Studies on the management of dairy cows during the transition period are increasingly frequent in recent years (Barraclough et al., Reference Barraclough, Shaw, Thorup, Haskell, Lee and Macrae2020; Redfern et al., Reference Redfern, Sinclair and Robinson2021a; Kerwin et al., Reference Kerwin, Burhans, Mann, Tetreault, Nydam and Overton2022). However, there is still a lack of information, especially regarding the appropriate energy level for optimal animal response, particularly in the period from three weeks pre-partum to three weeks post-partum (Pérez-Báez et al., Reference Pérez-Báez, Risco, Chebel, Gomes, Greco, Tao and Galvão2019).
During the transition period, the cow undergoes several physiological, hormonal, and behavioural changes, such as increased fetal growth, decreased feed intake, and the onset of milk production (Sundrum, Reference Sundrum2015; Wankhade et al., Reference Wankhade, Manimaran, Kumaresan, Jeyakumar, Ramesha, Sejian, Rajendran and Varghese2017). Due to these changes, having an adequate nutritional status in the prepartum period is extremely important to reduce the impact of negative energy balance (Yang et al., Reference Yang, Dong, Zheng, Kon, Lv, Sun, Wang, Cao, Wang and Li2022) and, consequently, the development of metabolic disorders.
A negative energy balance can be defined as a nutritional deficit resulting from inadequacy or non-fulfillment of the animal's energy needs through voluntary feed intake. Cows have increased energy requirements in the last month of pregnancy; however, their dry matter intake (DMI) decreases, making it difficult to meet their nutritional demands (Zambrano and Marques, Reference Zambrano and Marques2009; Sguizzato et al., Reference Sguizzato, Marcondes, Dijkstra, Valadares Filho, Campos, Machado, Silva and Rotta2020). Futhermore, the onset of lactation results in a sudden increase in energy requirements, which leads to severe NEB in early lactation that is exacerbated by the depressed DMI (Sundrum, Reference Sundrum2015).
The nutritional status of animals during the transition period must be carefully considered to prevent metabolic problems. With the approach of parturition, the decrease in DMI is accentuated, decreasing nutrient intake and acting negatively on the subsequent lactation (Havekes et al. Reference Havekes, Duffield, Carpenter and DeVries2020). Conversely, high energy intake in the prepartum transition period may increase body condition score (BCS, Useni et al., Reference Useni, Muller and Cruywagen2018; Nazhat et al., Reference Nazhat, Aziz, Zabuli and Rahmati2021). Animals with a BCS > 3.5 (5-point scale; 0.25-point increment) may exhibit low DMI due to an increase in leptin, a hormone produced by adipose tissue that acts as a limiter of intake in the close-up prepartum period (Block et al., Reference Block, Rhoads, Bauman, Ehrhardt, McGuire, Crooker, Griinari, Mackle, Weber, Van Amburgh and Boisclair2003).
Several studies described the improvement of metabolic parameters with pre-partum dietary management. However, it is crucial to strike a balance between sufficient physically effective fibre and starch fermentability. The following question thus arises: is there an ideal energy level for cows in the transition period, and what is the impact of this level on the energy production and metabolism of these animals during this period?
Distinct studies on dairy cattle have been undertaken with divergent foci, in different countries, and in large research centers investigating the reproductive, metabolic, and hormonal problems caused during the transition period (Girma et al., Reference Girma, Ma, Wang, Jiang, Callaway, Drackley and Bu2019; Redfern et al., Reference Redfern, Sinclair and Robinson2021b; Kerwin et al., Reference Kerwin, Burhans, Mann, Tetreault, Nydam and Overton2022), specific strategies such as monensin supplementation during the prepartum period (Vasquez et al., Reference Vasquez, McCarthy, Richards, Perfield, Carlson, Lock and Drackley2021), and to assess the effects of dietary energy density (Pineda et al., Reference Pineda, Cardoso, Murphy and Drackley2022). Nevertheless, none of them addresses the appropriate energy level for cows in this phase, nor do they employ the systematic review and meta-analysis technique.
Systematic reviews and meta-analyses are tools that have been widely used in animal science, reducing bias in the search for studies, allowing the compilation and use of existing experimental data, and ensuring more reliable results (Almeida and Goulart, Reference Almeida and Goulart2017). The present paper describes a systematic review and meta-analysis aimed at determining the appropriate energy level in prepartum diet to reduce the effects of a negative energy balance on milk production and energy metabolism of dairy cows in the transition period.
Materials and methods
Search strategy
This systematic review was conducted in accordance with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) (Moher et al., Reference Moher, Liberati, Tetzlaff and Altman2009). The PICO strategy followed the PRESS guidelines (McManaman, Reference McManaman2015) and defined Population – Patients: dairy cattle; Intervention: prepartum diet; Comparison: diets; and Results: energy metabolism and milk production and components. The PICO strategy was used to answer the research question regarding energy levels in the transition period: What is the most appropriate energy level in the diet of lactating cows and how does this level influence milk production and energy metabolism?
The searches were performed in January and February 2021, based on the title and the abstract, and involved language refinement that included articles in English, Portuguese, and Spanish. Four databases were used: Web of Science, Scopus, PubMed, and Scielo. As a strategy, the Boolean moderators “AND” and “OR” were used to help find as many results as possible. The search terms are presented in Fig. 1.
Literature retrieval flow chart – PRISMA.
To identify potential additional articles, the reference lists of the articles selected for inclusion in the database were reviewed. The extensive search for scientific articles in several databases was aimed at avoiding potential publication bias. After identification, the studies were critically evaluated according to relevance and quality regarding the study objectives. Fig. 1 shows a flow chart (PRISMA) of the summarized search procedure.
Selection of articles
After the literature search was performed, the articles were opened in the EndNote™ reference management tool, which helped to eliminate replicas and organize the items. All articles were tabulated in a MS Excel® (2020) file under the following headings: a) Author, b) Journal, c) Year, d) Title, e) Meets the selection criteria, f) Does not meet the selection criteria, g) Reason why the article does not meet the selection criteria. Two reviewers selected and assessed the eligibility of studies for systematic review.
Eligibility criteria were previously defined for selection by title, abstract, and full text. In the title selection phase, it was specified that the article should present characteristics referring to dairy cows in the transition period. In the abstract selection phase, the text should describe energy intake data in the transition period. In the full-text selection phase, the inclusion criteria were as follows: (1) in vivo experimental evaluation of diets with different energy levels; (2) presentation of initial, final, and/or total results and statement of treatment period; (3) description of DMI, milk production, blood and feed efficiency data; (4) articles published from the year 2000 onwards.
During the eligibility process, 971 articles were excluded at the title selection stage, 74 at the abstract reading stage, and 62 at the full-text reading stage. A total of 36 articles, published between 2000 and 2020, were selected to form the database, with the highest proportion published in 2020 (17.64%). These articles were primarily published in the Journal of Dairy Science (59.45%), and the studies were conducted predominantly in the United States (47.2%) and China (11%) (Fig. 2).
Origin of published studies used. The colors indicate the amount of publication by each country of origin. Number of publications: USA, 17; Canada, 3; Ireland, 2; China, 4; Brazil, 2; Iran, 1; Pakistan, 1; Denmark, 2; Finland, 2; Germany, 2.
Data systematization and coding
The methodology employed for constructing the database and data coding adhered to methods previously described in the literature (Lovatto et al., Reference Lovatto, Lehnen, Andretta, Carvalho and Hauschild2007; Sauvant et al., Reference Sauvant, Schmidely, Daudin and St-Pierre2008), whereby data were entered and organised in an spreadsheet. In this spreadsheet, rows represented the values and columns the explored variables. Information relevant to the purpose of this study (energy level, DMI, milk production, and blood metabolic data) and other variables (number of lactations, production system, dietary nutritional composition, and duration of the experimental period) was included to allow a critical and descriptive analysis of the studies (Table 1). Average or summarised values from the studies were used.
Overview of 36 publications included in the data tabulation of the meta-analysis
1 Some ingredients are commercial products and are fully described in the original articles
When tabulating the data, transformations were applied to the units used in the publications to align them with the units presented in our study. All data underwent standard transformations to the International System of Units (SI). Specifically for energy intake during the transition period, the equation NEL (Mcal/kg) = ME (Mcal/kg) * 0.66 was employed (National Academies of Sciences Engineering and Medicine – NASEM, 2021). Subsequently, the variables’ units were converted from Mcal to MJ.
Graphical analyses were utilised to examine data dispersion, data consistency, and behaviour. Descriptive analysis was performed to facilitate data visualisation. Based on these observations, hypotheses were formulated to define the statistical models, as proposed by Lovatto et al. (Reference Lovatto, Lehnen, Andretta, Carvalho and Hauschild2007). As the data from the articles exhibited a range of pre-partum energy levels, polynomial regression analysis was subsequently performed, employing a link function where necessary. The GLIMMIX procedure (SAS Institute Inc, 2018) was employed. A completely randomised design was adopted for the analysis, utilising a mixed-model methodology wherein fixed effects (pre-partum energy level) and random effects (article) were incorporated into the model, as follows:
Yijk = μ + αi + Aj + εijk
Where: Yijk is the observation related to the i-th pre-partum energy level (αi) within the j-th article effect (Aj). The optimal distribution and model fit were selected based on the corrected Akaike Information Criterion (AICc). SAS OnDemand was utilised for statistical analysis.
Results
Subsequent to the data collection through systematic review, the average chemical composition of the diets was determined, in conjunction with the dispersion measures (Table 2). The dispersion measures indicate variation in the responses among the articles evaluated (Table 3).
Chemical composition of the database
* Values expressed on a dry-matter basis; SEM, Standard error of mean; SD, Standard deviation
Dispersion measurements for milk yield, milk nutrient content, energy balance, and body and blood variables
Mean±Standard error of the mean; CV, coefficient of variation; SD, standard deviation;
§ Milk production corrected for 0.4g fat/kg of milk; BCS, Body condition score; DM, Dry matter; DMI, Dry matter intake; BHB, β-hydroxybutyrate; NEFA, Non-esterified fatty acids
No increase in DMI was observed, as evidenced by the slope coefficient of the line, i.e., the angular coefficient (β1; P>0.05; Table 4). Upon observing the milk production and milk solids parameters (Table 4), protein, fat, and lactose did not significantly differ with adjustments in energy intake during the transition period (P>0.05). Milk production and fat-corrected milk decreased with increased energy availability, in contrast to pre-partum DMI and BCS, which increased. However, blood parameters during the transition period did not correlate with energy consumed during this period, except for NEFA, which displayed a decrease in blood concentration with increased energy intake during the transition period (Table 4).
Regression model fitting of diet energy level during the 3-week prepartum period on milk yield, milk nutrient content, energy balance, and body and blood variables
* P<0.05; **P<0.01; ***P<0.001; β0, intercept; β1 angular coefficient; Article, article random effect on model; Residual, residual variance; Mean±Standard error of the mean; §Milk production corrected for 0.4g fat/kg of milk; BCS, Body condition score; DM, Dry matter; DMI, Dry matter intake; BHB, β-hydroxybutyrate; NEFA, Non-esterified fatty acids. §§y=exp (g)=β0+β1X
In the postpartum period, feed efficiency and BHB showed a significant increase with the higher energy in the transition period (Table 4). Blood glucose in the postpartum period did not fluctuate with the variation of energy intake in the transition period (P > 0.05). Lactation energy balance demonstrated no relationship with the energy intake during the transition period, as evidenced by non-significant regression coefficients (P > 0.05).
Discussion
Analysis of the collected data highlights the variability across the publications incorporated into the systematic review. This variation may be partly explained by the geographical context of the experiments and the publication timeline (Impellizzeri and Bizzini, Reference Impellizzeri and Bizzini2020; Pigott and Polanin, Reference Pigott and Polanin2020). Critically, the number of studies tends to strengthen the meta-analysis, ensuring its robustness and reliability (Papakostidis and Giannoudis, Reference Papakostidis and Giannoudis2023).
Intake and energy balance
Prepartum energy intake did not affect postpartum DMI. This finding corroborates the reports of Mann et al. (Reference Mann, Yepes, Overton, Wakshlag, Lock, Ryan and Nydam2015), who described that a lower energy intake in the prepartum period does not influence postpartum DMI. As observed in our study, the lower prepartum dry matter and energy intakes did not exhibit a significant difference for postpartum DMI. Due to the decline in feed intake in the last weeks prepartum, the energy density of the diet is normally increased to maximize the animal's energy intake.
Diets with higher energy levels tend to increase the BCS and reduce DMI by increasing the circulation of leptin, produced by adipose tissue, which limits intake in the transition period (Roche et al., Reference Roche, Friggens, Kay, Fisher, Stafford and Berry2009). Energy-overfed cows exhibited higher plasma leptin than those underfed (Kokkonen et al., Reference Kokkonen, Taponen, Anttila, Syrjälä-Qvist, Delavaud, Chilliard, Tuori and Tesfa2005). Conversely, Janovick et al. (Reference Janovick, Boisclair and Drackley2011), when evaluating the effect of prepartum energy intake level on metabolic profiles, found that cows fed ad libitum displayed a more pronounced NEB postpartum; however, this did not influence leptin concentration. A high BCS at calving can negatively impact a cow's reproductive health in several ways. Cows calving with a BCS of 3.5 or higher at calving are 2.5 times more likely to develop ketosis than cows with a BCS of 3.25 or lower (Gillund et al., Reference Gillund, Reksen, Gröhn and Karlberg2001). The risks associated with this condition include longer intervals to first ovulation, first oestrus, insemination, and conception (De Rensis et al., Reference De Rensis, Dall'Olio, Gnemmi, Tummaruk, Andrani and Saleri2024) and increased embryonic losses (Stevenson and Atanasov, Reference Stevenson and Atanasov2022). Otherwise, loss of BCS in the onset of pregnancy can also lead to increased embryonic losses.
A further pertinent aspect observed was the quality of the forage used, particularly grain-rich silages such as maize, the predominant forage encountered. The forage, or the source of starch employed, is a critical factor in dietary balance, as it shows a relationship with amylose or amylopectin content. Through adjustments, it is possible to mitigate the likelihood of impacts on fibre digestion, whilst also aiding in the maintenance of rumen acetate concentrations (Cañizares et al., Reference Cañizares, Rodrigues and Cañizares2009). The fermentation process converts amylopectin into shorter amylose chains by cleaving the α1,6 C-C bonds at branch points, thus accelerating its degradation rate relative to longer amylose chains.
Mann et al. (Reference Mann, Yepes, Overton, Wakshlag, Lock, Ryan and Nydam2015) examined diets containing 24% and 15% starch (dry-matter basis) and observed that the diet with the higher starch content resulted in a higher prepartum DMI; however, in the postpartum period, there was no significant difference in DMI, consistent with our study. However, excess energy intake pre-partum increases susceptibility to peripartum ketosis and may impair insulin sensitivity in parturient cows (Salin et al., Reference Salin, Vanhatalo, Elo, Taponen, Boston and Kokkonen2017). Also, postpartum DMI in dairy cows can be negatively impacted by high dietary starch levels due to increased volatile fatty acid production and potential rumen pH depression, while dietary NDF also plays a significant role in ruminal fill and intake (National Academies of Sciences Engineering and Medicine – NASEM, 2021; Mirzaei-Alamouti et al., Reference Mirzaei-Alamouti, Panahiha, Patra and Mansouryar2022). Haisan et al. (Reference Haisan, Inabu, Shi and Oba2021), assessing how varying starch levels in pre- and postpartum diets impact dairy cow productivity during the transition period, reports that the provision of high-starch postpartum diets may mitigate fat mobilisation and systemic inflammatory responses, as evidenced by serum indicators, and concurrently enhance milk yield, despite a preceding low-starch prepartum diet.
Schirmann et al. (Reference Schirmann, Chapinal, Weary, Vickers and Von Keyserlingk2013) and Mann et al. (Reference Mann, Yepes, Overton, Wakshlag, Lock, Ryan and Nydam2015) mentioned that diets with higher starch content during the end of lactation and dry period, improve the body condition of the animals, but ketone concentrations are higher in the postpartum period due to energy requirements not being met by voluntary intake, potentially causing ketosis, and reducing feed intake and milk production efficiency. Therefore, dietary adjustment, involving a reduction in NDF content and an increase in energy density, should be implemented while maintaining the minimum required levels of effective fibre (National Academies of Sciences Engineering and Medicine – NASEM, 2021).
Blood variables
NEB in early lactation is common to all mammals, but its intensity and duration can be minimized by dietary manipulation (Sundrum, Reference Sundrum2015). In our analysis, prepartum energy intake was not significantly associated with estimated postpartum energy balance but high energy intake was significantly associated with higher postpartum plasma BHB and NEFA concentrations.
With an increase in dietary energy density prepartum, an increase in BCS was observed, even when DMI was similar. This resulted in lower levels of glucose available for the hepatic metabolism of fatty acids. The high energy demand immediately after calving increases the mobilisation of energy stored in the tissues, which increases plasma NEFA and BHB concentrations. Thus, cows with a greater energy intake in the prepartum period, are more likely to present situations compliant with NEB indicators, such as low serum glucose levels and increased plasma concentrations of BHB and NEFA, not taking energy balance (variable) as the exclusive reference.
Conversely, the increment in the energy intake prepartum can indirectly induce an increase in NEB during postpartum. Animals with low plasma glucose levels prepartum tend to exhibit elevated BHB levels pre- and post-partum. Insulin resistance is the main factor to enhance plasma glucose levels prepartum (Qiao et al., Reference Qiao, Jiang, Contreras, Xie, Pascottini, Opsomer and Dong2024), when there is an increased requirement for energy and nutrients, particularly glucose and fatty acids, for fetal growth, in addition, this increase causes a reduction in insulin sensitivity in peripheral tissues, leading to insulin resistance and an increase in glucose levels in the bloodstream (Salin et al., Reference Salin, Vanhatalo, Elo, Taponen, Boston and Kokkonen2017). The increase in circulating insulin, stimulated by the rise in growth hormone (GH) pre-calving, promotes lipolysis (Gobikrushanth et al., Reference Gobikrushanth, Purfield, Colazo, Wang, Butler and Ambrose2018), which is consistent with the correlation between glucose and BHB and NEFA. The fluctuation in plasma glucose levels is not linked to DMI or energy intake during this period.
According to Pérez-Báez et al. (Reference Pérez-Báez, Risco, Chebel, Gomes, Greco, Tao and Galvão2019), a decrease in DMI at the end of the transition period and low postpartum DMI lead to a negative energy balance, characterized by increased lipid mobilization in the form of NEFA and a consequent increase in ketone bodies such as BHB. Marett et al. (Reference Marett, Auldist, Wales, Macmillan, Dunshea and Leury2018) mentioned that NEFA are a result of the mobilization of adipose tissue triggered by a negative energy balance, in addition to representing an important source of energy in the first days of lactation and being one of the main sources for the synthesis of milk fat (Štolcová et al., Reference Štolcová, Řehák and Bartoň2021).
Moreover, NEFA values above 0.40 mmol/L can be risk factors for the health of the animal and can be considered an optimal indicator of subclinical ketosis, reduced intake, greater mobilization of body reserves, as well as greater negative energy balance (Oetzel, Reference Oetzel2004; Whitaker, Reference Whitaker, Andrews, Blowey, Boyd and Eddy2004; Tremblay et al., Reference Tremblay, Kammer, Lange, Plattner, Baumgartner, Stegeman, Duda, Mansfeld and Döpfer2018).
McArt et al. (Reference McArt, Nydam, OetzeL, Overton and Ospina2013) reported that a periodic assessment of NEFA and BHB in dairy herds can provide important data, since herds with a prevalence of around 15% of animals with high levels of these indicators display problems in subsequent lactations, such as a drop in milk production and greater prevalence of problems arising from NEB. However, Piantoni et al. (Reference Piantoni, Ylioja and Allen2015) mentioned that, in the case of NEFA, these results are more evident in animals fed only once a day, and when related to other blood metabolites, like circulating glucose concentrations (generally an inverse relationship), cholesterol (Horst et al., Reference Horst, Kvidera and Baumgard2021), and hepatic triglyceride (Grummer, Reference Grummer1993). The increase in NEFA, especially postpartum, can lead to an increase in hepatic triglycerides (Vazquez-Añon et al., Reference Vazquez-Añon, Bertics, Luck, Grummer and Pinheiro1994; National Academies of Sciences Engineering and Medicine – NASEM, 2021), while changes in cholesterol can reflect liver dysfunction and alterations in lipoprotein metabolism (Schären et al., Reference Schären, Riefke, Slopianka, Keck, Gruendemann, Wichard, Brunner, Klein, Snedec, Theinert, Pietsch, Rachidi, Köller, Bannert, Spilke and Starke2021).
Ketosis can be considered in cases of the abnormal presence of ketone bodies in the bloodstream and the accumulation of hepatic fat. It is also considered one of the main disorders caused by a NEB during the transition period, which results from the increased energy requirement and reduced intake capacity in the postpartum period (Pérez-Báez et al., Reference Pérez-Báez, Risco, Chebel, Gomes, Greco, Tao and Galvão2019; Sammad et al., Reference Sammad, Khan, Abbas, Hu, Ullah, Wang, Zhu and Wang2022), as well as being one of the major problems in the transition period. BHB is one of the primary ketone bodies and a biochemical indicator. Suthar et al. (Reference Suthar, Canelas-Raposo, Deniz and Heuwieser2013) stated that BHB concentrations above 1.2 mmol/L indicate subclinical ketosis, and upon reaching 1.5mmol/L, clinical ketosis. Conversely, McArt et al. (Reference McArt, Nydam and Oetzel2012) indicate that subclinical ketosis is estimated to occur within the BHB concentration range of 1.2 to 2.9mmol/L. However, when comparing the initial milk production of cows in the minimum range of 1.2mmol/L, they cite that these cows produce up to 180kg more milk in early lactation when compared to cows with averages of 2.4mmol/L. Whilst we observed no significant relationship with the the energy levels fed prepartum, circulating BHB concentrations ranged from 0.66 to 0.87mmol/L, a range deemed to be within normal parameters.
Milk parameters
Although it was expected that lower energy levels in the prepartum diet could negatively impact milk production, we found that high energy prepartum was associated with significantly reduced lactational performance. This suggests that the levels of dietary components included in pre-partum diets, as evaluated in the studies, can serve as practical tools for mitigating productive issues associated with negative energy balance, given that milk production is an indicator of negative energy balance (NEB) and is among the first physiological processes to be impacted when the energy demands for milk synthesis are not met by energy intake (Churakov et al., Reference Churakov, Karlsson, Rasmussen and Holtenius2021). According to Mann et al. (Reference Mann, Yepes, Overton, Wakshlag, Lock, Ryan and Nydam2015), high-energy diets during the transition period may cause greater metabolic problems during the lactation phase, but the National Academies of Sciences Engineering and Medicine – NASEM (2021) mentions that the excess energy in the pre-partum period can lead to increased BCS and decreased dry matter intake post-partum, raising the risk of ketosis and other metabolic issues, therefore special care is recommended with excess energy in the pre-partum period.
In contrast, diets with a high energy content or high in non-fibrous carbohydrates can greatly increase the BCS of animals. Therefore, the feeding management from mid-lactation to the pre-calving period is critical for the cow to recover its BCS and has a direct impact on its milk production throughout the subsequent lactation. Nonetheless, increases in BCS to levels above 3.5 lead to a greater incidence of metabolic disorders postpartum (Wang et al., Reference Wang, Huo, Sun and Zhang2019; Zhao et al., Reference Zhao, Chen, Xiao, Chen, Zhang, Wang, Zhen and Qin2019).
Postpartum, tissue mobilisation is increased due to the high energy demand required for lactation, and one of the consequences of this process is the increase in circulating levels of the NEFA and BHB metabolites. This process can be associated with an increase in milk fat content, as BHB is a precursor of fat in the mammary epithelium (Zhang et al., Reference Zhang, Zhang, Hui, Lei, Du, Gao, Zhang, Liu, Li and Li2015), and an increase in circulating lipids, either via free fatty acids or VLDL, contributes to the increased synthesis of triacylglycerols in the epithelium (McManaman, Reference McManaman2015; Neville and Picciano, Reference Neville and Picciano1997).
As we observed, milk lactose content did not vary with prepartum energy intake, all energy levels yielding a concentration of 4.5g/100g of milk. Lactose concentration in milk varies according to days in milk and is related to fat, milk urea nitrogen, somatic cell count and the energy availability for physiological processes (Henao-Velásquez et al., Reference Henao-Velásquez, Múnera-Bedoya, Herrera, Agudelo-Trujillo and Cerón-Muñoz2014). As well as being an osmotic regulator of milk, an increase in lactose concentration of up to 4.5g/100g of milk results in an influx of water into the mammary gland, leading to increased milk production (Erickson and Kalscheur, Reference Erickson and Kalscheur2020).
Conclusions
Prepartum energy intake does not influence dry matter intake (DMI) or energy balance in the postpartum phase. A higher-energy diet pre-partum increased feed efficiency postpartum and resulted in an increase in blood levels of BHB and NEFA. However, it also led to a decrease in milk production and blood glucose.
Abbreviations
- ADF
Acid detergent fibre
- BHB
β-hydroxybutyrate
- BCS
Body condition score
- CP
Crude protein
- DM
Dry matter
- DMI
Dry matter intake
- NDF
Neutral detergent fibre; n, Number of observations
- NEB
Negative energy balance
- NEFA
Non-esterified fatty acids
- PRISMA
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
- PICO
Patient/Problem/Population; Intervention/Exposure; Comparison and Outcomes
- SD
Standard deviation; SEM, Standard error of the mean.
Funding Statement
The authors acknowledge Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
Competing interest
None
Author contributions
ACF, FRS, KMC and RM conceived and designed the study. ACF, FRS, LPB and RM data collect. OADC performed statistical analyses. ACF, OADC, BS and RM wrote the article. VF, FRS and KMC writing review.
