Effects of body condition score and trace minerals supplements on lactation performance and blood indices of transition dairy ewes

As an integral part of energy metabolism and immunity, adipose tissue supports lactation’s metabolic demand acting like an energy buffer. In late gestation, ewes with positive energy balance have positive associations with body condition score (BCS), lipid anabolic metabolism might experience oxidative stress. The current study aimed to evaluate the effect of trace minerals (TM) supplementation and different Body Condition Score (BCS) levels on milk production and blood parameters of transition dairy ewes. To achieve the aim, seventy-two dairy ewes (BW = 70.2 ± 0.60 kg, BCS = 3.44 ± 0.2 and parity = 3) were randomly allotted in a 2×3 factorial design of six groups (n = 12/group) according to BCS level (≤3; 3 to 4; ≥4, 2 replications) to be supplemented with organic and inorganic TM (OTM vs. ITM). Milk yield was recorded daily and sampled weekly for fat, protein, lactose, total solids (TS), and milk urinary nitrogen (MUN) analysis. Blood collection occurred on days −30, −20, −10, +24h, +10, +20, and +30 relative to expected lambing whereas the body weight (BW) and BCS change were accessed weekly. Results showed that BCS significantly affected BW and BCS changes during the experimental period (p < 0.01). BCS, TM, and time interaction affect significantly DMI (p < 0.01). Moreover, the same finding was observed for protein (p = 0.03), lactose (p < 0.01), MUN (p < 0.01), and TS (p < 0.01); in both groups with the highest values in BCS ≥ 4. MDA and TOAC were significantly affected by TM supplementation (p = 0.02) and time (p = 0.01), respectively. The cholesterol and ALP concentrations in plasma were affected by BCS and TM; the highest values were observed in BCS ≥ 4 group (OTM = 96.03 mg/dL; ITM = 84.8 mg/dL, p < 0.01) and in BCS from 3 to 4 (OTM = 48.2 U/L; ITM = 46.6 U/L; p = 0.02) for cholesterol and ALP, respectively. TM and BCS interaction influenced cholesterol concentration in the plasma (p = 0.06). TM supplementation significantly influenced plasma ALP; the ITM group had the highest compared to the OTM group (p < 0.05). In conclusion, the results showed that replacing ITM with OTM caused modest improvements in the performance and blood traits of transition ewes. As an integral part of energy metabolism and immunity, adipose tissue supports lactation's metabolic demand acting like an energy buffer. In late gestation, ewes with positive energy balance have positive associations with body condition score (BCS), lipid anabolic metabolism might experience oxidative stress.

1 Introduction

During the transition period, there is a notable decline in the intake of essential nutrients, such as trace minerals, and a negative energy balance (NEB), leading to diminished physiological performance, impaired immune function, and heightened risk of disease. Essential trace minerals, such as Cu, Zn, and Mn are crucial for body, and their insufficiency in the diet of livestock lead to health problems swayback, parakeratosis, skeletal deformities (Suttle, 2010). To prevent such shortages, dairy animals are routinely supplemented with the trace mineral sources (Daniel et al., 2020). An effective strategy for supplementing trace minerals (TMs) to tissues could alleviate the detrimental impact of metabolic stress in the transition period and positively influence lactation and reproductive efficiency (Mion et al., 2022). Although TM constitute a minor component of the diet and are found in low concentration in tissues, they are essential for various biological processes, including the activity of several enzymes and transcription factors (Goff, 2018).

Various physical attributes, body condition score (BCS) and body mass indices (BMI), are standard methods in animal husbandry and breeding strategies (Birteeb and Lomo, 2015; Kenyon et al., 2014; Ptáček et al., 2018). In dry land areas, shortage of nutrients and water resources, along with harsh environmental conditions, contribute to poor BCS, posing a major constraint to sheep farming (Sejian et al., 2010). Body condition scoring (BCS) is a qualitative assessment method employed to determine the physiological status of a sheep flock, functioning as a strategic indicator for producers seeking to optimize flock productivity and management efficiency (Lowman et al., 1976). Moreover, this tool provides an accurate representation of the flock’s overall BCS, allowing producers to make informed adjustments to dietary intake in accordance with the animal’s metabolic demands (Sezenler et al., 2011).

Maintaining an appropriate BCS is crucial for sustaining the health and productivity of dairy cows within the herd (Dale et al., 2017). The recommended BCS for dairy animals typically falls within the range of 3.0 to 3.5 on a 5-point scale, a range considered optimal for maintaining health, reproductive performance, and overall animal welfare (Roche et al., 2009). In conjunction with live weight and size measurements, BCS measurement is of significant importance and may help mitigate errors that commonly arise during critical physiological stages, such as gestation and lactation (Angeles Hernandez et al., 2018; Oldham et al., 2011). Short-term variations in body mass due to factors such as gastrointestinal fill, wool length, or moisture content do not influence the results obtained the BCS results (Kenyon et al., 2014; Oldham et al., 2011).

Supplementation with higher levels of inorganic or organic trace mineral sources in dairy animals has been predominantly associated with positive outcomes, such as enhanced milk production (Rabiee et al., 2010), optimized reproductive function (Rabiee et al., 2010), reduced somatic cell count (Kellogg et al., 2004), and reduced incidence of hoof disorders (Overton and Yasui, 2014). Nonetheless, there is a paucity of published data regarding the biological effects of organic trace mineral supplementation, including zinc, manganese, copper, and cobalt, particularly during the transition period of dairy animals (Osorio et al., 2016). Despite evidence suggesting that organic trace mineral supplementation induces only moderate effects on glucose and fatty acid metabolism (Nayeri et al., 2014), there is a growing rationale to investigate their potential benefits in alleviating oxidative stress and regulating inflammatory pathways (Nayeri et al., 2014). Additionally, during the postpartum period, the development of inflammatory conditions and associated disorders, such as ketosis and mastitis is commonly observed and is thought to facilitate the reallocation of trace minerals, including Zn, Fe, and Cu from the systemic circulation to various tissues (Zhang et al., 2024).

Several studies have examined the effects of organic trace mineral (OTM) supplementation on dairy cow’s performance; however, substantial variations in experimental methodologies, e.g., the use of OTM in addition to existing mineral premixes or as a partial or complete replacement for inorganic trace minerals (ITM), along with variable outcomes, have led to inconsistencies in findings (Mion et al., 2022). For instance, in their study (Yasui et al., 2019), found that replacement of ITM with OTM sources did not impact the mid-lactation performance of dairy cows. In contrast, Nocek et al. (2006) indicated higher milk production as a consequence of replacing ITM with OTM. Partial substitution of inorganic trace minerals, including Co, Cu, Mn, and Zn, with organic forms during the transition period has been shown to influence the physiological and productive performances in dairy cow (Osorio et al., 2016; Siciliano-Jones et al., 2008). The widespread use of partial replacement strategies in the dairy industry complicates the interpretation of related research findings, as outcomes are often influenced by confounding variables, including the type of mineral source, the level of inclusion, and their combined or interactive effects (Mion et al., 2022).

However, the effects of different types of trace minerals and body condition scores on performance and blood indices of transition dairy ewes have not been investigated. Thus, we hypothesized that TM supplementation during the transition period would affect differently the metabolic challenges and the performances of dairy ewes with different BCS. In the present study, we aimed to evaluate the effects of the different BCS and TM supplements on blood metabolites, metabolic status, and production performance of transitional dairy ewes.

2 Materials and methods

2.1 Animals and experimental procedure

The current experiment was carried out at the University of Tehran, Faculty of Agriculture Research Station, Alborz, Iran. The animals were cared according to the guidelines established by the Iranian Committee of Animal Care (1995, no. 19293).

Seventy-two pregnant Qhezel dairy ewes with 70.2 ± 0.60 kg and 3.44 ± 0.2 of average body weight (BW) and body condition score (BCS, scale 0–5) respectively were selected and enrolled 30 ± 2 days before the expected parturition. Dairy ewes were allocated to six groups (n = 12 ewes per group) in 2 × 3 factorial arrangement of treatments according to BCS as follows: (I): (1) BCS ≤ 3.0, (2) BCS of 3.0 to 4.0, (3) BCS ≥ 4.0 and (II): (4) BCS ≤ 3.0, (5) BCS of 3.0 to 4.0, (6) BCS ≥ 4.0. All the ewes of (I) and (II) were supplemented with inorganic trace mineral (ITM) and chelated organic trace mineral (OTM; Bonza, Sodour Ahrar Shargh Co, Tehran, Iran), respectively. The supplementation of 1 g of OTM provided 51 mg Zn, 28 mg Mn, 18 mg Cu, 8 mg Fe, 1.9 mg Co, 0.5 mg Cr, and 0.3 mg Se per kg DM of diet. For the ITM treatment, equivalent amounts of trace minerals were supplied using inorganic sources: 159 mg zinc sulfate (32% Zn), 82 mg manganese sulfate (34% Mn), 90 mg copper sulfate (20% Cu), 42 mg iron sulfate (19% Fe), 9 mg cobalt sulfate (19.5% Co), 2.5 mg chromium chloride (19.5% Cr), and 1 mg sodium selenite (42% Se) (Rajaei-Sharifabadi et al., 2024). During the whole period, ITM diets replaced 100% of the requirements with OTM supplements. Approximately 42 days prior to the expected lambing date, the experimental transition dairy ewes were transported to the research station. The animals underwent an acclimatization period to the new environment, including the pen and feed, which lasted one week. The experiment proceeded from 28 days before lambing to 60 days after lambing (which is referred to as days in milk (DIM). According to the procedure of Russel et al. (1969), the index of BCS (on a 5-point scale) was evaluated at different times during the study through meticulous palpation of the spinous and transverse processed in the lumber region, located directly posterior to the last rib. In addition, to access the BW change, all ewes were weighed individually every week before morning feeding. Around 147d of gestation, ewes were observed twice daily (morning and afternoon) to identify the signs of lambing. Once the ewes shown the lambing signs, they were transferred in individual ventilated pens of 1.8 × 1.6 m². The floors were concrete and periodically cleaned. The water was provided ad libitum from automatic waterers and salt blocks were available in each pen. Diets were offered daily at 0800 and 1600h in the form of total mixed ration (TMR), and were formulated to meet the nutrient requirements (Table 1; N.R.C.C (2007)), except for the experimental trace minerals. The ewes were fed ad libitum with a prediction of 10% of refusals.

Table 1

Table 1. Ingredient and chemical composition of experimental diets for ewes in pre- (−21 d) and post- (+60 d) partum (% of DM)¹.

2.2 Milk yield and components

The ewes were milked twice a day at 5:30 AM and 3:30 PM using DeLaval VMS™ Series milking system, and daily production was recorded. Milk yield and composition were recorded over three consecutive days per week until 30 days post-lambing. At each milking, samples were collected from each animal in the tubes preserved with 2-bromo2-nitropropane-1,3 diol (Broad Spectrum Microtabs II; Advanced Instruments Inc.) and kept at -20 °C until shipped overnight to the milk analysis laboratory (Isfahan, Iran). Milk concentrations of fat, true protein, lactose, milk urea nitrogen (MUN), and total solids (TS) were analyzed using a Fourier Transform Mid-Infrared (FT-MIR) spectrophotometer (MilkoScan FT1, Foss Analytical, Hillerød, Denmark). The analysis leverages the specific absorption of mid-infrared wavelengths by chemical bonds in each component (Sjaunja et al., 1991). For MUN, the instrument was calibrated against the standard enzymatic reference method (Roseler et al., 1993). The coefficient of variation for duplicate analysis was below 3%, confirming high analytical precision.

2.3 Blood parameters

Blood samples (10 mL) were collected on days -30, -20, -10, +1, +10, +20, and +30 relative to the expected lambing time. Samples were obtained via coccygeal venipuncture using tubes containing potassium-EDTA. The tubes were placed immediately on ice and maintained at 4 °C for at least 2 h to allow coagulation. The samples were then centrifuged at 3000×g at 4 °C for 30 min to collect the plasma, which was then frozen at −20 °C until further analysis. Blood metabolic parameters (glucose, albumin, and total protein) were determined by spectrophotometer using a commercial kit (Pars Azmon, Iran). The serum samples were also analyzed with an Auto Analyzer 7020 instrument (Hitachi High Technologies Corporation, Tokyo, Japan) using commercially obtained colorimetric detection kits (PERKINELMER35-Pars Azmon) for non-esterified fatty acid (NEFA), β-hydroxybutyric acid (BHBA), triacylglycerol (TG), cholesterol, gamma-glutamyl transpeptidase (GGT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), albumin (Alb), total antioxidant capacity (TOAC), and malondialdehyde (MDA). Before beginning each analytical session, the standards furnished in the assay kits were used to calibrate the multiparameter analyzer. After setting the calibration curve, 2 multiparameter control sera were used to verify internal accuracy and were considered satisfactory when the measured value deviated by no more than 3.00% from the manufacturer’s declared values. Plasma samples were used for oxidation parameters T-AOC (Dinardo et al., 2022) and MDA analysis (Forte et al., 2025).

2.4 Statistical analysis

All data collected was analyzed using PROC MIXED procedure of SAS software (version 9.4, SAS Institute Inc., Cary, NC). The experimental model was a 2 × 3 factorial design, where feeding diets (trace mineral supplements) and BCS were the fixed effects. The model was:

$$Y_{\text{ijk }}={\text{µ}}_{}+F_{\text{i }}+ L_{\text{j }}+T_{\text{k }}+{\left(F*L\right)}_{\text{ij}}+{\left(F*L*T\right)}_{\text{ijk}}+{\text{ϵ}}_{\text{ijk }}$$

where Y_ijk = dependent variable, µ = overall mean, F_i = fixed effect of trace minerals, L_j = fixed effect of BCS, T_k = fixed effect of time, FL_ij = interaction between trace minerals and BCS, FLT_ijk = interaction between minerals, BCS, and time, and ε_ijk = residual error. The fixed effects of prepartum trace mineral sources were included in the model for postpartum data. The model has fixed effects for time and treatment for prepartum data. First-order autoregressive was the covariate structure used for analysis because it resulted in the smallest Bayesian information criterion for most measured variables. Animals were included as a random effect. All residuals were tested for normality using the UNIVARIATE procedure of SAS. The significance threshold was set at P ≤ 0.05; trends were declared at 0.05 < P ≤ 0.10.

3 Results

3.1 Body condition score and body weight changes

The effect of dietary supplements of different mineral sources on body condition score (BCS) and body weight change during the transition period and early lactation of dairy ewes are presented in Table 2; Figure 1. The interaction between BCS and TM did not affect significantly BW and BCS parameters (p > 0.05). However, the BCS affect significantly body weight and body condition score change (p = 0.01) except the total period of BW (p = 0.38). In general, BW and BCS of ewes decreased from – 28 d before and +75 d after parturition for both groups fed with OTM and ITM and was more pronounced in BW than BCS (Figure 1). In addition, BW and BCS changes were increasing from BCS₁ to BCS₃ (BSC₁ < BCS₂ < BCS₃) for both groups fed with OTM and ITM.

Table 2

Table 2. Effects of different sources of trace minerals and BCS on body weight (BW) and body condition score (BCS) changes during the transition period and early lactation in dairy ewes ¹.

Figure 1

Figure 1. Effects of different sources of trace minerals and BCS on body weight (BW) and body condition score (BCS) changes during the transition period and early lactation in dairy ewes. Ewes were fed one of 6 treatments: (1) BCS ≤ 3.0 plus inorganic trace mineral supplements (ITM), (2) BCS of 3.0 to 4.0 plus inorganic trace mineral supplements (ITM), (3) BCS ≥ 4.0 plus inorganic trace mineral supplements (ITM), (4) BCS ≤ 3.0 plus organic trace mineral supplements (OTM), (5) BCS of 3.0 to 4.0 plus chelated trace mineral supplements (OTM), (6) BCS ≥ 4.0 plus chelated trace mineral supplements (OTM). Values are means, with SE represented by vertical bars.

3.2 Milk production traits

The effect of different sources of trace minerals and BCS on DMI, Milk yield, and milk composition during the transition period and early lactation of dairy ewes are reported in Table 3; Figure 2. Significant differences were observed for the interaction between BCS, TM, and time for DMI (p = 0.05); the highest amount was observed for OTM compared to inorganic trace mineral (ITM) with increasing the BCS. Moreover, during the time, there was an interaction between BCS and TM supplementation on the percentage of protein (p = 0.03), lactose (p < 0.01), MUN (p < 0.01), and TS (p < 0.01); in both groups, the ewes with BCS₃ had the highest amounts of milk components. Regarding the percentage of milk fat, there was not any interaction between TM sources and various BCS scores (p = 0.38).

Table 3

Table 3. Effects of different sources of trace minerals and BCS on DMI, Milk yield, and milk composition during the transition period and early lactation of dairy ewes¹.

Figure 2

Figure 2. Effects of different sources of trace minerals and BCS on milk composition during the transition period and early lactation of dairy ewes. Dietary treatments were of: Ewes were fed one of 6 treatments: (1) BCS ≤ 3.0 plus inorganic trace mineral supplements (ITM), (2) BCS of 3.0 to 4.0 plus inorganic trace mineral supplements (ITM), (3) BCS ≥ 4.0 plus inorganic trace mineral supplements (ITM), (4) BCS ≤ 3.0 plus organic trace mineral supplements (OTM), (5) BCS of 3.0 to 4.0 plus chelated trace mineral supplements (OTM), (6) BCS ≥ 4.0 plus chelated trace mineral supplements (OTM). Values are means, with SE represented by vertical bars.

3.3 Energy and oxidative stress indices

Effects of different sources of trace minerals and BCS on energy, inflammation, and stress oxidative indices during the transition period and early lactation of dairy ewes are indicated in Figure 3; Table 4. Except MDA and TOAC which were significantly affected by TM supplementation (p = 0.02) and time (p = 0.01) respectively, all other variables such as glucose, BHB, NEFA, TP, BUN, and albumin were not affected either by TM, BCS, time separately or their interaction (p > 0.05). The experimental TM sources were affected significantly by MDA, where the ITM source had the highest value compared to the OTM source (p = 0.02). Although the TM supplements did not have effect on the TOAC (p = 0.95), the parameter was affected during the time (p = 0.01).

Figure 3

Figure 3. Effects of different sources of trace minerals and BCS on energy, inflammation, and stress oxidative indices during the transition period and early lactation of dairy ewes. Ewes were fed one of 6 treatments: (1) BCS₁ ≤ 3.0 plus inorganic trace mineral supplements (ITM), (2) BCS₂ of 3.0 to 4.0 plus inorganic trace mineral supplements (ITM), (3) BCS₃ ≥ 4.0 plus inorganic trace mineral supplements (ITM), (4) BCS₁ ≤ 3.0 plus organic trace mineral supplements (OTM), (5) BCS₂ of 3.0 to 4.0 plus chelated trace mineral supplements (OTM), (6) BCS₃ ≥ 4.0 plus chelated trace mineral supplements (OTM). Values are means, with SE represented by vertical bars.

Table 4

Table 4. Effects of different sources of trace minerals and BCS on energy, inflammation, and stress oxidative indices during the transition period and early lactation of dairy ewes¹.

3.4 Liver function

The Effects of different sources of trace minerals and BCS on liver function indices during the transition period and early lactation of dairy ewes are presented in Table 5; Figure 4. The results showed that BCS and TM affected only the cholesterol and ALP content in the plasma; the highest values were observed in BCS₃ group (OTM = 96.03 mg/dL; ITM = 84.8 mg/dL; p < 0.01) and in BCS₂ (OTM = 48.2 U/L; 46.6 U/L; p = 0.02) for cholesterol and ALP, respectively. In addition, the parameters of liver function indices were significantly affected over time except gamma-glutamyl transferase (GGT). TM and BCS interaction tended to influence cholesterol concentration in plasma (p = 0.06) whereas TM supplementation (p = 0.11) and BCS (p = 0.07) tended to affect plasma VLDL. TM supplementation significantly influenced plasma ALP; the inorganic trace mineral (ITM) group had the highest compared to the OTM group (p < 0.05). TM supplementation and BCS tended as well to affect plasma ALT concentration (p = 0.10).

Table 5

Table 5. Effects of different sources of trace minerals and BCS on liver function indices during the transition period and early lactation of dairy ewes¹.

Figure 4

Figure 4. Effects of different sources of trace minerals and BCS on liver function indices during the transition period and early lactation of dairy ewes. Ewes were fed one of 6 treatments: (1) BCS₁ ≤ 3.0 plus inorganic trace mineral supplements (ITM), (2) BCS₂ of 3.0 to 4.0 plus inorganic trace mineral supplements (ITM), (3) BCS₃ ≥ 4.0 plus inorganic trace mineral supplements (ITM), (4) BCS₁ ≤ 3.0 plus organic trace mineral supplements (OTM), (5) BCS₂ of 3.0 to 4.0 plus chelated trace mineral supplements (OTM), (6) BCS₃ ≥ 4.0 plus chelated trace mineral supplements (OTM). Values are means, with SE represented by vertical bars.

4 Discussion

4.1 Body condition score and body weight changes

In the current study, either trace minerals (TM) source or body condition score (BCS) did not affect the BCS and body weight (BW) of transitional dairy ewes (p > 0.05). Also, the parameters were not affected by the interaction between TM and BCS (p > 0.05; Table 2). However, during the time, the OTM and ITM resulted in the increasing BW and BCS change with increasing BCS (BSC₁ < BCS₂ < BCS₃). The positive effects of TM sources on BW and BCS change and the close relation between BCS and BW have been established, which could be influenced by changes occurring throughout a production cycle, breed, and age (Vatankhah et al., 2012). For instance, the significant decrease in ewes’ BW has been reported in the last months of gestation (Semakula et al., 2021). Moreover, a study on Aragonesa sheep (Teixeira et al., 1989) found a curvilinear relationship between BW and BCS. Additionally, lack of a balanced diet during the transition period (final stages of gestation and early postpartum) can disrupt metabolic functions, some variations of BW, and a decrease in BCS (Yıldırır et al., 2022).

4.2 Dry matter intake and milk traits

Milk yield is an important indicator of the production performance of dairy animals, which is influenced by factors such as the pre-partum energy intake, oxidative stress, and inflammation (Tosto et al., 2021). Over time, experimental diets significantly influenced DMI, milk yield, and milk components (p < 0.01), except for the percentage of fat (p = 0.38). According to Mion et al. (2022), organic trace mineral (OTM) supplementation can modestly improve DMI during the transition period, highlighting the importance of developing nutritional and managerial strategies to counteract periparturient declines in DMI. Consistent with our findings, Osorio et al. (2016) observed a tendency for increased postpartum DMI when inorganic minerals (Co, Cu, Mn, and Zn) were partially replaced with organic trace mineral (OTM) sources. In a study on pre-partum dairy cows, linearly increasing the rate of Zn-methionine inclusion from 0 to 60 mg/kg of DM increased DMI (Chen et al., 2020).

The available data indicate that elevated DMI and BCS are likely critical determinants of increased milk yield and milk composition (Roche et al., 2009). In this case, Ghavipanje et al. (2021) demonstrated that variability in milk yield is primarily accounted for by differences in energy intake and DMI, thereby suggesting that increased energy intake promotes conditions conducive to optimal milk production. According to da Silva et al. (2023), the improvement in animal productivity in the supplemented group with TM may be partially explained by a greater DMI during the postpartum period (16.8 and 18.3 kg/d for CON and TM group, respectively). Indeed, Ballou et al. (2009) emphasized that maintaining DMI during early lactation is critical, as it may lead to improved energy balance and enhanced milk yield in dairy ruminants.

Studies investigating the effects of TM sources on milk production have reported inconsistent results, which are primarily attributed to the heterogeneity of TM sources and differences in experimental design (Mion et al., 2022). Although the replacing of ITM with OTM sources had beneficial effects on DMI during transition to lactation while milk yield was not improved. In agreement with our study, different levels of TM did not significantly affect the milk performance of dairy cows (Casper et al., 2021; Yasui et al., 2019). Correspondingly, replacing hydroxyl TM with sulfate TM sources of Cu, Mn, and Zn showed no significant changes in the yield or concentration of milk fat and protein (Faulkner et al., 2017). Furthermore, Daniel et al. (2020) described no differences in DMI and yields of milk, fat, and protein when replacing 30% of supplementary STM or HTM (Cu, Mn, and Zn) with OTM in the diet of mid-lactation cows. For complete replacements (Yasui et al., 2019), reported no difference in milk production, milk components, and DMI when mid-lactation multiparous cows were fed STM (Cu, Mn, and Zn) or OTM for 6 weeks. In contrast, Siciliano-Jones et al. (2008) reported a tendency for greater milk and ECM yields when partially replacing STM (Co, Cu, Mn, and Zn) by OTM during the transition period. Similarly, Osorio et al. (2016) reported beneficial effects on milk production when partially replacing STM (Co, Cu, Mn, and Zn) by OTM sources through oral boluses during the transition period. The difference in milk production between the studies is likely a result of changes in diet digestibility, changes in energy and nutrient partitioning, difference in experimental design to replacement of ITM with OTM sources, variety in feeding method (top-dressed or TMR), and variable duration of supplementation. Thus, additional research is needed to evaluate potential differences in TM requirements, utilization, and physiological responses to different supplementary TM sources and dietary inclusion levels in transition dairy ewes.

4.3 Energy and inflammation

Our results showed that the ewes with higher BCS in both groups fed with OTM and ITM had lower glucose and higher NEFA concentrations (p = 0.07 and p = 10, respectively). This findings was in disagreement with the findings of Wu et al. (2020). However, it is known that glucose is an important nutrient during the last stages of pregnancy since it acts as a substrate for the lactose production and provides energy for both the pregnant animals and their offspring. On the other hand, higher NEFA in plasma is a normal physiological adaptation in the transition period to provide energy for milk production (Ospina et al., 2010). As explained by Ospina et al. (2010), an increase in circulating NEFA and BHBA is expected during the transition period of dairy cows. This is due to their natural adaptation to high energy demands, which render cows in a high lipolytic state until energy intake catches up with the energy requirement to sustain milk production.

To adapt to the special physiological state of nutrient deficit in the transition period, dairy animals normally experience an increase in adipose tissue lipolysis due to changes in hormones, such as insulin (Tosto et al., 2021; Zamuner et al., 2020). Consequently, a large quantity of NEFA are released from adipose tissue into the circulation around parturition or in early lactation and are then transported to the liver where they can be oxidized to provide energy to the liver, partially oxidized to produce ketone bodies, or esterified to TAG (Tosto et al., 2021). Therefore, NEFA and BHBA are considered effective indicators of the energy status in transition dairy animals (Zamuner et al., 2020).

In addition, we observed no effect of TM on albumin and TOAC (Table 4). Previous studies have shown that replacing ITM with OTM supplementation has marginal effects on measurements associated with oxidative stress during the peripartum period of dairy animals (Batistel et al., 2017; Yasui et al., 2019). However, other studies have declared that OTM supplementation enhances the immune competence and health of the animals; this phenomenon may be related to the fact that OTM supplementation promotes the proliferation and differentiation of lymphocytes and increase the number of plasma cells, reducing inflammation and enhancing the immune capacity of the body (Palomares, 2022; Tanuwiria et al., 2022). Additionally, trace minerals, such as manganese, zinc, copper, and selenium, enhance humoral and cell-mediated immune responses, and maintain oxidative balance in the body (Palomares, 2022).

Blood TP and Alb were similar between the OTM and ITM groups, indicating that they provide an immune-enhancing environment that is beneficial to improve the metabolism of transition dairy sheep (Wang et al., 2023). On the other hand, Alb in sheep blood is correlated significantly and positively with TP concentration (M. Abdelsattar et al., 2022); it is a marker of liver function, and higher values of Alb imply improved liver function (Shah et al., 2020). Additionally, the protein content in the serum is closely linked to protein uptake and metabolism, as many proteins in the serum act as molecular carriers of nutrients, hormones, or metals and are extensively involved in a wide range of functions in body (Bern et al., 2015). Consequently, the lower TP indicates a poorer health condition of sheep, which increases the proportion of protein dealing with harsh environments or immune depletion, and it is not conducive to improving nutrient utilization; however, in the current study, we did not observe any differences between the two trace mineral supplements on the variables.

4.4 Liver function

The concentration of AST and ALT in plasma are commonly used to evaluate liver function (Giannini et al., 2005); involving reduced activity. These enzymes in transition dairy animals results in a healthier liver (Ghavipanje et al., 2021). However, in the current study, we did not observe any significant difference between the treatments on AST and ALT (Table 5).

The lipid and lipoprotein metabolism of lactating dairy ruminants can be disturbed by insulin resistance (Contreras et al., 2017), especially when they have higher BCS during the late pregnancy and early postpartum stages (Akbar et al., 2015). Additionally, mobilization of lipid in NEB reflecting lipid indicators, such as contents of TG, total cholesterol, and VLDL (Đuričić et al., 2015; Mushawwir et al., 2024). In our study, we did not find significant difference in TG concentration during the transition period; however, the concentration of VLDL tended to increase with the higher BCS scores. In disagreement with our study, Đuričić et al. (2015) have found significantly decreased of TG concentration during early lactation from day 19 until day 60 in cows with optimal and higher BCS scores. In addition, Sezenler et al. (2011) indicated a reduction in TG concentration during the first 8 weeks of lactation; this could be ascribed to increased accumulation of TG in hepatic cells in the early postpartum (Bremmer et al., 2000), as well as the increased needs of the mammary gland for milk fat synthesis (Bernard et al., 2008).

During the transition period, the BCS × TM tended to interacted each other to influence the cholesterol concentration; ewes with higher BCS had higher contents of cholesterol in plasma (P = 0.06). Folnožić et al. (2015) reported a higher cholesterol on days 26 and 60 of lactation in both optimal and adipose cows compared to values from late pregnancy to 5d post-partum. Also, Pysera and Opalka (2000) showed a lower concentration of cholesterol during late pregnancy, which is probably due to the increased needs for the growth and development of fetus, in addition to the requirements for the synthesis of steroid hormones in the ovaries (Mushawwir et al., 2022; Pysera and Opalka, 2000).

5 Conclusion

In conclusion, this study shows that ewes fed OTM performed better in milk composition, such as percentage of fat and protein, than those fed ITM. Additionally, the ewes fed OTM had better plasma energy indices than group receiving ITM treatment; we observed higher glucose and lower NEFA in the OTM group than in the ITM group. Our results showed that ITM supplementation significantly increased ALP concentration. These results indicate that OTM supplementation is a beneficial strategy to improve dairy ewes transition through different mechanisms. However, additional research is necessary to assess how TM supplementation strategies and various BCS affect the metabolic state and performance of transitional dairy sheep under various management and oxidative stress scenarios.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The animal study was approved by Iranian Committee of Animal Care (1995, no. 19293) of the University of Tehran, Faculty of Agriculture Research Station, Alborz, Iran. The study was conducted in accordance with the local legislation and institutional requirements. No potentially identifiable images or data are presented in this study.

Author contributions

HM: Data curation, Visualization, Validation, Methodology, Conceptualization, Project administration, Software, Investigation, Formal analysis, Writing – review & editing, Writing – original draft. MG: Writing – review & editing, Resources, Investigation, Software, Writing – original draft, Conceptualization, Funding acquisition, Supervision, Visualization, Data curation, Validation, Project administration, Formal analysis, Methodology. DK: Software, Data curation, Methodology, Visualization, Validation, Investigation, Writing – review & editing. AZ: Investigation, Funding acquisition, Validation, Resources, Writing – review & editing, Methodology, Data curation, Supervision, Project administration. AF: Writing – review & editing, Funding acquisition, Resources, Project administration, Writing – original draft, Formal analysis, Methodology, Data curation, Investigation, Validation, Conceptualization, Supervision. VP: Writing – review & editing, Investigation, Data curation, Methodology, Validation. SK: Methodology, Writing – review & editing, Data curation, Investigation, Validation. MN: Methodology, Data curation, Writing – review & editing, Investigation, Validation. AA: Methodology, Data curation, Project administration, Investigation, Validation, Writing – review & editing, Resources, Funding acquisition, Supervision.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This research received the funding of the University of Tehran (grant number 9028197).

Conflict of interest

Author SK and MN were employed by the company Sodour Ahrar Shargh Co.

The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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