3 resultados para systems thinking

em eResearch Archive - Queensland Department of Agriculture


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The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).

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Global trends in human population and agriculture dictate that future calls made on the resources (physical, human, financial) and systems involved in producing food will be increasingly more demanding and complex. Both plant breeding and improved agronomy lift the potential yield of crops, a key component in progressing farm yield, so society can reasonably expect both agronomy as a science and agronomists as practitioners to contribute to the successful delivery of necessary change. By reflecting on current trends in agricultural production (diversification, intensification, integration, industrialisation, automation) and deconstructing a futuristic scenario of attempting agricultural production on Mars, it seems the skills agronomists will require involve not only the mandatory elements of their discipline but also additional skills that enable engagement with, even leadership of, teams who integrate (in sum or part) engineering, (agri-)business, economics and operational management, and build the social capital required to create and maintain a diverse array of enhanced and new ethical production systems and achieve increasing efficiencies within them.

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The shelf life of mangoes is limited by two main postharvest diseases when not consistently managed. These are anthracnose ( Colletotrichum gloeosporioides) and stem end rots (SER) ( Fusicoccum parvum). The management of these diseases has often relied mainly on the use of fungicides either as field spray treatments or as postharvest dips. These have done a fairly good job at serving the industry and allowing fruits to be transported, stored and sold at markets distant from the areas of production. There are however concerns on the continuous use of these fungicides as the main or only tool for the management of these diseases. This has necessitated a re-think of how these diseases could be sustainably managed into the future using a systems approach that focuses on integrated crop management. It is a holistic approach that considers all the crop protection management strategies including the genetics of the plant and its ability to naturally defend itself from infection with plant activators and growth regulators. It also considers other cultural or agronomic management tools such as the use of crop nutrition, timely application of irrigation water and the pruning of trees on a regular basis as a means of reducing inoculum levels in the orchards. The ultimate aim of this approach is to increase yields and obtain long term sustainable production. It is guided by the sustainable crop production principle which states that producers should apply as little inputs as possible but as much as needed.