Comprehensive Insights into the Transformation of Camellia oleifera Cake during Ammonia-Enhanced Fermentation: Flavor Stabilization and Fungal Community Dynamics

Abstract

This study aimed to evaluate the effects of ammonia-enhanced solid state fermentation (AESSF) on the nutritional profile, structural integrity, flavor dynamics, and fungal community succession of Camellia oleifera cake (COC) for 30-day period to enhance its value as animal feed. AESSF effectively disrupted the recalcitrant lignocellulosic matrix, reducing neutral detergent fiber, acid detergent fiber, and lignin by 17.39%, 16.12%, and 28.04%, respectively, in the group treated with 5% urea. This structural breakdown, confirmed by scanning electron microscopy and X-ray diffraction analysis showing increased porosity and lattice expansion, led to a notable increase in the relative feed value from 63.87 to 85.77–87.12. Nutritionally, AESSF facilitated a genuine protein quality upgrade rather than simple nitrogen enrichment. In the 3% urea treatment, non-protein nitrogen decreased from 11.28% to 1.37%, while true protein content more than doubled (from 7.06% to 15.03%) after 12 days. Furthermore, the concentration of lysine, the first limiting amino acid, increased 3.7-fold compared to the control. Furthermore, the flavor of the COC evolved from a basic fermented character into a stabilized profile after 30 days of AESSF, suggesting a potential for improved palatability as animal feed. Microbial analysis revealed that AESSF reshaped the fungal community by promoting the transition from Ascomycota to Basidiomycota. Correlation analysis identified moisture, pH, and electrical conductivity as the primary environmental filters driving this microbial succession. Notably, Tausonia was selectively enriched, and functional prediction indicated a notable shift toward yeast proliferation, which restructured the growth-form composition and altered metabolite profiles toward a more stable and aromatic character. These findings provide comprehensive insights into how AESSF upgrades COC quality through the interplay of structural disruption, protein transformation and fungal community dynamics, thereby offering a sustainable pathway for the valorization of forestry residues.

Graphical abstract

Keywords

Camellia oleifera cake / Lignocellulose degradation / Nutritional improvement / HS–GC–IMS / Microbial community

Highlight

	● AESSF improves COC fiber degradation, raising DDM and RFV.
	● AESSF loosens COC surface, increasing porosity and enzyme accessibility.
	● AESSF promotes the bioconversion of NPN into microbial TP.
	● AESSF suppresses fusel alcohol production.
	● AESSF reshapes fungal succession, enriching Basidiomycota and late-stage Tausonia .

1 Introduction

The rapid growth in global consumption of livestock products has concurrently escalated the demand for feed grains and exacerbated environmental pressures [1,2]. Camellia oleifera cake (COC) is a common by-product from Camellia seed oil extraction, it is typically used as plant-derived functional protein [3]. However, COC is limited on animal feed due to anti-nutritional factors like tea saponin, tannins, phytic acid, and high crude fiber, which may impair digestion and nutrient absorption [4].

Solid-state fermentation (SSF) is a bioprocess in which microbial metabolism, whether from native microflora or inoculated strains, breaks down macromolecules and eliminates anti-nutritional factors with minimal or no free-flowing water [5,6]. This microbial conversion produces a safe, high-quality feed with substantially improved nutritional value, digestibility, and palatability [7]. SSF facilitates the simultaneous production of multiple hydrolytic and oxidative enzymes from agricultural wastes, which in turn degrade plant structural components to release trapped bioactive compounds and hydrolyze proteins to generate bioactive peptides [8]. However, the highly lignified structure of COC results in a structure that encapsulates nutrients, thereby limiting their accessibility for microbial fermentation. Additionally, fungal contamination (primarily species of Aspergillus and Penicillium) introduced during the harvesting and oil extraction poses a safety risk [9]. These fungi can produce potent mycotoxins, such as aflatoxins, which are heat-stable and can cause hepatotoxicity, reduced immunity, and impaired growth performance in livestock [10]. These limitations hinder the direct application of SSF to COC, underscoring the need for a pretreatment strategy to enhance substrate bioavailability and ensure feed safety.

Ammoniation (typically using urea) has been widely used to increase nitrogen content, disrupt lignocellulosic structure, and improve digestibility of low-quality roughages and agro-industrial byproducts [11,12]. Field applications, such as ammoniated straw, have been promoted in some regions, improving digestibility and helping bridge seasonal feed shortages [13]. In the context of COC, ammoniation disrupts the lignin barrier to release fermentable substrates, while its antibacterial properties inhibit harmful microorganisms [14]. Therefore, integrating ammoniation with SSF offers a promising strategy to overcome the structural and safety barriers of COC, enabling efficient bioconversion and the production of safe, high-quality feed. Despite extensive research on the detoxification and nutritional upgrading of COC, there is limited characterization of the potential of ammonia to act as a decisive ecological driver that modulates the functional dynamics of indigenous fungi toward metabolic stabilization. Therefore, it was hypothesized that the chemical alkalization associated with AESSF would increase substrate accessibility through ammonia-induced cell wall swelling and ester-bond cleavage. Furthermore, the combined stresses of high free ammonia and low temperature (10–15 °C) were expected to function as a selective ecological filter. This mechanism was anticipated to selectively favor psychrotrophic and alkali-tolerant fungal communities, thereby driving a successional shift that optimizes protein upgrading and flavor stabilization. To test this hypothesis, we focused on correlating the changes in nutrient profiles (particularly nitrogen fractions and fiber components) with the micro-morphological alterations, volatile organic compounds (VOCs) and fungal community dynamics, aiming to establish an optimized ammoniation strategy for converting this agro-industrial residue into unconventional feed resources.

2 Materials and Methods

2.1 Determination of physicochemical properties

The fermentation substrates were COC obtained from a professional plantation in Changsha City, Hunan Province, China. The seeds were harvested from mature trees in their full-fruit period, with an approximate age of 10–15 years. Ground COC was treated with 0, 1%, 3%, or 5% urea (designated CK, Am1, Am3, and Am5, respectively). To ensure a homogeneous distribution and consistent alkalization, the required amount of urea for each treatment was completely dissolved in distilled water and then sprayed evenly onto the COC powder using a fine-mist sprayer. The final moisture content was adjusted to 40% to provide an optimal environment for microbial metabolic activity, while the matrix was being continuously stirred and mechanically mixed for 5 min to achieve a high degree of homogeneity. The prepared substrates were then transferred to 3 L anaerobic fermenters to undergo spontaneous solid-state fermentation, relying on the indigenous microbial community already present in the COC. The fermentation was conducted at a temperature-controlled range of 10–15 °C for 30 days, simulating the typical ambient conditions of traditional on-farm ammoniation in late autumn or winter. All treatments were performed in triplicate. Qualitative sensory evaluation, including the assessment of odor, color, texture, and visible fungal growth, was performed at each sampling time point by a descriptive sensory panel of trained laboratory personnel. These observations provided a preliminary screening to evaluate the preservation quality and product stability across all treatment groups. For dry matter and moisture content, fresh samples were oven-dried at 105 °C to constant weight. For pH and electrical conductivity (EC), fresh samples were mixed with distilled water (1:10 w/v), agitated for 30 min, and the supernatant was measured after settling.

2.2 Determination of lignocellulose content and relative feed value

Neutral detergent fiber (NDF), acid detergent fiber (ADF), and acid detergent lignin (ADL) were determined using the Van Soest method [15]. Hemicellulose and cellulose contents were calculated as NDF minus ADF and ADF minus ADL, respectively. Relative Feed Value (RFV) was calculated according to the following formulas [16].

(1)\text{DDM}\left(\text{Digestible dry matter}\text{\%}\right)=88.9-\left(\text{0.779 × ADF}\text{\%}\right)

(2)\text{DMI}\left(\text{Dry matter intake}\text{\%}\right)=120/\text{NDF}\text{\%}

(3)\text{RFV =}\left(\text{DDM × DMI}\right)/1.29

2.3 Determination of nitrogen fractions and reducing sugar contents

The nitrogen fractions and reducing sugar contents of COC were systematically analyzed to monitor the biotransformation process. Total nitrogen (TN) was determined using the alkaline potassium persulfate digestion method. Briefly, 0.50 g of sample was digested with an alkaline potassium persulfate solution (40 g K₂S₂O₈ and 15 g NaOH per liter) at 121 °C autoclaving for 30 min. The absorbance of the supernatant was measured at 220 nm and 275 nm (A = A₂₂₀ − 2A₂₇₅), and crude protein (CP) was calculated as TN × 6.25. True protein (TP) was measured using the trichloroacetic acid (TCA) precipitation method. One gram of sample was boiled with 15 mL of distilled water for 10 min, followed by the addition of 15 mL of 10% (w/v) TCA. After precipitating at 4 °C for 2 h, the mixture was filtered. The residue was washed with 50 mL of 2.5% TCA and subjected to the alkaline potassium persulfate digestion method to determine the protein nitrogen (PN). TP was calculated as PN × 6.25. Non-protein nitrogen (NPN) was subsequently derived as the difference between CP and TP. Reducing sugar content was determined using the 3,5-dinitrosalicylic acid (DNS) method. Briefly, 1.0 g of the fermented sample was mixed with 20 mL of distilled water and agitated for 1 h to extract soluble sugars. After centrifugation (4000 r/min, 10 min), the supernatant was reacted with DNS reagent in a boiling water bath for 5 min. The absorbance was then measured at 540 nm. Soluble protein contents were quantified via the Coomassie Brilliant Blue method, with absorbance read at 595 nm. Free amino acids were analyzed using a Biochrom 30 + Amino Acid Analyzer (Biochrom Ltd., UK) following cation exchange chromatography and post-column ninhydrin derivatization. The absorbance was then measured by a microplate reader (Infinite E Plex, Switzerland).

2.4 Characterization of morphological structure

Samples were mixed with dry KBr (1:100, w/w) and pressed into transparent discs. Fourier transform infrared spectroscopy (FTIR) spectra were recorded on a Nicolet iS20 FTIR spectrometer (Thermo, USA). The crystalline structure and phase composition were analyzed by X-ray diffraction (XRD, SmartLab, Rigaku, Japan). The surface morphology of the samples was observed using scanning electron microscope (SEM, TESCAN, Czech Republic).

2.5 Gas chromatography-ion mobility spectrometry analysis

The VOCs of COC during AESSF were analyzed using a FlavourSpec^® Flavor Headspace–gas chromatography–ion mobility spectrometry (HS–GC–IMS, G.A.S., Germany) instrument, as previously described by Zhu et al. [17]. Samples collected at different fermentation time points (e.g., CK-18 denotes a control sample fermented for 18 days) were precisely weighed into 20 mL headspace vials and transferred to the autosampler tray. Each sample was then incubated at 80 °C for 20 min. Subsequently, a 0.1 mL aliquot of the headspace gas was automatically injected into the GC–IMS column via a heated syringe (50 °C) under the specified operating conditions. All analyses were performed in triplicate.

Gas chromatographic separation was achieved using an MXT-5 capillary column (15 m × 0.53 mm × 1 μm) maintained at 60 °C. High-purity nitrogen served as the drift gas at a constant flow rate of 150 mL/min. High-purity nitrogen was also employed as the carrier gas, following a programmed flow rate: an initial flow rate of 2 mL/min was held for 2 min, then linearly increased to 100 mL/min over 18 min, resulting in a total run time of 20 min. A series of n-ketones (C4–C9) were employed as external standards to calculate the retention index of each volatile compound based on its retention time. Qualitative identification was performed by cross-referencing the calculated retention indexs and the ion migration drift times with the NIST 2020 gas chromatography retention index database and the built-in IMS database of the VOCal software.

2.6 Fungi communities sequencing

Total DNA was eluted in 50 μL elution buffer and stored at −80 °C. The internal transcribed spacer 1 (ITS1) region of the fungal ribosomal RNA gene was amplified using the specific primers ITS1-F (5'-CTTGGTCATTTAGAGGAAGTAA-3') and ITS2R (5'-GCTGCGTTCTTCATCGATGC-3'). Polymerase chain reaction (PCR) amplification was performed in a total volume of 25 μL reaction mixture containing 25 ng of template DNA, 12.5 μL PCR Premix, and 2.5 μL of each primer. The PCR thermal cycling conditions consisted of an initial denaturation at 94 °C for 5 min, followed by 25 cycles consisting of denaturation at 94 °C for 30 s, annealing at 53 °C for 30 s, and extension at 72 °C for 45 s, with a final extension of 5 min at 72 °C. PCR amplicons were purified with Vazyme VAHTSTM DNA Clean Beads (Vazyme, China). The PCR products were confirmed by 2% agarose gel electrophoresis and purified using Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen, USA). The purified products were then used to construct a sequencing library, and the library quality was assessed on an Agilent 2100 Bioanalyzer (Agilent, USA). Finally, the libraries were sequenced on the Illumina MiSeq PE300 platform at Personal Biotechnology Co., Ltd., China.

2.7 Sequence analysis

Experimental data for physicochemical properties and nutritional components were evaluated using Two-way Analysis of Variance (ANOVA) by Tukey’s Honestly Significant Difference test. Differences were considered statistically significant at P < 0.05.

Microbiome bioinformatics were performed with QIIME2 2024.5 with slight modification [18]. Briefly, raw sequence data were demultiplexed using the demux plugin following by primers cutting with cutadapt plugin. Sequences were then quality filtered, denoised, merged and chimera removed using the DADA2 plugin. High-throughput sequencing data were deposited in the NCBI Sequence Read Archive (Bioproject ID PRJNA1276274).

Alpha diversity (Shannon, Simpson and Chao) was calculated; richness was identified by the amplicon sequence variants (ASVs) based on 100% similarity. One-way ANOVA was performed to determine the significance of microbial data. A P-value of < 0.05 was considered statistically significant. Beta diversity analysis was performed to investigate the structural variation of microbial communities across samples using Bray-Curtis distance. The statistical significance of community differences among treatment groups and fermentation stages was evaluated using Permutational Multivariate Analysis of Variance (PERMANOVA). Taxonomy was assigned to ASVs using the classify-sklearn naïve Bayes taxonomy classifier in feature classifier plugin [19] against UNITE Release 9.0 Database [20]. The relationships between fungal community structure and environmental factors were assessed as follows: the interactions among different ASVs were analyzed using the Pearson correlation coefficient, and the influence of environmental factors on specific microbial groups was further evaluated by the Mantel test. Linear discriminant analysis effect size (LEfSe) was performed to detect differentially abundant taxa across groups using the default parameters. The FUNGuild database was utilized to infer the functional roles and trophic modes of the identified fungal ASVs [21].

3 Results and Discussion

3.1 AESSF modulates appearance and physicochemical profiles

To investigate whether AESSF alters the appearance of COC, samples were collected and photographed on days 0, 12, 18, and 30 of cultivation. As shown in Fig. 1A, no visible differences were observed among CK, Am3, and Am5 at day 0. After 12 days, CK and Am1 exhibited more flocculent, clustered white or cyan fungi, while its surface remained yellowish-brown. In contrast, Am3 and Am5 appeared darker with a blackish coloration. By day 18, differences between Am3 and Am5 had further diminished. At day 30, CK and Am1 were completely encased in cyan-green fungal, whereas Am3 and Am5 appeared black with minimal visible surface microbes and no discernible differences between them.

In Fig. 1B, dry matter of all treatments gradually decreased to 18–30 d, with a more pronounced decline in CK at 30 d (55.9%) than in Am3 (59.4%). This suggests greater dry matter loss in the untreated control, while urea helped decrease the dry matter loss in the later stage. Similar reductions or modifications of dry matter during urea treatment have been reported for corn straw and açaí seeds, where urea and added moisture alter water content and structural carbohydrates [22,23].

Moisture content plays a critical role in microbial growth, metabolic activity, and reaction homogeneity. As illustrated in Fig. 1C, the moisture content of each treatment gradually increased and remained within the range of 30%–50%, which is generally considered suitable for achieving optimal microbial growth and enzyme activity throughout the entire AESSF process [24]. It is worth noting that, moisture increased gradually from day 18 to day 30 in CK and Am1, which was higher than that of Am3 and Am5. This trend is primarily attributed to the metabolic activity of the abundant fungal community utilizing residual oxygen trapped within the porous inter-particle spaces of the ground COC and the fermenter’s headspace. During the degradation of organic matter (especially carbohydrates), microorganisms produce carbon dioxide, heat, and metabolic water. In contrast, for the Am3 and Am5 groups, the biochemical process of urea hydrolysis actively consumes water molecules. This substantial water-consuming reaction, combined with the inhibition of fungal overgrowth by ammonia, explains why moisture levels in the high-urea treatments remained lower and more stable compared to the CK and Am1 groups. Consequently, excessive moisture in the CK and Am1 will promote the overgrowth of contaminating microorganisms.

Initial pH values ranged from 6.14 (CK) to 6.75 (Am5), increasing with higher urea addition. This dose-dependent increase is attributable to urea hydrolysis, which produces NH₃, CO₂ and H₂O; the subsequent dissolution of NH₃ in water forms NH₄⁺ and OH⁻, thereby elevating the pH, with Am5 exhibiting the highest value on day 0. After 30 days, pH values declined to a range of 5.52–5.84. A fluctuating decline in pH was observed in Fig. 1D, with Am5 showing the largest decrease among all treatments. This decline is attributed to the microbial fermentation of sugars into ethanol and its subsequent metabolism into various organic acids. Zhang et al. demonstrated that the accumulation of acidic substances is the main driving factor of pH decline [25].

The initial EC of CK was 7.44 mS·cm⁻¹ and increased gradually increase to 8.94 mS·cm⁻¹ after 30 days (Fig. 1E). During the same period, the EC of the Am5 group increased to 10.07 mS·cm⁻¹ by the end of fermentation. Notably, the Am3 group exhibited the highest conductivity among all treatments, reaching a maximum value of 12.95 mS·cm⁻¹ on day 24. Conductivity values remained relatively stable during the initial phase (days 0–13). However, a marked increase was observed after day 13, particularly in the Am3 and Am5, likely due to intensified metabolic activity during AESSF process [26].

Notably, while basic nutritional profiles were evaluated for all groups, the Am1 (1% urea) exhibited sub-optimal sensory characteristics, such as persistent mold growth and unstable odors throughout the fermentation period (Table S1). These observations indicate that 1% urea is insufficient to achieve the desired flavor stabilization and microbial control. Therefore, the subsequent advanced mechanistic investigations focused on the CK, Am3, and Am5 groups, utilizing structural characterization (SEM, XRD, and FTIR), flavor profiling (HS–GC–IMS), and fungal community sequencing to specifically elucidate the pathways of successful transformation and stabilization.

3.2 AESSF restructures fiber and nutrient composition, enhancing feed value

AESSF treatments markedly improved fiber quality relative to the untreated control (Table 1), rendering COC a more effective functional protein and fiber source for ruminants (e.g., cattle and sheep). In ruminant nutrition, the observed reduction in NDF and ADF is highly appropriate, as it signifies the disruption of the recalcitrant lignocellulosic matrix. In particular, Am5 treatment reduced NDF by 17.39% and ADF by 16.12%, indicating substantial disruption of the lignocellulosic complex. These reductions are greater than those reported for Citronella waste, where combined ammoniation and fermentation reduced NDF by 14.08% and ADF by 14.28% [11]. Overall, AESSF (Am3 and Am5) effectively decreased structural fibers and lignin contents. Specifically, ADL content in the Am5 group was reduced by 28.04% relative to the control, indicating a substantial degradation of the recalcitrant lignin barrier. The DDM of COC increased from 49.75% to approximately 55%–56% after AESSF, in line with the concomitant decline in ADF. Consistent with previous findings on ammoniated corn and rice straw, ammoniation markedly enhanced digestibility of DM, NDF, and ADF in low-quality roughages [27,28]. Improved fiber digestibility is generally associated with increased DMI and better production performance. In this study, the DMI increased from 1.66% in the CK group to 2.00% in the Am5 group. This suggested that ammoniation attenuated the “rumen fill” effect, where bulky and poorly digestible fiber restricts total feed intake, by shortening fiber retention time and improving the passage rate [29]. Notably, AESSF increased RFV from 63.87 to 85.77–87.12, a level comparable to medium-grade alfalfa hay. This improvement reflected the inverse relationship between fiber content and forage quality: as ADF and NDF decrease, both digestible DDM and potential DMI increase. Consistent with previous studies, ammonia-based pretreatment of lignocellulosic feedstocks enhances both their digestibility and energy utilization efficiency [30,31].

3.3 AESSF optimizes nitrogen fractions and protein quality

To further evaluate the nutritional upgrading of COC during AESSF, the dynamic changes in CP, TP, and NPN were systematically monitored (Figs. 2A–2C). The initial CP content was 12.60% in CK, 18.31% in Am3 and 23.13% in Am5, reflecting the incorporation of exogenous nitrogen. During the fermentation process, the CP content in AESSF (Am3 and Am5) showed a gradual decrease, which can be attributed to the loss of dry matter and the partial volatilization of ammonia under alkaline conditions. However, a more critical transition occurred in the protein quality. The TP content, which represents the actual nutritional protein available for livestock, exhibited a remarkable increase in the AESSF groups. In the Am3 treatment, TP jumped from an initial 7.06% to a peak of 15.03% at day 12, maintaining a significantly higher level than the control throughout the period. This trend was inversely mirrored by the NPN levels, which plummeted from 11.28% to 1.37% in the Am3 group during the first 12 days. The rise in TP together with the sharp decline in NPN indicates active microbial nitrogen assimilation and protein biosynthesis, consistent with the established role of urea and other NPN sources as nitrogen donors for microbial growth [32]. These findings demonstrate that AESSF improved COC converting inorganic NPN into nutritionally meaningful TP. It is noteworthy that while the Am5 group possessed the highest CP, its TP synthesis was significantly lower than that of the Am3 group. Excessive nitrogen in Am5 (5% urea) likely triggers an ammonia inhibition effect, where excessively high free ammonia and pH levels reduced conversion efficiency and increased nitrogen loss [33]. In contrast, Am3 appeared to favor a more balanced carbon-nitrogen relationship for microbial protein formation. Overall, these results indicate that AESSF successfully shifted COC from simple nitrogen enrichment toward substantial protein quality upgrading, transforming exogenous nitrogen into microbial true protein with greater nutritional value for animal feeding.

Furthermore, the TP content in the AESSF treatments reached a peak between day 12 and day 18, aligning perfectly with the observed trends in pH stabilization and sugar depletion. This period marks a metabolic golden spot where the chemical disruption of the lignocellulosic matrix has released sufficient fermentable sugars to support a surge in the yeast population. This timing is consistent with a staged SSF process in which lignocellulose disruption first releases fermentable sugars and then supports rapid yeast-driven protein accumulation [34]. After day 18, the stagnation or slight decline in TP content can be attributed to the exhaustion of easily fermentable carbon sources and the transition of the microbial community into a maintenance or decline phase. These results further reinforce the suggestion that a fermentation period of 12–18 days is optimal for balancing protein quality upgrading with production efficiency.

Compared with the control, AESSF (Am3 and Am5) treatments reshaped the time course of reducing sugar content (Fig. 2D), characterized by a faster decline at the early stage and a more stable profile thereafter. This pattern indicated a more efficient release and subsequent microbial utilization of fermentable sugars during fermentation [35,36]. The lower residual reducing sugar content in AESSF groups does not contradict fiber degradation; rather, it reflects a dynamic equilibrium where the rate of microbial consumption exceeds the rate of saccharification from the disrupted lignocellulosic matrix. This high consumption rate is explicitly corroborated by the synchronized surge in TP observed in AESSF groups. As NPN was rapidly assimilated, the microbial community utilized the released sugars as essential carbon skeletons for the biosynthesis of new microbial proteins, resulting in the doubling of TP content in the Am3 group (Fig. 2B). Under Am3 and Am5 conditions, the degradation dynamics of reducing sugars were more pronounced and better controlled. This is consistent with the view that ammonia-assisted pretreatments can enhance saccharification efficiency and increase the availability of fermentable sugars, thereby improving downstream fermentation performance and product quality [37]. During AESSF, soluble protein content ranged from 1.16% to 3.33% (Fig. 2E). In CK, soluble protein remained relatively stable at approximately 2.85%–3.20% during the early stage (0–8 d), but then decreased progressively to 1.16% by day 30, indicating a substantial loss of soluble protein in the late fermentation phase. In contrast, Am3 maintained comparatively high soluble protein throughout fermentation: values remained above 2.70% during 0–18 d with minimal fluctuations, followed by a transient dip to 1.50% at day 24, and a recovery to 2.12% by day 30. Am5 exhibited greater fluctuations during the early stage (decreasing to 2.29% at day 2 and increasing to 3.25% at day 4). However, from day 8 to day 30, soluble protein levels were sustained within a higher range of 2.38%–3.18%, notably exceeding the corresponding late-stage levels in CK. This preservation of soluble nitrogen coincides with the peak accumulation of TP (day 12–18), suggesting that the AESSF-reshaped community not only synthesized more microbial protein but also maintained it in a more soluble and accessible form. Overall, AESSF helped preserve protein in more soluble and nutritionally favorable forms, in line with reports that structural modification can significantly enhance the solubility and functional profiles of protein substrates [38]. Thus, AESSF appeared to be an effective strategy for maintaining higher soluble protein levels over prolonged fermentation, with promising potential to enhance the protein nutritional value of the fermented product.

The functional properties of proteins were determined by their amino acid composition. COC contains 17 amino acids (Fig. S1), dominated by proline (Pro, 45.18%) and arginine (Arg, 13.28%). Notably, COC is particularly rich in Arg, as reflected by its low Lys/Arg ratio (0.06 mg·g⁻¹), which is markedly lower than that of casein (1.89 mg·g⁻¹) and milk protein (2.29 mg·g⁻¹). Such a profile has been associated with favorable effects on blood lipids and a potential reduction in cardiovascular disease risk via cholesterol modulation [39]. In CK, Arg and Glu were the predominant amino acids, at 2.75 mg·g⁻¹ and 0.81 mg·g⁻¹, respectively, whereas lysine (Lys, the first limiting amino acid in cereals) was present at a low level [38]. Notably, following AESSF, the Lys concentration in the Am3 treatment substantially increased, reaching a level 3.7-fold higher than that of the CK group. This substantial enrichment improves the balance of essential amino acids, making the fermented product a more suitable as a feed protein source [40]. The total free amino acid content of COC hydrolysates decreased from 6.08 mg·g⁻¹ to 5.11 mg·g⁻¹ (Am3) and 4.19 mg·g⁻¹ (Am5). This reduction is likely related to fermentation induced protein aggregation and conversion of soluble peptides into less soluble or higher molecular weight structures.

3.4 AESSF disrupts the lignocellulosic architecture, increasing the structural accessibility

The nearly identical FTIR spectra observed for CK, Am3, and Am5 (Fig. 3A) demonstrate that the core functional groups and backbone structures remained largely intact throughout 30-days AESSF. The peak observed at 3424 cm⁻¹, assigned to the O–H stretching vibration [41], exhibited a weakened Am5 absorption, suggesting the disruption of the internal hydrogen-bonding network in cellulose [42]. Peaks observed at 2925 cm⁻¹ are attributed to C–H stretching vibrations, a characteristic feature of aliphatic chains. Their presence in the spectrum of COC suggests the existence of lipidic or other aliphatic constituents [43]. The weakened small peak at 1752 cm⁻¹ in Am3 and Am5 represented the partial degradation of hemicellulose [42].

The XRD patterns exhibited characteristic diffraction peaks near 22.5°(Fig. 3B), corresponding to cellulose I and amorphous polysaccharides [44]. Compared to CK, Am5 exhibited pronounced peak broadening, indicating greater loss of structural order. This disruption is likely attributable to preferential hydrolysis of amorphous domains during fermentation, which substantially attenuates diffraction signals [44]. Two mechanisms explain these structural modifications. First, alkaline ammonia penetration cleaves lignin-carbohydrate complexes (e.g., ester and ether bonds), disrupting the lignocellulosic matrix. Second, swelling disrupts hydrogen bonding between cellulose microfibrils, increasing porosity. Additionally, ammoniation may reorganize the hydrogen-bonding network in crystalline cellulose, facilitating allomorph transformation [35]. The resulting changes in inter-sheet spacing and crystallographic structure rearrange inter- and intra-chain hydrogen bonds, contributing to partial decrystallization [35].

Surface micromorphology supports these findings (Fig. 3C). After 30 days AESSF, CK retained a smooth, intact fibrous structure with no visible pores. In contrast, Am3 and Am5 displayed structural collapse, detachment, and dissolution effects more pronounced in Am5. These morphological changes stem from direct ammonia action and subsequent shifts in microbial activity [42]. Microbial growth and extracellular protease secretion disrupt proteins and macromolecules like cellulose, while chemical bond cleavage reduces molecular weight, enhancing solubility and digestibility [25]. Collectively, these results demonstrate that the synergistic effect of ammonia treatment and subsequent microbial fermentation disrupts the COC composite architecture, creating a more porous, disordered surface. The ammonia acts by disrupting the recalcitrant lignin-carbohydrate complexes, thereby increasing the enzyme-accessible surface area for the reshaped fungal community, which further facilitates the biological degradation of structural components and improves overall fermentation efficiency [22,45].

3.5 HS–GC–IMS spectrometry topographic plots

HS–GC–IMS was employed to compare conventional SSF (CK) with AESSF (using Am3 as an example). Prominent signal density was observed within 100–1000 s retention time and 1.0–2.0 normalized drift time ranges, with the majority of VOCs eluting between 150 and 550 s. The term “flavor stabilization” in this study refers to the achievement of a consistent metabolic state where the chemical constituents of the aroma reach a steady-state equilibrium, suppressing the development of off-flavors associated with spontaneous spoilage.

As shown in Figs. S2A and 4A, after 12 days of fermentation, abundant signals were observed in CK-12 and Am3-12, and these signals contributed to the overall aroma profile of COC. In Figs. S2B and 4B, the contrasting backgrounds serve to visualize the relative abundance of VOCs: white indicates comparable levels between the target sample and the reference, while red signifies a higher concentration and blue a lower concentration in the target sample. Analysis of these contrast patterns clearly distinguished the fermentation time points. For both CK and Am3, pronounced differences were observed between day 0 and day 12, suggesting a period of active volatile transformation. Conversely, the comparison between day 12 and day 30 revealed relatively subtle changes across the full retention time range, indicating a stabilization of the volatile profile during the later fermentation stage.

Fifty-five VOCs were identified in CK, including eleven esters, nine aldehydes, seven alcohols, five nitrogen-containing compounds, four ketones, four hydrocarbons, three sulfur-containing compounds, two ethers, one acid, and an additional nine compounds that remained unclassified due to database limitations. The fingerprint in Figs. S2C and 4C visualizes compound abundance across samples. Signal intensity is color-coded, with darker hues representing higher abundance and black indicating levels at or below the lowest quantile of detection.

Esters constituted the predominant class in CK. The identified esters included butyl formate, ethyl acetate (associated with pineapple [46] and fruity [47] aromas), methyl hexanoate, ethyl hexanoate, hexyl propionate, 2-methylpropyl acetate, 2-methylbutyl acetate, 3-methylbutyl ethyl butyrate, ethyl 2-methylpropanoate, ethyl 2-methylbutanoate, and (Z)-3-hexenyl acetate, collectively imparting fruity, floral, and sweet notes to the fermented product. Their formation proceeds primarily via two pathways: enzyme-catalyzed reactions and the esterification of alcohols and acids.

Owing to their low odor thresholds, both the aforementioned esters and the following aldehydes were identified as key flavor contributors in CK [47,48]. The aldehydes, primarily derived from lipid oxidation and the Strecker degradation of amino acids, exhibit pleasant fruity and grassy odors and comprised butanal, 2-methylbutanal (cocoa, almond), 3-methylbutanal (malt), pentanal (almond, malt, pungent) [46], 2-methylpentanal, (E)-2-hexenal, (Z)-4-heptenal, (E)-2-nonenal, and (E,Z)-2,6-nonadienal. The observed reduction in total free amino acids in AESSF treatments (as noted in Section 3.3) suggested that these synthesized amino acids are rapidly incorporated into microbial proteins and biomass rather than accumulating as free intermediates. This high nitrogen-utilization efficiency leads to a lower residual free amino acid pool but a higher quality of total protein, such as the significantly enriched lysine.

Notably, three compounds, 3-methylbutanal, 1-butanol, and ethyl acetate, were detected at the initial stage (CK-0) and remained undetected in the subsequent fermentation phases (Fig. S2C). Mechanistically, 3-methylbutanal is primarily generated from leucine via the Ehrlich pathway or transamination/deoxygenation reactions, with α-keto acid decarboxylase as the key rate-limiting enzyme [49]. 1-Butanol may originate from sugar metabolism, butyrate reduction, or threonine metabolism, while ethyl acetate is synthesized from ethanol and acetic acid via alcohol acyltransferase-catalyzed esterification under microbial action.

Furthermore, in the AESSF group, a total of forty-three VOCs were identified in Am3, including nine alcohols, six nitrogen-containing compounds, five aldehydes, five ketones, four esters, two acids, two ethers, one alkene, one sulfur-containing compound, and ten others. As shown in Fig. 4C, nine compounds were detected at 0 day, namely 2-methylbutan-1-ol, propanal, butyl formate, ethanol, 1-butanol, 3-methylbutanal, 2-methylpropanal, 2-propanol, acetic acid ethyl ester. Because these nine compounds are the immediate products of chemical reactions, rather than metabolic products of microorganisms. The addition of 3% urea significantly increased the pH of COC and provided an exogenous nitrogen source, promoting the vigorous proliferation and metabolic activity of microorganisms such as yeast species.

During 12–18 days, fifteen compounds were detected, including key alcohols such as 3-methylbutan-1-ol, 2-methyl-1-pentanol, 2-furanmethanol, and 2-methyl-2-propanol, along with other ketones and esters. This profile, dominated by alcohols followed by ketones and esters, is characteristic of primary metabolites and early nitrogen metabolites in fermentation. Isoamyl acetate imparts a typical banana-like fruity aroma [50], and is an important flavor ester in fermented foods. The 3-methylbutan-1-ol accumulated in this stage, derived from the leucine Ehrlich pathway [51], served as a key substrate for the subsequent formation of isoamyl acetate. On day 30, several pyrazines including 2-methoxy-3-methylpyrazine, 2,3-dimethyl pyrazine, and ethylpyrazine were detected in Am3. Pyrazines are formed via the aldose-amino acid condensation in the Maillard reaction, which produces unstable Schiff bases that subsequently rearrange into Amadori rearrangement products [52]. These ARPs undergo 2,3-enolization to yield α-keto compounds, which then cyclize with amino compounds to generate pyrazines [25], contributing nutty and roasted notes to COC. After 30 days of the AESSF process, the overall flavor profile of COC seems shifted from a fermented character toward a processed or roasted note. It should be noted that the enrichment of specific VOCs, such as esters and pyrazines, provides insights into the biochemical transformation of the flavor profile. In the context of this study, these shifts were utilized as indirect chemical indicators of flavor evolution during the AESSF process. While these aromatic compounds are generally associated with improved feed quality, they do not constitute direct evidence of animal preference. Actual palatability is a complex sensory and behavioral response that involves factors beyond volatile profiles, such as texture, taste, and individual animal metabolism. Therefore, our findings offer a molecular basis for the potential improvement of COC as feed, but future in vivo animal feeding trials are essential to definitively validate the actual intake and palatability.

Fig. 4D shows the principal component analysis (PCA) chart during different AESSF times, with the first principal component (PC1) accounting for 77% of the variance. By contrast, the second principal component (PC2) accounted for 19%, contributing 96% of the total variation. Complete separation between Am3-0 and Am3-30 was observed along PC1. However, it is worth noting that Am3-12 and Am3-18 displayed a close alignment between the two groups despite the aroma disparities, suggesting that the variations in VOCs between the two samples were minor. Collectively, the PCA plot indicates a four-cluster classification, with Am3-0 and Am3-30 exhibiting the greatest degree of separation.

Overall, after 30 days of conventional SSF, the diverse metabolites of COC may lead to the accumulation of undesirable off-flavor compounds. In contrast, the AESSF process concentrates metabolic pathways, resulting in purer and more aromatic flavor compounds. From the perspective of industrial application, the temporal dynamics of AESSF suggested a highly cost-effective window for production. While the experimental duration was extended to 30 days to verify the long-term stability and complete successional transition of the fungal community, the plateauing of key indicators, such as pH stabilization, true protein contents and flavor fingerprint consistency between day 12 and day 18 is significant. In a large-scale industrial setting, terminating the fermentation process during this period (days 12–18) would be strategically advantageous. Such optimization could reduce the processing cycle by approximately 40%–60%, thereby significantly enhancing the turnover rate of fermenters and reducing associated storage and labor costs. Consequently, the 12–18 day interval appears to be the gold spot for balancing nutritional enhancement with economic efficiency in COC valorization.

3.6 Fungal community and functional dynamics during AESSF

3.6.1 Species relative abundance and diversity

A total of 2,996,694 high-quality sequence reads were obtained from ITS1 rDNA after quality filtering, then assigned into 1529 fungal ASVs. Rarefaction analysis indicated that the current sampling depth was sufficient for revealing the majority of fungal diversity across all fermented COC samples (Fig. S3). As shown in Figs. 5A–5C, the α-diversity analysis results showed that the Shannon and Chao indices of the CK and Am3 treatments decreased over time, indicating that some microorganisms may not adapt to this process and gradually decline. Since the substrate was not sterilized prior to ammonia-treated fermentation, the initiating microbial community gradually shifted from the indigenous microbiota of the to a community selected by the added urea. However, on the eighth day, the Shannon and Simpson diversity indices of the Am3 treatment were significantly higher than those of the CK group, suggesting that the Am3 treatment slowed down the rate of microbial diversity decline. The PCoA results based on Bray-Curtis distance indicate that the fungal community structures of both the CK and Am3 treatments change significantly over time (Figs. 5D–5F). Interestingly, the trends of the changes in the community structures of these two treatments were significantly different: at day 0, the fungal community structures of the two varieties could hardly be distinguished. By day 18 and day 30, the communities became statistically distinct and completely separated in the PCoA space (PERMANOVA P < 0.01; R² = 0.531 and 0.465, respectively), with the treatment effect explains over 46% of the community variance. These results statistically confirmed that the fungal community structures of these two treatments developed into two distinct functional ecological niches under different environmental filters.

3.6.2 Comparison of the taxonomic composition of fungi communities

To investigate the dynamic changes in the fungal community during AESSF effective sequencing reads were classified into different taxon levels. In total, 4 phyla, 201 genera, and 295 species of fungi were identified in the five fermentation samples of the CK, and 4 phyla, 184 genera, and 295 species of fungi were identified in ammonia-treated. The distribution of the ASVs was categorized at the phylum and genus levels. As shown in Fig. 5G, at the initial stage of fermentation, the fungal community was overwhelmingly dominated by Ascomycota ( > 95%), whereas Basidiomycota constituted less than 3%, and both Chytridiomycota and unidentified fungi were extremely scarce. Although the relative abundance of Ascomycota declined as fermentation progressed, it remained the predominant fungal phylum throughout the entire fermentation process. This pattern aligns with results observed in previous studies on fermented feeds [53]. In AESSF group, the relative abundance of Basidiomycota increased to 30.8% after 12 days and peaked at 47.8% on day 18, whereas the maximum abundance in the CK group was limited to 8.86%. In lignocellulose-rich systems, Ascomycota typically dominates the early-to-mid stages of decomposition, while Basidiomycota is often associated with the degradation of recalcitrant substrates, such as lignin, in the later stages. The ammonia treatment pre-degraded the fibers and altered the structure of the lignocellulose complex, thereby creating conditions favorable for the expansion of Basidiomycota in the late phase [54], resulting in the abundance peak observed between days 12 and 18. At the genus level, the relative abundances of the top 20 fungal ASVs were calculated. As shown in Fig. 5H, Penicillium, Cladosporium, Tausonia, Aspergillus and Colletotrichum were identified as the crucial fungal genera throughout the whole COC fermentation process. Initially, Aspergillus exhibited high relative abundance (36.3% in CK, 40.5% in Am3), but decreased drastically by day 8 and nearly disappeared after day 12. Utilizing the nutrient-rich COC, Aspergillus species secreted copious amylases, proteases, and cellulases to rapidly metabolize polysaccharides and proteins, promoting vigorous hyphal growth and spore formation [55]. However, as readily available substrates were consumed, the remaining recalcitrant residues created a selective environment that favored the succession of other fungi (e.g., Basidiomycota) capable of degrading complex materials. Penicillium gradually accumulated over the course of fermentation and dominated the fungal community in the later stages. This success was driven by its ability to secrete abundant proteases and lipases and effectively degrade recalcitrant fibers like cellulose and hemicellulose, thereby promoting deep substrate breakdown and improving product quality [56,57].

Beyond the shifts in fungal community structure, the chemical environment created by AESSF provides a robust mechanism for ensuring feed safety. The high concentrations of free ammonia and the resulting alkaline conditions act as a dual barrier against mycotoxin risks. Specifically, the ammoniation process is a well-established industrial method for the deactivation of aflatoxins [58]. The free ammonia and hydroxyl ions can effectively attack and open the lactone ring of aflatoxin B1, converting it into non-toxic carboxylic acids, thereby eliminating its mutagenicity and toxicity [59]. This chemical detoxification, combined with our microbial findings that the relative abundance of potentially toxigenic genera (e.g., Aspergillus and Penicillium) is significantly suppressed in the Am3 and Am5 groups, suggests that AESSF creates an environment hostile to both the survival of toxigenic molds and the stability of their metabolites. In addition to lignocellulose degradation, the detoxification of camellia saponins is a critical component of COC valorization. These compounds serve as the primary anti-nutritional factors in the material and are responsible for its hemolytic activity and bitter taste. Although direct quantification was not performed, the AESSF environment provides two synergistic pathways for saponin reduction. Chemically, the alkaline environment generated during urea treatment likely facilitates the hydrolysis of alkali-sensitive acyl/ester linkages within camellia saponins, causing structural degradation of these triterpenoid glycosides into less hemolytic derivatives, which may help reduce the bitterness and anti-nutritional effects associated with untreated COC [60]. Biologically, the selective enrichment of specialized yeasts may facilitate saponin transformation, given that some yeasts possess β-glucosidase activity and have been shown to mediate glycoside bioconversion [61]. Therefore, the synergy between chemical ammoniation and microbial succession in AESSF likely provides an effective strategy for mitigating the anti-nutritional constraints of COC, making it a safer and more palatable protein source for ruminants.

Notably, AESSF suppressed fungal growth by increasing the pH and free ammonia nitrogen concentration, conditions known to inhibit spore germination and hyphal development [62]. As a result, while Penicillium still maintained dominance at the end of the process, its relative abundance in the ammoniated group (54.30%) was markedly lower compared to the control group (88.88%). Cladosporium dominated the mid-fermentation stage (day 8) in both CK and Am3, which is consistent with its documented capacity to produce cellulases, hemicellulases, and pectinases, as well as lignin-modifying enzymes such as laccase. These enzymes facilitate the substantial degradation of plant cell walls and enhance nutrient availability during SSF [63]. At the end of fermentation, Cladosporium still persisted and was even better retained in the ammoniated group (14.24% vs. 7.78% in CK), which may be attributed to the relatively high tolerance of certain Cladosporium species to alkaline or ammonium-rich environments and their ability to maintain extracellular enzyme production in the presence of inorganic nitrogen sources [64,65]. Tausonia was a low-abundance genus in the early stage of fermentation, but its relative abundance increased markedly in the late stage, especially under AESSF. In Am3, it reached 30.84% on day 12, climbed to a peak of 47.78% on day 18, and still remained at a relatively high level of 31.17% at the end of fermentation. By contrast, in the CK group, the relative abundance of Tausonia reached a maximum of 8.86% on day 12, followed by a substantial decline to minimal levels during the late fermentation stage. Similar to the “rare-to-dominant” succession patterns reported in other fermentation systems, the selective enrichment of initially rare fungi in the late stage is often associated with their key roles in deep degradation of complex substrates, reutilization of metabolic intermediates, and the formation of flavor and quality attributes [66,67]. Tausonia is significantly correlated with key flavor compounds, participating in the formation or regulation of volatile alcohols, esters, aldehydes, and ketones [68]. The selective enrichment of Tausonia in the mid-to-late stages of AESSF highlights its remarkable adaptation to extreme environmental filters. Its psychrotrophic nature likely provides an advantage at the fermentation temperature of 10–15 °C, because isolates from the basidiomycetous genus Tausonia were classified as psychrotolerant in a cold-environment yeast survey [69]. In addition, extracellular enzymatic activities are common among these cold-adapted yeasts, and Tausonia has shown broad hydrolytic potential [69]. These adaptive traits enable Tausonia to maintain active substrate conversion throughout the fermentation process, thereby securing a significant competitive survival advantage under such challenging environmental conditions.

As shown in Fig. S4, at day 0, CK was characterized by higher relative abundances of Ascomycota taxa such as Cladosporium and Capnodiales, whereas Am3 was enriched in Basidiomycota yeasts belonging to Tremellomycetes (e.g., Tausonia, Mrakiaceae), consistent with the general dominance of Ascomycota and Basidiomycota in fermentation and animal-associated mycobiota [70]. The strongest separation occurred at day 8, when Am3 induced extensive enrichment of multiple orders within Sordariomycetes, Dothideomycetes, and Agaricomycetes, indicating a marked restructuring of the fungal community under ammoniation; similar spatiotemporal shifts in dominant Ascomycota/ Basidiomycota lineages have been reported in Daqu systems, where environmental conditions and Ftime drive community assembly [70]. By day 12, differential taxa were largely restricted to Hypocreales in Am3, suggesting a transient stabilization phase. At day 18, CK became enriched in Eurotiomycetes (e.g., Penicillium and Aspergillaceae), taxa that are also common in environmental fungal communities [55], while Am3 maintained a Basidiomycota-biased profile dominated by Tremellomycetes. By day 30, Am3 still showed significant enrichment of Microbotryomycetes and Tremellomycetes (e.g., Rhodotorula, Tausonia), whereas CK accumulated several unclassified fungal taxa. Overall, these LEfSe-defined biomarkers indicated that ammoniation preferentially promotes Basidiomycota (especially yeast-like Tremellomycetes and Microbotryomycetes), while the conventional solid-state fermentation favors typical Ascomycota genera such as Cladosporium and Penicillium, echoing broader observations that environmental and process parameters govern the balance between Ascomycota- and Basidiomycota-dominated communities in fermentation and gut ecosystems.

3.6.3 Correlation analysis of environmental variables and fungi community

As shown in Fig. 6A, moisture, dry matter content and EC emerge as the dominant drivers of community composition, as indicated by their robust significant correlations with the ASV-based distance matrix (Mantel’s r ≥ 0.4, P < 0.01). At the genus level, different fungal taxa showed distinct response patterns to environmental gradients, consistent with previous reports that pH and EC are key determinants of fungal assemblages [41]. Penicillium were mainly associated with pH and EC, suggesting that this genus preferentially occupies microhabitats defined by specific ionic strength and acidity conditions, in line with the broad but pH-sensitive ecological niche reported for Penicillium in other systems [68]. In contrast, Aspergillus displayed pronounced environmental sensitivity: its ASVs were correlated with moisture and pH and also showed intense positive correlations among themselves, implying a highly coordinated response to environmental fluctuations and potential functional redundancy within the genus. ASVs affiliated with Cladosporium were comparatively less sensitive, responding mainly to variation in EC and pH, which is consistent with the moderate tolerance of many Cladosporium species to physicochemical stress. EC acted as a significant driver (P < 0.01) for several low-abundance or taxonomically unassigned ASVs (e.g., ASV_658, ASV_1130). ASVs belonging to the same genus were predominantly linked by positive correlations, indicating similar ecological niches or cooperative strategies under shared environmental constraints [69]. By contrast, some inter-generic pairs, for example between Penicillium and specific Cladosporium ASVs, were negatively correlated, implying potential competitive exclusion or niche partitioning along moisture, pH and EC gradients. Overall, these results indicate that moisture, dry matter and pH jointly act as primary environmental filters, differentially affecting Penicillium, Aspergillus and Cladosporium, while EC imposes a more selective pressure on particular ASVs and other taxa.

Correlation analysis between the differential genera identified by LEfSe and environmental physicochemical parameters (Fig. S5) indicates that moisture content, dry matter content, and pH emerge as the primary factors associated with microbial community composition. In particular, Rhodotorula and Penicillium were significantly correlated with four of the five measured indicators, with the exception of electrical conductivity, suggesting that these genera are tightly linked to shifts in substrate properties. In addition, Aspergillus, Talaromyces, and Colletotrichum exhibited significant correlations with moisture content, dry matter content, and pH, respectively. These taxa are therefore likely to represent key microbial drivers mediating changes in the physicochemical environment during fermentation.

3.6.4 Fungal functional prediction

Predictive analysis of fungal functional guilds (FUNGuild) showed that CK and Am3 exhibited broadly similar temporal trajectories in ecological functions over the 0–30 d incubation period (Fig. 6B). In both treatments, the relative abundances of endophytes and plant saprotrophs progressively declined with time, consistent with reports that endophytic and symbiotrophic fungi often decrease under intensified management or substrate transformation [70]. This pattern suggested a functional transition of the community from a plant-associated symbiotic/ saprotrophic stage to one increasingly dominated by parasitic and animal-related pathogenic or saprotrophic functions as fermentation proceeds. In the predicted fungal growth forms (Fig. 6C), the CK treatment maintained a relatively stable community structure across all sampling times, with microfungi remaining the overwhelmingly dominant growth form. By contrast, Am3 displayed pronounced temporal dynamics: between days 12 and 18, the relative abundance of yeasts increased sharply, peaking at nearly 50% on day 18 before declining again by day 30. This shift is likely driven by the selective pressure of the high pH and high ammonia concentration created by AESSF, which suppresses the growth of acidophilic filamentous molds while favoring the proliferation of alkali-tolerant Basidiomycota yeasts. These yeasts are more efficient at utilizing the ammonia-released sugars and nitrogen sources, leading to a more stabilized microbial equilibrium. Similar shifts in the dominance of yeast versus filamentous forms have been reported in fermentation ecosystems where changes in nutrient availability deterministically restructure fungal communities and favor specific yeast taxa [71]. These results indicated that Am3 effectively promoted yeast proliferation in the mid-late fermentation phase, thereby altering the original microfungus-dominated growth-form composition and potentially modifying process performance and metabolite profiles. The stabilization of VOC fingerprints further confirm that the AESSF process is not a simple chemical reaction, but a sophisticated bio-transformation. The ammonia serves as a selective “switch” that activates the latent functional potential of the indigenous microbiota, enabling a self-regulating fermentation process without the need for exogenous additives.

AESSF must be recognized as a complex and multi-kingdom spontaneous fermentation process. While the current study prioritized the fungal community because of its superior capacity for degrading the recalcitrant lignocellulosic matrix and its significant role in flavor stabilization, the contribution of bacterial activity cannot be ignored. Furthermore, a fundamental limitation exists regarding the lack of sterile controls. Because spontaneous fermentation was intentionally employed to simulate realistic industrial and on-farm conditions, the individual contributions of purely chemical effects cannot be rigorously distinguished from those of biological biotransformation. Consequently, the observed improvements in the nutritional and structural properties of COC are interpreted as a synergistic outcome of both chemical and biological drivers. Future research utilizing 16S rRNA gene sequencing and sterilized substrates will be essential to provide a more holistic understanding of the bacterial-fungal synergistic mechanisms and to quantify the isolated efficacy of chemical alkalization.

4 Conclusions

In conclusion, this study demonstrates that AESSF is a promising and effective strategy for upgrading the nutritional value and structural characteristics of COC. It achieves a transition from crude protein to true protein by effectively assimilating exogenous nitrogen into microbial biomass. The peak TP accumulation at days 12–18 confirms that a shortened fermentation cycle is sufficient for protein upgrading. This bio-transformation, coupled with recalcitrant fiber disruption and flavor stabilization, suggests the potential for transforming COC into a possible high-quality, stable, and aromatic protein source for ruminants. The interplay is driven by the synergy between chemical de-lignification and an indigenous ecological shift, where environmental filters (pH and nitrogen availability) restructure the fungal community toward a beneficial, yeast-dominated profile. This transition not only enhances nutrient accessibility and protein quality but also stabilizes the flavor profile by modulating core metabolic pathways. Practically, the AESSF-processed COC shows great potential as a cost-effective protein supplement in total mixed rations. These findings provide an integrative framework and a sustainable pathway for the large-scale valorization of agro-industrial lignocellulosic wastes into functional animal nutrition.

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The Author(s) 2026. This article is published by Higher Education Press.