29 resultados para Semiparametric efficiency bounds
Resumo:
Increase water use efficiency and productivity, and reduce energy and water usage and costs, of dairy and fodder enterprises, to reduce costs of milk production.
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Monitoring of soil moisture fluctuations under mulched and un-mulched native flowers will provide valuable information in assessing the crop water use and potential water savings associated with adoption of this practise. This information would be valuable in encouraging growers to adopt best management practises for sustainable flower production.
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Management of environmental emissions is a significant challenge and opportunity for all of horticulture, including the protected cropping sector. Energy is a significant input in controlled environment horticulture and an important source of environmental emissions. Energy underlies this industry’s capacity to provide a consistent supply of fresh, quality, safe food in a changing global climate.
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Calypso mango is a relatively new variety owned by DEEDI and managed/marketed by One Harvest (Queensland-based). It is a major mango variety for the retail chains. Its main limitation is a sensitive skin, which results in lenticel spotting and skin browning.
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The purpose of this proposal is to detail the proposed service provision project to be undertaken by staff from the Department of Employment, Economic Development and Innovation (DEEDI – formerly DPI&F) to the Flower Association of Queensland Inc (FAQI). FAQI to successfully fulfil FAQI’s requirements under the Rural Water Use Efficiency 4 project.
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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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Agri-Science Queensland to provide a range of extension services to improve water use efficiency in irrigated agriculture in the Queensland Murray Darling Basin and support the implementation of the Healthy Headwaters On-farm Water Use Efficiency program.
Development and adoption of a web-based irrigation management tool for improved water use efficiency
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Develop a web-based tool to assist farmers and consultants make strategic and tactical irrigation decisions.
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Presence of the dw3 sorghum dwarfing gene had negative effects on grain yield in some genetic backgrounds and environments. In a previous study we showed that this was due to a significant reduction in shoot biomass (mainly via reduced stem mass), which in turn negatively affected grain size. The current study examines whether shoot biomass was reduced via effects of dw3 on traits associated with resource capture, such as leaf area index (LAI), light interception (LI), and canopy extinction coefficient (k) or with resource use efficiency, such as radiation use efficiency (RUE). Three pairs of near-isogenic sorghum lines differing only in the presence or absence of the dwarfing allele dw3 (3-dwarfs vs 2-dwarfs) were grown in large field plots. Biomass accumulation and LI were measured for individual canopy layers to examine canopy characteristics of tall and short types. Similar to the previously reported effects on grain yield, the effects of dw3 on RUE, LI and k varied among genetic backgrounds and environments. Interactions between dw3 and genetic background, but also interactions with environment are likely to have modulated the extent to which RUE, LI, or k contributed to biomass differences between tall and short sorghum. © 2013 .
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The aim of this review is to report changes in irrigated cotton water use from research projects and on-farm practice-change programs in Australia, in relation to both plant-based and irrigation engineering disciplines. At least 80% of the Australian cotton-growing area is irrigated using gravity surface-irrigation systems. This review found that, over 23 years, cotton crops utilise 6-7ML/ha of irrigation water, depending on the amount of seasonal rain received. The seasonal evapotranspiration of surface-irrigated crops averaged 729mm over this period. Over the past decade, water-use productivity by Australian cotton growers has improved by 40%. This has been achieved by both yield increases and more efficient water-management systems. The whole-farm irrigation efficiency index improved from 57% to 70%, and the crop water use index is >3kg/mm.ha, high by international standards. Yield increases over the last decade can be attributed to plant-breeding advances, the adoption of genetically modified varieties, and improved crop management. Also, there has been increased use of irrigation scheduling tools and furrow-irrigation system optimisation evaluations. This has reduced in-field deep-drainage losses. The largest loss component of the farm water balance on cotton farms is evaporation from on-farm water storages. Some farmers are changing to alternative systems such as centre pivots and lateral-move machines, and increasing numbers of these alternatives are expected. These systems can achieve considerable labour and water savings, but have significantly higher energy costs associated with water pumping and machine operation. The optimisation of interactions between water, soils, labour, carbon emissions and energy efficiency requires more research and on-farm evaluations. Standardisation of water-use efficiency measures and improved water measurement techniques for surface irrigation are important research outcomes to enable valid irrigation benchmarks to be established and compared. Water-use performance is highly variable between cotton farmers and farming fields and across regions. Therefore, site-specific measurement is important. The range in the presented datasets indicates potential for further improvement in water-use efficiency and productivity on Australian cotton farms.
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To break the yield ceiling of rice production, a super rice project was developed in 1996 to breed rice varieties with super high yield. A two-year experiment was conducted to evaluate yield and nitrogen (N)-use response of super rice to different planting methods in the single cropping season. A total of 17 rice varieties, including 13 super rice and four non-super checks (CK), were grown under three N levels [0 (N0), 150 (N150), and 225 (N225) kg ha−1] and two planting methods [transplanting (TP) and direct-seeding in wet conditions (WDS)]. Grain yield under WDS (7.69 t ha−1) was generally lower than TP (8.58 t ha−1). However, grain yield under different planting methods was affected by N rates as well as variety groups. In both years, there was no difference in grain yield between super and CK varieties at N150, irrespective of planting methods. However, grain yield difference was dramatic in japonica groups at N225, that is, there was an 11.3% and 14.1% average increase in super rice than in CK varieties in WDS and TP, respectively. This suggests that high N input contributes to narrowing the yield gap in super rice varieties, which also indicates that super rice was bred for high fertility conditions. In the japonica group, more N was accumulated in super rice than in CK at N225, but no difference was found between super and CK varieties at N0 and N150. Similar results were also found for N agronomic efficiency. The results suggest that super rice varieties have an advantage for N-use efficiency when high N is applied. The response of super rice was greater under TP than under WDS. The results suggest that the need to further improve agronomic and other management practices to achieve high yield and N-use efficiency for super rice varieties in WDS.
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This ‘how to’ guide provides readers with method to measure fan performance and energy efficiency of fans installed in meat chicken sheds. These methods are also useful for identifying fans that are under-performing or require maintenance. For more information about fan energy efficiency, a complementary report is available on the RIRDC website ‘Review of fan efficiency in meat chicken sheds’ (RIRDC Publication No. 15/018). A spreadsheet was also developed under this project for comparing and ranking fans against others in terms of energy efficiency, air flow and costs (‘Tunnel Ventilation Fan Comparison Spreadsheet’), and is available on the RIRDC website.
Resumo:
Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.