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.
Inhaltsverzeichnis (Table of Contents)
- Abstract
- Résumé
- Riassunto
- Abbreviations and acronyms
- 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
- Predicting ruminal pH in beef cattle using mathematical models
- Evaluating the accuracy and performance of existing ruminal pH prediction models
- Developing new prediction models based on dietary compositions and ruminal fermentation characteristics
- Understanding the influence of diet composition and ruminal fermentation on ruminal pH
- Providing insights for optimizing nutritional management practices for beef cattle health and productivity
- Chapter 1: Introduction - This chapter provides an overview of ruminal acidosis in beef cattle, highlighting its significance and the need for effective prediction models. It discusses the use of mathematical models in animal nutrition, particularly for predicting ruminal pH, and reviews existing models based on dietary compositions and fermentation end-products.
- Chapter 2: Materials and Methods - This chapter details the methodology used in the dissertation, outlining the database compilation, description, dietary compositions, and ruminal fermentation characteristics. It further describes the process of developing new prediction equations, evaluating model adequacy, and performing residual analysis.
- Chapter 3: Results - This chapter presents the results of the study, covering descriptive statistics of the literature data, correlation analyses, and the development and evaluation of ruminal pH prediction models using various measurement techniques.
- Chapter 4: Discussion - This chapter analyzes and interprets the results, examining the performance of existing models, the use of ruminal fermentation characteristics and dietary composition in pH prediction, and the recommended equations for predicting mean ruminal pH. It also suggests potential areas for future research.
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This dissertation aims to develop and evaluate prediction models for ruminal pH in beef cattle, focusing on the impact of diet composition and ruminal fermentation characteristics. It explores the use of existing models and the development of new models based on various data sources and measurement techniques. The work contributes to a better understanding of ruminal pH dynamics in beef cattle and provides valuable insights for improving nutritional management strategies to optimize animal health and productivity.Zusammenfassung der Kapitel (Chapter Summaries)
Schlüsselwörter (Keywords)
This work focuses on the crucial areas of animal nutrition, sustainable agriculture, and beef cattle health. Key terms include ruminal pH, prediction models, dietary composition, ruminal fermentation, and acidosis in beef cattle. The study utilizes a comprehensive database, allowing for the development and evaluation of accurate models for predicting ruminal pH in beef cattle, contributing to improved animal health and productivity.- Quote paper
- M.Sc. Management of Animal Resources and Sustainable Development in Agriculture Mohamed Sarhan (Author), 2015, Prediction of Ruminal pH for Beef Cattle. A Physiological Modelling Approach, Munich, GRIN Verlag, https://www.grin.com/document/293688
