4 resultados para knowledge-based systems

em eResearch Archive - Queensland Department of Agriculture


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This paper describes a new knowledge acquisition method using a generic design environment where context-sensitive knowledge is used to build specific DSS for rural business. Although standard knowledge acquisition methods have been applied in rural business applications, uptake remains low and familiar weaknesses such as obsolescence and brittleness apply. We describe a decision support system (DSS) building environment where contextual factors relevant to the end users are directly taken into consideration. This "end user enabled design environment" (EUEDE) engages both domain experts in creating an expert knowledge base and business operators/end users (such as farmers) in using this knowledge for building their specific DSS. We document the knowledge organisation for the problem domain, namely a dairy industry application. This development involved a case-study research approach used to explore dairy operational knowledge. In this system end users can tailor their decision-making requirements using their own judgement to build specific DSSs. In a specific end user's farming context, each specific DSS provides expert suggestions to assist farmers in improving their farming practice. The paper also shows the environment's generic capability.

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Concepts of agricultural sustainability and possible roles of simulation modelling for characterising sustainability were explored by conducting, and reflecting on, a sustainability assessment of rain-fed wheat-based systems in the Middle East and North Africa region. We designed a goal-oriented, model-based framework using the cropping systems model Agricultural Production Systems sIMulator (APSIM). For the assessment, valid (rather than true or false) sustainability goals and indicators were identified for the target system. System-specific vagueness was depicted in sustainability polygons-a system property derived from highly quantitative data-and denoted using descriptive quantifiers. Diagnostic evaluations of alternative tillage practices demonstrated the utility of the framework to quantify key bio-physical and chemical constraints to sustainability. Here, we argue that sustainability is a vague, emergent system property of often wicked complexity that arises out of more fundamental elements and processes. A 'wicked concept of sustainability' acknowledges the breadth of the human experience of sustainability, which cannot be internalised in a model. To achieve socially desirable sustainability goals, our model-based approach can inform reflective evaluation processes that connect with the needs and values of agricultural decision-makers. Hence, it can help to frame meaningful discussions, from which actions might emerge.

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The global importance of grasslands is indicated by their extent; they comprise some 26% of total land area and 80% of agriculturally productive land. The majority of grasslands are located in tropical developing countries where they are particularly important to the livelihoods of some one billion poor peoples. Grasslands clearly provide the feed base for grazing livestock and thus numerous high-quality foods, but such livestock also provide products such as fertilizer, transport, traction, fibre and leather. In addition, grasslands provide important services and roles including as water catchments, biodiversity reserves, for cultural and recreational needs, and potentially a carbon sink to alleviate greenhouse gas emissions. Inevitably, such functions may conflict with management for production of livestock products. Much of the increasing global demand for meat and milk, particularly from developing countries, will have to be supplied from grassland ecosystems, and this will provide difficult challenges. Increased production of meat and milk generally requires increased intake of metabolizable energy, and thus increased voluntary intake and/or digestibility of diets selected by grazing animals. These will require more widespread and effective application of improved management. Strategies to improve productivity include fertilizer application, grazing management, greater use of crop by-products, legumes and supplements and manipulation of stocking rate and herbage allowance. However, it is often difficult to predict the efficiency and cost-effectiveness of such strategies, particularly in tropical developing country production systems. Evaluation and on-going adjustment of grazing systems require appropriate and reliable assessment criteria, but these are often lacking. A number of emerging technologies may contribute to timely low-cost acquisition of quantitative information to better understand the soil-pasture-animal interactions and animal management in grassland systems. Development of remote imaging of vegetation, global positioning technology, improved diet markers, near IR spectroscopy and modelling provide improved tools for knowledge-based decisions on the productivity constraints of grazing animals. Individual electronic identification of animals offers opportunities for precision management on an individual animal basis for improved productivity. Improved outcomes in the form of livestock products, services and/or other outcomes from grasslands should be possible, but clearly a diversity of solutions are needed for the vast range of environments and social circumstances of global grasslands.

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The in vivo faecal egg count reduction test (FECRT) is the most commonly used test to detect anthelmintic resistance (AR) in gastrointestinal nematodes (GIN) of ruminants in pasture based systems. However, there are several variations on the method, some more appropriate than others in specific circumstances. While in some cases labour and time can be saved by just collecting post-drench faecal worm egg counts (FEC) of treatment groups with controls, or pre- and post-drench FEC of a treatment group with no controls, there are circumstances when pre- and post-drench FEC of an untreated control group as well as from the treatment groups are necessary. Computer simulation techniques were used to determine the most appropriate of several methods for calculating AR when there is continuing larval development during the testing period, as often occurs when anthelmintic treatments against genera of GIN with high biotic potential or high re-infection rates, such as Haemonchus contortus of sheep and Cooperia punctata of cattle, are less than 100% efficacious. Three field FECRT experimental designs were investigated: (I) post-drench FEC of treatment and controls groups, (II) pre- and post-drench FEC of a treatment group only and (III) pre- and post-drench FEC of treatment and control groups. To investigate the performance of methods of indicating AR for each of these designs, simulated animal FEC were generated from negative binominal distributions with subsequent sampling from the binomial distributions to account for drench effect, with varying parameters for worm burden, larval development and drench resistance. Calculations of percent reductions and confidence limits were based on those of the Standing Committee for Agriculture (SCA) guidelines. For the two field methods with pre-drench FEC, confidence limits were also determined from cumulative inverse Beta distributions of FEC, for eggs per gram (epg) and the number of eggs counted at detection levels of 50 and 25. Two rules for determining AR: (1) %reduction (%R) < 95% and lower confidence limit <90%; and (2) upper confidence limit <95%, were also assessed. For each combination of worm burden, larval development and drench resistance parameters, 1000 simulations were run to determine the number of times the theoretical percent reduction fell within the estimated confidence limits and the number of times resistance would have been declared. When continuing larval development occurs during the testing period of the FECRT, the simulations showed AR should be calculated from pre- and post-drench worm egg counts of an untreated control group as well as from the treatment group. If the widely used resistance rule 1 is used to assess resistance, rule 2 should also be applied, especially when %R is in the range 90 to 95% and resistance is suspected.