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| Filter results20 paper(s) found. |
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1. Analyzing Organic Farming Training In The Curriculum Of The University Of Kwazulu-Natal, PietermaritzburgANALYZING ORGANIC FARMING TRAINING IN THE CURRICULUM OF THE UNIVERSITY OF KWAZULU-NATAL, PIETERMARITZBURG SJ, Polepole * and SH, Worth Agricultural Extension and Rural Resource Management Program; University of KwaZulu-Natal; School... S.H. Worth, S.J. Polepole |
2. Smart Agriculture: A Futuristic Vision of Application of the Internet of Things (IoT) in Brazilian AgricultureWith the economy based on agribusiness, Brazil is an important representative on the world stage in agricultural production, either in terms of quantity or cultivated diversity due to a scenario with vast arable land and favorable climate. There are many crops that are adapteble to soils of the country. Despite the global representation, it is known that the Brazilian agricultural production does not yet have a modern agriculture by restricting the use of new technologies to farmers with better... C.L. Bazzi, R. Araujo, E.G. Souza, K. Schenatto, A. Gavioli, N.M. Betzek |
3. Large-scale UAS Data Collection, Processing and Management for Field Crop ManagementNorth Dakota State University research and Extension personnel are collaborating with Elbit Systems of America to compare the usefulness and economics of imagery collected from a large unmanned aircraft systems (UAS), small UAS and satellite imagery. Project personnel are using a large UAS powered with an internal combustion engine to collect high-resolution imagery over 100,000 acres twice each month during the crop growing season. Four-band multispectral Imagery is also being collected twice... J. Nowatzki, S. Bajwa, D. Roberts, M. Ossowski, A. Scheve, A. Johnson, Y. Chaplin |
4. In-field Variability of Terrain and Soils in Southeast Kansas: Challenges for Effective ConservationA particular challenge for crop production in southeast Kansas is the shallow topsoil, underlain with a dense, unproductive clay layer. Concerns for topsoil loss have shifted production systems to reduced tillage or conservation management practices. However, historical erosion events and continued nutrient and sediment loss still limit the productive capacity of fields. To improve crop production and further adoption of conservation practices, identification of vulnerable areas of fields was... G.F. Sassenrath, T. Mueller, V.J. Alarcon, S.E. Kulesza, D. Shoup |
5. Nitrogen Sensing by Using Spectral Reflectance Measurements in Cereal Rye CanopyCereal rye (cereale secale L.) is a winter crop well suited for cultivation especially besides high yield areas because of its relatively low demands on the soil and on the climate as well. In 2016 about 4.9% of arable land in Germany was cultivated with cereal rye (Statistisches Bundesamt, 2017). Unlike other crops such as wheat, there is little research on cereal rye for site specific farming. Furthermore, also in a cereal rye cultivation it is necessary to minimize nitrogen loss.... M. Strenner, F.X. Maidl, K.J. Hülsbergen |
6. AgDataBox – API (Application Programming Interface)E-agricultural is an emerging field focusing in the enhancement of agriculture and rural development through improve in information and data processing. The data-intensive characteristic of these domains is evidenced by the great variety of data to be processed and analyzed. Countrywide estimates rely on maps, spectral images from satellites, and tables with rows for states, regions, municipalities, or farmers. Precision agriculture (PA) relies on maps of within field variability of soil and plant... C.L. Bazzi, E.P. Jasse, E.G. Souza, P.S. Magalhães, G.K. Michelon, K. Schenatto, A. Gavioli |
7. Evaluation of Strip Tillage Systems in Maize Production in HungaryStrip tillage is a form of conservation tillage system. It combines the benefits of conventional tillage systems with the soil-protecting advantages of no-tillage. The tillage zone is typically 0.25 to 0.3 m wide and 0.25 to 0.30 m deep. The soil surface between these strips is left undisturbed and the residue from the previous crop remain on the soil surface. The residue-covered area reaches 60-70%. Keeping residue on the surface helps prevent soil structure and reduce water loss from the soil.... T. Rátonyi, P. Ragán, D. Sulyok, J. Nagy, E. Harsányi, A. Vántus, N. Csatári |
8. Examining the Relationship Between SPAD, LAI and NDVI Values in a Maize Long-Term ExperimentIn Hungary, the preconditions for the use of precision crop production have undergone enormous development over the last five years. RTK coverage is complete in crop production areas. Consultants are increasingly using the vegetation index maps from Landsat and Sentinel satellite data, but measurements with on-site proximal plant sensors are also needed to exclude the influence of the atmosphere. The aim of our studies was to compare the values measured by proximal plant sensors in the... P. Ragán, E. Harsányi, J. Nagy, T. Ágnes, T. Rátonyi, A. Vántus, N. Csatári |
9. The Spread of Precision Livestock Farming Technology at Dairy Farms in East HungaryDuring the survey, 25 dairy farms were examined in East Hungary in Hajdú-Bihar (H-B) County between 2017 and 2018 by methodical observation and oral interviews with the farm managers, about the spread of Precision Livestock Farming (PLF) technologies. Among Holstein Friesian dairy farms in the County 60% were questioned, and the representativity was above 47 percent ins each size category. Nine precision farming equipment were examined on the farms: milking robot or robotic carousel milking... C. Nándor, T. Rátonyi, E. Harsányi, P. Ragán, Z. Hagymássy, J. Nagy, A. Vántus |
10. Variety Effects on Cotton Yield Monitor CalibrationWhile modern grain yield monitors are able to harvest variety and hybrid trials without imposing bias, cotton yield monitors are affected by varietal properties. With planters capable of site-specific planting of multiple varieties, it is essential to better understand cotton yield monitor calibration. Large-plot field experiments were conducted with two southeast Missouri cotton producers to compare yield monitor-estimated weights and observed weights in replicated variety trials. Two replications... E. Vories, A. Jones, G. Stevens, C. Meeks |
11. Forecasting Crop Yield Using Multi-Layered, Whole-Farm Data Sets and Machine LearningThe ultimate goal of Precision Agriculture is to improve decision making in the business of farming. Many broadacre farmers now have a number of years of crop yield data for their fields which are often augmented with additional spatial data, such as apparent soil electrical conductivity (ECa), soil gamma radiometrics, terrain attributes and soil sample information. In addition there are now freely available public datasets, such as rainfall, digital soil maps and archives of satellite remote... P. Filippi, E.J. Jones, M. Fajardo, B.M. Whelan, T.F. Bishop |
12. Optimising Nitrogen Use in Cereal Crops Using Site-Specific Management Classes and Crop Reflectance SensorsThe relative cost of Nitrogen (N) fertilisers in a cropping input budget, the 33% Nitrogen use efficiency (NUE) seen in global cereal grain production and the potential environmental costs of over-application are leading to changes in the application rates and timing of N fertiliser. Precision agriculture (PA) provides tools for producers to achieve greater synchrony between N supply and crop N demand. To help achieve these goals this research has explored the use of management classes derived... B. Whelan, M. Fajardo |
13. Improving Active Canopy Sensor-Based In-Season N Recommendation Using Plant Height Information for Rain-Fed Maize in Northeast ChinaThe inefficient utilization of nitrogen (N) fertilizer due to leaching, volatilization and denitrification has resulted in environmental pollution in rain-fed maize production in Northeast China. Active canopy sensor-based in-season N application has been proven effective to meet maize N requirement in space and time. The objective of this research was to evaluate the feasibility of using active canopy sensor for guiding in in-season N fertilizer recommendation for rain-fed maize in Northeast... X. Wang, Y. Miao, T. Xia, R. Dong, G. Mi, D.J. Mulla |
14. Calculating the Water Deficit of Apple Orchard by Means of Spatially Resolved ApproachIn semi-humid climate, spatially resolved analysis of water deficit was carried out in apple orchard (Malus x domestica 'Pinova'). The meteorological data were recorded daily by a weather station. The apparent soil electrical conductivity (ECa) was measured at field capacity, and twenty soil samples in 30 cm were gathered for texture, bulk density, and gravimetric soil water content analyses. Furthermore, ten trees were defoliated in different ECa regions in order to estimate the leaf... N. Tsoulias, D. Paraforos, N. Brandes, S. Fountas, M. Zude-sasse |
15. Fruit Fly Electronic Monitoring SystemInsects are a constant threat to agriculture, especially the cultivation of various types of fruits such as apples, pears, guava, etc. In this sense, it is worth mentioning the Anastrepha genus flies (known as fruit fly), responsible for billionaire losses in the fruit growing sector around the world, due to the severity of their attack on orchards. In Brazil, this type of pests has been controlled in most product areas by spraying insecticides, which due to the need for prior knowledge regarding... C.L. Bazzi, F.V. Silva, L. Gebler, E.G. Souza, K. Schenatto, R. Sobjak, R.S. Dos santos, A.M. Hachisuca, F. Franz |
16. Yield Mapping in Fruit FarmingDue to the importance of increasing the quantity and quality of world agricultural production, the use of technologies to assist in production processes is essential. Despite this, a timid adoption by precision agriculture (PA) technologies is verified by the Brazilian fruit producers, even though it is one of the segments that had been stood out in recent years in the country's economy. In the PA context, yield maps are rich sources of information, especially by species harvested through... C.L. Bazzi, M.R. Martins, L. Gebler, E.G. Souza, K. Schenatto, R. Sobjak, A. . Hachisuca, F. Franz |
17. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital AgricultureAgriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira |
18. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast TrackAgriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues |
19. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart FarmCurrently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues |
20. Sugarcane Yield Mapping Using an On-board Volumetric SensorFew alternatives are available to the sugarcane sector for monitoring crop productivity. However, in recent years, research has been dedicated to developing methods ranging from estimation based on engine parameters to using sensors and artificial intelligence. This study aims to present a new tool for monitoring productivity applied to sugarcane cultivation, which utilizes a volumetric optical sensor, in contrast to other methods already used for this measurement, and is recently being introduced... G. Balboa, J.C. Masnello, F. De oliveira moreira, R. Canal filho, E.R. Da silva, J.P. Molin |