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A computer vision approach to improving cattle digestive health by the monitoring of faecal samples
- Source :
- Scientific Reports, Vol 10, Iss 1, Pp 1-12 (2020), Scientific Reports
- Publication Year :
- 2020
- Publisher :
- Nature Publishing Group, 2020.
-
Abstract
- The digestive health of cows is one of the primary factors that determine their well-being and productivity. Under- and over-feeding are both commonplace in the beef and dairy industry; leading to welfare issues, negative environmental impacts, and economic losses. Unfortunately, digestive health is difficult for farmers to routinely monitor in large farms due to many factors including the need to transport faecal samples to a laboratory for compositional analysis. This paper describes a novel means for monitoring digestive health via a low-cost and easy to use imaging device based on computer vision. The method involves the rapid capture of multiple visible and near-infrared images of faecal samples. A novel three-dimensional analysis algorithm is then applied to objectively score the condition of the sample based on its geometrical features. While there is no universal ground truth for comparison of results, the order of scores matched a qualitative human prediction very closely. The algorithm is also able to detect the presence of undigested fibres and corn kernels using a deep learning approach. Detection rates for corn and fibre in image regions were of the order 90%. These results indicate the potential to develop this system for on-farm, real time monitoring of the digestive health of individual animals, allowing early intervention to effectively adjust feeding strategy.
- Subjects :
- 0209 industrial biotechnology
Farms
Livestock
Computer science
convolutional neural network
lcsh:Medicine
Dairy industry
Sample (statistics)
02 engineering and technology
Animal Welfare
computer vision
Article
Feces
020901 industrial engineering & automation
Deep Learning
3D imaging
Animal physiology
0202 electrical engineering, electronic engineering, information engineering
Image Processing, Computer-Assisted
Animals
Computer vision
Animal Husbandry
lcsh:Science
Ground truth
Multidisciplinary
Spectroscopy, Near-Infrared
Behavior, Animal
business.industry
Cattle digestive health
lcsh:R
Animal behaviour
Animal Feed
Dairying
Calibration
020201 artificial intelligence & image processing
Cattle
lcsh:Q
Artificial intelligence
business
faecal consistency
Algorithms
Software
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 10
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....c0accb395f53bae8c7ba2734fa5a2bd5