All animal handling, housing, and experimental procedures were carried out in strict accordance with internationally accepted principles for the ethical use of animals in research and relevant national regulations. The study adhered to the provisions of the Model Law of the Interparliamentary Assembly of the Commonwealth of Independent States “On the Treatment of Animals,” Article 20 (Resolution of the IPA of the CIS Member States No. 29-17, October 31, 2007), as well as the Methodological Recommendations for Working with Laboratory Animals.

All experimental protocols involving live animals were reviewed, evaluated, and officially approved by the Animal Care and Use Committee of the Federal Research Center for Biological Systems and Agrotechnologies of the Russian Academy of Sciences in Orenburg, Russia (Approval Protocol No. 4, dated September 30, 2024). The study was designed and conducted in accordance with the principles of Replacement, Reduction, and Refinement (3Rs) to minimize animal use and suffering while maintaining scientific validity.

Broiler chickens were housed in controlled environmental and hygienic conditions suitable for their age and physiological needs, with continuous access to feed and water. Animal health and welfare were checked twice daily by trained personnel under veterinary supervision. No therapeutic drugs, including antibiotics, were given during the experimental period. Criteria for humane intervention and removing animals from the experiment were predetermined and included severe injury, losing more than 15% of body weight, inability to access feed or water on their own, or signs of incurable disease.

Blood sampling and tissue collection were performed by trained personnel using standard veterinary procedures to minimize stress and discomfort. At the end of the experiment, birds selected for hematological and microbiome analyses were humanely euthanized with an intravenous injection of pentobarbital (150 mg/kg body weight) via the wing vein, in line with accepted veterinary guidelines. Death was confirmed before necropsy and sample collection.

Throughout the study, all efforts were made to ensure animal welfare, reduce distress, and adhere to ethical standards for animal research.

The experiment was conducted from November 2024 to July 2025 at the Experimental Biological Clinic (vivarium) of the Federal Research Center for Biological Systems and Agrotechnologies of the Russian Academy of Sciences in Orenburg, Russia (51.7727° N, 55.0988° E). The trial was performed under fully controlled, climate-regulated housing conditions to maintain consistent environmental parameters throughout the entire experimental period.

A total of 180 AA broiler chickens (supplier: LLC “Aviagen,” Tula, Russia), aged 7 days at the start of the experiment, were included in the study. Birds were grouped by live body weight using 10-g intervals and randomly assigned to four experimental groups (n = 45 per group) to ensure similar initial weights. Each group was then divided into three replicates of 15 birds each. All chicks were individually marked with colored plastic leg rings.

The average initial body weight on day 7 was 203.8 ± 1.5 g (mean ± Standard error of the mean [SEM]). Birds were of mixed sex, and stratified randomization ensured a balanced sex ratio across all groups. The experiment lasted 42 days, including a 7-day acclimation period followed by a 35-day experimental phase. The experimental layout is shown in Table 1.

At the end of the experiment, nine birds from each group were randomly chosen for hematological and microbiome analyses. Sampling was proportional, with one bird selected from each cage, resulting in three birds per replicate and nine per treatment group.

Broilers were housed in three-tier cages measuring 0.9 × 0.45 m, with five birds per cage, resulting in a stocking density of 0.08 m² per bird. The housing facility had a mechanical ventilation system to ensure continuous air exchange. Ambient temperature was initially maintained at 32°C and gradually decreased by 0.5°C daily until reaching 20°C–22°C. Relative humidity was kept between 50% and 70%.

A controlled lighting program was used with a light intensity of 20–25 lux at bird level: 23 h light and 1 h darkness from days 1–7, 20L:4D from days 8–21, and 18L:6D from days 22–42. This lighting schedule complied with European Council Directive 2007/43/EC on the protection of broiler chickens. Strict sanitary measures, including regular cleaning and disinfection of cages and equipment, were maintained throughout the study.

Birds were fed and watered on a group basis. QC dihydrate (purity ≥ 95%; 95+% AL33795-1, Sigma-Aldrich, China) was used as the dietary supplement and stored according to the manufacturer’s instructions. The control group received a basal diet (BD) formulated to meet nutritional requirements (Table 2).

Experimental diets were supplemented with QC dihydrate as follows: group QC1 received BD + 5 mg/kg feed/day, group QC2 received BD + 10 mg/kg feed/day, and group QC3 received BD + 15 mg/kg feed/day. QC was first mixed thoroughly with a small amount of BD to create a uniform premix, which was then incorporated into the total feed using a horizontal mixer for 15 minutes to ensure even distribution. Nutrient and trace element contents of the diets met broiler requirements for each growth phase (Table 3) [16].

All birds followed a standard commercial vaccination program for AA broilers in the Russian Federation. Vaccination started at the hatchery with Marek’s disease vaccine (CV1988/Rispens strain) applied subcutaneously, along with a combined infectious bronchitis and Newcastle disease vaccine delivered by coarse spray. Later vaccinations included infectious bronchitis vaccine (Ma5 strain) on day 5, infectious bursal disease vaccine (Winterfield R strain) on day 10, and booster shots against Newcastle disease (La Sota strain) and infectious bronchitis (Ma5 strain) on day 16 via drinking water.

Vaccines were administered using approved commercial products under veterinary supervision. No therapeutic drugs, including antibiotics, were used during the experiment. Bird health was monitored twice daily for behavior, general condition, and signs of distress. Mortality and euthanasia events were recorded daily with documented causes. Criteria for euthanasia included loss of more than 15% body weight, inability to access feed or water, severe injury, or incurable infection.

At the end of the experiment, blood samples were collected from the wing vein of nine randomly selected birds per group into 2-mL EDTA tubes. Sampling was performed in the morning before feeding to reduce diurnal variation. Each sample was tested in triplicate.

Following blood collection, birds were immediately euthanized with an intravenous dose of pentobarbital (150 mg/kg body weight). Hematological parameters, including hemoglobin, hematocrit, red blood cell count, white blood cell count, and leukocyte differential, were measured using an automated hematology analyzer (URIT-2900 Vet Plus; URIT Medical Electronic Co., China). The analyzer was calibrated beforehand, and quality control was maintained with commercial avian blood control materials.

Immediately after euthanasia on day 42, cecal contents were collected aseptically from the same birds used for hematological analysis. Sterile instruments were employed for each bird to prevent cross-contamination. About 200 µL of cecal content was transferred into sterile cryogenic tubes containing 200 µL of DNA/RNA Shield preservative (Zymo Research, USA). Samples were promptly frozen on dry ice and stored at −80°C until DNA extraction. The time between slaughter and sample freezing did not exceed 10–15 minutes.

Individual live body weights were recorded weekly. Feed intake was measured daily per cage by recording the feed offered and residual feed. Average daily gain (ADG), FCR, and EPEF were calculated using standard formulas. Higher EPEF values indicated better overall production efficiency.

Total genomic DNA was extracted from cecal samples using the FastDNA SPIN Kit for Feces (MP Biomedicals, USA). DNA concentration and purity were determined using a Qubit 4 fluorometer and confirmed by agarose gel electrophoresis.

The V3–V4 region of the 16S rRNA gene was amplified using primers 341F and 785R following Illumina’s standard protocol. Libraries were purified with AMPure XP beads and sequenced with paired-end 2 × 250 bp chemistry on an Illumina MiSeq platform.

Raw sequencing data were processed with the UPARSE pipeline (USEARCH v11) [17] After quality filtering and Operational taxonomic unit (OTU) clustering at 97% similarity, taxonomic classification was carried out using the Ribosomal Database Project Classifier against the SILVA v138 database. Taxonomy was further refined using the GTDB and National Center for Biotechnology Information databases. Downstream analyses were performed with MicrobiomeAnalyst 2.0 [18].

Low-abundance and low-variance OTUs were removed before analysis [19]. Data normalization was done using cumulative sum scaling and total sum scaling. Samples were rarefied to 20,000 reads per sample for diversity analysis. Alpha-diversity indices (Chao1, Shannon, Simpson) and beta-diversity metrics (Bray–Curtis, Jensen–Shannon) were calculated and visualized through Principal coordinate analysis and Non-metric multidimensional scaling ordinations.

All data, including performance parameters, hematological indicators, and alpha-diversity indices, were initially assessed for normality of distribution using the Shapiro–Wilk test and for homogeneity of variances using Levene’s test. Data that satisfied the assumptions of normality and homoscedasticity were analyzed with one-way analysis of variance (ANOVA), followed by Tukey’s post hoc test for multiple comparisons. Data that did not meet these assumptions were analyzed using nonparametric statistical methods, specifically the Kruskal–Wallis test followed by Dunn’s post hoc test with Benjamini–Hochberg correction.

All results are shown as mean ± SEM. Statistically significant differences between experimental groups at p ≤ 0.05 are indicated by different lowercase letters within the same row of the tables.

To assess differences in the overall structure of microbial communities (beta-diversity), nonparametric multivariate ANOVA was conducted using the Bray–Curtis similarity measure with 999 permutations. Differential abundance of microbiome taxa between experimental groups was analyzed with the EdgeR package. The resulting p-values were adjusted for multiple comparisons using the false discovery rate correction.

For subsequent pairwise comparisons of relative taxon abundance, either parametric methods (ANOVA followed by Tukey’s test) or nonparametric methods (Mann–Whitney U-test) were used, depending on whether the data met the assumptions required for each test. All statistical comparisons and graphical visualizations, including bar charts of taxonomic composition, ordination plots, and core microbiome analyses at the phylum and genus levels, were carried out using MicrobiomeAnalyst 2.0 and PAST software [20].

Statistical analyses were conducted using SPSS version 26.0 (IBM Corp., NY, USA) and Statistica version 20.0 (TIBCO Software Inc., USA). Raw data and derived variables were managed with Microsoft Excel 2023 (Microsoft Corporation, USA).

Analysis of live weight dynamics (Table 4) showed that all experimental groups outperformed the control group in terms of growth. The highest weight gain was observed in the QC1 group (5 mg/kg). On day 42, the birds reached an average weight of 2610 g (p ≤ 0.05), which was 10.1% higher than the control group (2371 g). The ADG was also highest in the QC1 group (68.74 g/day vs. 61.86 g/day in the control group). Groups QC2 and QC3 displayed intermediate values, indicating a dose-dependent effect of QC, with optimal results at the lowest dose.

The evaluation of feed intake and its conversion (Table 5) confirmed the benefits of the QC1 group: despite having the highest total feed intake (4201.89 g), this group achieved the best FCR (1.77 g feed per kg of gain vs. 1.80 g in the control). Livability in groups QC1 and QC3 was 98%, compared to 95% in the control, indicating a positive effect of QC on bird survival.

The standardized EPEF was used for a comprehensive comparison of performance results (Figure 1). The EPEF values in experimental groups I and III were 386.2 and 375.9 units, respectively, compared to 346 in the control, which was 40.2 and 29.9 units higher; in experimental group II, the difference from the control value was 9.5 units.

Blood analysis (Table 6) revealed that QC had a significant effect on immunological and physiological parameters. Group QC2 (10 mg/kg) showed the highest levels of leukocytes (48.11 × 10⁹/L) and lymphocytes (58.7%), indicating immune system stimulation. In group QC1, an increase in hemoglobin level was observed (121.25 g/L vs. 107.67 g/L in the control), likely linked to improved oxygen transport. Meanwhile, the 15 mg/kg dose (QC3) did not show additional benefits and, for some parameters (neutrophils and monocytes), approached control values.

Comparative analysis of the microbial community in the cecal contents of birds from the control and experimental groups revealed several significant changes caused by introducing small plant-derived molecules, such as QC at doses of 5, 10, and 15 mg/kg, which have been previously shown to inhibit bacterial communication systems reliant on population density. At the highest taxonomic level, two phyla were dominant across all groups: Bacillota (ranging from 51.12% in the control group to 73.88% in group I) and Bacteroidota (from 22.63% in group I to 42.01% in the control group).

The introduction of QC at various concentrations into the BD caused a significant (2–3 fold) increase in the proportion of representatives of the phylum Campylobacterota in groups II and III compared to the control group, along with a sevenfold increase in intra-group comparison relative to group I. This finding warrants attention, as this phylum includes many human, animal, and bird pathogens. Therefore, adding high concentrations of QC to the diet promotes an increase in pathogenic agents, with a clear dose-dependent relationship: the higher the concentration, the greater their proportion.

In group I, there was a twofold increase in the number of representatives of the phylum Actinomycetota and a twofold decrease in the number of Candidatus Melainabacteria representatives compared to groups II, III, and the control. Changes in the balance of other phyla were not significantly noticeable; specifically, there were no significant differences in the relative abundance of representatives of the phyla Pseudomonadota, Thermodesulfobacteriota, and Verrucomicrobia either within groups or when compared to the control (Table 7).

Analysis of lower taxonomic ranks (Figure 2) revealed 20 main genera that dominated in relative abundance. In the control group, the primary representatives were Alistipes (14%), Barnesiella (12%), Coprobacter (9%), and Faecalibacterium (9%). Among the unclassified genera, most were unclassified Oscillospiraceae (10%) and unclassified Lachnospiraceae (7%). The abundance of other genera ranged from 4% to 1%. Genera with less than 1% abundance were grouped into the “Other” category, which accounted for 11% of the overall microbiome diversity.

Adding QC at various concentrations caused changes in the microbiome at the genus level. In the first experimental group, the dominant genera were Faecalibacterium (12%), Subdoligranulum (10%), Alistipes (8%), and Barnesiella (8%). Among the unclassified types, unclassified Oscillospiraceae and unclassified Lachnospiraceae stood out, with abundances of 17% and 9%, respectively. The proportions of other genera ranged from 3% to 1%. The “Other” category accounted for 13%.

For experimental group II, the dominant genera were Barnesiella (12%), Alistipes, and Faecalibacterium (11% each); among unclassified forms, unclassified Oscillospiraceae and unclassified Lachnospiraceae were also noted at 14% and 6%, respectively. The “Other” category accounted for 12%.

In experimental group III, representatives of the genera Barnesiella (11%), Alistipes, and Faecalibacterium (9% and 7%, respectively) also dominated, but genera such as Helicobacter and Coprobacter (7% each) were also observed. The unclassified genera Oscillospiraceae and Lachnospiraceae made up 14% and 6%, respectively. The “Other” category accounted for a quarter of the total microorganisms in the cecal microbiome of broilers.

When comparing the experimental and control groups, several clear changes were observed. With the addition of QC, the number of members of the genus Faecalibacterium increased by 1.2 and 1.4 times in experimental groups I and II, respectively; however, the most noticeable change was seen with the genus Subdoligranulum, whose abundance in experimental groups I, II, and III increased by 14, 4, and 3 times, respectively, compared to the control. An inverse relationship between this effect and QC concentration was noted.

Representatives of this genus can have both positive and negative effects on the host as their numbers increase [21, 22]. If an increase in Subdoligranulum is linked with a rise in the genus Gemmiger, it may harm the development of experimental birds, since recent studies show a negative correlation between Subdoligranulum abundance and body weight. However, if an increase in Subdoligranulum occurs alongside Faecalibacterium [23, 24], a positive trend in body weight indicators is seen. Additionally, increasing QC concentration to 10 and 15 mg/kg also led to a 1.5-fold increase in representatives of the genus Helicobacter, compared to groups II and III; these bacteria were not detected in the control group or group I.

Assessment of alpha-diversity indices revealed that adding QC at different doses did not significantly impact species richness or evenness in the cecal microbial community (Table 8). The Chao-1 index, which measures expected species richness, was highest in group I (QC1, 41.6) receiving 5 mg/kg QC, although its values were similar to those of the control group across other experimental groups. The Shannon (Shannon_H) and Simpson (Simpson_1-D) indices, which consider both richness and evenness, also showed no significant differences between groups (Figures 3 and 4).

In contrast, beta-diversity analysis showed structural differences in microbial community composition between the control and experimental groups, as illustrated with non-metric multidimensional scaling plots based on Bray–Curtis and Jensen–Shannon indices (Figure 5). The clear separation of clusters suggests that QC mainly affected microbial composition rather than overall diversity.

The study results show a clear dose-dependent effect of QC on broiler performance, health, and cecal microflora. This research offers a comprehensive analysis that combines three related aspects: growth metrics, immunophysiological status (based on hematology data), and gut microbiota composition. Studying these components together is innovative in phytobiotic research.

The gut microbiome is essential for gut health, immunity, and broiler performance [25]. Feed quality greatly influences gut health [26], while phytogenic additives enhance gut microbiota, increasing its efficiency [27]. However, how antimicrobial growth promoters boost bird growth remains unclear; it is believed they enhance growth by modulating the gut microbiota [28]. A healthy gut with a balanced microbial population is vital for improving feed conversion, defending against pathogens, and increasing bird growth rates [29]. Beneficial microbes, such as Lactobacillus, are critical for gut functions like metabolism, energy transfer, and growth.

Conversely, an increase in harmful pathogens (e.g., E. coli, Salmonella, and Clostridium) can significantly disrupt the balanced gut ecosystem and hinder bird growth [30]. Phytogenic compounds lower the growth of pathogenic microorganisms [31] and enhance microbiota balance and gut function [32]. Therefore, phytogenic additives can boost bird health and performance [33]. Phytobiotics have antimicrobial properties due to their polyphenolic compounds, including flavonoids like QC. Antimicrobial activity is considered a key feature of phytochemicals used as growth promoters in poultry diets [34]. QC is widely recognized for its antibacterial and antioxidant properties, as well as its ability to improve gut health, stimulate growth, and modulate immunity [35].

In addition to the direct antimicrobial and antioxidant properties, our results highlight another potential mechanism: interference with bacterial QS. The dose-dependent restructuring of the microbiota, especially the suppression of certain taxa and the promotion of others, aligns with the action of a QS inhibitor. Previously, in vitro experiments have shown that QC antagonizes QS systems in pathogens like Pseudomonas aeruginosa, inactivating regulatory molecules and reducing biofilm formation [36].

Our study offers initial evidence that QC’s known properties as a QS inhibitor might also influence the regulation of commensal microbial networks, thereby maintaining leukocyte inflammatory responses. We propose that QC could act similarly within the ceca of broilers, disrupting cell-to-cell communication required for the production of virulence factors and enabling colonization by potential pathogens. This QS-inhibiting activity might explain the decrease in potential pathobionts without completely eliminating all bacteria, thus preserving overall microbial diversity and supporting a more stable gut ecosystem. This method of interfering with bacterial signaling presents a complex mode of action that sets phytobiotics apart from traditional antibiotics and lessens the selective pressure for resistance development [37, 38]

The results of this study show a clear effect of QC on the performance indicators of AA broiler chicks. The data obtained align well with modern understanding of flavonoid action mechanisms in poultry. The most notable increase in live weight was seen in the group receiving 5 mg/kg of QC (QC1). By day 42 of the experiment, the difference between the control and experimental groups was 238.8 g (2610.00 vs. 2371.20 g), representing a 10.1% increase.

Our results, showing significant growth stimulation at 5 mg/kg, align with data from Sohaib M. et al. [39], who reported an 8%–12% increase in final live weight. However, it is very important to note that the source and purity of QC can greatly influence its bioavailability and effectiveness. For example, Zhang S. and Kim I. H. [40] used plant-derived QC at higher doses (0.25–1.00 g/kg) to achieve similar benefits.

This discrepancy might be due to differences in chemical form (aglycone versus glycoside) and to the presence of co-extracts in plant preparations, which could improve stability or absorption. In contrast, our study used highly purified (>95%) QC dihydrate, which could explain the significantly lower effective dose. Variations in BD composition, broiler genetics (AA versus Ross), and health status across studies create different baseline conditions upon which phytobiotics act, making direct dose comparisons challenging. Abid et al. [41] found that feeding broilers diets containing 0.1, 0.2, or 0.3 g/kg QC extracted from acacia improved feed conversion.

The growth-promoting effect of QC in poultry seems to involve several factors. First, as shown by El-Kazaz et al. [42], QC demonstrates strong antioxidant activity, lowering tissue malondialdehyde levels by 25%–30% and boosting superoxide dismutase activity by 15%–20%. This helps create ideal conditions for cellular metabolism and protein production.

Second, according to Abdel-Latif et al. [43], QC increases the height and depth of the small intestinal villi, significantly expanding the absorptive surface area of the intestine. Therefore, flavonoids have a beneficial effect on the digestive system of chicks, restoring microbiota balance and enhancing nutrient absorption [44].

The observed rise in the genus Faecalibacterium, especially in the QC1 group, is highly noteworthy. Faecalibacterium prausnitzii, a key species in this genus, is a primary producer of the short-chain fatty acid butyrate. Butyrate not only provides a major energy source for colonocytes but also acts as a potent immunomodulator. It encourages the differentiation of regulatory T cells and suppresses the production of pro-inflammatory cytokines such as IL-6 and TNF-α [45].

This anti-inflammatory mechanism offers a plausible explanation for the observed hematological changes, including decreased monocyte and neutrophil levels, and supports the improved vitality and overall health status in the QC-supplemented groups. Therefore, the increase in Faecalibacterium likely resulted in higher butyrate production, which reduced inflammation levels and enhanced feed conversion, ultimately reflecting improved growth performance.

The clear dose-dependent effect of QC is a notable aspect of the results. Unlike previous reports that used a single-dose, this study shows a nonlinear, biphasic response: moderate inclusion promotes eubiosis, while higher levels disturb microbial balance. This dose-dependent opposition introduces a new idea of a “phytobiotic optimum” in broiler nutrition, identifying 5 mg/kg QC as a beneficial threshold beyond which microbial dysbiosis may happen.

Unlike previous single-dose reports, this study describes a nonlinear, biphasic effect of QC, where moderate inclusion supports eubiosis, while higher levels disrupt microbial balance. This phenomenon is well documented in previous studies [46–51], which show that high doses of flavonoids can have a pro-oxidant effect and inhibit certain metabolic pathways.

The dose-dependent increase in the phylum Campylobacterota at 10 and 15 mg/kg is a key point for application. A potential mechanistic hypothesis is suggested for this phenomenon. QC may exert selective pressure at higher concentrations, promoting more resistant bacteria. While beneficial bacteria like Faecalibacterium may thrive at lower doses, higher doses could induce a pro-oxidant effect or cause a redox imbalance in the gut environment that some pathogens tolerate better. Additionally, the strong antibacterial activity of QC against dominant beneficial bacteria may reduce competitive exclusion, unintentionally creating a niche for the growth of opportunistic members of the Campylobacterota phylum. This highlights the importance of finding the optimal, rather than the maximum, phytobiotic supplement dosage.

The pattern of live weight changes during the rearing periods should be carefully observed. In the first 14 days of the experiment, differences between groups were minimal. However, starting from day 21, the QC1 group began to show a clear advantage. This aligns with the idea that QC’s effects are most noticeable during the intensive growth phase, when the body’s antioxidant defenses are under the greatest stress [52–54].

The analysis of feeding parameters revealed several key patterns. The total feed intake during the experimental period in the QC1 group was 4201.89 g, which was 8.8% higher than that in the control group (3862.09 g). Despite the higher intake, the FCR in this group was lower (1.77 vs. 1.80 in the control group). These findings suggest that QC not only stimulates appetite but also improves nutrient metabolic utilization. Similar results were reported by Fathima et al. [55], who attributed this effect to increased activity of digestive enzymes (amylase by 15%–20%, lipase by 10%–12%) under the influence of flavonoids.

Notably, all experimental groups maintained high livability (97%–98% vs. 95% in the control group). This metric is especially important in industrial poultry farming, as even a slight decrease in mortality can yield significant economic gains in large-scale production. According to data from several researchers, this effect of QC is linked to its ability to decrease the incidence of sudden death syndrome by 30%–35% and gastrointestinal disorders by 20%–25% [56, 57].

Hematological data provide important insights into QC. The most notable changes were seen in WBC parameters. Groups QC1 and QC2 showed significant (p ≤ 0.05) increases in total WBC count of 17.4% and 33.5%, respectively, compared to the control. These findings align with existing data [58], showing QC’s ability to promote hematopoiesis in the red bone marrow through activation of the transcription factor NF-κB.

The dynamics of lymphocyte-mediated immunity are especially noteworthy. Groups QC2 and QC3 showed a significant increase in relative lymphocyte count, with the most notable effect observed in QC3 (26.35 × 10⁹ cells/L vs. 24.53 × 10⁹ cells/L in the control). These changes suggest activation of specific immunity, as reported by Phillips et al. [59], who observed a 25%–30% increase in antibody titers against vaccine strains when QC was used.

An important aspect of QC’s action is its effect on non-specific immunity parameters. In groups QC1 and QC2, significant decreases in monocyte and neutrophil levels were observed. As shown in studies by several authors [60, 61], these changes are linked to QC’s ability to inhibit the synthesis of pro-inflammatory cytokines (IL-1β, TNF-α) by 40%–45% and to stimulate IL-10 production by 25%–30%.

Notably, our assessment of inflammatory status was based on hematological parameters. Although these are reliable indicators of systemic immune activation, future studies including specific cytokine assays (e.g., IL-6, TNF-α) would offer a more detailed understanding of the molecular mechanisms behind the immunomodulatory effects of QC.

The behavior of eosinophils is particularly noteworthy; their levels decreased in QC1 compared to the control. This change could have important practical implications. According to Deng et al. [62], a reduction in eosinophil levels is linked to a 15%–20% decrease in the frequency of allergic reactions and respiratory diseases in poultry. Changes in red blood parameters under QC influence were less obvious but still meaningful. In group QC1, hemoglobin concentration increased by 12.6% (121.25 g/L vs. 107.67 g/L in the control), and hematocrit rose by 4.1% (28.43% vs. 24.33%). These findings align with Wang et al. [63], who suggest that this effect results from QC’s ability to boost iron absorption in the intestine by 20%–25% and stimulate erythropoietin production by 15%–18%.

The regional context of this study, carried out in the Southern Urals of Russia, is an important factor to consider. The BD used in our trial was based on locally predominant ingredients (such as specific types of wheat and soybean meal), which may have different nutritional and non-starch polysaccharide profiles compared to feed bases used in other regions. These compositional differences could significantly influence the structure and function of the gut microbiota. Therefore, the optimal QC dose identified here (5 mg/kg) may reflect a specific interaction with the local feed base and its associated microbial ecosystem.

This highlights the importance of conducting region-specific trials to tailor phytobiotic supplementation strategies, as a universal approach may not account for these vital agroecological and nutritional factors. Our findings offer useful insights for poultry production systems that utilize similar feed resources in comparable climatic zones. While this study examines the dose-dependent effects of QC on the gut–microbiome–immune axis in broilers, it also opens several promising avenues for future research. To expand on these results, future studies could investigate the synergistic effects of combining QC with probiotics or essential oils to improve its eubiotic and pathogen-suppressing properties.

Furthermore, comprehensive assessments of long-term carcass yields and meat quality are essential to establish a direct link between microbiome changes and concrete food safety and product quality outcomes, such as reduced pathogen levels and extended shelf life. Lastly, for mechanistic validation of the suspected microbiota–immune system interaction, targeted analysis of the expression of key immune pathway genes and cytokines in the gut and spleen is necessary. This would provide a deeper understanding of the molecular mechanisms behind the immunomodulatory effects of QC.

Although this study provides strong evidence for QC’s effectiveness, several limitations should be noted: the relatively short trial duration, the use of a single broiler breed, and the lack of direct biochemical markers of inflammation.

An interesting aspect of our study is the lack of a significant effect of QC on alpha-diversity of the microbiome. Despite notable dose-dependent shifts in taxonomic structure at the phylum and genus levels, the phylogenetic richness and diversity indices remained statistically unchanged. This indicates that QC does not cause overall depletion or enrichment of the microbial community but instead exerts targeted, selective modulation, altering the ratio of already existing taxa.

A redistribution effect without a significant loss of overall diversity is considered favorable because high alpha-diversity is typically linked to gut ecosystem stability and resilience [64]. The notable changes in beta-diversity clearly show that QC has a targeted impact on microbiota composition, encouraging the development of unique microbial profiles in the experimental groups compared to the control. This supports the main conclusion that the cecal microbiome is dose-dependently modulated, with significant restructuring of the bacterial community even in the absence of alterations in overall diversity.

The results obtained have important implications for modern poultry production. Using QC at a dose of 5 mg/kg of feed not only enhances production indicators but also reduces the risk of metabolic disorders, particularly in intensive farming conditions. Studies have shown that dietary flavonoid supplementation can reduce the incidence of ascites and fatty liver syndrome [65].

The potential of QC as an alternative to antibiotic growth promoters is particularly noteworthy. Based on available data, flavonoid supplementation can reduce prophylactic antibiotic doses without harming productivity or survival [66]. This supports the current trend of decreasing antibiotic use in animal husbandry.

Therefore, the results of this study and the literature indicate that adding plant-derived QC to broiler diets is a promising strategy for antibiotic-free poultry production. It helps reduce mortality, improves feed efficiency, and increases daily live weight gain by positively affecting the gut microbiome. Although a large amount of data has been gathered, several issues still need more research. Future studies should explore the combined use of QC with other bioactive substances, refine administration methods across different growth stages, develop cost-effective methods to incorporate it into feed, and assess its long-term effects on product quality.

Furthermore, future studies should include cytokine profiling, quantitative assessment of short-chain fatty acids (SCFA), and long-term evaluations of meat quality to verify the microbiome-related benefits of QC.