992 resultados para Precision agriculture


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The project will produce practical and relevant benchmarks, protocols and recommendations for the adoption of remote sensing technologies for improved in season management and therefore production within the Australian sugar cane industry.

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Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.

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There is an increasing requirement for more astute land resource management through efficiencies in agricultural inputs in a sugar cane production system. A precision agriculture (PA) approach can provide a pathway for a sustainable sugarcane production system. One of the impediments to the adoption of PA practices is access to paddock-scale mapping layers displaying variability in soil properties, crop growth and surface drainage. Variable rate application (VRA) of nutrients is an important component of PA. However, agronomic expertise within PA systems has fallen well behind significant advances in PA technologies. Generally, advisers in the sugar industry have a poor comprehension of the complex interaction of variables that contribute to within-paddock variations in crop growth. This is regarded as a significant impediment to the progression of PA in sugarcane and is one of the reasons for the poor adoption of VRA of nutrients in a PA approach to improved sugar cane production. This project therefore has established a number of key objectives which will contribute to the adoption of PA and the staged progression of VRA supported by relevant and practical agronomic expertise. These objectives include provision of base soils attribute mapping that can be determined using Veris 3100 Electrical Conductivity (EC) and digital elevation datasets using GPS mapping technology for a large sector of the central cane growing region using analysis of archived satellite imagery to determine the location and stability of yield patterns over time and in varying seasonal conditions on selected project study sites. They also include the stablishment of experiments to determine appropriate VRA nitrogen rates on various soil types subjected to extended anaerobic conditions, and the establishment of trials to determine nitrogen rates applicable to a declining yield potential associated with the aging of ratoons in the crop cycle. Preliminary analysis of archived yield estimation data indicates that yield patterns remain relatively stable overtime. Results also indicate the where there is considerable variability in EC values there is also significant variation in yield.

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This work presents a solution for the aerial coverage of a field by using a fleet of aerial vehicles. The use of Unmanned Aerial Vehicles allows to obtain high resolution mosaics to be used in Precision Agriculture techniques. This report is focus on providing a solution for the full simultaneous coverage problem taking into account restrictions as the required spatial resolution and overlap while maintaining similar light conditions and safety operation of the drones. Results obtained from real field tests are finally reported

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Remote sensed imagery acquired with mini aerial vehicles, in conjunction with GIS technology enable a meticulous analysis from surveyed agricultural sites. This paper sums up the ongoing work in area discretization and coverage with mini quad-­?rotors applied to Precision Agriculture practices under the project RHEA.

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A crop management and precision agriculture software application facilitates the flow of information between disparate software/equipment and the network of individuals that work with them. A new generation of farmers are using precision technology to help them more efficiently manage their roplands. By measuring precisely the way their fields reflect and emit energy at visible and infrared wavelengths, precision farmers can monitor a wide range of variables that affect their crops,such as soil moisture, surface temperature, photosynthetic activity, and weed or pest infestations. Over thirty years have passed since Nelson and Winter put the concept of routines firmly at the center of the analysis of organizational and economic change. Taken as the central unit of analysis, routines would help understand energy and agriculture economy evolution.

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Wheat (Triticum aestivum L.), rice (Oryza sativa L.), and maize (Zea mays L.) provide about two-thirds of all energy in human diets, and four major cropping systems in which these cereals are grown represent the foundation of human food supply. Yield per unit time and land has increased markedly during the past 30 years in these systems, a result of intensified crop management involving improved germplasm, greater inputs of fertilizer, production of two or more crops per year on the same piece of land, and irrigation. Meeting future food demand while minimizing expansion of cultivated area primarily will depend on continued intensification of these same four systems. The manner in which further intensification is achieved, however, will differ markedly from the past because the exploitable gap between average farm yields and genetic yield potential is closing. At present, the rate of increase in yield potential is much less than the expected increase in demand. Hence, average farm yields must reach 70–80% of the yield potential ceiling within 30 years in each of these major cereal systems. Achieving consistent production at these high levels without causing environmental damage requires improvements in soil quality and precise management of all production factors in time and space. The scope of the scientific challenge related to these objectives is discussed. It is concluded that major scientific breakthroughs must occur in basic plant physiology, ecophysiology, agroecology, and soil science to achieve the ecological intensification that is needed to meet the expected increase in food demand.

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Precision agriculture (PA) describes a suite of IT based tools which allow farmers to electronically monitor soil and crop conditions and analyze treatment options. This study tests a model explaining the difficulties of PA technology adoption. The model draws on theories of technology acceptance and diffusion of innovation and is validated using survey data from farms in Canada. Findings highlight the importance of compatibility among PA technology components and the crucial role of farmers' expertise. The model provides the theoretical and empirical basis for developing policies and initiatives to support PA technology adoption.

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There are few regulatory restrictions involving the use of fully autonomous unmanned aerial systems in unpopulated, farming areas of Australia. The combination of a fully autonomous aerial and ground systems would provide efficient and cost effective retrieval of soil and vegetation data for use in precision agriculture. The aerial system will survey the site and collect spectral imagery to analyse plant density, stress and nutrition. The ground sensors will collect soil moisture content readings throughout the site. The data from both systems will be collated at a central base station. The base station will also provide housing and interface with the aerial system.

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This thesis presents the design process and the prototyping of a lightweight, modular robotic vehicle for the sustainable intensification of broadacre agriculture. Achieved by the joint operation of multiple autonomous vehicles to improve energy consumption, reduce labour, and increase efficiency in the application of inputs for the management of crops. The Small Robotic Farm Vehicle (SRFV) is a lightweight and energy efficient robotic vehicle with a configurable, modular design. It is capable of undertaking a range of agricultural tasks, including fertilising and weed management through mechanical intervention and precision spraying, whilst being more than an order of magnitude lower in weight than existing broadacre agricultural equipment.

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Precision Spray is a technique to increase performance of Precision Agriculture. This spray technique may be aided by a Wireless Sensor Network, however, for such approach, the communication between the agricultural input applicator vehicle and network is critical due to its proper functioning. Thus, this work analyzes how the number of nodes in a wireless sensor network, its type of distribution and different areas of scenario affects the performance of communication. We performed simulations to observe system's behavior changing to find the most fitted non-controlled mobility model to the system.