946 resultados para Farm engines.
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BCC Benefits Composted Organics Farm Systems.
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Project Objectives: 1. Improving yield and water use efficiency of the wheat crop, the backbone of the Australia grains industry, by better matching management, variety, soil and climate. The aim is thus increasing kg grain/ha per mm evapotranspiration and kg grain/ha per mm rain. 2. Improving land and water productivity and profit by better arrangement of the components of the cropping system. This involves better allocation of farm resources (land, water, machinery, labour) and identifying strategies that account for trade-offs between profit and risk. The aim is thus improving $/ha per year and mm rain in a risk framework.
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Provision of technical advice for Tully cane demo farm sites as part of the Paddock-scale monitoring in the Wet Tropics Natural Resource Management region.
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The objectives of this project over a 3 years study period are: 1) validation and on-farm adoption of improved root growth and functioning for managing cotton production under limited water and nitrogen nutrition; and 2) Delivering improved understanding of enhancing root growth and functioning to about 50% cotton growers in the regions leading towards a better adaptation to future climate driven challenges, particularly limited water availability in Queensland and New South Wales. The research is expected to be supported through cash and/or in-kind contributions by CRDC and Agri-Science Queensland (DEEDI).
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Jointly manage The Farm Program within the Cotton Catchment Communities CRC.
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Enhanced On-farm Monitoring and Mitigation of Pesticide and Nutrient Transport.
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This paper examines the idea that plasticity in farm management introduces resilience to change and allows farm businesses to perform when operating in highly variable environments. We also argue for the need to develop and apply more integrative assessments of farm performance that combine the use of modelling tools with deliberative processes involving farmers and researchers in a co-learning process, to more effectively identify and implement more productive and resilient farm businesses. In a plastic farming system, farm management is highly contingent on environmental conditions. In plastic farming systems farm managers constantly vary crops and inputs based on the availability of limited and variable resources (e.g. land, water, finances, labour, machinery, etc.), and signals from its operating environment (e.g. climate, markets), with the objective of maximising a number of, often competing, objectives (e.g. maximise profits, minimise risks, etc.). In contrast in more rigid farming systems farm management is more calendar driven and relatively fixed sequences of crops are regularly followed over time and across the farm. Here we describe the application of a whole farm simulation model to (i) compare, in silico, the sensitivity of two farming systems designs of contrasting levels of plasticity, operating in two contrasting environments, when exposed to a stressor in the form of climate change scenarios;(ii) investigate the presence of interactions and feedbacks at the field and farm levels capable of modifying the intensity and direction of the responses to climate signals; and (iii) discuss the need for the development and application of more integrative assessments in the analysis of impacts and adaptation options to climate change. In both environments, the more plastic farm management strategy had higher median profits and was less risky for the baseline and less intensive climate change scenarios (2030). However, for the more severe climate change scenarios (2070), the benefit of plastic strategies tended to disappear. These results suggest that, to a point, farming systems having higher levels of plasticity would enable farmers to more effectively respond to climate shifts, thus ensuring the economic viability of the farm business. Though, as the intensity of the stress increases (e.g. 2070 climate change scenario) more significant changes in the farming system might be required to adapt. We also found that in the case studies analysed here, most of the impacts from the climate change scenarios on farm profit and economic risk originated from important reductions in cropping intensity and changes in crop mix rather than from changes in the yields of individual crops. Changes in cropping intensity and crop mix were explained by the combination of reductions in the number of sowing opportunities around critical times in the cropping calendar, and to operational constraints at the whole farm level i.e. limited work capacity in an environment having fewer and more concentrated sowing opportunities. This indicates that indirect impacts from shifts in climate on farm operations can be more important than direct impacts from climate on the yield of individual crops. The results suggest that due to the complexity of farm businesses, impact assessments and opportunities for adaptation to climate change might also need to be pursued at higher integration levels than the crop or the field. We conclude that plasticity can be a desirable characteristic in farming systems operating in highly variable environments, and that integrated whole farm systems analyses of impacts and adaptation to climate change are required to identify important interactions between farm management decision rules, availability of resources, and farmer's preference.
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BACKGROUND: The lesser grain borer, Rhyzopertha dominica (F.), is a highly destructive pest of stored grain that is strongly resistant to the fumigant phosphine (PH3). Phosphine resistance is due to genetic variants at the rph2 locus that alter the function of the dihydrolipoamide dehydrogenase (DLD) gene. This discovery now enables direct detection of resistance variants at the rph2 locus in field populations. RESULTS: A genotype assay was developed for direct detection of changes in distribution and frequency of a phosphine resistance allele in field populations of R. dominica. Beetles were collected from ten farms in south-east Queensland in 2006 and resampled in 2011. Resistance allele frequency increased in the period from 2006 to 2011 on organic farms with no history of phosphine use, implying that migration of phosphine-resistant R. dominica had occurred from nearby storages. CONCLUSION: Increasing resistance allele frequencies on organic farms suggest local movement of beetles and dispersal of insects from areas where phosphine has been used. This research also highlighted for the first time the utility of a genetic DNA marker in accurate and rapid determination of the distribution of phosphine-resistant insects in the grain value chain. Extending this research over larger landscapes would help in identifying resistance problems and enable timely pest management decisions. © 2013 Society of Chemical Industry © 2013 Society of Chemical Industry 69 6 June 2013 10.1002/ps.3514 Rapid Report Rapid Report © 2013 Society of Chemical Industry.
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This study presents the use of a whole farm model in a participatory modelling research approach to examine the sensitivity of four contrasting case study farms to a likely climate change scenario. The newly generated information was used to support discussions with the participating farmers in the search for options to design more profitable and sustainable farming systems in Queensland Australia. The four case studies contrasted in key systems characteristics: opportunism in decision making, i.e. flexible versus rigid crop rotations; function, i.e. production of livestock or crops; and level of intensification, i.e. dryland versus irrigated agriculture. Tested tactical and strategic changes under a baseline and climate change scenario (CCS) involved changes in the allocation of land between cropping and grazing enterprises, alternative allocations of limited irrigation water across cropping enterprises, and different management rules for planting wheat and sorghum in rainfed cropping. The results show that expected impacts from a likely climate change scenario were evident in the following increasing order: the irrigated cropping farm case study, the cropping and grazing farm, the more opportunistic rainfed cropping farm and the least opportunistic rainfed cropping farm. We concluded that in most cases the participating farmers were operating close to the efficiency frontier (i.e. in the relationship between profits and risks). This indicated that options to adapt to climate change might need to evolve from investments in the development of more innovative cropping and grazing systems and/or transformational changes on existing farming systems. We expect that even though assimilating expected changes in climate seems to be rather intangible and premature for these farmers, as innovations are developed, adaptation is likely to follow quickly. The multiple interactions among farm management components in complex and dynamic farm businesses operating in a variable and changing climate, make the use of whole farm participatory modelling approaches valuable tools to quantify benefits and trade-offs from alternative farming systems designs in the search for improved profitability and resilience.
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TRFLP (terminal restriction fragment length polymorphism) was used to assess whether management practices that improved disease suppression and/or yield in a 4-year ginger field trial were related to changes in soil microbial community structure. Bacterial and fungal community profiles were defined by presence and abundance of terminal restriction fragments (TRFs), where each TRF represents one or more species. Results indicated inclusion of an organic amendment and minimum tillage increased the relative diversity of dominant fungal populations in a system dependant way. Inclusion of an organic amendment increased bacterial species richness in the pasture treatment. Redundancy analysis showed shifts in microbial community structure associated with different management practices and treatments grouped according to TRF abundance in relation to yield and disease incidence. ANOVA also indicated the abundance of certain TRFs was significantly affected by farming system management practices, and a number of these TRFs were also correlated with yield or disease suppression. Further analyses are required to determine whether identified TRFs can be used as general or soil-type specific bio-indicators of productivity (increased and decreased) and Pythium myriotylum suppressiveness.
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Farms and rural areas have many specific valuable resources that can be used to create non-agricultural products and services. Most of the research regarding on-farm diversification has hitherto concentrated on business start-up or farm survival strategies. Resource allocation and also financial success have not been the primary focus of investigations as yet. In this study these specific topics were investigated i.e. resource allocation and also the financial success of diversified farms from a farm management perspective. The key question addressed in this dissertation, is how tangible and intangible resources of the diversified farm affect the financial success. This study’s theoretical background deals with resource-based theory, and also certain themes of the theory of learning organisation and other decision-making theories. Two datasets were utilised in this study. First, data were collected by postal survey in 2001 (n = 663). Second, data were collected in a follow-up survey in 2006 (n = 439). Data were analysed using multivariate data analyses and path analyses. The study results reveal that, diversified farms performed differently. Success and resources were linked. Professional and management skills affected other resources, and hence directly or indirectly influenced success per se. In the light of empirical analyses of this study, tangible and intangible resources owned by the diversified farm impacted on its financial success. The findings of this study underline the importance of skills and networks for entrepreneur(s). Practically speaking all respondents of this study used either agricultural resources for non-farm businesses or non-farm resources for agricultural enterprises. To share resources in this way was seen as a pragmatic opportunity recognised by farmers. One of the downsides of diversification might be the phenomenon of over-diversification, which can be defined as the situation in which a farm diversifies beyond its optimal limit. The empirical findings of this study reveal that capital and labour resource constrains did have adverse effects on financial success. The evidence indicates that farms that were capital and labour resource constrained in 2001 were still less profitable than their ‘no problems’ counterparts five years later.