| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
* Centre for Nutritional Modeling, Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario, Canada N1G 2W1
National Centre for Livestock and Environment, Department of Animal Science, University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2
Edgar L. Rhodes Center for ADS, University of Georgia, Athens 30602
1 Corresponding author: bmcbride{at}uoguelph.ca
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONREFERENCES |
|---|
Key Words: dairy cow • subacute ruminal acidosis • ruminal pH • ruminal temperature
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONREFERENCES |
|---|
|
MATERIALS AND METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONREFERENCES |
|---|
. The dietary treatments were fed twice a day at 0700 and 1300 h. The amount of feed was offered to allow a maximum of 5 kg of orts. Feed intake was recorded daily during the treatment period. Diets were formulated to meet or exceed NRC (2001) guidelines for lactating dairy cows and water was offered at all times. Feed samples were collected twice a week. Equal subsamples, from collected feed samples throughout the experiment, were pooled and submitted for analysis at Agri-Food Laboratory, Guelph, Ontario, Canada, for DM, CP, Ca, P, Mg, K, Na, ash, ether extract, lignin, ADF (AOAC, 1996), NDF (Mertens, 2002), soluble CP (Licitra et al., 1996), and starch content (Hall, 2000).
|
Ruminal pH and Ruminal Temperature Recording
Ruminal pH and ruminal temperature were measured continuously and recorded every minute for 4 d during adaptation and treatment weeks using a mobile recording system described by AlZahal et al. (2007b). Two days of continuous ruminal pH recording, 1 d for cow no. 3168 and 1 d for cow no. 3178 on the SARA treatment during d 4, were missing. Briefly, each fistulated cow was equipped with a recording unit consisting of 2 major components: an indwelling pH electrode and a portable data logger. The electrode (PHE-7352-6-PT100, Omega Engineering Inc., Stamford, CT) was heavy-duty and designed for submersible applications. The electrode had the ability to measure both pH and temperature simultaneously. The electrode was attached to a 0.5-kg stainless steel weight that helped keep it within the ventral sac of the rumen. The electrode’s cable was then connected to the data logger (pHTemp101, Monarch Instrument, Amherst, NH) for data acquisition. The data logger weighed 120 g and could hold up to 13,107 measurements per channel (pH and temperature). The source of power was a 9-V lithium battery. The data logger was housed in a plastic waterproof box with an external input port to facilitate data downloading without opening the box. The box was then mounted on the animal’s back using an adjustable belt fastened around the animal’s girth. The data were collected from individual units using a personal digital assistant (Palm Inc., Sunnyvale, CA) equipped with Monarch PDA Software v 1.0 (Monarch Instrument). A desktop computer equipped with Data Recorder Software v 2.0 (Monarch Instrument) was used to calibrate electrodes, synchronize data from different loggers, display graphs, perform analyses (i.e., mean, standard deviation, minimum, and maximum), and transfer data to other programs. Calibration was performed every 4 d of recording using the desktop software. Standard buffer solutions of pH 4.00 and 7.00 (Fisher Scientific, Fairlawn, NJ) were used for pH calibration. Temperature calibration was performed using room temperature (22°C) as the low temperature calibration point, and factory calibration values were unchanged for the high temperature calibration point (100°C). At the end of each calibration, electrodes were tested against a standard buffer and temperature.
pH Curve Inflection Point
The pH curve inflection point (IP) representing the effect of each dietary treatment on ruminal pH was determined as described by AlZahal et al. (2007a). Briefly, daily pH records obtained during wk 2 were examined individually, and only records that contained 
1,200 data points per d were included in the analysis. Amounts of accumulated time (min/d) spent below each pH cut-off point (5.0, 5.2, ...., 7.6) were calculated for each cow in each day. A pH curve was constructed for each day of recording for each animal (y-variate, 0 to 1,440 min/d; x-variate, pH 5 to 7.6; see for example Figure 1). In a previous study, AlZahal et al. (2007a), the logistic equation gave the best fit for pH curves. Therefore, in the current analysis, the logistic equation was fitted to pH curves from each dietary treatment separately using PROC NLMIXED of SAS:
|
 |
where y(x) = time spent below cut-off point x (min/d); x = pH – 5; y0, yf, k (all > 0) are parameters that define the scale and shape of the curve.
The IP(x,y) of the logistic curves were determined for each dietary treatment as follows:
 |
 |
where IP(x) and IP(y) are the x- and y-coordinates of the IP of the logistic curve.
Ruminal pH of a group of animals corresponding to a given dietary treatment can be described empirically by the position of the pH curve, which is indicated by IP(x) of that curve. A drop in ruminal pH means spending greater times below most critical pH cut-off points, which in turn translates into a shift of the pH curve position toward the lower pH ranges and a reduction in IP(x). Because studies in the literature that induced SARA nutritionally used different pH cut-off points to characterize ruminal pH, the aforementioned approach provides a useful tool that utilizes all pH cut-off points and allows comparison across studies.
Statistical Analysis
Data analyses were conducted on measurements collected during treatment week (wk 2) of the experiment only. The nadir of pH and its corresponding temperature reading were determined for each day and cow during that period.
Daily average ruminal pH and temperature data (for example, mean, maximum, and time (min/d) below or above a specific cut-off point) were analyzed using PROC MIXED of SAS (v 9.1; SAS Institute Inc., 2004) with day as a repeated measure. The model initially included the fixed effect of day, but this was not significant and was therefore removed. Analysis on weekly average DMI was conducted using PROC MIXED, and the model included the fixed effect of treatment.
Regression analysis of daily pH nadir against corresponding temperature was performed using PROC MIXED. The model included the fixed effects (slope and intercept) and the random effects (slope and intercept) for the independent variable (temperature). The fixed effects of the model were represented by the average of intercept and slope over all cows. The random effects of the model accounts for the random variation of intercept and slope from cow to cow. However, the random effect of slope was not significant and, thus, was removed from the model. The random effect of the intercept was left in the model whether it was significant or not to account for the experimental design. Also, the model included day as a repeated measurement with first-order auto regressive covariance structure. Adjusted observations (adjusted y values) were calculated for graphing purposes, by addition of regression-predicted values to the residuals (St-Pierre, 2001). Adjusted R2 was calculated using the GLM of SAS. The model included the adjusted observations as the dependent variables. Concordance correlation coefficient (Lin, 1989) was used to assess model precision and accuracy. The first component is the correlation coefficient (r) that measures precision. The second component (Cb) is the bias correction factor that assesses model accuracy. If Cb equals 1, this indicates that no deviation from a line of unity has occurred. The product of both values gives both the precision and accuracy of the model simultaneously. Correlation was performed using PROC CORR of SAS.
|
RESULTS AND DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONREFERENCES |
|---|
). Ruminal pH data obtained during the adaptation period (wk 1) were not presented. Mean and minimum ruminal pH and time below (min/d) pH 5.6, 5.8, and 6.0 were significantly different between treatments. Control cows dropped below pH 5.6 for 60 min/d compared with 412 min/d (6.8 h/d) for SARA cows.
|
). Because IP(y) of a pH curve always occurs at the cut-off point 720 min/d at the y axis (Figure 1), the IP(x) can be interpreted as a 720-min drop per day below pH 5.83 and 6.17 for SARA and control, respectively (Figure 1).
The continuous ruminal pH system (AlZahal et al., 2007b) has the ability to monitor ruminal temperature and ruminal pH, simultaneously using the same electrode. The results showed that ruminal temperature was inversely related to ruminal pH (Figure 2).
|
The relationship between ruminal pH nadir and ruminal temperature recorded at the same time has demonstrated a potential for ruminal temperature to predict ruminal pH minimum as follows (Figure 3):
|
 |
Performance evaluation indicated that the model had high precision and accuracy (r = 0.91, Cb = 0.997, concordance correlation coefficient = 0.91).
Ruminal temperature and ruminal pH were linearly associated within the range 39 to 41°C, but the relationship would be expected to be nonlinear over extreme and extended ranges of temperature and pH. The temperature range 39 to 41°C corresponds to the ruminal pH nadir range of 5 to 5.6 that is critical for detection of SARA. For example, inputting a temperature of 40°C into the equation gives a ruminal pH minimum of 5.3.
On the other hand, low ruminal temperature should not be translated as high ruminal pH due to possible interference of water and diet consumption (Figure 2). Time to nadir was not different between treatments and occurred 12.3 ± 4.0 h after first feeding of the day (0700 h). This time corresponds to the least interference of drinking.
In the field, veterinarians diagnose SARA by collecting rumen fluid (rumenocentesis) at the time when ruminal pH is expected to be the lowest of the day. Nordlund and Garrett (1994) suggested that rumenocentesis should be performed 2 to 4 h after consuming the main grain meal of the day in component-fed herds and 4 to 8 h after feeding in TMR-fed herds. Because continuous ruminal temperature recording is not practical in a field situation, it is proposed a ruminal temperature reading be obtained at the time of nadir as suggested by Nordlund and Garrett (1994) as a noninvasive alternative to rumenocentesis. Drinking bouts should be avoided when ruminal temperature is taken.
The use of ruminal temperature to diagnose SARA in field situations depends on future development of a practical and cost-effective intraruminal wireless telemetry temperature sensing device (see for example Bewley et al., 2007). In conclusion, ruminal temperature can predict a ruminal pH minimum and has the potential to be developed into a noninvasive diagnostic technique to detect SARA in cattle.
Received for publication July 20, 2007. Accepted for publication September 27, 2007.
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  O. AlZahal, M. A. Steele, E. V. Valdes, and B. W. McBride Technical note: The use of a telemetric system to continuously monitor ruminal temperature and to predict ruminal pH in cattle J Dairy Sci, November 1, 2009; 92(11): 5697 - 5701. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. Khafipour, D. O. Krause, and J. C. Plaizier Alfalfa pellet-induced subacute ruminal acidosis in dairy cows increases bacterial endotoxin in the rumen without causing inflammation J Dairy Sci, April 1, 2009; 92(4): 1712 - 1724. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. Kebreab, J. Dijkstra, A. Bannink, and J. France Recent advances in modeling nutrient utilization in ruminants J Anim Sci, April 1, 2009; 87(14_suppl): E111 - E122. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
, n = 12) and SARA (•, n = 10). Solid lines (pH curves) were obtained by fitting the logistic function to pH data. The equations are: for control cows y = 2.7 ± 1.0 x 1,450.0 ± 20.3/[2.7 ± 1.0 + (1,450.0 ± 20.3 – 2.7 ± 1.0) exp (– 5.4 ± 0.3 x)], n = 12, R2 > 0.99, P < 0.0001; and for SARA cows y = 42.4 ± 6.2 x 1,434.2 ± 16.7 / [42.4 ± 6.2 + (1,434.2 ± 6.1 – 42.4 ± 6.2) exp (– 4.2 ± 0.16 x)], n = 10, R2 > 0.99, P < 0.0001. The x- and y-coordinates of the point of inflection (IP) for control (
) and SARA (
) pH curves were indicated by arrows.
