of planting material, and over reliance on labour-intensive traditional yam production methods which are expensive, encourage the use of low quality planting materials, and inhibit mechanization of yam production. Yam Minisett Technology (YMT) is an on-farm yam multiplication technique which enables development of high quality planting materials for yam production. The aim of this project is to ascertain the potential of new technology and increased farmers efficiency for wellbeing improvement with reference to yam production and YMT in Nigeria. The specific objectives of this project are to: (i) describe yam production in Nigeria; (ii) compare farm activities and yam production systems in Nigeria; (iii) examine indicators and determinants of performance of yam producers (performance indicators being technical and economic); (iv) examine the role of technology adoption on farmer performance and wellbeing; (v) assess the superiority of seed yam from YMT over other planting materials; and (vi) ascertain determinants of adoption of improved technology. A multi-stage sampling technique was adopted to elicit cross-sectional data from three hundred and sixty yam farmers (120 respondents per State) in three yam-producing States of Nigeria. The States were Benue, Enugu and Ondo. The States are located in different agro-ecological zones of Nigeria and use different methods for yam production. Data were drawn from two Local Government Areas (LGAs) in each State. The LGAs were Katsina-Ala and Buruku in Benue State, Nkanu-east and Uzo-Uwani in Enugu State, and Ose and Owo in Ondo State. Primary and secondary data were used in this investigation. Primary data were collected from the respondents by using a well-structured questionnaire, direct observation and by interviewing farmers. Secondary data were obtained from databases, websites and literature. Data collected include socioeconomic data, resource endowment and utilization data, input and output data, data on farming systems and techniques, attitudinal data, environmental data and health data. Data were analyzed with descriptive statistics, econometrics and economic models. Descriptive statistics were used to describe yam production. An econometric model (stochastic frontier analysis) was used to evaluate the indicators of performance of yam farmers. Two functional forms, the Cobb-Douglas and the Translog production and cost functions, were used to investigate the production and cost of yam. The models were compared for goodness-of-fit. The best functional form was used to determine the technical and economic efficiency and factors influencing efficiency. Metafrontier analysis was used to test the presence of environment/technology gaps between States. The impact of YMT adoption on yam farmer performance was investigated using Propensity Score Matching. Factors influencing adoption were determined with Probit model. Gross Margin (GM) analysis was used to determine the profitability of yam with and without YMT. Partial budgeting was also performed to confirm the profitability of YMT. Net return was used to compare the yam cropping systems. The stochastic frontier analysis showed that, on average, Nigerian yam farmers in those States were not fully efficient in yam production. Benue State was technically efficient in yam production. Both Benue and Enugu yam farmers were relatively economically efficient. The performance (technical and economic efficiency) of Nigerian yam farmers is influenced by farmer’s socioeconomic profile, decisions, and access to inputs and facilities. Yam production is affected by farm size, quantity of planting material, labour and capital input. Cost of yam is determined by output, capital input, rent on land, planting material, wage rate and price of fertilizer. The result of the metafrontier analysis revealed that the production environment and technology for yam differ between States in Nigeria. Benue and Ondo States have more favourable environments for yam production. Enugu yam farmers are operating in a more restrictive environment. GM analysis established that yam production is relatively profitable. Yam had a higher GM than other root and tuber crops. Yam/Maize is the most profitable cropping system in Nigeria. Embracing Yam/Maize intercrop and increased investment in yam production can contribute to improving the poverty status in Nigeria. The adoption of YMT has the potential to improve farmer performance and wellbeing in Nigeria. YMT is a viable seed yam production technique. Yam production using YMT is more profitable than the traditional yam production techniques. Adopters of YMT in Nigeria outperformed non-adopters.

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.