# Ruminal pH sensing for monitoring volatile fatty acid concentrations in response to short-term dietary disruption

## TL;DR

This study explores using ruminal pH to track volatile fatty acid (VFA) concentrations in cows after dietary changes, but finds pH measurements are not reliable predictors of VFA levels.

## Contribution

The study evaluates the feasibility of using pH sensors to monitor VFA concentrations in response to short-term dietary changes in dairy cows.

## Key findings

- Ruminal pH measurements have poor accuracy in predicting VFA concentrations.
- Prediction errors in pH-based VFA estimation are influenced by the forage-to-concentrate ratio in the diet.
- Short-term dietary disruptions significantly affect VFA concentrations but not their molar proportions.

## Abstract

Summary The synthesis of volatile fatty acids (VFA), a primary product of microbial fermentation that provides a crucial source of energy for the animal, is driven primarily by diet characteristics. Exploration of commercially available sensors to estimate ruminal VFA concentrations across diets could drastically change how ration-formulation decisions are made. This study investigated the opportunity to leverage ruminal pH to track VFA concentrations in the rumen in response to short-term dietary disruption. Although significant, pH measurements have poor accuracy in predicting VFA, and prediction errors pattern with dietary forage to concentrate ratio.

Summary The synthesis of volatile fatty acids (VFA), a primary product of microbial fermentation that provides a crucial source of energy for the animal, is driven primarily by diet characteristics. Exploration of commercially available sensors to estimate ruminal VFA concentrations across diets could drastically change how ration-formulation decisions are made. This study investigated the opportunity to leverage ruminal pH to track VFA concentrations in the rumen in response to short-term dietary disruption. Although significant, pH measurements have poor accuracy in predicting VFA, and prediction errors pattern with dietary forage to concentrate ratio.

•Sensor technologies do not currently monitor ruminal VFA concentrations.•pH measurements relate to VFA, but relationships are diet dependent.•pH measurements have poor accuracy in predicting VFA.

Sensor technologies do not currently monitor ruminal VFA concentrations.

pH measurements relate to VFA, but relationships are diet dependent.

pH measurements have poor accuracy in predicting VFA.

The purpose of this study was to investigate the potential of using ruminal pH measurements to track time-series ruminal volatile fatty acid (VFA) concentrations occurring in response to short-term dietary disruption. Four ruminally cannulated dry Holstein dairy cows were individually housed and assigned to 4 treatments in a Latin square design. Treatments differing in forage-to-concentrate (F:C) ratio (100:0 to 55:45) were used because they were expected to result in large differences in VFA concentration, over which the relationships between pH and VFA could be robustly evaluated. Each sampling period lasted 36 h. Animals were removed from pasture and fasted for 24 h, after which time they were fed their treatment ration for 2 h and sampled for rumen fluid hourly for 12 h. Rumen fluid samples were analyzed immediately for pH, frozen, and subsequently analyzed for VFA concentrations using gas chromatography. Animals were returned to pasture for 7 d between sampling periods. To confirm that the short-term dietary disruptions resulted in expected variation in VFA concentrations, mean VFA concentrations during each animal period (n = 16) were analyzed using a linear mixed effects model with fixed (linear and quadratic) effects for F:C ratio and random effects for animal and period. Results indicated significant changes in VFA concentration across F:C ratio, but no significant shifts in VFA molar proportions, perhaps due to the short-term nature of the feeding protocol. To explore opportunity to use pH measurements to explain variability in VFA concentrations in real time across dietary conditions, a linear mixed-effect model was used to link the time-series measurements (n = 207). The VFA concentrations were analyzed with linear mixed effect models using linear and quadratic terms for pH, and random effects for animal and period. These models had poor accuracy, with residual error variance ranging from 21% to 38%, and residuals patterning significantly with F:C ratio. The data suggest that pH may lack reliability for VFA prediction in short-term feeding scenarios differing considerably in F:C ratio.