Special Issue:

Emerging and Re-emerging Animal Health Challenges in Low and Middle-Income Countries

Coenzyme Q10 and Zinc Methionine Treatment Impact Productive and Hematological Traits in Awassi Lambs

Abdulkhaliq Ahmed Farhan Al-Janabi*, Nawar Bahaa Abduljabbar, Mohammed A. Amean

Animal Production Department, College of Agriculture, Tikrit University, Tikrit, Iraq.

Received | October 28, 2025; Accepted | December 15, 2025; Published | December 22, 2025

*Correspondence | Abdulkhaliq Ahmed Farhan Al-Janabi, Animal Production Department, College of Agriculture, Tikrit University, Tikrit, Iraq; Email: [email protected]

Citation | Al-Janabi AAF, Abduljabbar NB, Amean MA (2025). Coenzyme Q10 and zinc methionine treatment impact productive and hematological traits in Awassi lambs. J. Anim. Health Prod. 13(s1): 945-953.

DOI | https://dx.doi.org/10.17582/journal.jahp/2025/13.s1.945.953

ISSN (Online) | 2308-2801

Copyright: 2025 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

INTRODUCTION

The Awassi sheep breed has a broad distribution across multiple Middle Eastern nations (Tabbaa et al., 2006). Awassi sheep demonstrate prominent meat production quality while showing high resilience against tough environmental and dietary situations (Merchen and Titgemeyer, 1992). The decline of animal nutrition leads to diminished production capabilities which requires the implementation of various enriched nutritional options. These nutritional additions are intended to boost the animals’ nutritional value while simultaneously improving productivity and strengthening their health and immune systems (Steen et al., 2008; Khan et al., 2010).

Researchers now study how adding antioxidants and mineral components to animal feed can protect cellular structures from free radicals while also improving animal health alongside reproductive capabilities and production efficiency (Hassan et al., 2021; Balani et al., 2018; El-Nagar and Wafa, 2021). Antioxidants maintain a crucial function by either stopping free radicals from forming due to biological processes in the body or moderating their harmful impacts (Videla et al., 2004; Law et al., 2018). Coenzyme Q10 functions as an antioxidant and is naturally found in living organisms including both macro and microorganisms. The body is capable of producing coenzyme Q10 which functions as a fat-soluble antioxidant (Littarru et al., 2016). The mitochondrial energy production process depends on Coenzyme Q10 which functions as an electron and proton transporter during oxidative phosphorylation (Shukla and Dubey, 2018). This substance defends cellular membranes and plasma lipid proteins against lipid peroxidation damage and helps restore other antioxidants such as vitamins E and C (Gvozdjáková et al., 2015).

Animal feed contains essential trace minerals whose bioavailability remains restricted and fails to fulfill the nutritional needs of animals according to Princewill et al. (2015). Rare minerals in animal feed become inaccessible for animal consumption because chemical compounds like phytates, oxalates, and tannins bind with them and prevent absorption which leads to nutritional deficiencies (Hummel et al., 2020). The repetitive farming practices along with grazing and deforestation activities have made the soil deficient in essential minerals which causes forage crops to become deficient as well (Datt and Chhabra, 2005). Research demonstrates that supplementing animal feed with suitable quantities of rare trace minerals enhances nutritional metabolism and growth while supporting reproduction and eliminating free radicals from oxidative stress through their role in enzymatic functions or as enzyme cofactors. The research by Yatoo et al. (2013) demonstrates that these minerals strengthen immune response functions.

Zinc serves as a vital element for growth promotion, immune function enhancement, cell division processes, protein synthesis, surface tissue integrity maintenance, antioxidant activity and hormone secretion regulation (Krishnaiah et al., 2019). Field animals rarely experience zinc toxicity because they can handle high amounts of zinc in their food sources according to studies by McDowell (1992) and NRC (1996). This investigation seeks to determine how Coenzyme Q10 and Zinc Methionine supplements affect productive and hematological traits in Awassi.

MATERIALS AND METHODS

The experiment took place at the University of Tikrit’s College of Agriculture Animal Production Department animal field from March 8 to June 5, 2023. For this research, a total of 20 local Awassi animals were used which ranged in age between 4 and 4.5 months and had an average weight of 21.71 ± 0.34 kg. divided these animals into five treatment groups, where the first group received distilled water while the second and third groups received Coenzyme Q10 at 25 mg and 50 mg doses, respectively, in 5 ml of water per animal. Groups four and five received combined treatments with Coenzyme Q10 and Zinc Methionine at doses of 25 mg of Q10 plus 150 mg of zinc methionine per 5 ml water per animal and a second dose of 50 mg of Q10 plus 150 mg of zinc methionine per 5 ml water per animal, respectively.

Throughout a 14-day acclimatization period closely monitored these animals to prevent health problems. The animals received a concentrated feeding mixture made of crushed barley (50%), crushed yellow corn (25%), soybean meal (13%), bran (10%), limestone (1%), and table salt (1%). The diet contained 14.4125% crude protein content while delivering 287,305 kcal/kg of energy content. Each treatment group received their provender, which constituted 3% of its live weight, split between morning and evening meals. Every two weeks, feed quantities were modified according to weight changes while animals had unlimited access to roughage (straw). Each pen received a clean water supply along with mineral salt blocks placed throughout all pens. Blood samples were regularly collected every forty-five days at 7: During a 12-hour fasting period. Blood samples from the jugular vein in animal necks at 7:30 AM were collected into clean and sterilised plastic tubes using a 10 ml sterile syringe.

Blood tests

Red blood corpuscles count

The measurement of red blood cell count was conducted using a hemocytometer slide. by using a specialised pipette to draw blood until the 0.5 mark before reaching the 101 mark with Hyme’s solution. prepared a counting slide after swirling the pipette contents gently for ten seconds. Three initial blood drops were discarded before depositing the fourth drop at the counting slide’s edge and covering it with a cover slide. waited two minutes to let the cells settle and stabilise. Through a light microscope at 40x magnification counted the cells present in five standard squares. 16 smaller squares were present within each average square according to Hughes et al. (2004). The total red blood cell was counted by implementing this formula:

RBC (mm3 of blood) = Number of cells in five average squares × 200 (dilution correction factor) × 50 (volume correction factor)

The process to measure packed red blood cell volume involved using open-ended capillary glass tubes inclined at a 45-degree angle without anticoagulants to determine the packed red blood cell volume percentage. Once the tube reached three-quarters of its capacity, sealed at the submerged ends with synthetic clay. The tubes were placed in a Micro-Hematocrit centrifuge and rotated at 10000 revolutions per minute for five minutes. A specialised Hematocrit reader was used to measure the blood sediment length in the capillary tube. The measurement recorded represents the percentage of packed red blood cell volume according to Hughes et al. (2004).

Blood hemoglobin concentration

Using an apel spectrophotometer type at 540nm measured blood hemoglobin concentration was measured through the Drabkin and Austin method 193,5 following Randox Laboratory Co. Ltd’s guidelines from Antrim, United Kingdom, for their analysis kit as described by Coles (1986). computed blood hemoglobin levels by applying this specific equation.

The blood hemoglobin concentration in grams per 100 mL of blood equals the sample reading on the device divided by the standard solution reading, multiplied by the dilution factor, then multiplied by the standard hemoglobin solution concentration and divided by 1000.

Red blood cell indices

These were calculated using the following equations:

• The Mean Corpuscular Volume (MCV in cubic micrometres) is calculated by dividing the volume of packed red blood cells by the red blood cell count and multiplying the result by 10.
• The MCH value in picograms is calculated by dividing the Hemoglobin Concentration by the Red Blood Cell Count and multiplying the result by 10.
• The calculation for Mean Corpuscular Hemoglobin Concentration (MCHC% %) requires dividing the Hemoglobin Concentration by the Volume of Packed Red Blood Cells and multiplying the result by 100.

White blood cell count

To count white blood cells with a hemocytometer slide the blood sample was drawn up to the 0.5 mark using a specialised pipette, followed by filling up to the 11th mark with Turk’s Solution. The sample was allowed to remain unstirred for three minutes to enable staining of the white blood cell nuclei after mixing its contents by hand for ten seconds. The counting slide preparation included discarding the first three drops and placing the fourth drop beside the counting chamber cover. The sample was left for two minutes until the cells settled and stabilised before examination through a light microscope at X40 magnification. The following formula allowed for calculating the total white blood cell count.

WBC (cells/mm3 of blood) = Number of Cells in the Central Large Square × 20 (dilution correction factor) × 10 (volume correction factor)

The process for determining the differential white blood cell count involved making a blood smear. A small blood drop was positioned on the corner of a glass slide, and another slide spread it to form an even layer. The smear dried completely after ten minutes before being fixed by placing it into methyl alcohol (0.97 N). The slides underwent half an hour of staining through immersion with Gamsa stain, which was prepared beforehand and detailed. The slides were cleaned of excess stain with gentle tap water washing. Under a light microscope with an oil immersion lens (X 100 examined) white blood cells, including Lymphocytes, Monocytes, Neutrophils, Eosinophils and Basophils. moved the slide along a Z-shaped path to count 100 white blood cells (Sood, 1985).

Statistical analysis

The performed statistical analysis through Complete Randomised Design (CRD), which followed a one-way path. The statistical significance of treatment differences was evaluated using Duncan’s multiple range test as reported by Duncan in 1955 and conducted statistical analysis through the SAS software version 2012. The following mathematical model served as the basis for data analysis.

Yij = μ + Ti + eij

Where: Yij denotes the jth observational data point from treatment i. The effect of treatment i corresponds to index I, which includes control as 1, second as 2, third as 3, fourth as 4, and fifth as 5. Experimental error eij maintains normal distribution properties while being independent with a zero mean and variance of ℮2σ.

RESULTS AND DISCUSSION

Impact of enzyme COQ10 and zinc methionine on productive performance in awassi lambs

As shown in the Table 1, there was no statistically significant differences (P≥0.05) in the body weight of Awassi lambs between treatments at the 28th day of study. At day 56, body weight measurements showed no significant differences between treatments, yet animals from the fifth treatment demonstrated significant improvement over treatments one, two, and four, along with improvements noted in the third and fourth treatments. Treatment three showed no significant variance when compared to other treatments. The final weight analysis revealed significant differences (P≤0.05) between the groups, showing that animals in the fifth treatment gained significantly more weight than those in treatments one, two, and four but displayed no significant weight difference when compared to treatment three.

 

Table 1: The effect of treatment with enzyme coenzyme Q10 and zinc methionine on productivity in Awassi lambs.

Significance level	Treatments					Traits
	Fifth (T5)	Fourth (T4)	Third (T3)	Second (T2)	First (T1)
N.S	21.93 ± 0.55 a	22.25 ± 0.81 a	21.60 ± 0.53 a	21.18 ± 1.29 a	21.40 ± 0.61 a	Initial Weight (kg)
N.S	25.30 ± 0.36 a	25.45 ± 0.72 a	24.73 ± 0.38 a	24.35 ± 1.6 a	24.00 ± 0.67 a	Weight after 28 days (kg)
N.S	29.95 ± 0.63 a	29.28 ± 0.72 a	29.23 ± 0.17 a	28.70 ± 1.00 a	27.68 ± 0.88 a	Weight after 56 days (kg)
**	34.68 ± 0.28 a	32.65 ± 0.93 bc	33.55 ± 0.49 ab	31.83 ± 0.77 c	30.80 ± 0.89 c	Final Weight (kg)
**	151.79 ± 7.51 a	121.43 ± 5.30 bc	142.26 ± 7.93 ab	126.78±6.81 bc	111.90± 10.7 c	Total Weight Gain (kg)

 

The values represent means ± standard error. N.S. means no significant differences (P ≥ 0.05). Means significant differences (P ≤ 0.05). ** means highly significant differences (P ≤ 0.01). T1 = Control, T2 = Enzyme Coenzyme Q10 25 mg/animal, T3 = Enzyme Coenzyme Q10 50 mg/animal, T4 = Enzyme Coenzyme Q10 25 mg/animal + 150 mg/animal Zinc Methionine, T5 = Enzyme Coenzyme Q10 50 mg/animal + 150 mg/animal Zinc Methionine.

 

Table 1 illustrates that CoQ10, along with zinc methionine treatment, produced significant results in total weight gain among the five Awassi lamb groups. The fifth treatment group exhibited a significant weight gain (P≤0.05) when compared to treatment groups one, two, and four, but showed no significant difference when compared to treatment three. Zinc in the fifth treatment appears to promote body weight gain because it boosts ghrelin secretion from the stomach and gastrointestinal tract lining. The peptide Ghrelin opposes leptin’s effects by triggering the release of appetite-inducing peptides Neuropeptide Y (NP-Y), Agouti-related peptide (AgRP), Orexin and Galanin from the arcuate nucleus within the hypothalamus. Adipose tissues produce less leptin when ghrelin is present, as shown in research by Zhang and Guo (2008) and Kharbanda et al. (2022).

Zinc protects pancreatic tissues from oxidative damage while enabling proper pancreatic functionality including digestive enzyme secretion which improves digestion and prevents an energy deficit that causes stress (Wang et al., 2021). Animal weight gain results from zinc’s ability to break down cellulose bonds in feed, which activates rumen microorganisms and improves microbial balance in the rumen environment. Enhanced feed conversion efficiency along with muscle tissue deposition during growth results from this (Ballantine et al., 2002; Hilal et al., 2016). The results align with the outcomes of research done by Mallaki et al. (2015) study discovered that Zandi animals fed with zinc- supplemented feed showed significant daily weight gain improvements compared to their control group counterparts. Similarly, Jafarpour et al (2015) and collaborators discovered that feeding sheep with various amounts of Zn-Met led to higher final weight and total weight gain, and daily weight gain than the control group.

The current study results are consistent with the found made by Towaje et al. (2018), goats experienced significant gains in final weight, total weight gain, and daily weight gain when fed diets supplemented with zinc at concentrations of 0, 15, 20, and 25 mg zinc/kg dry matter. The female goats in the four study groups achieved final weights of 27.75 kg, 28.44 kg, 29.84 kg, and 28.55 kg while their total weight gains amounted to 9.82 kg, 11.21 kg, 12.04 kg, and 11.15 kg, respectively with daily weight increases of 155 g/day, 177 g/day, 191 g/day, and 176 g/day, demonstrated substantial enhancements in final weight alongside daily and total weight gain in animals administered with Zn-Met relative to their control counterparts (Alimohamady et al, 2019). According to Mani et al. (2021), feeding calves zinc supplements at rates of 40 and 80 mg/kg dry matter over 90 days produced better growth performance metrics for body weight, daily weight gain, and body length compared to the control group. The study by Belewu and Adewumi (2021) demonstrated greater final body weight and daily weight gain in goats receiving 80 mg/kg zinc in their diet over 56 days versus other treatment groups.

The research by Al-Taie and Almahdawi (2021) demonstrated that Awassi animals receiving 50 mg of zinc per head three times weekly for 90 days showed significant increases in final body weight and daily and total weight gain when compared to control and selenium-treated groups. Ali et al. (2023) found that animals receiving nano-zinc at 6 and 12 mg/kg feed gained significant body weight, along with daily weight gain and total weight gain over 98 days, compared to the control group.

Effect of enzymatic co-treatment with q10 and zinc methionine on some physiological blood parameters in Awassi lambs

Red blood cells, packed cell volume, and hemoglobin

The results showed no significant differences in red blood cell counts, packed cell volume and hemoglobin concentration of Awassi lambs between five treatments when enzymatic co-treatment with Q10 and zinc methionine was performed during the initial 45 days of treatment. The treatment showed a significant impact (P ≤ 0.05) on red blood cell counts in the second treatment phase that lasted 90 days. The animals undergoing the fifth treatment exhibited a significant rise (P ≤ 0.05) in red blood cell numbers when compared to those in the first two

 

Table 2: The effect of enzymatic co-treatment with Q10 and zinc methionine on some physiological blood parameters in Awassi lambs.

Significance	Treatments					Period	Traits
	Fifth (T5)	Fourth (T4)	Third (T3)	Second (T2)	First (T1)
N.S	13.19± 0.31a	12.54± 0.21a	13.01± 0.45a	12.39± 0.48a	12.27± 0.42a	First (after 45 days)	R.B.C count x 106
*	14.35± 0.30a	13.59± 0.23ab	14.14± 0.38ab	13.23± 0.36b	13.10± 0.36b	Second (after 90 days)
N.S	31.75± 0.85a	30.50± 1.19a	31.25± 0.75a	30.50± 1.32a	30.25± 0.63a	First (after 45 days)	Packed cells volume
*	33.00± 0.91a	32.25± 1.11ab	32.75± 0.63a	31.25± 0.63ab	30.00± 0.71b	Second (after 90 days)
N.S	9.47± 0.23a	9.39± 0.33a	9.40± 0.18a	9.24± 0.36a	9.24± 0.40a	First (after 45 days)	Blood hemoglobin gm/100 ml
*	10.70± 0.28a	10.47± 0.34ab	10.62± 0.19a	10.17± 0.19ab	9.79± 0.21b	Second (after 90 days)

 

The values represent means ± standard error. N.S. means no significant differences (P ≥ 0.05), means significant differences (P ≤ 0.05). Treatment Groups: T1 = Control, T2 = Enzymatic assistant Q10 25 mg/animal, T3 = Enzymatic assistant Q10 50 mg/animal, T4 = Enzymatic assistant Q10 25 mg/animal + 150 mg/animal zinc methionine, and T5 = Enzymatic assistant Q10 50 mg/animal + 150 mg/animal zinc methionine.

 

Table 3: Effect of enzymatic assistant Q10 and zinc methionine treatment on some red blood cell indices in Awassi lambs.

Significance	Treatments					Period	Traits
	Fifth (T5)	Fourth (T4)	Third (T3)	Second (T2)	First (T1)
N.S	24.11 ± 0.76 a	24.35 ± 1.01 a	24.12 ± 1.10 a	24.67 ± 1.07 a	24.70 ± 0.55 a	First (after 45 days).	MCV (fl)
N.S	23.01 ± 0.67 a	23.74 ± 0.80 a	23.24 ± 0.93 a	23.65 ± 0.38 a	22.93 ± 0.37 a	(after 90 days)
N.S	7.18 ± 0.06 a	7.49 ± 0.23 a	7.25 ± 0.27 a	7.50 ± 0.47 a	7.53 ± 0.13 a	Second (after 45 days)	MCH (Pg)
N.S	7.46 ± 0.21 a	7.71 ± 0.25 a	7.54 ± 0.29 a	7.70 ± 0.13 a	7.48 ± 0.12 a	(after 90 days).
N.S	29.90± 1.16 a	31.02 ± 2.07 a	30.12 ± 0.98 a	30.49 ± 1.91 a	30.54 ± 1.05 a	First (after 45 days)	MCH (%)
N.S	32.42 ± 0.06 a	32.47 ± 0.08 a	32.44 ± 0.04 a	32.54 ± 0.04 a	32.63 ± 0.06 a	Second (after 90 days).

 

The values represent the means ± standard error. N.S. means no significant differences (P ≥ 0.05). T1 = Control, T2 = Enzyme Co-Adjuvant Q10 25 mg/animal, T3 = Enzyme Co-Adjuvant Q10 50 mg/animal, T4 = Enzyme Co-Adjuvant Q10 25 mg/animal + 150 mg/animal Zinc Methionine, T5 = Enzyme Co-Adjuvant Q10 50 mg/animal + 150 mg/animal Zinc Methionine.

 

treatments but showed no statistical differences when compared to groups in the third and fourth treatment groups. The third and fifth treatments showed significant increases (P ≤ 0.05) in packed cell volume percentage and hemoglobin concentration over the control group, with no notable differences when compared to the second and fourth treatments (Table 2).

The higher red blood cell counts and packed cell volume, and hemoglobin concentration found in the fifth and third treated groups result from the enzymatic assistant Q10’s effect on increasing testosterone hormone levels (Al-Samarai and Al-Janabi, 2021). The testosterone hormone controls red blood cell formation through two mechanisms: It triggers erythropoietin production in the kidney and increases red blood cell production in the bone marrow (Coles, 1986). The positive changes in blood properties likely stem from improved antioxidant status that could protect red blood cells from oxidative damage during their development or after they are produced in the bone marrow, which results in better stability and size of red blood cells (Kraus et al., 1997). Research shows that long-term zinc supplementation can improve blood properties because zinc deficiency leads to greater osmotic fragility of red blood cells and more oxidative harm, which reduces their size (Kraus et al., 1997).

Zinc plays a role in two stages of blood formation. The first function of zinc in blood formation involves stimulating erythropoietin synthesis, its effect on bone marrow cells through an unidentified process that likely activates growth hormone and IGF-1 to promote red blood cell production. The absence of this enzyme contributes to the development of anemia and the dysfunction of the respiratory system, according to Lukaski’s Research (2005).

This study’s findings match those reported by Shareef et al. (2019), Song and Shen (2020) and Abdelgayed et al. (2022), and Yusuf et al. (2023). All studies conducted in 2023 demonstrated substantial enhancements in counts of red blood cells alongside packed cell volume and hemoglobin levels following zinc supplementation in animals.

Red blood cell indices

Table 3 revealed that the treatments of enzymatic assistant Q10 combined with zinc methionine did not produce significant changes in red blood cell indices (MCV, MCH, MCHC) across all treatment groups during both the 45-day and 90-day intervals.

 

Table 4: The effect of treatment with the coenzyme Q10 and zinc methionine on white blood cell counts and their differential count in the blood of Awassi lambs.

Significance	Treatments					Period	Traits
	Fifth (T5)	Fourth (T4)	Third (T3)	Second (T2)	First (T1)
N.S	5.93 ± 0.37 a	٥.٨٥ ± ٠.٣٥ a	6.33 ± 0.51 a	7.15 ± 0.57 a	7.20 ± 0.43 a	First (after 45 days)	WBC count (103/ml)
*	5.85 ± 0.35 b	5.85± 0.35ab	5.93 ± 0.37 b	7.40 ± 0.46 a	7.43 ± 0.42 a	Second (after 90 days)
N.S	35.25± 1.11 a	6.65 ± 0.26 a	35.00± 1.08 a	35.75±0.75 a	36.25±0.25 a	First (after 45 days)	Neutrophil (%)
*	32.00± 0.70 c	35.25± 0.75bc	35.00± 0.58 b	35.75±0.75ab	37.25±0.75 a	Second (after 90 days)
N.S	4.50 ± 0.50 a	4.75 ± 0.48 a	4.75 ± 0.47 a	5.00 ± 0.58 a	5.00 ± 0.41 a	First (after 45 days)	Acidophils (%)
N.S	5.00 ± 0.40 a	5.00 ± 0.48 a	5.00± 0.41 a	5.00 ± 0.58 a	5.25 ± 0.48 a	Second (after 90 days)
N.S	1.00 ± 0.58 a	1.25 ± 0.25 a	1.50 ± 2.29 a	1.50 ± 0.28 a	1.50 ± 0.29 a	First (after 45 days)	Basophils
N.S	1.75 ± 0.25 a	1.00 ± 0.58 a	1.50 ± 0.29 a	1.50 ± 0.28 a	1.50 ± 0.29 a	Second (after 90 days)
N.S	54.25± 0.85a	53.50± 0.65 a	53.75± 0.85 a	52.75±0.25 a	52.25±0.25 a	First (after 45 days)	Lymphocytes
*	55.50± 0.65a	55.00± 0.41ab	53.25± 0.75ab	52.75±0.25 b	50.50±0.19 c	Second (after 90 days)
N.S	5.00 ± 0.58 a	5.25 ± 0.25 a	5.00 ± 0.58 a	5.00 ± 0.58 a	5.00 ± 0.57 a	First (after 45 days)	Mononuclear white blood cells
N.S	5.75 ± 0.25 a	5.00 ± 0.57 a	5.25 ± 0.25 a	5.00 ± 0.58 a	5.50 ± 0.29 a	Second (after 90 days)

 

Findings from this research matched Song and Shen (2020) because they found no significant changes in red blood cell indices for goats that received zinc supplements at 30, 60, and 90 mg/kg dry matter over 30 days compared to those in the control group. Similarly, Research by Nematpoor et al. (2021) demonstrated that administering 1500 mg of zinc per dairy cow daily throughout a 42-day lactation period did not produce significant changes in red blood cell indices (MCV, MCH, MCHC).

White blood cells and differential count

Table 4 showed that treatment with Q10 enzyme co-adjuvant and zinc methionine did not affect white blood cell counts in Awassi lambs after 45 days of treatment (first period). The second period (after 90 days of treatment) showed significant differences (P ≤ 0.05) with treatments three and five having a significant reduction compared to treatments one and two but remained statistically similar to treatment four. The outcomes align with findings by Yusuf et al. (2023) observed that Dwarf goats in West Africa showed a significant reduction in total white blood cell count when fed with 300 mg/kg of nano zinc oxide. Manimaran et al. Research by Manimaran et al. (2022) found no significant changes in total white blood cell counts among Osmanabadi goats that received daily doses of 100 mg of copper sulphate and 40 mg of zinc oxide.

The values represent the means ± standard error. N.S. indicates that there are no significant differences (P ≥ 0.05). (*) denotes significant differences (P ≤ 0.05). T1 = Control, T2 = Enzyme Coenzyme Q10 25 mg/animal, T3 = Enzyme Coenzyme Q10 50 mg/animal, T4 = Enzyme Coenzyme Q10 25 mg/animal + 150 mg/animal Zinc Methionine, T5 = Enzyme Coenzyme Q10 50 mg/animal + 150 mg/animal Zinc Methionine.

The differential white blood cell count in Awassi sheep showed no significant treatment effects on neutral, basophilic, eosinophilic, and mononuclear cells after 45 days of treatment (Table 4). The second period, after 90 days of treatment (second period), showed significant differences (P ≤ 0.05) in neutral white blood cell percentages, which decreased significantly in animals receiving the fifth treatment compared to those receiving the first and second treatments but remained unchanged compared to those treated with the fourth treatment (Table 4).

Both the third and fourth treatments demonstrated marked reductions when compared to the control group,yet showed no statistically relevant change compared to the second treatment. The elevated levels of lymphocytic white blood cells in animals receiving the fifth treatment compared to both the control group and the second treatment (Table 4). could result from the combined effects of zinc and co-adjuvant enzyme Q10. Zinc significantly activates the immune system by supporting thymus development and bone marrow maturation, according to Goswami et al. (2005). Zinc activates thymulin from the thymus gland, which binds tightly to Tlymphocyte receptors and stimulates the growth and activity of T lymphocytes across different lymphoid tissues throughout the body (Prasad, 2008). Zinc serves as an antioxidant to shield cells against free radical toxicity while boosting mineral absorption essential for blood cell function (Sanchez et al., 2009).

Table 4 demonstrates that there were no significant differences (P ≥ 0.05) between the five treatments for the stress index throughout the initial treatment period of 45 days. The fifth treatment, followed by the fourth and third treatments, displayed significant index value reductions (P ≤ 0.05) compared to controls throughout the second 90-day period, while the second treatment showed no significant stress index differences when compared to controls.

CONCLUSIONS

In conclusion, this study shows that treating Awassi lambs with a mixture of zinc methionine and coenzyme Q10 gave the best results related to production indicators and improved immune status through increasing the percentage of lymphocytes and decreasing the percentage of neutrophils. In addition, the long duration of treatment with coenzyme Q10 and zinc methionine had a positive effect on most of the studied traits.

ACKNOWLEDGMENTS

The researchers extend their sincere gratitude to the Department of Animal Production, College of Agriculture, Tikrit University, for their support in providing all the necessary materials to complete this study.

Novelty Statement

The authors declare that no generative artificial intelligence or AI-assisted techniques were used in the preparation, analysis, or writing of this manuscript.

AUTHOR’S CONTRIBUTION

AAFA-J: Conceptualization, investigation, supervision, validation, writing review and editing. NBA: Formal analysis, methodology, investigation, writing original draft. MAA: Data curation, investigation, writing original draft, project administration.

Generative AI and AI-assisted technology statement

We, the authors, declare that we did not use any artificial intelligence tools in writing the manuscript

Conflict of interest

The authors declare no conflict of interest with any financial, personal, or other relationships with other people or organizations related to the material discussed in the manuscript.

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