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Xu, Z
Buschermohle, M.J
Chen, T
Samborski, S.M
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Authors
Zhang, Y
Chen, T
Samborski, S.M
Larson, J.A
Stefanini, M
Lambert, D.M
Yin, X
Boyer, C.N
Varco, J.J
Scharf , P.C
Tubaña, B.S
Dunn, D
Savoy, H.J
Buschermohle, M.J
Tyler, D.D
Zhou, J
Xu, Z
Samborski, S.M
Szatylowicz, J
Gnatowski, T
Leszczyńska, R
Thornton, M
Walsh, O
Zhou, J
Xu, Z
Safranski, T.J
Bromfield, C
Topics
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Spatial Variability in Crop, Soil and Natural Resources
Profitability, Sustainability and Adoption
Farm Animals Health and Welfare Monitoring
On Farm Experimentation with Site-Specific Technologies
Precision Dairy and Livestock Management
Type
Oral
Poster
Year
2014
2016
2022
2024
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Filter results6 paper(s) found.

1. Does Nitrogen Balance Surplus Done At Field Level Help To Assess Environmental Effects Of Variable Nitrogen Application In Winter Wheat?

Increased nitrogen use efficiency (NUE) is important as a specific consideration to decrease negative impacts of nitrogen (N) on the environment and provide better crop quality. Therefore, in many European countries N is used with restrictions due to UE regulations, set to increase NUE. This is particularly important in wheat production because this crop in EU accounts for 48% of cereal production and uses about 25% of total N-fertilizer applied. One of the methods applied to increase NUE... S.M. Samborski

2. Application of Semantic Sensor Web in Agriculture

      In July 2013, heavy rainstorms across the Midwestern region of the US caused many rivers to breach their banks. Residents of Valley Park, a small town along the Meramec River, Missouri, had to decide whether to rely on a newly constructed levee or abandon their homes for higher ground. Although the levee held, many chose the latter option and fled their homes; it was a chaotic situation that might have been avoided through access to better situational knowledge... Y. Zhang, T. Chen

3. Net Returns and Production Use Efficiency for Optical Sensing and Variable Rate Nitrogen Technologies in Cotton Production

This research evaluated the profitability and N use efficiency of real time on-the-go optical sensing measurements (OPM) and variable-rate technologies (VRT) to manage spatial variability in cotton production in the Mississippi River Basin states of Louisiana, Mississippi, Missouri, and Tennessee. Two forms of OPM and VRT and the existing farmer practice (FP) were used to determine N fertilizer rates applied to cotton on farm fields in the four states. Changes in yields and N rates due to OPM... J.A. Larson, M. Stefanini, D.M. Lambert, X. Yin, C.N. Boyer, J.J. Varco, P.C. Scharf , B.S. Tubaña, D. Dunn, H.J. Savoy, M.J. Buschermohle, D.D. Tyler

4. Detect Estrus in Sows Using a Lidar Sensor and Machine Learning

Accurate estrus detection of sows is labor intensive and is crucial to achieve high farrowing rate. This study aims to develop a method to detect accurate estrus time by monitoring the change in vulvar swollenness around estrus using a light detection and ranging (LiDAR) camera. The measurement accuracy of the LiDAR camera was evaluated in laboratory conditions before it was used in monitoring sows in a swine research facility. In this study, twelve multiparous individually housed sows were continuously... J. Zhou, Z. Xu

5. Use of Remotely Measured Potato Canopy Characteristics As Indirect Yield Estimators

Prediction of potato yield before harvest is important for making agronomic and marketing decisions. Active optical sensors (AOS) are rarely used together with other hand-held instruments for monitoring potato growth, including yield prediction. The aim of the research was to determine the relationship between manually and remotely measured potato crop characteristics throughout the growing season and yield in commercial potato fields. Objective was also to identify crop characteristics that most... S.M. Samborski, J. Szatylowicz, T. Gnatowski, R. Leszczyńska, M. Thornton, O. Walsh

6. Automated Sow Estrus Detection Using Machine Vision Technology

Successful artificial insemination for gilts and sows relies on accurate timing that is determined by estrus check. Estrus checks in current farms are manually conducted by skilled breeding technicians using the back pressure test (BPT) method that is labor-intensive and inefficient due to the large animal-to-staff ratio. This study aimed to develop a robotic imaging system powered by artificial intelligence technology to automatically detect estrus status for gilts and sows in a stall-housing... J. Zhou, Z. Xu, T.J. Safranski, C. Bromfield