Abdi, H & Williams, LJ 2010 Principal component analysis. Wiley Interdisciplinary Reviews: Computational Statistics 2 433–459
Bareille, N, Beaudeau, F, Billon, S, Robert, A & Faverdin, P 2003 Effects of health disorders on feed intake and milk production in dairy cows. Livestock Production Science 83 53–62
Brandt, M, Haeussermann, A & Hartung, E 2010 Invited review: technical solutions for analysis of milk constituents and abnormal milk. Journal of Dairy Science 93 427–436
Burstyn, I 2004 Principal component analysis is a powerful Instrument in occupational hygiene inquiries. Annals of Occupational Hygiene 48 655–661
Cavero, D, Tölle, KH, Rave, G, Buxadé, C & Krieter, J 2007 Analysing serial data for mastitis detection by means of local regression. Livestock Science 110 101–110
Cavero, D, Tölle, KH, Henze, C, Buxadé, C & Krieter, J 2008 Mastitis detection in dairy cows by application of Neural Networks. Livestock Science 114 280–286
Chagunda, MGG, Friggens, NC, Rasmussen, MD & Larsen, T 2006 A model for detection of individual cow mastitis based on an indicator measured in milk. Journal of Dairy Science 89 2980–2998
Choi, SW, Lee, C, Lee, J-M, Park, JH & Lee, I-B 2005 Fault detection and identification of nonlinear processes based on kernel PCA. Chemometrics and Intelligent Laboratory Systems 75 55–67
de Mol, RM & Woldt, WE 2001 Application of fuzzy logic in automated cow status monitoring. Journal of Dairy Science 84 400–410
de Mol, RM, Kroeze, GH, Achten, JMFH, Maatje, K & Rossing, W 1997 Results of a multivariate approach to automated oestrus and mastitis detection. Livestock Production Science 48 219–227
de Mol, RM, Keen, A, Kroeze, GH & Achten, JMFH 1999 Description of a detection model for oestrus and diseases in dairy cattle based on time series analysis combined with a Kalman filter. Computers and Electronics in Agriculture 22 171–185
Dohoo, I 2001 Setting SCC cutpoints for cow and herd interpretation. In National Mastitis Council 2001-Annual Meeting Proceedings: Somatic Cell Count Symposium (Ed. Ontario Ministry of Agriculture, F.a.R.A., Fergus, Ontario, Canada), Ferguson, Canada
Gonzalez, LA, Tolkamp, BJ, Coffey, MP, Ferret, A & Kyriazakis, I 2008 Changes in feeding behavior as possible indicators for the automatic monitoring of health disorders in dairy cows. Journal of Dairy Science 91 1017–1028
Hogeveen, H, Kamphuis, C, Steeneveld, W & Mollenhorst, H 2010 Sensors and clinical mastitis—the quest for the perfect alert. Sensors 10 7991–8009
Hojsgaard, S & Friggens, NC 2010 Quantifying degree of mastitis from common trends in a panel of indicators for mastitis in dairy cows. Journal of Dairy Science 93 582–592
ISO 2007 Automatic milking systems—requirements and testing. Annex C: Example of methods of evaluating detection systems for milk deemed as abnormal due to blood or to changes in homogeneity. ISO 20966:2007, International Organization for Standardization, Geneva, Switzerland.
Kamphuis, C, Mollenhorst, H, Feelders, A, Pietersma, D & Hogeveen, H 2010 Decision-tree induction to detect clinical mastitis with automatic milking. Computers and Electronics in Agriculture 70 60–68
Kourti, T 2002 Process analysis and abnormal situation detection: from theory to practice. Control Systems Magazine, IEEE 22 10–25
Kourti, T 2006 The Process Analytical Technology initiative and multivariate process analysis, monitoring and control. Analytical and Bioanalytical Chemistry 384 1043–1048
Kourti, T & MacGregor, JF 1995 Process analysis, monitoring and diagnosis, using multivariate projection methods. Chemometrics and Intelligent Laboratory Systems 28 3–21
Kourti, T, Brown, SD, Tauler, R, Walczak, B 2009 4.02—Multivariate statistical process control and process control, using latent variables. In Brown, SD, Tauler, R & Walczak, B, Comprehensive Chemometrics, pp. 21–54. Oxford: Elsevier
Kramer, E, Cavero, D, Stamer, E & Krieter, J 2009 Mastitis and lameness detection in dairy cows by application of Fuzzy Logic. Livestock Science 125 92–96
Lukas, JM, Reneau, JK & Linn, JG 2008 Water intake and dry matter intake changes as a feeding management tool and indicator of health and estrus status in dairy cows. Journal of Dairy Science 91 3385–3394
Lukas, JM, Reneau, JK, Wallace, R, Hawkins, D & Munoz-Zanzi, C 2009 A novel method of analyzing daily milk production and electrical conductivity to predict disease onset. Journal of Dairy Science 92 5964–5976
MacGregor, JF & Kourti, T 1995 Statistical process control of multivariate processes. Control Engineering Practice 3 403–414
MacGregor, JF, Yu, H, García Muñoz, S & Flores-Cerrillo, J 2005 Data-based latent variable methods for process analysis, monitoring and control. Computers and Chemical Engineering 29 1217–1223
Matlab 2010 MathWorks, Release Notes for use with MATLAB® 7.10.0
Miekley, B, Traulsen, I & Krieter, J 2012 Detection of mastitis and lameness in dairy cows using wavelet analysis. Journal of Livestock Science 148 227–236
Milner, P, Page, KL & Hillerton, JE 1997 The effects of early antibiotic treatment following diagnosis of mastitis detected by a change in the electrical conductivity of milk. Journal of Dairy Science 80 859–863
Mollenhorst, H, van der Tol, PPJ & Hogeveen, H 2010 Somatic cell count assessment at the quarter or cow milking level. Journal of Dairy Science 93 3358–3364
Montgomery, DC 2009 Statistical Quality Control: A Modern Introduction. Arizona: John Wiley and Sons, Inc.
Nielen, M, Schukken, YH, Brand, A, Haring, S & Ferwerda-Van Zonneveld, RT 1995 Comparison of analysis techniques for on-line detection of clinical mastitis. Journal of Dairy Science 78 1050–1061
Pastell, ME & Kujala, M 2007 A probabilistic neural network model for lameness detection. Journal of Dairy Science 90 2283–2292
Petersen, HH, Gardner, IA, Rossitto, P, Larsen, HD & Heegard, PMH 2005 Milk amyloid A (MAA) concentration and somatic cell count (SCC) in the diagnosis of bovine mastitis. In Mastitis in Dairy Production: Current Knowledge and Future Solutions. Wageningen, The Netherlands: Wageningen Academic Publishers 473–476
Pyörälä, S 2003 Indicators of inflammation in the diagnosis of mastitis. Veterinary Research 34 565–578
Sloth, KHMN, Friggens, NC, Lovendahl, P, Andersen, PH, Jensen, J & Ingvartsen, KL 2003 Potential for improving description of bovine udder health status by combined analysis of milk parameters. J. Dairy Sci 86 1221–1232
Venkatasubramanian, V, Rengaswamy, R & Kavuri, SN 2003 A review of process fault detection and diagnosis: Part II: qualitative models and search strategies. Computers and Chemical Engineering 27 313–326
Windig, JJ, Calus, MPL, de Jong, G & Veerkamp, RF 2005 The association between somatic cell count patterns and milk production prior to mastitis. Livestock Production Science 96 291–299
Zhang, Y-W, Zhou, H & Qin, SJ 2010 Decentralized fault diagnosis of large-scale processes using multiblock kernel principal component analysis. Acta Automatica Sinica 36 593–597
