Proceedings
Authors
| Filter results4 paper(s) found. |
|---|
1. Remote Collection of Behavioral and Physiological Data to Detect Lame CowsAuthors of abstract: C. Kamphuis, J. Burke, J. Jago ... J. Jago, J. Burke, C. Kamphuis, B. Dela rue |
2. Two On-Farm Tests to Evaluate In-Line Sensors for Mastitis DetectionTo date, there is no independent and uniformly presented information available regarding detection performance of automated in-line mastitis detection systems. This lack of information makes it hard for farmers or... B. Dela rue, J. Jago, C. Kamphuis |
3. Field Evaluation of Automated Estrus Detection Systems - Meeting Farmers' ExpectationAutomated 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 |
4. Knowledge-based Approach for Weed Detection Using RGB ImageryA workflow was developed to explore the potential use of Phase One RGB for weed mapping in a herbicide efficacy trial in wheat. Images with spatial resolution of 0.8 mm were collected in July 2020 over an area of nearly 2000 square meters (66 plots). The study site was on a research farm at the University of Saskatchewan, Canada. Wheat was seeded on June 29, 2020, at a rate of 75 seeds per square meter with a row spacing of 30.5 cm. The weed species seeded in the trial were kochia, wild oat, wild... T. Ha, K. Aldridge, E. Johnson, S.J. Shirtliffe, S. Ryu |