Proceedings
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| Filter results10 paper(s) found. |
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1. Performance Evaluation Of Off-shelf Range Sensors For In-field Crop Height MeasurementAbstract: In-season plant height is a good predictor of yield potential, which needs to be measured with techniques of high spatial resolution and accuracy. In this study, systematic performance evaluations were conducted on three types of commercial range sensors, an ultrasonic sensor, a laser range finder and a range camera on plant height measurement, under laboratory and field conditions. Results showed that the average errors between the measured heights... N. Wang, Y. Shi, R.K. Taylor |
2. Proper Implementation Of Precision Agricultural Technologies For Conducting On-farm ResearchPrecision agricultural technologies provide farmers, practitioners and researchers the ability to conduct on-farm or field-scale research to refine farm management, improve long term crop production decisions, and implement site-specific management strategies. However, the limitations of these technologies must be understood to draw accurate and meaningful conclusions from such investigations. Therefore, the objective of this paper was to outline the limitations of several... J.P. Fulton, M.J. Darr, R.K. Taylor, T.P. Mcdonald |
3. Maximizing Agriculture Equipment Capacity Using Precision Agriculture TechnologiesGuidance systems are one of the primary Precision Agriculture technologies adopted by US farmers. While most practitioners establish their initial AB lines for fields based on previous management patterns, a potential exists in conducting analyses to establish AB lines or traffic patterns which maximize field capacity. The objective of this study was to... A.M. Poncet, T.P. Mcdonald, G. Pate, B. Tisseyre, J.P. Fulton |
4. I-SALUS: New Web Based Spatial Systems for Simulating Crop Yield and Environmental ImpactSALUS (System Approach to Land Use Sustainability) model is designed to simulate the impact of agronomic management on yield and environmental impact. SALUS model has new approaches and algorithms for simulating soil carbon, nitrogen, phosphorous, tillage, soil water balance and yield components. In the past, the use of the crop model was not easy for general... T. Chou, M. Yeh, J. Chen, B. Basso |
5. Development Of Online Soil Profile Sensor For Variable Depth TillageIntroduction First introduced in the early 1990s, precision agriculture technologies, or site-specific management, were considered by many to be perhaps the most significant development in production agriculture focused on improving farm profitability. The initial focus was on fertility, and treating the variability that we all knew existed from our experiences with soil sampling. However, to a large extent this application still... A.B. Tekin, H. Yalcin |
6. Cotton Field Relations Of Plant Height To Biomass Accumulation And N-Uptake On Conventional And Narrow Row SystemsAlthough studied for decades, cotton field management remains a challenge for growers, especially due to spatial variability of soil conditions and crop growth, which demands the use of variable rate application technology (VRT) for nitrogen and growth regulators to improve yields and quality and/or save inputs. Canopy optical reflectance sensors are being studied as an option to detect infield variability but may have some limitations due to the known effect of signal saturation when used... N. . Vilanova jr., J.P. Molin, C. Portz, L.V. Posada, G. Portz, R.G. Trevisan |
7. Soybean Maturity Stage Estimation with Unmanned Aerial SystemsMany agronomic decisions in soybean production systems revolve around crop maturity. The primary objective of this research was to evaluate the ability of UAS to determine when soybeans have reached maturity stage sufficient for harvest aid application. A producer typically applies harvest aid chemicals when he or she perceives the crop has reached a critical level of maturity (R6.5) based on a subjective assessment. A convention is to apply harvest aids when 65% of soybean pods reach a mature... J.M. Prince czarnecki, L.L. Wasson, J.T. Irby, A.B. Scholtes, S.M. Carver |
8. Using Deep Learning in Yield and Protein Prediction of Winter Wheat Based on Fertilization Prescriptions in Precision AgriculturePrecision Agriculture has been gaining interest due to the significant growth in the fields of engineering and computer science, hence leading to more sophisticated methods and tools to improve agricultural techniques. One approach to Precision Agriculture involves the application of mathematical models and machine learning to fertilization optimization and yield prediction, which is what this research focuses on. Specifically, in this work we report the results of predicting yield and protein... J. Sheppard, A. Peerlinck, B. Maxwell |
9. Generation of Site-specific Nitrogen Response Curves for Winter Wheat Using Deep LearningNitrogen response (N-response) curves are tools used to support farm management decisions. Conventionally, the N-response curve is modeled as an exponential function that aims to identify an important threshold for a given field: the economic optimum point. This is useful to determine the nitrogen rate beyond which there is no actual profit for the farmers. In this work, we show that N-response curves are not only field-specific but also site-specific and, as such, economic optimum points should... G. Morales, J.W. Sheppard, A. Peerlinck, P. Hegedus, B. Maxwell |
10. Optimizing Nitrogen Application to Maximize Yield and Reduce Environmental Impact in Winter Wheat ProductionField-specific fertilizer rate optimization is known to be beneficial for improving farming profit, and profits can be further improved by dividing the field into smaller plots and applying site-specific rates across the field. Finding optimal rates for these plots is often based on data gathered from said plots, which is used to determine a yield response curve, telling us how much fertilizer needs to be applied to maximize yield. In related work, we use a Convolutional Neural Network, known... A. Peerlinck, J. Sheppard, G.L. Morales luna, P. Hegedus, B. Maxwell |