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Short communication: Measuring feed volume and weight by machine vision
- Source :
- Journal of dairy science. 99(1)
- Publication Year :
- 2014
-
Abstract
- Individual dairy cow feed intake is closely related to the health and productive output of each cow, with healthy cows generally eating more feed than unhealthy cows. Incorporating the use of an automated system to monitor feed consumption for each cow may be beneficial for dairy farm management. This study examined the use of an inexpensive 3-dimensional video camera to measure feed volume, from which we derived feed weight. Proof-of-concept testing was conducted to determine the effectiveness and capability of the machine vision feed-scanning system and its possible use in feed intake monitoring. Such systems are ideal because they do not impede the workflow of the farm or interrupt feeding behavior. This is an improvement over existing systems that are labor and cost intensive. Our conducted experiments involve measuring feed volume at known weights, up to 22.68 kg, with the resulting volume and weight values analyzed by means of linear and quadratic least squares t-test regression analysis. The effects of feed positioning in the bin and near-range sensor limitations were also examined. The results showed that an estimation of feed weight from 3-dimensional scan of volume measurements could be made to within 0.5 kg of the physically measured feed weight using a digital scale. Future efforts will focus on extending this work to active bunks with multiple cows eating throughout the day and testing total mixed rations of varied composition.
- Subjects :
- 0301 basic medicine
Feed consumption
Machine vision
computer.software_genre
03 medical and health sciences
Automation
Animal science
Feeding behavior
Genetics
Animals
Dairy farming
Mathematics
Body Weight
0402 animal and dairy science
Regression analysis
04 agricultural and veterinary sciences
Feeding Behavior
040201 dairy & animal science
Animal Feed
Volume measurements
Dairying
030104 developmental biology
Volume (thermodynamics)
Animal Science and Zoology
Cattle
Female
Data mining
computer
Food Science
Subjects
Details
- ISSN :
- 15253198
- Volume :
- 99
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Journal of dairy science
- Accession number :
- edsair.doi.dedup.....0016b3a34a294c205cb59be33d91e8cd