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Article

Dietary Additive Combination for Dairy Calves After Weaning Has a Modulating Effect on the Profile of Short-Chain Fatty Acids in the Rumen and Fecal Microbiota

by
Tainara Leticia Dos Santos
1,
Jorge Augusto Rosina Favaretto
1,
Andrei Lucas Rebelatto Brunetto
1,
Emerson Zatti
1,
Maiara Sulzbach Marchiori
1,
Wanderson Adriano Biscola Pereira
2,
Miklos Maximiliano Bajay
1 and
Aleksandro S. Da Silva
1,3,*
1
Programa de Pós-Graduação em Zootecnia, Universidade do Estado de Santa Catarina (UDESC), Chapecó 89815-630, Brazil
2
Departamento de Clínica Veterinária da FMVZ, Universidade Estadual Paulista, São Paulo 01049-010, Brazil
3
Departamento de Zootecnia, Universidade do Estado de Santa Catarina (UDESC), Chapecó 89815-630, Brazil
*
Author to whom correspondence should be addressed.
Fermentation 2024, 10(10), 528; https://doi.org/10.3390/fermentation10100528
Submission received: 22 September 2024 / Revised: 13 October 2024 / Accepted: 13 October 2024 / Published: 17 October 2024
(This article belongs to the Special Issue Probiotics, Prebiotics and Their Use as Innovative Ingredients in Food Technology)
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Abstract

:
Background: This study aimed to verify whether adding a combination of additives (blend) to the diet of dairy calves after weaning can improve animal performance and health and influence the profile of ruminal short-chain fatty acids and intestinal microbiota. Methods: We used 35 Holstein calves, males, with an average age of 70 days and an average body weight of 68 kg. The treatments used were negative control (T-0: without additive), positive control (T-Control: flavomycin + monensin), T-500 (500 g blend/ton), T-1000 (1000 g blend/ton), and T-1500 (1500 g blend/ton). The additives were classified as zootechnical (probiotics, prebiotics, and essential oils of cinnamon and oregano) and nutritional additive (minerals). Results: Weight gain and daily weight gain were higher for calves in the T-Control, T-500, and T-1000 groups. The concentration of heavy-chain immunoglobulins was higher in the blood of calves in the T-Control and T-500 groups when compared to the other groups. In the T-1500 groups, higher levels of reactive oxygen species were observed, while, in the T-0 and T-1500 groups, higher levels of TBARS and glutathione S-transferase activity were detected. The 15 abundant microorganisms in the calves’ feces, regardless of treatment, were Treponema suis, Treponema saccharophilum, Faecalibacterium prausnitzii, Pseudoflavonifractor sp., Roseburia faecis, Rikenellaceae, Enterobacteriaceae_f, Clostridium sp., Roseburia intestinalis, Aeromonadales_o, Prevotella copri, Treponema succinifaciens, Eubacterium sp., Treponema porcium, and Succinivibrio sp. The T-1000 group showed greater alpha diversity for the intestinal microbiota than T-Control, T-0, and T-500. The additive combination (T-1000) increased the bacterial activity in the ruminal fluid, and the animals of T-1000 had a higher concentration of short-chain fatty acids compared to T-0 and T-1500; this difference is because, in these calves, the production of acetic, butyric, and propionic acid increased. Conclusions: The combination of additives had positive effects on animal health, ruminal volatile fatty acid production, and intestinal microbiota, resulting in animals with more significant weight gain and feed efficiency.

1. Introduction

Milk production has shown continuous growth, driven mainly by increased animal productivity. This progress can be attributed to the adoption of new technologies that have improved animal productivity and agricultural practices on farms in general [1]. In the context of livestock production of young cattle, there is a pressing need to develop a sustainable system that optimizes animal health and productivity. Implementing such a system is essential to ensure that cattle achieve efficient growth, production, and reproduction, following their genetic potential [2]. However, in 2012, the Food and Drug Administration expressed its intention to restrict the use of essential drugs for human medicine in food animal production, aiming to combat antimicrobial resistance. The recommendation of restrictions may lead to eliminating the subtherapeutic use of antimicrobials, which are used to promote growth and prevent disease. Thus, there is a growing need to explore and adopt alternatives to traditional antimicrobials to maintain animal health and development.
Cinnamon and oregano essential oils have been widely explored in animal feed, as they have properties that help modulate the production of volatile fatty acids [3]. In addition, oregano essential oil used in calves reflects an increase in daily weight gain associated with increased serum immunoglobulin concentrations [4]. Likewise, cinnamon essential oil has antibacterial and antioxidant properties via feed, favoring growth performance [5]. Both essential oils modulate the number and diversity of ruminal microorganisms [4,5], and these essential oils are now classified as additives that stimulate animal performance.
Likewise, yeasts have been incorporated into animal diets for their benefits, such as in calves, where their use improves performance and health [6]. Both active live yeast and yeast culture positively affect growth, gastrointestinal tract, immunity, and general health [7]. The benefits of Saccharomyces cerevisiae for calves are known, with a study highlighting the stimulation of consumption, growth, and feed efficiency, in addition to helping to reduce diarrhea in calves [7], just as Lactobacillus sp. and Bifidobacterium sp. are already established as probiotics for calves [8]. However, other microorganisms have been included in animal feed, such as Bacillus subtilis and Enterococcus faecium, with positive effects on animal health and resulting in more significant weight gain in calves [9,10]. Similarly, to provide health benefits and improve performance, monosaccharides and glucans (prebiotics) have shown positive effects in feeding dairy calves [11,12].
Mineral supplementation can help calves and is an effective strategy to optimize growth and prevent diseases during the critical weaning phase [13]. A practical example of using minerals is increased antioxidant status and animal metabolism when zinc supplementation is used [14]. Minerals are desirable nutritional additives that benefit calves’ health and favor their growth [15].
We hypothesize that the combination of minerals, essential oils, prebiotics, and pro-biotics in the diet of post-weaning calves will have a synergistic effect because the efficiency of these additives is proven separately but there are no studies in combination. The knowledge gap is mainly associated with growth-promoting and nutritional additives and knowing the product doses with a combination of alternative additives. Therefore, the objective was to verify whether this combination of additives in the diet of calves can improve animal health and weight gain, as well as its effects on volatile fatty acids (VFA) in the ruminal fluid and fecal microbiota.

2. Materials and Methods

2.1. Additive

The combination of additives (blend) used in this study is a commercial product (Enterobiosan®, Tecphy, Canelinha, Brazil). The composition of the product is based on potassium (3150 mg/kg), magnesium (3300 mg/kg), zinc (5790 mg/kg), manganese (2130 mg/kg), calcium (between 6.80 and 10 g/kg), Saccharomyces cerevisiae (2.4 × 1011 CFU/kg), mannan oligosaccharides (28 g/kg), beta-glucans (50 g/kg), Bacillus subtilis (6 × 1011 CFU/kg), Bifidobacterium bifidium (2 × 1011 CFU/kg), Enterococcus faecium (2 × 1011 CFU/kg), Lactobacillus acidophilus (2 × 1011 CFU/kg), Lactobacillus buchneri (4 × 1011 CFU/kg), Lactobacillus casei (2 × 1011 CFU/kg), and Lactobacillus lactis (2 × 1011 CFU/kg).

2.2. Installation and Animals

This research was developed at the experimental farm of the Universidade do Estado de Santa Catarina (FECEO), located in the municipality of Guatambu—SC (Latitude: 27°8′5″ South, Longitude: 52°47′15″ West). Thirty-five male Holstein calves were used. The animals were born on commercial properties in the region, where they received colostrum. When they completed an average of three days, they were transported to the experimental station, where they were housed in individual pens, fed with milk replacer (500 g/animal/day), and concentrated ad libitum. At 63 days, the calves were subjected to gradual weaning over seven days until entering the present experiment (in this weaning phase, hay was made available ad libitum). For the experiment, the calves were housed in an experimental shed with individual stalls measuring 4.5 m2 with a concrete floor and a wooden section for the animals to rest. All stalls were equipped with feeders and drinkers. The UDESC ethics committee approved the project (23 April 2021) on the use of animals in research (protocol number: 9192190421).

2.3. Experimental Design and Diet

The animals were divided into five groups, considering body weight (68.2 ± 1.94) and age (70 ± 2.5 days). The diet was adjusted to the body weight of each animal to meet the nutritional requirements of dry matter consumption, assuming an average daily weight gain of 800 g. The diet was formulated according to the BR Corte program (ed. 2016), and the nutritional requirements were considered according to the National Research Council 2001. The diet consisted of concentrate, silage, and chopped hay, with a proportion of 50% forage and 50% concentrate.
The same basal diet was used for all animals, differing only in adding the additive combination. We used a completely randomized design with five treatments and seven replicates per treatment (calf was the experimental unit): negative control (T-0: no additive), positive control (T-Control: monensin (0.81 mg/kg) and flavomicin (0.162 mg/kg)), T-500 (500 g of blend/ton), T-1000 (1000 g of blend/ton), and T-1500 (1500 g of blend/ton). Twice a day (at 8:00 h and 17:00 h), the mixture of concentrate, silage, and hay was supplied (total mixture ration: TMR).

2.4. Sample and Data Collection

The calves were weighed using a digital scale (Digitron®, Digi-Tron Indústria de Balanças, Curitiba, PR, Brazil). The animals were weighed individually at the beginning of the experiment and then every 15 days. The weight gain and average daily gain (ADG) was calculated as the regression coefficient of individual live weight on time. The feed supplied and leftovers were weighed in the morning (7:30 a.m.). Feed conversion and feed efficiency were calculated based on daily feed consumption and weight gain.
Blood samples were also collected on days 1, 15, 30, 45, and 60 of the experiment. Blood was collected through the jugular vein using needles and vacuolated tubes. The blood was placed in tubes without anticoagulants to obtain serum for biochemical analyses and with anticoagulants (EDTA) for complete blood count analyses. The tubes were sent to the laboratory in refrigerated isothermal boxes at 10 °C. In the laboratory, the blood samples from the tubes without anticoagulant were centrifuged for 10 min at a speed of 1300× g, and the serum obtained through this process was then stored in microtubes at a temperature of −20 °C until laboratory analyses were performed.
On days 1, 30, and 60 of the experiment, feces were collected directly from the rectal ampoule of the calves to analyze fecal microbiota. The material was placed in 3M™ Quick Swabs kits (Neogen®, Lansing, MI, USA) for qualitative and quantitative detection of microorganisms using metagenomics by sequencing the 16S rRNA gene, performed by the commercial laboratory.
On day 60 of the experiment, ruminal fluid was collected using an esophageal probe connected to a vacuum system. A volume of 100 mL was collected and filtered, and 2 mL was stored in microtubes under freezing (−20 °C) until analysis. Immediately after collecting ruminal fluid, the sedimentation activity time and the functional activity of the ruminal microbiota were analyzed through the methylene blue reduction test (MBRT) using a control tube (10 mL of liquid) and another in test tube (10 mL of liquid + 0.5 mL of methylene blue). When adding the dye, the time necessary for the methylene blue to be consumed by the bacteria was timed, and the color returned to the same as the control.

2.5. Laboratory Analysis

2.5.1. Feed Analysis

The ingredients and chemical composition of ingredients and experimental feed results are presented in Table 1. The samples were pre-dried in a forced ventilation oven at 54 °C for 72 h and ground to facilitate further analyses. The samples were placed in another forced ventilation study at 105 °C for 24 h to measure and weigh the dry matter (DM). Crude protein quantification was performed following digestion, distillation, and titration using the Kjeldahl method (Method 2001.11) [16]. To obtain the ash (ash), the samples were placed in a muffle furnace at 600 °C for six hours, which extracted all the organic matter from the sample, leaving only the ashes, which were weighed to obtain the percentage of ash. The quantification of neutral detergent fiber (NDF) and acid detergent fiber (ADF) was performed according to Van Soest [17], Van Soest and Wine [18], and Silva and Queiroz [16]. According to the manufacturer’s instructions, an automatic fat and lipid extractor (SER 158/6 VELP SCIENTIFICA®, Usmate Velate, Italy) was used to determine the quantification of the ether extract. Results are shown in Table 1.

2.5.2. Hemogram

An electronic cell counter determined leukocyte and erythrocyte counts and hemoglobin concentration (CELM®—model CC 530, Gaetecnica, São Paulo, Brazil). Hematocrit percentage was detected using microhematocrit tubes according to the methodology described by Feldman et al. [19]. For leukocyte differential, blood smears were made and stained with the commercial kit Panotico rapido®. Then, using a light microscope (100×), 100 white blood cells were identified.

2.5.3. Seric Biochemistry

Serum levels of total proteins (TP), glucose, albumin, cholesterol, and urea were measured using the Bio-2000 semi-automatic analyzer (BioPlus 2000®, Bioplus Produtos para Laboratórios Ltd.a, Barueri, SP, Brazil) and commercial kits (Analisa®). TP and albumin values were used to obtain globulin levels using an equation (globulin = TP − albumin).

2.5.4. Protein Profile by Electrophoresis

For protein fractionation of blood serum, sodium sulfate-polyacrylamide gel electrophoresis was performed according to Tomasi et al. [20] using mini-gels (10 cm × 10 cm). The gels were stained with Coomassie Blue and photographed to identify and quantify protein fractions using Labimage1D software L340 (Loccus®, Cotia, São Paulo, Brazil). A standard containing fractions with molecular weight between 10 and 250 KD (Kaleidoscope—BIO-RAD) was used as a reference; the levels of heavy-chain immunoglobulins, IgA, ferritin, ceruloplasmin, haptoglobin, transferrin, and C-reactive protein were measured.

2.5.5. Oxidative and Antioxidants Response

Levels of ROS in serum were determined by the 2′,7′-dichlorofluorescein diacetate (DCF-DA) oxidation method as described by Ali et al. [21] using excitation and emission of the wavelengths of 485 and 538 nm, respectively. Results were expressed as U DCF/mL. Lipid peroxidation was determined as TBARS levels according to Jentzsch et al. [22] for serum samples; the results were expressed as nM malondialdehyde (MDA)/mL. Levels of NOx were measured according to the Griess method, which indirectly quantifies the levels of nitrite/nitrate as previously described in detail by Tatsch et al. [23]. The results were expressed as µmol/L.
Glutathione S-transferase (GST) activity in serum was measured based on the method described by Habig et al. [24]. Enzymatic activity was expressed as U GST/mg of protein. Glutathione peroxidase (GPx) activity in serum was measured according to the methodology described by Paglia and Valentine [25] and reported in detail by Souza et al. [26]. Enzymatic activity was expressed as U GPx/mg of protein. Superoxide dismutase (SOD) activity in blood was evaluated spectrophotometrically as described by Marklund and Marklund [27], and the enzymatic activity was expressed as U SOD/mg of protein. In whole blood, catalase (CAT) enzyme activity was analyzed according to the technique described by Nelson and Kiesow [28], where the enzyme activity is determined as hydrogen peroxidation and measured with absorbance at 240 nm. Results are expressed in U CAT/mL.

2.5.6. Ruminal Fluid: VFA Levels

Ruminal fluid samples were thawed until they reached a temperature of 5 °C and then manually homogenized. After these processes, 1 mL aliquots of the supernatant of ruminal fluid samples were transferred to polypropylene microtubes (2 mL), which were subsequently centrifuged for 5 min (12,300× g). Then, 100 μL of the supernatant was removed and transferred to a new microtube containing 100 μL of formic acid. The mixture was vortexed for 30 s and centrifuged again for 3 min. After centrifugation, 50 μL of the supernatant of the mixture was transferred to 250 μL tubes and 100 μL of the methanolic solution of the internal standard 3-octanol (665 μg/mL) was added. Samples were injected into a gas chromatograph with a flame ionization detector (GC-FID; Varian Star 3400, Agilent, Santa Clara, CA, USA) and an autosampler (Varian 81000, SpectraLab Scientific Inc., Markham, ON, Canada). One microliter of the extract was injected in a 1:10 split mode. The carrier gas used was hydrogen at a constant pressure of 20 psi. The analytes (acetic, propionic, butyric, valeric, and isovaleric acids) were separated on a CP WAX-52CB capillary column (60 m × 0.25 mm; 0.25 μm stationary phase thickness). The initial temperature of the column was 80 °C for 1 min and increased by 15 °C/min, reaching 120 °C, then reaching 230 °C rising by 20 °C/min, where it remained for 1 min. The injector and detector temperatures were set to 250 °C. Method validation comprised the following parameters: selectivity, linearity, linear range, repeatability, precision, limit of detection (LOD), and limit of quantification (LOQ) for acetic, propionic, butyric, valeric, and isovaleric acids. Linearity was assessed by calculating a regression equation using the least squares method. LOD and LOQ values were achieved by sequential dilutions up to signal-to-noise ratios of 3:1 and 6:1, respectively. Precision was assessed by analyzing the repeatability of six replicated samples. Accuracy was determined by recovering known amounts of standard substances added to the samples. The results were expressed in mmol/L of each VFA in ruminal fluid.

2.5.7. Gut Microbiota (Feces)

On days 30 and 60, feces were collected directly from the rectal ampulla and stored in 3M™ Quick Swabs for qualitative and quantitative detection of microorganisms using metagenomics by sequencing the 16S rRNA gene, which was performed by the laboratory BPI—Biotechnology Research and Innovation®. It should be noted that animals undergoing antibiotic treatment due to diarrhea or other problems did not have their feces collected, as this would directly interfere with the analysis results.
Total DNA was extracted from 200 mg (wet weight) of samples with the ZR Fungal/Bacterial DNA MiniPrep kit (Zymo Research, Orange, CA, USA). Primers 341F (5′-CCTAYGGGRBGCASCAG-3′) and 806R (5′-GGACTACNNGGGTATCTAAT-3′) were selected to amplify the V3–V4 region of bacterial 16S rRNA gene by polymerase chain reaction [29].
Libraries were quantified by qPCR using the Kapa Library Quantification Kit (Illumina, San Diego, CA, USA) following the manufacturer’s recommendations. Samples were normalized to a final concentration of 2 nM and sequenced with an Illumina MiSeq for 250 cycles from each end.

2.6. Statistical Analysis

Data were tested for normality and homogeneity of variance using Shapiro–Wilk and Levene tests, respectively. Leukocyte count results required transformation to achieve normality and homogeneity and then were retransformed to the original units for description. All data were analyzed using the ‘MIXED procedure’ of SAS (SAS Inst. Inc., Cary, NC, USA; version 9.4) with the Satterthwaite approximation to determine the denominator degrees of freedom for the test of fixed effects. The weight gain, feed intake, feed efficiency, and VFA were tested for the fixed effect of treatment using animal (treatment) as a random effect. The data of BW and all blood results were analyzed as repeated measures and were tested for fixed effects of treatment, day, and treatment × day, using animal (treatment) as the random effect. All data obtained on day 1 for each variable were included as covariates in each analysis, and the initial weight was included as a variable in the model. The first-order autoregressive covariance structure was selected according to the lowest Akaike information criterion. Means were separated using the PDIFF method (Tukey test) and all results were reported as LSMEANS followed by the standard error of the mean. Regression analysis determined the ideal additive dose to enhance calf weight gain. Significance was defined when p ≤ 0.05 and tendency when p > 0.05 and ≤0.10.
For fecal microbiology, sequences were analyzed using Mothur software version 23.0.rc1 [30] at a minimum sequence length of 476 bp and clustering at the genus level using OTUs clustered with 97% identity. To identify the microorganisms present in the samples, the DNA oligotypes obtained were compared with the SILVA database [31]. The Vsearch algorithm [32] detected and removed chimeric sequences. All statistical analysis based on OTUs was performed in R (R Core Team, 2024) using the phyloseq [33] and microeco [34] packages. Alpha diversity was calculated using inverse Simpson’s test [35] and compared using ANOVA. Beta diversity was analyzed through ordination via PCoA using Bray’s distance. The relative abundance of the 15 most frequent OTUs was calculated by comparing the different treatments and sampling periods to explore the microbiota composition. The initial period was disregarded and the DESeq2 package [36] was used for differential abundance analyses correlated with weight gain data at 30 and 60 days. The Wilcoxon Rank Sum test tested significant differences at a 5% level by applying the Benjamini–Hochberg FDR correlation for multiple tests. All graphs were made in the ggplot2 package v 3.4.2.

3. Results

3.1. Performance

Performance results are presented in Table 2. The final weight, weight gain, and daily weight gain were higher for calves in the T-Control, T-500, and T-1000 groups when compared to the other groups (T-0 and T-1500). There was no difference between groups in feed consumption. Feed conversion was lower and feed efficiency was higher in calves in the T-Control and T-500 groups than in the T-0 and T-1500 groups. Figure 1 shows a quadratic effect of product (additive combination) consumption on weight gain, with the ideal dose being 818.9 mg/kg.

3.2. Hematology and Serum Biochemistry

Blood count results are shown in Table 3. The erythrocyte count, hemoglobin concentration, and hematocrit were higher in the blood of calves in the T-500 group compared to T-0. A treatment × day interaction was observed (days 45 and 60) for total leukocyte and lymphocyte counts, both lower in the blood of calves in the T-1500 group than in T-Control and T-0. There was no difference between groups regarding the count of neutrophils, eosinophils, and monocytes.
Serum biochemistry results are presented in Table 4. A treatment effect for cholesterol levels was observed, emphasizing higher levels in T-Control calves compared to all other groups. There was no treatment effect or interaction for glucose, urea, total protein, and albumin concentration, which differs from what was observed for globulins. On days 45 and 60, lower globulin levels were found in calves in the T-Control, T-500, T-1000, and T-1500 groups when compared to T-0.
Results of the protein profile in electrophoresis are presented in Table 4. The effect of treatment on the concentration of heavy-chain immunoglobulins was observed, with a higher concentration in the blood of calves from the T-Control and T-500 groups than in the other groups. Likewise, the treatment effect was observed for IgA levels, with the highest concentration in T-0 calves compared to all other groups. The effect of treatment and treatment × day interaction (days 30, 45, and 60) show higher levels of ceruloplasmin in the serum of T-0 calves compared to other experimental groups. Similarly, higher haptoglobin levels were observed on days 45 and 60 in T-0 calves compared to T-Control, T-1000, and T1500. A trend of treatment effect was seen for ferritin, lower in the serum of T-1500 calves when compared to T-Control, T-0, and T-500. Higher transferrin concentration was measured in the serum of calves from T-Control, T-500, T-1000, and T-1500 compared to T-0. No difference was observed in C-reactive protein levels.

3.3. Oxidative Status

Results of the oxidative profile in the calves are presented in Table 5. In general, consuming the additive blend in the highest dose (T-1500) increased the levels of reactive oxygen species and superoxide dismutase activity in the blood. Higher lipid peroxidation levels (TBARS) were observed in animals in groups T-0 and T-1500 compared to T-500. Greater GST activity was observed in the serum of calves from groups T-0 and T-1500 compared to T-Control and T-500. No treatment effect or treatment × day interaction was observed for NOx levels and GPx and CAT activity.

3.4. VFA Levels in Ruminal Liquid

The results of ruminal fluid biomarkers are presented in Table 6. The treatment did not affect pH. A shorter time for methylene blue consumption was observed in calves that consumed additives (T-Control, T-500, and T-1000) compared to T-0 and T-1500. A higher concentration of VFA was observed in the ruminal fluid of animals in T-1000, which was reflected in higher concentrations of acetic, propionic, and butyric acids in these animals when compared to T-0 and T-1500. Valeric and isovaleric acid did not differ between treatments.

3.5. Fecal Microbiota

The relative abundance of the intestinal microbiota with the 15 most abundant microorganisms is presented in Figure 2. From the image, there was a vast change in the microbiota of the calves on days 30 and 60 compared to the start of the experiment (d1). They appear on the list of the most abundant microorganisms: Treponema suis, Treponema saccharophilum, Faecalibacterium prausnitzii, Pseudoflavonifractor sp., Roseburia feces, Rikenellaceae, Enterobacteriaceae_f, Clostridium sp., Roseburia intestinalis, Aeromonadales_o, Prevotella copri, Treponema succinifaciens, Eubacterium sp., Treponema portion, Succinivibrio sp., and others.
In the analysis of alpha and beta diversity, presented in Figure 3, for alpha, we were able first to observe that using performance enhancers (antibiotics and phytogenics) tends to reduce alpha diversity when compared to d1. Furthermore, the T-1000 treatment had greater alpha diversity when compared to T-Control, T-0, and T-500. The beta diversity analysis allowed us to verify that there was an effect of the day without an effect of treatment; it is verified that results from day 30 have positive PCo1 values, while, on day 60, PCo1 values were less than zero and, therefore, negative values.
Among the differentially abundant organisms between treatments (Figure 4), it was observed that the OTUs had antagonistic effects in the two periods evaluated. While Phascolarctobacterium succinatutens is positively associated with weight gain at 60 days and negatively associated with weight gain at 30 days, the species Turicibacter sanguinis, Faecalibacterium prausnitzii, genus Eubacterium, and family Rikenellaceae are positively associated with weight gain at 30 days and negatively associated with weight gain at 60 days.

4. Discussion

The final weight, weight gain, and daily weight gain were higher for calves in the T-Control, T-500, and T-1000 groups when compared to the other groups (T-0 and T-1500). This result may be due to the impact of the use of the blend used in the T-500 and T-100 group diets. A study demonstrated that adding oregano essential oil significantly increased calves’ average daily weight gain and final body weight. This effect was attributed to essential oil oregano’s ability to enhance the gastrointestinal microbiota and improve immune function [4]. Likewise, the use of additives with essential oils in a diet for cows allowed an improvement in ruminal fermentation in the concentration of short-chain and branched-chain fatty acids in addition to positively influencing the digestibility of protein and dry matter in the diet [37], as we verified in the present study, that is, increased levels of acetic, butyric, and propionic acids in the rumen. Studies from the last decade have reported that essential oils can modulate ruminal fermentation in cattle, helping them with feeding efficiency [38]. Favaretto et al. [39], when testing the addition of microencapsulated essential oils to the diet of growing lambs, found more significant weight gains in the animals. This may have been influenced by reducing the animals’ challenge in the face of some stressor, thus making it possible for the lambs to direct more energy toward growth.
The minerals potassium, magnesium, zinc, manganese, and calcium make up the blend used in the treatment groups. These minerals at adequate levels in diets have a direct influence on cattle performance as a direct effect of nutritional character and an indirect impact, reflecting improvements in animal health, mainly in the improvement of the immune response. Dantas and Negrão [40] show that the deficiency of many minerals directly impacts animal performance; for example, less potassium in the body reduces appetite and growth; less magnesium interferes with the digestibility of nutrients; less zinc impacts reduced feed consumption, lower feed efficiency, and development, as well as a limited immune system; less manganese delays growth; and less calcium has a direct influence on growth. Therefore, it is believed that mineral supplementation and other additives played an essential role in animal weight gain and the benefits to animal health observed here.
Yeast also present in the blend positively impacts the body weight gain of animals that ingest it. Adding Saccharomyces cerevisiae to the beef calves’ diet increased final body weight gain and improved average feed conversion [41]. The use of yeast can stimulate fiber degradation by increasing the number of cellulolytic bacteria, improving animal performance due to pH stabilization, and increasing the use of lactate by bacteria present in the rumen [42]. Reis et al. [12] showed that dietary supplementation of 2 g/d of algae β-glucans to milk replacers improved fecal status and may affect growth, as evidenced by a higher weaning weight than control calves.
In summary, if 818.9 mg of the blend per kg of concentrate is added to a diet of 50% concentrate and 50% roughage, we will obtain the best weight gain results. The results were similar to those of calves in the conventional growth promoter group without antibiotics. According to Ramos et al. [43], combining monensin and flavomycin in steers provides more significant daily weight gain and a better result when compared to animals that received a diet with only monensin. Therefore, the data allow us to verify that combining these additives positively affected growth, similar to combining monensin and flavomycin, proving to be a new tool in animal nutrition.
Random findings were the higher erythrocyte count, hemoglobin concentration, and hematocrit in the blood of calves in the T-500 group compared to T-0. However, the literature has already described that using phytogenic additives in broiler feed increased the number of erythrocytes [44]. Researchers found that adding natural oils to the diet of heifers influenced the concentration of blood hemoglobin [45], as well as increasing hematocrit in heifers [46] and calves [47]. However, reviewing the literature shows that the consumption of yeast by animals, such as Saccharomyces cerevisiae, has not influenced the erythrogram of calves [7]. High values of hemoglobin concentration and hematocrit levels may be indicative of a reduction in energy intake [46] as well as an indication of oxygen transport capacity and food inefficiency [45].
It was expected that monensin consumption would alter blood urea and glucose levels. Still, cholesterol levels rose in T-Control calves, which is probably related to ruminal fermentation. According to the literature, monensin has been shown to increase propionate production, a glucogenic precursor. Therefore, it may reduce energy loss during feeding, improving glucose and lactose synthesis [48], with no known lipid pathway. The effect of the treatment (monensin) on cholesterol was not expected, especially since a meta-analysis with dairy cattle found that this additive does not affect cholesterol levels [49].
Lower globulin levels were noted in calves from the T-Control, T-500, T-1000, and T-1500 groups when compared to T-0. Globulin levels are related to the transport of metals and lipids in addition to playing a role in immunity [50]. According to Volpato et al. [47], when using essential oils in the diet of calves, they also found lower serum globulin levels, corroborating the present study. According to Bortoli [46], high globulin concentrations may be related to a more significant health challenge, which is a consequence of the nonconsumption of additives with antimicrobial action by T-0 calves. Therefore, it is believed that the additives had an anti-inflammatory effect, inhibiting the production of lymphocytes as observed in these animals, a type of cell responsible for producing globulins, or it would be the antimicrobial action of the additive, which protected the animal, preventing it from needing to stimulate the immune response. This hypothesis was reinforced by the effect of treatment on IgA levels, a higher concentration in the blood of T-0 calves when compared to all other groups. It is worth remembering that high IgA levels can be markers of inflammation and intestinal challenge, as IgA has a role in preventing the attachment of pathogens to the mucous membranes; that is, it is the immune system responding to pathogenic challenges, indicating an active defense mechanism; however, it can also suggest ongoing stress or infection that needs to be controlled [51].
The protein profile by electrophoresis also confirms that the combination of active ingredients was efficient as a performance enhancer and can replace antibiotics since the higher levels of haptoglobin in T-0 calves compared to the other groups reinforce that the elevation of this acute-phase protein challenged these animals. According to the literature, elevated levels of haptoglobin are often associated with respiratory infections, gastrointestinal problems, and other inflammatory conditions; it is known that increased haptoglobin helps moderate inflammation and protect tissues [52]. Similarly, T-0 calves had higher ceruloplasmin levels in the blood than the other experimental groups, indicating infections, inflammation, or tissue injuries [53]. Serum transferrin from calves in the T-Control, T-500, T-1000, and T-1500 groups was higher when compared to T-0, as this is a harmful acute-phase protein, reinforcing the hypothesis that the T-0 calves were in a health challenge. It is known that these lower transferrin levels in negative control animals (without additives) are indicative of inflammation [54].
The highest dose (T-1500) of the additive combination increased the levels of reactive oxygen species and lipid peroxidation in the blood of calves. It increased the activity of SOD and GST in the blood. These results show why the T-1500 calves were the ones that gained the least body weight; that is, there was an indication that the dose was high and presented toxicity, causing tissue damage that led to greater production of free radicals and stimulation of the antioxidant system [55,56]. This is because SOD is an antioxidant enzyme that plays a crucial role in defending against the damaging effects of free radicals to minimize oxidative damage [56]. GST is an adaptive response that helps neutralize these free radicals and protect cells against oxidative damage, especially in the liver, a multifunctional organ [57]. We cannot rule out that there was an antioxidant effect of prebiotics and probiotics, but we believe that this antioxidant protection is related to minerals, such as zinc and manganese, which are important metals in the composition of SOD; in addition, cinnamon and oregano essential oil has properties with antioxidant capacity, which can help in the health and performance of animals [4,5].
Regarding changes in the microbiota of calves, performance enhancers increased alpha diversity in T-1000 animals compared to T-Control, T-0, and T-500; this may be directly related to more significant body weight gain in these calves. It is already known that oregano essential oil [4,58] and yeast [59] can modulate the ruminal microbiota, but little is known about their effects on the intestinal microbiota. We found that the change from positive to negative values in PCo1 between days 30 and 60 indicates a change in the composition of the intestinal microbiota. This can occur due to several factors, such as age, the animal’s physiological development, exposure to different environments, and changes in diet and interactions of the intestinal microbiota [60]. The animal’s health status can also affect the microbiota; different intestinal parasites can affect the bacteria in the intestine [61].
Among the predominant populations in the intestinal microbiota is Prevotella spp., which is a genus associated with the ruminal fermentation of carbohydrates and proteins [62]. Prevotella copri was one of the most abundant microorganisms in the fecal microbiota. According to Brooke et al. [63], the increase in the Prevotella copri population may indicate high feed efficiency and may be a potential marker for increased feed efficiency in feces. For Hennessy et al. [64], the increased presence of Treponema indicates a fiber-rich diet, guaranteed in our study by hay and corn silage since Treponema is a fibrinolytic bacterium. Succinivibrio sp. plays a vital role in high feed efficiency [65], as it can be easily absorbed by the rumen for hepatic gluconeogenesis, thus improving the feed efficiency of ruminants [66]. In addition, Succinivibrio sp. aids feed efficiency by reducing methane emissions [67]. Faecalibacterium is known as a beneficial bacterium since Holstein calves treated with F. prausnitzii showed a lower incidence of severe diarrhea during the weaning period in addition to having influenced the increase in weight gain [68]. Possibly because it is a commensal bacterium related to the reduction of colitis through the modulation of metabolites of the gastrointestinal tract, making clear its anti-inflammatory potential [69], the differentially abundant organisms between treatments, the Rikenellaceae family was found to be related to the ruminal fermentation function and growth performance of weaned calves [70]. The Eubacterium genus is positively associated with ruminal fermentation, bacteria, and total volatile fatty acids in Holstein’s calves [71]. Phascolarctobacterium can convert succinate to propionate in the intestine; its abundance may contribute to animal growth since propionate is essential for gluconeogenesis [72].
Observing the abundance of images of microorganisms makes it possible to verify numerical differences but not statistical significance, which may be related to the small sample size for this type of analysis. However, it is known that additives provided via diet have the power to alter the microbiota in the gastrointestinal tract. An example is the recent study by [4], who, when feeding calves with oregano essential oil, observed an increase in Turicibacter, which is positively related to the digestibility function; thus, it is a desirable effect of the additive. According to literature, the ruminal microbiota can be modulated by the ingredients in the animal’s diet, as seen in the greater microbial diversity observed in sheep fed wheat flour compared to those fed wheat pellets. This was marked by an increase in bacteria from the Bacteroidetes phylum, particularly the Prevotella genus, which were positively correlated with weight gain [73]. In our study, the basal diet was the same for all groups, changing only the additive, which, even in small quantities, already influenced intestinal microbiota; which suggests that changes in the rumen microbiota may have occurred here.
The regression analysis had a quadratic effect, which made it possible to determine the dose of 818.9 mg of the blend/kg of concentrate. Knowing that the calves consumed 3.35 kg of concentrate in natural matter per day, the quantity of the product consumed by the calf per day was calculated, i.e., 2.74 g.

5. Conclusions

The combination of additives known as performance additives (prebiotics, probiotics, and essential oils) and nutritional additives (minerals) had a beneficial effect on the health of the calves, stimulating the antioxidant response and preventing the inflammatory response. The consumption of this mixture of additives increased the volatile fatty acid profile, just as the dose of T-1000 increased alpha biodiversity and was effective for weight gain of these animals. The dose T-1500 presented toxicity, causing tissue damage that led to greater production of free radicals and stimulation of the antioxidant system.

Author Contributions

Conceptualization, T.L.D.S., J.A.R.F. and A.S.D.S.; methodology, formal analysis, and investigation, T.L.D.S., J.A.R.F., A.L.R.B., E.Z., M.S.M., W.A.B.P. and A.S.D.S.; software, M.M.B. and A.S.D.S.; resources, project administration, and funding acquisition, A.S.D.S.; writing—original draft preparation, T.L.D.S. and J.A.R.F.; writing—review and editing, all authors. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The UDESC ethics committee approved the project on the use of animals in research (protocol number: 9192190421) at 23 April 2021.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are in the possession of the authors but may be made available upon request.

Acknowledgments

We thank Techy, UDESC, CAPES, FAPESC, and CNPq for their technical and financial support.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Regression analysis demonstrates the quadrative effect of additive consumption on weight gain during the experimental period (days 1–60).
Figure 1. Regression analysis demonstrates the quadrative effect of additive consumption on weight gain during the experimental period (days 1–60).
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Figure 2. Relative abundance of the 15 most frequent microorganisms in the feces of calves fed with the additive combination (T-500, T-1000, and T-1500) compared to negative control (T-0) and positive control (T-Control: monensin and virginicin) groups: data by period (day 30 and 60) and by experimental group.
Figure 2. Relative abundance of the 15 most frequent microorganisms in the feces of calves fed with the additive combination (T-500, T-1000, and T-1500) compared to negative control (T-0) and positive control (T-Control: monensin and virginicin) groups: data by period (day 30 and 60) and by experimental group.
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Figure 3. Alpha diversity (Simpson’s inverse) and beta diversity (Pco2) of the intestinal microbiota of calves fed additive combination (T-500, T-1000, and T-1500) compared to negative control (T-0) and positive control (T-Control: monensin and virginicin) groups. Different letters between groups in alpha diversity represent statistical differences between groups (p < 0.05), as well as compared to day 1 (collection performed before starting additive consumption).
Figure 3. Alpha diversity (Simpson’s inverse) and beta diversity (Pco2) of the intestinal microbiota of calves fed additive combination (T-500, T-1000, and T-1500) compared to negative control (T-0) and positive control (T-Control: monensin and virginicin) groups. Different letters between groups in alpha diversity represent statistical differences between groups (p < 0.05), as well as compared to day 1 (collection performed before starting additive consumption).
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Figure 4. Correlation between relative abundance of microorganisms versus weight gain on days 30 and 60 of the experiment (* = p < 0.05; ** = p < 0.01; *** = p < 0.001).
Figure 4. Correlation between relative abundance of microorganisms versus weight gain on days 30 and 60 of the experiment (* = p < 0.05; ** = p < 0.01; *** = p < 0.001).
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Table 1. Ingredients and chemical composition of ingredients and experimental feeds.
Table 1. Ingredients and chemical composition of ingredients and experimental feeds.
IngredientsComposition (%)
Corn silage13.4
Hay: Tifton 8535.9
Concentrate 150.7
Chemical composition 2 (%)Corn silageHayConcentrate a
DM26.189.889.1
Ash3.638.766.35
CP5.6812.320.9
NDF44.969.919.0
ADF23.631.58.43
a Basal concentrate—used in all groups. The chemical composition of the concentrate of the four groups was identical; that is, the additive did not alter the chemical composition of the concentrate ingested by the calves. 1 Proximate composition: ground corn (52%), soybean meal (26%), wheat bran (17%), calcitic limestone (1%), sodium bicarbonate (0.4%), and 3.7% of premix (calcium min. 180 max. 220 g; phosphorus min. 32 g; sodium min. 40 g; sulfur min. 20 g; magnesium min. 20 g; cobalt min. 16 mg; iodine min. 17 mg; manganese min. 420 mg; selenium min. 730 mg; zinc min. 730 mg; fluoride max. 600 mg; niacin min. 500 mg; vitamin A min. 95,000 IU; vitamin D min. 20,000 IU; vitamin Min 350 IU). 2 DM (dry matter), Ash (ash), CP (crude protein), NDF (neutral detergent fiber), ADF (acid detergent fiber).
Table 2. Growth performance of calves fed with a combination of additives.
Table 2. Growth performance of calves fed with a combination of additives.
Variables T-CON 1T-0 1T-500 1T-1000 1T-1500 1SEMp-Valor
Body weight, kg
  Initial68.268.268.567.969.61.940.97
  Final105.5 a95.5 a105.1 a102.7 a90.1 b2.040.05
Weight gain, kg
  Day 1 to 6037.2 a32.2 bc36.5 a35.1 a29.9 c1.430.03
ADG, kg 20.620 a0.536 bc0.608 a0.585 a0.498 c0.060.03
DMI kg/day 26.126.066.056.116.010.120.95
  FC, kg/kg 29.87 b11.3 a9.95 b10.4 ab12.0 b0.040.01
  FE, kg/kg 20.101 a0.088 bc0.100 a0.095 ab0.082 c0.060.01
1 Treatments were: T-CON, the combination of monensin (0.81 mg/kg) and flavomicin (0.162 mg/kg of body weight (positive control)); T-0, 0 mg phytogenic/kg (negative control), T-500, T-100, and T-1500, 500, 1000, and 1500 mg of phytogenic per kg of concentrate; 2 feed conversion—FC (Dry Matter Intake (DMI)/Average Daily Gain (ADG)), feed efficiency—FE (ADG/DMI). Note: when p ≤ 0.05, there was a treatment effect, illustrated by lowercase letters (a–c) on the same line.
Table 3. Blood count analysis in calves fed conventional additives (monesin and flavomycin) and alternative additives (combination of minerals, essential oils, prebiotics, and probiotics).
Table 3. Blood count analysis in calves fed conventional additives (monesin and flavomycin) and alternative additives (combination of minerals, essential oils, prebiotics, and probiotics).
VariablesT-CONT-0T-500T-1000T-1500SEMP: TreatP: Treat × Day
Erythrocytes (×106/µL) 0.010.01
d18.758.909.599.039.470.69
d159.189.9210.49.9710.50.72
d308.41 B8.31 B10.3 A8.91 AB8.34 B0.72
d458.63 B8.43 B10.6 A8.90 AB8.68 B0.66
d608.49 B8.65 B10.7 A9.21 AB8.56 B0.52
Hemoglobin (mg/dL) 0.040.01
d18.638.419.298.949.110.16
d159.5310.210.710.611.30.18
d3012.1 B11.2 B14.7 A12.9 AB11.3 B0.17
d4512.7 B11.9 B15.9 A12.9 AB12.2 B0.15
d6013.0 AB11.5 B15.9 A14.5 AB11.9 A0.16
Hematocrit (%) 0.030.01
d139.138.242.240.141.40.65
d1543.242.446.045.545.80.62
d3040.8 B38.9 B50.1 A44.3 AB38.3 B0.64
d4543.2 B40.6 B53.9 A43.9 B41.8 B0.59
d6041.9 B40.1 B49.5 A46.1 AB40.2 B0.54
Leukocytes (×103/µL) 0.320.02
d116.614.614.414.912.51.52
d1515.014.713.014.713.51.50
d3014.811.714.913.510.61.56
d4512.5 A12.4 A10.7 AB10.3 AB8.31 B1.48
d6011.3 AB12.8 A10.9 A10.2 BC9.41 B1.45
Lymphocytes (×103/µL) 0.250.01
d19.148.568.368.678.131.14
d158.898.348.418.257.991.21
d307.767.257.948.107.081.15
d457.41 A7.65 A6.58 AB6.39 AB5.24 B1.15
d607.32 A7.58 A6.52 AB6.14 AB5.38 B1.12
Neutrophilis (×103/µL)3.243.123.052.972.850.950.190.28
Monocytes (×103/µL)0.810.740.720.680.540.500.510.69
Eosinophilis (×103/µL)0.520.450.360.480.510.840.630.77
Note: when p ≤ 0.05, a significant treatment × day interaction is illustrated by uppercase letters on the same line (A–C). No treatment effect (p > 0.05).
Table 4. Seric biochemistry and proteinogram analysis in calves fed conventional additives (monesin and flavomycin) and alternative additives (combination of minerals, essential oils, prebiotics, and probiotics).
Table 4. Seric biochemistry and proteinogram analysis in calves fed conventional additives (monesin and flavomycin) and alternative additives (combination of minerals, essential oils, prebiotics, and probiotics).
VariablesT-CONT-0T-500T-1000T-1500SEMP: TreatP: Treat × Day
Cholesterol (mg/dL)91.1 a77.7 ab80.7 ab76.2 ab68.0 b2.810.050.15
Urea (mg/dL)32.826.129.730.225.22.090.450.26
Glucose (mg/dL)10810594.598.11044.120.650.54
Total protein (g/dL)8.338.388.608.198.080.140.890.21
Globulin (g/dL)
d14.504.034.814.234.110.110.150.01
d155.094.975.815.134.640.10
d306.275.945.866.406.010.10
d455.36 B6.20 A5.58 B5.47 B5.24 B0.11
d605.42 B6.30 A5.51 B5.02 B5.02 B0.09
Albumin (g/dL)2.802.642.652.692.850.060.820.73
Ig- heavy-chain (g/dL)1.24 a1.03 b1.27 a1.11 b1.08 b0.050.020.11
IgA0.95 b1.67 a0.89 b0.94 b1.02 b0.080.050.17
Ceruloplasmin (g/dL) 0.010.01
d10.740.760.710.740.750.04
d150.710.820.700.760.780.04
d300.68 B0.97 A0.81 AB0.71 B0.67 B0.05
d450.70 B0.92 A0.73 B0.66 B0.65 B0.05
d600.69 B0.99 B0.75 B0.67 B0.62 B0.06
Haptoglobin (g/dL) 0.120.02
d10.420.470.450.450.420.03
d150.490.510.470.540.520.04
d300.520.540.580.510.500.04
d450.47 B0.59 A0.52 AB0.46 B0.42 B0.04
d600.49 B0.64 A0.55 AB0.48 B0.45 B0.05
Ferritin (g/dL)0.39 a0.41 a0.42 a0.37 ab0.32 b0.030.080.12
Transferrin (g/dL)0.52 a0.35 b0.50 a0.57 a0.60 a0.040.030.25
C-reactive protein (g/dL)0.280.320.270.280.270.020.110.20
Note: when p ≤ 0.05, there was a treatment effect, illustrated by lowercase letters (a–b) on the same line; whereas a significant treatment × day interaction is illustrated by uppercase letters on the same line (A–B).
Table 5. Oxidative status in calves fed with conventional additives (monesin and flavomycin) and alternative additives (combination of minerals, essential oils, prebiotics, and probiotics).
Table 5. Oxidative status in calves fed with conventional additives (monesin and flavomycin) and alternative additives (combination of minerals, essential oils, prebiotics, and probiotics).
VariablesT-CONT-0T-500T-1000T-1500SEMP: TreatP: Treat × Day
ROS (U DCF/mL) 0.010.01
d18.108.068.217.968.410.85
d157.967.927.857.377.650.85
d307.687.257.368.888.960.85
d456.79 C8.54 BC7.61 C10.7 AB12.7 A1.05
d606.82 C9.28 AB6.24 C7.68 BC11.0 A0.92
SOD (U SOD/mg
of protein)		 0.010.01
d13.523.473.483.243.810.09
d153.54 B3.74 B4.56 AB4.74 AB5.10 A0.09
d303.08 C2.85 C4.44 B5.01 AB5.27 A0.12
d452.57 C2.96 BC3.68 AB4.42 A4.76 A0.10
d602.81 B2.95 B4.25 A4.63 A5.04 A0.08
TBARS (MDA/mL)14.1 ab21.7 a10.8 b18.9 ab22.1 a4.010.050.12
NOx (µmol/L)52.457.150.660.257.62.940.220.15
GST (U GST/mg of protein)241 b260 a245 b253 ab265 a7.100.040.35
GPx (U GPx/mg of protein)6.855.965.716.255.870.520.460.23
CAT (mmol/mg Hb)4.254.014.624.644.270.130.680.41
Note: when p ≤ 0.05, there was a treatment effect, illustrated by lowercase letters (a–b) on the same line; whereas a significant treatment × day interaction is illustrated by uppercase letters on the same line (A–C).
Table 6. Ruminal liquid analysis (pH, bacterium activity, and volatile fatty acid) in calves fed with conventional additives (monesin and flavomycin) and alternative additives (combination of minerals, essential oils, prebiotics, and probiotics) at day 60 of experiment.
Table 6. Ruminal liquid analysis (pH, bacterium activity, and volatile fatty acid) in calves fed with conventional additives (monesin and flavomycin) and alternative additives (combination of minerals, essential oils, prebiotics, and probiotics) at day 60 of experiment.
VariablesT-CONT-0T-500T-1000T-1500SEMP: Treat
pH6.426.406.376.546.560.060.31
MBRT (seconds)102 b125 a99.5 b88.2 bc122 a4.620.01
SCFA (mmol/L)56.7 ab50.4 b58.4 ab61.6 a52.7 c2.570.04
Acetic acid (mmol/L)37.9 bc32.7 c38.9 ab40.5 a34.1 c1.250.01
Propionic acid (mmol/L)11.5 bc10.4 c12.2 ab12.6 a10.6 c0.280.03
Butyric acid (mmol/L)5.86 b5.77 b5.73 b7.16 a6.21 ab0.110.05
Isovaleric acid (mmol/L)0.920.900.830.960.980.070.45
Valeric acid (mmol/L)0.520.630.740.700.810.180.12
Note: methylene blue reduction test (MBRT). Note: when p ≤ 0.05, there was a treatment effect, illustrated by lowercase letters (a–c) on the same line.
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Dos Santos, T.L.; Favaretto, J.A.R.; Brunetto, A.L.R.; Zatti, E.; Marchiori, M.S.; Pereira, W.A.B.; Bajay, M.M.; Da Silva, A.S. Dietary Additive Combination for Dairy Calves After Weaning Has a Modulating Effect on the Profile of Short-Chain Fatty Acids in the Rumen and Fecal Microbiota. Fermentation 2024, 10, 528. https://doi.org/10.3390/fermentation10100528

AMA Style

Dos Santos TL, Favaretto JAR, Brunetto ALR, Zatti E, Marchiori MS, Pereira WAB, Bajay MM, Da Silva AS. Dietary Additive Combination for Dairy Calves After Weaning Has a Modulating Effect on the Profile of Short-Chain Fatty Acids in the Rumen and Fecal Microbiota. Fermentation. 2024; 10(10):528. https://doi.org/10.3390/fermentation10100528

Chicago/Turabian Style

Dos Santos, Tainara Leticia, Jorge Augusto Rosina Favaretto, Andrei Lucas Rebelatto Brunetto, Emerson Zatti, Maiara Sulzbach Marchiori, Wanderson Adriano Biscola Pereira, Miklos Maximiliano Bajay, and Aleksandro S. Da Silva. 2024. "Dietary Additive Combination for Dairy Calves After Weaning Has a Modulating Effect on the Profile of Short-Chain Fatty Acids in the Rumen and Fecal Microbiota" Fermentation 10, no. 10: 528. https://doi.org/10.3390/fermentation10100528

APA Style

Dos Santos, T. L., Favaretto, J. A. R., Brunetto, A. L. R., Zatti, E., Marchiori, M. S., Pereira, W. A. B., Bajay, M. M., & Da Silva, A. S. (2024). Dietary Additive Combination for Dairy Calves After Weaning Has a Modulating Effect on the Profile of Short-Chain Fatty Acids in the Rumen and Fecal Microbiota. Fermentation, 10(10), 528. https://doi.org/10.3390/fermentation10100528

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