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| Filter results10 paper(s) found. |
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1. Hyperspectral Imagery for the Detection of Nitrogen Stress in Potato for In-season Management... T.J. Nigon, C. Rosen, D. Mulla, Y. Cohen, V. Alchanatis, R. Rud |
2. A Low Cost, Modular Robotics Tool Carrier for Precision Agriculture ResearchCurrent research within agricultural crop production focus on using autonomous robot technology to optimize the production efficiency, enhance sustainability and minimize tedious, monotonous and wearing tasks. But progress is slow partly... A. Bøgild, S.H. Nielsen, N.J. Jacobsen, C.L. Jaeger-hansen, R.N. Jørgensen, K. Jensen, O.J. Jørgensen |
3. Effect Of Nitrogen Application Rate On Soil Residual N And Cotton YieldA long-term study was conducted on nitrogen application rate and its impact on soil residual nitrogen and cotton (FM960B2RF) lint yield under a drip irrigation production system near Plainview, Texas. The experiment was a randomized complete block design with five nitrogen application rates (0, 56, 112, 168 and 224 kg per ha) and five replications. The soil nitrogen treatment was applied as side dressing. Cotton yield, leaf N, seed N, soil residual nitrate, amount of irrigation, and rainfall data... M. Parajulee, D. Neupane, C. Wang, S. Carroll, R. Shrestha |
4. A Method For Sampling Scab Spots On Apple Leaves In The Orchard Using Machine VisionIntroduction One of the largest threats in apple orchards is scab. Current procedures involve models based on weather data that predict the likelihood of scab attacks. In case of alarm the orchard is sprayed with preventive pesticides and this typically happens 25-30 times per season. The scab attacks the leaves and stays on fallen leaves that reinfect the trees with rainwater, making it an advantage to include a-priori knowledge on previous... M.G. Bertelsen, K. Nielsen, M.R. Nielsen |
5. Fusion Of Multi Exposure Stereo Images And Thermography For Obstacle Detection On Agricultural VehiclesIntroduction Over the years agricultural vehicles become increasingly automated with trajectory row tracking and master-slave vehicle configurations, and autoguided vehicles. Safety is an important aspect. Auto guided vehicles exist in industry, where the surroundings are semistructured and flat. Sopme cars have collision sensors. But in agriculture the ground is not flat. The vehicles are meant to be driven into crops, and there are certain paths... K. Nielsen, M.R. Nielsen |
6. Precision Nutrient Management Through Drip Irrigation in Aerobic RiceA field experiment was conducted during kharif 2015 to asses the spatial variability and precision nutrient management through drip irrigation in aerobic rice at ZARS, GKVK, Bangalore. The experimental field has been delineated into 48 grids of 4.5 m x 4.5 m using geospatial technology. Soil samples from 0-15 cm depth were collected and analysed. There was spatial variability for available nitrogen (154 to 277 kg ha-1), phosphorous (45 to 152 kg ha-1) and potassium... N. Dr., S. T, M. Giriyappa, H. D.c, B. Patil, D. Prabhudeva, G. Kombali, S. Noorasma, M. Thimmegowda |
7. Changing the Cost of Farming: New Tools for Precision FarmingAccurate prescription maps are essential for effective variable rate fertilizer application. Grid soil sampling has most frequently been used to develop these prescription maps. Past research has indicated several technical and economic limitations associated with this approach. There is a need to keep the number of samples to a minimum while still allowing a reasonable level of map quality. As can be seen, precision agriculture management... P. Nagel, K. Fleming |
8. You Can Not Manage What You Dont MeasureThe problem of variability in soil nutrient analysis has been studied for years by a number of industry experts; unable to decipher and commercialize hyperspectral soil sensing. Many studies have taken years of testing to account for variability thathas a dramatic impacts on precision of recommendations. The main tradeoff we have identified is between accuracy and precision. Large quantities of raw data are required... K. Fleming, N. Schottle, P. Nagel, G. Koch |
9. Impacts of Interpolating Methods on Soil Agri-environmental Phosphorus Maps Under Corn ProductionPhosphorus (P) is an essential nutrient for crops production including corn. However, the excessive P application, tends to P accumulation at the soil surface under crops systems. This may contribute to increase water and groundwater pollution by surface runoff. To prevent this, an agri-environmental P index, (P/Al)M3, was developed in Eastern Canada and USA. This index aims to estimate soil P saturation for accurate P fertilizer recommendations, while integrating agronomical aspects... J. Nze Memiaghe, A.N. Cambouris, N. Ziadi, M. Duchemin, A. Karam |
10. Delineating Management Zones for Optimizing Soil Phosphorus Recommendations Under a No Till Field in Eastern CanadaCorn (Zea mays L.) and soybean (Glycine max L.) represent the most common crop rotation in Eastern Canada. These crops are cultivated using no-tillage (NT) practice to enhance agroecosystem sustainability. However, NT practice can cause several agri-environmental issues related to phosphorus (P) stratification, movement and runoff leading to P eutrophication in waters. Another major challenge is the expensive costs of extensive soil sampling and laboratory tests needed for accurate... J. Nze Memiaghe, A. Cambouris, M. Duchemin, N. Ziadi, A. Karam |