Quantitative Analysis of the Relationship between Ruminal Redox Potential and pH in Dairy Cattle : Influence of Dietary Characteristics

The ruminal redox potential (Eh) can reflect the microbiological activity and dynamics of fermentation in the rumen. It might be an important indicator of rumen fermentation in combination with pH. However, the ruminal Eh has been rarely studied in dairy cows due to the difficulty of its measurement, and the relationship between ruminal Eh and pH is not clear. The objective of this study was to investigate the relationship between ruminal Eh and pH of dairy cows by meta-analysis of systematic measurements from different experiments. A database was constructed from 22 experiments on cannulated dairy cattle including 57 dietary treatments. The ruminal pH and Eh were measured without air contact between 0 and 8 h post-feeding. The results demonstrated a quadratic correlation between ruminal Eh and pH with a reliable withinanimal variation (Eh = −1697 + 540.7 pH −47.7 pH2, nobservation = 70, nanimal = 26, P < 0.001, RMSE = 56, AIC = 597). The dietary characteristics (NDF, NDFf, OM, starch, degradable starch, soluble sugars contents, and the dietary ionic balance) influencing the ruminal pH also affected the ruminal Eh, but not always to the same extent. Some of them still influenced the relationship between ruminal Eh and pH. While the mechanism of the interaction between ruminal Eh and pH remains to be elucidated, it would be interesting to associate Eh to microbial profile, ruminal VFA concentration and milk production performance in future studies. How to cite this paper: Huang, Y.Y., Marden, J.P., Benchaar, C., Julien, C., Auclair, E. and Bayourthe, C. (2017) Quantitative Analysis of the Relationship between Ruminal Redox Potential and pH in Dairy Cattle: Influence of Dietary Characteristics. Agricultural Sciences, 8, 616-630. https://doi.org/10.4236/as.2017.87047 Received: June 8, 2017 Accepted: July 22, 2017 Published: July 25, 2017 Copyright © 2017 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access


Introduction
Oxidation-reduction conditions are classically assessed by measuring the redox potential (E h ), also called oxidation-reduction potential (usually named ORP) expressed in millivolts (mV).It measures the ability of a solution to accept or donate electrons and corresponds to the potential difference between a platinum electrode and a standard hydrogen electrode [1].Oxidation-reduction and acidbase reactions are essential for the maintenance of all living organisms.The chemistry of living organisms relies even more on oxidation-reduction reactions than it does on acid-base reactions, which are more focused on proton transfers [1] [2].
The role of E h has been reported in many biological media such as dairy products [3], wine [4] and rumen fluid [5] [6] [7].The ruminal E h can reflect the microbiological activity and dynamics of fermentation in the rumen [8].As a matter of fact, ruminal E h is a mixed potential because of the strong fermentative activity involving numerous oxido-reduction couples.It reflects a weighted average of the potentials contributed by each of the redox couples as mentioned by De Laune and Reddy [9] for soil.The ruminal milieu is anaerobic with an E h markedly negative, reflecting a strong reducing power in absence of oxygen [6].
It has been reported that dry matter intake can cause an increase of E h , and the higher E h also seems to be associated with higher concentrate proportions in the diet and lower ruminal pH [7], which may indicate digestive disorder.Indeed, a low E h seems to be more favorable to the strict anaerobic bacteria such as fibrolytic and lactate utilizing bacteria [10].Therefore, the ruminal E h might be an important indicator of rumen function along with other ruminal variables.Until now, no threshold of ruminal E h value has been proposed to evaluate rumen function.Since the ruminal pH is considered as the most direct indicator of the rumen digestive disorder and has been extensively studied [11] [12], comparing with ruminal pH could be helpful to interpret ruminal E h value.
However, compared to other ruminal parameters, the E h is rarely discussed in dairy cows, and the relationship between ruminal E h and pH is not clear.Indeed, the ruminal E h measurement method is not standardized.Three methods of E h potentiometric measurements have been reported in the literature.The first one consisted of a manual suction-strainer device that pumped out ruminal fluid from a cannulated animal to measure E h on collected hand-samples in contact with atmospheric air, after a stabilization period of 25 to 30 min as recommended by Andrade et al. [13] and adapted by Giger-Reverdin et al. [14].The two others are ex vivo measurements performed on continuously pumped rumen fluid without air contact [6] and in vivo measurements performed conti-nuously by wireless probes inside the rumen as described by Penner et al. [15] and adapted by Qin et al. [16].Considerable difference in ruminal E h values has been reported.The major difference is due to the different reference electrodes used.By definition, E h is the potential difference between a platinum electrode and a standard hydrogen electrode.Some authors [13] [17] who used a reference electrode of calomel or silver chloride did not correct the raw E h data (+199 mV at 39˚C).Also, the accurate ruminal E h measurement requires strict anaerobic conditions which are not always satisfied [6].
For several years, our research team has conducted numerous experiments with simultaneous measurements of ruminal E h and pH of dairy cows fed various diets under anaerobic conditions by ex vivo and in vivo methods.Analysis of these aggregated measurements could provide a better understanding of factors controlling ruminal E h and pH, and might demonstrate a quantifiable relationship between ruminal E h and pH.The objective of this study was to investigate the relationship between ruminal E h and pH of dairy cows by meta-analysis of systematic measurements from different experiments.

Selection of Studies
A database was constructed from 22 experiments with cannulated dairy cattle including 57 dietary treatments (Table 1).As explained above, due to the heterogeneity of the ruminal E h values reported in the literature, associated with time of measurement, anaerobic conditions and electrode used [5]  [21] [22] and unpublished studies [23] [24].Both lactating (12 experiments) and non-lactating cows (10 experiments) were used.Qualitative factors such as physiological status of animals (lactating vs. non-lactating) and site of the experiment (France vs. Canada) were collected.
All animal housing and handling procedures were in accordance with the guidelines for animal research of the French Ministry of Agriculture [25].Cannulation techniques provided for humane treatment of cows, adhering to locally approved procedures, and were similar to those described by Streeter et al. [26].
All animals were housed in individual tie stalls throughout the experiment with free access to water.Each experimental period covered an adaptation period (2 to 3 weeks) to the different dietary treatment and a measurement period (3 days).
The diets were formulated to meet energy and protein requirements, with two equal distributions at 0900 and 1700 h.The composition of the diets (Table 2) varied widely (e.g. the proportion of concentrate ranged from 0 to 63%).Some of the dietary characteristics such as neutral detergent fiber from forages (NDFf), ruminally degradable starch, rumen protein balance (RPB) were estimated by the 1 Nexp = number of experiments; 2 Method 1 = measurements performed with probes on continuously pumped rumen fluid [6]; Method 2 = measurements performed continuously with probes inside the rumen and wireless device [15].
online software "systool.fr"[27] using the equations published in Sauvant and Nozière [28].The influence of dietary ionic balance on acid-base balance of animal has been reported [29] [30] [31], it can be expressed (in mEq/kg of DM) as the dietary cation anion difference (DCAD = Na + K-Cl-S) or electrolytic balance (EB = Na + K − Cl).We also calculated these values according to the INRA tables [32] for all the diets used in the data base.

Measurement of Ruminal E h and pH
A total of 775 kinetics of ruminal E h and pH measurements were gathered together.Each kinetic includes 9 measurements of ruminal pH and E h taken at 1 h intervals from the morning diet distribution to 8 hours after.The average E h and pH of these 9 measurements have been calculated for each kinetic.The measurement of ruminal E h and pH on each animal under each dietary treatment was repeated in three consecutive days during the measurement period.
All E h and pH values were measured under strict anaerobic conditions, by ex vivo (Method 1) [6], or in vivo method (Method 2) [15].In Method 1, rumen fluid was pumped continuously through a rubber tube into a 50-mL-doublewalled thermo controlled vessel outside the rumen, the E h and pH were measured by electrodes dipped in the collected rumen fluid without air contamination.In Method 2, a wireless real-time data logger (Dascor, Escondido, CA, USA) was submersed into the ventral rumen sac via the ruminal cannula after calibration, and the E h and pH were measured by external sensors of the data logger and stored in the memory chip.For both methods, the accuracy E h electrode was checked by measuring the standard solution at 220 mV (Fishier Scientific) before and after each measurement.
Considering both methods used an E h platinum electrode, all records of the potential difference were corrected relative to the standard hydrogen electrode (+199 mV at 39˚C) [33].Moreover, as Huang et al. [34] observed an effect of the method on the E h value, due to the difference of sensors and location of measurements, the E h values measured by Method 2 were corrected (+35.4 mV) to avoid the influence of method effect.

Statistical Analysis
Interpretation of the database was based on a statistical meta-analysis [35] [36].
At each step of the meta-analysis process, graphical observations were made to check the coherence of relationships and to identify obviously abnormal values.
All analyses were performed using the statistical software R version 2.15.1 (R Development Core Team, 2012).

Influence of Dietary Characteristics on E h and pH
The average E h and pH of each dietary treatment were calculated for this analysis.
The experiment effect was considered to be random.The within-experiment correlation was calculated using a mixed model.The general form of the mixed model was: where i = number of studies, j = number of observations, B 0 + B 1 X ij is the fixed effect part of the model and s i + b i X ij + e ij is the random effect part of the model.
The goodness of fit of the model was evaluated using the Akaike Information Criterion (AIC) [37].Because a reliable within-experiment response requires a minimal variation of descriptive variables, only the experiments tested a sufficient range of dietary characteristics (OM > 25 g/kg, starch > 70 g/kg, soluble sugar > 20 g/kg, CP > 18 g/kg, NDF > 80 g/kg, DCAD > 50 mEq/kg, EB > 100 m Eq/kg) were selected for within-experiment analysis.
For each relationship, the number of treatments (n treat ) and of experiments (n exp ) used in the analysis are reported.Treatments with high normalized residuals (<−3 or >+3) were identified and discarded from the model as statistical outliers if they had a high leverage effect based on Hi calculation (Hi > 3× k/n, where k is number of independent variables in the model and n is the number of observations) and Cook distance (Cook > 1) [35].A one-way ANOVA was used to test whether ruminal E h or pH varied according to the qualitative factors such as physiological status and site of the experiment.

Relationship between Ruminal E h and pH
Since the individualized ruminal E h and pH measurements are available, the average E h and pH of each animal in each dietary treatment (3 repetitions) were calculated to take into account the variability within one animal under different dietary treatments.Only the animals (70 observations from 26 animals) presenting a sufficient range of ruminal pH (≥0.2) were selected to this analysis.The within-animal correlation was calculated using a mixed model.The animal effect was considered to be random.The model was: where i = number of animals, j = number of observations, B 0 + B 1 X ij is the fixed effect part of the model and s i + b i X ij + e ij is the random effect part of the model.The influence of co-variables (OM, NDF, NDFf, total starch, degradable starch, CP, soluble sugars, DCAD, EB, and RPB contents in diets) on the relationship between ruminal E h and pH was tested.The first step consisted in highlighting the co-variables influencing the residuals (i.e. the difference between observed E h and predicted E h by the equation).The influence of all co-variableson residuals (observed minus predicted E h ) was tested using the Stepwise procedure.In the second step of the analysis, the significant co-variables were included in the model.

Results
A summary of E h and pH value in the database is given in Table 3.Both E h (ranged from −233.4 to −99.6 mV) and pH (ranged from 5.48 to 6.76) covered a wide range.

Influence of Dietary Characteristics on Ruminal E h and pH
Table 4 reports the relationship between ruminal E h and dietary characteristics.Ruminal E h was positively correlated to OM (P = 0.022), total starch (P = 0.012), degradable starch (P = 0.041), and soluble sugars (P < 0.001) contents, and negatively correlated to total NDF (P = 0.024), NDFf (P = 0.049), DCAD (P < 0.001), and EB (P < 0.001).The ruminal E h was not related to CP (P = 0.713), and RPB (P = 0.209).No experiment tested the effect of intake and only two experiments tested a sufficient range of proportion of concentrate (≥30%), which did not permit the analysis of within-experiment relationship between ruminal E h and these two parameters., P = 0.003, RMSE = 8, AIC = 183).The ruminal E h was significantly affected by physiological status (-188.5 ± 24.0 and -169.1 ± 20.8 mV for non-lactating and lactating cows respectively, P = 0.002), but not affected by the site of experiment (P = 0.353).
No quadratic adjustment was significant for relationship between ruminal pH and dietary characteristics (data not shown).The ruminal pH was significantly affected by physiological status (6.32 ± 0.25 and 5.99 ± 0.17 for non-lactating and lactating cows respectively, P < 0.001), but not affected by the measurement method of E h (P = 0.942), and the site of the experiment (P = 0.950).

Relationship between Ruminal E h and pH
The relationship between ruminal E h and pH is presented in Figure 1.The ruminal E h and pH were negatively correlated.The linear relationship (Equation ( 1)) and quadratic adjustment (Equation ( 2)) were both significant (P < 0.001): ( )

Variables Influencing the Relationship between Ruminal E h and pH
The intake (P < 0.001), soluble sugars contents (P = 0.008), DCAD (P = 0.003) were selected by the Stepwise analysis and significantly influenced the residuals   of Equation ( 2).Once included in Equation ( 2), only the DMI was significant (P = 0.03) and slightly improved the equation:

Discussion
Meta-analyses use scientific methods based on statistics to summarize and quantify knowledge acquired through previously conducted studies [35].Until now, there is alimited number of studies reporting ruminal E h measurements.Unlike a classical empirical modeling of biological responses based on exhaustive data collection from published experimental results, our study used the aggregation of measurements from our experiments in order to ensure the homogeneity of E h values and avoided the considerable influence of measurement method explained previously.Use of such analysis leads to a better understanding of factors that controlling the variables.
The database of present study covered a wide range of ruminal E h and pH values.The range of ruminal E h value in dairy cattle in our database (−233.4 to −99.6 mV) is comparable with that in sheep (−260 to −150 mV) [8] [19], in goat (−190 to −145 mV) [5] and in dairy cow (−241 to −185 mV) [38].Some authors reported much lower ruminal E h values: from −340 to −302 mV in sheep [17] and from −352 to −327 mV in goat [13].It is due to the different reference electrodes used as explained above.The significant effect of physiological status on ruminal E h and pH was expected and could be explained by dietary difference between lactating and non-lactating cows.

Dietary Characteristics Influencing Ruminal E h
The influence of dietary concentrate proportion on ruminal E h observed in previous studies [5] [8] [14] was not confirmed by our analysis due to the limited number of experiments (n = 2) presenting a sufficient range of dietary concentrate proportion.However, the variables associated with slowly or rapidly degradable materials contents (NDF, NDFf, OM, starch, degradable starch and especially soluble sugars, which resulted low RMSE and AIC) showed consistent correlation with ruminal E h .
Few studies investigated the influence of these dietary characteristics on ruminal E h .However, the effect of slowly or rapidly degradable diet on ruminal E h has been reported.Andrade et al. [13] observed a higher ruminal E h for the goats fed rapidly degradable diet (−327 mV) compared to that of goats fed slowly degradable diet (−352 mV).These E h values were lower than ours due to the different reference electrodes used, but the difference of ruminal E h caused by two type of diet was significant (P < 0.001).Our results are in agreement with these observations.
To our knowledge, the effect of dietary ionic balance (DCAD and EB) on ruminal E h has never been reported.According to our results, the DCAD and EB showed consistent correlation with ruminal E h .The quadratic adjustment of the within-experiment relationship resulted slightly higher AIC (187 and 183 for DCAD and EB respectively) but lower RSME (9 and 8 for DCAD and EB respectively).The mechanism of this effect remains unclear.But it is known that E h can affect mineral availability.As demonstrated in soil, E h is a factor that strongly influences the mobility of many elements such as N, P, S, K and Na.Conversely, E h is influenced by the various elements [1].Considering that the effect of dietary ionic balance was not investigated as a determining factor by the experiments in the database, it deserves to be confirmed by a classic experiment with in vivo measurements.

Dietary Characteristics Influencing Ruminal pH
The influence of OM, NDF, NDFf, starch, degradable starch and soluble sugars contents on ruminal pH is well documented.Among these variables, the relationship between NDF and starch content and ruminal pH are frequently studied.The relationship (y = 5.53 + 0.022x) between pH and diet NDF content (% DM) reported by Pitt et al. [39] is close to the relationship obtained in our study.By analyzing results from 23 studies of lactating dairy cows fed pasture, Kolver and de Veth [40] reported a within study equation between ruminal pH and NDF content (% DM) with a numerically lower slope than ours (y = 5.84 + 0.0075x, P = 0.014, n = 100), when taking into account the difference of unit of NDF (g/kg DM in our analysis).Regarding the influence of degradable starch in the rumen (% of intake dry matter) on ruminal pH (dairy and beef cattle), Sauvant and Peyraud [11] reported a similar relationship (y = 6.4 -0.01x) compared to ours.
The DCAD and EB are close (the only difference is that the EB does not consider sulfur ions) and highly correlated [41].Both influence ruminal pH.Their influence on acid-base balance of animal has been described [42].Indeed, Na and K are absorbed from the gastrointestinal tract in exchange for the secretion of a proton, whereas Cl and S are often absorbed in exchange for the secretion of a bicarbonate ion [31] [43].Increasing DCAD in the diet allows the cows to overcome the saturation of the renal mechanisms for saving HCO 3 and contributes to increase blood bicarbonate concentration which could be recycled into the rumen to limit the decrease of ruminal pH.Several studies reported that a shift from negative or null DCAD to highly positive values increases DMI and milk yield [42] [44].A meta-analysis [30] grouping 27 experiments reported positive relationship between EB and blood pH, EB and bicarbonate content in blood, EB and pH of urine.Our results showed clear positive relationship between DCAD or EB and ruminal pH, which is in agreement with the hypothesis of the acid-base balance mechanism in ruminant.The equation between ruminal pH and DCAD obtained by our analysis is consistent with that of Iwaniuk and Erdman [45], obtained by a meta-analysis of 63 published journal articles (y = 6.31 + 0.0003x, P = 0.034, r 2 = 0.19, n = 83).Considering these results, DCAD and EB deserve to be more often measured and taken into account in future studies.

Relationship between Ruminal E h and pH
The results of present study confirmed the negative relationship between ruminal E h and pH reported by previous studies in goats [5] [13] [46].The slope of the linear relationship in our study is similar to that of Giger-Reverdin et al. [46].
The lower average ruminal E h value (−354 ± 22 mV) reported by these authors could be explained by the different measurement methods used as explained previously.By gathering together a large data base of wide range ruminal E h and pH values, we further demonstrated a quadratic correlation Equation (2) between ruminal E h and pH with a reliable within-animal variation of the variable.
Considering that in biological media, such as rumen, many oxidation-reduction reactions involve protons, it is not surprising that ruminal E h and pH are related [1] [13] as is shown by the Nernst's equation [47].
It is noteworthy that the diet characteristics (NDF, NDFf, OM, starch, degradable starch, soluble sugars contents, and the dietary ionic balance) influencing the ruminal pH also affected ruminal E h , but not always in same extent.Indeed, the complex reactions which determine E h are not necessarily the same reactions which determine pH: for example, when rapidly-oxidizable organic matter is added, the E h could be changed without changing pH [48].Also, Friedman et al. [49] highlighted the E h as a key factor in the structuring of anaerobic microbial communities through their experimental system separating E h from pH effect.
In our database, we can observe some high pH values (e.g.pH > 6, without SARA according to the ruminal pH thresholds proposed in the literature) associated with high E h which is unfavorable to activities of fibrolytic and lactate utilizing bacteria, and also some low E h values associated with low pH (Figure 1).Therefore, in some circumstances, the E h could better reflect the fermentation dynamics than pH and vice versa.
The measurement of ruminal pH alone might not be sufficient for diagnosing digestive disorder in some cases.The simultaneous measurement of ruminal E h and pH could be useful to provide complementary information about the rumen fermentation.Nevertheless, no threshold has been proposed to evaluate the rumen digestive disorder.In order to initiate the use of ruminal E h, we could propose a preliminary threshold of ruminal E h > −166 mV (correspond to pH < 6 according to Equation ( 2)) indicating digestive disorder.

Conclusion
By gathering together a large database of uniformly measured ruminal E h and pH under anaerobic conditions, the present study demonstrated a quadratic correlation between ruminal E h and pH.The analysis highlights the influence of dietary characteristics on ruminal E h .Within experiments, a good prediction of ruminal E h could be made using soluble sugars content and the dietary ionic balance.The dietary characteristics (NDF, NDFf, OM, starch, degradable starch, soluble sugars contents, and the dietary ionic balance) influencing the ruminal pH also affected the ruminal E h , but not always in same extent.Some of them still influence the relationship between ruminal E h and pH.The mechanism of the interaction between ruminal E h and pH remains to be elucidated; it would be interesting to associate microbial profile and ruminal VFA concentration and milk production performance in future studies.

Figure 1 .
Figure 1.Relationship between ruminal redox potential (Eh) and pH.Each symbol represents the data from one animal in one experiment.The solid lines represent the linear regression of the data from each animal.The dotted line represents the average within-animal quadratic adjustment of all observations (Eh = -1697 + 540.7 pH -47.7 pH 2 , nobservations = 70, nanimals = 26, P < 0.001, RMSE = 16, AIC = 597, R 2 = 0.77).

Table 1 .
Summarize of 22 experiments in the database.

Table 2 .
Descriptive variables of the diets composition (n = 57) for data set used in the meta-analysis.

Table 3 .
Summary of the redox potential and pH value in the database.

Table 4 .
Relationship between ruminal redox potential and dietary characteristics.

Table 5 .
Relationship between ruminal pH and dietary characteristics.