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| Filter results9 paper(s) found. |
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1. Mapping the Leaf Area Index In Vineyard Using a Ground-Based LIDAR ScannerThe leaf area index (LAI) is defined as the one-sided leaf area per unit ground area and is probably the most widely used index to characterize grapevine vigour. However, direct LAI measurement requires the use of destructive leaves sampling methods which are costly and time-consuming and so are other indirect methods. Faced with these techniques, vineyard leaf area can be indirectly estimated using ground-based LIDAR sensors that scan the vines and get information about the geometry and/or structure... J. Arno, I. Del moral, A. Escolà, J. Company, J.A. MartÍnez-casasnovas, J. Masip, R. Sanz, J.R. Rosell |
2. Raven Sponsor Presentation: Slingshot OverviewSlingshot, a suite of products and services centered around high-speed wireless connectivity in the cab ... D. Schwiesow |
3. Production And Conservation Results From A Decade-Long Field-Scale Precision Agriculture SystemResearch is needed that simultaneously evaluates production and conservation outcomes of precision agriculture practices. From over a decade (1993-2003) of yield and soil mapping and water quality assessment, a multi-faceted, “precision agriculture system” (PAS) was developed and initiated in 2004 on a 36-ha field in Central Missouri. The PAS assessment was accomplished by comparing it to the previous decade of conventional corn-soybean... C. Baffaut, K. Sudduth, J. Sadler, R. Kremer, R. Lerch, N. Kitchen, K. Veum |
4. A Novel Hyperspectral Feature Extraction Algorithm Based On Waveform Resolving For Raisin ClassificationNear infrared hyperspectral imaging technology was adopted in the paper to determine the variety of raisins produced in Xinjiang Uygur Autonomous Region, China. There are 2 varieties of raisins taking part in the research and the wavelengths of the hyperspectral images are from 900nm to 1700nm. A novel waveform resolving method was proposed in the paper to reduce the hyperspectral data and extract features. The waveform resolving method compresses the original hyperspectral data for one pixel... Y. Zhao, X. Xu, Y. Shao, Y. He, Q. Li |
5. In-season Diagnosis of Rice Nitrogen Status Using Crop Circle Active Canopy Sensor and UAV Remote SensingActive crop canopy sensors have been used to non-destructively estimate nitrogen (N) nutrition index (NNI) for in-season site-specific N management. However, it is time-consuming and challenging to carry the hand-held active crop sensors and walk across large paddy fields. Unmanned aerial vehicle (UAV)-based remote sensing is a promising approach to overcoming the limitations of proximal sensing. The objective of this study was to combine unmanned aerial vehicle (UAV)-based remote sensing system... J. Lu, Y. Miao, Y. Huang, W. Shi |
6. Sensor-based Nitrogen Applications Out-performed Producer-chosen Rates for Corn in On-farm DemonstrationsOptimal nitrogen fertilizer rate for corn can vary substantially within and among fields. Current N management practices do not address this variability. Crop reflectance sensors offer the potential to diagnose crop N need and control N application rates at a fine spatial scale. Our objective was to evaluate the performance of sensor-based variable-rate N applications to corn, relative to constant N rates chosen by the producer. Fifty-five replicated on-farm demonstrations... P. Scharf, K. Shannon, K. Sudduth, N. Kitchen |
7. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPTAgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy |
8. Impact of Cover Crop and Soil Apparent Electrical Conductivity on Cotton Development and YieldCotton is one of the major crops in the New Madrid Seismic Zone (NMSZ) of the U.S. Lower Mississippi River Valley region. Because cotton production doesn’t leave a lot of crop residue in the field, low soil organic matter levels are common. While the benefits of crop rotation are well known, cotton is often grown year after year in the same fields for economic reasons. Soils in the region are generally quite variable, with areas of very high sand content. Winter cover crops and reduced tillage... E. Vories, K. Veum, K. Sudduth |
9. Supervised Feature Selection and Clustering for Equine Activity RecognitionIn this paper we introduce a novel supervised algorithm for equine activity recognition based on accelerometer data. By combining an approach of calculating a wide variety of time-series features with a supervised feature significance test we can obtain the best suited features using just 5 labeled samples per class and without requiring any expert domain knowledge. By using a simple cluster assignment algorithm with these obtained features, we get a classification algorithm that achieves a mean... T. De waele, D. Peralta, A. Shahid, E. De poorter |