Rumen bacteria, carcass traits, and meat quality of growing goat fed diets with different levels of Azolla Pinnata

TL;DR

This study shows that adding Azolla to goat feed improves rumen bacteria, growth, and meat quality by reducing fat and increasing healthy fatty acids.

Contribution

The study demonstrates that Azolla can replace part of conventional feed in goats, improving rumen diversity and meat quality.

Findings

Replacing 10% of concentrate feed with Azolla increased rumen bacteria diversity and growth rates in goats.

Azolla reduced meat fat content and saturated fatty acids while enhancing antioxidant capacity and unsaturated fatty acids.

The optimal Azolla substitution level was 10%, as higher levels showed reduced benefits.

Abstract

Low availability and high prices of concentrate feeds drive the use of sustainable animal feeds, such as Azolla. Azolla is rich in nutrients and bioactive compounds that improve rumen microbial fermentation and animal performance. This study investigated the effect of replacing concentrate feed mixture (CFM) with Azolla pinnata on the rumen bacteria and fermentation, growth performance, and meat quality of growing Damascus (Shami) goats. Twenty-seven growing male goats were used for 153 days to receive three treatments (n = 9): a control group received a non-supplemented diet composed of Berseem hay and CFM (CC); a group received the control diet with 10% Azolla from the CFM (AZ10); and a group received the control diet with 20% Azolla from the CFM (AZ20). Replacing CFM with Azolla increased the diversity of the rumen bacteria, with the enrichment of phyla Bacteroidota and Firmicutes. Azolla enhanced the prevalence of fibrolytic bacteria, Ruminococcus, Butyrivibrio, and Christensenellaceae R-7 group. Total volatile fatty acids (VFA) increased in AZ10 by 39% and 25% compared to groups CC and AZ20, respectively. Growth rate was higher in AZ10 by 35% and 18% compared to CC and AZ20, respectively. Azolla supplementation reduced the fat content of meat and reduced saturated fatty acids of meat by 52% in AZ10 and 21.5% in AZ20 compared to group CC, while it improved the antioxidant capacity and unsaturated fatty acids in meat. Azolla can substitute the conventional feed mixture of growing goats at 10%.

The online version contains supplementary material available at 10.1186/s13568-026-02019-3.

Figures

Principal coordinates analysis (PCoA) of the bacterial community was performed based on Bray–Curtis dissimilarity. The analyses were conducted between three growing goat groups: red circles for the control group (C), green circles for goats supplemented with 10% azolla (AZ10), and blue circles for goats supplemented with 20% azolla (AZ20)

Principal component analysis (PCA) was determined using the results of ADG, rumen fermentation parameters, and the relative abundances of dominant bacterial phyla and genera, carcass characteristics, meat quality, and fatty acids in meat. The black dots are for goats of the control group (C), the blue squares are for goats supplemented with 10% azolla (AZ10), and the red triangles are for goats supplemented with 20% azolla (AZ20)

Full text

Introduction

Feed deficiency and the high cost of conventional feed resources remain major challenges to livestock production in developing countries, particularly under the pressure of global warming (Sihag et al. 2018). Traditional animal feeds, especially protein sources, are scarce or unaffordable. Therefore, integrating low-cost, unconventional feed resources into animal diets can enhance the profitability and sustainability of livestock production by reducing feed costs and the use of local feed resources (Hassanein et al. 2023). Consequently, it is necessary to explore available non-traditional feed resources, such as Azolla, that are well adapted to local conditions (Abd-Elgwad et al. 2025).

Azolla is a floating aquatic fern that grows in a wide range of cultivation conditions, such as the surface of water in tropical and subtropical regions of Africa, Asia, and the Americas. Additionally, it can grow in stagnant water of ponds, drains, streams, lagoons, paddy fields, and covered marginal lands such as salty and rocky lands, making it a vital and sustainable feed resource with minimal land requirements and minimal cultivation costs (Sihag et al. 2018; Abd-Elgwad et al. 2025). Therefore, integrating Azolla into the agricultural system provides a sustainable feed source.

Moreover, Azolla is characterized by rapid growth and a rich nutritional profile, being a valuable source of carbohydrates, protein, unsaturated fatty acids, essential minerals (i.e., calcium and phosphorus), and vitamins such as vitamin A, B12, and ß-carotene. In addition, Azolla is rich in phytogenic compounds with several antimicrobial, antioxidant, and immunostimulatory properties, which enhance animal health (Kewan et al. 2021; Hassanein et al. 2023). These attributes have drawn attention to Azolla as a sustainable alternative for conventional feed ingredients in animal diets (Abou El-Fadel et al. 2020; Vahedi et al. 2021).

On the other hand, phytogenic compounds in Azolla can improve animal efficiency through modulating the rumen microbiome and improving the digestibility of nutrients (Hassanein et al. 2023; Rabee et al. 2024). However, limited information is available on the effect of Azolla on rumen microbiota. An in vitro study indicated that the inclusion of Azolla in animal diets modified the rumen bacterial community, which was dominated by genera Prevotella, Rikenellaceae RC9 gut group, Streptococcus, and Christensenellaceae R-7 group (Abd-Elgwad et al. 2025). This study reported that optimum in vitro degradability and volatile fatty acid (VFA) production were noticed when Azolla replaced 10–20% of the CFM. However, no in vivo studies have been conducted on the effect of Azolla on rumen microbiota. In goats, dietary inclusion of phytochemicals enhanced fiber-degrading bacteria such as Prevotella and Rikenellaceae RC9 gut group and family Ruminococcaceae, while reducing rumen methanogenic genus Methanobrevibacter, which reduced methane production (Rabee et al. 2024). These microbial modulations improved fiber digestibility, VFA production, and growth performance (Rabee et al. 2024, 2025). Similarly, Azolla supplementation promoted VFA production in both sheep and goats (Abou El-Fadel et al. 2020; Hassanein et al. 2023).

Inclusion of Azolla up to 20% of the diet of growing goats improved growth performance (Al-Suwaiegh 2023). While Sihag et al. (2018) reported that Azolla can be incorporated in growing goats’ diets up to 15% without adverse effect on feed utilization or growth performance. Thus, more studies are needed to assign a suitable inclusion level of Azolla in the diet of growing animals. On the other hand, data on the effects of Azolla on carcass characteristics and meat quality are also limited. Azolla did not affect carcass characteristics and meat quality in lambs (Vahedi et al. 2021), whereas dietary phytochemicals reduced renal fat and enhanced the polyunsaturated fatty acid content in goat meat (Rabee et al. 2025).

Goats are an essential component of animal production in developing countries. Shami (Damascus) goats are dual-purpose and a common goat breed in the Mediterranean area. This goat breed is known for its high productivity under harsh desert conditions, including heat stress and scarcity of water and low-quality feeds, making it an integral part of food security in marginal areas (Alsheikh 2013; Sallam et al. 2023; Rabee et al. 2025). However, the performance of animals in developing countries is challenged by health problems and the deficiency of sustainable feed resources (Ibrahim et al. 2020). Therefore, the suitable inclusion of unconventional feed resources such as Azolla, and its effect on animal performance and rumen microbiota need to be evaluated. Thus, the objectives of this study were to evaluate the effect of two levels of Azolla on rumen bacteria, rumen fermentation, growth performance, and meat quality of growing Shami goats.

Material and methods

Ethics

The study, including euthanasia of the animals, was conducted according to the guidelines and regulations of the Institutional Animal Care and Use Committee, Desert Research Center (DRC), Egypt (Reference number: AN-7-2024). All methods and protocols in this study comply with the ARRIVE guidelines and EU standards for animal protection. The sample size was decided based on the availability of animals with similar physical and physiological status. The experiment does not include clinical trials.

Animals, diets, and experimental design

The study was conducted at Maryout Research Station, DRC, Alexandria, Egypt. Twenty-seven growing male Shami goats (4 months old, 14.84 ± 1.16 kg average body weight) were randomly selected for a 153-day feeding trial. All animals were offspring of the station’s goat herd and were used with the required consent from the administration of Maryout Research Station and the Animal and Poultry Production Division, DRC. Azolla cultivation, management, harvesting, and preparation were previously described in Abd-Elgwad et al (2025).

Goat kids were randomly assigned to three dietary treatment groups (n = 9) and group-housed in shaded pens (40 m^2^ per group) with free access to drinking water. Body weights were recorded at both the beginning and biweekly. All diets consisted of 70% concentrate feed mixture (CFM) and 30% berseem clover hay (Trifolium alexandrinum) formulated to meet the nutritional requirements for growing goats as the National Research Council (NRC 2007). The three experimental diets differed in the levels of dried Azolla included in the CFM (Table 1): Control diet (CC): 30% Berseem clover and 70% CFM; AZ10: 10% of the CFM of the control diet was replaced with dried Azolla; and AZ20: 20% of the CFM of the control diet was replaced with dried Azolla.Table 1. The ingredients of concentrate feed mixtures used in experimental groups and chemical composition of animal dietsControlAZ10AZ20AzollaBerseem hayCorn56.0050.4045.00––Soya meal23.0020.9018.75––wheat brane16.0014.4012.80––Cotton meal2.501.801.00––Azolla010.0020.00––Yeast0.250.250.25––Vitamins and minerals0.250.250.25––Salt0.750.750.75––Calcium carbonate1.051.051.05––Antitoxins0.100.100.10––Bicarbonate0.100.100.10––Chemical composition, %DM, %88.8988.5888.4289.8284.72OM, %93.5592.0090.4079.986.59CP, %17.0217.0217.0017.0814.1EE, %3.253.393.304.753.04CF, %7.509.0011.0020.5922.51Ash, %6.458.009.6020.1013.41GE, MJ/Kg DM*18.2018.0017.7016.1716.80DM = Dry matter; OM = Organic matter; CP = Crude protein; EE = Ether extract; CF = Crude fiber; GE = Gross energy; *Calculated value. Control = goats supplemented with a non-supplemented diet; AZ10 = goats supplemented 10% azolla; AZ20 = goats supplemented with 20% azolla

The inclusion levels of Azolla (10 and 20%) were based on recommendations from an in vitro study by Abd-Elgwad et al. (2025), which suggested up to 20% replacement of CFM with Azolla. All concentrate mixtures were formulated to be isonitrogenous, containing 17% CP. The proximate chemical composition of Azolla Pinnata, Berseem clover hay, and CFM used in the three diets is shown in Table 1. The concentrate feed mixtures were offered to the animals in pellets according to their weight and the proportion of concentrate in the experimental diets. The experimental rations were offered two times a day at 7:00 and 15:00. The animals consumed all the CFM, and the refused hay was weighed, and feed intake was recorded daily. Diet and refused diets were sampled weekly and dried in a forced-air oven at 65 °C for 48 h.

Rumen fermentation and predicted methane production

At the end of the experiment, rumen samples were collected. Rumen contents were collected from the animals using stomach tubing before the morning feeding with a standardized tube depth across all goats. The initial portion of rumen content was discarded to minimize saliva contamination in the rumen sample. The samples were filtered using two layers of cheesecloth to remove large particles, and the pH of the rumen fluids was immediately measured using a digital pH meter (WPA CD70, ADWA, Szeged, Hungary).

The filtered rumen samples were then used to measure VFA, ammonia, and microbial DNA extraction. For VFA and ammonia analyses, rumen fluid samples were centrifuged at 15,000 rpm for 15 min, and the supernatant was collected. The concentration of rumen ammonia (NH_3_-N) and VFAs was previously described in Rabee et al. (2024). Briefly, 1 mL of rumen fluid was acidified with 200 μL of meta-phosphoric acid 25% (w/v). Rumen ammonia nitrogen (NH_3_-N) was assessed using ammonia assay kits (Biodiagnostic, Cairo, Egypt). VFAs were measured by a Thermo Scientific TRACE 1300 gas chromatography system (Thermo Scientific, Massachusetts, United States) equipped with a capillary column (TR-FFAP 30 m × 0.53 mmI D × 0.5 μm) with nitrogen as the carrier gas. Calibration was performed using standard solutions with known VFAs concentrations.

Carcass traits and meat quality assessment

At the end of the experimental period, all goats were fasted for 12 h with free access to water before being transported to the slaughterhouse at Maryout Research Station, Alexandria, Egypt. The slaughtering was conducted by cutting the arteries and veins at the throat area in the neck with a sharp knife, with no electrical stimulation, stunning, or chemical treatments. All animals were alive and conscious at the time of slaughter and were not anaesthetized or unconscious. Following bleeding, skinning, and evisceration, hot carcass weights were recorded to calculate dressing percentage (Zayed et al. 2022).

Carcass cuts, including neck, shoulders, rack, flank, loin, legs, and tail, were individually weighted. Additionally, the weights of edible organs such as liver, heart, and kidneys were recorded. The best ribs (9th, 10th, and 11th) from each carcass were isolated and dissected into meat, fat, and bone, which were weighed separately. The meat portion was used for chemical composition analysis using a Food Scan Pro meat analyzer (Foss Analytical A/S, Model 78,810, Denmark).

Meat color was assessed on the best ribs muscle using a chroma meter (Konica Minolta, model CR 410, Japan). Color parameters included lightness (L*), redness (a*), and yellowness (b*). Chroma and Hue were also calculated. Meat pH was measured using a portable digital waterproof pH meter (HANNA, model HI 9025) immediately after slaughter and again 24 h postmortem. The shear force of cooked cuts was determined using an Instron Universal Testing Machine (Zayed et al. 2022). Total antioxidant activity of meat was evaluated using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay (Fasseas et al. 2008).

Fatty acid composition in meat

Fatty acids extraction and preparation of fatty acid methyl ester were performed according to Folch et al. (1957) and Ichihara and Fukubayashi (2009). The fatty acids were analyzed using a Thermo Scientific TRACE 1300 gas chromatography system (Thermo Scientific, Massachusetts, United States). Long-chain fatty acids were identified using a TG-5MS Zebron capillary column and helium as the carrier gas.

Microbial community

DNA extraction and PCR amplification

Total microbial DNA was extracted from 500 µl of rumen fluid. Samples were first centrifuged at 13,000 rpm for 15 min, and the resulting pellets were used for DNA isolation using the QIAamp DNA Stool Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. DNA concentration and quality were assessed using a Nanodrop spectrophotometer 2000 (Thermo Scientific, Massachusetts, United States) and gel electrophoresis. Rumen bacterial communities were investigated by PCR amplification of the V4 variable region of the 16S rDNA using the primer pair 515F and 926R. The PCR conditions were as follows: initial denaturation at 94 °C for 3 min; 35 cycles of 94 °C for 45 s, annealing at 50 °C for 60 s, and extension at 72 °C for 90 s; followed by a final extension at 72 °C for 10 min. PCR amplicons were purified and sequenced using the Illumina MiSeq system at Integrated Microbiome Resource, Dalhousie University, Halifax, Canada.

Bioinformatics analysis

The bioinformatic analysis was previously described in Rabee et al. (2024). Briefly, the generated paired-end raw sequence reads (Average 49,242 ± 4435 sequence reads per sample) were analyzed using the DADA2 (version 1.11.3) pipeline within the R environment (version 3.5.2) (Callahan et al. 2016). Fastq files were demultiplexed, and sequence quality was determined based on the quality scores. Reads were subsequently filtered, trimmed, and dereplicated. Read 1 and read 2 were merged to get the denoised sequences. Only high-quality samples with a quality score ≥ 30 were retained for subsequent analyses. Consequently, five samples were kept for every group (n = 5) for the bacterial community analysis. The chimeras were identified and removed to generate Amplicon Sequence Variants (ASVs). Taxonomic assignment of ASVs was conducted using assignTaxonomy and assignSpecies functions referring to the SILVA reference database (version 138). For all samples, the alpha diversity indices (observed ASVs, Chao1, Shannon, and Inverse Simpson) were measured to analyze richness and evenness across the treatment groups. Beta diversity was determined using principal coordinate analysis (PCoA) based on Bray–Curtis dissimilarity and visualized using the phyloseq and ggplot2 packages in R. The raw sequence data have been deposited in the NCBI sequence read archive (SRA) under accession number: PRJNA1291118.

Proximate chemical analysis, phytochemical compounds, and fatty acids of animal feeds

Dried Azolla, feeds, and fecal samples were ground and analyzed according to the method of AOAC (1997) to determine dry matter (DM: method 930.15), crude protein (CP: method 954.01), ether extract (EE, method 920.39), and crude fiber (CF: method 978.10). Phytochemical compounds, including total flavonoids, total phenols, and total tannins, were quantified in Berseem hay, CFM, and Azolla as described in Rabee et al. (2024). Fatty acid profiles were determined in Berseem hay, CFM, and Azolla as described in Abd-Elgwad et al. (2025).

Gross energy was calculated using the equation: Gross energy (GE) (MJ/Kg DM)

= 0.0176 OM (g/kg) + 0.0064 CP(g/kg) + 0.0214 EE(g/kg) according to SCA (1990).

Statistical analysis

Data on the relative abundances of microbial groups were tested for normality and homogeneity by the Shapiro–Wilk test, and non-normal variables were then arcsine transformed. The effect of Azolla supplementation level (independent variable) on the differences in feed intake, growth performance, rumen fermentation parameters, diversity and relative abundances of rumen bacteria, carcass characteristics, meat quality parameters, and meat fatty acids profile (dependent variables) was examined using one-way ANOVA (Y_ij = μ + T_i + e_ij). Post hoc comparison using Duncan’s test was conducted to assess the variation between groups at a significance level set at p < 0.05, where the individual goat was considered the experimental unit for all analyses. Principal component analysis (PCA) and Permutational multivariate analysis of variance (PERMANOVA) and Pearson correlation analyses that were visualized as a Heatmap, were conducted to assess patterns of sample distribution correlation relationships due to Azolla replacement level using the data of growth performance, rumen fermentation parameters, relative abundances of rumen bacteria, carcass characteristics, meat quality parameters, and meat fatty acids profile. Analysis of Covariance (ANCOVA) was used to analyze the effect of initial body weight (Covariate) on the ADG (dependent variable). The statistical analyses were performed using SPSS v. 20.0 software package (SPSS 1999) and PAST software (Hammer et al. 2001).

Results

Proximate chemical analysis

Berseem hay (BH) exhibited lower crude protein content (14.1%) compared to both Azolla and the CFM, which contained approximately 17% crude protein (Table 1). Azolla had a higher ether extract compared to BH and CFMs, while BH had the highest CF content, followed by Azolla and CFMs, respectively. Ash content was higher in Azolla, followed by BH and CFMs, respectively. Increasing the inclusion level of Azolla in diets (AZ10 and AZ20) resulted in elevated CF and ash, which resulted in slight differences in the gross energy (GE) (MJ/Kg DM) (Table 1).

Phytochemical content in animal feeds

The results indicate that Azolla contains higher levels of total polyphenols and tannins compared to both BH and CFM (Supplementary Table S1 ). In contrast, CFM exhibited the highest flavonoid. Azolla contained a wide range of polyphenolic compounds, some of which were shared with BH and CFM, including gallic acid, chlorogenic acid, ellagic acid, resorcinol, rutin, quercetin, and kaempferol. Notably, several phytogenic compounds were unique to Azolla, such as methyl gallate, caffeic acid, vanillin, rosmarinic acid, catechin, naringenin, daidzein, hesperetin, and hesperidin (Supplementary Table S1).

Fatty acid content in animal feeds

The fatty acid profile of Azolla, CFM, and BH (Supplementary Table S2) showed that the predominant saturated fatty acids (SFAs) were palmitic acid and stearic acid. Notably, pentadecanoic acid and tridecanoic acid were detected exclusively in Azolla. Among the monounsaturated fatty acids (MUFAs), oleic acid and palmitoleic acid were the most abundant. The primary polyunsaturated fatty acids (PUFAs) identified were linoleic acid and linolenic acid. Additionally, Azolla uniquely contained several PUFAs, including gamma-linolenic acid, homo-γ-linolenic acid, and linolelaidic acid (Supplementary Table S2).

Diversity of the bacterial community

Illumina amplicon sequencing of the V4 regions of the 16S rDNA genes generated a total of 738,635 high-quality sequence reads, with an average of 49,242 ± 4435 reads per sample. Azolla supplementation level significantly affected the alpha diversity indices of the rumen microbial communities. Specifically, the AZ20 group showed higher Amplicon Sequence Variants (ASVs) and Chao1 index (p < 0.05) (Table 2; Supplementary Figure S1). Azolla-supplemented groups (AZ10 and AZ20) showed higher Shannon and Inverse Simpson indices than the control group (p < 0.05) (Table 2; Supplementary Figure S1). Beta diversity analysis, based on PCoA and Bray–Curtis dissimilarity, revealed distinct clustering of microbial communities. The bacterial communities in the Azolla-supplemented groups (AZ10 and AZ20) were separated from those of the control group, indicating a shift in microbial composition due to dietary treatment (Fig. 1).Table 2. Effect of azolla supplementation level on alpha diversity indices of bacterial community and the relative abundance of bacterial phylaCCAZ10AZ20SEMp-valueMeanMeanMeanAnimal number555––Alpha Diversity indicesObserved ASVs169.80^a^237.80^ab^319.00^b^22.400.01Chao1181.03^a^246.78^ab^332.79^b^23.700.01Shannon3.62^a^4.24^b^4.56^b^0.140.01Invers Simpson18.72^a^31.65^b^49.45^b^5.780.08Bacterial Phyla, %Actinobacteriota6.592.930.901.010.05Bacteroidota38.3935.5637.822.270.88Cyanobacteria0.000.000.040.000Desulfobacterota0.560.530.340.060.34Firmicutes48.7950.7949.691.520.88Planctomycetota3.645.713.800.560.25Proteobacteria2.511.741.190.270.12Synergistota0.620.390.210.090.18Verrucomicrobiota3.00^ab^2.31^a^3.23^b^0.160.03ASVs = Amplicon Sequence Variants; ^a,b,c,d^Means within a row with different subscripts differ significantly (p < 0.05). SEM = Standard error of means. CC = goats supplemented with a non-supplemented diet; AZ10 = goats supplemented 10% azolla; AZ20 = goats supplemented with 20% azollaFig. 1Principal coordinates analysis (PCoA) of the bacterial community was performed based on Bray–Curtis dissimilarity. The analyses were conducted between three growing goat groups: red circles for the control group (C), green circles for goats supplemented with 10% azolla (AZ10), and blue circles for goats supplemented with 20% azolla (AZ20)

Bacterial community

The bacterial community in the rumen of goats was classified into nine phyla, dominated by phyla and Firmicutes (49.76%) and Bacteroidota (37.26%). Bacterial phyla that represented more than 1% of the bacterial community were: Planctomycetota (4.38%), Actinobacteriota (3.47%), Verrucomicrobiota (2.85%), Proteobacteria (1.81%) (Table 2). Bacterial phyla that represented less than 1% of the bacterial community were: Desulfobacterota (0.48%) and Synergistota (0.40%) (Table 2). Additionally, the phylum Cyanobacteria was detected only in group AZ20, accounting for 0.04% of the bacterial community (Table 2).

Phylum Actinobacteriota was affiliated mainly with families Atopobiaceae and Bifidobacteriaceae, which decreased with increasing Azolla supplementation (p < 0.05) (Tables 2 and 3). Phylum Bacteroidota, the second dominant phylum, was dominated by families Prevotellaceae, Rikenellaceae, and Muribaculaceae, which were not affected by Azolla supplementation (Tables 2 and 3). At the genus level, Prevotella was the most dominant (27.91%), followed by Rikenellaceae RC9 gut group (3.27%).Table 3. Effect of azolla supplementation on the relative abundance (%) of dominant bacterial families and generaCCAZ10AZ20SEMp-valueMeanMeanMeanAnimal number555––P: Actinobacteriota; F: AtopobiaceaeG: Atopobium0.180.100.150.020.14G: Olsenella5.60^b^1.79^ab^0.20^a^0.960.043F: Bifidobacteriaceae1.05^a^1.03^a^0.48^b^0.0770.0001P: BacteroidotaF: Prevotellaceae32.9030.1729.171.910.74G: Prevotella28.8226.6728.232.120.92F: Rikenellaceae2.613.234.210.400.27Rikenellaceae RC9 gut group2.593.054.170.390.26F: Muribaculaceae2.631.953.970.660.48F: F0820.110.1030.3200.0430.05P: DesulfobacterotaG: Desulfovibrio0.530.350.270.060.23G: Desulfobulbus0.040.1730.0690.030.13P: FirmicutesF: Ruminococcaceae1.60^b^0.29^a^1.78^b^0.270.04F: Ruminococcaceae_Unclassified1.180.070.690.220.11G: Ruminococcus0.64^b^0.22^a^1.09^c^0.100.0001F: Lachnospiraceae22.8517.0813.281.840.09G: Lachnospiraceae NK3A20 group10.19^b^1.92^a^1.12^a^1.550.02G: Acetitomaculum0.92^a^5.82^b^3.68^a^0.740.01G: Moryella1.411.181.390.230.92G: Oribacterium0.990.110.580.150.06G: Syntrophococcus1.25^c^0.59^b^0.29^a^0.110.0001G: Butyrivibrio0.32^a^1.68^b^2.16^b^0.260.003G: Howardella0.130.130.150.010.55F: Selenomonadaceae2.677.498.971.280.10G: Selenomonas0.38^a^1.27^b^0.83^ab^0.130.01G: Quinella0.22^a^1.77^b^0.37^a^0.260.018G: Veillonellaceae UCG-0010.25^a^0.26^a^0.72^b^0.080.01F: Oscillospiraceae3.50^a^6.90^b^7.35^b^0.670.02G: NK4A214 group3.09^a^6.83^b^7.22^b^0.710.02F: Anaerovoracaceae1.21^b^0.36^a^0.48^a^0.120.001G: Family XIII AD3011 group0.140.200.260.020.28G: Mogibacterium1.05^b^0.15^a^0.22^a^0.130.001F: Acidaminococcaceae1.300.300.170.220.06G: Succiniclasticum2.53^a^0.12^b^0.99^b^0.450.03F: Erysipelotrichaceae2.340.150.190.440.05G: Sharpea2.340.150.190.440.05F: Christensenellaceae4.95^a^16.31^b^14.59^b^1.560.0001G: Christensenellaceae R-7 group4.95^a^16.28^b^14.54^b^1.560.0001P: ProteobacteriaF: Alcaligenaceae; G: Achromobacter0.901.170.940.140.75F: Burkholderiaceae; G: Ralstonia0.030.030.0280.0040.64P: SynergistotaG: Pyramidobacter0.550.190.030.0950.055G: Fretibacterium0.06^a^0.18^b^0.23^b^0.020.0001P = phylum; F = Family; G = genus; ^a,b,c,d^Means within a row with different subscripts differ significantly (p < 0.05). SEM = Standard error of errors. CC = goats supplemented with a non-supplemented diet; AZ10 = goats supplemented 10% azolla; AZ20 = goats supplemented with 20% azolla

Phylum Firmicutes dominated the bacterial community and was affiliated with families Ruminococcaceae, Lachnospiraceae, Selenomonadaceae, Oscillospiraceae, Anaerovoracaceae, Acidaminococcaceae, Erysipelotrichaceae, and Christensenellaceae. Family Ruminococcaceae was dominated by the genus Ruminococcus and unclassified Ruminococcaceae that showed the lowest relative abundance in AZ10 compared with AZ20 and control groups (p < 0.05) (Table 3). Family Lachnospiraceae that was dominated by the Lachnospiraceae NK3A20 group, Acetitomaculum, Syntrophococcus, and Butyrivibrio, which were affected by Azolla supplementation. Lachnospiraceae NK3A20 group and Syntrophococcus were decreased significantly by increasing the Azolla level (p < 0.05) (Table 3). Acetitomaculum and Butyrivibrio were increased by Azolla supplementation (p < 0.05) (Table 3). Family Selenomonadaceae was dominated by Selenomonas and Quinella. Genus Quinella was higher in group AZ10, compared to groups CC and AZ20 (p < 0.05) (Table 3). Family Oscillospiraceae was dominated by the candidate genus NK4A214 group, which increased with increasing Azolla supplementation (p < 0.05). Family Anaerovoracaceae was dominated by Mogibacterium, which was decreased by increasing the Azolla supplementation (p < 0.05). Family Acidaminococcaceae that was dominated by genus Succiniclasticum, which declined by increasing Azolla supplementation (p < 0.05) (Table 3). Family Christensenellaceae was dominated by the genus Christensenellaceae R-7 group, which was increased by increasing the Azolla supplementation (p < 0.05).

Phylum Synergistota was dominated by genera Pyramidobacter and Fretibacterium. The genus Fretibacterium was increased by Azolla supplementation (p < 0.05).

Rare bacterial genera

Several bacterial genera were found to be specific to certain treatment groups (Supplementary File S1). For example, within the phylum Bacteroidota, the genus Alloprevotella was detected exclusively in the AZ20 group, while the genus Prevotellaceae NK3B31 group was detected only in the AZ10 and AZ20 groups.

Rumen fermentation

Rumen pH did not differ significantly among the experimental groups (Table 4). Group AZ10 received 10% Azolla, showed significantly higher total VFA, acetic, isobutyric, butyric, isovaleric, and valeric acids (p < 0.05) (Table 4). In contrast, propionic acid concentration decreased with Azolla supplementation, as the control group showed the highest concentration and the AZ20 group the lowest.Table 4. Effect of azolla supplementation level on the feed intake, growth performance, and rumen fermentation parameters in growing goat kidsCCAZ10AZ20SEMp-valueMeanMeanMeanTotal feed intake, g/kg^0.75^Animal number999––DMI81.3587.8183.191.210.06OMI74.4679.4174.331.080.08CPI13.1614.2013.450.200.06EEI2.59^a^2.88^b^2.68^a^0.050.014CFI9.64^a^11.35^b^11.94^b^0.320.0001Growth performance, 153 daysInitial BW, kg12.5317.9514.001.160.08Final BW, kg25.82^a^35.82^b^29.4^ab^1.650.02Body weight change, kg14.32^a^19.3^b^16.32^ab^0.830.03ADG, g/day93.62^a^126.14^b^106.70^ab^5.480.03Rumen fermentation parameterspH5.956.106.210.090.56Ammonia (mg/dL)10.5811.129.580.560.56Total VFA, mM87.47^a^122.43^b^97.51^a^5.820.02Acetic, mM49.31^a^71.81^b^64.18^ab^3.760.025Propionic, mM20.36^c^17.45^b^15.29^a^0.720.001Isobutyric, mM0.44^a^0.68^b^0.27^a^0.060.01Butyric, mM14.66^a^27.63^b^16.21^a^2.060.003Isovaleric, mM0.87^a^2.02^b^0.58^a^0.220.005Valeric, mM1.80^ab^2.82^b^0.96^a^0.290.01DMI = Dry matter intake; OMI = Organic matter intake; CPI = Crude protein intake; EEI = Ether extract intake; CFI = Crude fiber intake; BW = Body weight; ADG = Average daily gain.VFA = Volatile fatty acids; ^a,b,c,d^ Means within a row with different subscripts differ significantly (p < 0.05). SEM = Standard error of means. CC = goats supplemented with a non-supplemented diet; AZ10 = goats supplemented 10% azolla; AZ20 = goats supplemented with 20% azolla

Feed intake and growth performance

Azolla supplementation level significantly affected the feed intake of EE, CF, and ash (p < 0.05) (Table 4). The highest EE intake was found in the AZ10 group, followed by AZ20 and the CC group. Conversely, CF and ash intake were highest in the AZ20 group, with the CC group showing the lowest values. Initial body weights were not significantly different (p > 0.05). However, goats in the AZ10 group showed higher final body weight and body weight change (p < 0.05). Furthermore, AZ10 improved average daily gain (ADG) by 35% and 18% compared to CC and AZ20 treatments, respectively (p < 0.05). Furthermore, the results of ANCOVA revealed that the effect of the initial body weight on the ADG was not significant (p = 0.24).

Principal component analysis (PCA) and bray–curtis permutational multivariate analysis of variance (PERMANOVA)

PCA analysis was performed using data on ADG, rumen fermentation parameters, and the relative abundances of dominant bacterial phyla and genera, carcass characteristics, meat quality, and fatty acids in the meat (Fig. 2). The results showed that the samples clustered based on feeding treatments. The clustering was driven by ADG; the relative abundances of Bacteroidota, Firmicutes, Lachnospiraceae NK3A20 group, Acetitomaculum, and Christensenellaceae R-7 group; concentration of acetic, butyric, and VFA; meat antioxidant capacity and ∑SFA and ∑MUFA of meat. PERMANOVA analysis confirmed that the differences among groups were significant (p = 0.0001). Pairwise comparisons using Bonferroni-corrected p-value showed significant differences between the CC group and AZ10 (p = 0.006), the CC and AZ20 (p = 0.01), and AZ10 and AZ20 (p = 0.007).Fig. 2. Principal component analysis (PCA) was determined using the results of ADG, rumen fermentation parameters, and the relative abundances of dominant bacterial phyla and genera, carcass characteristics, meat quality, and fatty acids in meat. The black dots are for goats of the control group (C), the blue squares are for goats supplemented with 10% azolla (AZ10), and the red triangles are for goats supplemented with 20% azolla (AZ20)

Carcass characteristics and meat quality

Results revealed that Azolla supplementation significantly increased kidney weight (p < 0.05) (Table 5). Additionally, the weight of renal fat was higher in the AZ20 group compared to the CC and AZ10 groups (p < 0.05). The fat content of the best ribs was lower in the supplemented groups (AZ10, 0.06 kg; and AZ20, 0.07 kg), compared to the CC group (0.09 kg) (p < 0.05) (Table 5).Table 5. Effect of Azolla supplementation on carcass characteristics and meat quality of goatsCCAZ10AZ20SEMp-valueMeanMeanMeanPre-Slaughter, Fasting, kg26.6727.9330.450.800.12Hot Carcass, Kg13.0013.7014.630.440.32Cold Carcass, Kg12.6913.5514.080.450.45Dressing 1%48.4049.0548.040.550.76Carcass offalsHeart, kg0.110.120.130.0040.15Liver. kg0.500.560.590.020.29Kidneys, kg0.10^a^0.13^b^0.14^b^0.0050.0001Spleen, kg0.060.050.060.0040.47Lungs, trachea, kg0.400.510.470.020.08Renal (Kidney) fat, kg0.11^a^0.14^a^0.21^b^0.010.003Abdominal fat, kg0.390.390.390.020.99Tests, kg0.220.240.270.010.35Wholesales cutsHead, kg1.85^a^1.99^ab^2.12^b^0.040.01Pelt, kg2.83^a^2.99^ab^3.53^b^0.120.03Feet, kg0.870.930.940.020.36Shoulders, kg2.832.963.170.120.5Racks, kg3.614.044.310.160.18Flank, kg0.500.570.570.030.49Lion, kg0.770.700.730.020.29Legs, kg4.104.354.400.150.71Neck, kg0.830.860.840.020.88Tail, kg0.050.060.060.000.08Best ribs 9-10-11Best ribs 9-10-11, kg0.570.530.570.020.62Lean, kg0.280.300.300.010.92Bone, kg0.190.160.190.010.34Fat, kg0.09^b^0.06^a^0.07^a^0.0030.0001Meat qualitypH, direct6.16^a^6.47^b^6.51^b^0.040.0001Temperature, direct39.8340.0040.000.030.08pH, 24 h6.13^b^6.04^a^6.14^b^0.010.005Temperature, 24 h7.70^b^7.00^a^7.97^b^0.110.0001Cook loss, %37.3937.4437.870.300.77Shear force5.71^ab^5.43^a^6.21^b^0.120.02L, Brightness40.4439.3239.150.300.18a, Redness17.7517.9717.430.230.65b, Yellowness4.28^ab^4.62^b^3.19^a^0.250.03Chemical compositionCollagen2.112.082.180.040.61Intramuscular fat10.35^a^10.58^a^14.19^b^0.620.007Moisture67.48^b^67.97^b^65.39^a^0.460.03Protein19.9019.9619.350.120.07Antioxidant capacity DPPH42.88^a^35.07^a^68.43^b^4.610.001^a,b,c,d^Means within a row with different subscripts differ significantly (p < 0.05). SEM = Standard error of means. CC = goats supplemented with a non-supplemented diet; AZ10 = goats supplemented 10% azolla; AZ20 = goats supplemented with 20% azolla

Several meat quality parameters were affected by Azolla supplementation. Direct pH increased significantly with supplementation (p < 0.05). The AZ10 group had lower 24-h pH, 24-h temperature, and shear force values compared to other groups (p < 0.05). In terms of color, the AZ10 group showed the highest yellowness, followed by the control and AZ20 groups. Azolla supplementation also affected the chemical composition of the meat. The AZ20 group had significantly higher fat content and total antioxidant capacity, along with lower moisture content, compared to the other groups (p < 0.05).

Fatty acid profile in the meat

The dominant fatty acids in goat meat samples under investigation included homo-γ-linolenic, gamma-linolenic, eicosapentaenoic, palmitoleic, arachidonic, pentadecanoic, and myristoleic. The CC group exhibited higher levels of total saturated fatty acids (SFA), while the AZ10 group had higher polyunsaturated fatty acids (∑PUFA) (p < 0.05) (Table 6). Fatty acids that were affected by Azolla supplementation, including tridecanoic acid, cis-10-heptadecanoic acid, gamma-linolenic acid, homo-γ-linolenic acid, and linolelaidic acid, were also found in Azolla and goat meat (Supplementary Table S2).Table 6. Effect of azolla supplementation on the fatty acid profile of goat meatCCAZ10AZ20SEMp-valueMeanMeanMeanMyristic acid3.58^b^2.58^a^2.62^a^0.110.0001Margaric acid3.41^a^2.77^a^6.72^b^0.450.001Palmitic acid2.48^a^3.06^b^4.65^c^0.590.005Stearic acid7.51^b^2.62^a^2.81^a^0.520.0001Pentadecanoic9.54^c^1.76^a^4.01^b^0.720.0001∑ SFA26.51^c^12.81^a^20.81^b^1.260.0001Myristoleic acid4.32^a^8.22^c^5.83^b^1.710.0001Oleic acid8.19^c^1.27^a^4.98^b^2.810.0001Palmitoleic acid5.41^a^7.81^c^6.33^b^1.880.001cis-10-heptadecanoic2.51^a^3.72^b^5.41^c^1.310.0001cis-10-Pentadecanoic acid2.752.522.910.510.32∑ MUFA23.1123.5125.512.070.054Arachidonic acid5.43^a^6.61^ab^6.83^b^0.270.081gamma-Linolenic acid7.01^a^9.11^b^7.75^ab^0.310.018Homo-γ-linolenic acid17.41^a^26.53^c^19.15^b^0.880.0001Linolelaidic acid5.55^b^1.61^a^1.37^a^0.450.0001Linoleic acid4.11^a^5.81^c^4.95^b^0.610.001Linolenic acid4.66^a^6.81^c^5.49^b^0.610.0001Eicosapentaenoic acid6.31^a^7.27^ab^8.17^b^0.750.03∑ PUFA50.47^a^63.71^c^53.73^b^2.010.001SFA = saturated fatty acids; MUFA = Mono unsaturated fatty acids; PUFA = Poly unsaturated fatty acids^a,b,c,d^Means within a row with different subscripts differ significantly (p < 0.05). SEM = Standard error of means. CC = goats supplemented with non-supplemented diet; AZ10 = goats supplemented 10% azolla; AZ20 = goats supplemented with 20% azolla

Correlation analysis

Pearson correlation analysis was conducted between growth performance, rumen fermentation parameters, relative abundances of rumen bacteria, carcass characteristics, meat quality parameters, and meat fatty acids profile. The correlation relationships were visualized in the heatmap (Supplementary Figure S2). The heatmap revealed positive and negative correlation relationships. Average daily gain correlated positively with the relative abundances of phylum Firmicutes, and genera Acetitomaculum, Butyrivibrio, Selenomonas, Quinella, and Christensenellaceae R-7 group, as well as VFA production and meat PUFA.

Discussion

Nutritive value of Azolla

Azolla pinnata has considerable nutrients, bioactive compounds, and both saturated and unsaturated fatty acids. These components modulate rumen microbiota and fermentation, thereby enhancing animal performance and the quality of animal products. The nutritional value of Azolla varies depending on environmental conditions and management system (Pillai et al. 2002; Muradov et al. 2014; Abd-Elgwad et al. 2025). The chemical composition of Azolla in the present study was in the range of previous studies (Mithraja et al. 2011; El Naggar and El-Mesery 2022; Hassanein et al. 2023). The proportions of polyphenols, tannins, and flavonoids in the current study were in the range of previous studies (Tran et al. 2020; Abd-Elgwad et al. 2025; Phesatcha et al. 2025). Phytochemicals affect rumen microbial fermentation and improve animal health (Abd-Elgwad et al. 2025; Phesatcha et al. 2025). Furthermore, Azolla contains a variety of fatty acids (Kösesakal and Yıldız 2019) that affect rumen fermentation and the quality of animal products (Rabee et al. 2024, 2025). Subsequently, Azolla supplementation level affects the composition of the animal diet, which affects the rumen microbial community, rumen fermentation, animal performance, and animal products.

Effect of Azolla on the diversity and composition of rumen bacteria and fermentation

Alpha diversity of bacterial community was higher in the supplemented groups (AZ10, AZ20), which agrees with lambs fed Ulva spp (De la Cruz Gómez et al. 2024) and sheep supplemented with microalgae (Rabee et al. 2022). De la Cruz Gómez et al. (2024) reported that nutrients and bioactive compounds with antimicrobial properties in macroalgae modify rumen microbiota. Higher microbial diversity was associated with higher energy metabolism, forage digestion, and faster adaptation to forage diet in weaned goats (Belanche et al. 2023).

The bacterial community was dominated by members of the phyla Bacteroidota and Firmicutes, which agrees with in vitro study on Azolla-supplemented diets (Abd-Elgwad et al. 2025), and lambs fed Ulva spp (De la Cruz Gómez et al. 2024). Within Bacteroidota, Prevotella and Rikenellaceae RC9 gut group were the most abundant genera. Similar findings were obtained by studies on Azolla and other phytochemical sources (Rabee et al. 2024; Abd-Elgwad et al. 2025). The Rikenellaceae RC9 gut group is a fiber-degrading bacteria and produces acetic and propionic acids, and succinate, which consumes hydrogen from the rumen and could reduce methane production (Andrade et al. 2022). Prevotella plays a central role in rumen fermentation by degrading proteins, peptides, and hemicellulose and producing propionate (Abd-Elgwad et al. 2025).

The members of the phylum Firmicutes were affected by Azolla supplementation. This is consistent with studies on Azolla and seaweeds (De la Cruz Gómez et al. 2024; Abd-Elgwad et al. 2025). Azolla supplementation increased Acetitomaculum, Butyrivibrio, Quinella, NK4A214 group, and Christensenellaceae R-7 group. Butyrivibrio degrades a wide range of substrates such as cellulose, hemicellulose, pectin, amylose, and protein, and is involved in biohydrogenation, and produces butyric acid, which affects meat quality and decline methane production (Qi et al. 2024). It also degrades some types of phytochemicals, such as tannins (Rabee et al. 2024), which may explain its higher prevalence in azolla-supplemented groups and demonstrates the positive correlation between ADG and Butyrivibrio (Supplementary Figure S2).

Christensenellaceae R-7 group was higher in the Azolla-supplemented groups. This genus survives the tannins and other phytochemicals (Rabee et al. 2024) and has a potential role in fiber and protein digestion and produces acetic and butyric acids, which explains its higher prevalence in efficient animals (Bach et al. 2019; Huang et al. 2021). Acetitomaculum utilizes hydrogen to produce acetic acid, which reduces methane production and energy loss, and enhances feed efficiency (McLoughlin et al. 2023). This speculation is supported by the positive correlation between this genus and ADG (Supplementary Figure S2). Genuse Quinella consumes hydrogen in the rumen to produce lactate and propionate, contributing to lower methane production and higher feed efficiency (Kumar et al. 2022). This genus was increased in Azolla-fed goats, which agrees with findings in black goats fed fermented herbal tea residue rich in phenolic compounds (Wang et al. 2023; Zhuang et al. 2021). The NK4A214 group, an unclassified bacteria, has been positively correlated with improved growth performance in goats (Chen et al. 2024).

The negative impacts of Azolla on some rumen bacteria

Several Firmicutes genera were declined with Azolla supplementation, including Lachnospiraceae NK3A20 group, Mogibacterium, Sharpea, and Succiniclasticum. Lachnospiraceae NK3A20 group is involved in carbohydrate metabolism and the production of acetic and butyric acids (Hou et al. 2025). This candidate genus decreased in the diets supplemented with grape pomace, which contains phenols (Khiaosa-ard et al. 2023), indicating the sensitivity of this bacterial group to phenolic compounds present in the Azolla. Mogibacterium has also been shown to decline in response to phytochemicals in goats’ diet (Rabee et al. 2024) and is associated with lower average daily gain in sheep (McLoughlin et al. 2020). This may support the current findings and indicates the sensitivity of this bacteria to plant secondary metabolites. Succiniclasticum, which converts succinate to propionic acid (Qi et al. 2024) was declined in the rumen of lambs supplemented with tannins from Caesalpinia spinosa (Salami et al. 2018). Additionally, genus Fretibacterium within the phylum Synergistota declined in Azolla-supplemented groups, consistent with findings in sheep supplemented with garlic skin, where it was positively correlated with long-chain fatty acids in rumen and milk fat (Zhu et al. 2021; Yu et al. 2025).

Thus, the composition of Azolla (nutrients and phytochemicals) modulates rumen bacteria. Nutrients in Azolla provide the microbial community with diversified growth substrates. Furthermore, phytochemicals have negative effects on some bacteria, while other bacteria survive or degrade different types of phytochemicals (Salami et al. 2018; Rabee et al. 2024).

Effect of Azolla on rumen fermentation parameters

The increment in the fiber-degrading bacteria due to Azolla supplementation contributes to improved feed utilization (Rabee et al. 2024; Abd-Elgwad et al. 2025; Phesatcha et al. 2025), which demonstrates higher total VFA, acetic, and butyric in the AZ10 group. Similar findings were obtained by previous studies on Azolla, seaweeds, and phytogenic compounds (De la Cruz Gómez et al. 2024; Rabee et al. 2024; Abd-Elgwad et al. 2025). Similar increases in VFA production were reported in lambs supplemented with 10% Azolla (Abou El-Fadel et al. 2020) and goats supplemented with two levels of Azolla (Hassanein et al. 2023).

Effect of Azolla supplementation on feed intake and growth performance

The modulation in the rumen bacteria and higher VFA in the AZ10 group were aligned with higher feed intake and growth rates, and is supported by a positive correlation between ADG, fiber-degrading bacteria, and VFA production (Supplementary Figure S2). The improvement in the growth performance observed in AZ10 may be attributed to improved digestibility and VFA production **(**Rabee et al. 2024, 2025). Similarly, a higher growth rate was reported in lambs fed diets contained 10 and 20% of Azolla (Vahedi et al. 2021).

Additionally, the higher growth rate in AZ10 could be due to the presence of nutrients, minerals, vitamins, and bioactive compounds that support digestion and overall health by enhancing immunity and antioxidant capacity (Al-Suwaiegh 2023). Moreover, the phytochemicals have been shown to suppress the rumen methanogens and reduce methane production (Rabee et al. 2024), which improves feed efficiency as methane production represents a loss in gross energy intake. These compounds also exhibit antimicrobial properties against gut pathogens, contributing to improved animal performance and immune response (Phesatcha et al. 2025; Rabee et al. 2025).

Replacing 20% of CFM by Azolla increased body weight gain compared to the control, which agrees with results on Ardi goats (Al-Suwaiegh 2023). Lower feed intake and growth rate in the AZ20 group relative to AZ10 may be attributed to the decline in digestibility due to higher fiber and ash (Indira et al. 2009; Hassanein et al. 2023).

Carcass characteristics and meat quality

The higher weights of the head, kidneys, and pelt in supplemented groups are consistent with the increased final body weight (Asizua et al. 2014; Suliman et al. 2025). Additionally, the increase in kidney weight was also reported in sheep fed by-products of Astragalus membranaceus and grape pomace, which are rich in phytogenic compounds (Zhao et al. 2018; Abdallah et al. 2020).

The decline in fat accumulation in the best ribs could be attributed to enhanced fatty acid β-oxidation, likely due to phytogenic compounds in the supplemented Azolla (Rabee et al. 2025). Similar results have been reported in sheep supplemented with Astragalus by-products (Abdallah et al. 2020) and in goats supplemented with herbal plants (Saturno et al. 2020; Rabee et al. 2025).

Meat color influences consumer purchasing decisions and is affected by dietary composition (Abdallah et al. 2020). Meat yellowness observed in Azolla-supplemented groups in the current study could be attributed to the dietary pigments, as Azolla is rich in carotenoids and other pigments (Abou El-Fadel et al. 2020; Rabee et al. 2025). Consistently, an increase in yellowness was previously reported in sheep and goats supplemented with herbal plants (Abdallah et al. 2020; Rabee et al. 2025).

Lower shear force refers to increased tenderness, which enhances meat palatability and consumer acceptance (Al-Moadhen et al. 2024). Moreover, meat pH is an indicator of meat quality as lower pH levels inhibit the growth of putrefactive bacteria (Saturno et al. 2020). Shear force is affected by the meat collagen, fat, and pH, as well as dietary factors (Kannan et al. 2006).

Higher energy and higher protein supply in the form of rumen VFA and microbial protein improve the meat tenderness and decline pH, which decreases the shear force (Kannan et al. 2006; Li et al. 2024). These speculations explain the lower pH and shear force in group AZ10, which showed higher rumen fiber-degrading bacteria and rumen VFA production. Lower shear force in Azolla-supplemented groups agrees with sheep supplemented with Azolla (Vahedi et al. 2021), Astragalus membranaceus by-products (Abdallah et al. 2020), and goats receiving Lasalocid (Suliman et al. 2025). Additionally, the observed decline in the 24h postmortem pH in the AZ10 group aligns with findings in goats supplemented with Lasalocid (Suliman et al. 2025) and herbal plants containing bioactive compounds (Saturno et al. 2020).

The increase in the meat moisture increases the meat juiciness and tenderness and decreases shear force (Abdallah et al. 2020; Saturno et al. 2020). Higher fat feed intake contributes to higher moisture in meat (Goetsch et al. 2011), which demonstrates the higher moisture in group AZ10 had higher extract (EE) feed intake. The increase in meat moisture agrees with the results of sheep supplemented with Astragalus membranaceus by-product (Abdallah et al. 2020).

Fatty acids in the goat meat

Fatty acids content of meat is affected by dietary fatty acids, fatty acids biohydrogenation in the rumen, and fatty acid absorption (Saturno et al. 2020; Rabee et al. 2025). Animal diet affects rumen microbiota and the biohydrogenation of fatty acids in the rumen, which affects fatty acids of animal products (Kannan et al. 2007; Abdallah et al. 2020; Saturno et al. 2020).

Azolla supplementation reduced SFA and improved UFA, aligning with findings in sheep fed Astragalus membranaceus (Abdallah et al. 2020) and goats supplemented with herbal plants (Saturno et al. 2020; Rabee et al. 2025). Notably, some of these fatty acids, such as gamma-Linolenic, homo-γ-linolenic, and linolelaidic, were uniquely present in Azolla-supplemented meat. Orzuna-Orzuna et al. (2023) reported that microalgae, that is higher in PUFA and phytochemicals, improved PUFA and antioxidant capacity in meat. Polyphenols increase PUFA in the meat (Saturno et al. 2020) by protecting the PUFA against the oxidation reaction (Chen et al. 2000).

The content of UFA in meat is affected by rumen microbiota involved in biohydrogenation (Abdallah et al. 2020; Saturno et al. 2020). Some bacteria, such as Butyrivibrio is directly involved in biohydrogenation, while others affect it indirectly by modulating hydrogen availability in the rumen (Dewanckele et al. 2020b; Mackie et al. 2023). For instance, genus Rikenellaceae RC9 gut group (Andrade et al. 2022), Acetitomaculum (McLoughlin et al. 2023), and Quinella (Kumar et al. 2022) use hydrogen in VFA production, which affects the biohydrogenation efficiency (Mackie et al. 2023). Additionally, the supplementation reduced bacterial genera that have a direct role in the biohydrogenation, such as Sharpea (Dewanckele et al. 2020a). On the other hand, PUFAs exhibit toxicity toward gram-positive bacteria and protozoa responsible for biohydrogenation of unsaturated fatty acids (Sun et al. 2022). Furthermore, microalgae supplementation has been shown to disrupt the final phase of biohydrogenation, leading to an accumulation of intermediate compounds such as conjugated linoleic acid (CLA) and trans-11 C18:1 fatty acid (Zhu et al. 2016). Azolla has a symbiotic relationship with microalgae Anabaena Azollae that can be found within ovoid cavities inside the leaves of Azolla (Hassanein et al. 2023). The Azolla-Anabaena system is rich in PUFA (Miranda et al. 2018).

Thus, the Azolla supplementation has direct and indirect roles in increasing UFA in the goats’ meat. The reduction in SFAs and the increase in MUFA and PUFA are associated with reduced cholesterol synthesis, offering health benefits to consumers (Bezerra et al. 2016; Rabee et al. 2025), which is a positive point of Azolla supplementation.

Effect of Azolla on the antioxidant capacity of meat

Azolla is rich in phytochemicals such as phenols, tannins, flavonoids, and saponins, all of which possess antioxidant activities (Hassanein et al. 2023). These compounds can be deposited in the muscles (Abdallah et al. 2020), contributing to the enhanced antioxidant capacity observed in the meat of the AZ20 group. Similar effects have been reported in goats supplemented with seaweed or herbal plants (Kannan et al. 2007; Saturno et al. 2020). Thus, phytochemical-rich feed supplementations, such as Azolla, provide a promising strategy to improve the quality of red meat (Chanjula et al. 2022). Additionally, higher butyric-producing bacteria, such as Butyrivibrio and Christensenellaceae R-7 group in Azolla-supplemented groups, improve the antioxidant capacity of meat by increasing the butyric production in the rumen, which improves the antioxidant capacity of the animal muscles (Huang et al. 2021; Qi et al. 2024; Zhang et al. 2024).

In conclusion, Azolla is a sustainable feed rich in nutrients and bioactive compounds and can be produced at low cost. Azolla supplementation enhanced fiber-degrading bacteria, contributing to improved volatile fatty acid production and feed intake, particularly in the AZ10 group, which was translated into better growth performance. Additionally, Azolla influenced carcass traits by reducing fat deposition in goat carcasses. The supplementation increased unsaturated fatty acids and decreased saturated fatty acids of meat. Increasing the supplementation to 20% reduced the performance of animals compared to animals supplemented with 10% Azolla. Consequently, Azolla can replace 10% of the concentrate feed mixture in the diets of growing goats. This study was constrained by limitations, including a limited number of animals to study more Azolla supplementation levels, such as 15% of the concentrate feed mixture. Moreover, limited funds constrained the repetition of DNA sequencing of discarded samples. Therefore, future studies are recommended to study more supplementation levels with higher animals per group.

Supplementary Information

Supplementary Material 1. Supplementary Material 2. Supplementary Material 3. Supplementary Material 4. Supplementary Material 5. Supplementary Material 6.