Authors
| Filter results11 paper(s) found. |
|---|
1. Near Real-time Meter-resolution Airborne Imagery For Precision Agriculture: AerocamPrecision agriculture often relies on high resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require meter-solution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collaboration... X. Zhang, C.R. Streeter, H. Kim, D.R. Olsen |
2. Evaluation Of Different N Management Strategies Using A Tool For Fuzzy Multi Attributive Comparison Of AlternativesApplication of precision agriculture is related with choosing of optimal agrotechnilogy and, in particular, with definition of the best alternative of N management strategy. A potential satisfactory solution of this decision analysis problem could be the uses of multi attribute decision-making analysis based on fuzzy set theory and fuzzy logic (FMADA). This technique provides a means to achieve an optimal decision for real world problems which involve multiple alternatives and criteria... E. Krueger, D. Kurtener, D. Kurtener, R. Khosla |
3. Evaluation Of Yield Maps Using Fuzzy IndicatorsThe ultimate goal of application of yield maps is profitable crop output in many farming systems. Yield maps are the starting point in the precision farming system, and provide the final record indicating the effectiveness of any management changes. Researches on yield mapping shown, that positions and boundaries of zones with different levels of... E. Krueger shvetsova, D. Kurtener, D. Kurtener, H. Torbert |
4. The Effect Of Variable-Rate Fertilizer Nitrogen Decision-Making On Winter WheatPrecision ... J. Guo, L. Chen, X. Wang, R. Zhang, L. Zotarelli |
5. Evaluation Of The Multiplex® Fluorescence Sensor For The Assessment Of Corn Nitrogen StatusThe Multiplex® is a new hand-held optical fluorescence sensor for non-destructive measurement of about 20 parameters descriptive of plant physiological status. The Multiplex is of potential value for in-season assessment of crop nitrogen status, but no evaluation has been released for that matter as of yet. An experiment was therefore conducted which consisted of four nitrogen fertilization treatments with 0, 20, 50... Y. Zhang, N. Tremblay |
6. Estimating Spatial Variation In Annual Pasture YieldYield mapping is an essential tool for precision management of arable crops. Crop yields can be measured once, at harvest, automatically by the harvesting machinery, and be used to inform a wide range of activities. However yield mapping has had minimal adoption by pastoral farmers. Yield mapping is also a potentially valuable tool for precision management of pastures. However it is difficult to practically map yields on pastures, as they... S.J. Dennis, W. Clarke-hill, A. Taylor, R. Dynes, K. O'neill, T. Jowett |
7. Zone Mapping Application for Precision-farming: a Decision Support Tool for Variable Rate ApplicationWe have developed a web-based decision support tool, Zone Mapping Application for Precision Farming (ZoneMAP, http://zonemap.umac.org), which can automatically determine the optimal number of management zones and delineate them using satellite imagery and field survey data provided by users. Application rates, say for fertilizer, can be prescribed for each zone and downloaded in a variety of formats to ensure compatibility with GPS-enabled farming applicators. ZoneMAP is linked to Digital Northern... X. Zhang, C. Helgason, G. Seielstad, L. Shi |
8. Estimating Cotton Water Requirements Using Sentinel-2Crop coefficient (Kc)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management. Spectral modeling of Kc is possible due to the high correlations between Kc and the crop phenologic development and spectral reflectance. In this study, cotton evapotranspiration was measured in the field using several methods, including eddy covariance, surface renewal, and heat pulse. Kc was estimated as the ratio between reference evapotranspiration... O. Rozenstein, N. Haymann, G. Kaplan , J. Tanny |
9. Using Unmanned Aerial Vehicle and Active-Optical Sensor to Monitor Growth Indices and Nitrogen Nutrition of Winter WheatUsing unmanned aerial vehicle (UAV) remote sensing monitoring system can rapidly and cost-effectively provide crop canopy information for growth diagnosis and precision fertilizer regulation. RapidScan CS-45 (Holland, Lincoln, NE, USA) is a portable active-optical sensor designed for timely, non-destructive obtaining plant canopy information without being affected by weather condition. UAV equipped with RapidScan, is of great significant for rapidly monitoring crop growth and nitrogen (N) status.... X. Liu, Q. Cao, Y. Tian, Y. Zhu, Z. Zhang, W. Cao |
10. Evaluation of a Wireless Pulse Oximeter to Measure Arterial Oxygen Saturation and Pulse Rate in Newborn Holstein Friesian CalvesPulse oximetry is a well-established technique in nowadays human and veterinarian medicine. Also in the farm animal sector, it could be a useful tool to detect critical conditions of the oxygen supply and the cardiovascular system of the patient. However, its use in ruminant medicine is still limited to experimental application. The objective of this study was to evaluate the accuracy of a Radius-7 Wearable Pulse Oximeter (Masimo Corporation, Irvine, CA) for monitoring the vital parameters of... P. Kanz, S. Krieger, M. Drillich, M. Iwersen |
11. Using a UAV-Based Active Canopy Sensor to Estimate Rice Nitrogen StatusActive canopy sensors have been widely used in the studies of crop nitrogen (N) estimation as its suitability for different environmental conditions. Unmanned aerial vehicle (UAV) is a low-cost remote sensing platform for its great flexibility compared to traditional ways of remote sensing. UAV-based active canopy sensor is expected to take the advantages of both sides. The objective of this study is to determine whether UAV-based active canopy sensor has potential for monitoring rice N status,... S. Li, Q. Cao, X. Liu, Y. Tian, Y. Zhu |