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sensors
Article
Inline Reticulorumen pH as an Indicator of Cows
Reproduction and Health Status
Ram ¯
unas Antanaitis 1, *, Vida Juozaitien˙
e2, Dovil˙
e Malašauskien˙
e1and Mindaugas Televiˇcius 1
1Large Animal Clinic, Veterinary Academy, Lithuanian University of Health Sciences, Tilž˙
es str 18,
Kaunas LT44307, Lithuania
; dovile.malasauskiene@lsmuni.lt (D.M.); mindaugas.televicius@lsmuni.lt (M.T.)
2Department of Animal Breeding, Veterinary Academy, Lithuanian University of Health Sciences, Tilž˙
es str
18, Kaunas LT44307, Lithuania; vida.juozaitiene@lsmuni.lt
*Correspondence: ramunas.antanaitis@lsmuni.lt; Tel.: +370-6734-9064
Received: 8 January 2020; Accepted: 11 February 2020; Published: 14 February 2020
Abstract:
Our study hypothesis is that the interline registered pH of the cow reticulum can be used
as an indicator of health and reproductive status. The main objective of this study was to examine
the relationship of pH, using the indicators of the automatic milking system (AMS), with some
parameters of cow blood components. The following four main groups were used to classify cow
health status: 15–30 d postpartum, 1–34 d after insemination, 35 d after insemination (not pregnant),
and 35 d (pregnant). Using the reticulum pH assay, the animals were categorized as
pH <6.22
(5.3%
of cows), pH 6.22–6.42 (42.1% of cows), pH 2.6–6.62 (21.1% of cows), and pH >6.62 (10.5% of cows).
Using milking robots, milk yield, fat protein, lactose level, somatic cell count, and electron conductivity
were registered. Other parameters assessed included the temperature and pH of the contents of
reticulorumens. Assessment of the aforementioned parameters was done using specific smaX-tec
boluses. Blood gas parameters were assessed using a blood gas analyzer (EPOC (Siemens Healthcare
GmbH, Erlangen, Germany). The study findings indicated that pregnant cows have a higher pH
during insemination than that of non-pregnant ones. It was also noted that cows with a low fat/protein
ratio, lactose level, and high SCC had low reticulorumen pH. They also had the lowest blood pH. It
was also noted that, with the increase of reticulorumen pH, there was an increased level of blood
potassium, a high hematocrit, and low sodium and carbon dioxide saturation.
Keywords:
blood gas; reticulorumen; precision livestock farming (PLF); automatic milking system
(AMS)
1. Introduction
The first widely adopted application of precision livestock farming (PLF), years before the term
PLF was introduced, was the individual electronic milk meter [
1
]. The term PLF was coined in
the early 1970s and 1980s. The other most commonly used parameters in PLF include the use of
commercialized behavior based on estrus detection [
2
], rumination tags [
3
], and the use of an online
milk time analyzer [
4
]. The sensors in these applications provide useful data that can be used by farmers
to identify livestock that need special care before health conditions worsen [
5
]. One of the most accurate
data sources used for continuous monitoring of individual livestock health status is the reticuloruminal
pH (RRpH). The advantage of utilizing RRpH is due to its diurnal recording ability. Various scientific
investigations have used continuous measurements of ruminal pH to assess livestock health status [
6
].
The technique entails the use of a memory chip inserted in the livestock’s rumen, and to retrieve
the data, it has to be physically removed or an external cable is used to transmit data to an external unit.
According to Cantor [
7
], the use of reticulorumen temperature is an effective measure to predict
livestock health status, such as via dairy herd water intake. Cantor argues that real-time observations of
Sensors 2020,20, 1022; doi:10.3390/s20041022 www.mdpi.com/journal/sensors
Sensors 2020,20, 1022 2 of 14
reticulorumen pH and temperature in fresh dairy cows are effective in assessing the risk of subclinical
ruminal acidosis (SARA) because they provide an opportunity to evaluate the prophylactic effect of
the treatment strategies applied [7]. Antanaitis [8] argues that some blood parameters and dairy cow
rumination times can be used as indicators to accurately diagnose subclinical acidosis and ketosis.
However, there is limited information on how the two parameters can be used to assess disease,
so future studies should compare data findings using many animals. Over the last few decades,
there has been a dramatic decrease in dairy cow fertility rate due to various preventable causes [
9
].
Reticuloruminal pH data can also be used to predict the reproductive health of livestock [
10
]. Dairy
cows with altered rumen metabolism (that is, low pH) have low fertility rates. Therefore, using
reticuloruminal pH is a great predictor of a dairy cow’s reproductive success. However, more studies
on the role of reticuloruminal pH in determining cow reproductive health are needed [
10
].
Alzahal et al.
assessed the ruminal temperature and pH of dairy cows and their association in predicting dairy cow
nutritional and health status [
11
]. Similar studies conducted by Cooper-Prado et al. reported that
ruminal temperature lowers one day prior to parturition [
12
]. Optimum diet fermentation and fiber
digestion are achieved at a ruminal pH between 6.0 and 6.4. At this pH level, the cellulolytic bacteria
effectively digest fiber, which is inhibited in pH levels below 6.0 [
13
]. Therefore, a decrease in ruminal
pH increases acidity, which in turn increases the temperature of the abomasum [
14
]. Thus, by using
the two parameters, one can predict the health status of a cow.
The two parameters/data are gathered using wireless sensor nodes that are often attached to
the animal. The wireless sensors are then attached to wireless health monitoring systems. Analysis of
the data collected can be used to assess, detect, and prevent numerous livestock diseases. Another
method of collecting data is the use of rumen fluid samples, whereby the samples are collected using
an oral–ruminal probe or rumen fistula. [
15
]. Rumen pH and temperature parameters fluctuate.
However, the collection of rumen fluid samples should be avoided when possible because it causes
distress to the research subjects [
16
]. With technological advancements, new noninvasive technologies,
such as the use of intra-ruminal boluses, have been developed to collect pH and temperature data to
monitor a cow intra-ruminal metabolism. However, there is limited information on how the interline
registered reticulorumen pH can be utilized as an indicator to assess cow health status and reproductive
systems. This study hypothesizes that interline registered reticulorumen pH can accurately predict
cow reproduction and health status. The main objective of this study is to examine the relationship
of reticulorumen pH with indicators and compare the automatic milking system (AMS) and blood
indicators to determine the reproduction and health status of dairy cows.
2. Materials and Methods
2.1. Location and Experimental Design
The experiment was conducted on a dairy cow farm located in the Eastern part of Europe
(54.9587408, 23.784146). About 95 Lithuanian black and white dairy cows that matched the selection
criteria were identified. The inclusion criteria were cows that had two or more lactations. The cows
needed to be identified as clinically healthy, have a temperature of 38.8 degrees Celsius, 5–6 rumen
contractions every three minutes, and no signs and symptoms of laminitis, metritis, or mastitis.
The research subjects were taken to an accommodation with loose-housing system where they were put
on a constant feeding rotation during the entire research period. Nutritional balance was maintained
to ensure that physiological needs were adequately met. The TMR comprised 30% corn silage, 4%
hay grass, 50% grain mash concentrate, and 10% grass silage. This diet was formulated using NRC
2001 guidelines for a 550 kg Holstein cow producing 35 kg/d. The composition ration was as follows:
DM (%)—48.8, NEL (Mcal/kg) 1.6; NDF, ADF, NFC, and CP percentage of DM was 28.2, 19.8, 38.7, and
15.8 respectively. Using this aforementioned mixed ration, the research subjects were fed twice a day at
10:00 h and 20:00 h. Two kilograms per day of concentrate was used to feed the cows at the milking
site. The average BCS used was 3.45 (±0.25).
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2.2. Measurements
SmaX-tec boluses (smaXtec animal care GmbH, Graz, Austria) were used to assess the content
of cow reticulorumen pH and temperature. This device was preferred for this study because of its
ability to display real-time pH and temperature data. Using the instruction manual, boluses were put
into the cows’ reticulorumen. The data were collected using specific antennas on the SmaX-tec device.
The boluses in the cows’ reticulorumens from 2–9 January 2019. Reticuloruminal pH was evaluated
using an indwelling wireless data transmitting system (smaXtec). The entire system was controlled by
a microprocessor. After conversion using an AD converter, the data was stored in an external memory
chip. The device size was small enough to permit oral administration to an adult cow. More so, it was
resistant to rumen fluid. At the beginning of the study, pH probes were calibrated using pH 4 and
pH 7 buffers.
Lely Astronaut
®
A3 milking robots were used to milk the cows. The robots were also used to
register rumination time (RT) (min/d), yield MY (kg/d), bodyweight BW (kg), lactose ration (%), milk
fat/protein ratio (F/P), milk electrical conductivity of all quarters of the udder (front left and right,
EC1 and EC2, respectively; rear left (EC3) and right (EC4), respectively, in mS/cm), and conception of
concentrates. Blood gas samples were obtained and stored in an ice bath until processing. Using Epoc
blood gas analyzers (EPOC, Canada), the following parameters were obtained: base excess in blood
(BE), partial carbon dioxide pressure (PCO2), partial oxygen pressure (PO2), bicarbonate (Chco3),
Hydrogen potential (pH), total carbon dioxide carbon (TCO2), base excess in extracellular fluid (BE ecf),
Sodium (Na), Calcium (C), Potassium (K), hematocrit (HCT), chlorides (cl), hemoglobin concentration
(cHgb), and lactate (Lac).
2.3. Animals and Experimental Condition
The dairy cow reproductive system is classified as follows (Table 1):
Table 1. Creation of experimental groups.
Group Days/Status of Reproduction n %
I 15–30 d. postpartum 35 36.8
II 1–34 d. after insemination 20 21.1
III 35 d. after insemination (non-pregnant) 20 21.1
IV 35 d. after insemination (pregnant) 20 21.1
Total 95 100.0
According to the reticulorumen pH assay, the experimental animals were divided into four classes:
1. pH <6.22 (5.3% of cows), 2. pH 6.22–6.42 (42.1% of cows), 3. pH 6.42–6.62 (21.1% of cows), and
4. pH >6.62 (10.5% of cows). Estrus was identified with specific devices in this study measuring
activity in steps, and rumination time (min/d) (by increasing activity and decreasing rumination time)
was monitored by the herd management program, Lely Astronaut
®
(24/7). The research subject was
considered estrus according to the following parameters: restlessness, type and amount of mucous
discharge, extent of alertness, tail raising, and congestion of the mucous membrane around the vulvar
area. Uterine tone was assessed using rectal palpations. About 12 h after estrus signs were presented,
the research subjects were inseminated using frozen semen. Successful implantation and pregnancies
were confirmed using an Easi-Scan ultrasound device (IMV imaging, Scotland, UK) once around day
30 to 35. The pregnant cows were grouped in a different group from the non-pregnant ones.
2.4. Data Analysis and Statistics
Statistical data analysis was conducted using SPSS 20.0 (SPSS, Inc., Chicago, IL, USA) software.
The data were then presented using descriptive statistics and normal distribution analysis methods,
such as the Kolmogorov–Smirnov test. The statistical relationship between reticulorumen pH and AMS
Sensors 2020,20, 1022 4 of 14
indicators, body weight (BW), activity of cows, milk yield (MY), milk fat/protein ratio (F/P), somatic
cell count in milk (SCC), milk lactose content, and electrical conductivity of all four udder quarters
were shown using Pearson correlations. To effectively analyze SCC variables, they were converted to
SCClog 10. Analysis of the linear relationship between reticulorumen pH and the analyzed AMS was
done using Pearson correlation. Multiple comparisons of groups means were calculated using Tukey’s
test. A probability below 0.05 was considered reliable (p-Value <0.05).
All the data were registered on the investigation day, except for pregnant and non-pregnant cows,
whose data were registered on the insemination day.
3. Results
We determined that the average pH of the reticulorumen was 6.47
±
0.016, temperature of
the reticulorumen was 38.779
±
0.020
◦
C, and rumination time was 455.26
±
6.052. The average milk
productivity of cows was 40.41
±
0.724 kg, BW was 648.37
±
13.265 kg, and the ratio of fat to protein in
milk was 1.17 ±0.013.
3.1. Reticulorumen pH as an Indicator of Reproduction Status of Cows
Analysis of the reticulorumen pH of cows by reproductive status showed the highest average value
of this indicator in Group IV (Figure 1A), which was 2.13% higher compared to Group I, 0.76% higher
compared to Group II, and 1.37% higher compared to Group III. According to multiple comparisons of
means, all differences between the groups of cows by reproductive status were found to be statistically
significant (p<0.05).
Sensors2020,20,xFORPEERREVIEW4of13
StatisticaldataanalysiswasconductedusingSPSS20.0(SPSS,Inc.,Chicago,IL,USA)software.
Thedatawerethenpresentedusingdescriptivestatisticsandnormaldistributionanalysismethods,
suchastheKolmogorov–Smirnovtest.ThestatisticalrelationshipbetweenreticulorumenpHand
AMSindicators,bodyweight(BW),activityofcows,milkyield(MY),milkfat/proteinratio(F/P),
somaticcellcountinmilk(SCC),milklactosecontent,andelectricalconductivityofallfourudder
quarterswereshownusingPearsoncorrelations.ToeffectivelyanalyzeSCCvariables,theywere
convertedtoSCClog10.AnalysisofthelinearrelationshipbetweenreticulorumenpHandthe
analyzedAMSwasdoneusingPearsoncorrelation.Multiplecomparisonsofgroupsmeanswere
calculatedusingTukey’stest.Aprobabilitybelow0.05wasconsideredreliable(p‐Value<0.05).
Allthedatawereregisteredontheinvestigationday,exceptforpregnantandnon‐pregnant
cows,whosedatawereregisteredontheinseminationday.
3.Results
WedeterminedthattheaveragepHofthereticulorumenwas6.47±0.016,temperatureofthe
reticulorumenwas38.779±0.020°C,andruminationtimewas455.26±6.052.Theaveragemilk
productivityofcowswas40.41±0.724kg,BWwas648.37±13.265kg,andtheratiooffattoprotein
inmilkwas1.17±0.013.
3.1.ReticulorumenpHasanIndicatorofReproductionStatusofCows
AnalysisofthereticulorumenpHofcowsbyreproductivestatusshowedthehighestaverage
valueofthisindicatorinGroupIV(Figure1A),whichwas2.13%highercomparedtoGroupI,0.76%
highercomparedtoGroupII,and1.37%highercomparedtoGroupIII.Accordingtomultiple
comparisonsofmeans,alldifferencesbetweenthegroupsofcowsbyreproductivestatuswere
foundtobestatisticallysignificant(p<0.05).
(A)
6.250
6.300
6.350
6.400
6.450
6.500
6.550
6.600
6.650
I II III IV
Reticulorumen pH
Group of cows by status of reproduction
Figure 1. Cont.
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(B)
Figure1.(A).AnalysisofreticuloromenreticulorumenpHincowsbyreproductionstatus.GroupI:
15–30dayspostpartum,GroupII:1–34daysafterinsemination,GroupIII:35daysafterinsemination
(non‐pregnant),GroupIV:35daysafterinsemination(pregnant).(B).AnalysisofreticulorumenpH
incowsbystatusofreproduction.Class1:pH<6.22,Class2:pH6.22—6.42,Class3:pH6.42—6.62,
andClass4:pH>6.62.
Wefound(Figure1B)thatallpregnantcows(GroupIV,n=20)belongedtothethirdclass
accordingtotheirreticulorumenpH,whichrangedbetween6.42to6.62(50.00%oftheanimalsin
thisclasswereGroupIIIcows).
ThedatainFigure2AshowthatthepHofthefirstgroup(15–30dayspostpartum)changed
from6to6.98duringtheday.Therangeofchangesinthisindicatorwas2–2.24timeshigher
comparedtocowsintheothergroups.
(A)
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
100.00
<6.22 6.22-6.42 6.42-6.62 >6.62
%
Reticulorumen pH classes
group IV
group III
group II
group I
6.00
6.10
6.20
6.30
6.40
6.50
6.60
6.70
6.80
6.90
7.00
0:06:00
1:06:00
2:06:00
3:06:00
4:06:00
5:06:00
6:06:00
7:06:00
8:06:00
9:06:00
10:06:00
11:06:00
12:06:00
13:06:00
14:06:00
15:06:00
16:06:00
17:06:00
18:06:00
19:06:00
20:06:00
21:06:00
22:06:00
23:06:00
Reticulorumen pH
Time interval (24 h)
group I
group II
Figure 1.
(
A
). Analysis of reticuloromenreticulorumen pH in cows by reproduction status. Group I:
15–30 days postpartum, Group II: 1–34 days after insemination, Group III: 35 days after insemination
(non-pregnant), Group IV: 35 days after insemination (pregnant). (
B
). Analysis of reticulorumen pH in
cows by status of reproduction. Class 1: pH <6.22, Class 2: pH 6.22–6.42, Class 3: pH 6.42–6.62, and
Class 4: pH >6.62.
We found (Figure 1B) that all pregnant cows (Group IV, n =20) belonged to the third class
according to their reticulorumen pH, which ranged between 6.42 to 6.62 (50.00% of the animals in this
class were Group III cows).
The data in Figure 2A show that the pH of the first group (15–30 days postpartum) changed from
6 to 6.98 during the day. The range of changes in this indicator was 2–2.24 times higher compared to
cows in the other groups.
Sensors2020,20,xFORPEERREVIEW5of13
(B)
Figure1.(A).AnalysisofreticuloromenreticulorumenpHincowsbyreproductionstatus.GroupI:
15–30dayspostpartum,GroupII:1–34daysafterinsemination,GroupIII:35daysafterinsemination
(non‐pregnant),GroupIV:35daysafterinsemination(pregnant).(B).AnalysisofreticulorumenpH
incowsbystatusofreproduction.Class1:pH<6.22,Class2:pH6.22—6.42,Class3:pH6.42—6.62,
andClass4:pH>6.62.
Wefound(Figure1B)thatallpregnantcows(GroupIV,n=20)belongedtothethirdclass
accordingtotheirreticulorumenpH,whichrangedbetween6.42to6.62(50.00%oftheanimalsin
thisclasswereGroupIIIcows).
ThedatainFigure2AshowthatthepHofthefirstgroup(15–30dayspostpartum)changed
from6to6.98duringtheday.Therangeofchangesinthisindicatorwas2–2.24timeshigher
comparedtocowsintheothergroups.
(A)
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
100.00
<6.22 6.22-6.42 6.42-6.62 >6.62
%
Reticulorumen pH classes
group IV
group III
group II
group I
6.00
6.10
6.20
6.30
6.40
6.50
6.60
6.70
6.80
6.90
7.00
0:06:00
1:06:00
2:06:00
3:06:00
4:06:00
5:06:00
6:06:00
7:06:00
8:06:00
9:06:00
10:06:00
11:06:00
12:06:00
13:06:00
14:06:00
15:06:00
16:06:00
17:06:00
18:06:00
19:06:00
20:06:00
21:06:00
22:06:00
23:06:00
Reticulorumen pH
Time interval (24 h)
group I
group II
Figure 2. Cont.
Sensors 2020,20, 1022 6 of 14
Sensors2020,20,xFORPEERREVIEW6of13
(B)
Figure2.(A).ReticulorumenpHchangesduring24hbyreproductionstatusofcows.GroupI:15–30
dayspostpartum,GroupII:1–34daysafterinsemination.(B).ReticulorumenpHchangesover24h
byreproductionstatusofcows.GroupIII:35daysafterinsemination(non‐pregnant),GroupIV:35
daysafterinsemination(pregnant).
OncomparingthereticulorumenpHinnon‐pregnantandpregnantcows35–90daysafter
insemination,weseeahigherlevelofthisindicatorinpregnantcows.
3.2.ReticulorumenpHasanIndicatorofHealthStatusinCows
TheaverageactivityofcowsinreticulorumenpHClass1was3.5%lowercomparedtothatof
Class4and14.3–14.96%lowercomparedtothatofClasses1and3.IncowsfromClass3,we
determinedthehighesttemperatureofthereticulorumen,andinClass4,thelowesttemperature
wasfound(0.07°Clower).Thedifferencesinarithmeticmeanswerenotstatisticallysignificant
(Table2).
Table2.InfluenceofreticulorumenpHandreproductivestatusonautomaticmilkingsystem(AMS)
indicatorsandmilktraitsofcows.
Reticulorumen
pHClassAMSParameters(M,SE)AMEParameters(M,SE)
1
Activity
(steps/hour)
10.24`1.239
Fat(%)
3.58 0.187
210.300.5064.58 0.076
38.96 0.6203.93 0.094
49.27 0.8763.93 0.132
1
Reticulorumen
temperature(°C)
38.78 0.078
Protein
(%)
3.37 0.057
238.76 0.0323.58 0.023
338.79 0.0393.43 0.028
438.72 0.0553.37 0.040
1
BW(kg)
756.00 61.710
F/P
1.06 0.048
2593.67 25.1931.28 0.020
3630.75 30.8551.15 0.024
4630.00 43.6361.17 0.031
1
RT(min/d)
487.00 24.947
Lactose
(%)
4.53 0.028
2423.50 10.1854.61 0.011
3436.75 12.4744.59 0.014
4478.50 17.6404.56 0.020
1MY(kg/d)37.50 2.214SCC124.00 222.028
6.00
6.10
6.20
6.30
6.40
6.50
6.60
6.70
6.80
6.90
7.00
0:06:00
0:56:00
1:46:00
2:36:00
3:26:00
4:16:00
5:06:00
5:56:00
6:46:00
7:36:00
8:26:00
9:16:00
10:06:00
10:56:00
11:46:00
12:36:00
13:26:00
14:16:00
15:06:00
15:56:00
16:46:00
17:36:00
18:26:00
19:16:00
20:06:00
20:56:00
21:46:00
22:36:00
23:16:00
Reticulorumen pH
Time interval (24 h)
group III
group IV
Figure 2.
(
A
). Reticulorumen pH changes during 24 h by reproduction status of cows. Group I:
15–30 days postpartum, Group II: 1–34 days after insemination. (
B
). Reticulorumen pH changes over
24 h by reproduction status of cows. Group III: 35 days after insemination (non-pregnant), Group IV:
35 days after insemination (pregnant).
On comparing the reticulorumen pH in non-pregnant and pregnant cows 35–90 days after
insemination, we see a higher level of this indicator in pregnant cows.
3.2. Reticulorumen pH as an Indicator of Health Status in Cows
The average activity of cows in reticulorumen pH Class 1 was 3.5% lower compared to that
of Class 4 and 14.3–14.96% lower compared to that of Classes 1 and 3. In cows from Class 3, we
determined the highest temperature of the reticulorumen, and in Class 4, the lowest temperature was
found (0.07 ◦C lower). The differences in arithmetic means were not statistically significant (Table 2).
Table 2.
Influence of reticulorumen pH and reproductive status on automatic milking system (AMS)
indicators and milk traits of cows.
Reticulorumen
pH Class AMS Parameters (M, SE) AME Parameters (M, SE)
1
Activity
(steps/hour)
10.24 1.239
Fat (%)
3.58 0.187
2 10.30 0.506 4.58 0.076
3 8.96 0.620 3.93 0.094
4 9.27 0.876 3.93 0.132
1
Reticulorumen
temperature (◦C)
38.78 0.078
Protein (%)
3.37 0.057
2 38.76 0.032 3.58 0.023
3 38.79 0.039 3.43 0.028
4 38.72 0.055 3.37 0.040
1
BW (kg)
756.00 61.710
F/P
1.06 0.048
2 593.67 25.193 1.28 0.020
3 630.75 30.855 1.15 0.024
4 630.00 43.636 1.17 0.031
1
RT (min/d)
487.00 24.947
Lactose (%)
4.53 0.028
2 423.50 10.185 4.61 0.011
3 436.75 12.474 4.59 0.014
4 478.50 17.640 4.56 0.020
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Table 2. Cont.
Reticulorumen
pH Class AMS Parameters (M, SE) AME Parameters (M, SE)
1
MY (kg/d)
37.50 2.214
SCC
(tousd/mL)
124.00 222.028
2 41.07 1.067 105.83 90.643
3 37.13 1.307 135.25 111.014
4 49.85 1.849 95.00 156.998
Means with different superscripts among classes are significantly different (p<0.05). M—mean; SE—standard of
error of the mean; RT—rumination time; BW—body weight; SCC—somatic cell count; MY—milk yield; F/P—milk
fat-protein ratio.
In Class 2, we found the lowest level of milk (EC) (68.5–70.5), and in the other classes, these were
statistically significantly higher (from 70.5 to 72 mS/cm, p<0.05) (Figure 3).
Sensors2020,20,xFORPEERREVIEW7of13
241.07 1.067(tousd/
mL)
105.8390.643
337.13 1.307135.25 111.014
449.85 1.84995.00 156.998
Meanswithdifferentsuperscriptsamongclassesaresignificantlydifferent(p<0.05).M—mean;
SE—standardoferrorofthemean;RT—ruminationtime;BW—bodyweight;SCC—somaticcell
count;MY—milkyield;F/P—milkfat‐proteinratio.
InClass2,wefoundthelowestlevelofmilk(EC)(68.5–70.5),andintheotherclasses,these
werestatisticallysignificantlyhigher(from70.5to72mS/cm,p<0.05)(Figure3).
Figure3.Comparisonofelectricalconductivityofmilk(EC)(mS/cm)byudderquarterlevel
accordingtoreticulorumenpHclasses.EC1—frontleft,EC2—frontright,EC3—rearleft,EC4—rear
right.mS/cm—milisiemenspercentimetre.
ReticulorumenClass2hadalower(p<0.05)RT(3.12%lowercomparedtoClass3,12.99%
lowercomparedtoClass4,and15%lowercomparedtoClass1).Thestudyshowedthatthehighest
levelsofmilkfatandmilkproteinandtheoptimalF/Pwereinthesecondclass.InClass1,wefound
thelowestratioofmilkfattoproteinandthelowestconcentrationofmilklactose.Wedetermined
thelowestSCCinthemilkofClass4andClass2,whilethehighestwasinClass3andClass1(Table
2).Ontheotherhand,classesofcowswiththehighestmilkSCCshowedthehighestelectrical
conductivityinmilkattheudderquarterlevel(Figure3).
3.3.CorrelationsofReticulorumenpHwithIndicatorsfromAutomaticMilkingSystem(AMS)
CorrelationcoefficientsbetweenreticulorumenpHandindicatorsfromAMSarepresentedin
Figure4A,B).
65.0
66.0
67.0
68.0
69.0
70.0
71.0
72.0
73.0
74.0
class 1 class 2 class 3 class 4
mS/cm
EC by reticulorumen class at the udder quarters level
EC1 EC2 EC3 EC4
Figure 3.
Comparison of electrical conductivity of milk (EC) (mS/cm) by udder quarter level according
to reticulorumen pH classes. EC1—front left, EC2—front right, EC3—rear left, EC4—rear right.
mS/cm—milisiemens per centimetre.
Reticulorumen Class 2 had a lower (p<0.05) RT (3.12% lower compared to Class 3, 12.99% lower
compared to Class 4, and 15% lower compared to Class 1). The study showed that the highest levels of
milk fat and milk protein and the optimal F/P were in the second class. In Class 1, we found the lowest
ratio of milk fat to protein and the lowest concentration of milk lactose. We determined the lowest SCC
in the milk of Class 4 and Class 2, while the highest was in Class 3 and Class 1 (Table 2). On the other
hand, classes of cows with the highest milk SCC showed the highest electrical conductivity in milk at
the udder quarter level (Figure 3).
3.3. Correlations of Reticulorumen pH with Indicators from Automatic Milking System (AMS)
Correlation coefficients between reticulorumen pH and indicators from AMS are presented in
Figure 4A,B).
Sensors 2020,20, 1022 8 of 14
Sensors2020,20,xFORPEERREVIEW8of13
Figure4.(A,B).ReticulorumenpHcorrelationswithindicatorsfromAMS.RT—ruminationtime;
BW—bodyweight;SCC—somaticcellcount;EC—electricalconductivityofmilkattheudderquarter
level(DU—rearright,KU—rearleft,DP—frontright,KP—frontleft).
ReticulorumentemperatureandRTwereweaklynegativelyrelatedwithreticulorumenpH(r=
−0.131–0.234)andweaklypositivelycorrelatedwithBWandactivityofcows(r=−0.051–0.104).MY
(r=0.583,p<0.001),milklactose(r=0.240,p<0.05),andF/P(r=0.250,p<0.05)werepositively
relatedwithreticulorumenpHandwerenegativelyrelatedwithmilkprotein(−0.304,p<0.01),SCC
(−0.329,p<0.05),EC(−0.213–0.498,p<0.05–0.01),andmilkfat(−0.042).
ThehighestbloodpHlevelwasdeterminedinreticulorumenclasses2and4,anditwaslowest
inClass1(p<0.05).Onthecontrary,inClass1weestimatedthehighestpCO2andlowestpO2and
Calevels.InClass4,wefoundthelowestcHCO3‐,BE(ecf),TCO2,andNaandthehighestlevelsof
KandHCT(Table3).
ReticulorumenpHwasstatisticallyreliableandpositivelycorrelatedwithbloodK(p<0.01)
andHct(p<0.001),whileitwasnegativelycorrelatedwithpCO2andTCO2(p<0.01)aswellaswith
pO2,cHCO3‐,BE(ecf),andNa(p<0.05).DataarepresentedinFigure5.
Table3.InfluenceofreticulorumenpHlevelonbloodindicatorsincows.
Reticulorumen
pHClassBloodParameters(M,SE) BloodParameters(M,SE)
1
pH
7.38a0.016
Na
137.00a0.601
27.43b0.005137.13ab0.212
37.42b0.008137.25ab0.3
47.43b0.011136.00ac0.425
1
pCO2
49.20a2.204
K
3.90a0.11
245.20b0.7794.10a0.039
345.13b1.1024.00a0.055
440.55a1.5584.30b0.078
1
pO2
49.90a19.062
Ca
1.24a0.016
267.11a6.7401.13b0.006
361.45a9.5311.14b0.008
452.00a13.4791.22a0.011
1
cHCO3‐
29.30a1.288
TCO2
29.20a1.257
230.23ab0.45529.90ab0.445
329.03a0.64428.78a0.629
427.00ac0.9126.75ac0.889
1BE(ecf)4.20a1.372Hct24.00a0.884
-0.30
-0.20
-0.10
0.00
0.10
0.20
Activity
Temperature
BW
RT
A. Correlation
‐0.60
‐0.40
‐0.20
0.00
0.20
0.40
0.60
MY
Fat
Protein
F/P
Lactosis
SCC_log10
EC_KP
EC_DP
EC_KU
EC_DU
B.Correlation
Figure 4.
(
A
,
B
). Reticulorumen pH correlations with indicators from AMS. RT—rumination time;
BW—body weight; SCC—somatic cell count; EC—electrical conductivity of milk at the udder quarter
level (DU—rear right, KU—rear left, DP—front right, KP—front left).
Reticulorumen temperature and RT were weakly negatively related with reticulorumen pH
(r =−0.131–0.234)
and weakly positively correlated with BW and activity of cows (r =
−
0.051–0.104).
MY (r =0.583, p<0.001), milk lactose (r =0.240, p<0.05), and F/P (r =0.250, p<0.05) were positively
related with reticulorumen pH and were negatively related with milk protein (
−
0.304, p<0.01), SCC
(−0.329, p<0.05), EC (−0.213–0.498, p<0.05–0.01), and milk fat (−0.042).
The highest blood pH level was determined in reticulorumen classes 2 and 4, and it was lowest in
Class 1 (p<0.05). On the contrary, in Class 1 we estimated the highest pCO2 and lowest pO2 and Ca
levels. In Class 4, we found the lowest cHCO3-, BE (ecf), TCO2, and Na and the highest levels of K and
HCT (Table 3).
Table 3. Influence of reticulorumen pH level on blood indicators in cows.
Reticulorumen
pH Class Blood Parameters (M, SE) Blood Parameters (M, SE)
1
pH
7.38 a0.016
Na
137.00 a0.601
27.43 b0.005 137.13 ab 0.212
37.42 b0.008 137.25 ab 0.3
47.43 b0.011 136.00 ac 0.425
1
pCO2
49.20 a2.204
K
3.90 a0.11
245.20 b0.779 4.10 a0.039
345.13 b1.102 4.00 a0.055
4 40.55 a1.558 4.30 b0.078
1
pO2
49.90 a19.062
Ca
1.24 a0.016
2 67.11 a6.740 1.13 b0.006
3 61.45 a9.531 1.14 b0.008
4 52.00 a13.479 1.22 a0.011
1
cHCO3-
29.30 a1.288
TCO2
29.20 a1.257
230.23 ab 0.455 29.90 ab 0.445
3 29.03 a0.644 28.78 a0.629
4 27.00 ac 0.91 26.75 ac 0.889
Sensors 2020,20, 1022 9 of 14
Table 3. Cont.
Reticulorumen
pH Class Blood Parameters (M, SE) Blood Parameters (M, SE)
1
BE (ecf)
4.20 a1.372
Hct
24.00 a0.884
25.98 ab 0.485 23.75 a0.313
3 4.48 a0.686 26.00 b0.442
4 2.70 ac 0.97 27.00 b0.625
a,b,c Means with different superscripts among classes are significantly different (p<0.05). M—mean; SE—standard
of error of the mean; BE—base excess in blood; PCO2—partial carbon dioxide pressure; PO2—partial oxygen
pressure; cHCO3—bicarbonate; pH—hydrogen potential; TCO2—total carbon dioxide carbon; BE (ecf)—base excess
in extracellular fluid; Na—sodium; Ca—Calcium; K—potassium.
Reticulorumen pH was statistically reliable and positively correlated with blood K (p<0.01) and
Hct (p<0.001), while it was negatively correlated with pCO2 and TCO2 (p<0.01) as well as with pO2,
cHCO3-, BE (ecf), and Na (p<0.05). Data are presented in Figure 5.
Sensors2020,20,xFORPEERREVIEW9of13
25.98ab0.48523.75a0.313
34.48a0.68626.00b0.442
42.70ac0.9727.00b0.625
a,b,cMeanswithdifferentsuperscriptsamongclassesaresignificantlydifferent(p<0.05).M—mean;
SE—standardoferrorofthemean;BE—baseexcessinblood;PCO2—partialcarbondioxide
pressure;PO2—partialoxygenpressure;cHCO3—bicarbonate;pH—hydrogenpotential;
TCO2—totalcarbondioxidecarbon;BE(ecf)—baseexcessinextracellularfluid;Na—sodium;
Ca—Calcium;K—potassium.
Figure5.ReticulorumenpHcorrelationswithbloodindicators.BE—baseexcessinblood;
PCO2—partialcarbondioxidepressure;PO2—partialoxygenpressure;cHCO3—bicarbonate;
pH—hydrogenpotential;TCO2—totalcarbondioxidecarbon;BE(ecf)—baseexcessinextracellular
fluid;Na—sodium;Ca—Calcium;K—potassium.
4.Discussion
4.1.ReticulorumenpHasanIndicatorofCowReproductionSuccess
ThecurrentstudyindicatedthatpregnantcowstendtohavehigherreticulorumenpHduring
inseminationthanthatofnon‐pregnantcows.Thestudyfindingsalsoindicatethatdairycowswith
adisturbedrumenmetabolismhavealowchanceofconceiving.Therefore,thishighlightsthat
reticuloruminalpHcanbeusedeffectivelyasapredictorfordairycowreproductivehealth.
AccordingtoInchaisrietal.[17],pHsignificantlyinfluencesconceptionduringinsemination.
Arguably,alowpHinthereticulorumenincreasesthetemperatureofthereticulorumenand
abomasum.Fromthisstudy,theaveragetemperatureofthereticulorumenduringpost
inseminationuntilday170wasconsiderablyhigherthanthatinnon‐pregnantcows[10].Itwas
observedthatvaginaltemperaturebeforeestruswasconsiderablyhigherthanthatduringthe
post‐ovulationperiod[18].Duringestrus,theaveragetemperatureinthereticulorumenincreases.
4.2.ReticulorumenpHandHealthStatusofCows
TheavailableliteratureindicatesthattheassessmentofruminalpHisanoptimummeasureto
evaluatetheriskofSARAbecauseofvariationindairycows’rumenpH[19].Thestudyfindings
indicatethatdairycowsreactuniquelytolowpHvaluesoftherumen.Therefore,eachcowhas
varyingsusceptibilitytoSARA[20].Ruminationactivityandfermentationprocessesare
interconnected.Thus,reducedruminationactivitycauseslowerproductionofsalivabuffering,
therebyincreasingriskforSARA[21].Theincreasedruminationactivityobservedafterthecalving
periodisduetothehighfeedintakeduringthepost‐pregnancyprocess.Theacceleratedpassage
ratecausesareducedruminationactivityofDMI.ContrarytoPahletal.’sfindings,itwasobserved
-0.4
-0.2
0
0.2
0.4
0.6
pH
pCO2
pO2
cHCO3-
BE (ecf)
Na
K
Ca
TCO2
Hct
Correlation
Figure 5.
Reticulorumen pH correlations with blood indicators. BE—base excess in blood;
PCO2—partial carbon dioxide pressure; PO2—partial oxygen pressure; cHCO3—bicarbonate;
pH—hydrogen potential; TCO2—total carbon dioxide carbon; BE (ecf)—base excess in extracellular
fluid; Na—sodium; Ca—Calcium; K—potassium.
4. Discussion
4.1. Reticulorumen pH as an Indicator of Cow Reproduction Success
The current study indicated that pregnant cows tend to have higher reticulorumen pH during
insemination than that of non-pregnant cows. The study findings also indicate that dairy cows with
a disturbed rumen metabolism have a low chance of conceiving. Therefore, this highlights that
reticuloruminal pH can be used effectively as a predictor for dairy cow reproductive health. According
to Inchaisri et al. [
17
], pH significantly influences conception during insemination. Arguably, a low pH
in the reticulorumen increases the temperature of the reticulorumen and abomasum. From this study,
the average temperature of the reticulorumen during post insemination until day 170 was considerably
higher than that in non-pregnant cows [
10
]. It was observed that vaginal temperature before estrus
was considerably higher than that during the post-ovulation period [
18
]. During estrus, the average
temperature in the reticulorumen increases.
Sensors 2020,20, 1022 10 of 14
4.2. Reticulorumen pH and Health Status of Cows
The available literature indicates that the assessment of ruminal pH is an optimum measure to
evaluate the risk of SARA because of variation in dairy cows’ rumen pH [
19
]. The study findings
indicate that dairy cows react uniquely to low pH values of the rumen. Therefore, each cow has varying
susceptibility to SARA [
20
]. Rumination activity and fermentation processes are interconnected.
Thus, reduced rumination activity causes lower production of saliva buffering, thereby increasing
risk for SARA [
21
]. The increased rumination activity observed after the calving period is due to
the high feed intake during the post-pregnancy process. The accelerated passage rate causes a reduced
rumination activity of DMI. Contrary to Pahl et al.’s findings, it was observed that treatment did not
affect the rumination patterns of the dairy cows [
22
]. It was observed that the chew per minute and
bolus rumination of dairy cows reduced considerably during the last days before calving and the last
days after calving. Similar observations were reported by Schmitz et al. [21].
The study findings indicate that cows with a lower RRpH had a low milk fat/protein ratio, a low
lactose concentration, and a high SCC. They also had a low blood pH. Available literature indicates
that low ruminal pH triggers the lysing and death of gram-negative bacteria found in the rumen. This
action causes an increase in the concentration of lipopolysaccharides, which in turn triggers an increase
in the concentration of systemic inflammatory markers, such as cytokines, haptoglobin, and acute
protein serum Amyloid A [
23
]. It is well known that the reticulum has a higher pH level than that
of the rumen. Therefore, SARA detection thresholds should be designed in a manner that identifies
the localized pH of the reticulum [
24
]. The current standards for SARA detection involve the use of
high-resolution kinetics of rumen pH sensors. However, it was observed that the addition of buffering
agents to a high-concentrate diet was effective in preventing milk fat concentration. [
25
]; this is because
it re-established an optimum pH level in the rumen and reticulum.
Feed composition determines the milk fat ratio [
26
]. The dairy cows under investigation had
a low milk fat/protein concentration on most of the test days, which indicated that the energy level
of the number of feeds obtained was generally low [
27
]. This is one of the signs observed in cows
presenting with sub-acute rumen acidosis [
28
]. Dairy cows that have been diagnosed with SARA and
non-acute ruminal acidosis generally tend to have lower milk-fat percentages [
29
]. However, because
the disease has different actions on milk fat content per cow, the findings of low milk fat contents
concerning feeding composition in most bulk tank testing scenarios remain unclear [
30
]. The pH
of the ruminal fluid was found to be low. This is because the microbes in the rumen break down
carbohydrates into short-chain fatty acids at a faster rate than the rumen absorptive rate, outflow,
and buffering activity [
20
]. The reduction of microbial populations in the rumen causes reduced fiber
digestion [
31
]. Consequently, the feed intake reduces [
32
], further causing a reduction in milk fat
production [
33
]. Altered unsaturated fat bio-hydrogenation processes in the rumen, liver abscesses,
systemic and localized tissue inflammation in the rumen papillae, and SARA are the key causes of
lameness and horn lesions [
34
]. Owens et al. [
35
] argues that chronic and acute acidosis occurs due to
the ingestion of diets that contain readily fermented carbohydrates in excess. As a dairy animal adapts
to rich concentrates of feeds in their feeding yards, it causes acute acidosis and becomes chronic as
the yard feeding continues. In the acute acidosis phase, ruminal acidity and osmolality lead to elevated
acids and glucose accumulation, which in turn causes increased damage in the rumen and intestinal
wall due to high blood pH and dehydration. These events, if not well managed, can be fatal.
According to the study findings, an increase in RRpH causes an increase in Hct and blood K,
and a decrease in BE (ecf), Na, and CO2. According to Giensella et al. [
36
], it is vital to perform
blood gas analyses, as it is a valuable tool, especially during the diagnosis of acidosis. The analysis
provides great insight into the extent of acidosis using a noninvasive approach. According to a study
conducted by Gokce et al. [
37
], animals with additional pathological disorders, such as respiratory
diseases like pneumonia, tend to display an altered acidotic response. In this study, it was noted that
PCO2 differed significantly during the different stages of SARA, which suggested an indication of
acute respiratory acidosis. PO2 was observed to decrease statistically during SARA, and it is argued
Sensors 2020,20, 1022 11 of 14
that this pathology is likely due to increased consumption of vascular O2. In this case, decreased
PO2 values are associated with increased anaerobic metabolism and O2 consumption [
37
]. Metabolic
disturbances initially present in a hidden form, and their information is associated with problems
of fermentation processes in the rumen. It is evident that nutrient conversion is the key precursor
of milk production and is largely dependent on rumen fermentation [
38
]. The functional ability of
the mammary gland is directly correlated with the dairy cow’s health status; thus, milk ingredients
reflect the level of total metabolism [
39
]. Therefore, biochemical markers in the milk accurately depict
the metabolic status of dairy cows.
5. Conclusions
The present study concludes that the interline registered pH of cow reticulum can be used as an
indicator of the animal’s health and reproductive status. In pregnant cows, the reticulorumen pH is
considerably high during insemination, as compared to that of non-pregnant cows. Cows with a lower
RRpH have the lowest milk fat ratio and lactose concentration and the highest SCC. The high RRpH
increased the concentration of K and HCT in the blood, but caused a reduction in CO2, BE, and Na.
Therefore, reticulorumen pH can be used effectively to predict cow reproductive and health status.
Author Contributions:
R.A.: overall research study process, including literature search, carrying out research
experiments, and compiling the final manuscript. The entire process was revised by the co-authors. V.J.: Assisted
in designing and setting up field data collection activities and developed the software and algorithm for data
analysis. D.M. and M.T.: aided in fieldwork set-up, data collection, and sampling of the experimental animals. All
authors have read and agreed to the published version of the manuscript.
Funding: No external funding was received.
Conflicts of Interest: The authors declare no conflict of interest.
Abbreviations
◦C Celsius
ADF Acid detergent fiber
AMS Automatic milking system
BCS Body condition score
BE (ecf) base excess in extracellular fluid
BW Body weight
Ca Calcium
Chco3 Bicarbonate
cHgb Hemoglobin concentration
CL Chlorides
CP Crude protein
d Days
DM Dry matter
EC Electrical milk conductivity
F/P Milk fat-protein ratio
Fat Milk fat
HCT Hematocrit
h Hours
K Potassium
Kg Kilogram
Kg Kilograms
Lac Lactate
Mcal/kg mega calories per kilogram
min/d Minutes per day
Sensors 2020,20, 1022 12 of 14
mS/cm Milisiemens per centimeter
MY Milk yield
Na Sodium
NDF Neutral detergent fiber
NEL Neto energy for lactation
NFC Nonfiber carbohydrates
PCO2 Partial carbon dioxide pressure
pH Hydrogen potential
PLF Precision livestock farming
RRpH Reticulorumen pH
RT Rumination time
SARA Subclinical acidosis
SCC Somatic cell count
TCO2 Total carbon dioxide carbon
TMR Total mix ration
tousd/mL Thousand per millilitre
References
1. Brayer, E. Control Apparatus for Milking Machines. US Patent 4,348,984, 4 September 1982.
2.
Wathes, C.M.; Kristensen, H.H.; Aerts, J.M.; Berckmans, D. Is precision livestock farming an engineer’s
daydream or nightmare, an animal’s friend or foe, and a farmer’s panacea or pitfall? Comput. Electron. Agric.
2008,64, 2–10. [CrossRef]
3.
Soriani, N.; Trevisi, E.; Calamari, L. Relationships between rumination time, metabolic conditions, and health
status in dairy cows during the transition period. J. Anim. Sci. 2012,90, 4544–4554. [CrossRef] [PubMed]
4.
Schmilovitch, Z.; Katz, G.; Maltz, E.; Kutscher, M.I.; Sarig, M.; Halachmi, I.; Hoffman, A.; Egozi, H.; Uner, E.
Spectroscopic Fluid Analyzer. US Patent 7,236,237, 26 June 2007.
5.
Halachmi, I.; Guarino, M.; Bewley, J.; Pastell, M. Smart Animal Agriculture: Application of Real-Time Sensors
to Improve Animal Well-Being and Production. Annu. Rev. Anim. Biosci.
2019
,7, 403–425. [CrossRef]
[PubMed]
6.
AlZahal, O.; Kebreab, E.; France, J.; Froetschel, M.; McBride, B. Ruminal Temperature May Aid in the Detection
of Subacute Ruminal Acidosis. J. Dairy Sci. 2008,91, 202–207. [CrossRef]
7.
Cantor, M.C.; Costa, J.H.C.; Bewley, J.M. Impact of Observed and Controlled Water Intake on Reticulorumen
Temperature in Lactating Dairy Cattle. Animals 2018,8, 194. [CrossRef] [PubMed]
8.
Antanaitis, R.; Juozaitien
˙
e, V.; Malašauskien
˙
e, D.; Televiˇcius, M. Can rumination time and some blood
biochemical parameters be used as biomarkers for the diagnosis ofsubclinical acidosis and subclinical ketosis?
Vet. Anim. Sci. 2019,8, 100077. [CrossRef]
9.
Albaaj, A.; Foucras, G.; Raboisson, D. High somatic cell counts and changes in milk fat and protein contents
around insemination are negatively associated with conception in dairy cows. Theriogenology
2017
,88, 18–27.
[CrossRef]
10.
Antanaitis, R.; Juozaitien
˙
e, V.; Rutkauskas, A.; Televiˇcius, M.; Stasiuleviˇci
¯
ut
˙
e, I. Reticulorumen temperature
and pH as indicators of the likelihood of reproductive success. J. Dairy Res. 2018,85, 23–26. [CrossRef]
11.
AlZahal, O.; AlZahal, H.; Steele, M.; Van Schaik, M.; Kyriazakis, I.; Duffield, T.; McBride, B. The use of
a radiotelemetric ruminal bolus to detect body temperature changes in lactating dairy cattle. J. Dairy Sci.
2011,94, 3568–3574. [CrossRef]
12.
Cooper-Prado, M.J.; Long, N.M.; Wright, E.C.; Goad, C.L.; Wettemann, R.P. Relationship of ruminal
temperature with parturition and estrus of beef cows1. J. Anim. Sci. 2011,89, 1020–1027. [CrossRef]
13.
AlZahal, O.; Steele, M.; Valdes, E.; McBride, B. Technical note: The use of a telemetric system to continuously
monitor ruminal temperature and to predict ruminal pH in cattle. J. Dairy Sci.
2009
,92, 5697–5701. [CrossRef]
[PubMed]
14.
Antanaitis, R.; Žilaitis, V.; Juozaitiene, V.; Stoškus, R.; Televiˇcius, M. Changes in reticulorumen content
temperature and pH according to time of day and yearly seasons. Pol. J. Veter Sci.
2016
,19, 771–776.
[CrossRef] [PubMed]
Sensors 2020,20, 1022 13 of 14
15.
Colman, E.; Fokkink, W.; Craninx, M.; Newbold, J.; De Baets, B.; Fievez, V. Effect of induction of subacute
ruminal acidosis on milk fat profile and rumen parameters. J. Dairy Sci.
2010
,93, 4759–4773. [CrossRef]
[PubMed]
16.
Danscher, A.M.; Li, S.; Andersen, P.H.; Khafipour, E.; Kristensen, N.B.; Plaizier, J.C. Indicators of induced
subacute ruminal acidosis (SARA) in Danish Holstein cows. Acta Veter Scand.
2015
,57, 39. [CrossRef]
[PubMed]
17.
Inchaisri, C.; Chanpongsang, S.; Noordhuizen, J.; Hogeveen, H. The association of ruminal pH and some
metabolic parameters with conception rate at first artificial insemination in Thai dairy cows. Trop. Anim.
Health Prod. 2013,45, 1183–1190. [CrossRef] [PubMed]
18.
Suthar, V.; Burfeind, O.; Patel, J.; Dhami, A.; Heuwieser, W. Body temperature around induced estrus in
dairy cows. J. Dairy Sci. 2011,94, 2368–2373. [CrossRef]
19.
AlZahal, O.; Kebreab, E.; France, J.; McBride, B. A Mathematical Approach to Predicting Biological Values
from Ruminal pH Measurements. J. Dairy Sci. 2007,90, 3777–3785. [CrossRef]
20.
Plaizier, J.; Krause, D.; Gozho, G.; McBride, B. Subacute ruminal acidosis in dairy cows: The physiological
causes, incidence and consequences. Veter J. 2008,176, 21–31. [CrossRef]
21.
Schmitz, R.; Schnabel, K.; Von Soosten, D.; Meyer, U.; Hüther, L.; Spiekers, H.; Rehage, J.; Dänicke, S. Changes
of ruminal pH, rumination activity and feeding behaviour during early lactation as affected by different
energy and fibre concentrations of roughage in pluriparous dairy cows. Arch. Anim. Nutr.
2018
,72, 1–20.
[CrossRef]
22.
Pahl, C.; Hartung, E.; Grothmann, A.; Mahlkow-Nerge, K.; Haeussermann, A. Rumination activity of dairy
cows in the 24 h before and after calving. J. Dairy Sci. 2014,97, 6935–6941. [CrossRef]
23.
Khafipour, E.; Li, S.; Plaizier, J.C.; Krause, D.O. Rumen Microbiome Composition Determined Using Two
Nutritional Models of Subacute Ruminal Acidosis. Appl. Environ. Microbiol.
2009
,75, 7115–7124. [CrossRef]
[PubMed]
24.
Sato, S.; Ikeda, A.; Tsuchiya, Y.; Ikuta, K.; Murayama, I.; Kanehira, M.; Okada, K.; Mizuguchi, H. Diagnosis of
subacute ruminal acidosis (SARA) by continuous reticular pH measurements in cows. Veter Res. Commun.
2012,36, 201–205. [CrossRef] [PubMed]
25.
Khorasani, G.; Okine, E.; Kennelly, J. Effects of Substituting Barley Grain with Corn on Ruminal Fermentation
Characteristics, Milk Yield, and Milk Composition of Holstein Cows. J. Dairy Sci.
2001
,84, 2760–2769.
[CrossRef]
26.
Esmaeili, M.; Khorvash, M.; Ghorbani, G.; Nasrollahi, S.; Saebi, M. Variation of TMR particle size and physical
characteristics in commercial Iranian Holstein dairies and effects on eating behaviour, chewing activity, and
milk production. Livest. Sci. 2016,191, 22–28. [CrossRef]
27.
Bergk, N.; Swalve, H.H. Fat-to-protein-ratio in early lactation as an indicator of herdlife for first lactation
dairy cows. Züchtungskunde 2011,83, 89–103.
28.
Rossow, N. Nutzung der Ergebnisse der Milchleistungsprüfung für die Fütterungs- und Stoffwechselkontrolle.
Portal-Rind. 2003.
29.
Oetzel, G.R. Clinical aspects of ruminal acidosis in dairy cattle. In Proceedings of the Thirty-Third Annual
Conference, American Association of Bovine Practitioners, Rapid City, SD, USA, 21–23 September 2000;
pp. 46–53.
30. Nocek, J.E. Bovine Acidosis: Implications on Laminitis. J. Dairy Sci. 1997,80, 1005–1028. [CrossRef]
31.
Plaizier, J.C.; Keunen, J.E.; Walton, J.-P.; Duffield, T.F.; McBride, B.W. Effect of subacute ruminal acidosis on
in situ digestion of mixed hay in lactating dairy cows. Can. J. Anim. Sci. 2001,81, 421–423. [CrossRef]
32.
Gozho, G.; Plaizier, J.; Krause, D.; Kennedy, A.; Wittenberg, K. Subacute Ruminal Acidosis Induces Ruminal
Lipopolysaccharide Endotoxin Release and Triggers an Inflammatory Response. J. Dairy Sci.
2005
,88,
1399–1403. [CrossRef]
33.
Khafipour, E.; Krause, D.; Plaizier, J. A grain-based subacute ruminal acidosis challenge causes translocation
of lipopolysaccharide and triggers inflammation. J. Dairy Sci. 2009,92, 1060–1070. [CrossRef]
34.
Peterse, D.J. [Nutrition as a possible factor in the pathogenesis of ulcers of the sole in cattle (author’s transl)].
Tijdschr. Diergeneeskd. 1979,104, 966–970.
35.
Owens, F.N.; Secrist, D.S.; Hill, W.J.; Gill, D.R. Acidosis in cattle: A review. J. Anim. Sci.
1998
,76, 275.
[CrossRef] [PubMed]
Sensors 2020,20, 1022 14 of 14
36.
Gianesella, M.; Morgante, M.; Cannizzo, C.; Stefani, A.; Dalvit, P.; Messina, V.; Giudice, E. Subacute Ruminal
Acidosis and Evaluation of Blood Gas Analysis in Dairy Cow. Veter Med. Int.
2010
,2010, 1–4. [CrossRef]
[PubMed]
37.
Gokce, G.; Citil, M.; Gunes, V.; Atalan, G. Effect of time delay and storage temperature on blood gas and
acid-base values of bovine venous blood. Res. Veter Sci. 2004,76, 121–127. [CrossRef] [PubMed]
38.
Vajda, P.; Pinter, A.B.; Harangi, F.; Farkas, A.; Vastyan, A.M.; Oberritter, Z. Metabolic findings after
colocystoplasty in children. Urol 2003,62, 542–546. [CrossRef]
39.
Hamann, J.; Krömker, V. Potential of specific milk composition variables for cow health management.
Livest. Prod. Sci. 1997,48, 201–208. [CrossRef]
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