Ruminal fluid pH (RpH) is an important parameter for controlling the rumen functions. The ability to predict the RpH of beef cattle fed a given diet without depending on the invasive techniques for its measurements (i.e., rumen cannula) is important to avoid ruminal acidosis. The objectives of this research were to: (i) identify key variables that have a significant associations with RpH; (ii) collect data points (DB) from in-vivo beef cattle studies to identify suitable predictors of RpH after considering the animal measures and the dietary variables from a wide range of diets that can safely be fed to beef cattle; (iii) evaluate the extant RpH models relevant to the study; and (iv) develop a new statistical models for mean RpH predictions. Therefore, feed additives (i.e., monensin) were excluded from the analysis. Models tested that use physically effective fiber (peNDF) as a dependent variable were Pitt et al. (1996, PIT), Mertens (1997, MER), Fox et al. (2004, FOX), Zebeli et al. (2006, ZB6), and Zebeli et al. (2008, ZB8), and those that use rumen volatile fatty acids (VFAs) were Tamminga and Van Vuuren (1988, TAM), Lescoat and Sauvant (1995, LES), and Allen (1997, ALL). The final database was categorized into DB (1) and (2) that included a total of 232 and 95 treatment means from 65 and 26 peer-reviewed publications, respectively, spanning from the 1969s to 2014. The DB included information on animal characteristics, ration composition, and ruminal fermentation and pH, that has been used for independent evaluation and development of RpH prediction models. The average bodyweight was 437±168 vs.556±114 kg, dry matter intake (DMI) was 8.57±2.62 vs.9.60±2.10 kgd-1, peNDF (% DM) was 20.3±17.0 vs.17.2±14.6, and forage (% DM) was 34.8±36.1 vs.26.9±31.0 for DB (1) and (2), respectively. The cattle used were of various ages (i.e., calves, yearlings, mature) and represented various production systems (i.e., backgrounding, finishing, and zero-grazing). The originality of our work is to provide for the first time effective coefficients that are better adapted to beef cattle production. The external validation remains to be done to confirm the effect of the integration of environmental, nutritional, and microbial factors on the RpH fluctuations, using a resilient data source, because of their vitality in accurately predicting the animal responses.
Table of Contents
1. Introduction
1.1 Changes in the Mean Ruminal pH Profile of Beef Cattle during Acidosis
1.2 Mathematical Modelling in Animal Nutrition
1.2.1 Prediction of the Mean Ruminal pH from Dietary Compositions
1.2.1.1 Mertens, (1986-1997)
1.2.1.2 Cornell Net Carbohydrate Protein System, (1992-2008)
1.2.1.3 Zebeli et al. (2006) and (2008) models
1.2.2 Prediction of the Mean Ruminal pH from Ruminal Fermentation end-products
1.2.2.1 Tamminga and Van Vuuren, (1988)
1.2.2.2 Institut National de la Recherche Agronomique, (1995)
1.2.2.3 Allen, (1997)
2. Materials and Methods
2.1 Database Compilation
2.2 Database Description
2.3 Dietary Compositions and Missing Values
2.4 Ruminal Fermentation Characteristics and Calculations
2.5 Extant Prediction Equations
2.6 Development of new prediction equations
2.7 Models adequacy and evaluation
2.8 Residual analysis
3. Results
3.1. Descriptive Statistics of Literature Data
3.2. Correlation Analyses of Literature Data
3.3. Development of mean Rumen pH prediction models from all of the pH measurements observations
3.4. Development of mean Rumen pH prediction models from continuously measured observations
3.5. Evaluation of extant Rumen pH prediction models
3.5.1 Performance of the tested models against all the different rumen pH measurements.observations
3.5.2 Performance of the tested models against continuously measured rumen pH observations
4. Discussion
4.1. Ruminal pH Prediction from the extant published models
4.2 Use of ruminal fermentation characteristics (VFA) in mean Ruminal pH Prediction
4.3 Use of dietary composition and ruminal variables in mean Ruminal pH Prediction
4.4 Recommended Equations for prediction of mean Rumen pH for beef cattle
4.5 Recommendations for Further Research
5. Conclusion
6. Appendix
6.1. List of Tables
6.2. List of Figures
Objectives and Topics
The primary research objective is to develop accurate statistical models to predict mean ruminal pH (RpH) in beef cattle without relying on invasive measurement techniques. The study addresses the challenge of RpH regulation and its role in preventing sub-acute ruminal acidosis (SARA) by synthesizing data from numerous in-vivo studies to identify key dietary and ruminal predictors.
- Identification of physiological and dietary variables significantly associated with RpH.
- Compilation and meta-analysis of a comprehensive database spanning multiple decades.
- Evaluation and validation of existing RpH prediction models against beef cattle data.
- Development of novel predictive equations using mixed model regression analysis.
- Assessment of prediction accuracy through cross-validation and rigorous statistical criteria.
Excerpt from the Book
1.1 Changes in the Mean Ruminal pH Profile of Beef Cattle during Acidosis
Transition from feeding high-quality pastures to grain-based diets in beef cattle can lead to ACRA and SARA. These incidence may result in a complex intra-ruminal processes (Figure 1; adapted from Schwartzkopf-Genswein et al., 2003). As noted by Nagaraja and Titgemeyer, (2007) for feedlot cattle, the average RpH typically around 5.80 to 6.20 during the feeding cycle. A drop in the RpH below 5.80 (Beauchemin et al., 2001; Moya et al., 2011), 5.60 (Owens et al., 1998; Cooper et al., 1999; Brown et al., 2000; Bevans et al., 2005), or 5.50 (Wierenga et al., 2010; Zhang et al., 2013a) have been used to signify SARA. Most researchers use a drop in RpH below 5.0 (Nocek, 1997), or below 5.20 (Wierenga et al., 2010) as an indication for ACRA. Others have suggested that the ACRA is identified by an increase in ruminal lactate higher than 5 mM (Aschenbach et al., 2010) or higher than 50 mM (Goad et al., 1998; Nagaraja and Titgemeyer, 2007). The lowest mean RpH (nadir) in the feedlot cattle usually varies from 5.0 to 6.50 (Beauchemin et al., 2001; Koenig et al., 2003).
When RpH is maintained above 5.50, equilibrium exists between producers and utilizers of lactic acids (Nocek et al., 1997). In contrast when RpH is less than 5.50, S.bovis multiplies until RpH is less than 4.70, a pH that allows an increase in acid-tolerant Lactobacillus growth (Allison et al., 1978). Both of these bacterial species produce D and L-lactic acid, which is metabolized more rapidly than D-lactate, the RA is due in large part to the accumulation of the latter (Slyter, 1976; Bolton and Pass 1988; Nagaraja and Titgemeyer, 2007; Mills et al., 2014).
Summary of Chapters
1. Introduction: Defines ruminal pH, its importance for rumen health, and the current challenges in predicting it in beef cattle to avoid acidosis.
2. Materials and Methods: Details the compilation of a multi-study database, inclusion criteria, statistical regression methods, and the evaluation criteria used for model validation.
3. Results: Presents descriptive statistics, correlation analyses, and the performance of newly developed prediction equations compared to existing ones.
4. Discussion: Explores the physiological factors influencing RpH, compares the utility of VFA and dietary-based models, and provides recommendations for future research.
5. Conclusion: Summarizes that the new equations are effectively adapted to beef cattle and emphasizes the need for further external validation.
6. Appendix: Provides comprehensive tables detailing data, including list of tables and figures used throughout the research.
Keywords
Beef cattle, Modelling, Meta-Analysis, Prediction, pH, Rumen, Ruminal acidosis, Dietary composition, VFA, peNDF, SARA, Rumen health, Feed intake, Regression analysis.
Frequently Asked Questions
What is the fundamental purpose of this research?
The research aims to create reliable, non-invasive predictive models for mean ruminal pH in beef cattle to help prevent the onset of ruminal acidosis, a metabolic disorder caused by dietary imbalances.
What are the central themes of this work?
The central themes include the physiological mechanisms of ruminal acidification, the impact of dietary composition and intake on rumen fermentation, and the application of mathematical modeling to optimize cattle nutrition.
What is the primary goal or research question?
The primary goal is to determine if ruminal pH can be predicted accurately from dietary and fermentation variables, providing a practical tool for feedlot management.
Which scientific methodology is employed?
The study utilizes a meta-analysis approach, aggregating data from over 60 peer-reviewed publications, followed by mixed-model regression analysis and cross-validation to assess model performance.
What does the main body of the work cover?
It covers the mathematical modeling of rumen function, the collection of a dual-dataset (DB1 and DB2) based on different pH measurement techniques, and the development and testing of new linear and non-linear prediction equations.
Which keywords characterize this work?
Key terms include beef cattle, ruminal acidosis, meta-analysis, predictive modeling, volatile fatty acids (VFAs), and physically effective fiber (peNDF).
How do the new equations differ from previous ones?
The new equations provide, for the first time, effective coefficients specifically adapted to beef cattle production, whereas many previous models were derived primarily from dairy cattle data.
Why are continuous and non-continuous pH measurements separated in the database?
They are separated because the method of measurement (indwelling electrodes vs. periodic sampling) introduces variations in data, necessitating distinct evaluations for model accuracy and bias.
- Arbeit zitieren
- M.Sc. Management of Animal Resources and Sustainable Development in Agriculture Mohamed Sarhan (Autor:in), 2015, Prediction of Ruminal pH for Beef Cattle. A Physiological Modelling Approach, München, GRIN Verlag, https://www.grin.com/document/293688
