Low rumen pH has deleterious effects for the dairy cow: it can alter feed intake, microbial metabolism and feed digestion and cause diarrhoea and laminitis. Amongst other factors rumen pH is affected by diet and so a way to predict the consequences of different feeding regimes on rumen pH would be beneficial. Mathematical modelling is a helpful tool to model the complexity of the rumen and to predict multiple responses of the rumen environment to different diets. Biopara-Milk is a whole cow model, simulating the digestive system and predicting performance and circadian pH dynamics. Intra-ruminal boluses are capable of measuring pH dynamics in non-fistulated animals. The aim of this study was to compare Biopara-Milk pH predictions against those obtained with rumen pH boluses in lactating dairy cows. Fourteen dairy cows were offered a partial mixed ration diet with concentrate fed to yield. Cows were orally administered an intraruminal bolus in order to measure rumen pH. Model input data included: detailed information on the feed-stuffs (chemical composition and degradation kinetics) and the animals (bodyweight, condition score, lactation potential, milk composition, week of lactation and lactation number, eating behaviour) and were input into Biopara-Milk. Correlation coefficient (r), concordance correlation coefficient (CCC) and the limits of agreement (LoA) method were performed to determine the relationship between the rumen pH flux obtained with the boluses and the predictions from Biopara-Milk. Average pH values per hour were obtained with both methods and r and CCC for the rumen pH data were acceptable (r=0.93, P<0.05 CCC=0.85; n=24,). The LoA showed that disagreements between the two methods were evenly distributed across the range. Estimates obtained with Biopara-Milk were 0.02 (95% C.I.=-0.33 and 0.29) lower than those obtained with the rumen pH boluses. The results showed the capabilities of Biopara-Milk to predict rumen pH dynamics in dairy cows.
Precision livestock farming applications
Making sense of sensors to support farm management
EditorIlan Halachmi
Published: May 2015 Pages: 328
eISBN: 978-90-8686-815-5 | ISBN: 978-90-8686-268-9
Book Type: Edited Collection
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