38 resultados para Agronomic efficiency
Development and adoption of a web-based irrigation management tool for improved water use efficiency
Resumo:
Develop a web-based tool to assist farmers and consultants make strategic and tactical irrigation decisions.
Resumo:
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 .
Resumo:
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.
Resumo:
Dry-seeded rice (DSR) is an emerging resource-conserving technology in many Asian countries, but weeds remain the major threat to the production of DSR systems. A field study was conducted in 2012 and 2013 at the International Rice Research Institute (IRRI), Los Baños, Philippines, to evaluate the performance of sole and sequential applications of preemergence (oxadiazon and pendimethalin), early postemergence (butachlor + propanil and thiobencarb + 2,4-D), and late postemergence herbicides (bispyribac-sodium and fenoxaprop + ethoxysulfuron) with different modes of action in comparison to manual weeding in DSR. The sequential applications of all preemergence and postemergence herbicides reduced weed density and biomass by 80–100% compared to the nontreated plots. The sole application of postemergence herbicides reduced weed density by only 44–54% and weed biomass by 51–61%, whereas oxadiazon alone reduced weed density and biomass by 96–100%. All herbicide treatments and manual weeding significantly affected tiller number, biomass, crop growth rate, agronomic indices, yield-contributing parameters (panicle density and filled grains), and yield (biological and grain) of rice. The highest grain yield was obtained in the manually weeded plots (5.9–6.1 t ha−1) and the plots treated with oxadiazon alone (5.4–5.6 t ha−1) and oxadiazon followed by postemergence herbicides (5.2–5.8 t ha−1). The lowest paddy yield (0.22 t ha−1) was achieved in the nontreated plots followed by the plots treated with the sole application of bispyribac-sodium and fenoxaprop + ethoxysulfuron. The results suggest that oxadiazon is the best broad-spectrum and economically effective herbicide when applied alone or in combination with other effective postemergence herbicides with different modes of action, depending on the weed species present in the field.
Resumo:
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:
With the aim of increasing peanut production in Australia, the Australian peanut industry has recently considered growing peanuts in rotation with maize at Katherine in the Northern Territory—a location with a semi-arid tropical climate and surplus irrigation capacity. We used the well-validated APSIM model to examine potential agronomic benefits and long-term risks of this strategy under the current and warmer climates of the new region. Yield of the two crops, irrigation requirement, total soil organic carbon (SOC), nitrogen (N) losses and greenhouse gas (GHG) emissions were simulated. Sixteen climate stressors were used; these were generated by using global climate models ECHAM5, GFDL2.1, GFDL2.0 and MRIGCM232 with a median sensitivity under two Special Report of Emissions Scenarios over the 2030 and 2050 timeframes plus current climate (baseline) for Katherine. Effects were compared at three levels of irrigation and three levels of N fertiliser applied to maize grown in rotations of wet-season peanut and dry-season maize (WPDM), and wet-season maize and dry-season peanut (WMDP). The climate stressors projected average temperature increases of 1°C to 2.8°C in the dry (baseline 24.4°C) and wet (baseline 29.5°C) seasons for the 2030 and 2050 timeframes, respectively. Increased temperature caused a reduction in yield of both crops in both rotations. However, the overall yield advantage of WPDM increased from 41% to up to 53% compared with the industry-preferred sequence of WMDP under the worst climate projection. Increased temperature increased the irrigation requirement by up to 11% in WPDM, but caused a smaller reduction in total SOC accumulation and smaller increases in N losses and GHG emission compared with WMDP. We conclude that although increased temperature will reduce productivity and total SOC accumulation, and increase N losses and GHG emissions in Katherine or similar northern Australian environments, the WPDM sequence should be preferable over the industry-preferred sequence because of its overall yield and sustainability advantages in warmer climates. Any limitations of irrigation resulting from climate change could, however, limit these advantages.
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.