38 resultados para Agriculture--Honduras.


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This paper describes how urban agriculture differs from conventional agriculture not only in the way it engages with the technologies of growing, but also in the choice of crop and the way these are brought to market. The authors propose a new model for understanding these new relationships, which is analogous to a systems view of information technology, namely Hardware-Software- Interface.
The first component of the system is hardware. This is the technological component of the agricultural system. Technology is often thought of as equipment, but its linguistic roots are in ‘technis’ which means ‘know how’. Urban agriculture has to engage new technologies, ones that deal with the scale of operation and its context which is different than rural agriculture. Often the scale is very small, and soils are polluted. There this technology in agriculture could be technical such as aquaponic systems, or could be soil-based agriculture such as allotments, window-boxes, or permaculture. The choice of method does not necessarily determine the crop produced or its efficiency. This is linked to the biotic that is added to the hardware, which is seen as the ‘software’.
The software of the system are the ecological parts of the system. These produce the crop which may or may not be determined by the technology used. For example, a hydroponic system could produce a range of crops, or even fish or edible flowers. Software choice can be driven by ideological preferences such as permaculture, where companion planting is used to reduce disease and pests, or by economic factors such as the local market at a particular time of the year. The monetary value of the ‘software’ is determined by the market. Obviously small, locally produced crops are unlikely to compete against intensive products produced globally, however the value locally might be measured in different ways, and might be sold on a different market. This leads to the final part of the analogy - interface.
The interface is the link between the system and the consumer. In traditional agriculture, there is a tenuous link between the producer of asparagus in Peru and the consumer in Europe. In fact very little of the money spent by the consumer ever reaches the grower. Most of the money is spent on refrigeration, transport and profit for agents and supermarket chains. Local or hyper-local agriculture needs to bypass or circumvent these systems, and be connected more directly to the consumer. This is the interface. In hyper-localised systems effectiveness is often more important than efficiency, and direct links between producer and consumer create new economies.

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During the early medieval period, Ireland was politically organised into a large number of very small kingdoms. Unlike much of Western Europe, it had not been incorporated into the Roman Empire, and as a consequence, settlement remained exclusively rural in character until the Viking period. Extensive documentary, archaeological, zooarchaeological and macro-plant evidence provides a detailed reconstruction of the livestock and arable economy of the period. Cattle ownership formed the basis of wealth as well as being an indicator of status in society, and this is reflected in its clear dominance of the livestock economy during this period. From the eighth century onwards, however, cereal production appears to grow in importance as subsistence farming gave way to the production of agricultural surplus. This is reflected in cereal diversification and in the construction of watermills and more efficient grain-drying kilns. At the same time, settlement underwent significant changes and the relative importance of cattle in some areas began to decline.

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Climate and other environmental change presents a number of challenges for effective food safety. Food production, distribution and consumption takes place within functioning ecosystems but this backdrop is often ignored or treated as static and unchanging. The risks presented by environmental change include novel pests and diseases, often caused by problem species expanding their spatial distributions as they track changing conditions, toxin generation in crops, direct effects on crop and animal production, consequences for trade networks driven by shifting economic viability of production methods in changing environments and finally, wholesale transformation of ecosystems as they respond to novel climatic regimes.

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In this paper, an automatic Smart Irrigation Decision Support System, SIDSS, is proposed to manage irrigation in agriculture. Our system estimates the weekly irrigations needs of a plantation, on the basis of both soil measurements and climatic variables gathered by several autonomous nodes deployed in field. This enables a closed loop control scheme to adapt the decision support system to local perturbations and estimation errors. Two machine learning techniques, PLSR and ANFIS, are proposed as reasoning engine of our SIDSS. Our approach is validated on three commercial plantations of citrus trees located in the South-East of Spain. Performance is tested against decisions taken by a human expert.