Short-term liveweight changes of dairy cows measured by stationary and walk-over weighing scales.

Monitoring and detecting individual cows' liveweight (LW) and liveweight change (LWC) are important for estimation of nutritional requirements and health management, and could be useful to measure short-term feed intake, water consumption, defecation, and urination. Walk-over weighing (WOW) systems can facilitate measurements of LW for these purposes, providing automated LW recorded at different times of the day. We conducted a field study to (1) quantify the contribution of feed and water intake, as well as urine and feces excretions, to short-term LWC and (2) determine the feasibility of stationary and WOW scales to detect subtle changes in LW as a result of feed and water intake, urination, and defecation. In this experiment, 10 cows walked through a WOW system and then stood individually on a stationary scale collecting weights at 10 and 3.3 Hz, respectively. Cows were offered 4 kg of feed and 10 kg of water on the stationary scale. For each animal, LW before and after eating and drinking was then calculated using different approaches. Liveweight change was calculated as the difference between the initial and final LW before and after eating and drinking for each statistical measure. The weights of feed intake, water consumption, urination, and defecation were measured and used as predictors of LWC. Urine and feces were collected from individual cows while the cow was on the scale, using a container, and weighed separately. The agreement between LWC measured using either stationary or WOW scales was assessed to determine the sensitivity of the scales to detect subtle changes in LW using the coefficient of determination (R2), Lin's concordance correlation coefficient (CCC), and mean bias. The prediction model showed that most of the regression coefficients were not significantly different from +1.0 for feed and water, or -1.0 for urine and feces. The R2 and CCC values demonstrated a satisfactory agreement between calculated and stationary LWC and values ranged from 0.60 to 0.92 and 0.71 to 0.94, respectively. A moderate agreement was achieved between calculated and automated LWC with R2 and Lin's CCC values of 0.45 to 0.63 and 0.60 to 0.74, respectively. Therefore, results demonstrated that new algorithms and data processing methods need to be continuously explored and improved to obtain accurate measurements of LW to measure changes in LW, especially from WOW scales.

[1]  D. Scott Adjustment of Animal Growth Rate Responses in Repeat MeasurementGrazing Trials , 2011 .

[2]  P. Koerkamp,et al.  Automated body weight prediction of dairy cows using 3-dimensional vision. , 2018, Journal of dairy science.

[3]  Henk Hogeveen,et al.  The body weight of the dairy cow I. Introductory study into body weight changes in dairy cows as a management aid , 1997 .

[4]  Gang Liu,et al.  Research on a Dynamic Algorithm for Cow Weighing Based on an SVM and Empirical Wavelet Transform , 2020, Sensors.

[5]  R. K. Heitshmidt Diurnal Variation in Weight and Rates of Shrink of Range Cows and Calves. , 1982 .

[6]  M. Stevenson,et al.  Automatic recording of daily walkover liveweight of dairy cattle at pasture in the first 100 days in milk. , 2011, Journal of dairy science.

[7]  Luis Orlindo Tedeschi,et al.  Assessment of the adequacy of mathematical models , 2006 .

[8]  M. Allen Physical constraints on voluntary intake of forages by ruminants. , 1996, Journal of animal science.

[9]  Georg Wendl,et al.  Dynamic weighing of dairy cows: using a lumped-parameter model of cow walk , 2004 .

[10]  J. Rushen,et al.  Weight distribution and gait in dairy cattle are affected by milking and late pregnancy. , 2009, Journal of dairy science.

[11]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[12]  P. Penning,et al.  An evaluation of the use of short‐term weight changes in grazing sheep for estimating herbage intake , 1985 .

[13]  Holly Cuthbertson,et al.  Methodology for data processing and analysis techniques of infrared video thermography used to measure cattle temperature in real time , 2019, Comput. Electron. Agric..

[14]  Yael Edan,et al.  Automatic Weighing of Dairy Cows , 1993 .

[16]  N. Friggens,et al.  On-farm estimation of energy balance in dairy cows using only frequent body weight measurements and body condition score. , 2012, Journal of dairy science.

[17]  J. McLean,et al.  The partition of insensible losses of body weight and heat from cattle under various climatic conditions , 1963, The Journal of physiology.

[18]  Yansong Deng,et al.  Portable Dynamic Weighing System of Yak based on BP Neural Network , 2017 .

[19]  K. McLeod,et al.  Relationships of a novel objective chute score and exit velocity with growth performance of receiving cattle. , 2016, Journal of animal science.

[20]  M. Friger,et al.  Analysis of daily body weight of high-producing dairy cows in the first one hundred twenty days of lactation and associations with ovarian inactivity. , 2008, Journal of dairy science.

[21]  E. Maltz The body weight of the dairy cow: III. Use for on-line management of individual cows , 1997 .

[22]  E. González-Garcia,et al.  A mobile and automated walk-over-weighing system for a close and remote monitoring of liveweight in sheep , 2018, Comput. Electron. Agric..

[23]  I Kyriazakis,et al.  Review: Precision nutrition of ruminants: approaches, challenges and potential gains. , 2018, Animal : an international journal of animal bioscience.

[25]  Dragan Cveticanin,et al.  Modelling and simulation of cow locomotion for dynamic weighing in modern dairy farming , 2005 .

[26]  THE INSENSIBLE LOSS IN BODY WEIGHT OF CATTLE ' , 2010 .

[27]  J. Morton,et al.  An automated walk-over weighing system as a tool for measuring liveweight change in lactating dairy cows. , 2013, Journal of dairy science.

[28]  K. Schwartzkopf-Genswein,et al.  Factors affecting body weight loss during commercial long haul transport of cattle in North America. , 2012, Journal of animal science.

[29]  E. Mäntysaari,et al.  Modeling of daily body weights and body weight changes of Nordic Red cows. , 2015, Journal of dairy science.

[30]  R. Almeida,et al.  Analysis of daily body weight of dairy cows in early lactation and associations with productive and reproductive performance , 2015 .

[31]  J. Fike,et al.  Comparison of three techniques for estimating the forage intake of lactating dairy cows on pasture. , 2003, Journal of animal science.

[32]  K. Soder,et al.  REVIEW: The Interaction of Diurnal Grazing Pattern, Ruminal Metabolism, Nutrient Supply, and Management in Cattle , 2008 .

[33]  R van der Tol,et al.  Time Series Analysis of Live Weight as Health Indicator , 2010 .

[34]  M Pastell,et al.  Use of force sensors to detect and analyse lameness in dairy cows , 2008, Veterinary Record.

[35]  M. Chizzotti,et al.  Achieving Body Weight Adjustments for Feeding Status and Pregnant or Non-Pregnant Condition in Beef Cows , 2014, PloS one.

[36]  A. Stott,et al.  Liveweight loss associated with handling and weighing of grazing sheep , 2017 .

[37]  J. Dijkstra,et al.  Intake regulation and grazing behavior of dairy cows under continuous stocking. , 2004, Journal of dairy science.

[38]  L. Lin,et al.  A concordance correlation coefficient to evaluate reproducibility. , 1989, Biometrics.

[39]  J. Rushen,et al.  Measures of weight distribution of dairy cows to detect lameness and the presence of hoof lesions. , 2010, Journal of dairy science.

[40]  Paul L. Greenwood,et al.  Precision of estimating individual feed intake of grazing animals offered low, declining pasture availability1 , 2014 .

[41]  A. Bródy On measuring growth , 1992 .

[42]  Luciano A. González,et al.  Wireless sensor networks to study, monitor and manage cattle in grazing systems , 2014 .