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Lee, W.S
Long, J
Lacroix, R
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Authors
Weckler, P
Wang, N
Zhai, C
Zhang, L
Luo, B
Long, J
Taylor, R
Gan, H
Lee, W.S
Alchanatis, V
Abd-Elrahman, A
Warner, D
Lacroix, R
Vasseur, E
Lefebvre, D
Fadul-Pacheco, L
Bisson, G
Lacroix, R
Séguin, M
Roy, R
Vasseur, E
Lefebvre, D
Dallago, G.M
Figueiredo, D
Santos, R
Andrade, P
Santschi, D.E
Lacroix, R
Lefebvre, D.M
Topics
Engineering Technologies and Advances
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Farm Animals Health and Welfare Monitoring
Precision Dairy and Livestock Management
Type
Poster
Oral
Year
2016
2018
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1. Evaluation of a Seed-fertilizer Application System Using a Laser Scanner

The system evaluated is a design that combines planter and sprayer technologies to allow clients to plant crops while simultaneously spraying initial fertilizer on or in close proximity to the seed.  The system is an idea Capstan Ag Systems has been pursuing for around 15 years, and has recently been revived in a partnership with Great Plains Manufacturing Company.  Great Plains Manufacturing released the final product under the name AccushotTM at the 2015... P. Weckler, N. Wang, C. Zhai, L. Zhang, B. Luo, J. Long, R. Taylor

2. An Active Thermography Method for Immature Citrus Fruit Detection

Fast and accurate methods of immature citrus fruit detection are critical to building early yield mapping systems. Previously, machine vision methods based on color images were used in many studies for citrus fruit detection. Despite the high resolutions of most color images, problems such as the color similarity between fruit and leaves, and various illumination conditions prevented those studies from achieving high accuracies. This project explored a novel method for immature citrus fruit detection... H. Gan, W.S. Lee, V. Alchanatis, A. Abd-elrahman

3. Detection and Monitoring the Risk Level for Lameness and Lesions in Dairy Herds by Alternative Machine-Learning Algorithms

Machine-learning methods may play an increasing role in the development of precision agriculture tools to provide predictive insights in dairy farming operations and to routinely monitor the status of dairy cows. In the present study, we explored the use of a machine-learning approach to detect and monitor the welfare status of dairy herds in terms of lameness and lesions based on pre-recorded farm-based records. Animal-based measurements such as lameness and lesions are time-consuming, expensive... D. Warner, R. Lacroix, E. Vasseur, D. Lefebvre

4. Usage of Milk Revenue Per Minute of Boxtime to Assess Cows Selection and Farm Profitability in Automatic Milking Systems

The number of farms implementing robotic milking systems, usually referred as automatic milking systems (AMS), is increasing rapidly. AMS efficiency is a priority to achieve high milk production and higher incomes from dairy herds. Recent studies suggested that milkability (i.e., amount of milk produced per total time spent in the AMS [kg milk/ minute of boxtime]) could be used for as a criteria for genetic evaluations. Therefore, an indicator of milkability was developed, which combines economical... L. Fadul-pacheco, G. Bisson, R. Lacroix, M. Séguin, R. Roy, E. Vasseur, D. Lefebvre

5. Relationships Between First Test Day Metrics of First Lactation Cows to Evaluate Transition Period

The objective of this study was to apply principal component analysis (PCA) and multiple correspondence analysis (MCA) on Dairy Herd Improvement (DHI) data of animals on their first lactation to discover the most meaningful set of variables that describe the outcome on the first test day. Data collected over 4 years were obtained from 13 dairy herds located in Québec – Canada. The data set was filtered to contain only information from first test day of animals on their first lactation,... G.M. Dallago, D. Figueiredo, R. Santos, P. Andrade, D.E. Santschi, R. Lacroix, D.M. Lefebvre