Effects of Total Mixed Ration on Blood Biochemistry, Productivity, and Reproduction in Bangladeshi Frisian Crossbred Lactating Cows

Effects of Total Mixed Ration on Blood Biochemistry, Productivity, and Reproduction in Bangladeshi Frisian Crossbred Lactating Cows | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of Total Mixed Ration on Blood Biochemistry, Productivity, and Reproduction in Bangladeshi Frisian Crossbred Lactating Cows Md. Abdur Rahim, Mst. Sanjida Safawat, Debasish Raha, Uttam Kumar Roy, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7972443/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background This study assessed the impact of the total mixed ratio (TMR) on milking cow productivity and reproductive and serum biochemical profiles and investigated the correlations between TMR nutrient values and cow traits. Results A total of 95 lactating cows were used and grouped into TMR1, TMR2 and TMR3 according to the TMR provided. The study revealed that all three meals had 96.3% dry matter, with TMR3 having the most nitrogen-free extract, crude fiber, and crude protein, whereas TMR-1 had the least protein, crude fiber, and neutral detergent fiber. Considering the nutritive values of the TMR provided to the lactating cows, crude fiber (CF), crude protein (CP), N-free extract, acid detergent fiber (ADF), and neutral detergent fiber (NDF) percentages significantly (p < 0.05) differed among the TMR subgroups. The study revealed no significant outliers in body weight, daily milk yield, lactation length, first day of peak yield, or duration of peak yield in cows in the TMR3 group. The cows in the TMR 1 group presented the greatest first-day pick yield after calving, daily milk output, lactation length, and pick yield duration. Daily milk output and lactation duration were moderately to strongly positively correlated with CP and CF. Reproductive indicators varied more than productive features did in Group TMR3 cows. However, the medians for age at first artificial insemination (AI), calving to first heat, first AI, and the calving interval were comparable across all groups. Energy- and protein-rich meals improved reproductive efficiency, whereas fat content had no effect. The research revealed that TMR2 cows had considerably lower magnesium levels than TMR1 and TMR3 cows did. AST levels were higher in TMR2 and TMR3 cows than in TMR1 cows, whereas ALP levels were lower in TMR2 cows. Body weight had a significant (p < 0.01) positive relationship with crude fiber% and NDF%, a negative relationship with crude protein%, nitrogen-free extract, and ADF% milk yield, a strong (p < 0.01) negative relationship with DM%, Ash%, crude fiber%, fat%, and NDF%, and a positive relationship with CP%, N-free extract%, and ADF. The results revealed a significant negative relationship between the duration of pick yield and N-free extract%, ADF%, triglyceride, alkaline phosphatase (ALP), and glucose contents and a positive relationship with crude protein% and NDF%. Calving to the first heat was significantly (p < 0.01) negatively related to TP and ALP and positively related to lactation duration (p < 0.01). Conclusion This study suggests that efficient ration formulation can enhance milk production, reproductive performance, and metabolic health in dairy herds of Frisian crossbred lactating cows in Bangladesh. Animal Science Total mixed ratio Serum biochemical profiles Frisian crossbred Production Reproduction Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Bangladesh has been experiencing the dairy revolution for the last five years. Farmers are pressured to provide sufficient milk due to the high demand for milk and milk products. A feeding standard is lacking due to inadequate scientific assessments of balanced rations in Bangladesh. This results in resource scarcity and insufficient understanding of feeding standards, hindering animal production performance. Traditional feeding strategies, characterized by selective feed intake, result in feed waste and inadequate nutrient utilization, adversely impacting ruminal digestion, absorption, and transit rates ( 1 ). Excessive concentrate intake in dairy cows increases the risk of ruminal acidosis. To combat this, total mixed ration (TMR) is used, which combines concentrate and forage in a balanced manner. Over the past 50 years, dairy cow feed has significantly transformed from traditional concentrates and forages to a comprehensive mixed ration due to its superior benefits. The TMR results in a well-rounded diet, a stable rumen environment, reduced weight loss, reduced rumen acidosis, and increased energy and protein consumption [1, 2, 3, 4]. Reproductive performance is a critical factor in the sustainability and profitability of dairy farms that employ TMR systems. Group housing with TMR feeding is the primary production system used on commercial dairy farms in developed countries ( 5 ). Successful reproduction involves resuming ovarian cyclicity postpartum, ovulation, fertilization, uterus restoration, embryo development, and pregnancy maintenance. Dietary formulation and feeding management can facilitate or interrupt these reproductive phases by altering metabolic profiles ( 6 ). Severe dietary deficits can decrease reproductive performance in high-yielding lactating cows, as they require more nutrients for reproduction. Nutrition is a pivotal technological element that can instigate remarkable transformations in the metabolic dynamics of animals. A lack of essential minerals, proteins, and vitamins in the nourishment of lactating cows leads to significant alterations in their metabolic processes. Metabolic profiles are crucial in assessing a cow’s nutritional and health status, as changes in components such as glucose, cholesterol, and TP can lead to reproductive failure ( 7 ). Standard biochemical profiles in lactating cows indicate good health and strong milk yield, whereas blood analysis can reveal nutritional discrepancies ( 8 ). However, biochemical indicators in a healthy herd are crucial for predicting diseases. Nevertheless, information on the relationships between blood biochemical parameters and dairy cow productivity and nutrition is limited in Bangladesh. A lack of feed and fodder contributes to high production costs in this country. Therefore, this study aimed to assess the productivity, reproductive parameters and serum biochemical profiles of Bangladeshi Frisian crossbred (LXFXF) lactating cows via TMR and to determine the relationships among their biochemical profiles, productive and reproductive parameters, and nutrient values. Method The study was conducted by the Department of Surgery and Obstetrics, Bangladesh Agricultural University, Bangladesh. This research focuses on the “selection of donor and recipient cows and heifers” under the research project titled “Speeding up genetic gain through embryo production and transfer for sustainable improvement of milk production in dairy cattle of Bangladesh (RP-A-01-26)”. The experimental design and all protocols related to the research project were approved by the Animal Welfare and Experimentation Ethical Committee [Ethical Approval Number: AWEEC/BAU/2023 (03)] of Bangladesh Agricultural University, Bangladesh. Animals and experimental approach The sample size for this study was 95 crossbred Frisian (LXFXF) lactating cows selected from a commercial dairy farm located in Rangpur, Bangladesh. Standard management practices, including deworming and vaccinations, were carried out following the farm schedule, and the experimental animals were kept in consistent housing and lighting. Machine milking was used to harvest milk twice a day, between 0500 and 0600 in the morning and between 1500 and 1600 in the evening. All the animals were maintained in the loose barn, which had free access to water and was provided with TMR. On the basis of the TMR types provided, all cows were grouped into TMR-1 (N=27), TMR-2 (N=43), and TMR-3 (N=25) groups. The data were collected on productive parameters, including body weight, milk yield, duration of pick yield, time of first day of pick yield after calving, lactation length, and reproductive parameters, including age of first AI; calving to first heat and calving to first service and calving interval; and serum biochemical profiles of total protein (TP), triglyceride (TG), cholesterol, alanine transaminase (ALT), aspartate transaminase (AST) and alkaline phosphatase (ALP), calcium, phosphorus, and magnesium. Laboratory analysis of blood serum Before blood collection, a clinical examination of all lactating cows was performed to ensure that the animals were free from infections. Blood was collected from the jugular vein by inserting a 19G needle attached to a 10 ml disposable syringe into the vein. The blood was transferred to a red-capped clot activator tube and centrifuged by a centrifuge for 15 minutes at 3000 rpm at room temperature. The serum samples were pipetted into a labeled Eppendorf tube with the help of a dropper and stored at -20°C until further analysis. The collected serum samples were preserved at -20°C in a refrigerator until use. TP, TG, cholesterol, ALT, AST and ALP were measured by using a semiautomatic biochemistry analyzer (Dymind DP-C16), Germany. Minerals (calcium, phosphorus, and magnesium) were determined via a T80 double-beam spectrophotometer from Dr. Mohammad Hussain Central Laboratory, Bangladesh Agricultural University, Mymensingh. Analysis of the Feed sample Home-mixed TMR samples were collected from the dairy farm and sealed in plastic bags for chemical analysis. Chemical analysis of the samples was performed at Bangladesh Agricultural University. The dry matter (DM) and ash contents of the feed samples were determined by oven drying at 105°C overnight and igniting in a muffle furnace at 600°C for 6 hours (AOAC, 2016). The nitrogen content was determined via the Kjeldahl method, and the crude protein (CP) content was calculated as N*6.25. Nutrients supplied per milk yield through TMR were estimated from the total amount of TMR offered per cow/day, divided by the milk produced by the respective cow/day, multiplied by their respective DM and nutrient concentrations, following the method described by (9). Statistical analysis Statistical analysis of the collected data was performed via IBM SPSS Statistics version 22 software. One-way analysis of variance (ANOVA) was used to determine significant differences in each parameter among the different groups. Pearson’s correlation test was performed to examine the associations among biochemical, productive, reproductive and feed components. All the data are presented as the means ± standard errors of the means (SEMs). The P value was adjusted by comparing all pairs via the Duncan test. Probabilities of P<0.01 and P<0.05 were considered statistically significant. Results Nutritional value of TMRs This study was conducted to evaluate the productive, reproductive and biochemical profiles of lactating cows on the basis of the TMRs supplied. The chemical compositions of the TMRs are shown in Table 1. All three meals had the same amount of dry matter (DM), which was approximately 96.3%. TMR-3 contained the most nitrogen-free extract (48.3%), the least crude fiber (19.21%), and the greatest amount of crude protein (17.31%), indicating that it has more energy and protein. TMR-1, on the other hand, had the lowest amount of protein (13.66%), crude fiber (28.61%) and neutral detergent fiber (NDF) (53.61%), indicating that the feed contained fewer nutrients. There were statistically significant differences (p<0.05) between the TMRs in terms of the amounts of ash, crude fiber, crude protein, NFE, ADF, and NDF. Table 1: Nutritional value of the TMR provided during the experimental period Nutritional value Total mixed ration TMR-1 TMR-2 TMR-3 DM % 96.33± 0.0 96.35± 0.0 96.31± 0.0 Ash % 8.57± 0.0 ab 9.48± 0.0 b 7.65± 0.0 a Crude fiber % 28.61± 0.0 a 22.08± 0.0 b 19.21± 0.0 b Crude protein % 13.66± 0.0 a 15.14± 0.0 ab 17.31± 0.0 b Fat % 7.33± 0.0 6.92± 0.0 7.53± 0.0 N free extract% 42.43± 0.0 a 46.38± 0.0 b 48.3± 0.0 b ADF % 24.1± 0.0 a 26.53± 0.0 b 26.56± 0.0 b NDF % 53.61± 0.0 a 40.29± 0.0 b 36.66± 0.0 c a, b, c values indicate a significant (p<0.05) difference among groups. Productive parameters The box plot analysis shown in Figure 1 revealed no significant outliers in body weight (1a), daily milk yield (1b), lactation length (1c), first day peak yield (1d), or duration of peak yield (1e) across the three TMR groups (TMR1, TMR2, TMR3) in the cows in the TMR 3 group. The results revealed the highest value of body weight (515.00±12.27 kg) in cows in the TMR 1 group, the first day of pick yield after calving (41.00±2.84 days) in cows in the TMR 2 group, the daily milk yield (21.28±0.9 1 liter), the lactation length (308.33±27.86 D) and the duration of pick yield (3.87±0.38 months). The median values for body weight and daily milk yield were marginally greater in TMR2, although those differences were not statistically significant (P > 0.05). Pearson correlation analysis (Figure 2) revealed that crude protein (CP) and nonfiber carbohydrates (NFEs) presented moderate to strong positive correlations with daily milk yield (r = 0.54 and r = 0.63, respectively) and lactation length (r = 0.48 and r = 0.57, respectively). In contrast, acid detergent fiber (ADF) and neutral detergent fiber (NDF) contents were negatively correlated with daily milk yield (r = -0.46 and r = -0.51) and lactation length (r = -0.42 and r = -0.47), suggesting that increased fiber content may hinder productive performance. The dietary fat content was weakly positively correlated with the duration of peak yield (r = 0.29). Figure 1: Box plots presenting productive parameters, including body weight (a), daily milk yield (b), lactation length (c), first day of peak yield (d), and duration of peak yield (e), among the three TMR groups. Figure 2: Pearson's correlation between productive and nutritive values of TMRs Reproductive parameters Box plots (Figure 3) of the reproductive parameters revealed broader variability than did the productive traits, particularly in the cows of Group TMR3. Despite this variation, the medians for age at first AI (3a), calving to first heat (3b), calving to first AI (3c), and calving interval (3d) remained statistically similar across all groups. Lactating cows in TMR-3 had somewhat longer intervals between calving and the first heat and first service (73.8 ± 9.68 days and 91.92 ± 6.99 days, respectively), but these differences were not statistically significant (P > 0.05). The correlation data (Figure-4) revealed that CP and NFE were inversely correlated with age at first AI (r = -0.40 and r = -0.36) and the calving interval (r = -0.45 and r = -0.41), indicating a potential positive influence of energy- and protein-rich diets on reproductive efficiency. ADF and NDF again showed positive correlations with extended reproductive intervals, including calving to first AI (r = 0.39 and r = 0.43), suggesting a delaying effect from high fiber content. Fat content presented a minimal correlation (r < 0.20) with most reproductive traits. Figure 3: Box plots for reproductive parameters of age at first AI (a), calving to first heat (b), calving to first AI (c), and calving interval (d). Figure-4: Pearson's correlation between the reproductive and nutritive values of TMRs Serum biochemical profiles Figure 5 presents the biochemical profiles of lactating cows provided with TMRs. The results from the serum biochemical tests revealed that all the groups had normal levels of total protein (5a), cholesterol (5c), calcium (5 h), and phosphorus (5i). The levels of magnesium (5j) in the TMR-2 cows were significantly lower (p<0.05) than those in the TMR-1 and TMR-3 cows. The AST (5f) levels were significantly higher (p<0.05) in the cows of TMR-2 (84.45 ± 3.77 U/L) and TMR-3 (88.53 ± 5.30 U/L) than in the cows of TMR-1 (70.46 ± 2.82 U/L). The ALP 53 g) level in TMR-2 was much lower (157.70 ± 6.25 U/L) than that in TMR-1 and TMR-3. The Pearson correlations between the biochemical parameters and nutritive values of the TMRs obtained in this study are presented in Figure 6. The TP content was positively correlated with the crude protein content in the cows in the TMR1 and TMR3 groups. Triglycerides were negatively correlated with crude fiber and NDF in TMR1, and cholesterol was strongly positively correlated with fat content in cows in the TMR2 group. ALT was negatively correlated with crude fiber, NDF and ADF in cows in the TMR1 and TMR3 groups and positively correlated with crude protein and fat in cows in the TMR2 group (Figure-6). AST was negatively correlated with crude fiber and ADF in the cows in the TMR1 group and positively correlated with crude protein in the TMR2 group. Mg was negatively correlated with ADF and NDF in the cows in the TMR2 group and weakly positively correlated with NFE in the cows in the TMR3 group. Figure 5: Box plots presenting the biochemical profiles of total protein (a), triglyceride (b), cholesterol (c), creatinine (d), alanine transaminase (e), aspartate transferase (f), alkaline phosphatase (g), calcium (h), phosphorus (i), and magnesium (j) in lactating cows fed different TMRs. Figure-6: Pearson's correlation between serum biochemical profiles and nutritive values of TMRs. Associations among the productive, reproductive, and biochemical profiles of lactating cows Figure 7 shows the relationships among productive traits (e.g., milk yield), reproductive indicators (e.g., calving intervals), and various biochemical markers in lactating cows. Body weight was strongly negatively correlated with daily milk yield (r = -0.281, p = 0.000), ALT (r = -0.152, p = 0.026), and triglycerides (r = -0.138, p = 0.043). However, a slight positive correlation with duration of milk yield (r = 0.403, p = 0.000) and TP (r = 0.141, p = 0.037) was also observed. The daily milk yield was strongly positively correlated with triglycerides (r = 0.180, p = 0.009) and ALT (r = 0.273, p = 0.000) and negatively correlated with cholesterol (r = -0.303, p = 0.000) and ALP (r = 0.195, p = 0.005). There was a strong positive correlation of lactation length with the calving interval (r = 0.462, p = 0.003) and creatinine level (r = 0.465, p = 0.000) and moderate correlations with ALT and TG. A marked negative correlation was also observed between ALP (r = -0.350, p = 0.009) and TG (r = -0.304, p = 0.024). The first day of peak yield after calving was strongly positively correlated with triglycerides (r = 0.330, p = 0.000) and ALT (r = 0.239, p = 0.000). However, the duration of peak yield was positively correlated with creatinine (r = -0.121, p = 0.079) and negatively correlated with triglycerides (r = -0.193, p = 0.005) and ALP (r = -0.170, p = 0.014). Age at the first AI showed a significant negative correlation with TP (r = -0.192, p = 0.005). Calving to first heat was strongly correlated with calving to first AI (r = 0.943, p = 0.000) and showed a moderate correlation with ALT. The calving interval was significantly negatively correlated with creatine (r = -0.397, p = 0.000), AST (r = -0.241, p = 0.008), and Mg (r = -0.239, p = 0.008). A positive correlation was also found with lactation duration (r = 0.462, p = 0.003) (r = 0.208, p = 0.024). The study revealed a strong positive correlation between TP and cholesterol (r = 0.352, p = 0.000) and a negative correlation with Mg (r = -0.197, p = 0.004). TG was strongly positively correlated with ALT (r = 0.820, p = 0.000) and cholesterol (r = 0.409, p = 0.000). Cholesterol was positively correlated with ALT and creatinine, whereas ALT was significantly positively associated with milk production. ALP was negatively correlated with the reproductive interval and peak yield duration. Figure 7: Associations among productive, reproductive and biochemical parameters of lactating cows Discussion Suitable feeding strategies with balanced nutrients and appropriate management techniques are crucial to reduce stress and avoid metabolic diseases linked to maximal milk production in lactating cows ( 10 ). Notably, the profitability and viability of dairy farms depend on successful reproduction. Information regarding the anticipated response of feeding systems to production and reproduction parameters that incorporate varying proportions of TMR is particularly scarce in Bangladesh. This study analyzed feed and blood profiles with productive and reproductive features depending on the feed provided. The dairy cows selected for the experiment were grouped on the basis of three different TMRs supplied and practiced at the selected dairy farm. However, decisions regarding the grouping of dairy cows are influenced by several variables, including herd demographics (i.e., distribution among parties, lactation stage, milk yield and distributions, reproductive stage, etc.), mixer wagon sizes, feed and forage inventories, and feed and milk prices ( 5 ). CF%, CP%, N-free extract, ADF%, and NDF% all showed significant (p < 0.05) variations in subgroups on the basis of TMR when the nutritional benefits of TMR given to lactating cows were considered. The nutrient values for CP% and NDF% of the TMRs obtained in this study were higher than those recommended by ( 11 )The National Research Council (NRC) (2021). NRC (2021) suggested a CP% of 16–17.4% and an NDF level of approximately 25–33% of dry matter in the rations of lactating dairy cows. As dietary NDF levels increase, milk production decreases linearly ( 12 ). According to ( 13 )Grille et al. (2019) and ( 14 )Capelesso et al. (2019), TMR-based systems improve productive performance in terms of milk yield, lipid profile, blood parameters, and energy status. Research has shown that blood parameters are affected by the amount of energy and minerals consumed. Diets high in energy, especially those that increase the levels of glucogenic precursors, are associated with increased levels of glucose, cholesterol, and triglycerides ( 15 ). The study revealed that the body weight of cows in the TMR-1 group was highest and positively related to CF, NDF, and TP, which suggests that higher fiber intake is associated with better weight management and overall health. Body weight is negatively associated with CP, nitrogen-free extract, TG, ALT, and P. During peak lactation, an increase in body weight may be achieved by better rumen fermentation and feeding behavior, which are associated with increased NDF levels ( 12 ). Protein levels are essential for maintaining body weight, whereas high crude protein levels may not be beneficial due to metabolic inefficiencies. Milk yields were highest in cows given TMR 3, suggesting that these diets were successful in achieving maximum output. There seems to be a link between nutrition and continued milk production since lactating cows on TMR 3 had the most extended lactation durations. In this study, milk production was shown to be inversely related to dry matter (DM), ash, crude fiber, fat, NDF, and cholesterol contents and positively associated with oil protein, N-free extract, ADF, total protein, ALT, and ALP levels. Similar findings have been reported previously ( 16 ). The significance of early lactation nutrition on peak yield was highlighted by the fact that TMR 2 cows had the highest first-day peak yield in this study. ( 17 )Hristov et al. (2004) reported a moderately favorable link between milk output and dry matter intake (DMI). Lowering prepartum energy consumption may reduce the milk supply ( 18 ). High-yielding cows often have more energy in their milk than they consume, which can negatively impact their metabolism and reproductive ability ( 19 ). The results show that the duration of peak yield is associated with TMR 3. Nutritional interventions may prolong productive periods ( 20 ). On the other hand, dairy cows whose fertility is compromised due to an emphasis on high milk output should be nourished to promote both milk production and reproductive health ( 16 ). The reproductive performance indicators discussed, such as the calving interval, age at first AI, calving to first heat, and calving to first AI, demonstrated a general consistency across the different TMR groups, indicating that diet type does not influence these metrics. The optimal age for AI in cows is influenced by factors such as breed, growth rate, and management practices. Holstein cows typically have an AFC of 15–30 months, whereas Jersey cows may calve earlier. Early AI promotes reproductive efficiency and longer herd life ( 21 , 22 ). Adequate nutrition and postpartal diseases are essential for optimal AFC ( 23 , 24 ). Reducing the AFC can increase lifetime milk production and herd profitability ( 25 ). The interval from calving to first heat (ICH) is a crucial indicator of reproductive recovery postpartum and is influenced by factors such as parity, body condition score (BCS), and environmental conditions. Multiparous cows tend to exhibit estrus earlier ( 26 ), whereas cows with lower BCSs experience delayed estrus ( 23 ). Heat stress can prolong ICH by disrupting ovarian activity. The optimal duration of ICH is 40–60 days, whereas the interval from calving to first AI (CFI) is 60–80 days, allowing sufficient time for uterine involution and recovery while maintaining reproductive efficiency ( 24 , 27 , 28 ). The value of calving to the first service interval achieved in the current study was greater than the value of 115 days for HF breeds in the Central Highlands of Ethiopia reported by ( 29 )Tadesse et al. (2010), who also reported that negative energy balance, poor oestrus detection, and inadequate dairy cow oestrus expression contribute to extended CFSI in dairy production systems. Providing TMRs on the basis of parity and production level can impact reproductive performance, as high-producing cows require specialized TMRs for energy balance and reproductive health ( 24 , 30 ). The optimal calving interval for dairy cows is 12–14 months, with variations in parity, health, and management techniques resulting in large swings. Multiparous cows have shorter intervals due to improved reproductive tract health, whereas seasonality influences calving intervals ( 24 , 26 , 31 ). However, findings on the calving interval, age at first AI, calving to first heat, and calving to first AI collectively underscore the robustness of reproductive performance across management groups, suggesting that under current conditions, other factors beyond diet might play a more critical role in influencing these key metrics. The physiological and nutritional health of dairy cows may be determined by measuring certain biochemical markers in their blood serum ( 32 ). The study revealed similar TP levels in lactating cows in the three TMR groups. Higher total protein levels may indicate earlier reproductive maturity, as research revealed a strong negative relationship between TP and the age of first AI. Low plasma protein levels result in a lack of amino acids needed for gonadotropin and gonadal hormone biosynthesis, potentially causing reproductive hormonal disturbances and inactive ovaries ( 33 ). According to ( 34 )Alberghina et al. (2011), the environment (nutritional management, season, climate, etc.), breed, lactation stage, parity, and health condition all affect the concentration of blood proteins. The serum triglyceride level was the highest in the TMR 2 group. Dietary variation in TMR formulations had a minimal effect on circulating triglyceride concentrations. Usually, in lactating animals, the serum TG concentration increases as lactation progresses, as reported by ( 10 , 35 , 36 )Ghanem and El-Deeb (2010), Monteiro et al. (2012), and Perumal et al. (2023). Dairy cows use TG for lactation energy, forming milky fats. Triglyceride levels should be less than 150 mg/dl for steroidogenesis and milk fat production ( 37 ). All TMR diets were assumed to be equally effective in supporting lipid homeostasis, which aligns with the findings of previous studies. The highest value of cholesterol was found in cows supplied with TMR 3, but cholesterol concentrations in dairy cows were not significantly affected by TMR. The observed variability within groups suggests that other physiological or environmental factors may play a role in cholesterol regulation. A prolonged calving-to-first-heating interval was slightly linked with cholesterol levels, suggesting that postpartum reproductive recovery may have been delayed. High cholesterol levels resulting from fat supplementation increase progesterone and estradiol concentrations, reduce estradiol levels, and increase PGFM and PGF2 in addition to other hormones ( 38 ). The physiological adjustment to satisfy the lactation requirements is a higher level of cholesterol as lactation progresses ( 39 ). Creatinine, a byproduct of muscle metabolism, typically serves as an indicator of renal function and overall muscle mass. The dietary differences among the TMR groups did not cause detectable alterations in muscle metabolism or kidney performance under the conditions of this study, as there were no significant differences in the TMR groups (P = 0.264). Its usefulness as a stable biochemical marker in nonpathological circumstances is supported by prior research, such as that of ( 40 )Piccione et al. (2012), who reported low changes in blood creatinine levels throughout several physiological stages in dairy cattle. Creatinine levels demonstrated a mild negative relationship with age at first AI, implying that elevated creatinine may be linked to earlier sexual maturity. ALT, a liver enzyme, was not affected by TMR composition in this study, suggesting that the liver enzyme response was more physiologically driven than nutritionally driven. This aligns with findings from ( 41 )González et al. (2011), who reported that the lactation stage can modulate liver enzyme activities independently of diet. Unlike ALT, AST levels varied significantly among the TMR groups, suggesting dietary effects on tissue metabolism or muscle turnover. Increased AST levels in the TMR2 and TMR3 diets may reflect subtle hepatocellular or muscular stress, possibly linked to diet composition. Similar patterns have been described by ( 40 )Piccione et al. (2012), emphasizing the influence of specific feed components on enzymatic markers. ALP levels remained stable across dietary treatments, indicating that diet does not significantly affect bone metabolism or liver-related ALP production. These findings are consistent with those of previous reports ( 42 ), highlighting the stability of ALP in healthy lactating cows. Liver enzymes (ALT, AST, and ALP) were weakly positively associated with the calving interval, which could reflect mild metabolic or physiological stress affecting fertility. However, aminotransferases are known to maintain protein balance during the peak lactation phase of metabolism. The serum calcium concentrations of lactating cows were stable across the TMR diets, suggesting effective homeostatic regulation of calcium despite the high demands of lactation. This highlights the adequacy of the TMR formulations in maintaining mineral balance, in agreement with ( 43 )Goff (2008), who noted robust calcium regulatory mechanisms in lactating cattle. The phosphorus concentration did not significantly differ with the TMR diet, reflecting the proper dietary phosphorus supply and homeostasis during lactation. The serum Mg levels slightly differed according to diet. The higher Mg concentration in TMR3-fed animals suggests minor dietary effects on magnesium status, possibly due to differences in mineral supplementation or fiber composition influencing absorption. Similar modest dietary effects on magnesium have been previously reported by ( 44 )Grünberg (2014). There was a minimal link between magnesium and milk production features, such as lactation time and daily output, although phosphorus and calcium showed a favorable correlation. These biochemical indicators may be useful for tracking dairy output and enhancing reproductive efficiency, as suggested by ( 40 , 41 )González et al. (2011) and Piccione et al. (2012). In TMR1, elevated levels of crude fiber and ADF appear to correlate with improved liver health indicators, specifically lower ALT and AST levels. Elevated crude protein levels seem to be advantageous for sustaining higher total protein concentrations in the serum. These findings are consistent with those of ( 45 )Anderson et al. (2009), who reported that increased dietary fiber may decrease hepatic lipid accumulation and associated enzyme elevation. ( 46 )Vasilachi et al. (2022) reported that dietary composition marginally affects liver enzymes, total protein, and urea levels, although plasma mineral and enzyme levels are within physiological ranges. The biochemical profiles of TMR1-fed animals had a relatively minor influence on diet composition. The modest triglyceride‒fat relationship aligns with the general understanding that dietary fat intake can influence blood lipid profiles ( 47 ). Increased crude protein intake in TMR2 may lead to mild elevations in liver enzymes (ALT/AST), potentially indicating heightened protein turnover or hepatic load, in line with the findings of ( 48 )Bernabucci et al. (2005). The negative impact of dietary fiber on magnesium absorption may have significant implications for diet formulation. The observed correlation between digestible carbohydrates (NFE) and magnesium in TMR3 indicates that energy-dense diets may increase mineral utilization. ( 49 )Voronina et al. (2017) also highlighted the link between dietary energy and lipid metabolism. Furthermore, the negative correlation between liver enzymes and fiber content highlights the potential hepatic advantages of high-fiber diets. ( 50 )Lattimer and Haub (2010) documented similar relationships in studies of dairy cattle metabolism. In TMR3, while energy components still modestly influenced lipid metabolism, liver enzymes showed reduced sensitivity to diet. This suggests a possible better adaptation or a more balanced ratio profile. Similar stabilization effects have been reported by ( 51 )Trevisi et al. (2010) in cows fed more balanced rations. The blood and biochemicals of crossbred cows are affected by lactational phases ( 52 – 54 ). Notably, substantial nutritional inadequacies are obstacles to tropical cattle production methods ( 55 ). Effective reproductive plans control the dynamics and structure of the herd, increasing on-farm replacements and reducing replacement and mortality costs. Reproductive performance is closely related to herd net return on TMR systems ( 56 , 57 ). Conclusion This study revealed that the ingredients of TMR significantly affect milk yield, pick yield duration, magnesium, ALT, and AST in lactating cows. In addition, there was a strong correlation between feed nutrient values and biochemical, productive, and reproductive parameters. To our knowledge, this study provides the first information on the effects of TMR content on blood metabolites and productive and reproductive performance in Frisian crossbred lactating cows reared in Bangladesh. Integrating biochemical, feed intake, and production data can improve dairy management's predictive accuracy. Multistage modeling in further research can optimize herd performance by assigning the most suitable TMR for each dairy cow. Feeding strategies should be adjusted on the basis of the lactation stage, reproductive intervals should be reduced through nutrition, and overreliance on fat content should be limited. Further research on ALT and TG as predictive biomarkers is suggested. Abbreviations TMR – Total mixed ratio; TP – Total protein; TG – Triglyceride; ALT – Alanine transaminase; AST – Aspartate transaminase; ALP – Alkaline phosphatase; CP – Crude protein; NFE – Nitrogen-free extract; ADF – Acid detergent fiber; NDF – Neutral detergent fiber Declarations Acknowledgments The authors express their deepest gratitude and gratitude to the Livestock and Dairy Development Project (LDPP), Department of Livestock Services (DLS), Ministry of Fisheries and Livestock, Bangladesh, for funding this work, as it was a part of the Sub-Project "Speeding up genetic gain through embryo production and transfer for sustainable improvement of milk production in dairy cattle of Bangladesh (RP-A-01-26)" conducted by the Department of Surgery and Obstetrics, Bangladesh Agricultural University, Mymensingh, Bangladesh. Author contributions MAR conceptualized and designed the study. MSS, DR, UKR, MH,and AA collected the data. M H performed the statistical analysis and interpretation of the results. MAR and MSS prepared the original draft of the manuscript. NSJ, MH, RNF, and MSK critically reviewed and revised the manuscript. NSJ supervised the overall research activity, and she, along with RNF and MSK contributed to project administration. All the authors have read and approved the final manuscript. Conflict of interest statement The authors declare that they do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted. Ethics approval Approved by the BAU Ethics Committee (Ref: AWEEC/BAU/2023 (03)) Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Prior publication Data have not been published previously References Kerketta S, Sarangdevot S, Naruka P, Pachauri C, Verma S, Bhadauria S, et al. Production performance comparison of lactating buffaloes on feeding of total mixed ration versus conventional feeding. J Entomol Zool Stud. 2020;8(4):1657–60. Schingoethe DJ. A 100-Year Review: Total mixed ration feeding of dairy cows. J Dairy Sci. 2017 Dec;100(12):10143–50. Sarker NR, Yeasmin D, Tabassum F, Habib MdA. An On-Farm Study for Feeding Impact of Total Mixed Ration (TMR) in Milking Cow. Curr J Appl Sci Technol. 2019 May 2;1–8. He Y, Zhong R, Cheng L, You P, Li Y, Sun X. Effects of the Supplementation of Lysophospholipids through Pelleted Total Mixed Rations on Blood Biochemical Parameters and Milk Production and Composition of Mid-Lactation Dairy Cows. Animals. 2020 Jan 28;10(2):215. Cabrera VE, Kalantari AS. Economics of production efficiency: Nutritional grouping of the lactating cow. J Dairy Sci. 2016 Jan;99(1):825–41. Noakes D, Parkinson T, England G. In: Arthur’s Veterinary Reproduction and Obstetrics. 9th ed. Philadelphia: Elsevier Health Sciences; 2018. Guzel S, Tanriverdi M. Comparison of serum leptin, glucose, total cholesterol and total protein levels in fertile and repeat breeder cows. Rev Bras Zootec. 2014 Dec;43(12):643–7. Coroian CO, Miresan V, Coroian A, Raducu C, Andronie L, Marchis Z, et al. Biochemical and Hematological Blood Parameters at Different Stages of Lactation in Cows. Bull Univ Agric Sci Vet Med Cluj-Napoca Anim Sci Biotechnol. 2017 May 18;74(1):31. McDonald P, Edwards R, Greenhalgh J, Morgan C, Sinclair L, Wilkinson R. Animal Nutrition. 7th ed. Harlow (UK): Pearson Education Limited; 2011. Perumal P, De AK, Bhattacharya D, Chakurkar EB. Lactation stages modulate the hematological, serum biochemical, and endocrinological profiles and oxidative stress markers in crossbred cows under tropical humid island ecosystem of Andaman and Nicobar Islands. Trop Anim Health Prod. 2023 Apr;55(2):131. Nutrient Requirements of Beef Cattle. In: National Research Council. 7th ed. Washington (DC): National Academies Press; 2000. Shi R, Dong S, Mao J, Wang J, Cao Z, Wang Y, et al. Dietary Neutral Detergent Fiber Levels Impacting Dairy Cows’ Feeding Behavior, Rumen Fermentation, and Production Performance during the Period of Peak-Lactation. Animals. 2023 Sep 10;13(18):2876. Grille L, Adrien ML, Olmos M, Chilibroste P, Damián JP. Diet change from a system combining total mixed ration and pasture to confinement system (total mixed ration) on milk production and composition, blood biochemistry and behavior of dairy cows. Anim Sci J. 2019 Nov;90(11):1484–94. Capelesso A, Kozloski G, Mendoza A, Pla M, Repetto JL, Cajarville C. Reducing milking frequency in early lactation improved the energy status but reduced milk yield during the whole lactation of primiparous Holstein cows consuming a total mixed ration and pasture. J Dairy Sci. 2019 Oct;102(10):8919–30. Krupin EO, Shakirov ShK. Changes in individual diagnostic markers of carbohydrate, lipid and mineral metabolism in dairy cows due to feeding. Agrar Sci. 2023 Mar 3;(2):30–4. Ibtisham F, Nawab A, Li G, Xiao M, An L, Naseer G. Effect of nutrition on reproductive efficiency of dairy animals. Med Weter. 2018;74(1):6025–2018. Hristov AN, Etter RP, Ropp JK, Grandeen KL. Effect of dietary crude protein level and degradability on ruminal fermentation and nitrogen utilization in lactating dairy cows1. J Anim Sci. 2004 Nov 1;82(11):3219–29. Silva-del-Río N, Fricke PM, Grummer RR. Effects of twin pregnancy and dry period feeding strategy on milk production, energy balance, and metabolic profiles in dairy cows1. J Anim Sci. 2010 Mar 1;88(3):1048–60. Reynolds CK. Production and metabolic effects of site of starch digestion in dairy cattle. Anim Feed Sci Technol. 2006 Sep;130(1–2):78–94. McNamara JP, Shields SL. Reproduction during lactation of dairy cattle: Integrating nutritional aspects of reproductive control in a systems research approach. Anim Front. 2013 Oct 1;3(4):76–83. Atashi H, Asaadi A, Hostens M. Association between age at first calving and lactation performance, lactation curve, calving interval, calf birth weight, and dystocia in Holstein dairy cows. Abuelo A, editor. PLOS ONE. 2021 Jan 4;16(1):e0244825. Vargas-Leitón B, Romero-Zúñiga JJ, Castillo-Badilla G, Saborío-Montero A. Optimal Age at First Calving in Pasture-Based Dairy Systems. Dairy. 2023 Oct 30;4(4):581–93. Hernandez-Gotelli C, Manríquez D, Azocar J, De Vries A, Pinedo PJ. Factors associated with the time and magnitude of the nadir body condition score in early lactation and its subsequent effects on fertility of Holstein cows. J Anim Sci. 2023 Jan 3;101:skad119. Edvardsson Rasmussen A, Holtenius K, Båge R, Strandberg E, Åkerlind M, Kronqvist C. A randomized study on the effect of extended voluntary waiting period in primiparous dairy cows on milk yield during first and second lactation. J Dairy Sci. 2023 Apr;106(4):2510–8. Do C, Wasana N, Cho K, Choi Y, Choi T, Park B, et al. The Effect of Age at First Calving and Calving Interval on Productive Life and Lifetime Profit in Korean Holsteins. Asian-Australas J Anim Sci. 2013 Nov 1;26(11):1511–7. Koyama K, Kubo T, Koyama T, Takahashi Y. Parity affects the relationship between the insemination–ovulation interval and the conception rate in lactating dairy cows. Reprod Domest Anim. 2023 Jul;58(7):895–902. Haile B. Reproductive Performance of Holstein Friesian Dairy Cows at Alage Dairy Farm, Ethiopia. J Dairy Vet Sci [Internet]. 2018 Aug 20 [cited 2025 Sep 12];7(3). Available from: https://juniperpublishers.com/jdvs/JDVS.MS.ID.555713.php Strickland JM, Martins JPN, Neuder L, Pursley JR. When Implementing the Presynch-11/Ovsynch Reproductive Management Program, the Fertility of Lactating Dairy Cows Improved When They Received Timed Artificial Insemination Compared with the Inclusion of Estrus Detection. Animals. 2024 Jul 31;14(15):2235. Tadesse M, Thiengtham J, Pinyopummin A, Prasanpanich S. Productive and reproductive performance of Holstein Friesian dairy cows in Ethiopia. Livest Res Rural Dev. 2010;22(2). Talukder S, Celi P, Kerrisk KL, Garcia SC, Dhand NK. Factors affecting reproductive performance of dairy cows in a pasture-based, automatic milking system research farm: a retrospective, single-cohort study. Anim Prod Sci. 2015;55(1):31. Funakoshi D, Shiotani H, Seki M. Equine chorionic gonadotropin treatment and timed artificial insemination for dairy cow production under heat stress. J Reprod Dev. 2024;70(1):30–4. Jóźwik A, Strzałkowska N, Bagnicka E, Grzybek W, Krzyżewski J, Poławska E, et al. Relationship between milk yield, stage of lactation, and some blood serum metabolic parameters of dairy cows. Czech J Anim Sci. 2012 Aug 31;57(8):353–60. Arosh A, Kathiresan D, Devanathan T, Rajasunadaram R, Rajasekaran J. Blood biochemical profile in normal cyclical and anoestrus cows. Indian J Anim Sci. 2012;68(11). Alberghina D, Giannetto C, Vazzana I, Ferrantelli V, Piccione G. Reference intervals for total protein concentration, serum protein fractions, and albumin/globulin ratios in clinically healthy dairy cows. J Vet Diagn Investig Off Publ Am Assoc Vet Lab Diagn Inc. 2011 Jan;23(1):111–4. Ghanem MM, El-Deeb WM. Lecithin cholesterol acyltransferase (LCAT) activity as a predictor for ketosis and parturient hemoglobinuria in Egyptian water buffaloes. Res Vet Sci. 2010 Feb;88(1):20–5. Monteiro BM, Yasuoka MM, Pogliani FC, Ayres H, Viana RB, Birgel Junior EH. Lipid and glucose profiles of dairy buffaloes during lactation and dry period. Rev Ciênc Agrár. 2012;55(1):33–9. Roccio F, Claude-Taupin A, Botti J, Morel E, Codogno P, DuPont N. Monitoring lipophagy in kidney epithelial cells in response to shear stress. In: Methods in Cell Biology [Internet]. Elsevier; 2021 [cited 2025 Sep 12]. p. 11–25. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0091679X20302090 Ahmad I, Lodhi L, Qureshi Z, Younis M. Studies on blood glucose, total proteins, urea and cholesterol levels in cyclic, noncyclic and endometritic crossbred cows. Pak Vet J. 2004;24(2):92–4. Ashmawy NA. Blood Metabolic Profile and Certain Hormones Concentrations in Egyptian Buffalo During Different Physiological States. Asian J Anim Vet Adv. 2015 May 15;10(6):271–80. Piccione G, Messina V, Marafioti S, Casella S, Giannetto C, Fazio F. Changes of some hematochemical parameters in dairy cows during late gestation, post partum, lactation and dry periods. 2012;58:59-64. González FD, Muiño R, Pereira V, Campos R, Benedito JL. Relationship among blood indicators of lipomobilization and hepatic function during early lactation in high-yielding dairy cows. J Vet Sci. 2011;12(3):251. Klinkon M, Jeek J. Values of Blood Variables in Calves. In: Perez-Marin CC, editor. A Bird’s-Eye View of Veterinary Medicine [Internet]. InTech; 2012 [cited 2025 Sep 12]. Available from: http://www.intechopen.com/books/a-bird-s-eye-view-of-veterinary-medicine/values-of-blood-variables-in-calves Goff JP. The monitoring, prevention, and treatment of milk fever and subclinical hypocalcemia in dairy cows. Vet J. 2008 Apr;176(1):50–7. Grünberg W. Treatment of Phosphorus Balance Disorders. Vet Clin North Am Food Anim Pract. 2014 Jul;30(2):383–408. Anderson JW, Baird P, Davis RH, Ferreri S, Knudtson M, Koraym A, et al. Health benefits of dietary fiber. Nutr Rev. 2009 Apr;67(4):188–205. Vasilachi A, Ciurescu G, Hăbeanu M. Plasma biochemical profile of dairy cows, with respect to diet and breed. Arch Zootech. 2022 Jun 1;25(1):75–89. Bobe G, Young JW, Beitz DC. Invited Review: Pathology, Etiology, Prevention, and Treatment of Fatty Liver in Dairy Cows. J Dairy Sci. 2004 Oct;87(10):3105–24. Bernabucci U, Ronchi B, Lacetera N, Nardone A. Influence of Body Condition Score on Relationships Between Metabolic Status and Oxidative Stress in Periparturient Dairy Cows. J Dairy Sci. 2005 Jun;88(6):2017–26. A. Voronina О, S. Tsarkova M, Yu. Zaitsev S. Nutrition Influence on Blood Colloid and Biochemistry Parameters of the Lactating Cow. Biosci Biotechnol Res Asia. 2017 Mar 28;14(1):89–92. Lattimer JM, Haub MD. Effects of Dietary Fiber and Its Components on Metabolic Health. Nutrients. 2010 Dec 15;2(12):1266–89. Trevisi E, Minuti A. Assessment of the innate immune response in the periparturient cow. Res Vet Sci. 2018 Feb;116:47–54. Hasan M, Rahman M, Mahbub A, Belal S, Ahmed T. Performance of different crossbred cattle at Comilla District of Bangladesh. J Sylhet Agric Univ. 2014;1(2):161–7. Fadlalla IMT, Omer SA, Atta M. Determination of some serum macroelement minerals levels at different lactation stages of dairy cows and their correlations. Sci Afr. 2020 Jul;8:e00351. Gautam K, Pant V, Pradhan S, Pyakurel D, Bhandari B, Shrestha A. Blood lead levels in rag-pickers of Kathmandu and its association with hematological and biochemical parameters. Electron J Int Fed Clin Chem Lab Med. 2020;31(2):125. Hudaya MF, Sitaresmi PI, Noviandi CT, Widyobroto BP, Widayati DT. Behavior and blood profile in Friesian-Holstein dairy cows in the special region of Yogyakarta, Indonesia. J Anim Behav Biometeorol. 2020 Jun 26;8(4):244–9. Giordano JO, Kalantari AS, Fricke PM, Wiltbank MC, Cabrera VE. A daily herd Markov-chain model to study the reproductive and economic impact of reproductive programs combining timed artificial insemination and estrus detection. J Dairy Sci. 2012 Sep;95(9):5442–60. Galvão KN, Federico P, De Vries A, Schuenemann GM. Economic comparison of reproductive programs for dairy herds using estrus detection, timed artificial insemination, or a combination. J Dairy Sci. 2013 Apr;96(4):2681–93. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7972443","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":536435574,"identity":"2a267388-4208-436c-ba95-cac05d2eb59e","order_by":0,"name":"Md. Abdur Rahim","email":"","orcid":"","institution":"Bangladesh Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Abdur","lastName":"Rahim","suffix":""},{"id":536435912,"identity":"7e26d80c-4c41-4976-9155-19b1c07abac6","order_by":1,"name":"Mst. Sanjida Safawat","email":"","orcid":"","institution":"Bangladesh Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Mst.","middleName":"Sanjida","lastName":"Safawat","suffix":""},{"id":536439640,"identity":"00d5790b-cfc8-418b-a2d2-f72fb9d51143","order_by":2,"name":"Debasish Raha","email":"","orcid":"","institution":"Bangladesh Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Debasish","middleName":"","lastName":"Raha","suffix":""},{"id":536439641,"identity":"22349246-59c2-40d4-a3fc-46bf553e78e9","order_by":3,"name":"Uttam Kumar Roy","email":"","orcid":"","institution":"Rangpur Dairy Limited, Paragon Group, Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Uttam","middleName":"Kumar","lastName":"Roy","suffix":""},{"id":536439642,"identity":"aa55bc0c-7971-44bf-af8f-53272efc46b9","order_by":4,"name":"Mazedul Haque","email":"","orcid":"","institution":"Rangpur Dairy Limited, Paragon Group, Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Mazedul","middleName":"","lastName":"Haque","suffix":""},{"id":536439643,"identity":"37f34b2b-b47c-499e-80b5-91046d1cd0ef","order_by":5,"name":"Aklima Afroz","email":"","orcid":"","institution":"University of Kiel, Germany","correspondingAuthor":false,"prefix":"","firstName":"Aklima","middleName":"","lastName":"Afroz","suffix":""},{"id":536439644,"identity":"daca5b26-b0eb-497d-b66e-330b88d51de1","order_by":6,"name":"Md. Shane Khoda","email":"","orcid":"","institution":"Department of Livestock Services, Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Shane","lastName":"Khoda","suffix":""},{"id":536439645,"identity":"f8141568-4721-4bd7-9cd2-6b2a8ab0f5e3","order_by":7,"name":"Moinul Hasan","email":"","orcid":"","institution":"University of Melbourne, Australia","correspondingAuthor":false,"prefix":"","firstName":"Moinul","middleName":"","lastName":"Hasan","suffix":""},{"id":536439646,"identity":"b692e832-23c6-4b4f-97e8-2d80fe0fdb0c","order_by":8,"name":"Raihana Nasrin Ferdousy","email":"","orcid":"","institution":"Shimane University, Japan","correspondingAuthor":false,"prefix":"","firstName":"Raihana","middleName":"Nasrin","lastName":"Ferdousy","suffix":""},{"id":536439647,"identity":"ef335682-dbf0-4c61-bfa9-4e3e1d595429","order_by":9,"name":"Nasrin Sultana Juyena","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYHCCBDDJLwGmmBkYJBgMiNMiOYMELRBgcINYLeb8B55J81TckTe+3fxMgqHCOrFBunkDXi2WMxLSpHnOPDPcdueYmQTDmfTEBpljBYTckybN23aYcduNBDMJxrbDiQ0SOfgdZnD+AFDLv8P2m2ekf5Ng/EeMlgNAh/E2HE7cIJEDtKWBGC03EpIt5xw7nDzjzplii4Rj6cZtBP1y/kzijTc1h237Z7dvvPGhxlq2n1CIMTDwJDDxwNgJQMxGQD0QsB9g/EFY1SgYBaNgFIxkAAArqUpYMw5mHAAAAABJRU5ErkJggg==","orcid":"","institution":"Bangladesh Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Nasrin","middleName":"Sultana","lastName":"Juyena","suffix":""}],"badges":[],"createdAt":"2025-10-28 17:36:23","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-7972443/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7972443/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94749831,"identity":"88b56f9c-c61c-4718-a524-81b4887f0510","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":984024,"visible":true,"origin":"","legend":"","description":"","filename":"Rahimetal202528oct.docx","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/0396cbe18fe41981a69ce2e9.docx"},{"id":94822912,"identity":"d57a6caf-eacc-416b-8ed4-5da4063be8bd","added_by":"auto","created_at":"2025-10-31 06:45:07","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs7972443.json","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/49714238ac612101136a1b07.json"},{"id":94823252,"identity":"f71ca722-4eb4-4723-88d5-e9a8399b6dc2","added_by":"auto","created_at":"2025-10-31 06:46:52","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":134127,"visible":true,"origin":"","legend":"","description":"","filename":"rs79724430enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/f8c47029fe1d3531c7e6b202.xml"},{"id":94749828,"identity":"4147c475-3660-4595-99b4-007414e32fb5","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"jpeg","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":303344,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/14ff55af4e94bbdebc56e681.jpeg"},{"id":94749830,"identity":"f575f363-f549-41e9-9ef3-694348b7310a","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":618966,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/b68b9352d018595483c0c16b.jpeg"},{"id":94749837,"identity":"0ae588c5-85d9-4dcd-8a9a-7ea9288061cf","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"jpeg","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":306971,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/b588cd62951297a1d38f0bf2.jpeg"},{"id":94823248,"identity":"e22644b5-02a9-4fc5-9008-f15a4de8db4f","added_by":"auto","created_at":"2025-10-31 06:46:52","extension":"jpeg","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":470843,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/00d059d04bc3140d83d632b6.jpeg"},{"id":94823010,"identity":"69936460-46d0-4ebe-bdfe-4094a8226911","added_by":"auto","created_at":"2025-10-31 06:45:47","extension":"jpeg","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":525703,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/e177a56d7d934db85bd959ad.jpeg"},{"id":94749832,"identity":"df4ff24f-fa3e-498f-89b1-905b1628489e","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"jpeg","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":546092,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/230f7ae8f53cfe7da033902f.jpeg"},{"id":94823110,"identity":"72628e75-aee4-44c5-93e8-8a14b219d176","added_by":"auto","created_at":"2025-10-31 06:46:10","extension":"jpeg","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":542246,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/0ee68be63882c5b76a53408b.jpeg"},{"id":94749841,"identity":"c241b0d2-82cd-4408-b961-ca6e63f51826","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":187785,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/6e9267f707148fc800e3c40a.png"},{"id":94824010,"identity":"37da1ab0-affb-498e-8d8e-5cd6897dbf0d","added_by":"auto","created_at":"2025-10-31 06:48:22","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":100309,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/dc0227f0eb5888e75c97a1e5.png"},{"id":94749847,"identity":"0f746656-59a2-488f-9c92-2a57836c2987","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":164809,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/a4d83dadabeb4d52052559d8.png"},{"id":94749844,"identity":"6bb5855b-47c5-4587-9509-e1d5d2016a39","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":69723,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/0ff62031c5dd1e0d85541729.png"},{"id":94749846,"identity":"23aeb090-0fd4-4405-98e1-c821ef61c719","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":436830,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/37ee446365297f4a4edd43c8.png"},{"id":94823295,"identity":"7423cde4-1fee-4a8d-baa2-7705f70172e3","added_by":"auto","created_at":"2025-10-31 06:47:01","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":80653,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/966cb8126e002ff2171624e2.png"},{"id":94749836,"identity":"cf393bd5-e1f4-4dff-991e-e16161407b60","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":94018,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/021a0add1c90a395ddb7fb27.png"},{"id":94823934,"identity":"c2819288-082a-484d-a713-5f561009d6d6","added_by":"auto","created_at":"2025-10-31 06:48:18","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":132014,"visible":true,"origin":"","legend":"","description":"","filename":"rs79724430structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/5bde0022afe2fba77993fbac.xml"},{"id":94749842,"identity":"83cc1c67-8b1c-4f0a-9874-97a73cbd9800","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":143707,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/f5482eb8dc4ee1253023ab69.html"},{"id":94749820,"identity":"7caa8541-64a1-4593-80ba-0e53586ee2c6","added_by":"auto","created_at":"2025-10-30 10:09:13","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":116090,"visible":true,"origin":"","legend":"\u003cp\u003eBox plots presenting productive parameters, including body weight (a), daily milk yield (b), lactation length (c), first day of peak yield (d), and duration of peak yield (e) among the three TMR groups.\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/b558870506e8264c3e3304b4.jpeg"},{"id":94823972,"identity":"b1d90c1d-3853-44e5-8295-f9b018da7c9c","added_by":"auto","created_at":"2025-10-31 06:48:20","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":142604,"visible":true,"origin":"","legend":"\u003cp\u003ePearson's correlation between productive and nutritive values of TMRs\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/b30d99407fb10fe28e1adb92.jpeg"},{"id":94749822,"identity":"ac9ad5b1-0242-4a8d-8bf9-4b5008b3f024","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":108453,"visible":true,"origin":"","legend":"\u003cp\u003eBox plots for reproductive parameters of age at first AI (a), calving to first heat (b), calving to first AI (c), and calving interval (d).\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/7fdea4adeb9bf93570f3b41d.jpeg"},{"id":94749839,"identity":"00999c80-03c9-49d2-94d0-07bf8a96a066","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":113040,"visible":true,"origin":"","legend":"\u003cp\u003ePearson's correlation between reproductive and nutritive values of TMRs\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/cb0e87f23f3c36dd7c4bd247.jpeg"},{"id":94824087,"identity":"4bbafd74-31b1-406e-bb75-e335c8d0c67f","added_by":"auto","created_at":"2025-10-31 06:48:27","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":165007,"visible":true,"origin":"","legend":"\u003cp\u003eBox plots presenting the biochemical profiles \u0026nbsp;of total protein (a), triglyceride (b), cholesterol (c), creatinine (d), alanine transaminase (e), aspartate transferase (f), alkaline phosphatase (g) calcium (h), phosphorus (i), magnesium (j) in lactating cows fed different TMRs.\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/d115c237e413828015018382.jpeg"},{"id":94749824,"identity":"65285ee2-db64-436a-9e5e-03b967eaeaea","added_by":"auto","created_at":"2025-10-30 10:09:14","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":148514,"visible":true,"origin":"","legend":"\u003cp\u003ePearson's correlation between serum biochemical profiles and nutritive values of TMRs.\u003c/p\u003e","description":"","filename":"image6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/abb64d6110302bafa0132370.jpeg"},{"id":94824269,"identity":"532e82ed-d37d-4ecf-8bbc-699b2d92c90d","added_by":"auto","created_at":"2025-10-31 06:48:44","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":96855,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations among productive, reproductive and biochemical parameters of lactating cows.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/f27b09d799e1baf1d6cc2832.png"},{"id":94984641,"identity":"2e6be401-3208-4960-814c-3c9de3a102a1","added_by":"auto","created_at":"2025-11-03 06:54:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1449134,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7972443/v1/bf2769f1-23d9-46f5-b4ae-121932fc7494.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eEffects of Total Mixed Ration on Blood Biochemistry, Productivity, and Reproduction in Bangladeshi Frisian Crossbred Lactating Cows\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eBangladesh has been experiencing the dairy revolution for the last five years. Farmers are pressured to provide sufficient milk due to the high demand for milk and milk products. A feeding standard is lacking due to inadequate scientific assessments of balanced rations in Bangladesh. This results in resource scarcity and insufficient understanding of feeding standards, hindering animal production performance. Traditional feeding strategies, characterized by selective feed intake, result in feed waste and inadequate nutrient utilization, adversely impacting ruminal digestion, absorption, and transit rates (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Excessive concentrate intake in dairy cows increases the risk of ruminal acidosis. To combat this, total mixed ration (TMR) is used, which combines concentrate and forage in a balanced manner. Over the past 50 years, dairy cow feed has significantly transformed from traditional concentrates and forages to a comprehensive mixed ration due to its superior benefits. The TMR results in a well-rounded diet, a stable rumen environment, reduced weight loss, reduced rumen acidosis, and increased energy and protein consumption [1, 2, 3, 4]. Reproductive performance is a critical factor in the sustainability and profitability of dairy farms that employ TMR systems. Group housing with TMR feeding is the primary production system used on commercial dairy farms in developed countries (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Successful reproduction involves resuming ovarian cyclicity postpartum, ovulation, fertilization, uterus restoration, embryo development, and pregnancy maintenance. Dietary formulation and feeding management can facilitate or interrupt these reproductive phases by altering metabolic profiles (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Severe dietary deficits can decrease reproductive performance in high-yielding lactating cows, as they require more nutrients for reproduction.\u003c/p\u003e\u003cp\u003eNutrition is a pivotal technological element that can instigate remarkable transformations in the metabolic dynamics of animals. A lack of essential minerals, proteins, and vitamins in the nourishment of lactating cows leads to significant alterations in their metabolic processes. Metabolic profiles are crucial in assessing a cow\u0026rsquo;s nutritional and health status, as changes in components such as glucose, cholesterol, and TP can lead to reproductive failure (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Standard biochemical profiles in lactating cows indicate good health and strong milk yield, whereas blood analysis can reveal nutritional discrepancies (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, biochemical indicators in a healthy herd are crucial for predicting diseases. Nevertheless, information on the relationships between blood biochemical parameters and dairy cow productivity and nutrition is limited in Bangladesh. A lack of feed and fodder contributes to high production costs in this country. Therefore, this study aimed to assess the productivity, reproductive parameters and serum biochemical profiles of Bangladeshi Frisian crossbred (LXFXF) lactating cows via TMR and to determine the relationships among their biochemical profiles, productive and reproductive parameters, and nutrient values.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003eThe study was conducted by the Department of Surgery and Obstetrics, Bangladesh Agricultural University, Bangladesh. This research focuses on the \u0026ldquo;selection of donor and recipient cows and heifers\u0026rdquo; under the research project titled \u0026ldquo;Speeding up genetic gain through embryo production and transfer for sustainable improvement of milk production in dairy cattle of Bangladesh (RP-A-01-26)\u0026rdquo;. The experimental design and all protocols related to the research project were approved by the Animal Welfare and Experimentation Ethical Committee [Ethical Approval Number: AWEEC/BAU/2023 (03)] of Bangladesh Agricultural University, Bangladesh.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnimals and experimental approach\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size for this study was 95 crossbred Frisian (LXFXF) lactating cows selected from a commercial dairy farm located in Rangpur, Bangladesh. Standard management practices, including deworming and vaccinations, were carried out following the farm schedule, and the experimental animals were kept in consistent housing and lighting. Machine milking was used to harvest milk twice a day, between 0500 and 0600 in the morning and between 1500 and 1600 in the evening. All the animals were maintained in the loose barn, which had free access to water and was provided with TMR. On the basis of the TMR types provided, all cows were grouped into TMR-1 (N=27), TMR-2 (N=43), and TMR-3 (N=25) groups. The data were collected on productive parameters, including body weight, milk yield, duration of pick yield, time of first day of pick yield after calving, lactation length, and reproductive parameters, including age of first AI; calving to first heat and calving to first service and calving interval; and serum biochemical profiles of total protein (TP), triglyceride (TG), cholesterol, alanine transaminase (ALT), aspartate transaminase (AST) and alkaline phosphatase (ALP), calcium, phosphorus, and magnesium.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLaboratory analysis of blood serum\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBefore blood collection, a clinical examination of all lactating cows was performed to ensure that the animals were free from infections. Blood was collected from the jugular vein by inserting a 19G needle attached to a 10 ml disposable syringe into the vein. The blood was transferred to a red-capped clot activator tube and centrifuged by a centrifuge for 15 minutes at 3000 rpm at room temperature. The serum samples were pipetted into a labeled Eppendorf tube with the help of a dropper and stored at -20\u0026deg;C until further analysis. The collected serum samples were preserved at -20\u0026deg;C in a refrigerator until use. TP, TG, cholesterol, ALT, AST and ALP were measured by using a semiautomatic biochemistry analyzer (Dymind DP-C16), Germany. Minerals (calcium, phosphorus, and magnesium) were determined via a T80 double-beam spectrophotometer from Dr. Mohammad Hussain Central Laboratory, Bangladesh Agricultural University, Mymensingh.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnalysis of the Feed sample\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHome-mixed TMR samples were collected from the dairy farm and sealed in plastic bags for chemical analysis. Chemical analysis of the samples was performed at Bangladesh Agricultural University. The dry matter (DM) and ash contents of the feed samples were determined by oven drying at 105\u0026deg;C overnight and igniting in a muffle furnace at 600\u0026deg;C for 6 hours (AOAC, 2016). The nitrogen content was determined via the Kjeldahl method, and the crude protein (CP) content was calculated as N*6.25. Nutrients supplied per milk yield through TMR were estimated from the total amount of TMR offered per cow/day, divided by the milk produced by the respective cow/day, multiplied by their respective DM and nutrient concentrations, following the method described by (9).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis of the collected data was performed via IBM SPSS Statistics version 22 software. One-way analysis of variance (ANOVA) was used to determine significant differences in each parameter among the different groups. Pearson\u0026rsquo;s correlation test was performed to examine the associations among biochemical, productive, reproductive and feed components. All the data are presented as the means \u0026plusmn; standard errors of the means (SEMs). The P value was adjusted by comparing all pairs via the Duncan test. Probabilities of\u0026nbsp;\u003cem\u003eP\u0026lt;0.01\u003c/em\u003e and \u003cem\u003eP\u0026lt;0.05\u003c/em\u003e were considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eNutritional value of TMRs\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted to evaluate the productive, reproductive and biochemical profiles of lactating cows on the basis of the TMRs supplied. The chemical compositions of the TMRs are shown in Table 1. All three meals had the same amount of dry matter (DM), which was approximately 96.3%. TMR-3 contained the most nitrogen-free extract (48.3%), the least crude fiber (19.21%), and the greatest amount of crude protein (17.31%), indicating that it has more energy and protein. TMR-1, on the other hand, had the lowest amount of protein (13.66%), crude fiber (28.61%) and neutral detergent fiber (NDF) (53.61%), indicating that the feed contained fewer nutrients. There were statistically significant differences (p\u0026lt;0.05) between the TMRs in terms of the amounts of ash, crude fiber, crude protein, NFE, ADF, and NDF.\u003c/p\u003e\n\u003cp\u003eTable 1: Nutritional value of the TMR provided during the experimental period\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eNutritional value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 448px;\"\u003e\n \u003cp\u003eTotal mixed ration\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003eTMR-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003eTMR-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003eTMR-3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eDM %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e96.33\u0026plusmn; 0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e96.35\u0026plusmn; 0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e96.31\u0026plusmn; 0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eAsh \u0026nbsp;%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e8.57\u0026plusmn; 0.0\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e9.48\u0026plusmn; 0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e7.65\u0026plusmn; 0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eCrude fiber \u0026nbsp;%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e28.61\u0026plusmn; 0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e22.08\u0026plusmn; 0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e19.21\u0026plusmn; 0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eCrude protein \u0026nbsp;%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e13.66\u0026plusmn; 0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e15.14\u0026plusmn; 0.0\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e17.31\u0026plusmn; 0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eFat \u0026nbsp;%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e7.33\u0026plusmn; 0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e6.92\u0026plusmn; 0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e7.53\u0026plusmn; 0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eN free extract%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e42.43\u0026plusmn; 0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e46.38\u0026plusmn; 0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e48.3\u0026plusmn; 0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eADF %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e24.1\u0026plusmn; 0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e26.53\u0026plusmn; 0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e26.56\u0026plusmn; 0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003eNDF %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e53.61\u0026plusmn; 0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e40.29\u0026plusmn; 0.0\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 149px;\"\u003e\n \u003cp\u003e36.66\u0026plusmn; 0.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003ea,\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003csup\u003eb,\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003csup\u003ec\u003c/sup\u003e values indicate a significant (p\u0026lt;0.05) difference among groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eProductive\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eparameters\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe box plot analysis shown in Figure 1 revealed no significant outliers in body weight (1a), daily milk yield (1b), lactation length (1c), first day peak yield (1d), or duration of peak yield (1e) across the three TMR groups (TMR1, TMR2, TMR3) in the cows in the TMR 3 group. The results revealed the highest value of body weight (515.00\u0026plusmn;12.27 kg) in cows in the TMR 1 group, the first day of pick yield after calving (41.00\u0026plusmn;2.84 days) in cows in the TMR 2 group, the daily milk yield (21.28\u0026plusmn;0.9 1 liter), the lactation length (308.33\u0026plusmn;27.86 D) and the duration of pick yield (3.87\u0026plusmn;0.38\u003csup\u003e\u0026nbsp;\u003c/sup\u003emonths). The median values for body weight and daily milk yield were marginally greater in TMR2, although those differences were not statistically significant (P \u0026gt; 0.05). Pearson correlation analysis (Figure 2) revealed that crude protein (CP) and nonfiber carbohydrates (NFEs) presented moderate to strong positive correlations with daily milk yield (r = 0.54 and r = 0.63, respectively) and lactation length (r = 0.48 and r = 0.57, respectively). In contrast, acid detergent fiber (ADF) and neutral detergent fiber (NDF) contents were negatively correlated with daily milk yield (r = -0.46 and r = -0.51) and lactation length (r = -0.42 and r = -0.47), suggesting that increased fiber content may hinder productive performance. The dietary fat content was weakly positively correlated with the duration of peak yield (r = 0.29).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 1: Box plots presenting productive parameters, including body weight (a), daily milk yield (b), lactation length (c), first day of peak yield (d), and duration of peak yield (e), among the three TMR groups.\u003c/p\u003e\n\u003cp\u003eFigure 2: Pearson\u0026apos;s correlation between productive and nutritive values of TMRs\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eReproductive parameters\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBox plots (Figure 3) of the reproductive parameters revealed broader variability than did the productive traits, particularly in the cows of Group TMR3. Despite this variation, the medians for age at first AI (3a), calving to first heat (3b), calving to first AI (3c), and calving interval (3d) remained statistically similar across all groups. Lactating cows in TMR-3 had somewhat longer intervals between calving and the first heat and first service (73.8 \u0026plusmn; 9.68 days and 91.92 \u0026plusmn; 6.99 days, respectively), but these differences were not statistically significant (P \u0026gt; 0.05). The correlation data (Figure-4) revealed that CP and NFE were inversely correlated with age at first AI (r = -0.40 and r = -0.36) and the calving interval (r = -0.45 and r = -0.41), indicating a potential positive influence of energy- and protein-rich diets on reproductive efficiency. ADF and NDF again showed positive correlations with extended reproductive intervals, including calving to first AI (r = 0.39 and r = 0.43), suggesting a delaying effect from high fiber content. Fat content presented a minimal correlation (r \u0026lt; 0.20) with most reproductive traits.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 3: Box plots for reproductive parameters of age at first AI (a), calving to first heat (b), calving to first AI (c), and calving interval (d).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure-4: Pearson\u0026apos;s correlation between the reproductive and nutritive values of TMRs\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSerum biochemical profiles\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFigure 5 presents the biochemical profiles of lactating cows provided with TMRs. The results from the serum biochemical tests revealed that all the groups had normal levels of total protein (5a), cholesterol (5c), calcium (5 h), and phosphorus (5i). The levels of magnesium (5j) in the TMR-2 cows were significantly lower (p\u0026lt;0.05) than those in the TMR-1 and TMR-3 cows. The AST (5f) levels were significantly higher (p\u0026lt;0.05) in the cows of TMR-2 (84.45 \u0026plusmn; 3.77 U/L) and TMR-3 (88.53 \u0026plusmn; 5.30 U/L) than in the cows of TMR-1 (70.46 \u0026plusmn; 2.82 U/L). The ALP 53 g) level in TMR-2 was much lower (157.70 \u0026plusmn; 6.25 U/L) than that in TMR-1 and TMR-3.\u003c/p\u003e\n\u003cp\u003eThe Pearson correlations between the biochemical parameters and nutritive values of the TMRs obtained in this study are presented in Figure 6. The TP content was positively correlated with the crude protein content in the cows in the TMR1 and TMR3 groups. Triglycerides were negatively correlated with crude fiber and NDF in TMR1, and cholesterol was strongly positively correlated with fat content in cows in the TMR2 group. ALT was negatively correlated with crude fiber, NDF and ADF in cows in the TMR1 and TMR3 groups and positively correlated with crude protein and fat in cows in the TMR2 group (Figure-6). AST was negatively correlated with crude fiber and ADF in the cows in the TMR1 group and positively correlated with crude protein in the TMR2 group. Mg was negatively correlated with ADF and NDF in the cows in the TMR2 group and weakly positively correlated with NFE in the cows in the TMR3 group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 5: Box plots presenting the biochemical profiles of total protein (a), triglyceride (b), cholesterol (c), creatinine (d), alanine transaminase (e), aspartate transferase (f), alkaline phosphatase (g), calcium (h), phosphorus (i), and magnesium (j) in lactating cows fed different TMRs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure-6: Pearson\u0026apos;s correlation between serum biochemical profiles and nutritive values of TMRs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAssociations\u003c/em\u003e\u003cem\u003e\u0026nbsp;among\u0026nbsp;\u003c/em\u003e\u003cem\u003ethe\u0026nbsp;\u003c/em\u003e\u003cem\u003eproductive, reproductive, and biochemical profiles of lactating cows\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFigure 7 shows the relationships among productive traits (e.g., milk yield), reproductive indicators (e.g., calving intervals), and various biochemical markers in lactating cows. Body weight was strongly negatively correlated with daily milk yield (r = -0.281, p = 0.000), ALT (r = -0.152, p = 0.026), and triglycerides (r = -0.138, p = 0.043). However, a slight positive correlation with duration of milk yield (r = 0.403, p = 0.000) and TP (r = 0.141, p = 0.037) was also observed. The daily milk yield was strongly positively correlated with triglycerides (r = 0.180, p = 0.009) and ALT (r = 0.273, p = 0.000) and negatively correlated with cholesterol (r = -0.303, p = 0.000) and ALP (r = 0.195, p = 0.005). There was a strong positive correlation of lactation length with the calving interval (r = 0.462, p = 0.003) and creatinine level (r = 0.465, p = 0.000) and moderate correlations with ALT and TG. A marked negative correlation was also observed between ALP (r = -0.350, p = 0.009) and TG (r = -0.304, p = 0.024). The first day of peak yield after calving was strongly positively correlated with triglycerides (r = 0.330, p = 0.000) and ALT (r = 0.239, p = 0.000). However, the duration of peak yield was positively correlated with creatinine (r = -0.121, p = 0.079) and negatively correlated with triglycerides (r = -0.193, p = 0.005) and ALP (r = -0.170, p = 0.014).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Age at the first AI showed a significant negative correlation with TP (r = -0.192, p = 0.005). Calving to first heat was strongly correlated with calving to first AI (r = 0.943, p = 0.000) and showed a moderate correlation with ALT. The calving interval was significantly negatively correlated with creatine (r = -0.397, p = 0.000), AST (r = -0.241, p = 0.008), and Mg (r = -0.239, p = 0.008). A positive correlation was also found with lactation duration (r = 0.462, p = 0.003) (r = 0.208, p = 0.024). The study revealed a strong positive correlation between TP and cholesterol (r = 0.352, p = 0.000) and a negative correlation with Mg (r = -0.197, p = 0.004). TG was strongly positively correlated with ALT (r = 0.820, p = 0.000) and cholesterol (r = 0.409, p = 0.000). Cholesterol was positively correlated with ALT and creatinine, whereas ALT was significantly positively associated with milk production. ALP was negatively correlated with the reproductive interval and peak yield duration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 7: Associations among productive, reproductive and biochemical parameters of lactating cows\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSuitable feeding strategies with balanced nutrients and appropriate management techniques are crucial to reduce stress and avoid metabolic diseases linked to maximal milk production in lactating cows (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Notably, the profitability and viability of dairy farms depend on successful reproduction. Information regarding the anticipated response of feeding systems to production and reproduction parameters that incorporate varying proportions of TMR is particularly scarce in Bangladesh. This study analyzed feed and blood profiles with productive and reproductive features depending on the feed provided. The dairy cows selected for the experiment were grouped on the basis of three different TMRs supplied and practiced at the selected dairy farm. However, decisions regarding the grouping of dairy cows are influenced by several variables, including herd demographics (i.e., distribution among parties, lactation stage, milk yield and distributions, reproductive stage, etc.), mixer wagon sizes, feed and forage inventories, and feed and milk prices (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). CF%, CP%, N-free extract, ADF%, and NDF% all showed significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) variations in subgroups on the basis of TMR when the nutritional benefits of TMR given to lactating cows were considered. The nutrient values for CP% and NDF% of the TMRs obtained in this study were higher than those recommended by (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)The National Research Council (NRC) (2021). NRC (2021) suggested a CP% of 16\u0026ndash;17.4% and an NDF level of approximately 25\u0026ndash;33% of dry matter in the rations of lactating dairy cows. As dietary NDF levels increase, milk production decreases linearly (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). According to (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)Grille et al. (2019) and (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)Capelesso et al. (2019), TMR-based systems improve productive performance in terms of milk yield, lipid profile, blood parameters, and energy status. Research has shown that blood parameters are affected by the amount of energy and minerals consumed. Diets high in energy, especially those that increase the levels of glucogenic precursors, are associated with increased levels of glucose, cholesterol, and triglycerides (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe study revealed that the body weight of cows in the TMR-1 group was highest and positively related to CF, NDF, and TP, which suggests that higher fiber intake is associated with better weight management and overall health. Body weight is negatively associated with CP, nitrogen-free extract, TG, ALT, and P. During peak lactation, an increase in body weight may be achieved by better rumen fermentation and feeding behavior, which are associated with increased NDF levels (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Protein levels are essential for maintaining body weight, whereas high crude protein levels may not be beneficial due to metabolic inefficiencies.\u003c/p\u003e\u003cp\u003eMilk yields were highest in cows given TMR 3, suggesting that these diets were successful in achieving maximum output. There seems to be a link between nutrition and continued milk production since lactating cows on TMR 3 had the most extended lactation durations. In this study, milk production was shown to be inversely related to dry matter (DM), ash, crude fiber, fat, NDF, and cholesterol contents and positively associated with oil protein, N-free extract, ADF, total protein, ALT, and ALP levels. Similar findings have been reported previously (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The significance of early lactation nutrition on peak yield was highlighted by the fact that TMR 2 cows had the highest first-day peak yield in this study. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)Hristov et al. (2004) reported a moderately favorable link between milk output and dry matter intake (DMI). Lowering prepartum energy consumption may reduce the milk supply (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). High-yielding cows often have more energy in their milk than they consume, which can negatively impact their metabolism and reproductive ability (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The results show that the duration of peak yield is associated with TMR 3. Nutritional interventions may prolong productive periods (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). On the other hand, dairy cows whose fertility is compromised due to an emphasis on high milk output should be nourished to promote both milk production and reproductive health (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe reproductive performance indicators discussed, such as the calving interval, age at first AI, calving to first heat, and calving to first AI, demonstrated a general consistency across the different TMR groups, indicating that diet type does not influence these metrics. The optimal age for AI in cows is influenced by factors such as breed, growth rate, and management practices. Holstein cows typically have an AFC of 15\u0026ndash;30 months, whereas Jersey cows may calve earlier. Early AI promotes reproductive efficiency and longer herd life (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Adequate nutrition and postpartal diseases are essential for optimal AFC (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Reducing the AFC can increase lifetime milk production and herd profitability (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The interval from calving to first heat (ICH) is a crucial indicator of reproductive recovery postpartum and is influenced by factors such as parity, body condition score (BCS), and environmental conditions. Multiparous cows tend to exhibit estrus earlier (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), whereas cows with lower BCSs experience delayed estrus (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Heat stress can prolong ICH by disrupting ovarian activity. The optimal duration of ICH is 40\u0026ndash;60 days, whereas the interval from calving to first AI (CFI) is 60\u0026ndash;80 days, allowing sufficient time for uterine involution and recovery while maintaining reproductive efficiency (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The value of calving to the first service interval achieved in the current study was greater than the value of 115 days for HF breeds in the Central Highlands of Ethiopia reported by (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)Tadesse et al. (2010), who also reported that negative energy balance, poor oestrus detection, and inadequate dairy cow oestrus expression contribute to extended CFSI in dairy production systems.\u003c/p\u003e\u003cp\u003eProviding TMRs on the basis of parity and production level can impact reproductive performance, as high-producing cows require specialized TMRs for energy balance and reproductive health (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The optimal calving interval for dairy cows is 12\u0026ndash;14 months, with variations in parity, health, and management techniques resulting in large swings. Multiparous cows have shorter intervals due to improved reproductive tract health, whereas seasonality influences calving intervals (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). However, findings on the calving interval, age at first AI, calving to first heat, and calving to first AI collectively underscore the robustness of reproductive performance across management groups, suggesting that under current conditions, other factors beyond diet might play a more critical role in influencing these key metrics.\u003c/p\u003e\u003cp\u003eThe physiological and nutritional health of dairy cows may be determined by measuring certain biochemical markers in their blood serum (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). The study revealed similar TP levels in lactating cows in the three TMR groups. Higher total protein levels may indicate earlier reproductive maturity, as research revealed a strong negative relationship between TP and the age of first AI. Low plasma protein levels result in a lack of amino acids needed for gonadotropin and gonadal hormone biosynthesis, potentially causing reproductive hormonal disturbances and inactive ovaries (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). According to (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)Alberghina et al. (2011), the environment (nutritional management, season, climate, etc.), breed, lactation stage, parity, and health condition all affect the concentration of blood proteins.\u003c/p\u003e\u003cp\u003eThe serum triglyceride level was the highest in the TMR 2 group. Dietary variation in TMR formulations had a minimal effect on circulating triglyceride concentrations. Usually, in lactating animals, the serum TG concentration increases as lactation progresses, as reported by (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e)Ghanem and El-Deeb (2010), Monteiro et al. (2012), and Perumal et al. (2023). Dairy cows use TG for lactation energy, forming milky fats. Triglyceride levels should be less than 150 mg/dl for steroidogenesis and milk fat production (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). All TMR diets were assumed to be equally effective in supporting lipid homeostasis, which aligns with the findings of previous studies.\u003c/p\u003e\u003cp\u003eThe highest value of cholesterol was found in cows supplied with TMR 3, but cholesterol concentrations in dairy cows were not significantly affected by TMR. The observed variability within groups suggests that other physiological or environmental factors may play a role in cholesterol regulation. A prolonged calving-to-first-heating interval was slightly linked with cholesterol levels, suggesting that postpartum reproductive recovery may have been delayed. High cholesterol levels resulting from fat supplementation increase progesterone and estradiol concentrations, reduce estradiol levels, and increase PGFM and PGF2 in addition to other hormones (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The physiological adjustment to satisfy the lactation requirements is a higher level of cholesterol as lactation progresses (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCreatinine, a byproduct of muscle metabolism, typically serves as an indicator of renal function and overall muscle mass. The dietary differences among the TMR groups did not cause detectable alterations in muscle metabolism or kidney performance under the conditions of this study, as there were no significant differences in the TMR groups (P\u0026thinsp;=\u0026thinsp;0.264). Its usefulness as a stable biochemical marker in nonpathological circumstances is supported by prior research, such as that of (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)Piccione et al. (2012), who reported low changes in blood creatinine levels throughout several physiological stages in dairy cattle. Creatinine levels demonstrated a mild negative relationship with age at first AI, implying that elevated creatinine may be linked to earlier sexual maturity.\u003c/p\u003e\u003cp\u003eALT, a liver enzyme, was not affected by TMR composition in this study, suggesting that the liver enzyme response was more physiologically driven than nutritionally driven. This aligns with findings from (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e)Gonz\u0026aacute;lez et al. (2011), who reported that the lactation stage can modulate liver enzyme activities independently of diet. Unlike ALT, AST levels varied significantly among the TMR groups, suggesting dietary effects on tissue metabolism or muscle turnover. Increased AST levels in the TMR2 and TMR3 diets may reflect subtle hepatocellular or muscular stress, possibly linked to diet composition. Similar patterns have been described by (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)Piccione et al. (2012), emphasizing the influence of specific feed components on enzymatic markers. ALP levels remained stable across dietary treatments, indicating that diet does not significantly affect bone metabolism or liver-related ALP production. These findings are consistent with those of previous reports (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), highlighting the stability of ALP in healthy lactating cows. Liver enzymes (ALT, AST, and ALP) were weakly positively associated with the calving interval, which could reflect mild metabolic or physiological stress affecting fertility. However, aminotransferases are known to maintain protein balance during the peak lactation phase of metabolism.\u003c/p\u003e\u003cp\u003eThe serum calcium concentrations of lactating cows were stable across the TMR diets, suggesting effective homeostatic regulation of calcium despite the high demands of lactation. This highlights the adequacy of the TMR formulations in maintaining mineral balance, in agreement with (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)Goff (2008), who noted robust calcium regulatory mechanisms in lactating cattle. The phosphorus concentration did not significantly differ with the TMR diet, reflecting the proper dietary phosphorus supply and homeostasis during lactation. The serum Mg levels slightly differed according to diet. The higher Mg concentration in TMR3-fed animals suggests minor dietary effects on magnesium status, possibly due to differences in mineral supplementation or fiber composition influencing absorption. Similar modest dietary effects on magnesium have been previously reported by (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e)Gr\u0026uuml;nberg (2014). There was a minimal link between magnesium and milk production features, such as lactation time and daily output, although phosphorus and calcium showed a favorable correlation. These biochemical indicators may be useful for tracking dairy output and enhancing reproductive efficiency, as suggested by (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e)Gonz\u0026aacute;lez et al. (2011) and Piccione et al. (2012).\u003c/p\u003e\u003cp\u003eIn TMR1, elevated levels of crude fiber and ADF appear to correlate with improved liver health indicators, specifically lower ALT and AST levels. Elevated crude protein levels seem to be advantageous for sustaining higher total protein concentrations in the serum. These findings are consistent with those of (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e)Anderson et al. (2009), who reported that increased dietary fiber may decrease hepatic lipid accumulation and associated enzyme elevation. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e)Vasilachi et al. (2022) reported that dietary composition marginally affects liver enzymes, total protein, and urea levels, although plasma mineral and enzyme levels are within physiological ranges. The biochemical profiles of TMR1-fed animals had a relatively minor influence on diet composition. The modest triglyceride‒fat relationship aligns with the general understanding that dietary fat intake can influence blood lipid profiles (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Increased crude protein intake in TMR2 may lead to mild elevations in liver enzymes (ALT/AST), potentially indicating heightened protein turnover or hepatic load, in line with the findings of (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e)Bernabucci et al. (2005). The negative impact of dietary fiber on magnesium absorption may have significant implications for diet formulation. The observed correlation between digestible carbohydrates (NFE) and magnesium in TMR3 indicates that energy-dense diets may increase mineral utilization. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e)Voronina et al. (2017) also highlighted the link between dietary energy and lipid metabolism.\u003c/p\u003e\u003cp\u003eFurthermore, the negative correlation between liver enzymes and fiber content highlights the potential hepatic advantages of high-fiber diets. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e)Lattimer and Haub (2010) documented similar relationships in studies of dairy cattle metabolism. In TMR3, while energy components still modestly influenced lipid metabolism, liver enzymes showed reduced sensitivity to diet. This suggests a possible better adaptation or a more balanced ratio profile. Similar stabilization effects have been reported by (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e)Trevisi et al. (2010) in cows fed more balanced rations. The blood and biochemicals of crossbred cows are affected by lactational phases (\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Notably, substantial nutritional inadequacies are obstacles to tropical cattle production methods (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Effective reproductive plans control the dynamics and structure of the herd, increasing on-farm replacements and reducing replacement and mortality costs. Reproductive performance is closely related to herd net return on TMR systems (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed that the ingredients of TMR significantly affect milk yield, pick yield duration, magnesium, ALT, and AST in lactating cows. In addition, there was a strong correlation between feed nutrient values and biochemical, productive, and reproductive parameters. To our knowledge, this study provides the first information on the effects of TMR content on blood metabolites and productive and reproductive performance in Frisian crossbred lactating cows reared in Bangladesh. Integrating biochemical, feed intake, and production data can improve dairy management's predictive accuracy. Multistage modeling in further research can optimize herd performance by assigning the most suitable TMR for each dairy cow. Feeding strategies should be adjusted on the basis of the lactation stage, reproductive intervals should be reduced through nutrition, and overreliance on fat content should be limited. Further research on ALT and TG as predictive biomarkers is suggested.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eTMR \u0026ndash; Total mixed ratio; TP \u0026ndash; Total protein; TG \u0026ndash; Triglyceride; ALT \u0026ndash; Alanine transaminase; AST \u0026ndash; Aspartate transaminase; ALP \u0026ndash; Alkaline phosphatase; CP \u0026ndash; Crude protein; NFE \u0026ndash; Nitrogen-free extract; ADF \u0026ndash; Acid detergent fiber; NDF \u0026ndash; Neutral detergent fiber\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their deepest gratitude and gratitude to the Livestock and Dairy Development Project (LDPP), Department of Livestock Services (DLS), Ministry of Fisheries and Livestock, Bangladesh, for funding this work, as it was a part of the Sub-Project \u0026quot;Speeding up genetic gain through embryo production and transfer for sustainable improvement of milk production in dairy cattle of Bangladesh (RP-A-01-26)\u0026quot; conducted by the Department of Surgery and Obstetrics, Bangladesh Agricultural University, Mymensingh, Bangladesh.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMAR conceptualized and designed the study. MSS, DR, UKR, MH,and AA collected the data. M H performed the statistical analysis and interpretation of the results. MAR and MSS prepared the original draft of the manuscript. NSJ, MH, RNF, and MSK \u0026nbsp;critically reviewed and revised the manuscript. NSJ supervised the overall research activity, and she, along with RNF and MSK contributed to project administration. All the authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Approved by the BAU Ethics Committee (Ref: AWEEC/BAU/2023 (03))\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003ePrior publication Data have not been published previously\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKerketta S, Sarangdevot S, Naruka P, Pachauri C, Verma S, Bhadauria S, et al. Production performance comparison of lactating buffaloes on feeding of total mixed ration versus conventional feeding. J Entomol Zool Stud. 2020;8(4):1657\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eSchingoethe DJ. A 100-Year Review: Total mixed ration feeding of dairy cows. J Dairy Sci. 2017 Dec;100(12):10143\u0026ndash;50.\u003c/li\u003e\n\u003cli\u003eSarker NR, Yeasmin D, Tabassum F, Habib MdA. An On-Farm Study for Feeding Impact of Total Mixed Ration (TMR) in Milking Cow. Curr J Appl Sci Technol. 2019 May 2;1\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eHe Y, Zhong R, Cheng L, You P, Li Y, Sun X. Effects of the Supplementation of Lysophospholipids through Pelleted Total Mixed Rations on Blood Biochemical Parameters and Milk Production and Composition of Mid-Lactation Dairy Cows. Animals. 2020 Jan 28;10(2):215.\u003c/li\u003e\n\u003cli\u003eCabrera VE, Kalantari AS. Economics of production efficiency: Nutritional grouping of the lactating cow. J Dairy Sci. 2016 Jan;99(1):825\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eNoakes D, Parkinson T, England G. In: Arthur\u0026rsquo;s Veterinary Reproduction and Obstetrics. 9th ed. Philadelphia: Elsevier Health Sciences; 2018.\u003c/li\u003e\n\u003cli\u003eGuzel S, Tanriverdi M. Comparison of serum leptin, glucose, total cholesterol and total protein levels in fertile and repeat breeder cows. Rev Bras Zootec. 2014 Dec;43(12):643\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eCoroian CO, Miresan V, Coroian A, Raducu C, Andronie L, Marchis Z, et al. Biochemical and Hematological Blood Parameters at Different Stages of Lactation in Cows. Bull Univ Agric Sci Vet Med Cluj-Napoca Anim Sci Biotechnol. 2017 May 18;74(1):31.\u003c/li\u003e\n\u003cli\u003eMcDonald P, Edwards R, Greenhalgh J, Morgan C, Sinclair L, Wilkinson R. Animal Nutrition. 7th ed. Harlow (UK): Pearson Education Limited; 2011.\u003c/li\u003e\n\u003cli\u003ePerumal P, De AK, Bhattacharya D, Chakurkar EB. Lactation stages modulate the hematological, serum biochemical, and endocrinological profiles and oxidative stress markers in crossbred cows under tropical humid island ecosystem of Andaman and Nicobar Islands. Trop Anim Health Prod. 2023 Apr;55(2):131.\u003c/li\u003e\n\u003cli\u003eNutrient Requirements of Beef Cattle. In: National Research Council. 7th ed. Washington (DC): National Academies Press; 2000.\u003c/li\u003e\n\u003cli\u003eShi R, Dong S, Mao J, Wang J, Cao Z, Wang Y, et al. Dietary Neutral Detergent Fiber Levels Impacting Dairy Cows\u0026rsquo; Feeding Behavior, Rumen Fermentation, and Production Performance during the Period of Peak-Lactation. Animals. 2023 Sep 10;13(18):2876.\u003c/li\u003e\n\u003cli\u003eGrille L, Adrien ML, Olmos M, Chilibroste P, Dami\u0026aacute;n JP. Diet change from a system combining total mixed ration and pasture to confinement system (total mixed ration) on milk production and composition, blood biochemistry and behavior of dairy cows. Anim Sci J. 2019 Nov;90(11):1484\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eCapelesso A, Kozloski G, Mendoza A, Pla M, Repetto JL, Cajarville C. Reducing milking frequency in early lactation improved the energy status but reduced milk yield during the whole lactation of primiparous Holstein cows consuming a total mixed ration and pasture. J Dairy Sci. 2019 Oct;102(10):8919\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eKrupin EO, Shakirov ShK. Changes in individual diagnostic markers of carbohydrate, lipid and mineral metabolism in dairy cows due to feeding. Agrar Sci. 2023 Mar 3;(2):30\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eIbtisham F, Nawab A, Li G, Xiao M, An L, Naseer G. Effect of nutrition on reproductive efficiency of dairy animals. Med Weter. 2018;74(1):6025\u0026ndash;2018.\u003c/li\u003e\n\u003cli\u003eHristov AN, Etter RP, Ropp JK, Grandeen KL. Effect of dietary crude protein level and degradability on ruminal fermentation and nitrogen utilization in lactating dairy cows1. J Anim Sci. 2004 Nov 1;82(11):3219\u0026ndash;29.\u003c/li\u003e\n\u003cli\u003eSilva-del-R\u0026iacute;o N, Fricke PM, Grummer RR. Effects of twin pregnancy and dry period feeding strategy on milk production, energy balance, and metabolic profiles in dairy cows1. J Anim Sci. 2010 Mar 1;88(3):1048\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eReynolds CK. Production and metabolic effects of site of starch digestion in dairy cattle. Anim Feed Sci Technol. 2006 Sep;130(1\u0026ndash;2):78\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eMcNamara JP, Shields SL. Reproduction during lactation of dairy cattle: Integrating nutritional aspects of reproductive control in a systems research approach. Anim Front. 2013 Oct 1;3(4):76\u0026ndash;83.\u003c/li\u003e\n\u003cli\u003eAtashi H, Asaadi A, Hostens M. Association between age at first calving and lactation performance, lactation curve, calving interval, calf birth weight, and dystocia in Holstein dairy cows. Abuelo A, editor. PLOS ONE. 2021 Jan 4;16(1):e0244825.\u003c/li\u003e\n\u003cli\u003eVargas-Leit\u0026oacute;n B, Romero-Z\u0026uacute;\u0026ntilde;iga JJ, Castillo-Badilla G, Sabor\u0026iacute;o-Montero A. Optimal Age at First Calving in Pasture-Based Dairy Systems. Dairy. 2023 Oct 30;4(4):581\u0026ndash;93.\u003c/li\u003e\n\u003cli\u003eHernandez-Gotelli C, Manr\u0026iacute;quez D, Azocar J, De Vries A, Pinedo PJ. Factors associated with the time and magnitude of the nadir body condition score in early lactation and its subsequent effects on fertility of Holstein cows. J Anim Sci. 2023 Jan 3;101:skad119.\u003c/li\u003e\n\u003cli\u003eEdvardsson Rasmussen A, Holtenius K, B\u0026aring;ge R, Strandberg E, \u0026Aring;kerlind M, Kronqvist C. A randomized study on the effect of extended voluntary waiting period in primiparous dairy cows on milk yield during first and second lactation. J Dairy Sci. 2023 Apr;106(4):2510\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eDo C, Wasana N, Cho K, Choi Y, Choi T, Park B, et al. The Effect of Age at First Calving and Calving Interval on Productive Life and Lifetime Profit in Korean Holsteins. Asian-Australas J Anim Sci. 2013 Nov 1;26(11):1511\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eKoyama K, Kubo T, Koyama T, Takahashi Y. Parity affects the relationship between the insemination\u0026ndash;ovulation interval and the conception rate in lactating dairy cows. Reprod Domest Anim. 2023 Jul;58(7):895\u0026ndash;902.\u003c/li\u003e\n\u003cli\u003eHaile B. Reproductive Performance of Holstein Friesian Dairy Cows at Alage Dairy Farm, Ethiopia. J Dairy Vet Sci [Internet]. 2018 Aug 20 [cited 2025 Sep 12];7(3). Available from: https://juniperpublishers.com/jdvs/JDVS.MS.ID.555713.php\u003c/li\u003e\n\u003cli\u003eStrickland JM, Martins JPN, Neuder L, Pursley JR. When Implementing the Presynch-11/Ovsynch Reproductive Management Program, the Fertility of Lactating Dairy Cows Improved When They Received Timed Artificial Insemination Compared with the Inclusion of Estrus Detection. Animals. 2024 Jul 31;14(15):2235.\u003c/li\u003e\n\u003cli\u003eTadesse M, Thiengtham J, Pinyopummin A, Prasanpanich S. Productive and reproductive performance of Holstein Friesian dairy cows in Ethiopia. Livest Res Rural Dev. 2010;22(2).\u003c/li\u003e\n\u003cli\u003eTalukder S, Celi P, Kerrisk KL, Garcia SC, Dhand NK. Factors affecting reproductive performance of dairy cows in a pasture-based, automatic milking system research farm: a retrospective, single-cohort study. Anim Prod Sci. 2015;55(1):31.\u003c/li\u003e\n\u003cli\u003eFunakoshi D, Shiotani H, Seki M. Equine chorionic gonadotropin treatment and timed artificial insemination for dairy cow production under heat stress. J Reprod Dev. 2024;70(1):30\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eJ\u0026oacute;źwik A, Strzałkowska N, Bagnicka E, Grzybek W, Krzyżewski J, Poławska E, et al. Relationship between milk yield, stage of lactation, and some blood serum metabolic parameters of dairy cows. Czech J Anim Sci. 2012 Aug 31;57(8):353\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eArosh A, Kathiresan D, Devanathan T, Rajasunadaram R, Rajasekaran J. Blood biochemical profile in normal cyclical and anoestrus cows. Indian J Anim Sci. 2012;68(11).\u003c/li\u003e\n\u003cli\u003eAlberghina D, Giannetto C, Vazzana I, Ferrantelli V, Piccione G. Reference intervals for total protein concentration, serum protein fractions, and albumin/globulin ratios in clinically healthy dairy cows. J Vet Diagn Investig Off Publ Am Assoc Vet Lab Diagn Inc. 2011 Jan;23(1):111\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eGhanem MM, El-Deeb WM. Lecithin cholesterol acyltransferase (LCAT) activity as a predictor for ketosis and parturient hemoglobinuria in Egyptian water buffaloes. Res Vet Sci. 2010 Feb;88(1):20\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eMonteiro BM, Yasuoka MM, Pogliani FC, Ayres H, Viana RB, Birgel Junior EH. Lipid and glucose profiles of dairy buffaloes during lactation and dry period. Rev Ci\u0026ecirc;nc Agr\u0026aacute;r. 2012;55(1):33\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eRoccio F, Claude-Taupin A, Botti J, Morel E, Codogno P, DuPont N. Monitoring lipophagy in kidney epithelial cells in response to shear stress. In: Methods in Cell Biology [Internet]. Elsevier; 2021 [cited 2025 Sep 12]. p. 11\u0026ndash;25. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0091679X20302090\u003c/li\u003e\n\u003cli\u003eAhmad I, Lodhi L, Qureshi Z, Younis M. Studies on blood glucose, total proteins, urea and cholesterol levels in cyclic, noncyclic and endometritic crossbred cows. Pak Vet J. 2004;24(2):92\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eAshmawy NA. Blood Metabolic Profile and Certain Hormones Concentrations in Egyptian Buffalo During Different Physiological States. Asian J Anim Vet Adv. 2015 May 15;10(6):271\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003ePiccione G, Messina V, Marafioti S, Casella S, Giannetto C, Fazio F. Changes of some hematochemical parameters in dairy cows during late gestation, post partum, lactation and dry periods. 2012;58:59-64.\u003c/li\u003e\n\u003cli\u003eGonz\u0026aacute;lez FD, Mui\u0026ntilde;o R, Pereira V, Campos R, Benedito JL. Relationship among blood indicators of lipomobilization and hepatic function during early lactation in high-yielding dairy cows. J Vet Sci. 2011;12(3):251.\u003c/li\u003e\n\u003cli\u003eKlinkon M, Jeek J. Values of Blood Variables in Calves. In: Perez-Marin CC, editor. A Bird\u0026rsquo;s-Eye View of Veterinary Medicine [Internet]. InTech; 2012 [cited 2025 Sep 12]. Available from: http://www.intechopen.com/books/a-bird-s-eye-view-of-veterinary-medicine/values-of-blood-variables-in-calves\u003c/li\u003e\n\u003cli\u003eGoff JP. The monitoring, prevention, and treatment of milk fever and subclinical hypocalcemia in dairy cows. Vet J. 2008 Apr;176(1):50\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eGr\u0026uuml;nberg W. Treatment of Phosphorus Balance Disorders. Vet Clin North Am Food Anim Pract. 2014 Jul;30(2):383\u0026ndash;408.\u003c/li\u003e\n\u003cli\u003eAnderson JW, Baird P, Davis RH, Ferreri S, Knudtson M, Koraym A, et al. Health benefits of dietary fiber. Nutr Rev. 2009 Apr;67(4):188\u0026ndash;205.\u003c/li\u003e\n\u003cli\u003eVasilachi A, Ciurescu G, Hăbeanu M. Plasma biochemical profile of dairy cows, with respect to diet and breed. Arch Zootech. 2022 Jun 1;25(1):75\u0026ndash;89.\u003c/li\u003e\n\u003cli\u003eBobe G, Young JW, Beitz DC. Invited Review: Pathology, Etiology, Prevention, and Treatment of Fatty Liver in Dairy Cows. J Dairy Sci. 2004 Oct;87(10):3105\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003eBernabucci U, Ronchi B, Lacetera N, Nardone A. Influence of Body Condition Score on Relationships Between Metabolic Status and Oxidative Stress in Periparturient Dairy Cows. J Dairy Sci. 2005 Jun;88(6):2017\u0026ndash;26.\u003c/li\u003e\n\u003cli\u003eA. Voronina О, S. Tsarkova M, Yu. Zaitsev S. Nutrition Influence on Blood Colloid and Biochemistry Parameters of the Lactating Cow. Biosci Biotechnol Res Asia. 2017 Mar 28;14(1):89\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eLattimer JM, Haub MD. Effects of Dietary Fiber and Its Components on Metabolic Health. Nutrients. 2010 Dec 15;2(12):1266\u0026ndash;89.\u003c/li\u003e\n\u003cli\u003eTrevisi E, Minuti A. Assessment of the innate immune response in the periparturient cow. Res Vet Sci. 2018 Feb;116:47\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eHasan M, Rahman M, Mahbub A, Belal S, Ahmed T. Performance of different crossbred cattle at Comilla District of Bangladesh. J Sylhet Agric Univ. 2014;1(2):161\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eFadlalla IMT, Omer SA, Atta M. Determination of some serum macroelement minerals levels at different lactation stages of dairy cows and their correlations. Sci Afr. 2020 Jul;8:e00351.\u003c/li\u003e\n\u003cli\u003eGautam K, Pant V, Pradhan S, Pyakurel D, Bhandari B, Shrestha A. Blood lead levels in rag-pickers of Kathmandu and its association with hematological and biochemical parameters. Electron J Int Fed Clin Chem Lab Med. 2020;31(2):125.\u003c/li\u003e\n\u003cli\u003eHudaya MF, Sitaresmi PI, Noviandi CT, Widyobroto BP, Widayati DT. Behavior and blood profile in Friesian-Holstein dairy cows in the special region of Yogyakarta, Indonesia. J Anim Behav Biometeorol. 2020 Jun 26;8(4):244\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eGiordano JO, Kalantari AS, Fricke PM, Wiltbank MC, Cabrera VE. A daily herd Markov-chain model to study the reproductive and economic impact of reproductive programs combining timed artificial insemination and estrus detection. J Dairy Sci. 2012 Sep;95(9):5442\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eGalv\u0026atilde;o KN, Federico P, De Vries A, Schuenemann GM. Economic comparison of reproductive programs for dairy herds using estrus detection, timed artificial insemination, or a combination. J Dairy Sci. 2013 Apr;96(4):2681\u0026ndash;93.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Bangladesh Agricultural University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Total mixed ratio, Serum biochemical profiles, Frisian crossbred, Production, Reproduction","lastPublishedDoi":"10.21203/rs.3.rs-7972443/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7972443/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThis study assessed the impact of the total mixed ratio (TMR) on milking cow productivity and reproductive and serum biochemical profiles and investigated the correlations between TMR nutrient values and cow traits.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 95 lactating cows were used and grouped into TMR1, TMR2 and TMR3 according to the TMR provided. The study revealed that all three meals had 96.3% dry matter, with TMR3 having the most nitrogen-free extract, crude fiber, and crude protein, whereas TMR-1 had the least protein, crude fiber, and neutral detergent fiber. Considering the nutritive values of the TMR provided to the lactating cows, crude fiber (CF), crude protein (CP), N-free extract, acid detergent fiber (ADF), and neutral detergent fiber (NDF) percentages significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) differed among the TMR subgroups. The study revealed no significant outliers in body weight, daily milk yield, lactation length, first day of peak yield, or duration of peak yield in cows in the TMR3 group. The cows in the TMR 1 group presented the greatest first-day pick yield after calving, daily milk output, lactation length, and pick yield duration. Daily milk output and lactation duration were moderately to strongly positively correlated with CP and CF. Reproductive indicators varied more than productive features did in Group TMR3 cows. However, the medians for age at first artificial insemination (AI), calving to first heat, first AI, and the calving interval were comparable across all groups. Energy- and protein-rich meals improved reproductive efficiency, whereas fat content had no effect. The research revealed that TMR2 cows had considerably lower magnesium levels than TMR1 and TMR3 cows did. AST levels were higher in TMR2 and TMR3 cows than in TMR1 cows, whereas ALP levels were lower in TMR2 cows. Body weight had a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) positive relationship with crude fiber% and NDF%, a negative relationship with crude protein%, nitrogen-free extract, and ADF% milk yield, a strong (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) negative relationship with DM%, Ash%, crude fiber%, fat%, and NDF%, and a positive relationship with CP%, N-free extract%, and ADF. The results revealed a significant negative relationship between the duration of pick yield and N-free extract%, ADF%, triglyceride, alkaline phosphatase (ALP), and glucose contents and a positive relationship with crude protein% and NDF%. Calving to the first heat was significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) negatively related to TP and ALP and positively related to lactation duration (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis study suggests that efficient ration formulation can enhance milk production, reproductive performance, and metabolic health in dairy herds of Frisian crossbred lactating cows in Bangladesh.\u003c/p\u003e","manuscriptTitle":"Effects of Total Mixed Ration on Blood Biochemistry, Productivity, and Reproduction in Bangladeshi Frisian Crossbred Lactating Cows","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 10:09:06","doi":"10.21203/rs.3.rs-7972443/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"af5d9cb9-0d29-46c4-88d6-33fb1f662ac4","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57039343,"name":"Animal Science"}],"tags":[],"updatedAt":"2025-10-30T10:09:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-30 10:09:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7972443","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7972443","identity":"rs-7972443","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}