Proceedings
Authors
| Filter results17 paper(s) found. |
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1. GNSS Tracking Of Livestock: Towards Variable Fertilizer Strategies For The Grazing IndustryThis study reveals the potential for GPS tracking in the grazing industry. By monitoring the locations and movement of livestock, times of peak grazing activity can be identified and these can in turn produce maps of preferred grazing areas, and by examining residency times provide an indication of spatial variability in grazing pressure. A comparison of grazing preference can be made to similarly inferred camping areas to understand the potential redistribution of nutrients within a paddock.... M.G. Trotter, D.W. Lamb, G.N. Hinch, C.N. Guppy |
2. Matching Nitrogen To Plant Available Water For Malting Barley On Highly Constrained Vertosol SoilCrop yield monitoring, high resolution aerial imagery and electromagnetic induction (EMI) soil sensing are three widely used techniques in precision agriculture (PA). Yield maps provide an indication of the crop’s response to a particular management regime in light of spatially-variable constraints. Aerial imagery provides timely and accurate information about photosynthetically-active biomass during crop growth and EMI indicates spatial variability in soil texture, salinity and/or... B. Sauer, C.N. Guppy, M.G. Trotter, D.W. Lamb, J.A. Delgado |
3. Laboratory Evaluation Of Ion-selective Electrodes For Simultaneous Analysis Of Macronutrients In Hydroponic Solution... H. Kim, , , , K.A. Sudduth |
4. Use of Active Crop Canopy Reflectance Sensor for Nitrogen Sugarcane FertilizationResearches about the use of ground-based canopy reflectance sensors aiming the nitrogen management fertilization on variable-rate over the sugarcane crop have been conducted in São Paulo, Brazil since 2007. Sugarcane response to nitrogen is variable, making difficult the development of models to estimate its demands.... L.R. Amaral, G. Portz, H. Rosa, J. Molin |
5. Vegetation Indices from Active Crop Canopy Sensor and Their Potential Interference Factors on SugarcaneAmong the inputs usually used in the sugarcane production the nitrogen (N) is the most significant. With the use of ground-based canopy sensors to obtain vegetation indexes (VI), it is possible to obtain recommendations of nutrient supply in... L.R. Amaral, J.P. Molin, L. Taubinger |
6. Remote Control System for Greenhouse Environment Using Mobile DevicesProtected crop production facilities such as greenhouse and plant factory have drawn interest and the area is increasing in Korea as well as in other countries in the world. Remote... S. Chung, K. Kim, H. Kim, J. Choi, Y. Zhang, S. Kang, K. han, S. Hur |
7. Transient Water Flow Model in a Soil-Plant System for Subsurface Precision IrrigationThe spatial variability of plant-water characteristic in the soil is still unclear. This limits the attempt to model the soil-plant-atmosphere system with this factor. Understanding the non-steady water flow along the soil-plant component is essential to understand their spatial variability.... M.B. Zainal abidin, S. Shibusawa, M. Ohaba, Q. Li, M. Kodaira, M.B. Khalid |
8. Water Distribution Response in a Soil-Root System for Subsurface Precision IrrigationA subsurface capillary irrigation system with a water source buried in a soil has been developed for precision irrigation. This system has advantages in the efficient irrigation to save much water and the real time measurement of evapotranspiration of plants. Creating this new subsurface capillary... S. Shibusawa, M. Ohaba, M.B. Zainal abidin, M. Kodaira, Q. Li |
9. Determination of Sensor Locations for Monitoring of Soil Water Content in GreenhouseMonitoring and control of environmental condition is highly important for optimum control of the conditions, especially in greenhouse and plant factor, and the condition... S. Chung, Y. Huh, J. Choi, D. Ryu, K. Kim, H. Kim, H. Kim |
10. Optimum Sugarcane Growth Stage for Canopy Reflectance Sensor to Predict Biomass and Nitrogen UptakeThe recent technology of plant canopy reflectance sensors can provide the status of biomass and nitrogen nutrition of sugarcane spatially and in real time, but it is necessary to know the right moment to use this technology aiming the best predictions of the crop parameters... L.R. Amaral, J.P. Molin, J. Jasper, G. Portz |
11. Precision Nutrient Management System Based on Ion and Crop Growth SensingAutomated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs)... W. Cho, D. Kim, C. Kang, H. Kim, J. Son, S. Chung, J. Jiang, H. Yun |
12. Soil Attributes Estimation Based on Diffuse Reflectance Spectroscopy and Topographic VariabilityThe local management of crop areas, which is the basic concept of precision agriculture, is essential for increasing crop yield. In this context, diffuse reflectance spectroscopy (DRS) and digital elevation modelling (DEM) appears as an important technique for determining soil properties, on an adequate scale to agricultural management, enabling faster and less costly evaluations in soil studies. The objective of this work was to evaluate the use of DRS together with topographic parameters for... J.V. fontenelli, L.R. Amaral, J.M. Demattê, P.G. Magalhães, G. Sanches |
13. Apparent Electrical Conductivity Sensors and Their Relationship with Soil Properties in Sugarcane FieldsOne important tool within the technological precision agriculture (PA) package are the apparent electrical conductivity (ECa) sensors. This kind of sensor shows the ability in mapping soil physicochemical variability quickly, with high resolution and at low cost. However, the adoption of this technology in Brazil is not usual, particularly on sugarcane fields. A major issue for farmers is the applicability of ECa, how to convert ECa data in knowledge that may assist the producer in decision-making... G.M. Sanches, L.R. Amaral, T. Pitrat, T. Brasco, P.S. Magalhaes, D.G. Duft, H.C. Franco |
14. Optimized Soil Sampling Location in Management Zones Based on Apparent Electrical Conductivity and Landscape AttributesOne of the limiting factors to characterize the soil spatial variability is the need for a dense soil sampling, which prevents the mapping due to the high demand of time and costs. A technique that minimizes the number of samples needed is the use of maps that have prior information on the spatial variability of the soil, allowing the identification of representative sampling points in the field. Management Zones (MZs), a sub-area delineated in the field, where there is relative homogeneity in... G.K. Michelon, G.M. Sanches, I.Q. Valente, C.L. Bazzi, P.L. De menezes, L.R. Amaral, P.G. Magalhaes |
15. Strawberry Pest Detection Using Deep Learning and Automatic Imaging SystemStrawberry growers need to monitor pests to determine the options for pest management to reduce damage to yield and quality. However, manually counting strawberry pests using a hand lens is time-consuming and biased by the observer. Therefore, an automated rapid pest scouting method in the strawberry field can save time and improve counting consistency. This study utilized six cameras to take images of the strawberry leaf. Due to the relatively small size of the strawberry pest, six cameras... C. Zhou, W. Lee, A. Pourreza, J.K. Schueller, O.E. Liburd, Y. Ampatzidis, G. Zuniga-ramirez |
16. Minnesota Corn Growers AssociationWith more than 6,500 members, the Minnesota Corn Growers Association is one of the largest grassroots farm organizations in the United States. Working in close partnership with the Minnesota Corn Research & Promotion Council, MCGA identifies and promotes opportunities for Minnesota’s 24,000 corn farmers while building connections with the non-farming public. We accomplish this by investing in third-party research that focuses on water quality and soil health, targeted consumer outreach,... M. Kazula |
17. Optimizing Corn Irrigation Strategies: Insights from NDVI Trends, Soil Moisture Dynamics, and Remote SensingThis comprehensive field experiment systematically examines the impact of varied irrigation rates on corn growth and yield across three treatments: 33%, 67%, and 100% irrigation rates. Utilizing the normalized difference vegetation index (NDVI) as a parameter for vegetation health, distinct patterns emerge throughout key growth stages. The 100% irrigation treatment consistently exhibits superior vegetation health, sustaining higher NDVI values across all stages, while the 33% treatment reveals... J.O. Abon, A. Sharda |