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Burke, C.R
Busscher, W.J
Bari, M.A
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Authors
Dela Rue, B.T
Kamphuis, C
Jago, J.G
Burke, C.R
Stone, K
Bauer, P.J
Busscher, W.J
Millen, J.A
Evans, D.E
Strickland, E.E
Bari, M.A
Bakshi, A
Witt, T
Caragea, D
Jagadish, K
Felderhoff, T
Pramanik, S
Choton, J
Topics
Precision Dairy and Livestock Management
Profitability, Sustainability, and Adoption
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2010
2024
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Filter results3 paper(s) found.

1. Field Evaluation of Automated Estrus Detection Systems - Meeting Farmers' Expectation

Automated systems for oestrus detection are commonly marketed as a suitable, or in some cases, a higher performing alternative to visual observation. Farmers, particularly those with larger herds relying on less experienced staff, view the perceived benefits of automated systems as both economic and physical, with expectations of improved oestrus detection efficiency with lower labour input. There is little evidence-based information available on the field performance of these systems to... B.T. Dela rue, C. Kamphuis, J.G. Jago, C.R. Burke

2. Variable-rate Irrigation Management For Peanut Using Irrigator Pro

  Variable-rate irrigation has the potential to save substantial water. These water savings will become more important as urban, industrial, and environmental sectors compete with agriculture for available water. However, methodologies to precision-apply water for maximum agronomic and economic utility are needed.  Information is needed to optimally management variable-rate irrigation systems. In this study, we conducted irrigation experiments on peanut to compare... K. Stone, P.J. Bauer, W.J. Busscher, J.A. Millen, D.E. Evans, E.E. Strickland

3. Deep Learning to Estimate Sorghum Yield with Uncrewed Aerial System Imagery

In the face of growing demand for food, feed, and fuel, plant breeders are challenged to accelerate yield potential through quick and efficient cultivar development. Plant breeders often conduct large-scale trials in multiple locations and years to address these goals. Sorghum breeding, integral to these efforts, requires early, accurate, and scalable harvestable yield predictions, traditionally possible only after harvest, which is time-consuming and laborious. This research harnesses high-throughput... M.A. Bari, A. Bakshi, T. Witt, D. Caragea, K. Jagadish, T. Felderhoff