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Rilevamento automatico degli atteggiamenti posturali e del comportamento di abbeverata nei suini per individuare alterazioni dello stato sanitario

Bibliografia

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2. Hulsen, J. & Scheepens, K. Pig Signals: Look, Think and Act (Roodbont, Zutphen, 2006).

3. Pritchard, G., Dennis, I. & Waddilove, J. Biosecurity: reducing disease risks to pig breeding herds. practice 27, 230–237 (2005).

4. Matthews, S. G., Miller, A. L., Clapp, J., Plötz, T. & Kyriazakis, I. Early detection of health and welfare compromises through automated detection of behavioural changes in pigs. Vet. J. 217, 43–51 (2016).

5. Kyriazakis, I. & Tolkamp, B. J. Disease. In The Encyclopedia of Applied Animal Behaviour and Welfare (ed Mills, D. S.) 176–177 (CAB International, Wallingford, Oxon, 2010).

6. Rostagno, M. H., Eicher, S. D. & Lay, D. C. Jr. Immunological, physiological, and behavioral effects of salmonella enterica carriage and shedding in experimentally infected finishing pigs. Foodborne Pathogens Dis 8, 623–630 (2011).

7. Andersen, H.-L., Dybkjær, L. & Herskin, M. S. Growing pigs’ drinking behaviour: number of visits, duration, water intake and diurnal variation. Animal 8, 1881–1888 (2014).

8. Maselyne, J. et al. Measuring the drinking behaviour of individual pigs housed in group using radio frequency identification (RFID). Animal 10, 1557–1566 (2016).

9. Marcon, M., Brossard, L. & Quiniou, N. Precision feeding based on individual daily body weight of group housed pigs with an automatic feeder developed to allow for restricting feed allowance. Precis. Livest. Farming 15, 592–601 (2015).

10. Matthews, S. G., Miller, A. L., PlÖtz, T. & Kyriazakis, I. Automated tracking to measure behavioural changes in pigs for health and welfare monitoring. Sci. Rep. 7, 17582 (2017).

11. Moen, E. et al. Deep learning for cellular image analysis. Nat. Methods 1–14 (2019).

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13. Alameer, A., Degenaar, P. & Nazarpour, K. Objects and scenes classification with selective use of central and peripheral image content. J. Vis. Commun. Image Represent. 66, 102698 (2020).

14. Kleanthous, N. et al. Machine learning techniques for classification of livestock behavior. In International Conference on Neural Information Processing, 304–315 (Springer, 2018).

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17. Miguel-Pacheco, G. G. et al. Behavioural changes in dairy cows with lameness in an automatic milking system. Appl. Anim. Behav. Sci. 150, 1–8 (2014).

18. Mittek, M. et al. Tracking of group-housed pigs using multi-ellipsoid expectation maximisation. IET Comput. Vis. 12, 121–128 (2017).

19. Sa, J. et al. Fast pig detection with a top-view camera under various illumination conditions. Symmetry 11, 266 (2019).

20. Huang, W., Zhu, W., Ma, C., Guo, Y. & Chen, C. Identification of group-housed pigs based on gabor and local binary pattern features. Biosyst. Eng. 166, 90–100 (2018).

21. Psota, E. T., Mittek, M., Pérez, L. C., Schmidt, T. & Mote, B. Multi-pig part detection and association with a fully-convolutional network. Sensors 19, 852 (2019).

22. Zhuang, X. & Zhang, T. Detection of sick broilers by digital image processing and deep learning. Biosyst. Eng. 179, 106–116 (2019).

23. Yang, Q., Xiao, D. & Lin, S. Feeding behavior recognition for group-housed pigs with the faster r-cnn. Comput. Electron. Agric. 155, 453–460 (2018).

24. Zhang, L., Gray, H., Ye, X., Collins, L. & Allinson, N. Automatic individual pig detection and tracking in pig farms. Sensors 19, 1188 (2019).

25. Seo, J. et al. A YOLO-based separation of touching-pigs for smart pig farm applications. In 21st International Conference on Advanced Communication Technology (ICACT), 395–401 (IEEE, 2019)

 

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Dal web internazionale
08/10/2020

Intossicazione da alcaloidi: materie prime, micotossine e salute della scrofa

Le materie prime sono necessarie per l’alimentazione delle scrofe, poiché forniscono energia, proteine e nutrienti. Tuttavia, spesso nascondono insidie, quali i fattori anti-nutrizionali. Le micotossine sono alcuni di questi e sono estremamente numerose e pericolose per i riproduttori suini. La salute degli animali è la prima a venire in meno in caso di presenza di tali sostanze nel mangime. I ricercatori francesi dell’Università di Tolosa hanno voluto studiare gli effetti di un’intossicazione acuta da alcaloidi in un allevamento industriale.

 
 

Formazione a distanza abbinata a SUMMA

 

 

Formazione Settore Agro-Zootecnico