72 resultados para Cropping systems and livestock

em University of Queensland eSpace - Australia


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Systems approaches can help to evaluate and improve the agronomic and economic viability of nitrogen application in the frequently water-limited environments. This requires a sound understanding of crop physiological processes and well tested simulation models. Thus, this experiment on spring wheat aimed to better quantify water x nitrogen effects on wheat by deriving some key crop physiological parameters that have proven useful in simulating crop growth. For spring wheat grown in Northern Australia under four levels of nitrogen (0 to 360 kg N ha(-1)) and either entirely on stored soil moisture or under full irrigation, kernel yields ranged from 343 to 719 g m(-2). Yield increases were strongly associated with increases in kernel number (9150-19950 kernels m(-2)), indicating the sensitivity of this parameter to water and N availability. Total water extraction under a rain shelter was 240 mm with a maximum extraction depth of 1.5 m. A substantial amount of mineral nitrogen available deep in the profile (below 0.9 m) was taken up by the crop. This was the source of nitrogen uptake observed after anthesis. Under dry conditions this late uptake accounted for approximately 50% of total nitrogen uptake and resulted in high (>2%) kernel nitrogen percentages even when no nitrogen was applied,Anthesis LAI values under sub-optimal water supply were reduced by 63% and under sub-optimal nitrogen supply by 50%. Radiation use efficiency (RUE) based on total incident short-wave radiation was 1.34 g MJ(-1) and did not differ among treatments. The conservative nature of RUE was the result of the crop reducing leaf area rather than leaf nitrogen content (which would have affected photosynthetic activity) under these moderate levels of nitrogen limitation. The transpiration efficiency coefficient was also conservative and averaged 4.7 Pa in the dry treatments. Kernel nitrogen percentage varied from 2.08 to 2.42%. The study provides a data set and a basis to consider ways to improve simulation capabilities of water and nitrogen effects on spring wheat. (C) 1997 Elsevier Science B.V.

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Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.

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To simulate cropping systems, crop models must not only give reliable predictions of yield across a wide range of environmental conditions, they must also quantify water and nutrient use well, so that the status of the soil at maturity is a good representation of the starting conditions for the next cropping sequence. To assess the suitability for this task a range of crop models, currently used in Australia, were tested. The models differed in their design objectives, complexity and structure and were (i) tested on diverse, independent data sets from a wide range of environments and (ii) model components were further evaluated with one detailed data set from a semi-arid environment. All models were coded into the cropping systems shell APSIM, which provides a common soil water and nitrogen balance. Crop development was input, thus differences between simulations were caused entirely by difference in simulating crop growth. Under nitrogen non-limiting conditions between 73 and 85% of the observed kernel yield variation across environments was explained by the models. This ranged from 51 to 77% under varying nitrogen supply. Water and nitrogen effects on leaf area index were predicted poorly by all models resulting in erroneous predictions of dry matter accumulation and water use. When measured light interception was used as input, most models improved in their prediction of dry matter and yield. This test highlighted a range of compensating errors in all modelling approaches. Time course and final amount of water extraction was simulated well by two models, while others left up to 25% of potentially available soil water in the profile. Kernel nitrogen percentage was predicted poorly by all models due to its sensitivity to small dry matter changes. Yield and dry matter could be estimated adequately for a range of environmental conditions using the general concepts of radiation use efficiency and transpiration efficiency. However, leaf area and kernel nitrogen dynamics need to be improved to achieve better estimates of water and nitrogen use if such models are to be use to evaluate cropping systems. (C) 1998 Elsevier Science B.V.

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Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.

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Agriculture in limited resource areas is characterized by small farms which an generally too small to adequately support the needs of an average farm family. The farming operation can be described as a low input cropping system with the main energy source being manual labor, draught animals and in some areas hand tractors. These farming systems are the most important contributor to the national economy of many developing countries. The role of tillage is similar in dryland agricultural systems in both the high input (HICS) and low input cropping systems (LICS), however, wet cultivation or puddling is unique to lowland rice-based systems in low input cropping systems. Evidence suggest that tillage may result in marginal increases in crop yield in the short term, however, in the longer term it may be neutral or give rise to yield decreases associated with soil structural degradation. On marginal soils, tillage may be required to prepare suitable seedbeds or to release adequate Nitrogen through mineralization, but in the longer term, however, tillage reduces soil organic matter content, increases soil erodibility and the emission of greenhouse gases. Tillage in low input cropping systems involves a very large proportion of the population and any changes: in current practices such as increased mechanization will have a large social impact such as increased unemployment and increasing feminization of poverty, as mechanization may actually reduce jobs for women. Rapid mechanization is likely to result in failures, but slower change, accompanied by measures to provide alternative rural employment, might be beneficial. Agriculture in limited resource areas must produce the food and fiber needs of their community, and its future depends on the development of sustainable tillage/cropping systems that are suitable for the soil and climatic conditions. These should be based on sound biophysical principles and meet the needs of and he acceptable to the farming communities. Some of the principle requirements for a sustainable system includes the maintenance of soil health, an increase in the rain water use efficiency of the system, increased use of fertilizer and the prevention of erosion. The maintenance of crop residues on the surface is paramount for meeting these requirements, and the competing use of crop residues must be met from other sources. These requirements can be met within a zonal tillage system combined with suitable agroforestry, which will reduce the need for crop residues. It is, however, essential that farmers participate in the development of any new technologies to ensure adoption of the new system. (C) 2001 Elsevier Science B.V. All rights reserved.

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Wide and ‘skip row’ row configurations have been used as a means to improve yield reliability in grain sorghum production. However, there has been little effort put to design of these systems in relation to optimal combinations of root system characteristics and row configuration, largely because little is known about root system characteristics. The studies reported here aimed to determine the potential extent of root system exploration in skip row systems. Field experiments were conducted under rain-out shelters and the extent of water extraction and root system growth measured. One experiment was conducted using widely-spaced twin rows grown in the soil. The other experiment involved the use of specially constructed large root observation chambers for single plants. It was found that the potential extent of root system exploration in sorghum was beyond 2m from the planted rows using conventional hybrids and that root exploration continued during grain filling. Preliminary data suggested that the extent of water extraction throughout this region depended on root length density and the balance between demand for, and supply of, water. The results to date suggest that simultaneous genetic and management manipulation of wide row production systems might lead to more effective and reliable production in specific environments. Further study of variation in root-shoot dynamics and root system characteristics is required to exploit possible opportunities.

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While some recent frameworks on cognitive agents addressed the combination of mental attitudes with deontic concepts, they commonly ignore the representation of time. An exception is [1]that manages also some temporal aspects both with respect to cognition and normative provisions. We propose in this paper an extension of the logic presented in [1]with temporal intervals.

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A recent result of Bryant and Lindner shows that the quasigroups arising from 2-perfect m-cycle systems form a variety only when m = 3, 5 and 7. Here we investigate the situation in the case where the distance two cycles are required to be in the original system.

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In this paper we completely settle the embedding problem for m-cycle systems with m less than or equal to 14. We also solve the more general problem of finding m-cycle systems of K-v - K-u when m is an element of {4,6,7,8,10,12,14}.