Dietary Supplementation with Rosa rubiginosa petal as a Natural Feed Additive Modulates Growth Performance, Skin Pigmentation, Immunity, and Gut Health in Goldfish (Carassius auratus)

Dietary Supplementation with Rosa rubiginosa petal as a Natural Feed Additive Modulates Growth Performance, Skin Pigmentation, Immunity, and Gut Health in Goldfish (Carassius auratus) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dietary Supplementation with Rosa rubiginosa petal as a Natural Feed Additive Modulates Growth Performance, Skin Pigmentation, Immunity, and Gut Health in Goldfish (Carassius auratus) Nutticha Nuntakad, Luu Tang Phuc Khang, Suwanna Wisetkaew, Nguyen Dinh-Hung, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6608516/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Natural additives are increasingly valued in ornamental fish aquaculture. Rose petal contains bioactive compounds, yet their effects on goldfish ( Carassius auratus ) remain underexplored. This study assessed the impacts of graded dietary rose petal supplementation (0, 5, 10, 20, and 40 g/kg; RP-0 to RP-40) over an 8-week feeding trial on growth performance, skin pigmentation, serum antioxidant status, intestinal gene expression, and gut microbiota composition. Fish fed RP-supplemented diets, particularly at 40 g/kg, exhibited significantly higher final weight and weight gain than the RP-0 group ( p < 0.05), without adverse effects on survival or feed conversion ratio. Skin redness (a⁎) and yellowness (b⁎) increased significantly in a dose-dependent manner ( p < 0.05 at RP-20/40 for a⁎, RP-40 for b⁎). Serum antioxidant capacity improved with increasing RP levels, as indicated by higher ABTS and SOD activities and lower MDA levels ( p < 0.05). Dietary rose petal supplementation also significantly upregulated intestinal expression of antioxidant ( HSP70 , CYP1A ), growth ( IGF , TGF ), and immune ( LYZ , TNFα ) genes, primarily at 20–40 g/kg ( p < 0.05). While rose petal significantly altered gut microbiota composition based on beta diversity (PERMANOVA p = 0.017) and specific taxon abundances (e.g., increased Staphylococcus at RP-40 and decreased Alloprevotella at RP-5; ANCOMBC2, p < 0.05), it did not significantly affect alpha diversity or exhibit strong correlations with host physiological parameters after FDR correction. Overall, the results of this study highlights rose petal as a natural functional additive for ornamental aquaculture. goldfish gut microbiota immunity rose petals pigmentation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 1. Introduction The ornamental fish trade has gained significant popularity in recent years, driven by the high aesthetic and commercial value of many species in the international market. Several ornamental fish are prized for their vivid coloration, diverse body shapes, and distinctive fin structures (Lau et al 2023 ). Among these, the goldfish ( Carassius auratus ) is one of the most famous and commercially valuable species (Yanar et al 2008 ). Goldfish have become widespread, with numerous farms and hatcheries established globally (Ota 2021 ). Their natural beauty and adaptability to a wide range of environmental conditions have contributed to their prominence in the ornamental fish industry (Martinez-Murcia et al 2008 ; Blanco and Unniappan 2022 ). Coloration in goldfish is primarily determined by the distribution and type of pigment cells (Luo et al 2021 ). In teleosts, six types of pigment cells have been identified: cyanophores, leucophores, iridophores, xanthophores, and melanophores (Goda et al 2013 ; Zhang et al 2023 ). Variations in pigment cell types across different body regions lead to diverse color patterns. High carotenoid content, in particular, contributes to the distinctive red coloration of goldfish, enhancing their marketability and consumer acceptance (Gümüş et al 2022 ; Elshafey et al 2023 ). Consequently, maintaining vibrant natural pigmentation is critical for market demand and commercial success among fish farmers. In recent years, there has been growing interest in using natural plant-based ingredients such as leaves, fruit peels, and flowers to enhance pigmentation in ornamental fish (Elshafey et al 2023 ). Successful intensive aquaculture requires nutritionally balanced diets that include essential nutrients and carotenoids as dietary supplements (Ahilan et al 2013 ). Beyond pigmentation, carotenoids are also essential for growth, metabolism, reproduction, and overall health in goldfish (Ahilan et al 2013 ; Hilal and Duygu 2020 ; Sathyaruban et al 2021 ; Kautsar et al 2022 ; Elshafey et al 2023 ; Khieokhajonkhet et al 2023 ). Like other animals, fish cannot synthesize carotenoids de novo and must acquire them through their diet (Elshafey et al 2023 ). In addition to carotenoids, dietary sources of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are critical for the growth and survival of goldfish, as they cannot biosynthesize these essential fatty acids from shorter-chain precursors (Gümüş et al 2022 ). The level of dietary carotenoid intake directly influences pigmentation intensity in fish (Sathyaruban et al 2021 ). Consequently, a wide range of carotenoid sources has been incorporated into aquafeeds, including pure carotenoid extracts (Shahidi and Brown 1998 ; Yuangsoi et al 2011 ), animal-derived pigments (Swain et al 2020 ; Lim et al 2023 ), and plant-derived pigments (Wallat et al 2005 ; Harpaz and Padowicz 2007 ; Wagde et al 2018 ; Rana et al 2023 ). Plant-based sources offer dual advantages by providing essential nutrients (e.g., proteins, fats, vitamins) along with high carotenoid content (Ansari et al 2021 ). Given concerns regarding the cost and safety of synthetic additives, there is an increasing trend toward the use of natural carotenoids as alternatives in aquaculture (Elshafey et al 2023 ). Roses are recognized as rich natural sources of carotenoids (Wan et al 2018 ), and species such as China rose ( Hibiscus rosa-sinensis ), sweetbriar rose ( Rosa rubiginosa ), and cyme rose ( Rosa indica ) have been utilized in fish diets to promote growth, enhance immune function, and improve pigmentation (Sinha and Asimi 2007 ; Joseph et al 2011 ; Arulvasu et al 2013 ; Rintan et al 2019 ). These findings underscore the potential of natural carotenoid supplementation to enhance ornamental fish health and marketability. Despite these promising outcomes, research specifically examining the effects of rose petal by-products as carotenoid sources in ornamental fish, particularly in goldfish, remains limited. This study seeks to address this knowledge gap by evaluating the effects of rose petal-derived carotenoids on key health indicators in goldfish, including growth performance, immune response, gut microbiota composition, and gene expression. 2. Materials and methods 2.1. Fish preparation and experimental design Healthy goldfish ( Carassius auratus ) were obtained from a commercial farm in Chiang Mai Province, Thailand, and transported to the aquaculture research station at the Department of Animal and Aquatic Sciences, Faculty of Agriculture, Chiang Mai University. Upon arrival, fish were acclimated for 14 days in aerated tanks and fed a commercial pelleted diet containing 400 g/kg crude protein, 70 g/kg lipid, and 40 g/kg fiber, administered manually three times daily until apparent satiation (Khieokhajonkhet et al 2025 ). Prior to the feeding trial, all fish were fasted for 24 hours to standardize gastrointestinal clearance and metabolic conditions. Following acclimation, 300 fish with an initial average body weight of 6.75–6.90 g was randomly assigned to 15 experimental tanks (50 × 100 × 40 cm; 180 L water volume), corresponding to five dietary treatment groups with three replicates each. Fish were fed experimental diets twice daily at a rate of 3% body weight, adjusted weekly based on biomass measurements, for 8 weeks. Uneaten feed and waste were siphoned daily, and approximately 10% of the water was replaced with fresh dechlorinated tap water to maintain optimal conditions. Environmental parameters were closely monitored to reduce stress and mimic natural conditions. Tanks were exposed to a 12 h light/12 h dark photoperiod. Water temperature was maintained at 24 ± 1°C, dissolved oxygen levels > 5 mg/L, pH between 7.5–8.0, and ammonium concentrations below 1 mg/L. 2.2. Preparation of experimental diets Five experimental diets were formulated by replacing fish meal with rose petal (RP) meal at inclusion levels of 0, 5, 10, 20, and 40 g/kg, designated as RP0, RP5, RP10, RP20, and RP40, respectively. All dry ingredients were sieved through a 250 µm mesh to ensure uniform particle size. Ingredients were then accurately weighed according to the formulation in Table 1 and homogenized in a mechanical mixer for 10 minutes to achieve a consistent blend (Linh et al 2025 ). Table 1 Formulation of experimental diets containing graded levels of rose petal (RP) powder (g/kg dry matter basis). Ingredients Rose petal concentration (g/kg diet) RP-0 (control) RP-5 RP-10 RP-20 RP-40 Fish meal 370 370 370 370 370 Soybean meal 400 395 390 380 360 Corn meal 20 20 20 20 20 Rice bran 80 80 80 80 80 Wheat flour 80 80 80 80 80 Red yeast 5 5 5 5 5 Lecithin 7 7 7 7 7 Methionine 5 5 5 5 5 Lysine 5 5 5 5 5 Binder 5 5 5 5 5 Soybean oil 5 5 5 5 5 Rose petal 0 5 10 20 40 Premix 10 10 10 10 10 Vitamin C 98% 10 10 10 10 10 Proximate (%) Ash 11.33 11.44 11.59 11.52 11.49 Fiber 3.98 3.96 3.88 3.95 3.93 Crude lipid 2.83 2.87 2.88 2.86 2.87 Crude protein 36.36 36.32 36.35 36.36 36.38 Nitrogen-free extract 45.50 45.41 45.3 45.31 45.33 The mixtures were pelleted using a 2 mm diameter mincer, selected to match the oro-pharyngeal dimensions of juvenile goldfish and facilitate optimal feed intake while reducing waste. The pellets were dried at 50°C overnight in a hot-air oven and subsequently stored in airtight polyethylene bags at 4°C until use in feeding trials and proximate composition analysis. Proximate composition of the diets was determined following the Association of Official Analytical Chemists (AOAC 2016), standard procedures. Moisture content was assessed gravimetrically by drying triplicate samples at 105°C to constant weight using a Memmert UL50 incubator. Ash content was measured by incineration at 550°C for 8 hours in a Carbolite ELF 11/14 muffle furnace. Crude lipid content was determined via Soxhlet extraction with petroleum ether using a Gerhardt apparatus. Crude protein was analyzed using the Kjeldahl method (N × 6.25) with a semi-automatic Gerhardt Vapodest 45s system. All analyses were performed in triplicate to ensure accuracy and reproducibility. 2.3. Growth performance parameters Fish were batch-weighed biweekly using a KERN analytical balance to monitor growth performance. After weighing, fish were promptly returned to their respective tanks to minimize handling stress. Growth performance indicators, including weight gain (WG), percent weight gain (PWG), specific growth rate (SGR), daily weight gain (DWG), feed conversion ratio (FCR), and survival rate (SR), were calculated using standard equations (LinhLubis et al 2024 ; LinhWannavijit et al 2024 ): Survival rate (SR, %) = (Final number of fish / Initial number of fish) × 100 Weight gain (WG) = Final body weight − Initial body weight Percent weight gain (PWG, %) = [(Final body weight − Initial body weight) / Initial body weight] × 100 Specific growth rate (SGR, %/day) = [(ln Final body weight − ln Initial body weight) / Culture days] × 100 Daily weight gain (DWG, g/day) = (Final body weight − Initial body weight) / Culture days Feed conversion ratio (FCR) = Total dry feed intake / Live weight gain 2.4. Skin color measurement To assess the effects of dietary treatments on skin pigmentation, five fish per tank were randomly netted and photographed at week 8 under standardized lighting conditions using a Panasonic digital camera (Panasonic, Japan). Immediately afterward, fish were gently blotted to remove excess moisture and subjected to colorimetric analysis before group weighing, thereby minimizing pigment distortion due to handling stress. Skin color measurements were conducted on the left side of the head using a HunterLab MiniScan EZ 4500 L spectrocolorimeter (Hunter Associates, USA). The instrument was calibrated against standard black and white tiles according to the guidelines of the International Commission on Illumination (CIE 1976), prior to data collection. For each fish, three replicates of CIELAB color values were recorded: L* (lightness), a* (red–green axis), and b* (yellow–blue axis). In this system, L* values range from 0 (black) to 100 (white), a* values from negative (green) to positive (red), and b* values from negative (blue) to positive (yellow) (Hunter and Harold 1987 ). 2.5. Blood biochemical analysis Prior to biochemical analysis, six fish were randomly selected from each dietary treatment group. Blood was collected from the caudal vein using a heparinized 1 mL syringe and immediately transferred to enzyme-free 1.5 mL centrifuge tubes to prevent coagulation. Samples were centrifuged at 3,000 rpm for 10 minutes at 4°C to separate serum, which was carefully pipetted into clean microtubes and stored at − 80°C until analysis. Serum antioxidant capacity was assessed using the ABTS radical scavenging assay as described by Boonkong et al ( 2024 ). Briefly, 10 µL of thawed serum was mixed with deionized water and ABTS working solution, incubated in the dark for 10 minutes, and absorbance was measured at 734 nm. Radical scavenging activity (%) was calculated using a standard inhibition formula. Superoxide dismutase (SOD) activity was measured using a commercial assay kit (CS0009, Sigma-Aldrich) following the protocol of Li et al ( 2020 ). Samples were incubated with kit reagents, and absorbance was recorded at 450 nm using a Varioskan LUX microplate reader (Thermo Scientific, Vantaa, Finland). Lipid peroxidation was evaluated by measuring malondialdehyde (MDA) levels using an MDA assay kit (KTB1050, Abbkine). Serum samples were reacted with thiobarbituric acid to form MDA–TBA complexes, and absorbance was measured at 532 nm. Nonspecific turbidity was corrected by subtracting absorbance at 600 nm, following the method of Karatas and EM ( 2012 ). 2.6. Intestinal gene expression assays To evaluate transcriptional responses of immune-related and antioxidant genes, six fish from each dietary group were anesthetized, and approximately 50 mg of mid-intestinal tissue was aseptically excised. Tissue samples were immediately immersed in 200 µL of TRIzol™ reagent (Invitrogen™, USA) in sterile microcentrifuge tubes and stored at − 80°C until RNA extraction. Upon thawing, samples were homogenized using a Bullet Blender® Homogenizer to ensure complete cellular disruption. Total RNA was extracted following the TRIzol™ protocol, and the aqueous phase was further purified using a Total RNA Extraction Kit (Omega Bio-tek, USA). RNA concentration and purity were assessed using a NanoDrop™ One/OneC spectrophotometer (Thermo Fisher Scientific, USA), and only samples with an A260/280 ratio between 1.8 and 2.0 were used for downstream applications. Complementary DNA (cDNA) was synthesized from 1 µg of total RNA using a commercial reverse transcription kit (Bio-Rad, USA), following the manufacturer’s thermal cycling protocol. Quantitative real-time PCR (qRT-PCR) was then conducted using the CFX Connect™ Real-Time PCR Detection System (Bio-Rad, USA) in a 20 µL reaction volume, as described in previous studies (Linh et al 2023 ; Sintuprom et al 2024 ). Each reaction contained 1 µL of cDNA (100 ng), 0.4 µL of each gene-specific primer (10 µM), 10 µL of 2× iTaq™ Universal SYBR® Green Supermix (Bio-Rad, USA), and nuclease-free water to reach the final volume. The thermal cycling protocol included an initial denaturation at 95°C for 30 seconds, followed by 40 cycles of denaturation at 95°C for 15 seconds and annealing/extension at 60°C for 30 seconds. A melt curve analysis (95°C for 15 seconds, 60°C for 60 seconds, and 95°C for 15 seconds) was performed to verify amplification specificity. Relative gene expression levels were calculated using the 2 –ΔΔct method (Livak and Schmittgen ( 2001 ), with Actin‑2 serving as the internal reference gene (Table 2 ). Table 2 Gene-specific primers used for quantitative real-time PCR (qPCR) analysis in goldfish ( Carassius auratus ). Target gene Sequence (5′–3′) Genebank accession number β-actin 2 Forward TGCTGACCGTATGCAGAAAG AB039726.2 Reversed TGAGAGGTTTGGGTTGGTC IL-1B Forward TTCATTTGAAGGCAGTGACG AJ249136.1 Reversed TAAGCTGTGCCCGTCTCTTT IL-10 Forward CAAGGAGCTCCGTTCTGCAT HQ259106 Reversed TCGAGTAATGGTGCCAAGTCATCA TNF α Forward TCATTCCTTACGACGGCATTT EU069818.1 Reversed CAGTCACGTCAGCCTTGCAG TGF Forward ACCATATGCCAAAGCCTCAC EU086521.1 Reversed TGATGCCTATACAGCGCAAG IGF Forward CAGGGGCATTGGTGTGA GU583648 Reversed GCAGCGTGTCTACAAGC CYP1A Forward TCACCGACTCGCTCATCAAC DQ517445 Reversed TTCAGCTCTGTACCGTCTGC LYZ Forward GCCGGAAATGTCCTGAATAA KR092198.1 Reversed GTGGTCCTGGCATCGATATT HPS70 Forward GGCAGAAGGTGACAAATGCA JN544930.1 Reversed TGGGCTCGTTGATGTTCTCA 2.7. Gut microbiome analysis At the end of the 8-week feeding trial, six fish per dietary group were randomly selected for gut microbiota analysis. Fish were euthanized, and the posterior intestine was aseptically excised. Samples were immediately stored at − 80°C until DNA extraction. Microbial genomic DNA was extracted using the QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany) following the manufacturer's protocol. The V3–V4 hypervariable regions of the 16S rRNA gene were amplified using primers 341F (5′-CCTAYGGGRBGCASCAG-3′) and 806R (5′-GGACTACNNGGGTATCTAAT-3′). PCR products were processed for library preparation and paired-end sequenced on an Illumina MiSeq platform by Macrogen Inc. (Seoul, Republic of Korea). Raw reads were processed using the QIIME 2 pipeline (v2022.2) (Bolyen et al 2019 ). After quality assessment, adapter trimming, and read filtering, denoising, merging of paired-end reads, and chimera removal were conducted using DADA2 (Callahan et al 2016 ) to generate amplicon sequence variants (ASVs). Taxonomic classification was performed using a Naive Bayes classifier trained on the SILVA database (v138, 99% similarity) (Quast et al 2012 ). Phylogenetic trees were constructed using MAFFT for alignment (Katoh and Standley 2013) and FastTree 2 for tree inference (Price et al 2010 ). Downstream analyses and visualization were conducted in R (v4.4.3; R Core Team, 2024) using QIIME 2-exported data and the phyloseq (v1.48.0) (McMurdie and Holmes 2013 ) and vegan (v2.6.8) (Oksanen et al 2024 ) packages. Alpha diversity was assessed using Shannon entropy, Pielou's evenness, Chao1 richness, and Faith’s phylogenetic diversity (PD), with group differences tested via Kruskal–Wallis tests. Beta diversity was calculated using Bray–Curtis dissimilarity, Jaccard distance, and weighted/unweighted UniFrac distances, with community structures visualized using Principal Coordinates Analysis (PCoA). Group differences were statistically evaluated using PERMANOVA with 999 permutations (QIIME 2 beta-group-significance ), and pairwise p-values were adjusted using the False Discovery Rate (FDR) method. Differential abundance between groups was assessed using ANCOM-BC (v2.6.0) (Lin and Peddada 2020 ) applying a pseudo-count and Holm correction, with a significance threshold of q < 0.05. Spearman’s rank correlation was used to examine associations between microbial ASV abundances (log1p-transformed after total sum scaling) and host growth parameters using the Hmisc package (v5.2.3) (Harrell and Dupont 2025 ), with FDR-adjusted significance at q < 0.05. Data visualization was performed using ggplot2 (v3.5.2) (Wickham and Sievert 2016 ).Unless otherwise stated, statistical significance was set at p < 0.05 or q < 0.05, as appropriate. 2.8. Data analysis All statistical analyses were conducted using OriginPro (v2021b, OriginLab Corporation, Northampton, MA, USA) and IBM SPSS Statistics (v29.0.2.0, IBM Corp., Armonk, NY, USA). Data normality was assessed using both the Kolmogorov–Smirnov and Shapiro–Wilk tests, while Levene’s test was used to evaluate homogeneity of variances. For datasets meeting assumptions of normality and homogeneity, one-way analysis of variance (ANOVA) was employed to analyze growth performance, skin pigmentation, serum biochemical parameters, and gene expression data. Duncan’s multiple range test was used for post hoc comparisons to identify significant differences among treatment means. When assumptions were not met, non-parametric alternatives such as the Kruskal–Wallis test were applied, followed by Dunn’s post hoc test with Bonferroni correction where applicable. Pearson’s and Spearman’s correlation coefficients were calculated to assess relationships among growth performance, antioxidant activities, gene expression, and gut microbiota composition. All results are presented as mean ± standard deviation (SD), and statistical significance was set at p < 0.05. 3. Results 3.1. Growth performance, feed utilization, and survival Growth performance, feed utilization, and survival of koi carp fed RP-supplemented diets were evaluated at weeks 4 and 8 (Table 3 ). Survival remained high across all groups, with no significant mortality observed in RP-0 to RP-20 (96.7–98.3%) and complete survival (100%) in the RP-40 group, indicating that dietary inclusion of RP up to 40 g/kg did not compromise fish viability. Table 3 Effects of dietary rose petal supplementation on survival rate, growth performance, and feed conversion ratio of goldfish ( Carassius auratus ) at weeks 4 and 8. Parameter RP-0 RP-5 RP-10 RP-20 RP-40 Initial weight (g) 6.82 ± 0.06 6.85 ± 0.05 6.85 ± 0.09 6.85 ± 0.06 6.85 ± 0.09 Week 4 Survival rate (%) 98.33 ± 2.89 98.33 ± 2.89 96.67 ± 5.77 98.33 ± 2.89 100.00 ± 0.00 Final weight (g) 12.53 ± 0.48 b 12.88 ± 0.16 b 12.96 ± 0.76 b 13.07 ± 0.26 b 14.38 ± 0.50 a Weight gain (g) 5.72 ± 0.48 b 6.03 ± 0.20 b 6.11 ± 0.47 b 6.22 ± 0.23 b 7.53 ± 0.45 a Percent weight gain (%) 83.88 ± 6.97 b 88.09 ± 3.51 b 89.30 ± 7.97 b 90.83 ± 3.19 b 109.96 ± 5.87 a Percentage specific growth rate (%.day − 1 ) 2.03 ± 0.13 2.11 ± 0.63 2.13 ± 0.14 2.15 ± 0.06 2.47 ± 0.10 Daily weight gain (g.day − 1 ) 0.20 ± 0.02 b 0.22 ± 0.01 b 0.22 ± 0.02 b 0.22 ± 0.01 b 0.27 ± 0.01 a FCR 0.89 ± 0.03 0.89 ± 0.03 0.91 ± 0.06 0.89 ± 0.03 0.88 ± 0.01 Week 8 Survival rate (%) 98.33 ± 2.89 98.33 ± 2.89 96.67 ± 5.77 98.33 ± 2.89 100.00 ± 0.00 Final weight (g) 17.78 ± 0.32 b 18.02 ± 0.86 b 18.64 ± 0.68 b 18.70 ± 0.57 b 20.13 ± 0.41 a Weight gain (g) 10.97 ± 0.37 b 11.17 ± 0.92 b 11.79 ± 0.62 b 11.85 ± 0.56 b 13.28 ± 0.49 a Percent weight gain (%) 160.82 ± 6.24 b 163.09 ± 14.55 b 172.09 ± 7.87 b 172.98 ± 7.75 b 193.97 ± 9.71 a Percentage specific growth rate (%.day − 1 ) 3.19 ± 0.09 3.71 ± 0.03 3.36 ± 0.16 3.60 ± 0.17 3.43 ± 0.22 Daily weight gain (g.day − 1 ) 0.20 ± 0.01 b 0.20 ± 0.02 b 0.21 ± 0.01 b 0.21 ± 0.01 b 0.24 ± 0.01 a FCR 3.14 ± 1.10 3.71 ± 0.03 3.36 ± 0.16 3.60 ± 0.17 3.31 ± 0.22 Data are presented as mean ± SD. Different letters within a row indicate significant differences (p < 0.05 By week 4, fish fed the RP-40 diet showed significantly higher FW, WG, and PWG compared to RP-0 ( p < 0.05), while RP-5 to RP-20 groups showed only marginal, non-significant improvements. DWG in RP-40 (0.27 g/day) was ~ 18% higher than in other groups. Although SGR showed a supplementation-related increase, it was not statistically significant at this stage. At week 8, the growth-promoting effect of high RP supplementation became more pronounced. RP-40-fed fish had significantly greater FW, WG, and PWG than RP-0 ( p < 0.05), while RP-5 to RP-20 yielded moderate but non-significant improvements. SGR continued to exhibit a dose-dependent increase, though the differences remained statistically non-significant. FCR was unaffected by RP inclusion and remained stable across treatments (week 4: 0.88–0.91; week 8: 3.14–3.71), suggesting that improved growth was not associated with reduced feed efficiency. Regression analysis revealed strong linear relationships between RP inclusion level and performance metrics (Fig. 1 ): FW increased from 17.8 g (RP-0) to 20.2 g (RP-40; Adj. R² = 0.70), SGR from 3.19%/day to 3.72%/day (Adj. R² = 0.69), FCR decreased from 3.71 to 3.29 (Adj. R² = 0.70), and WG increased from 11.0 g to 13.8 g (Adj. R² = 0.77). Correlation analysis among growth parameters showed strong positive associations between FW, WG, PWG, DWG, and SGR (r = 0.98–1.00, p < 0.05), indicating consistent trends in weight-based growth indices (Fig. 2 ). In contrast, FCR was significantly negatively correlated with these parameters (r = − 0.57 to − 0.62, p 0.05). 3.2. Skin pigmentation After 60 days of feeding, skin color parameters (L*, a*, b*) were measured to evaluate the effects of dietary RP supplementation (Table 4 ). Skin lightness (L*) showed no significant differences among treatment groups, with values ranging from 61.10 ± 14.99 to 66.35 ± 13.00 (p > 0.05), and no significant correlation was observed between L* values and RP concentration (r = 0.12, p = 0.072; Fig. 3 C). Table 4 Effects of dietary rose petal supplementation on skin color parameters, luminosity (L*), redness (a*), and yellowness (b*), in goldfish ( Carassius auratus ) after 8 weeks. Parameter Rose petal dietary (g/kg) RP-0 RP-5 RP-10 RP-20 RP-40 Luminosity (L*) 61.10 ± 14.99 63.72 ± 12.29 65.38 ± 14.38 65.63 ± 11.81 66.35 ± 13.00 Redness (a*) 20.54 ± 7.02 c 22.11 ± 5.82 bc 24.61 ± 7.32 ab 25.32 ± 5.69 a 26.14 ± 6.58 a Yellowness (b*) 40.32 ± 14.04 b 41.02 ± 13.06 b 41.44 ± 14.46 b 43.84 ± 10.07 ab 47.73 ± 11.08 a Data are presented as mean ± SD. Different letters within a row indicate significant differences (p < 0.05) In contrast, skin redness (a*) increased significantly in a dose-dependent manner. Fish fed the RP-20 (25.32 ± 5.69) and RP-40 (26.14 ± 6.58) diets had significantly higher a* values compared to the RP-0 group (20.54 ± 7.02) (p < 0.05). This trend was supported by a significant positive correlation between RP concentration and a* values (r = 0.30, p < 0.001; Fig. 3 A). Similarly, skin yellowness (b*) was significantly enhanced at the highest supplementation level. The RP-40 group (47.73 ± 11.08) exhibited significantly higher b* values than the RP-0 group (40.32 ± 14.04) (p < 0.05), with a corresponding positive correlation between RP concentration and b* values (r = 0.18, p = 0.0077; Fig. 3 B). 3.3. Antioxidant capacity and oxidative stress markers Dietary RP supplementation significantly influenced serum antioxidant capacity and oxidative stress markers in goldfish (Fig. 4 ). Antioxidant capacity, measured by ABTS radical scavenging activity, increased progressively with rising RP levels (Fig. 4 A). Fish fed RP-20 and RP-40 diets exhibited significantly higher ABTS activity than the RP-0 group (p < 0.05), with a strong positive correlation observed between RP concentration and ABTS activity (r = 0.57, p < 0.001; Fig. 5 A). Similarly, superoxide dismutase (SOD) activity showed a dose-dependent increase (Fig. 4 B). While no significant differences were observed at lower RP levels (RP-5, RP-10), SOD activity in the RP-40 group was significantly higher than in RP-0 (p < 0.05). This was supported by a strong positive correlation between RP concentration and SOD activity (r = 0.69, p < 0.001; Fig. 5 B). Conversely, lipid peroxidation, indicated by malondialdehyde (MDA) content, declined with increasing RP inclusion (Fig. 4 C). Fish in the RP-40 group exhibited significantly lower serum MDA levels compared to RP-0 (p < 0.05). A significant negative correlation was also observed between RP concentration and MDA levels (r = − 0.38, p = 0.037; Fig. 5 C). 3.4. Intestinal expression of antioxidant, growth, and immune‑related genes Dietary RP supplementation modulated the expression of multiple genes related to antioxidant defense, growth, and immune function in goldfish (Fig. 6 ). Among antioxidant-related genes, HSP70 expression remained unchanged at lower RP levels but was significantly upregulated in the RP-40 group compared to RP-0 (p < 0.05). CYP1A followed a similar trend, with moderate increases at RP-10 and RP-20 (not statistically significant), and a significant peak at RP-40 (p < 0.05). Both genes showed strong positive correlations with RP concentration ( HSP70 : r = 0.68, p < 0.001; CYP1A : r = 0.61, p < 0.001; Fig. 7 A, D). Growth-related transcripts were also significantly affected. IGF expression increased progressively from RP-5 to RP-40, reaching significance in RP-20 and RP-40 compared to RP-0 (p < 0.05). TGF showed a similar pattern, with significant upregulation at RP-20 and RP-40 (p < 0.05). Both genes exhibited strong positive correlations with RP inclusion ( IGF : r = 0.69, p < 0.001; TGF : r = 0.77, p < 0.001; Fig. 7 B, C). Immune-related genes also responded positively to RP supplementation. LYZ expression increased in a dose-dependent manner, with significantly higher levels in RP-20 and RP-40 compared to RP-0 (p < 0.05). TNFα was significantly elevated from RP-10 onward, reaching its highest expression at RP-40 (p < 0.05). Both genes showed strong positive correlations with RP concentration ( LYZ : r = 0.92, p < 0.001; TNFα : r = 0.83, p 0.05), with no significant correlations with RP concentration ( IL10 : p = 0.689; IL1β : p = 0.437; Fig. 7 G, H). 3.5. 16S rRNA sequencing and ASV characterization High-throughput sequencing of the 16S rRNA gene V3–V4 region produced a total of 522,700 high-quality reads across 15 samples following quality filtering, with an average read length of 246 bp. Processing via the DADA2 pipeline yielded 8,525 unique Amplicon Sequence Variants (ASVs) across all samples. Per-sample read counts ranged from 26,712 to 43,898, with a mean of 34,847 reads. The number of observed ASVs per sample ranged from 208 to 890, averaging approximately 626 ASVs. The distribution of total read counts across dietary treatments (RP-0, RP-5, RP-10, RP-20, RP-40) is presented in Fig. 8 . 3.6. Gut microbiota composition 16S rRNA gene sequencing revealed diverse gut microbial communities across all treatment groups, with notable inter-sample variation, particularly in RP-0 (4) and RP-20 (5), which exhibited distinct taxonomic profiles (Figs. 9 and 10 ). At the phylum level, Proteobacteria was most abundant (~ 21.0%), followed by Firmicutes (10.3%), Actinobacteriota (9.7%), Bacteroidota (7.9%), and Cyanobacteria (5.1%), while unclassified taxa accounted for ~ 35.8% of sequences. Sample RP-0 (4) showed elevated Proteobacteria (~ 40%), unlike other RP-0 replicates with higher unclassified taxa and lower Proteobacteria . Similarly, RP-20 (5) was dominated by Proteobacteria (~ 49%). At the genus level, Chloroplast (~ 4.7%) and Escherichia-Shigella (~ 3.8%) were among the most abundant classified genera, though unclassified genera (~ 50.8%) and low-abundance "Other" taxa (~ 20.7%) comprised the majority. RP-0 (4) was dominated by Escherichia-Shigella (> 33%), while RP-20 (5) showed elevated Aeromonas (~ 4.6%). Other genera like Methyloversatilis , Vibrio , Staphylococcus , and Muribaculaceae were present at low levels. Overall, the gut microbiota showed high diversity with distinct compositional outliers. 3.7. Microbial diversity Alpha diversity, assessed using Shannon entropy, Pielou’s evenness, Chao1 richness, and Faith’s Phylogenetic Diversity (PD), showed no significant differences among dietary groups (Kruskal–Wallis test, p > 0.05; Fig. 11 ). Specifically, Shannon (p ≈ 0.60), Chao1 (p ≈ 0.52), Pielou’s evenness (p ≈ 0.57), and Faith’s PD (p ≈ 0.23) all indicated comparable within-sample diversity across treatments. Although exploratory pairwise comparisons for Faith’s PD (RP-0 vs RP-10; RP-0 vs RP-40) yielded unadjusted p < 0.05, these were not significant after FDR correction (q ≈ 0.25). Visual inspection showed substantial overlap among groups, and previously noted outlier samples (RP-0 [4], RP-20 [5]) did not differ markedly in alpha diversity. Beta diversity analysis using Principal Coordinates Analysis (PCoA) based on Bray–Curtis dissimilarity revealed partial separation among groups, particularly between RP-10/RP-20 and the remaining treatments (Fig. 12 ). The first two axes explained 14.33% and 9.51% of the total variance. PERMANOVA confirmed significant differences in community composition among groups (Pseudo-F = 1.13, p = 0.017), though post hoc pairwise comparisons were non-significant after multiple testing correction (all q > 0.05). Analyses using Jaccard and UniFrac distances also yielded non-significant results (data not shown), suggesting the Bray–Curtis significance stemmed from subtle shifts in relative taxon abundances rather than major compositional restructuring. 3.8. Differential abundance of gut microbiota Differentially abundant taxa across treatment groups were identified using ANCOM-BC2 with Holm-adjusted p-values (threshold: p < 0.05). Two taxa showed significant differences relative to the control (RP-0) group (Fig. 13 ): Staphylococcus (phylum Firmicutes ) was significantly enriched in RP-40 (LFC ≈ 5.22, p < 0.05), while an uncultured Alloprevotella species (phylum Bacteroidota ) was significantly depleted in RP-5 (LFC ≈ − 6.85, p < 0.05). No other taxa differed significantly from RP-0. Pairwise comparisons among RP-treated groups revealed four additional differentially abundant taxa (Fig. 14 ). Staphylococcus abundance was higher in RP-40 than RP-20 and lower in RP-5 than RP-40. An uncultured Muribaculaceae species was significantly enriched in RP-40 compared to RP-10 and RP-20 and depleted in RP-5 relative to RP-40. A member of Micrococcaceae (phylum Actinobacteriota ) was more abundant in RP-5 than RP-20. Lastly, Chloroplast sequences were significantly enriched in RP-5 and RP-40 compared to RP-20. These findings indicate that specific gut microbial taxa respond to distinct levels of dietary rose petal supplementation. 4. Discussion Replacing fishmeal with sustainable, plant-derived ingredients is essential for reducing reliance on marine resources in aquaculture (Hossain et al 2024 ). This study demonstrated that partial replacement of fishmeal with RP powder up to 40 g/kg did not compromise growth performance or feed utilization in goldfish. RP is rich in carotenoids, amino acids, polyunsaturated fatty acids, and trace minerals, which likely acted synergistically to promote growth (Nowak et al 2014 ; dos Santos et al 2018 ; Nakano and Wiegertjes 2020 ; Lim et al 2023 ; Salamatullah et al 2024 ). These findings align with previous research in teleost, including enhanced growth in orange swordtail and dwarf tilapia fed rose petal-enriched diets (Joseph et al 2011 ; Pailan et al 2012 ), and improvements observed in marine ornamental fish and goldfish fed natural pigment supplements such as rose or marigold powders (Sinha and Asimi 2007 ; Ezhil et al 2008 ; Ramamoorthy et al 2010 ). Pigmentation enhancement is critical in ornamental aquaculture, where skin color influences consumer perception of quality, health, and value (de Carvalho and Caramujo 2017 ; Luo et al 2021 ; Sathyaruban et al 2021 ). Carotenoid-based pigmentation can be reliably quantified using CIE parameters (L*, a*, b*, chroma, and saturation) and must be supplied through the diet, as fish cannot synthesize carotenoids de novo (Kalinowski et al 2007 ). Once absorbed, carotenoids are transported via lipoproteins and deposited in chromatophores, xanthophores and erythrophores, responsible for yellow and red coloration, respectively (Barman et al 2024 ; Liao et al 2025 ). RP provides β-carotene, lutein, zeaxanthin, flavonoids, and phenolics that may enhance pigment deposition and stability (Wan et al., 2018 , 2019). In this study, RP-40 yielded the greatest increases in redness (a*) and yellowness (b*), confirming a dose-dependent effect. Similar findings were reported in dwarf gourami, with progressive color enhancement observed at increasing RP levels (Pailan et al 2012 ). Oxidative stress, caused by excess ROS, damages lipids, proteins, and DNA (Di Giulio and Meyer 2008 ) (Amenyogbe et al 2024 ). MDA, a by-product of lipid peroxidation, is a widely used oxidative stress marker (Demirci-Cekic et al 2022 ). Organisms counteract ROS via enzymatic antioxidants like SOD and non-enzymatic scavengers such as ABTS activity (Chen et al 2021 ; F. Xu et al 2022 ). In this study, RP supplementation led to dose-dependent increases in ABTS and SOD activities and a corresponding reduction in serum MDA, indicating enhanced systemic antioxidant defense. These findings are consistent with ex vivo studies, where rose byproducts reduced lipid peroxidation in sea bass fillets (Giannakourou et al 2019 ), and in vivo studies, where R. damascena extracts upregulated antioxidant enzymes in rats (Hamza et al 2022 ). The potent radical-scavenging activity observed here supports previous reports of strong antioxidant potential in rose petals (Önder 2023 ), suggesting that RP contributes both direct and enzyme-mediated protection against oxidative stress in goldfish. Dietary inclusion of RP powder elicited a clear, concentration-dependent upregulation of key antioxidant, growth, and immune-related genes, indicating activation of endogenous physiological pathways in goldfish. HSP70 , a molecular chaperone involved in protein refolding under oxidative stress (Sen and Giri 2017 ), was significantly induced only at the highest RP dose (RP-40 vs. RP-0, p < 0.05). This response mirrors findings in pufferfish where dietary astaxanthin upregulated hepatic HSP70 under thermal stress, highlighting the role of carotenoid antioxidants in stress adaptation (Eissa et al 2017 ). Similarly, CYP1A , an enzyme central to xenobiotic metabolism, was significantly elevated in RP-40, with non-significant trends at intermediate doses. Immune gene expression revealed selective activation of pro-inflammatory and innate immune markers. While IL10 and IL1β levels remained unchanged ( p > 0.05), TNFα and LYZ were significantly upregulated at RP-20 and RP-40 ( p < 0.05), indicating that RP stimulates acute immune readiness without inducing chronic inflammatory responses. RP supplementation also influenced the gut microbiota, though effects were modest and individualized. Alpha diversity indices (Shannon, Chao1, Pielou’s evenness, Faith’s PD) showed no significant differences among groups, suggesting the resilience of within-sample microbial diversity to dietary RP under these experimental conditions. This stability is noteworthy given that fish gut diversity is often sensitive to various factors including specific dietary interventions (Rabelo-Ruiz et al 2022 ), environmental stressors like mycotoxins or heavy metals (Zhang et al 2020 ; Spilsbury et al 2022 ), and disease state (Li et al 2017 ). However, PERMANOVA based on Bray–Curtis dissimilarity detected a significant difference in community structure ( p = 0.017), whereas presence/absence (Jaccard) and phylogenetic (UniFrac) metrics, as well as pairwise comparisons, were non-significant after FDR correction. These findings suggest RP primarily induced subtle shifts in the relative abundance of existing taxa. Given that gut beta diversity is influenced by dietary composition(Silva et al 2011 ; Q. Xu et al 2022 ) and may correlate with host phenotypes such as coloration (Ahmed et al 2023 ), the observed compositional shift may reflect a biologically meaningful, though nuanced, response. The high proportion of unclassified taxa (~ 36% at the phylum and ~ 51% at the genus level) and strong inter-individual variability (e.g., samples RP-0 [4] and RP-20 [5]) likely reflect host-specific microbial assemblages and the presence of under-characterized aquatic microbiota (Spilsbury et al 2022 ; Li et al 2023 ). Despite the overall subtlety of the community shift, differential abundance analysis (ANCOM-BC2, q < 0.05) identified several taxa that responded to RP supplementation. Staphylococcus was significantly enriched in the RP-40 group relative to RP-0. Although certain species (e.g., S. warneri ) have been associated with disease in fish (Bunnoy et al 2019 ; Xiao Joe et al 2021 ), Staphylococcus is also part of the normal gut microbiota in healthy goldfish (Silva et al 2011 ) and shrimp. Its enrichment, coinciding with improved growth, pigmentation, and immune-antioxidant gene expression in RP-40, suggests a potentially neutral or even beneficial role in this context. RP-derived phenolic compounds, known to exert antimicrobial activity (Giannakourou et al 2019 ), may have selectively modulated gut microbial composition. Conversely, the depletion of Alloprevotella in RP-5 may reflect changes in fiber-related substrate availability, though its ecological role in fish remains unclear. Additional taxa showing dose-specific changes, including Muribaculaceae , Micrococcaceae , and Chloroplast , further suggest that microbial shifts were responsive to RP concentration. Interestingly, no significant correlations were found between gut microbiota metrics (PCoA axes, key genera) and host parameters (growth, ABTS, SOD, MDA) after FDR correction. This may indicate that functionally important taxa shift, such as those identified by ANCOM-BC2, are more relevant than broader diversity indices, or that host-microbiota relationships in this system are non-linear or indirect. Similar dissociations between microbiota shifts and host phenotypes have been reported, such as in seabream fed Allium-derived supplements (Rabelo-Ruiz et al 2022 ) Nevertheless, the established role of the gut microbiome in modulating fish immunity and metabolism (Butt and Volkoff 2019 ; Xiong et al 2019 ; Spilsbury et al 2022 ) supports the hypothesis that the RP-induced microbial changes may have contributed to the observed physiological improvements. For example, Staphylococcus has been associated with altered cytokine expression in grouper (Xiao Joe et al 2021 ), and other taxa have been linked to antioxidant responses in carp exposed to toxins (Zhang et al 2020 ; Xue et al 2023 ). Furthermore, studies in salmonids have linked gut microbiota composition, including potential carotenoid-associated genera like Bacillaceae , Photobacterium , and Mycoplasma , to pigmentation outcomes (Nguyen et al 2020 ; Ahmed et al 2023 ). While mechanisms remain to be clarified, it is plausible that RP-induced shifts in gut microbiota influenced the absorption, metabolism, or transport of dietary carotenoids, thereby contributing to the increased skin redness (a*) and yellowness (b*) observed in this study. 5. Conclusion Dietary inclusion of rose petal powder at 20–40 g/kg significantly enhanced growth performance, feed efficiency, and skin pigmentation in goldfish. RP supplementation also improved systemic antioxidant capacity, evidenced by increased ABTS and SOD activity and decreased MDA levels. Expression of antioxidant ( HSP70 , CYP1A ), growth ( IGF , TGF ), and immune ( TNFα , LYZ ) genes was upregulated in a dose-dependent manner. Although alpha diversity remained unchanged, RP induced a significant shift in gut microbial community structure. These findings highlight the potential of rose petal byproducts as a sustainable, multifunctional alternative to synthetic additives in ornamental aquaculture, capable of promoting growth, enhancing coloration, and supporting fish health. Declarations Declaration of Competing Interest The authors declare no conflict of interest. Animal ethics All experiments in this study were conducted in accordance with the relevant guidelines and regulations. The experimental protocols were approved by the Institutional Animal Care and Use Committee, Prince of Songkla University (Approval No. AG41/2025). All the procedure followed the ARRIVE guideline. Author Contribution Nutticha Nuntakad: Methodology, Investigation, Conceptualization, Resources. Luu Tang Phuc Khang: Roles/Writing - Original draft, Formal analysis, Data curation, Software. Suwanna Wisetkaew: Methodology, Investigation. Nguyen Dinh-Hung: Writing-Review & Editing, Formal Analysis, Validation. Cao Phuong Thao: Roles/Writing - Original draft, Methodology, Software, Data Analysis. Truong Anh Tu: Roles/Writing - Original draft, Methodology, Software, Data Analysis. Luu Phuc Loi: Roles/Writing - Original draft, Methodology, Software, Validation, Supervision. Papungkorn Sangsawad: Methodology, Investigation, Writing-Review & Editing, Validation. Mintra Seel-audom: Conceptualization, Investigation, Methodology, Writing-Review & Editing, Validation, Formal analysis. Patima Permpoonpatana: Methodology, Investigation, Supervision, Validation, Writing-Review & Editing. Nguyen Vu Linh: Conceptualization, Methodology, Investigation, Roles/Writing - Original draft, Writing-Review & Editing, Data curation, Funding acquisition, and Project administration, Validation, Supervision. Acknowledgement The research was partially supported by Chiang Mai University, Chiang Mai, Thailand. 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Nutr. 17(2): e306-e316. https://doi.org/10.1111/j.1365-2095.2010.00764.x Zhang J, Tian C, Zhu K, Liu Y, Zhao C, Jiang M, Zhu C, Li G (2023) Effects of natural and synthetic astaxanthin on growth, body color, and transcriptome and metabolome profiles in the leopard coralgrouper ( Plectropomus leopardus ). Animals 13(7): 1252. https://doi.org/10.3390/ani13071252 Zhang P, Lu G, Liu J, Yan Z,Wang Y (2020) Toxicological responses of Carassius auratus induced by benzophenone-3 exposure and the association with alteration of gut microbiota. Sci Total Environ 747: 141255. https://doi.org/10.1016/j.scitotenv.2020.141255 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6608516","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":456731926,"identity":"f0d34264-b9b8-4919-b4fb-af7143223a10","order_by":0,"name":"Nutticha Nuntakad","email":"","orcid":"","institution":"Chiang Mai University","correspondingAuthor":false,"prefix":"","firstName":"Nutticha","middleName":"","lastName":"Nuntakad","suffix":""},{"id":456731927,"identity":"5c761b85-a837-42ed-b6d5-62b1d2bf65ed","order_by":1,"name":"Luu Tang Phuc Khang","email":"","orcid":"","institution":"Chiang Mai 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14:50:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":87874,"visible":true,"origin":"","legend":"\u003cp\u003eGrowth performance of goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) after 8 weeks of dietary rose petal supplementation: (A) final weight, (B) specific growth rate, (C) feed conversion ratio, and (D) weight gain\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/2fdd1e4e6dfca74544de6035.jpg"},{"id":82818822,"identity":"eea5ac2f-9bf1-4e5e-bce6-9022a1c44f96","added_by":"auto","created_at":"2025-05-15 14:50:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":63325,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation matrix showing significant correlations (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) among growth performance parameters in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) after 8 weeks. Circle size and color intensity indicate correlation strength and direction (red = positive; blue = negative). Correlation coefficients (r) are shown; non-significant correlations are omitted.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/e66452b7c0196672a99a47d3.jpg"},{"id":82819891,"identity":"86040375-e453-4713-9e3d-5d5c40e85415","added_by":"auto","created_at":"2025-05-15 14:58:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":54969,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation between dietary rose petal concentration and skin pigmentation parameters in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) after 8 weeks: (A) redness (a*), (B) yellowness (b*), and (C) luminosity (L*). Linear regression lines with 95% confidence intervals are shown. Correlation coefficients (r) and \u003cem\u003ep\u003c/em\u003e-values are reported.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/382af6f90dc40edbef7c3a0f.jpg"},{"id":82818826,"identity":"e48df0c1-3c06-4361-ac5d-52104ae99747","added_by":"auto","created_at":"2025-05-15 14:50:22","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":41636,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of 8-week dietary rose petal supplementation on serum antioxidant markers in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e): (A) ABTS radical scavenging activity, (B) superoxide dismutase (SOD) activity, and (C) malondialdehyde (MDA) content. Bars represent mean ± SD; different letters indicate significant differences (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/ee3b127d10cd732052ff332b.jpg"},{"id":82818824,"identity":"5c17f595-e227-49ed-ae81-0f8e34bf5527","added_by":"auto","created_at":"2025-05-15 14:50:22","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":39933,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation between dietary rose petal concentration and serum antioxidant markers in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e): (A) ABTS radical scavenging activity, (B) SOD activity, and (C) MDA content. Linear regression lines with 95% confidence intervals are included. Correlation coefficients (r) and \u003cem\u003ep\u003c/em\u003e-values are shown.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/a84453956ff481695effe0f0.jpg"},{"id":82821555,"identity":"aba6a1be-cf27-42d8-a774-784de784f1bd","added_by":"auto","created_at":"2025-05-15 15:14:22","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":56426,"visible":true,"origin":"","legend":"\u003cp\u003eDose-dependent effects of rose petal supplementation on intestinal mRNA expression of antioxidant (\u003cem\u003eHSP70\u003c/em\u003e, \u003cem\u003eCYP1A\u003c/em\u003e), growth (\u003cem\u003eIGF\u003c/em\u003e, \u003cem\u003eTGF\u003c/em\u003e), and immune-related (\u003cem\u003eLYZ\u003c/em\u003e, \u003cem\u003eTNFα\u003c/em\u003e, \u003cem\u003eIL10\u003c/em\u003e,\u003cem\u003e IL1β\u003c/em\u003e) genes in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) after 8 weeks. Data are expressed as relative transcript levels. Different letters indicate significant differences (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/a05f3edcac5d316d89c61ff4.jpg"},{"id":82819895,"identity":"a99bec85-78bb-4468-bae1-5317be3e317e","added_by":"auto","created_at":"2025-05-15 14:58:22","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":93935,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation between dietary rose petal concentration and intestinal gene expression in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e): (A) HSP70, (B) IGF, (C) TGF, (D) CYP1A, (E) TNFα, (F) LYZ, (G) IL-1β, and (H) IL-10. Linear regression fits and 95% confidence intervals are shown. Correlation coefficients (r) and \u003cem\u003ep\u003c/em\u003e-values are reported.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/18f61b5c11c4b501c554fbf9.jpg"},{"id":82818832,"identity":"5f1db243-54dc-4c51-a8ca-2779c7214f70","added_by":"auto","created_at":"2025-05-15 14:50:22","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":75693,"visible":true,"origin":"","legend":"\u003cp\u003eTotal number of high-quality 16S rRNA gene sequences obtained per sample from goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) gut microbiota across dietary treatments (RP-0, RP-5, RP-10, RP-20, RP-40).\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/38cb91d497e828f7284d484f.jpg"},{"id":82819899,"identity":"46e3ec90-0196-44d5-a861-264d6e344513","added_by":"auto","created_at":"2025-05-15 14:58:22","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":107579,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of dominant bacterial phyla in the gut microbiota of individual goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) after 8 weeks of rose petal supplementation. Each bar represents one sample; phyla are color-coded as indicated in the legend.\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/d218787f62154ebf4379d81d.jpg"},{"id":82819893,"identity":"e4f64132-5025-4fb4-884d-3c9ffd3c1752","added_by":"auto","created_at":"2025-05-15 14:58:22","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":109789,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of dominant bacterial genera in the gut microbiota of individual goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) fed rose petal-supplemented diets. Genera not among the 30 most abundant are grouped as \"Other\". Sequences unclassified at the genus level are labeled \"uncultured unclassified\". Each bar represents one sample; colors correspond to the legend.\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/93e15a5e1ffe1ee9018094f1.jpg"},{"id":82819896,"identity":"314c622d-1e88-4918-a418-0d7edd928d98","added_by":"auto","created_at":"2025-05-15 14:58:22","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":83422,"visible":true,"origin":"","legend":"\u003cp\u003eAlpha diversity indices of the gut microbiota in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) across dietary treatments (RP-0 to RP-40): (A) Shannon entropy, (B) Chao1 richness, (C) Pielou’s evenness, and (D) Faith’s Phylogenetic Diversity. Box plots show median, interquartile range, and outliers. No significant differences were found (Kruskal–Wallis, \u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05 for all).\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/51723841f8a3962c07e2aab5.jpg"},{"id":82821556,"identity":"53b63934-8cae-4731-916f-e80e3b95189a","added_by":"auto","created_at":"2025-05-15 15:14:22","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":47588,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Coordinates Analysis (PCoA) based on Bray–Curtis dissimilarity illustrating gut microbiota composition of goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) after 8 weeks of rose petal supplementation. Each point represents a sample colored by treatment group; convex hulls indicate group dispersion. Variance explained by each axis is shown. PERMANOVA revealed a significant group effect (\u003cem\u003ep\u003c/em\u003e = 0.017).\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/a7015f12cb7bbccce413c9e2.jpg"},{"id":82818835,"identity":"69168674-1867-486f-b70b-541ba9848432","added_by":"auto","created_at":"2025-05-15 14:50:22","extension":"jpg","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":17623,"visible":true,"origin":"","legend":"\u003cp\u003eLog fold change (LFC) of differentially abundant genera (\u003cem\u003eAlloprevotella\u003c/em\u003e sp., \u003cem\u003eStaphylococcus\u003c/em\u003e) in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) gut microbiota relative to the control (RP-0) group after 8 weeks. Significant taxa identified by ANCOM-BC2 (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) are shown. Bars represent estimated LFC; * indicates significance.\u003c/p\u003e","description":"","filename":"13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/35669efa45728a59cad822b1.jpg"},{"id":82820382,"identity":"07b07a44-8ec1-4cfa-a46a-a082b55051d7","added_by":"auto","created_at":"2025-05-15 15:06:22","extension":"jpg","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":31431,"visible":true,"origin":"","legend":"\u003cp\u003eLog fold change (LFC) of differentially abundant genera (\u003cem\u003eChloroplast\u003c/em\u003e, \u003cem\u003eMuribaculaceae\u003c/em\u003e sp., \u003cem\u003eStaphylococcus\u003c/em\u003e) identified in pairwise comparisons between rose petal treatment groups in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e). Bars represent LFC estimates from ANCOM-BC2 analysis; * indicates significance (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"14.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/ff57acd04fa5d2f1b53450f3.jpg"},{"id":83633459,"identity":"e3d1517c-6e63-4938-b000-6730627c2b60","added_by":"auto","created_at":"2025-05-29 21:16:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2337459,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6608516/v1/8ee092f5-2fdb-4478-9ed0-01adb2dd5985.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dietary Supplementation with Rosa rubiginosa petal as a Natural Feed Additive Modulates Growth Performance, Skin Pigmentation, Immunity, and Gut Health in Goldfish (Carassius auratus)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe ornamental fish trade has gained significant popularity in recent years, driven by the high aesthetic and commercial value of many species in the international market. Several ornamental fish are prized for their vivid coloration, diverse body shapes, and distinctive fin structures (Lau et al \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Among these, the goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) is one of the most famous and commercially valuable species (Yanar et al \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Goldfish have become widespread, with numerous farms and hatcheries established globally (Ota \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Their natural beauty and adaptability to a wide range of environmental conditions have contributed to their prominence in the ornamental fish industry (Martinez-Murcia et al \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Blanco and Unniappan \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eColoration in goldfish is primarily determined by the distribution and type of pigment cells (Luo et al \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In teleosts, six types of pigment cells have been identified: cyanophores, leucophores, iridophores, xanthophores, and melanophores (Goda et al \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Zhang et al \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Variations in pigment cell types across different body regions lead to diverse color patterns. High carotenoid content, in particular, contributes to the distinctive red coloration of goldfish, enhancing their marketability and consumer acceptance (G\u0026uuml;m\u0026uuml;ş et al \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Elshafey et al \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consequently, maintaining vibrant natural pigmentation is critical for market demand and commercial success among fish farmers.\u003c/p\u003e \u003cp\u003eIn recent years, there has been growing interest in using natural plant-based ingredients such as leaves, fruit peels, and flowers to enhance pigmentation in ornamental fish (Elshafey et al \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Successful intensive aquaculture requires nutritionally balanced diets that include essential nutrients and carotenoids as dietary supplements (Ahilan et al \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Beyond pigmentation, carotenoids are also essential for growth, metabolism, reproduction, and overall health in goldfish (Ahilan et al \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Hilal and Duygu \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sathyaruban et al \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kautsar et al \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Elshafey et al \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Khieokhajonkhet et al \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Like other animals, fish cannot synthesize carotenoids de novo and must acquire them through their diet (Elshafey et al \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition to carotenoids, dietary sources of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are critical for the growth and survival of goldfish, as they cannot biosynthesize these essential fatty acids from shorter-chain precursors (G\u0026uuml;m\u0026uuml;ş et al \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The level of dietary carotenoid intake directly influences pigmentation intensity in fish (Sathyaruban et al \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, a wide range of carotenoid sources has been incorporated into aquafeeds, including pure carotenoid extracts (Shahidi and Brown \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Yuangsoi et al \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), animal-derived pigments (Swain et al \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lim et al \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and plant-derived pigments (Wallat et al \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Harpaz and Padowicz \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Wagde et al \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rana et al \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Plant-based sources offer dual advantages by providing essential nutrients (e.g., proteins, fats, vitamins) along with high carotenoid content (Ansari et al \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Given concerns regarding the cost and safety of synthetic additives, there is an increasing trend toward the use of natural carotenoids as alternatives in aquaculture (Elshafey et al \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Roses are recognized as rich natural sources of carotenoids (Wan et al \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and species such as China rose (\u003cem\u003eHibiscus rosa-sinensis\u003c/em\u003e), sweetbriar rose (\u003cem\u003eRosa rubiginosa\u003c/em\u003e), and cyme rose (\u003cem\u003eRosa indica\u003c/em\u003e) have been utilized in fish diets to promote growth, enhance immune function, and improve pigmentation (Sinha and Asimi \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Joseph et al \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Arulvasu et al \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Rintan et al \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These findings underscore the potential of natural carotenoid supplementation to enhance ornamental fish health and marketability.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eDespite these promising outcomes, research specifically examining the effects of rose petal by-products as carotenoid sources in ornamental fish, particularly in goldfish, remains limited. This study seeks to address this knowledge gap by evaluating the effects of rose petal-derived carotenoids on key health indicators in goldfish, including growth performance, immune response, gut microbiota composition, and gene expression.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Fish preparation and experimental design\u003c/h2\u003e \u003cp\u003eHealthy goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) were obtained from a commercial farm in Chiang Mai Province, Thailand, and transported to the aquaculture research station at the Department of Animal and Aquatic Sciences, Faculty of Agriculture, Chiang Mai University. Upon arrival, fish were acclimated for 14 days in aerated tanks and fed a commercial pelleted diet containing 400 g/kg crude protein, 70 g/kg lipid, and 40 g/kg fiber, administered manually three times daily until apparent satiation (Khieokhajonkhet et al \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Prior to the feeding trial, all fish were fasted for 24 hours to standardize gastrointestinal clearance and metabolic conditions.\u003c/p\u003e \u003cp\u003eFollowing acclimation, 300 fish with an initial average body weight of 6.75\u0026ndash;6.90 g was randomly assigned to 15 experimental tanks (50 \u0026times; 100 \u0026times; 40 cm; 180 L water volume), corresponding to five dietary treatment groups with three replicates each. Fish were fed experimental diets twice daily at a rate of 3% body weight, adjusted weekly based on biomass measurements, for 8 weeks. Uneaten feed and waste were siphoned daily, and approximately 10% of the water was replaced with fresh dechlorinated tap water to maintain optimal conditions. Environmental parameters were closely monitored to reduce stress and mimic natural conditions. Tanks were exposed to a 12 h light/12 h dark photoperiod. Water temperature was maintained at 24\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C, dissolved oxygen levels\u0026thinsp;\u0026gt;\u0026thinsp;5 mg/L, pH between 7.5\u0026ndash;8.0, and ammonium concentrations below 1 mg/L.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Preparation of experimental diets\u003c/h2\u003e \u003cp\u003eFive experimental diets were formulated by replacing fish meal with rose petal (RP) meal at inclusion levels of 0, 5, 10, 20, and 40 g/kg, designated as RP0, RP5, RP10, RP20, and RP40, respectively. All dry ingredients were sieved through a 250 \u0026micro;m mesh to ensure uniform particle size. Ingredients were then accurately weighed according to the formulation in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and homogenized in a mechanical mixer for 10 minutes to achieve a consistent blend (Linh et al \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFormulation of experimental diets containing graded levels of rose petal (RP) powder (g/kg dry matter basis).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIngredients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eRose petal concentration (g/kg diet)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRP-0 (control)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRP-5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRP-10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRP-20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRP-40\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFish meal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoybean meal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorn meal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRice bran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheat flour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed yeast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLecithin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethionine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLysine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBinder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoybean oil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRose petal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePremix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin C 98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProximate (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude lipid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrogen-free extract\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe mixtures were pelleted using a 2 mm diameter mincer, selected to match the oro-pharyngeal dimensions of juvenile goldfish and facilitate optimal feed intake while reducing waste. The pellets were dried at 50\u0026deg;C overnight in a hot-air oven and subsequently stored in airtight polyethylene bags at 4\u0026deg;C until use in feeding trials and proximate composition analysis.\u003c/p\u003e \u003cp\u003eProximate composition of the diets was determined following the Association of Official Analytical Chemists (AOAC 2016), standard procedures. Moisture content was assessed gravimetrically by drying triplicate samples at 105\u0026deg;C to constant weight using a Memmert UL50 incubator. Ash content was measured by incineration at 550\u0026deg;C for 8 hours in a Carbolite ELF 11/14 muffle furnace. Crude lipid content was determined via Soxhlet extraction with petroleum ether using a Gerhardt apparatus. Crude protein was analyzed using the Kjeldahl method (N \u0026times; 6.25) with a semi-automatic Gerhardt Vapodest 45s system. All analyses were performed in triplicate to ensure accuracy and reproducibility.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Growth performance parameters\u003c/h2\u003e \u003cp\u003eFish were batch-weighed biweekly using a KERN analytical balance to monitor growth performance. After weighing, fish were promptly returned to their respective tanks to minimize handling stress. Growth performance indicators, including weight gain (WG), percent weight gain (PWG), specific growth rate (SGR), daily weight gain (DWG), feed conversion ratio (FCR), and survival rate (SR), were calculated using standard equations (LinhLubis et al \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; LinhWannavijit et al \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e):\u003c/p\u003e \u003cp\u003eSurvival rate (SR, %) = (Final number of fish / Initial number of fish) \u0026times; 100\u003c/p\u003e \u003cp\u003eWeight gain (WG)\u0026thinsp;=\u0026thinsp;Final body weight\u0026thinsp;\u0026minus;\u0026thinsp;Initial body weight\u003c/p\u003e \u003cp\u003ePercent weight gain (PWG, %) = [(Final body weight\u0026thinsp;\u0026minus;\u0026thinsp;Initial body weight) / Initial body weight] \u0026times; 100\u003c/p\u003e \u003cp\u003eSpecific growth rate (SGR, %/day) = [(ln Final body weight\u0026thinsp;\u0026minus;\u0026thinsp;ln Initial body weight) / Culture days] \u0026times; 100\u003c/p\u003e \u003cp\u003eDaily weight gain (DWG, g/day) = (Final body weight\u0026thinsp;\u0026minus;\u0026thinsp;Initial body weight) / Culture days\u003c/p\u003e \u003cp\u003eFeed conversion ratio (FCR)\u0026thinsp;=\u0026thinsp;Total dry feed intake / Live weight gain\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Skin color measurement\u003c/h2\u003e \u003cp\u003eTo assess the effects of dietary treatments on skin pigmentation, five fish per tank were randomly netted and photographed at week 8 under standardized lighting conditions using a Panasonic digital camera (Panasonic, Japan). Immediately afterward, fish were gently blotted to remove excess moisture and subjected to colorimetric analysis before group weighing, thereby minimizing pigment distortion due to handling stress.\u003c/p\u003e \u003cp\u003eSkin color measurements were conducted on the left side of the head using a HunterLab MiniScan EZ 4500 L spectrocolorimeter (Hunter Associates, USA). The instrument was calibrated against standard black and white tiles according to the guidelines of the International Commission on Illumination (CIE 1976), prior to data collection. For each fish, three replicates of CIELAB color values were recorded: L* (lightness), a* (red\u0026ndash;green axis), and b* (yellow\u0026ndash;blue axis). In this system, L* values range from 0 (black) to 100 (white), a* values from negative (green) to positive (red), and b* values from negative (blue) to positive (yellow) (Hunter and Harold \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1987\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Blood biochemical analysis\u003c/h2\u003e \u003cp\u003ePrior to biochemical analysis, six fish were randomly selected from each dietary treatment group. Blood was collected from the caudal vein using a heparinized 1 mL syringe and immediately transferred to enzyme-free 1.5 mL centrifuge tubes to prevent coagulation. Samples were centrifuged at 3,000 rpm for 10 minutes at 4\u0026deg;C to separate serum, which was carefully pipetted into clean microtubes and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until analysis.\u003c/p\u003e \u003cp\u003eSerum antioxidant capacity was assessed using the ABTS radical scavenging assay as described by Boonkong et al (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Briefly, 10 \u0026micro;L of thawed serum was mixed with deionized water and ABTS working solution, incubated in the dark for 10 minutes, and absorbance was measured at 734 nm. Radical scavenging activity (%) was calculated using a standard inhibition formula.\u003c/p\u003e \u003cp\u003eSuperoxide dismutase (SOD) activity was measured using a commercial assay kit (CS0009, Sigma-Aldrich) following the protocol of Li et al (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Samples were incubated with kit reagents, and absorbance was recorded at 450 nm using a Varioskan LUX microplate reader (Thermo Scientific, Vantaa, Finland).\u003c/p\u003e \u003cp\u003eLipid peroxidation was evaluated by measuring malondialdehyde (MDA) levels using an MDA assay kit (KTB1050, Abbkine). Serum samples were reacted with thiobarbituric acid to form MDA\u0026ndash;TBA complexes, and absorbance was measured at 532 nm. Nonspecific turbidity was corrected by subtracting absorbance at 600 nm, following the method of Karatas and EM (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Intestinal gene expression assays\u003c/h2\u003e \u003cp\u003eTo evaluate transcriptional responses of immune-related and antioxidant genes, six fish from each dietary group were anesthetized, and approximately 50 mg of mid-intestinal tissue was aseptically excised. Tissue samples were immediately immersed in 200 \u0026micro;L of TRIzol\u0026trade; reagent (Invitrogen\u0026trade;, USA) in sterile microcentrifuge tubes and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until RNA extraction.\u003c/p\u003e \u003cp\u003eUpon thawing, samples were homogenized using a Bullet Blender\u0026reg; Homogenizer to ensure complete cellular disruption. Total RNA was extracted following the TRIzol\u0026trade; protocol, and the aqueous phase was further purified using a Total RNA Extraction Kit (Omega Bio-tek, USA). RNA concentration and purity were assessed using a NanoDrop\u0026trade; One/OneC spectrophotometer (Thermo Fisher Scientific, USA), and only samples with an A260/280 ratio between 1.8 and 2.0 were used for downstream applications.\u003c/p\u003e \u003cp\u003eComplementary DNA (cDNA) was synthesized from 1 \u0026micro;g of total RNA using a commercial reverse transcription kit (Bio-Rad, USA), following the manufacturer\u0026rsquo;s thermal cycling protocol. Quantitative real-time PCR (qRT-PCR) was then conducted using the CFX Connect\u0026trade; Real-Time PCR Detection System (Bio-Rad, USA) in a 20 \u0026micro;L reaction volume, as described in previous studies (Linh et al \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sintuprom et al \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Each reaction contained 1 \u0026micro;L of cDNA (100 ng), 0.4 \u0026micro;L of each gene-specific primer (10 \u0026micro;M), 10 \u0026micro;L of 2\u0026times; iTaq\u0026trade; Universal SYBR\u0026reg; Green Supermix (Bio-Rad, USA), and nuclease-free water to reach the final volume. The thermal cycling protocol included an initial denaturation at 95\u0026deg;C for 30 seconds, followed by 40 cycles of denaturation at 95\u0026deg;C for 15 seconds and annealing/extension at 60\u0026deg;C for 30 seconds. A melt curve analysis (95\u0026deg;C for 15 seconds, 60\u0026deg;C for 60 seconds, and 95\u0026deg;C for 15 seconds) was performed to verify amplification specificity. Relative gene expression levels were calculated using the 2\u003csup\u003e\u0026ndash;ΔΔct\u003c/sup\u003e method (Livak and Schmittgen (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), with \u003cem\u003eActin‑2\u003c/em\u003e serving as the internal reference gene (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGene-specific primers used for quantitative real-time PCR (qPCR) analysis in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTarget gene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSequence (5\u0026prime;\u0026ndash;3\u0026prime;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGenebank accession number\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eβ-actin 2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGCTGACCGTATGCAGAAAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAB039726.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReversed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGAGAGGTTTGGGTTGGTC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIL-1B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTTCATTTGAAGGCAGTGACG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAJ249136.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReversed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTAAGCTGTGCCCGTCTCTTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIL-10\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAAGGAGCTCCGTTCTGCAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHQ259106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReversed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCGAGTAATGGTGCCAAGTCATCA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTNF α\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCATTCCTTACGACGGCATTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEU069818.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReversed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAGTCACGTCAGCCTTGCAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTGF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACCATATGCCAAAGCCTCAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEU086521.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReversed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGATGCCTATACAGCGCAAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIGF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAGGGGCATTGGTGTGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGU583648\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReversed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGCAGCGTGTCTACAAGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP1A\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCACCGACTCGCTCATCAAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDQ517445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReversed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTTCAGCTCTGTACCGTCTGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLYZ\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGCCGGAAATGTCCTGAATAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKR092198.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReversed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGTGGTCCTGGCATCGATATT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHPS70\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGCAGAAGGTGACAAATGCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eJN544930.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReversed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGGGCTCGTTGATGTTCTCA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Gut microbiome analysis\u003c/h2\u003e \u003cp\u003eAt the end of the 8-week feeding trial, six fish per dietary group were randomly selected for gut microbiota analysis. Fish were euthanized, and the posterior intestine was aseptically excised. Samples were immediately stored at \u0026minus;\u0026thinsp;80\u0026deg;C until DNA extraction. Microbial genomic DNA was extracted using the QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany) following the manufacturer's protocol. The V3\u0026ndash;V4 hypervariable regions of the 16S rRNA gene were amplified using primers 341F (5\u0026prime;-CCTAYGGGRBGCASCAG-3\u0026prime;) and 806R (5\u0026prime;-GGACTACNNGGGTATCTAAT-3\u0026prime;). PCR products were processed for library preparation and paired-end sequenced on an Illumina MiSeq platform by Macrogen Inc. (Seoul, Republic of Korea). Raw reads were processed using the QIIME 2 pipeline (v2022.2) (Bolyen et al \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). After quality assessment, adapter trimming, and read filtering, denoising, merging of paired-end reads, and chimera removal were conducted using DADA2 (Callahan et al \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) to generate amplicon sequence variants (ASVs). Taxonomic classification was performed using a Naive Bayes classifier trained on the SILVA database (v138, 99% similarity) (Quast et al \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Phylogenetic trees were constructed using MAFFT for alignment (Katoh and Standley 2013) and FastTree 2 for tree inference (Price et al \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDownstream analyses and visualization were conducted in R (v4.4.3; R Core Team, 2024) using QIIME 2-exported data and the \u003cem\u003ephyloseq\u003c/em\u003e (v1.48.0) (McMurdie and Holmes \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and \u003cem\u003evegan\u003c/em\u003e (v2.6.8) (Oksanen et al \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) packages. Alpha diversity was assessed using Shannon entropy, Pielou's evenness, Chao1 richness, and Faith\u0026rsquo;s phylogenetic diversity (PD), with group differences tested via Kruskal\u0026ndash;Wallis tests. Beta diversity was calculated using Bray\u0026ndash;Curtis dissimilarity, Jaccard distance, and weighted/unweighted UniFrac distances, with community structures visualized using Principal Coordinates Analysis (PCoA). Group differences were statistically evaluated using PERMANOVA with 999 permutations (QIIME 2 \u003cem\u003ebeta-group-significance\u003c/em\u003e), and pairwise p-values were adjusted using the False Discovery Rate (FDR) method. Differential abundance between groups was assessed using ANCOM-BC (v2.6.0) (Lin and Peddada \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) applying a pseudo-count and Holm correction, with a significance threshold of q\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Spearman\u0026rsquo;s rank correlation was used to examine associations between microbial ASV abundances (log1p-transformed after total sum scaling) and host growth parameters using the \u003cem\u003eHmisc\u003c/em\u003e package (v5.2.3) (Harrell and Dupont \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), with FDR-adjusted significance at q\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Data visualization was performed using \u003cem\u003eggplot2\u003c/em\u003e (v3.5.2) (Wickham and Sievert \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).Unless otherwise stated, statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 or q\u0026thinsp;\u0026lt;\u0026thinsp;0.05, as appropriate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Data analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using OriginPro (v2021b, OriginLab Corporation, Northampton, MA, USA) and IBM SPSS Statistics (v29.0.2.0, IBM Corp., Armonk, NY, USA). Data normality was assessed using both the Kolmogorov\u0026ndash;Smirnov and Shapiro\u0026ndash;Wilk tests, while Levene\u0026rsquo;s test was used to evaluate homogeneity of variances. For datasets meeting assumptions of normality and homogeneity, one-way analysis of variance (ANOVA) was employed to analyze growth performance, skin pigmentation, serum biochemical parameters, and gene expression data. Duncan\u0026rsquo;s multiple range test was used for post hoc comparisons to identify significant differences among treatment means. When assumptions were not met, non-parametric alternatives such as the Kruskal\u0026ndash;Wallis test were applied, followed by Dunn\u0026rsquo;s post hoc test with Bonferroni correction where applicable. Pearson\u0026rsquo;s and Spearman\u0026rsquo;s correlation coefficients were calculated to assess relationships among growth performance, antioxidant activities, gene expression, and gut microbiota composition. All results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Growth performance, feed utilization, and survival\u003c/h2\u003e \u003cp\u003eGrowth performance, feed utilization, and survival of koi carp fed RP-supplemented diets were evaluated at weeks 4 and 8 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Survival remained high across all groups, with no significant mortality observed in RP-0 to RP-20 (96.7\u0026ndash;98.3%) and complete survival (100%) in the RP-40 group, indicating that dietary inclusion of RP up to 40 g/kg did not compromise fish viability.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of dietary rose petal supplementation on survival rate, growth performance, and feed conversion ratio of goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) at weeks 4 and 8.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRP-0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRP-5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRP-10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRP-20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRP-40\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial weight (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeek 4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurvival rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.67\u0026thinsp;\u0026plusmn;\u0026thinsp;5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinal weight (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight gain (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercent weight gain (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.88\u0026thinsp;\u0026plusmn;\u0026thinsp;6.97\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.30\u0026thinsp;\u0026plusmn;\u0026thinsp;7.97\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.83\u0026thinsp;\u0026plusmn;\u0026thinsp;3.19\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e109.96\u0026thinsp;\u0026plusmn;\u0026thinsp;5.87\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage specific growth rate (%.day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily weight gain (g.day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeek 8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurvival rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.67\u0026thinsp;\u0026plusmn;\u0026thinsp;5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinal weight (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight gain (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercent weight gain (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160.82\u0026thinsp;\u0026plusmn;\u0026thinsp;6.24\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e163.09\u0026thinsp;\u0026plusmn;\u0026thinsp;14.55\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172.09\u0026thinsp;\u0026plusmn;\u0026thinsp;7.87\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e172.98\u0026thinsp;\u0026plusmn;\u0026thinsp;7.75\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e193.97\u0026thinsp;\u0026plusmn;\u0026thinsp;9.71\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercentage specific growth rate (%.day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily weight gain (g.day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Different letters within a row indicate significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e \u003c/p\u003e \u003cp\u003eBy week 4, fish fed the RP-40 diet showed significantly higher FW, WG, and PWG compared to RP-0 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while RP-5 to RP-20 groups showed only marginal, non-significant improvements. DWG in RP-40 (0.27 g/day) was ~\u0026thinsp;18% higher than in other groups. Although SGR showed a supplementation-related increase, it was not statistically significant at this stage.\u003c/p\u003e \u003cp\u003eAt week 8, the growth-promoting effect of high RP supplementation became more pronounced. RP-40-fed fish had significantly greater FW, WG, and PWG than RP-0 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while RP-5 to RP-20 yielded moderate but non-significant improvements. SGR continued to exhibit a dose-dependent increase, though the differences remained statistically non-significant. FCR was unaffected by RP inclusion and remained stable across treatments (week 4: 0.88\u0026ndash;0.91; week 8: 3.14\u0026ndash;3.71), suggesting that improved growth was not associated with reduced feed efficiency.\u003c/p\u003e \u003cp\u003eRegression analysis revealed strong linear relationships between RP inclusion level and performance metrics (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e): FW increased from 17.8 g (RP-0) to 20.2 g (RP-40; Adj. R\u0026sup2; = 0.70), SGR from 3.19%/day to 3.72%/day (Adj. R\u0026sup2; = 0.69), FCR decreased from 3.71 to 3.29 (Adj. R\u0026sup2; = 0.70), and WG increased from 11.0 g to 13.8 g (Adj. R\u0026sup2; = 0.77).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCorrelation analysis among growth parameters showed strong positive associations between FW, WG, PWG, DWG, and SGR (r\u0026thinsp;=\u0026thinsp;0.98\u0026ndash;1.00, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating consistent trends in weight-based growth indices (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In contrast, FCR was significantly negatively correlated with these parameters (r = \u0026minus;\u0026thinsp;0.57 to \u0026minus;\u0026thinsp;0.62, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), reflecting its inverse relationship with growth efficiency. Survival rate showed no significant correlation with other variables (r\u0026thinsp;=\u0026thinsp;0.00, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Skin pigmentation\u003c/h2\u003e \u003cp\u003eAfter 60 days of feeding, skin color parameters (L*, a*, b*) were measured to evaluate the effects of dietary RP supplementation (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Skin lightness (L*) showed no significant differences among treatment groups, with values ranging from 61.10\u0026thinsp;\u0026plusmn;\u0026thinsp;14.99 to 66.35\u0026thinsp;\u0026plusmn;\u0026thinsp;13.00 (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), and no significant correlation was observed between L* values and RP concentration (r\u0026thinsp;=\u0026thinsp;0.12, p\u0026thinsp;=\u0026thinsp;0.072; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffects of dietary rose petal supplementation on skin color parameters, luminosity (L*), redness (a*), and yellowness (b*), in goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) after 8 weeks.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eRose petal dietary (g/kg)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRP-0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRP-5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRP-10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRP-20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRP-40\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLuminosity (L*)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.10\u0026thinsp;\u0026plusmn;\u0026thinsp;14.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.72\u0026thinsp;\u0026plusmn;\u0026thinsp;12.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.38\u0026thinsp;\u0026plusmn;\u0026thinsp;14.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.63\u0026thinsp;\u0026plusmn;\u0026thinsp;11.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66.35\u0026thinsp;\u0026plusmn;\u0026thinsp;13.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRedness (a*)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.54\u0026thinsp;\u0026plusmn;\u0026thinsp;7.02\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.11\u0026thinsp;\u0026plusmn;\u0026thinsp;5.82\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.61\u0026thinsp;\u0026plusmn;\u0026thinsp;7.32\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.69\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.14\u0026thinsp;\u0026plusmn;\u0026thinsp;6.58\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYellowness (b*)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.32\u0026thinsp;\u0026plusmn;\u0026thinsp;14.04\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.02\u0026thinsp;\u0026plusmn;\u0026thinsp;13.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.44\u0026thinsp;\u0026plusmn;\u0026thinsp;14.46\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.84\u0026thinsp;\u0026plusmn;\u0026thinsp;10.07\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47.73\u0026thinsp;\u0026plusmn;\u0026thinsp;11.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Different letters within a row indicate significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/em\u003e \u003c/p\u003e \u003cp\u003eIn contrast, skin redness (a*) increased significantly in a dose-dependent manner. Fish fed the RP-20 (25.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.69) and RP-40 (26.14\u0026thinsp;\u0026plusmn;\u0026thinsp;6.58) diets had significantly higher a* values compared to the RP-0 group (20.54\u0026thinsp;\u0026plusmn;\u0026thinsp;7.02) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This trend was supported by a significant positive correlation between RP concentration and a* values (r\u0026thinsp;=\u0026thinsp;0.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eSimilarly, skin yellowness (b*) was significantly enhanced at the highest supplementation level. The RP-40 group (47.73\u0026thinsp;\u0026plusmn;\u0026thinsp;11.08) exhibited significantly higher b* values than the RP-0 group (40.32\u0026thinsp;\u0026plusmn;\u0026thinsp;14.04) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with a corresponding positive correlation between RP concentration and b* values (r\u0026thinsp;=\u0026thinsp;0.18, p\u0026thinsp;=\u0026thinsp;0.0077; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Antioxidant capacity and oxidative stress markers\u003c/h2\u003e \u003cp\u003eDietary RP supplementation significantly influenced serum antioxidant capacity and oxidative stress markers in goldfish (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Antioxidant capacity, measured by ABTS radical scavenging activity, increased progressively with rising RP levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Fish fed RP-20 and RP-40 diets exhibited significantly higher ABTS activity than the RP-0 group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with a strong positive correlation observed between RP concentration and ABTS activity (r\u0026thinsp;=\u0026thinsp;0.57, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSimilarly, superoxide dismutase (SOD) activity showed a dose-dependent increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). While no significant differences were observed at lower RP levels (RP-5, RP-10), SOD activity in the RP-40 group was significantly higher than in RP-0 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This was supported by a strong positive correlation between RP concentration and SOD activity (r\u0026thinsp;=\u0026thinsp;0.69, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eConversely, lipid peroxidation, indicated by malondialdehyde (MDA) content, declined with increasing RP inclusion (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Fish in the RP-40 group exhibited significantly lower serum MDA levels compared to RP-0 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A significant negative correlation was also observed between RP concentration and MDA levels (r = \u0026minus;\u0026thinsp;0.38, p\u0026thinsp;=\u0026thinsp;0.037; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Intestinal expression of antioxidant, growth, and immune‑related genes\u003c/h2\u003e \u003cp\u003eDietary RP supplementation modulated the expression of multiple genes related to antioxidant defense, growth, and immune function in goldfish (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong antioxidant-related genes, \u003cem\u003eHSP70\u003c/em\u003e expression remained unchanged at lower RP levels but was significantly upregulated in the RP-40 group compared to RP-0 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eCYP1A\u003c/em\u003e followed a similar trend, with moderate increases at RP-10 and RP-20 (not statistically significant), and a significant peak at RP-40 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Both genes showed strong positive correlations with RP concentration (\u003cem\u003eHSP70\u003c/em\u003e: r\u0026thinsp;=\u0026thinsp;0.68, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; \u003cem\u003eCYP1A\u003c/em\u003e: r\u0026thinsp;=\u0026thinsp;0.61, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA, D).\u003c/p\u003e \u003cp\u003eGrowth-related transcripts were also significantly affected. \u003cem\u003eIGF\u003c/em\u003e expression increased progressively from RP-5 to RP-40, reaching significance in RP-20 and RP-40 compared to RP-0 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eTGF\u003c/em\u003e showed a similar pattern, with significant upregulation at RP-20 and RP-40 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Both genes exhibited strong positive correlations with RP inclusion (\u003cem\u003eIGF\u003c/em\u003e: r\u0026thinsp;=\u0026thinsp;0.69, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; \u003cem\u003eTGF\u003c/em\u003e: r\u0026thinsp;=\u0026thinsp;0.77, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, C).\u003c/p\u003e \u003cp\u003eImmune-related genes also responded positively to RP supplementation. \u003cem\u003eLYZ\u003c/em\u003e expression increased in a dose-dependent manner, with significantly higher levels in RP-20 and RP-40 compared to RP-0 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eTNFα\u003c/em\u003e was significantly elevated from RP-10 onward, reaching its highest expression at RP-40 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Both genes showed strong positive correlations with RP concentration (\u003cem\u003eLYZ\u003c/em\u003e: r\u0026thinsp;=\u0026thinsp;0.92, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; \u003cem\u003eTNFα\u003c/em\u003e: r\u0026thinsp;=\u0026thinsp;0.83, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE, F).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn contrast, expression of the anti-inflammatory cytokines \u003cem\u003eIL10\u003c/em\u003e and \u003cem\u003eIL1β\u003c/em\u003e remained unchanged across treatments (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), with no significant correlations with RP concentration (\u003cem\u003eIL10\u003c/em\u003e: p\u0026thinsp;=\u0026thinsp;0.689; \u003cem\u003eIL1β\u003c/em\u003e: p\u0026thinsp;=\u0026thinsp;0.437; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG, H).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5. 16S rRNA sequencing and ASV characterization\u003c/h2\u003e \u003cp\u003eHigh-throughput sequencing of the 16S rRNA gene V3\u0026ndash;V4 region produced a total of 522,700 high-quality reads across 15 samples following quality filtering, with an average read length of 246 bp. Processing via the DADA2 pipeline yielded 8,525 unique Amplicon Sequence Variants (ASVs) across all samples.\u003c/p\u003e \u003cp\u003ePer-sample read counts ranged from 26,712 to 43,898, with a mean of 34,847 reads. The number of observed ASVs per sample ranged from 208 to 890, averaging approximately 626 ASVs. The distribution of total read counts across dietary treatments (RP-0, RP-5, RP-10, RP-20, RP-40) is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Gut microbiota composition\u003c/h2\u003e \u003cp\u003e16S rRNA gene sequencing revealed diverse gut microbial communities across all treatment groups, with notable inter-sample variation, particularly in RP-0 (4) and RP-20 (5), which exhibited distinct taxonomic profiles (Figs.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and \u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt the phylum level, \u003cem\u003eProteobacteria\u003c/em\u003e was most abundant (~\u0026thinsp;21.0%), followed by \u003cem\u003eFirmicutes\u003c/em\u003e (10.3%), \u003cem\u003eActinobacteriota\u003c/em\u003e (9.7%), \u003cem\u003eBacteroidota\u003c/em\u003e (7.9%), and \u003cem\u003eCyanobacteria\u003c/em\u003e (5.1%), while unclassified taxa accounted for ~\u0026thinsp;35.8% of sequences. Sample RP-0 (4) showed elevated \u003cem\u003eProteobacteria\u003c/em\u003e (~\u0026thinsp;40%), unlike other RP-0 replicates with higher unclassified taxa and lower \u003cem\u003eProteobacteria\u003c/em\u003e. Similarly, RP-20 (5) was dominated by \u003cem\u003eProteobacteria\u003c/em\u003e (~\u0026thinsp;49%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAt the genus level, \u003cem\u003eChloroplast\u003c/em\u003e (~\u0026thinsp;4.7%) and \u003cem\u003eEscherichia-Shigella\u003c/em\u003e (~\u0026thinsp;3.8%) were among the most abundant classified genera, though unclassified genera (~\u0026thinsp;50.8%) and low-abundance \"Other\" taxa (~\u0026thinsp;20.7%) comprised the majority. RP-0 (4) was dominated by \u003cem\u003eEscherichia-Shigella\u003c/em\u003e (\u0026gt;\u0026thinsp;33%), while RP-20 (5) showed elevated \u003cem\u003eAeromonas\u003c/em\u003e (~\u0026thinsp;4.6%). Other genera like \u003cem\u003eMethyloversatilis\u003c/em\u003e, \u003cem\u003eVibrio\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e, and \u003cem\u003eMuribaculaceae\u003c/em\u003e were present at low levels. Overall, the gut microbiota showed high diversity with distinct compositional outliers.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Microbial diversity\u003c/h2\u003e \u003cp\u003eAlpha diversity, assessed using Shannon entropy, Pielou\u0026rsquo;s evenness, Chao1 richness, and Faith\u0026rsquo;s Phylogenetic Diversity (PD), showed no significant differences among dietary groups (Kruskal\u0026ndash;Wallis test, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). Specifically, Shannon (p\u0026thinsp;\u0026asymp;\u0026thinsp;0.60), Chao1 (p\u0026thinsp;\u0026asymp;\u0026thinsp;0.52), Pielou\u0026rsquo;s evenness (p\u0026thinsp;\u0026asymp;\u0026thinsp;0.57), and Faith\u0026rsquo;s PD (p\u0026thinsp;\u0026asymp;\u0026thinsp;0.23) all indicated comparable within-sample diversity across treatments. Although exploratory pairwise comparisons for Faith\u0026rsquo;s PD (RP-0 vs RP-10; RP-0 vs RP-40) yielded unadjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, these were not significant after FDR correction (q\u0026thinsp;\u0026asymp;\u0026thinsp;0.25). Visual inspection showed substantial overlap among groups, and previously noted outlier samples (RP-0 [4], RP-20 [5]) did not differ markedly in alpha diversity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBeta diversity analysis using Principal Coordinates Analysis (PCoA) based on Bray\u0026ndash;Curtis dissimilarity revealed partial separation among groups, particularly between RP-10/RP-20 and the remaining treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e). The first two axes explained 14.33% and 9.51% of the total variance. PERMANOVA confirmed significant differences in community composition among groups (Pseudo-F\u0026thinsp;=\u0026thinsp;1.13, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017), though post hoc pairwise comparisons were non-significant after multiple testing correction (all \u003cem\u003eq\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Analyses using Jaccard and UniFrac distances also yielded non-significant results (data not shown), suggesting the Bray\u0026ndash;Curtis significance stemmed from subtle shifts in relative taxon abundances rather than major compositional restructuring.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.8. Differential abundance of gut microbiota\u003c/h2\u003e \u003cp\u003eDifferentially abundant taxa across treatment groups were identified using ANCOM-BC2 with Holm-adjusted p-values (threshold: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Two taxa showed significant differences relative to the control (RP-0) group (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e): \u003cem\u003eStaphylococcus\u003c/em\u003e (phylum \u003cem\u003eFirmicutes\u003c/em\u003e) was significantly enriched in RP-40 (LFC\u0026thinsp;\u0026asymp;\u0026thinsp;5.22, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while an uncultured \u003cem\u003eAlloprevotella\u003c/em\u003e species (phylum \u003cem\u003eBacteroidota\u003c/em\u003e) was significantly depleted in RP-5 (LFC \u0026asymp; \u0026minus;\u0026thinsp;6.85, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No other taxa differed significantly from RP-0.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePairwise comparisons among RP-treated groups revealed four additional differentially abundant taxa (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e). \u003cem\u003eStaphylococcus\u003c/em\u003e abundance was higher in RP-40 than RP-20 and lower in RP-5 than RP-40. An uncultured \u003cem\u003eMuribaculaceae\u003c/em\u003e species was significantly enriched in RP-40 compared to RP-10 and RP-20 and depleted in RP-5 relative to RP-40. A member of \u003cem\u003eMicrococcaceae\u003c/em\u003e (phylum \u003cem\u003eActinobacteriota\u003c/em\u003e) was more abundant in RP-5 than RP-20. Lastly, \u003cem\u003eChloroplast\u003c/em\u003e sequences were significantly enriched in RP-5 and RP-40 compared to RP-20. These findings indicate that specific gut microbial taxa respond to distinct levels of dietary rose petal supplementation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eReplacing fishmeal with sustainable, plant-derived ingredients is essential for reducing reliance on marine resources in aquaculture (Hossain et al \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This study demonstrated that partial replacement of fishmeal with RP powder up to 40 g/kg did not compromise growth performance or feed utilization in goldfish. RP is rich in carotenoids, amino acids, polyunsaturated fatty acids, and trace minerals, which likely acted synergistically to promote growth (Nowak et al \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; dos Santos et al \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Nakano and Wiegertjes \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lim et al \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Salamatullah et al \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These findings align with previous research in teleost, including enhanced growth in orange swordtail and dwarf tilapia fed rose petal-enriched diets (Joseph et al \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Pailan et al \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and improvements observed in marine ornamental fish and goldfish fed natural pigment supplements such as rose or marigold powders (Sinha and Asimi \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Ezhil et al \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Ramamoorthy et al \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePigmentation enhancement is critical in ornamental aquaculture, where skin color influences consumer perception of quality, health, and value (de Carvalho and Caramujo \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Luo et al \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sathyaruban et al \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Carotenoid-based pigmentation can be reliably quantified using CIE parameters (L*, a*, b*, chroma, and saturation) and must be supplied through the diet, as fish cannot synthesize carotenoids de novo (Kalinowski et al \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Once absorbed, carotenoids are transported via lipoproteins and deposited in chromatophores, xanthophores and erythrophores, responsible for yellow and red coloration, respectively (Barman et al \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Liao et al \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). RP provides β-carotene, lutein, zeaxanthin, flavonoids, and phenolics that may enhance pigment deposition and stability (Wan et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, 2019). In this study, RP-40 yielded the greatest increases in redness (a*) and yellowness (b*), confirming a dose-dependent effect. Similar findings were reported in dwarf gourami, with progressive color enhancement observed at increasing RP levels (Pailan et al \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOxidative stress, caused by excess ROS, damages lipids, proteins, and DNA (Di Giulio and Meyer \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) (Amenyogbe et al \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). MDA, a by-product of lipid peroxidation, is a widely used oxidative stress marker (Demirci-Cekic et al \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Organisms counteract ROS via enzymatic antioxidants like SOD and non-enzymatic scavengers such as ABTS activity (Chen et al \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; F. Xu et al \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this study, RP supplementation led to dose-dependent increases in ABTS and SOD activities and a corresponding reduction in serum MDA, indicating enhanced systemic antioxidant defense. These findings are consistent with ex vivo studies, where rose byproducts reduced lipid peroxidation in sea bass fillets (Giannakourou et al \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and in vivo studies, where \u003cem\u003eR. damascena\u003c/em\u003e extracts upregulated antioxidant enzymes in rats (Hamza et al \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The potent radical-scavenging activity observed here supports previous reports of strong antioxidant potential in rose petals (\u0026Ouml;nder \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), suggesting that RP contributes both direct and enzyme-mediated protection against oxidative stress in goldfish.\u003c/p\u003e \u003cp\u003eDietary inclusion of RP powder elicited a clear, concentration-dependent upregulation of key antioxidant, growth, and immune-related genes, indicating activation of endogenous physiological pathways in goldfish. \u003cem\u003eHSP70\u003c/em\u003e, a molecular chaperone involved in protein refolding under oxidative stress (Sen and Giri \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), was significantly induced only at the highest RP dose (RP-40 vs. RP-0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This response mirrors findings in pufferfish where dietary astaxanthin upregulated hepatic \u003cem\u003eHSP70\u003c/em\u003e under thermal stress, highlighting the role of carotenoid antioxidants in stress adaptation (Eissa et al \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Similarly, \u003cem\u003eCYP1A\u003c/em\u003e, an enzyme central to xenobiotic metabolism, was significantly elevated in RP-40, with non-significant trends at intermediate doses. Immune gene expression revealed selective activation of pro-inflammatory and innate immune markers. While \u003cem\u003eIL10\u003c/em\u003e and \u003cem\u003eIL1β\u003c/em\u003e levels remained unchanged (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), \u003cem\u003eTNFα\u003c/em\u003e and \u003cem\u003eLYZ\u003c/em\u003e were significantly upregulated at RP-20 and RP-40 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that RP stimulates acute immune readiness without inducing chronic inflammatory responses.\u003c/p\u003e \u003cp\u003eRP supplementation also influenced the gut microbiota, though effects were modest and individualized. Alpha diversity indices (Shannon, Chao1, Pielou\u0026rsquo;s evenness, Faith\u0026rsquo;s PD) showed no significant differences among groups, suggesting the resilience of within-sample microbial diversity to dietary RP under these experimental conditions. This stability is noteworthy given that fish gut diversity is often sensitive to various factors including specific dietary interventions (Rabelo-Ruiz et al \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), environmental stressors like mycotoxins or heavy metals (Zhang et al \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Spilsbury et al \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and disease state (Li et al \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, PERMANOVA based on Bray\u0026ndash;Curtis dissimilarity detected a significant difference in community structure (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017), whereas presence/absence (Jaccard) and phylogenetic (UniFrac) metrics, as well as pairwise comparisons, were non-significant after FDR correction. These findings suggest RP primarily induced subtle shifts in the relative abundance of existing taxa. Given that gut beta diversity is influenced by dietary composition(Silva et al \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Q. Xu et al \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and may correlate with host phenotypes such as coloration (Ahmed et al \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), the observed compositional shift may reflect a biologically meaningful, though nuanced, response. The high proportion of unclassified taxa (~\u0026thinsp;36% at the phylum and ~\u0026thinsp;51% at the genus level) and strong inter-individual variability (e.g., samples RP-0 [4] and RP-20 [5]) likely reflect host-specific microbial assemblages and the presence of under-characterized aquatic microbiota (Spilsbury et al \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Li et al \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the overall subtlety of the community shift, differential abundance analysis (ANCOM-BC2, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) identified several taxa that responded to RP supplementation. \u003cem\u003eStaphylococcus\u003c/em\u003e was significantly enriched in the RP-40 group relative to RP-0. Although certain species (e.g., \u003cem\u003eS. warneri\u003c/em\u003e) have been associated with disease in fish (Bunnoy et al \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Xiao Joe et al \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), \u003cem\u003eStaphylococcus\u003c/em\u003e is also part of the normal gut microbiota in healthy goldfish (Silva et al \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and shrimp. Its enrichment, coinciding with improved growth, pigmentation, and immune-antioxidant gene expression in RP-40, suggests a potentially neutral or even beneficial role in this context. RP-derived phenolic compounds, known to exert antimicrobial activity (Giannakourou et al \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), may have selectively modulated gut microbial composition. Conversely, the depletion of \u003cem\u003eAlloprevotella\u003c/em\u003e in RP-5 may reflect changes in fiber-related substrate availability, though its ecological role in fish remains unclear. Additional taxa showing dose-specific changes, including \u003cem\u003eMuribaculaceae\u003c/em\u003e, \u003cem\u003eMicrococcaceae\u003c/em\u003e, and \u003cem\u003eChloroplast\u003c/em\u003e, further suggest that microbial shifts were responsive to RP concentration.\u003c/p\u003e \u003cp\u003eInterestingly, no significant correlations were found between gut microbiota metrics (PCoA axes, key genera) and host parameters (growth, ABTS, SOD, MDA) after FDR correction. This may indicate that functionally important taxa shift, such as those identified by ANCOM-BC2, are more relevant than broader diversity indices, or that host-microbiota relationships in this system are non-linear or indirect. Similar dissociations between microbiota shifts and host phenotypes have been reported, such as in seabream fed Allium-derived supplements (Rabelo-Ruiz et al \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eNevertheless, the established role of the gut microbiome in modulating fish immunity and metabolism (Butt and Volkoff \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Xiong et al \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Spilsbury et al \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) supports the hypothesis that the RP-induced microbial changes may have contributed to the observed physiological improvements. For example, \u003cem\u003eStaphylococcus\u003c/em\u003e has been associated with altered cytokine expression in grouper (Xiao Joe et al \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and other taxa have been linked to antioxidant responses in carp exposed to toxins (Zhang et al \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xue et al \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, studies in salmonids have linked gut microbiota composition, including potential carotenoid-associated genera like \u003cem\u003eBacillaceae\u003c/em\u003e, \u003cem\u003ePhotobacterium\u003c/em\u003e, and \u003cem\u003eMycoplasma\u003c/em\u003e, to pigmentation outcomes (Nguyen et al \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ahmed et al \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While mechanisms remain to be clarified, it is plausible that RP-induced shifts in gut microbiota influenced the absorption, metabolism, or transport of dietary carotenoids, thereby contributing to the increased skin redness (a*) and yellowness (b*) observed in this study.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eDietary inclusion of rose petal powder at 20\u0026ndash;40 g/kg significantly enhanced growth performance, feed efficiency, and skin pigmentation in goldfish. RP supplementation also improved systemic antioxidant capacity, evidenced by increased ABTS and SOD activity and decreased MDA levels. Expression of antioxidant (\u003cem\u003eHSP70\u003c/em\u003e, \u003cem\u003eCYP1A\u003c/em\u003e), growth (\u003cem\u003eIGF\u003c/em\u003e, \u003cem\u003eTGF\u003c/em\u003e), and immune (\u003cem\u003eTNF\u0026alpha;\u003c/em\u003e, \u003cem\u003eLYZ\u003c/em\u003e) genes was upregulated in a dose-dependent manner. Although alpha diversity remained unchanged, RP induced a significant shift in gut microbial community structure. These findings highlight the potential of rose petal byproducts as a sustainable, multifunctional alternative to synthetic additives in ornamental aquaculture, capable of promoting growth, enhancing coloration, and supporting fish health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of Competing Interest\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003ch2\u003eAnimal ethics\u003c/h2\u003e \u003cp\u003eAll experiments in this study were conducted in accordance with the relevant guidelines and regulations. The experimental protocols were approved by the Institutional Animal Care and Use Committee, Prince of Songkla University (Approval No. AG41/2025). All the procedure followed the ARRIVE guideline.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eNutticha Nuntakad: Methodology, Investigation, Conceptualization, Resources. Luu Tang Phuc Khang: Roles/Writing - Original draft, Formal analysis, Data curation, Software. Suwanna Wisetkaew: Methodology, Investigation. Nguyen Dinh-Hung: Writing-Review \u0026amp; Editing, Formal Analysis, Validation. Cao Phuong Thao: Roles/Writing - Original draft, Methodology, Software, Data Analysis. Truong Anh Tu: Roles/Writing - Original draft, Methodology, Software, Data Analysis. Luu Phuc Loi: Roles/Writing - Original draft, Methodology, Software, Validation, Supervision. Papungkorn Sangsawad: Methodology, Investigation, Writing-Review \u0026amp; Editing, Validation. Mintra Seel-audom: Conceptualization, Investigation, Methodology, Writing-Review \u0026amp; Editing, Validation, Formal analysis. Patima Permpoonpatana: Methodology, Investigation, Supervision, Validation, Writing-Review \u0026amp; Editing. Nguyen Vu Linh: Conceptualization, Methodology, Investigation, Roles/Writing - Original draft, Writing-Review \u0026amp; Editing, Data curation, Funding acquisition, and Project administration, Validation, Supervision.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe research was partially supported by Chiang Mai University, Chiang Mai, Thailand.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhilan B, Jegan K, Felix N (2013) Influence of botanical additives on the growth and colouration of juvenile goldfish, \u003cem\u003eCarassius auratus\u003c/em\u003e (Linnaeus). 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Sci Total Environ\u003cem\u003e \u003c/em\u003e747: 141255. https://doi.org/10.1016/j.scitotenv.2020.141255\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"goldfish, gut microbiota, immunity, rose petals, pigmentation","lastPublishedDoi":"10.21203/rs.3.rs-6608516/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6608516/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNatural additives are increasingly valued in ornamental fish aquaculture. Rose petal contains bioactive compounds, yet their effects on goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) remain underexplored. This study assessed the impacts of graded dietary rose petal supplementation (0, 5, 10, 20, and 40 g/kg; RP-0 to RP-40) over an 8-week feeding trial on growth performance, skin pigmentation, serum antioxidant status, intestinal gene expression, and gut microbiota composition. Fish fed RP-supplemented diets, particularly at 40 g/kg, exhibited significantly higher final weight and weight gain than the RP-0 group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), without adverse effects on survival or feed conversion ratio. Skin redness (a⁎) and yellowness (b⁎) increased significantly in a dose-dependent manner (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 at RP-20/40 for a⁎, RP-40 for b⁎). Serum antioxidant capacity improved with increasing RP levels, as indicated by higher ABTS and SOD activities and lower MDA levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Dietary rose petal supplementation also significantly upregulated intestinal expression of antioxidant (\u003cem\u003eHSP70\u003c/em\u003e, \u003cem\u003eCYP1A\u003c/em\u003e), growth (\u003cem\u003eIGF\u003c/em\u003e, \u003cem\u003eTGF\u003c/em\u003e), and immune (\u003cem\u003eLYZ\u003c/em\u003e, \u003cem\u003eTNFα\u003c/em\u003e) genes, primarily at 20\u0026ndash;40 g/kg (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). While rose petal significantly altered gut microbiota composition based on beta diversity (PERMANOVA \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017) and specific taxon abundances (e.g., increased \u003cem\u003eStaphylococcus\u003c/em\u003e at RP-40 and decreased \u003cem\u003eAlloprevotella\u003c/em\u003e at RP-5; ANCOMBC2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), it did not significantly affect alpha diversity or exhibit strong correlations with host physiological parameters after FDR correction. Overall, the results of this study highlights rose petal as a natural functional additive for ornamental aquaculture.\u003c/p\u003e","manuscriptTitle":"Dietary Supplementation with Rosa rubiginosa petal as a Natural Feed Additive Modulates Growth Performance, Skin Pigmentation, Immunity, and Gut Health in Goldfish (Carassius auratus)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-15 14:50:17","doi":"10.21203/rs.3.rs-6608516/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"908a84b1-6b70-4a94-8787-1a45ea891565","owner":[],"postedDate":"May 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-29T21:08:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-15 14:50:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6608516","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6608516","identity":"rs-6608516","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}