The application of cluster analysis methods in assessment of daily physical activity of dairy cows milked in the Voluntary Milking System

Abstract A great individual variability of dairy cows and the diversity of conditions of their maintenance make it difficult to unequivocally interpret the animals’ behaviour and, consequently, to assess their welfare objectively. Thus, technical support to cattle breeders seems increasingly important in this respect at the stage of data collection, the analysis of data and assessment of rearing conditions. Therefore, the aim of the project was to examine the possibility of using cluster analysis to assess physical activity of dairy cows milked in the Voluntary Milking System while taking into account environmental conditions. The research included ten Holstein-Friesian cows in June, September, and December of 2015. The data concerning the cows’ physical activity were classified with Ward’s method and the Kohonen’s networks. In general, during individual months, the distribution of cows’ average daily physical activity was similar and its variability small. Nevertheless, over the individual months, the following three groups for this feature were distinguished with the use of the cluster analysis: night-morning, morning before noon, and afternoon-evening. At the same time, it was observed that, in at least a few cases, the division could be associated with such environmental conditions as daytime light length changes, temperature, or relative humidity of the air. Therefore, in our opinion, cluster analysis can be helpful in classifying dairy cows physical activity, thus contribute to an objective assessment of behavioural indicators of their welfare.

[1]  Steven D. Prager,et al.  The dynamics of animal social networks: analytical, conceptual, and theoretical advances , 2014 .

[2]  H. Rulquin,et al.  Effects of lying or standing on mammary blood flow and heart rate of dairy cows , 1992 .

[3]  R. W. Palmer,et al.  Feeding behavior, milking behavior, and milk yields of cows milked in a parlor versus an automatic milking system. , 2003, Journal of dairy science.

[4]  Miloslav Šoch,et al.  EffEct of hIgh tEmpEraturE on mIlk productIon of cows from frEE-stall housIng wIth natural vEntIlatIon , 2009 .

[5]  P R Tozer,et al.  Using activity and milk yield as predictors of fresh cow disorders. , 2004, Journal of dairy science.

[6]  William M. Rand,et al.  Objective Criteria for the Evaluation of Clustering Methods , 1971 .

[7]  Teuvo Kohonen,et al.  Essentials of the self-organizing map , 2013, Neural Networks.

[8]  Mohamed M. Mostafa,et al.  A neuro-computational intelligence analysis of the US retailers' efficiency , 2010, Int. J. Intell. Comput. Cybern..

[9]  Ulrich Brehme,et al.  ALT pedometer-New sensor-aided measurement system for improvement in oestrus detection , 2008 .

[10]  E. Skjerve,et al.  Dairy farmer attitudes and empathy toward animals are associated with animal welfare indicators. , 2010, Journal of dairy science.

[11]  S. Mihina,et al.  Effect of management change on selected welfare parameters of cows , 2013 .

[12]  G. W. Milligan,et al.  Methodology Review: Clustering Methods , 1987 .

[13]  Christoph Menke,et al.  Individual differences in behaviour and in adrenocortical activity in beef-suckler cows , 2003 .

[14]  Shu-Hsien Liao,et al.  Data mining techniques and applications - A decade review from 2000 to 2011 , 2012, Expert Syst. Appl..

[15]  Elisabetta Riva,et al.  ONE YEAR STUDY OF LYING AND STANDING BEHAVIOUR OF DAIRY COWS IN A FRESTALL BARN IN ITALY , 2009 .

[16]  J. Jago,et al.  Validation of a technology for objectively measuring behaviour in dairy cows and its application for oestrous detection , 2007 .

[17]  J. Oprzadek,et al.  Locomotor activity of dairy cows in relation to season and lactation , 2014 .

[18]  Helen Hansen Axelsson,et al.  Breeding for Sustainable Milk Production – from Nucleus Herds to Genomic Data , 2013 .

[19]  Piotr Herbut,et al.  Impact of Barn Orientation on Insolation and Temperature of Stalls Surface , 2016 .

[20]  E. Fredrickson,et al.  An assessment of behavioural syndromes in rangeland-raised beef cattle , 2012 .

[21]  W. Bieda,et al.  Influence of hygrothermal conditions on milk production in a free stall barn during hot weather , 2015 .

[22]  Matti Pastell,et al.  Daily lying time, motion index and step frequency in dairy cows change throughout lactation. , 2017, Research in veterinary science.

[23]  Tadayuki Yanagi Junior,et al.  Frequency of free-stall occupancy by dairy cows , 2015 .

[24]  J M Siegford,et al.  Invited review: The impact of automatic milking systems on dairy cow management, behavior, health, and welfare. , 2012, Journal of dairy science.

[25]  Z. Gil,et al.  Relationship between milk yield of cows and their 24-hour walking activity. , 2011 .

[26]  Z. Gil,et al.  Relationships between milk peRfoRmance and behaviouR of cows undeR loose housing conditions , 2011 .

[27]  Zhen-Ping Lo,et al.  Analysis of the convergence properties of topology preserving neural networks , 1993, IEEE Trans. Neural Networks.

[28]  N. Cook,et al.  Monitoring indices of cow comfort in free-stall-housed dairy herds. , 2005, Journal of dairy science.

[29]  Melody Y. Kiang,et al.  Extending the Kohonen self-organizing map networks for clustering analysis , 2002 .

[30]  Elisabetta Riva,et al.  The lying and standing activity indices of dairy cows in free-stall housing , 2011 .

[31]  Jeffrey Rushen,et al.  Forced versus free traffic in an automated milking system , 2011 .

[32]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[33]  Mac Schwager,et al.  Robust classification of animal tracking data , 2007 .

[34]  J W West,et al.  Effects of heat-stress on production in dairy cattle. , 2003, Journal of dairy science.

[35]  Gary D. Schnitkey,et al.  ECONOMIC LOSSES FROM HEAT STRESS BY US LIVESTOCK INDUSTRIES , 2003 .

[36]  Zahid Anwar,et al.  Data mining techniques and applications — A decade review , 2017, 2017 23rd International Conference on Automation and Computing (ICAC).

[37]  A. H. Ipema,et al.  Dairy cow interactions with an automatic milking system starting with `walk-through' selection , 1999 .

[38]  O. Szenci,et al.  Cardiac autonomic activity has a circadian rhythm in summer but not in winter in non-lactating pregnant dairy cows , 2016, Physiology & Behavior.

[39]  Michael M Schutz,et al.  Influence of milk yield, stage of lactation, and body condition on dairy cattle lying behaviour measured using an automated activity monitoring sensor , 2009, Journal of Dairy Research.

[40]  A Bach,et al.  Forced traffic in automatic milking systems effectively reduces the need to get cows, but alters eating behavior and does not improve milk yield of dairy cattle. , 2009, Journal of dairy science.

[41]  Clive J. C. Phillips,et al.  Interactions between housed dairy cows during feeding, lying, and standing , 2008 .

[42]  Camille Roth,et al.  Natural Scales in Geographical Patterns , 2017, Scientific Reports.

[43]  H. Wiktorsson,et al.  The effects of restricted feed access and social rank on feeding behavior, ruminating and intake for cows managed in automated milking systems , 2007 .

[44]  Greg Bishop-Hurley,et al.  Dynamic cattle behavioural classification using supervised ensemble classifiers , 2015, Comput. Electron. Agric..

[45]  A. H. Ipema,et al.  The effect of two traffic situations on the behavior and performance of cows in an automatic milking system. , 2003, Journal of dairy science.

[46]  Nigel B Cook,et al.  Behavioral needs of the transition cow and considerations for special needs facility design. , 2004, The Veterinary clinics of North America. Food animal practice.