Cellier, M.; Aigueperse, N.; Shepley, E.; Villetaz-Robichaud, M.; Vasseur, E.
Let’s mo(o)ve cows! Quantifying and optimizing locomotor activity by providing different modalities of exercise access [External] Divers
2022.
Résumé | Liens | BibTeX | Étiquettes: Presentation
@misc{cellier_lets_2022,
title = {Let’s mo(o)ve cows! Quantifying and optimizing locomotor activity by providing different modalities of exercise access},
author = {M. Cellier and N. Aigueperse and E. Shepley and M. Villetaz-Robichaud and E. Vasseur},
url = {https://www.applied-ethology.org/},
year = {2022},
date = {2022-09-01},
urldate = {2022-09-01},
address = {Ohrid, North Macedonia},
abstract = {The intensifi cation of the animal industry is characterized by an increased indoor confi nement, which is criticized as the public sees freedom of movement as one of the most important living conditions for farm animals. One way to assess restricted movement opportunities is to consider the locomotor activity of cows living in systems where movement is more or less restricted, ranging from tie-stall to pasture. This study seeks to evaluate the impact of a management practice aiming to reduce the level of movement restriction imposed to animals housed in such systems, and to promote solutions for on-farm implementation. The objectives of our study were to 1) quantify the locomotor activity of cows housed in a movement-restricted environment when provided opportunity for movement outside the stall with an exercise area (trials 1-6); 2) evaluate which modalities of access to exercise optimize locomotor activity: i. outdoor vs indoor access (trials 1-2), ii. a combination of different durations of outing (1 vs 2h) and sizes of the exercise area (20, 40, 60 and 80m²) (trials 3-4); and 3) investigate activities performed when cows have access to these areas (trials 1-5). A series of six trials involving different exercise modalities were conducted between 2018 and 2021, with between 18 to 30 tie-stall-housed lactating Holstein depending on the trial (n=141 cows overall), as a model for movement-restricted cows. A meta-analysis was conducted on the least square means of daily number of steps for the exercise vs non-exercise treatments, while generalized linear mixed models were utilized to determine the impact on the number of daily steps by the modalities. The activities performed when cows had access to the exercise area were also analysed by descriptive statistics. Providing access to an exercise area for 1h increased daily steps by 53% (304 steps; 95% CI: 215-393; P<0.001), with modalities such as type of access (167 more steps, around 20% outdoor vs indoor; P<0.001), space (146 more steps, around 16% for large vs small area; P<0.001) and duration of the outing (84 more steps, around 9% with 2h vs 1h; P=0.002), playing a role. Apart from locomotor activities, cows also spent 50-65% of their time idle; and engaged in other activities such as exploration (5-20% of time) or social behaviors (5%). Our study highlights that 1h of daily exercise has a major impact on the amount of locomotion performed, while allowing cows to engage a greater range of natural behaviors.},
keywords = {Presentation},
pubstate = {published},
tppubtype = {misc}
}
The intensifi cation of the animal industry is characterized by an increased indoor confi nement, which is criticized as the public sees freedom of movement as one of the most important living conditions for farm animals. One way to assess restricted movement opportunities is to consider the locomotor activity of cows living in systems where movement is more or less restricted, ranging from tie-stall to pasture. This study seeks to evaluate the impact of a management practice aiming to reduce the level of movement restriction imposed to animals housed in such systems, and to promote solutions for on-farm implementation. The objectives of our study were to 1) quantify the locomotor activity of cows housed in a movement-restricted environment when provided opportunity for movement outside the stall with an exercise area (trials 1-6); 2) evaluate which modalities of access to exercise optimize locomotor activity: i. outdoor vs indoor access (trials 1-2), ii. a combination of different durations of outing (1 vs 2h) and sizes of the exercise area (20, 40, 60 and 80m²) (trials 3-4); and 3) investigate activities performed when cows have access to these areas (trials 1-5). A series of six trials involving different exercise modalities were conducted between 2018 and 2021, with between 18 to 30 tie-stall-housed lactating Holstein depending on the trial (n=141 cows overall), as a model for movement-restricted cows. A meta-analysis was conducted on the least square means of daily number of steps for the exercise vs non-exercise treatments, while generalized linear mixed models were utilized to determine the impact on the number of daily steps by the modalities. The activities performed when cows had access to the exercise area were also analysed by descriptive statistics. Providing access to an exercise area for 1h increased daily steps by 53% (304 steps; 95% CI: 215-393; P<0.001), with modalities such as type of access (167 more steps, around 20% outdoor vs indoor; P<0.001), space (146 more steps, around 16% for large vs small area; P<0.001) and duration of the outing (84 more steps, around 9% with 2h vs 1h; P=0.002), playing a role. Apart from locomotor activities, cows also spent 50-65% of their time idle; and engaged in other activities such as exploration (5-20% of time) or social behaviors (5%). Our study highlights that 1h of daily exercise has a major impact on the amount of locomotion performed, while allowing cows to engage a greater range of natural behaviors.
Tonooka, J. M.; Vasseur, E.; Robichaud, M. Villettaz
Graduate Student Literature Review: What is known about the eliminative behaviors of dairy cattle? [External] Article de journal
Dans: Journal of Dairy Science, vol. 105, no 7, p. 6307–6317, 2022, ISSN: 00220302.
Liens | BibTeX | Étiquettes: Article de journal
@article{tonooka_graduate_2022,
title = {Graduate Student Literature Review: What is known about the eliminative behaviors of dairy cattle?},
author = {J. M. Tonooka and E. Vasseur and M. Villettaz Robichaud},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0022030222003113},
doi = {10.3168/jds.2021-20651},
issn = {00220302},
year = {2022},
date = {2022-07-01},
urldate = {2024-06-05},
journal = {Journal of Dairy Science},
volume = {105},
number = {7},
pages = {6307–6317},
keywords = {Article de journal},
pubstate = {published},
tppubtype = {article}
}
Naghashi, Vahid; Diallo, Abdoulaye Banire
A Model for the Prediction of Lifetime Profit Estimate of Dairy Cattle (Student Abstract) [External] Article d'actes
Dans: Proceedings of the AAAI Conference on Artificial Intelligence, p. 13021–13022, 2022.
Résumé | Liens | BibTeX | Étiquettes: Article de conference
@inproceedings{naghashi_model_2022,
title = {A Model for the Prediction of Lifetime Profit Estimate of Dairy Cattle (Student Abstract)},
author = {Vahid Naghashi and Abdoulaye Banire Diallo},
url = {https://ojs.aaai.org/index.php/AAAI/article/view/21647},
doi = {10.1609/aaai.v36i11.21647},
year = {2022},
date = {2022-06-01},
urldate = {2024-10-16},
booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
volume = {36},
pages = {13021–13022},
abstract = {In livestock management, the decision of animal replacement requires an estimation of the lifetime profit of the animal based on multiple factors and operational conditions. In Dairy farms, this can be associated with the profit corresponding to milk production, health condition and herd management costs, which in turn may be a function of other factors including genetics and weather conditions. Estimating the profit of a cow can be expressed as a spatio-temporal problem where knowing the first batch of production (early-profit) can allow to predict the future batch of productions (late-profit).
This problem can be addressed either by a univariate or multivariate time series forecasting. Several approaches have been designed for time series forecasting including Auto-Regressive approaches, Recurrent Neural Network including Long Short Term Memory (LSTM) method and a very deep stack of fully-connected layers. In this paper, we proposed a LSTM based approach coupled with attention and linear layers to better capture the dairy features. We compare the model, with three other architectures including NBEATs, ARIMA, MUMU-RNN using dairy production of 292181 dairy cows. The results highlight the performence of the proposed model of the compared architectures. They also show that a univariate NBEATs could perform better than the multi-variate approach there are compared to. We also highlight that such architecture could allow to predict late-profit with an error less than 3$ per month, opening the way of better resource management in the dairy industry.},
keywords = {Article de conference},
pubstate = {published},
tppubtype = {inproceedings}
}
In livestock management, the decision of animal replacement requires an estimation of the lifetime profit of the animal based on multiple factors and operational conditions. In Dairy farms, this can be associated with the profit corresponding to milk production, health condition and herd management costs, which in turn may be a function of other factors including genetics and weather conditions. Estimating the profit of a cow can be expressed as a spatio-temporal problem where knowing the first batch of production (early-profit) can allow to predict the future batch of productions (late-profit).
This problem can be addressed either by a univariate or multivariate time series forecasting. Several approaches have been designed for time series forecasting including Auto-Regressive approaches, Recurrent Neural Network including Long Short Term Memory (LSTM) method and a very deep stack of fully-connected layers. In this paper, we proposed a LSTM based approach coupled with attention and linear layers to better capture the dairy features. We compare the model, with three other architectures including NBEATs, ARIMA, MUMU-RNN using dairy production of 292181 dairy cows. The results highlight the performence of the proposed model of the compared architectures. They also show that a univariate NBEATs could perform better than the multi-variate approach there are compared to. We also highlight that such architecture could allow to predict late-profit with an error less than 3$ per month, opening the way of better resource management in the dairy industry.
This problem can be addressed either by a univariate or multivariate time series forecasting. Several approaches have been designed for time series forecasting including Auto-Regressive approaches, Recurrent Neural Network including Long Short Term Memory (LSTM) method and a very deep stack of fully-connected layers. In this paper, we proposed a LSTM based approach coupled with attention and linear layers to better capture the dairy features. We compare the model, with three other architectures including NBEATs, ARIMA, MUMU-RNN using dairy production of 292181 dairy cows. The results highlight the performence of the proposed model of the compared architectures. They also show that a univariate NBEATs could perform better than the multi-variate approach there are compared to. We also highlight that such architecture could allow to predict late-profit with an error less than 3$ per month, opening the way of better resource management in the dairy industry.
Dallago, G. M.; Bradtmueller, A.; Boatswain-Jacques, A.; Shepley, E.
Making sense of sensors to focus on cow health and welfare: The case of building machine learning models to evaluate locomotion ability. [External] Présentation
Montreal, 01.05.2022.
Liens | BibTeX | Étiquettes: Presentation
@misc{dallago_making_2022,
title = {Making sense of sensors to focus on cow health and welfare: The case of building machine learning models to evaluate locomotion ability.},
author = {G. M. Dallago and A. Bradtmueller and A. Boatswain-Jacques and E. Shepley},
url = {https://www.icar.org/index.php/icar-meetings-news/montreal-2022-home-page/},
year = {2022},
date = {2022-05-01},
urldate = {2022-05-01},
address = {Montreal},
keywords = {Presentation},
pubstate = {published},
tppubtype = {presentation}
}
Ayat, M.; Bisson, G.; Prince, J.; Fuentes, V.; Warner, D.; Lefebvre, D. M.; Santschi, D. E.; Lacroix, R.
Automated anomaly detection for milk components and diagnostics in dairy herds [External] Article d'actes
Dans: Proceedings ICAR Annual Conference 2022 in Montreal ICAR Technical Series #26, Montreal, 2022.
Liens | BibTeX | Étiquettes: Article de conference
@inproceedings{ayat_automated_2022,
title = {Automated anomaly detection for milk components and diagnostics in dairy herds},
author = {M. Ayat and G. Bisson and J. Prince and V. Fuentes and D. Warner and D. M. Lefebvre and D. E. Santschi and R. Lacroix},
url = {https://www.icar.org/Documents/technical_series/ICAR-Technical-Series-no-26-Montreal/19%20Automated%20anomaly%20detection%20for%20milk%20components.pdf},
year = {2022},
date = {2022-05-01},
booktitle = {Proceedings ICAR Annual Conference 2022 in Montreal ICAR Technical Series #26},
address = {Montreal},
keywords = {Article de conference},
pubstate = {published},
tppubtype = {inproceedings}
}
Fuentes, V.; Martin, T.; Valtchev, P.; Diallo, A. B.; Lacroix, R.; Leduc, M.
DCPO: The dairy cattle performance ontology, a tool for domain modelling and data analytics [External] Article d'actes
Dans: Proceedings ICAR Annual Conference 2022 in Montreal ICAR Technical Series #26.pdf, Montreal, 2022.
Liens | BibTeX | Étiquettes: Article de conference
@inproceedings{fuentes_dcpo_2022,
title = {DCPO: The dairy cattle performance ontology, a tool for domain modelling and data analytics},
author = {V. Fuentes and T. Martin and P. Valtchev and A. B. Diallo and R. Lacroix and M. Leduc},
url = {https://www.icar.org/Documents/technical_series/ICAR-Technical-Series-no-26-Montreal/11%20DCPO%20Dairy%20cattle%20performance%20ontology.pdf},
year = {2022},
date = {2022-05-01},
booktitle = {Proceedings ICAR Annual Conference 2022 in Montreal ICAR Technical Series #26.pdf},
address = {Montreal},
keywords = {Article de conference},
pubstate = {published},
tppubtype = {inproceedings}
}