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Song, M
Solie, J.B
Schindelbeck, R
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Authors
Moss, J.Q
Bell, G.E
Solie, J.B
Stone, M.L
Martin, D.L
Payton, M.E
Kim, Y
Song, M
Chung , S
Kabir, M.S
Huh, Y
van Es, H
Sela, S
Marjerison, R
Moebiu-Clune, B
Schindelbeck, R
Moebius-Clune, D
Topics
Precision Horticulture
Engineering Technologies and Advances
Decision Support Systems in Precision Agriculture
Type
Poster
Oral
Year
2010
2014
2016
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Filter results3 paper(s) found.

1. Development Of A Precision Sensing Sprayer For The Application Of Nitrogen Fertilizer To Turfgrass

  Normalized difference vegetation index (NDVI) may be very useful for turfgrass managers to measure turf quality and obtain an indirect measurement of turf N status. The objective of this research was to develop a Nitrogen Fertilization Optimization Algorithm (NFOA) for use in a turfgrass variable rate N applicator on bermudagrass [Cynodon dactylon (L.) Pers] fairways and creeping bentgrass (Agrostis stolonifera L.) greens in Oklahoma. Plots (0.9 X 1.5 m)... J.Q. Moss, G.E. Bell, J.B. Solie, M.L. Stone, D.L. Martin, M.E. Payton

2. Performance Evaluation Of Single And Multi-GNSS Receivers In Agricultural Field Conditions

Selection of appropriate receivers and utilization methods of positioning systems are important for better positioning in different applications of precision agriculture. Objective of this research was to evaluate the performance of single and multi-GNSS receivers at stationary and moving conditions in typical Korean agricultural sites such as open field, orchard area, and mountainous area A single-GNSS receiver (Model: R100; Hemisphere GNSS, Scottsdale, AZ, USA) and a multi-GNSS... Y. Kim, M. Song, S. Chung , M.S. Kabir, Y. Huh

3. Comparing Adapt-N to Static N Recommendation Approaches for US Maize Production

Large temporal and spatial variability in soil N availability leads many farmers across the US to over apply N fertilizers in maize (Zea Mays L.) production environments, often resulting in large environmental N losses.  Static N recommendation tools are typically promoted in the US, but new dynamic model-based tools allow for more precise and adaptive N recommendations that account for specific production environments and conditions. This study compares two static N recommendation tools,... H. Van es, S. Sela, R. Marjerison, B. Moebiu-clune, R. Schindelbeck, D. Moebius-clune