28 resultados para Agricultural inputs


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This paper focuses on the higher order factors affecting successful adoption of technologies. Drawing on the "actor-oriented perspective" in rural sociology, it is argued that successful examples of adoption at this higher level result from a complex conjunction of people and events, with outcomes that may have been quite unanticipated at the outset. From this perspective, research and extension projects and programs are viewed as arenas in which social actors–village leaders, farmers, researchers (local and international), aid officials, municipal agents, extension workers, and traders–pursue their own short- and long-term objectives and strategies. To this end, they maneuver, negotiate, organize, cooperate, participate, coerce, obstruct, form coalitions, adopt, adapt, and reject, all within a specific geographical and historical context.

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This paper uses data collected from migrants' wives in the Nyeri district of Kenya. The main objective is to determine whether migration and remittances contribute to the development of agriculture. Our results suggest that most migrants are pushed out of rural areas, belong to the group of low-paid workers in urban areas, send little and irregular remittances to their wives back in rural areas and that these remittances are mainly used for consumption purposes and do not contribute to any significant development in agriculture. Our results also indicate that altruism or social obligation might be the main reason for migrants sending remittances back to their rural wives.

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Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Recent investigations have demonstrated the presence of an unidentified source of polychlorinated dibenzo-p-dioxins (PCDDs) in the coastal zone of Queensland (Australia). The present study provides new information on the possible PCDD sources and their temporal input to this environment. Two estuarine sediment cores were collected in northern Queensland for which radiochemical chronologies were established. Core sections from different depositional ages, up to three centuries, have been analyzed for 2,3,7,8-substituted PCDDs and polychlorinated dibenzofurans (PCDFs). Variations of PCDD concentrations in the sediment cores over several centuries of depositional history were relatively small, and elevated PCDD levels were still present in sediment slices from the early 17th century. PCDD/F isomer patterns and congener profiles in sediments deposited during the last 350 years were almost identical and correlated well to the characteristic profiles observed in surface sediments and soils from the entire Queensland coastline. Profiles were dominated by higher chlorinated PCDDs, in particular octachlorodibenzodioxin (OCDD), whereas PCDF concentrations were below or near the limit of detection. These results indicate the presence of a PCDD source prior to industrialization and production of commercial organochlorine products. Further, the present study demonstrates that PCDD input patterns have been similar along an extensive but localized area over at least several centuries, contributing relatively high concentrations of PCDDs to the coastal system of Queensland.

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Use of chemical inputs such as pesticides has increased agricultural production and productivity. However, negative externalities from such use have increased too. These externalities include damage to agricultural land, fisheries, fauna and flora. Another major externality is the unintentional destruction of beneficial predators of pests thereby increasing the virulence of many species of agricultural pests. Furthermore, increased mortality and morbidity of humans due to exposure to pesticides are recorded especially in developing countries. The costs from these externalities are large and affect farmers' returns. However, despite these high costs, farmers continue to use pesticides and in most countries in increasing quantities. In this paper, we examine this paradox and show why farmers continue to use pesticides despite the increasing costs. We also emphasize 'lock-in' aspects of pesticide use. (C) 2001 Elsevier Science B.V. All rights reserved.

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We studied the foraging habitat of the endangered black-breasted button-quail (Turnix melanogaster) in 13 rainforest patches of an agricultural landscape (23.4 km(2)) in eastern Australia to assess its use of fragmented habitats outside conservation reserves. The species foraged only in the three largest patches (17.4, 40.0, 63.8 ha in size), all of which were connected to open eucalypt forest, and in intact rainforest. Occurrence of birds was greatest in the largest patch. The maximum number of individuals within the study area was estimated to be 22. Radio-tracking of nine birds revealed that three were resident in the largest patch for periods of over 100 days; no movements between patches were detected. Three radio-tagged birds were taken by avian and mammalian predators. Our results indicated that the long-term future of the species in agricultural landscapes is bleak and that management action is urgently needed to arrest its decline in these ecosystems, (C) 2001 Elsevier Science Ltd. All rights reserved.

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The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Despite growing attention to crop and property damage caused by the Asian elephant, uncertainty exists about the magnitude of this problem. This article explores the nature and, Magnitude of this problem in Sri Lanka. An economic analysis of individual farmers'. decisions to control elephants is provided. Government policies to assist farmers in coping with the elephant pest problem are assessed. Appropriate compensation schemes for farmers are seen as potentially more effective for conserving elephants in Sri Lanka than legal prohibitions on the killing of elephants. The issues raised here have wider relevance than merely to Sri Lanka or Asian elephants.

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Observations of an insect's movement lead to theory on the insect's flight behaviour and the role of movement in the species' population dynamics. This theory leads to predictions of the way the population changes in time under different conditions. If a hypothesis on movement predicts a specific change in the population, then the hypothesis can be tested against observations of population change. Routine pest monitoring of agricultural crops provides a convenient source of data for studying movement into a region and among fields within a region. Examples of the use of statistical and computational methods for testing hypotheses with such data are presented. The types of questions that can be addressed with these methods and the limitations of pest monitoring data when used for this purpose are discussed. (C) 2002 Elsevier Science B.V. All rights reserved.

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The Agricultural Production Systems slMulator, APSIM, is a cropping system modelling environment that simulates the dynamics of soil-plant-management interactions within a single crop or a cropping system. Adaptation of previously developed crop models has resulted in multiple crop modules in APSIM, which have low scientific transparency and code efficiency. A generic crop model template (GCROP) has been developed to capture unifying physiological principles across crops (plant types) and to provide modular and efficient code for crop modelling. It comprises a standard crop interface to the APSIM engine, a generic crop model structure, a crop process library, and well-structured crop parameter files. The process library contains the major science underpinning the crop models and incorporates generic routines based on physiological principles for growth and development processes that are common across crops. It allows APSIM to simulate different crops using the same set of computer code. The generic model structure and parameter files provide an easy way to test, modify, exchange and compare modelling approaches at process level without necessitating changes in the code. The standard interface generalises the model inputs and outputs, and utilises a standard protocol to communicate with other APSIM modules through the APSIM engine. The crop template serves as a convenient means to test new insights and compare approaches to component modelling, while maintaining a focus on predictive capability. This paper describes and discusses the scientific basis, the design, implementation and future development of the crop template in APSIM. On this basis, we argue that the combination of good software engineering with sound crop science can enhance the rate of advance in crop modelling. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.