Received: 30 July 2019 | Accepted: 26 December 2019

DOI: 10.1111/rda.13618

ORIGINAL ARTICLE

Effects of mineral supplementation on reproductive

performance of pregnant cross-breed Bonsmara cows: An
experimental study

Keitiretse Molefe | Mulunda Mwanza

Department of Animal Health, Faculty of

Natural and Agricultural Sciences, North- Abstract
West University, Mmabatho, South Africa Minerals in animal feed occur in variable structures, most of which determine the uptake
Correspondence and usage in biological processes in the body. Effective chemical breakdown of minerals
Keitiretse Molefe, Department of Animal may ensure efficient utilization in metabolism. The aim this study was to evaluate the
Health, Faculty of Natural and Agricultural
Sciences, North-West University, Mafikeng effects of mineral supplementation on reproduction in cows. A farm was selected for
Campus, Private Bag X 2046 Mmabatho the experiment due to the fact that it previously experienced different reproductive
2735, South Africa.
Email: mkeitiretse@yahoo.com conditions in the farm. The farm comprises cross-breed cows with Bonsmara domi-
nating in the farm. Twelve pregnant primiparous and multiparous cows of different
Funding information
This study was supported by the North- ages, parity and weight, that had previously experienced reproductive conditions, were
West University Postgraduate Bursary,
randomly selected for this study. The cows were then randomly sub-divided into two
HWSETA and the National Research
Foundation. groups (experimental and control group) of six. The experimental group was injected
with MULTIMIN™ + Se + Cu at a dosage of 1 ml/45 kg BW and Calci 50 p.i. at a dos-
age of 100–150 ml/500 kg BW at an interval of 6 weeks (from June to October 2017).
Blood samples were collected before every injection date. The t test was used to relate
the mean weight gain and serum metabolite between the experimental and control
groups. The body weight gain was significantly higher in the experimental group com-
pared to the non-supplemented group. Supplemented cows had significantly (p < .05)
high levels of triglycerides and creatinine kinase. A case of retained placenta and dysto-
cia among non-supplemented cows were noted. Thus, mineral supplementation can be
used to improve productivity and reproductive well-being.

KEYWORDS

communal rearing, cows, minerals, reproductive condition, supplementation

1 | I NTRO D U C TI O N for nutritional demands during this period can affect reproductive
performance and foetal growth (Caldow & Riddell, 2015). Minerals,
Globally, contribution of livestock production has a significant influ- in particular, are greatly essential, as any alteration in supply during
ence on agricultural growth (Randolph et al., 2007). Nutrient require- gestation can predispose cows to reproductive failure (Andrieu,
ments increase as the pregnancy progresses and failure to account 2008; Griffiths, Loeffler, Socha, Tomlinson, & Johnson, 2007). In

[The copyright line for this article was changed to open access on 18 May 2020 after original online publication.]

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction
in any medium, provided the original work is properly cited and is not used for commercial purposes.
© 2020 North West University. Reproduction in Domestic Animals published by Blackwell Verlag GmbH.

Reprod Dom Anim. 2020;55:301–308. wileyonlinelibrary.com/journal/rda | 301

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302 MOLEFE and MWANZA

mammals, reproductive needs for minerals are commonly consistent cows in each group: experimental (supplemented) or control (non-
with the foetal, conception product (i.e. foetal fluid, uterus and pla- supplemented) group. A selected sample of primiparous and multipa-
centa) and mineral content (Suttle, 2010). rous cows (3–5 years old, 347–540 kg initial body weight and parity
Deficiencies in calcium, magnesium, phosphorus, copper, sele- of 1–2) were assigned to the experimental and control groups and the
nium, zinc and manganese have been associated with occurrences experiment performed for 18 weeks (from June to October 2017).
of hypocalcaemia, retained placenta, abortion, dystocia, vaginal pro-
lapse, downer cow syndrome and overall depressed reproductive
performance in cows (Amen & Muhammad, 2016; Mokolopi, 2019; 2.4 | Treatment
Sepúlveda-Varas, Weary, Noro, & Keyserlingk, 2015; Velladurai,
Selvaraju, & Napolean, 2016; Yatoo et al., 2018). The experimental group was given three injections of
Whenever natural grasslands are the main or only source of nu- MULTIMIN™ + Se + Cu at a dosage of 1 ml/45 kg BW and Calci 50
trition supply, it is essential to determine the nutritional content of p.i. at a dosage of 100–150 ml/500 kg BW at an interval of 6 weeks
pastures, to quantify and measure different elements in order to ac- during mid-late gestation. MULTIMIN™ + Se + Cu contains 15 mg
count for deficiencies and improve the feed in order to enhance pro- Cu/ml (as Cu disodium EDTA), 40 mg Zn/ml (as Zn disodium EDTA),
duction and reproduction (Al-Ghareebawi, Almansor, & Muhammad, 10 mg Mn/ml (as Mn disodium EDTA), 5 mg Se/ml (as sodium sele-
2017). Increased attempts to reduce mineral deficiencies have as well nite) and Calci 50 p.i. containing calcium 45.6 mg, magnesium 7.8 mg
increased the risk of toxicity. It is a common practice to offer cow and phosphorus 1.32 mg. All cows were allowed to graze in the veld.
mineral lick in an effort to balance requirements; however, this is not
achievable unless the concentrations of minerals in the supplement are
exactly the amount required. Thus, proper supplementation is neces- 2.5 | Chemical analysis
sary in order to reduce incidences of reproductive problems and animal
losses due to nutritional imbalances. Hence, the aim of this study was Blood samples were collected from both groups once before the
to assess the role of mineral supplementation on pregnant cows in the beginning of the experiment and on three occasions, prior every
prevention of peri-partum reproductive conditions. injection date. Samples were later analysed for serum biochemical
parameters such as magnesium (Mg), total protein (TP), creatinine
kinase (CK), lipase (LIPA), triglycerides (TRIG), blood urea nitrogen
2 | M ATE R I A L S A N D M E TH O DS (Urea/BUN), uric acid (URIC), aspartate amino-transferase (AST),
cholesterol (CHOL), total bilirubin (TBIL), gamma-glutamyltransferase
2.1 | Study area (GGT) and ammonia (NH3) using IDEXX Catalyst chemistry analyser
accordance with the instructions in the manufacturer's manual.
This study was conducted in Mafikeng, North-West Province, South
Africa. The area is situated on the following coordinates: 25°51′S
and 25°38′E. Mafikeng is a semi-arid area comprising both rural 2.6 | Analysis of pasture and preparation of
and commercial farms, most of which are rural farms. Temperatures grass samples
range from 22 to 35°C in summer (between August and March) and
rainfall fluctuates between 200 and 500 mm/year. Pasture samples around the area (Mogosane Village), where the
cows were grazing, were also harvested according to species and
analysed for their mineral content. Different species of the grass
2.2 | Animals were randomly collected across the grazing area using a pair of scis-
sors in June 2017. The different species were as follows: Eragostis
A farm in Mogosane Village (Mafikeng) with cross-breed Bonsmara rigidor (Curly grass); Bothriochloa radicans (stinking grass); Eragrostis
cows was selected for the study due to its previous history of expo- lehmanniana (Lehmann's Love Grass); Panicum maximum (White buf-
sure to reproductive cases such as dystocia, retained placenta, vagi- falo grass); Aristida Congesta Subsp. barbicollis (Spreading Three-
nal prolapses, downer cow syndrome and abortions. The breeding awn); Eragostis rotifer (Pearly Love Grass); Urochloa oligotricha
history (as observed by farmers) for all cows selected for the experi- (Perennial Signal Grass); Themeda triandra (Red grass); Heteropogon
ment was recorded. contortus (Spear grass); Erogostic superba (Saw-tooth Love grass);
and Brachiaria nigropedata (Black footed grass). These species were
identified according to Van Oudtshoorn and Van Wyk (2012). The
2.3 | Experimental design pastures were picked at the stage of maturity and about 10 cm from
the ground (van Niekerk, Hassen, & Bechaz, 2010). The different
Twelve pregnant cows, between the ages of 3–4 years and types of grass were then taken to the Animal Health laboratories of
3–4.5 months, were selected for the study. The cows were tagged the North-West University for analysis. During analysis, a portion of
and randomly allocated to one of the two treatment groups with six each grass sample was mixed in one plastic bag and a representative
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MOLEFE and MWANZA 303

sample (1 kg) used for analysis. The samples were later placed on 2.7 | Conditions of instrument used for ICP-MS
benches to air dry. Samples were ground using a POLYMIX PX-MFC (inductively coupled plasma mass spectrometry)
90D (Thermo Fisher Scientific) grinder. Powdered samples were
subsequently placed in sample containers and stored until analysis. All chemicals used were of analytical grade quality. Ultrapure water
Preparation of samples was done following the procedure de- was obtained from a Millipore water system (Millipore) and ultrapure
scribed by Ndou and Dlamini (2012). Laboratory tools (crucibles) re- Nitric acid (HNO3, Merck) used to digest the samples. Stock standard
quired for the digestion and preparation of grass samples were soaked solutions of Arsenic and Mercury containing 10 μg/ml in 2% HNO3
overnight in 36% hydrochloric acid (HCl). They were then rinsed three were procured from Sigma Aldrich, USA, and prepared in accordance
times with distilled water and placed for 16 hr (at 60°C) in a hot air oven with the procedure described by Uluozlu et al. (2017). Certified ref-
to dry. After drying, the crucibles were placed in a desiccator for 6 hr erence materials (CRM) were purchased from the National Institute
to allow cooling, and later weighed to obtain crucible weight before of Standard Technology (NIST-8436) and used for standardization
adding the samples. Grass samples were sun-dried and ground. An an- and validation of the method.
alytical scale calibrated to four decimal places was used to weigh the
grass samples. The difference between the mass of the crucible and
fresh grass samples and the weight of the empty crucible were used 2.8 | Statistical analysis
to calculate the fresh weight {fresh weight = (crucible + weight of fresh
sample) − (weight of empty crucible)}. Exactly 1 g of the powdered The data were captured in excel and analysed using the Statistical
grass sample was weighed into the clean crucible. Crucibles contain- Package for the Social Sciences (SPSS) Version 25. The t test was
ing ground grass samples were placed in the oven to dry at 106°C used to compare the mean differences (body weight and serum me-
for 16 hr to remove excess moisture. After removing the crucible tabolites) between the control (non-supplemented) and the experi-
from the oven, samples were then placed in a desiccator to cool and mental (supplemented) groups. The level of significance was set at
weighed after 6 hr. The differences between the weight of the cruci- p < .05.
ble, the dry sample and weight of the empty crucible were recorded
as the dry weight of the sample {Dry weight = (crucible + weight of dry
samples) − (weight of empty crucible)}. After weighing, the samples 3 | R E S U LT S
were ashed in a muffle furnace at 800°C for 16 hr.
The ash was removed from the furnace and cooled, then 1 ml The results of this study are summarized in Table 1, showing the ex-
Nitric acid and 9 ml hydrochloric acid were added to the cruci- perimental mean weight gain in pregnant cows given mineral sup-
ble, and the mixture transferred to the rotors of the microwave plements (Multimin) compared to those not supplemented. The
digester and properly placed in the microwave for digestion. mean values indicate both positive and negative weight gain (i.e. for
The samples were digested using a microwave digestion system June–July, the experimental group gained on an average weight of
MD2100 (CEM, Mathews, NC). After digestion, samples were about 61.5 kg while in the control group, there was a weight loss
transferred to 100 ml volumetric flasks and topped up with dis- of 19.5 kg). Table 2 shows variations in mean weight gain between
tilled water to reach the 100 ml mark using a clean glass funnel. the experimental and control groups. The results of the t test show
The solution was left overnight on the bench. The following day, that the mean weight gain (June–July) differed significantly (p < .05)
the sample was filtered using Whatman filter papers into sterile between the experimental and control groups with the former ex-
centrifuge tubes. Then, analysis of digested samples was per- ceeding the latter by 81.
formed using the Inductively Coupled Plasma Mass Spectrometry- Table 3 shows the results of the t test. The results show the
NexION 300Q ICP-MS (PerkinElmer ®). means of weight gain (June–July) were not significantly different

TA B L E 1 Experimental mean weight gain in pregnant cows given mineral supplements (Multimin) compared to those not supplemented

Group statistics

Months Group ID Mean weight gain Std. deviation Std. error mean

June–July Experimental 61.500 58.037 23.694

Control −19.500 46.561 19.008
July–August Experimental −13.500 75.931 30.999
Control 17.500 22.314 9.110
August–September Experimental −20.000 30.835 12.588
Control −12.667 18.811 7.680
September–October Experimental 19.000 53.051 21.658
Control −51.500 33.441 13.652
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304 MOLEFE and MWANZA

TA B L E 2 Mean live weight gain

Std. error
variations between supplemented and
t df Sig. (2-tailed) Mean difference difference
non-supplemented cows
Weight gain (June–July) 2.667* 10 0.024 81.000 30.376
Weight gain −0.959 10 0.360 −31.000 32.309
(July–August)
Weight gain −0.497 10 0.630 −7.333 14.746
(August–September)
Weight gain 2.754* 10 0.020 70.500 25.602
(September–October)

*Significantly different (p > .05) across the ages and parities of the animals.

TA B L E 3 Mean differences of the experimental (supplemented) and control (non-supplemented) groups within a particular age and
parities

Age in years Parity Mean ± Std. deviation Std. error mean Sig. (p-value)

Weight gain (June–July) 3.00 1st 42.750 ± 89.574 44.787 .538

4.00 2nd 10.125 ± 54.057 19.112
Weight gain (July–August) 3.00 1st −33.500 ± 81.847 40.924 .287
4.00 2nd 19.750 ± 30.570 10.808
Weight gain (August–September) 3.00 1st −12.750 ± 18.839 9.420 .704
4.00 2nd −18.125 ± 28.140 9.949
Weight gain (September–October) 3.00 1st −6.500 ± 76.857 38.429 .745
4.00 2nd −21.125 ± 48.230 17.052

TA B L E 4 Comparison of serum
Serum metabolites t df Sig. (p-value) Mean difference
metabolite between the experimental
UREA/BUN −0.955 10 0.362 −0.433 mM (supplemented) and the control (non-
Phosphates (PHOS) −0.114 10 0.911 −0.018 mM supplemented) groups before the first
injection (June- 2017)
URIC Acid 2.983* 10 0.014 17.667 μM
Total protein (TP) 1.136 10 0.282 3.667 g/L
ALT 0.656 10 0.527 3.833 U/L
AST −0.064 10 0.950 −1.167 U/L
GGT 0.649 10 0.531 2.333 U/L
Total bilirubin (TBIL) 0.327 10 0.751 1.167 μM
Cholesterol (CHOL) −0.029 10 0.978 −0.012 mM
Ammonia (NH3) 1.270 10 0.233 86.167 μM
Triglycerides (TRIG) −0.791 10 0.448 −0.003 mM
LIPA 0.285 10 0.781 3.667 U/L

*Sig. = significant differences (p < .05).

(p > .05) across the ages and parities of the animals. Results of com- acid, triglycerides and creatinine were significantly variable be-
parison of serum metabolite between the experimental and control tween the groups. The results in Table 7 show that the concen-
groups are shown in Table 4. The results also show that serum uric tration of P, Zn, Cu and I in the grass was lower than the normal
acid concentrations differed significantly between the experimental range.
and control groups (Table 4). Table 5 shows comparison of serum
metabolite between the experimental and the control groups after
the second supplementation. Serum triglycerides (TRIG) and creat- 4 | D I S CU S S I O N
inine kinase (CK) were significantly different between the experi-
mental and control groups. The aim of this study was to evaluate the effects of mineral sup-
Table 6 shows significantly altered serum metabolites levels plementation on the reproductive performance of pregnant cross-
at the first sampling in the experiment, the concentrations of uric breed Bonsmara cows reared in semi-arid areas of South Africa.
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MOLEFE and MWANZA 305

TA B L E 5 Comparison of serum
Serum metabolites t df Sig. (2-tailed) Mean difference
metabolite between the experimental
(supplemented) and control (non- UREA/BUN 1.916 10 0.084 0.917 mM
supplemented) groups after the second Phosphates (PHOS) −0.025 10 0.981 −0.008 mM
supplementation, before the last injection
URIC Acid 2.072 10 0.065 12.500 μM
of minerals (6-October-2017)
Total protein (TP) −0.499 10 0.628 −6.667 g/L
ALT −0.517 10 0.616 −7.500 U/L
AST −0.837 10 0.422 −20.833 U/L
GGT −1.027 10 0.328 −2.000 U/L
Total bilirubin (TBIL) 0.850 10 0.415 0.833 μM
Cholesterol (CHOL) −0.451 10 0.662 −0.195 mM
Ammonia (NH3) −1.083 10 0.304 −99.167 μM
Triglycerides (TRIG) −4.661* 10 0.001 −1.800 mM
LIPA −2.018 10 0.071 −45.833 U/L
Creatinine kinase (CK) −4.817* 10 0.001 −110.333 U/L

*Sig. = significant differences (p ≤ .001).

TA B L E 6 Serum metabolites
Serum metabolites means ± standard error
mean ± standard errors of cows given
mineral supplements from 3–4.5 months Uric acid Triglyceride Creatinine kinase
of pregnancy
Experimental groups
Treatment 52.1667 ± 3.986 0.2167 ± 0.034 69.5 ± 6.312
Control 34.5 ± 4.379 2.0167 ± 0.384 179.833 ± 22.015
Normal ranges 2.81–3.93 mg/dl 0.08–0.20 mM 0–110 U/L

Note: Normal ranges for uric acid, tryclycerides and creatinine kinase were sourced from Mamun et
al. (2013) and Cozzi et al. (2011).

TA B L E 7 Composition of grass nutrient

Level of
in the grazing area of the experimental
Nutrients Mean ± std (μg/ml) Reference ranges concentration
farm chosen for mineral supplementation
experiment, mean standard deviation and Phosphorus (P) 9.412 ± 1.622 81.4464–723.968 mg/L* L
reference ranges Magnesium (Mg) 17.946 ± 2.279 12.0188–36.6033 mg/L* N
Manganese (Mn) 4.97 ± 4.135 0.18–0.19 mg/L*** H
Iron (Fe) 8.827 ± 1.6118 1–2 μg/ml*** H
Zinc (Zn) 0.209 ± 0.125 0.8–1.2 μg/ml*** L
Copper (Cu) 0.389 ± 0.125 0.57–0.96 μg/ml*** L
Selenium (Se) 10.66 ± 9.832 0.7–1.3 μg/ml*** H
Iodine (I) 2.858 ± 1.943 4.96–19.85 mg/L** L

Note: Sources of reference ranges: *Djoković et al. (2014); **Cozzi et al. (2011); ***Yatoo et al.
(2018).
Keys: L-below the normal range; N-within the normal range; H-Higher than normal range.
NB: μg/ml = mg/L.

The results that pasture concentrations of phosphorus and availability of grasses are seen as more rainfall is experienced
(mg/L) 9.412 ± 1.622, zinc (μg/ml) 0.209 ± 0.125, copper (μg/ml) (Bezabih, Pellikaan, Tolera, Khan, & Hendriks, 2014). Consequently,
0.389 ± 0.125 and iodine (mg/L) 2.858 ± 1.943 were lower than animals reared under such conditions are prone to nutritional im-
the normal ranges of 81.446–723.968 mg/L, 0.8–1.2 μg/ml, 0.57– balance due to fluctuating nutrient consumption, leading to poor
0.96 μg/ml and 4.96–19.85 mg/L, respectively, as shown in Table 7 reproductive performance (Velladurai et al., 2016). Phosphorus is
(Cozzi et al., 2011; Djoković et al., 2014; Yatoo et al., 2018). frequently stated as a ‘fertility’ mineral (Fageria, He, & Baligar, 2017).
Rainfall patterns in semi-arid areas affect the quality and availabil- An earlier study on mineral content revealed that phosphorus levels
ity of pastures during the dry season, and improvements in quality in natural pastures are not adequate to improve productivity (Ateba
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306 MOLEFE and MWANZA

& Beighle, 2011). Hadžimusić, Krnić, and Hodžić (2013) found very show that mean weight gain (June–July) differed significantly
high phosphorus requirements in cows and that what is provided by (p < .05) between the experimental and the control groups, with
plants may be less due to low levels in the soil. Natural pastures are the former exceeding the latter by 81 (Table 2). During winter
generally low in phosphorus, which predisposes cows to impaired (June–July), the experimental group (61.5 ± 58.037 kg) gained
muscle function, retained placenta and downer cow syndrome (Ate, more weight than the control group, showing an average weight
Rekwot, Nok, & Tekdek, 2009). Thus, cow productivity and improved loss of 19.5 ± 46.56 kg (Table 1).
reproductive performance are directly connected to phosphorus in- The results also revealed that that mean weight gain in spring
take (Wang et al., 2017). (September–October) differed significantly (p < .05) between the
The study revealed low zinc, copper and iodine in grass con- experimental and the control groups, with the former exceeding
sumed by cows (Table 7). These deficiencies have been linked with the latter by 70.5 (Table 2). Variations in body mass have tradition-
disease susceptibility and, reproductive disorders, such as abortions ally been used to monitor energy balance, which is an important
and retained placenta in cows (Balamurugan et al., 2017; Kumar, nutritional indicator related to both animal health and reproduc-
2014; Suttle, 2010; Velladurai et al., 2016). This is an indication that tion (Salehi, Colazo, Oba, & Ambrose, 2016). Lack of mineral sup-
cows consuming mineral-deficient grass are predisposed to repro- plementation (as observed in the study) can cause production
ductive failures, making mineral supplementation important to avoid losses mainly in animals relying only on natural pasture (Dhakal
and reduce reproductive complications. et al., 2013). Losses in body mass have been associated with poor
The study also revealed that concentrations of iron productivity and incidences of reproductive conditions (Rossato,
(8.827 ± 1.6118 μg/ml), manganese (4.97 ± 4.135 mg/L) and selenium Gonzalez, Dias, Riccó, Valle, Rosa, & Wald, 2001). The results
(10.66 ± 9.832 μg/ml) in the different types of grass were higher than imply that supplementation improves animal production during
the normal ranges of 1–2 μg/ml, 12.0188–36.6033 mg/L and 0.7– the dry season and maintains a healthier body condition compared
1.3 μg/ml, respectively, as indicated in Table 7 (Djoković et al., 2014; to non-supplementation.
Yatoo et al., 2018). Serum metabolites are used as physiological indicators, which
Increase in dietary iron causes copper deficiency, leading to im- better reflect metabolic disorders, animal health, nutritional status
paired reproduction, and high selenium may lead to stillbirths and and reproductive performance (Wu et al., 2018). Significantly altered
abortions due to toxicity (Abramowicz, Kurek, Dębiak, Madany, & serum metabolite levels were seen at the beginning of the experi-
Lutnicki, 2019; Omeje, 2016). The results show that increases in ment, before and after supplementation. Concentrations of uric acid,
the grass minerals could influence the reproductive health of cows. triglycerides and creatinine significantly varied between supple-
The occurrence of mineral imbalances in communal pastures could mented (treatment) and non-supplemented (control) cows (Table 6).
explain incidences of reproductive conditions in cows (Bindari, Serum mean concentrations of uric acid were significantly high in
Shrestha, Shrestha, & Gaire, 2013; López-Alonso, 2012; Taylor, both the experimental and control groups before the commencement
2007). Deficiencies observed and excess of mineral in the grass sug- of the supplementation (Table 4). Additionally, the mean difference
gest that supplementation could influence reproduction. for uric acid (17.667 mg/dl) showed that the experimental mean was
The role of supplementary trace mineral during pregnancy greater than the control mean concentration (Table 4). Uric acid is an
has revealed controversial (positive, negative and sometimes neu- inorganic compound (2,6,8 trioxypurine-C5H4N4O3) and an endog-
tral) results on reproductive performance (Joksimović-Todorović, enous product of purine metabolite in animals (De Oliveira & Burini,
Davidović, & Bojanić-Rašović, 2016). Nonetheless, the current study 2012). Cardiovascular diseases, chronic kidney diseases, increase
showed that the non-supplemented group experienced retained pla- body mass, insulin resistance and leptin production, and decreased
centa and dystocia, while the supplemented group did not experi- excretion of renal uric acid are some of the factors known to increase
ence any reproductive disorders. Another similar study associated concentrations of uric acid (Dórea, Danés, Zanton, & Armentano,
mineral deficiencies with increased incidences of retained placenta 2017; Laughon, Catov, Powers, Roberts, & Gandley, 2011; Zhu, Peng,
and dystocia (Tucho & Ahmed, 2017). These results suggest that & Ling, 2017). Additionally, reduced body weight has been associated
minerals influence reproductive aptitude and health of cows reared with high level of uric acid, due to oxidative stress, resulting from
on natural pastures. excess production of uric acid (De Oliveira & Burini, 2012). This could
In the current study, significant differences (p < .05) in body mass explain the increase in uric acid in the current study before the com-
and serum metabolites were seen between pregnant cows injected mencement of the experiment (Table 4).
with Multimin mineral supplements and those that were not. It is Serum triglycerides (TRIG) and creatinine kinase (CK) were
difficult to measure the state of nutrition in cows traditionally reared significantly different between the experimental (supplemented)
on natural pasture; hence, live-body weight measures become a very and control (non-supplemented) groups (Table 5). The level of CK
useful management tool for monitoring nutritional status during and (179.833 ± 22.015 U/L) was significantly higher in the control group,
after pregnancy (Dhakal et al., 2013). in which dystocia and retained placenta were observed (Table 6). It
Changes in body mass and metabolic profile measures in cows has been documented that high CK levels may be due to the impair-
are known to simplify interpretations of reproduction and nutri- ment or exertion of skeletal muscles resulting from difficult partu-
tion interactions (Caldow & Riddell, 2015). The current results rition (Murray et al., 2015). This could be the reason for the high
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MOLEFE and MWANZA 307

creatinine kinase levels seen in the control group of cows, which ex- DATA AVA I L A B I L I T Y
perienced difficult birth in the present study. Data for this study can be obtained from the corresponding author
The present study showed the mean TRIG (2.0167 ± 0.384 mM) upon reasonable request.
level was above normal in the control group (Table 6). Other re-
searchers have associated negative energy feedback and high nu- ORCID
tritional requirements with low levels of triglycerides (Alves et al., Keitiretse Molefe https://orcid.org/0000-0003-2826-0122
2014; Petkova, Kitanov, & Girginov, 2008). In situations of positive Mulunda Mwanza https://orcid.org/0000-0002-9311-6517
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