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| Filter results9 paper(s) found. |
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1. Is A Nitrogen-rich Reference Needed For Canopy Sensor-based Corn Nitrogen Applications?The nitrogen (N) supplying capacity of the soil available to support corn (Zea mays L.) production can be highly variable both among and within fields. In recent years, canopy reflectance sensing has been investigated for in-season assessment of crop N health and fertilization. Typically the procedure followed compares the crop in an area known to be non-limiting in N (called a N-rich area) to the crop in areas inadequately fertilized. Measurements from the two areas are used to calculate... N.R. Kitchen, K.S. Suddth, S.T. Drummond |
2. Comparison Of Three Canopy Reflectance Sensors For Variable-rate Nitrogen Application In CornIn recent years, canopy reflectance sensing has been investigated for in-season assessment of crop nitrogen (N) health and subsequent control of N fertilization. The several sensor systems that are now commercially available have design and operational differences. One difference is the sensed wavelengths, although these typically include wavelengths in both the visible and near-infrared ranges. Another difference is orientation – the sensors most commonly used in the US are designed to... K.A. Sudduth, N.R. Kitchen, S.T. Drummond |
3. Assessment Of The Success Of Variable Rate Seeding Based On EMI MapsGood plant establishment is the critical first step in growing a crop. To achieve this, the correct seed rate must be calculate. This is done by assessing the optimum target plant population per m² and then making an estimate of any losses over winter. Losses will depend on the quality of seedbed created which is related to texture, stoniness and compaction of the soil. If there is any variation in these field characteristics then the correct seed... S. Griffin, M. Darr |
4. 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 |
5. A Long-Term Precision Agriculture System Maintains ProfitabilityAfter two decades of availability of grain yield-mapping technology, long-term trends in field-scale profitability for precision agriculture (PA) systems and conservation practices can now be assessed. Field-scale profitability of a conventional or ‘business-as-usual’ system with an annual corn (Zea mays L.)-soybean (Glycine max [L.]) rotation and annual tillage was assessed for 11 years on a 36-ha field in central Missouri during 1993 to 2003. Following this, a ‘precision agriculture... M.A. Yost, N.R. Kitchen, K.A. Sudduth, S.T. Drummond, R.E. Massey |
6. Automated Southern Leaf Blight Severity Grading of Corn Leaves in RGB Field ImageryPlant stress phenotyping research has progressively addressed approaches for stress quantification. Deep learning techniques provide a means to develop objective and automated methods for identifying abiotic and biotic stress experienced in an uncontrolled environment by plants comparable to the traditional visual assessment conducted by an expert rater. This work demonstrates a computational pipeline capable of estimating the disease severity caused by southern corn leaf blight in images of field-grown... C. Ottley, M. Kudenov, P. Balint-kurti, R. Dean, C. Williams |
7. Utilizing Hyperspectral Field Imagery for Accurate Southern Leaf Blight Severity Grading in CornCrop disease detection using traditional scouting and visual inspection approaches can be laborious and time-consuming. Timely detection of disease and its severity over large spatial regions is critical for minimizing significant yield losses. Hyperspectral imagery has been demonstrated as a useful tool for a broad assessment of crop health. The use of spectral bands from hyperspectral data to predict disease severity and progression has been shown to have the capability of enhancing early... G. Vincent, M. Kudenov, P. Balint-kurti, R. Dean, C.M. Williams |
8. A Field Machine for Automated Quantification of Sweet Potato Phenotypic TraitsSweet potato is a globally important food crop, and its breeding is essential for enhancing nutritional value, ensuring food security, and promoting sustainable agriculture. However, the current process of parental selection largely depends on manual visual assessment, which is time-consuming and subject to human bias, thereby limiting both the efficiency and accuracy of breeding programs. In this work, a field machine for automated quantification of sweet potato phenotypic traits was proposed... S. Hsieh |
9. Thermoelectric Infrared Sensor Integrated with SHA AbsorberThis paper details the design of a high-performance thermoelectric infrared (IR) sensor using the UMC 0.18 μm CMOS-MEMS process, targeting the 8–14 μm wavelength for applications like IoT. To enhance performance, the sensor integrates two key innovations: a Sub-Wavelength Hole Array (SHA) absorber and a novel double-layer thermopile structure with 64 pairs of thermocouples. Finite-Difference Time-Domain (FDTD) simulations show the SHA structure achieves an average IR absorptivity of... Z. Dai |