Sericulture Mechanization Poses New Challenges for Environmental Disinfection—Evaluating the Effects of Three Newly Introduced Disinfectants

Abstract

While conventional sericulture has developed effective disinfection methods, the increasing demand for silk and pupae is driving mechanization, potentially altering or introducing silkworm pathogens. New disinfection strategies are essential for sustainable sericulture production. This study first investigated the bacterial community differences between conventional and mechanized silkworm-rearing environments. Then, under the mechanized environment, we evaluated three commercially available disinfectants with different mechanisms: hypochlorous acid (HClO), nano platinum-polyhexamethylene guanide (Pt-PHMG), and medium-chain fatty acids (MCFA). Our results indicated significant bacterial differences between the two environments, with potential pathogenic bacteria present in both environments. Moreover, the bacterial communities remained relatively stable, while conventional disinfection methods were less effective in mechanized conditions. In contrast, regardless of whether they were applied before or after silkworm rearing, all three disinfectants demonstrated significant efficacy, with the total environmental bacterial load reduced by approximately 0.5 to 1 order of magnitude after application. Among them, Pt-PHMG exhibited the best performance by inhibiting pathogens such as Staphylococcus, Enterococcus, and Bacillus, followed by MCFA and HClO. The results also suggested a need for stronger disinfection strategies after silkworm rearing. These findings not only provide important hygiene practices to ensure mechanized silkworm rearing, but also offer valuable insights for the future development of disinfection strategies in modern sericulture.

1. Introduction

The silkworm (Bombyx mori), a lepidopteran insect domesticated for millennia, remains an economically significant species in global agriculture [1]. While traditionally valued for silk production in textiles, contemporary research also highlights the emerging importance of pupae as a multifunctional bioresource. Silkworm pupae contain 71.9% total protein, 20.1% lipids, and 4.0% ash by dry weight [2,3,4,5]. They also harbor diverse bioactive compounds such as flavonoids, which collectively exhibit potential antioxidant, anti-inflammatory, antibacterial, and lipid- and glucose-regulating effects [6,7]. At present, they have gained a wider acceptance due to their rich nutrition and unique flavor [8]. Additionally, silkworm pupae are a promising source of animal feed protein, suitable for poultry, aquaculture, and pigs [9]. They provide essential nutrients for animal growth with a lower risk of allergic reactions [8,10,11].

The growing demand for silk and pupae necessitates an increased production efficiency in sericulture. Mechanization, as a crucial component of the global Green Revolution, is an optimal strategy for improving livestock production efficiency [12,13]. Therefore, conventional small-scale, labor-intensive silkworm rearing has progressively transitioned to large-scale mechanized farming systems (Figure 1). This mechanization serves as the cornerstone of modern sericulture by facilitating industrial-scale operations, enhancing batch productivity, and enabling continuous production cycles. Such advancements boost the overall production output. Nevertheless, this unique high-density and consistent silkworm rearing often leads to disease outbreaks that can cause an over 60% yield loss [14,15]. Moreover, residual pathogens may contaminate surviving silkworms, compromising their products’ commercial quality. These risks underscore the importance of implementing rigorous sanitation practices to control pathogen proliferation in the rearing environment, thereby safeguarding production efficiency [16].

Conventionally, aldehyde and chlorine-based disinfectants are commonly used, with application methods including soaking, spraying, and fumigation [17]. However, sericulture mechanization introduces novel environmental conditions: metal machinery replaces wooden or plastic tools, automated climate controls regulate temperature and humidity, and facilities expand significantly (Figure 1a,b). Since microbial communities exhibit environmental niche specificity [18], these changes may selectively enrich certain microorganisms, reducing conventional disinfectant efficacy. Additionally, aldehyde and chlorine-based formulations have strong corrosive effects on metals, and pose a threat to the precision metal components in automated systems. Conventional application methods cannot be directly applied to large-scale sericulture machinery and expanded spaces, which highlights the urgent need to explore alternative disinfection strategies.

In recent years, there has been a growing interest in the development and optimization of disinfectants, and some of them have been commercialized [19,20,21]. Here, we focus on evaluating the effect of three representative disinfectants when used in the large-scale mechanized sericulture farm. The three disinfectants, namely hypochlorous acid (HClO), nano platinum-polyhexamethylene guanide (Pt-PHMG), and medium-chain fatty acids (MCFA), have different disinfection mechanisms (Figure 2). HClO, due to its strong oxidizing nature and low molecular weight, is uncharged and can easily penetrate cell walls. It rapidly interacts with microbial nucleases, functional enzymes, and surface proteins, thereby eliminating them [22,23]. Research indicates that a mildly acidic HClO disinfectant is more effective at killing bacteria on steel carriers compared to cloth carriers, likely due to the stronger bacterial adsorption on steel carriers [24]. HClO is widely employed in livestock production for disinfection purposes, particularly in the aerosolized disinfection of animal housing facilities [25].Additionally, with its low content of available chlorine, mildly acidic HClO exhibits a weaker corrosiveness to metals, indicating a potential for widespread use in mechanized environments. Pt-PHMG is composed of cage-like PtNPs and PHMG. The PtNPs disrupt the protective peptidoglycan and damage intracellular proteins, lipids, and nucleic acids, leading to growth arrest or the death of microbes [26]. Additionally, the highly catalytic cage-like PtNPs enhance the antibacterial properties of organic acids [27]. PHMG is a cationic surfactant, and its highly active guanidine groups render the polymer positively charged, allowing it to be easily adsorbed by the negatively charged bacterial cell walls and membranes [28]. This adsorption alters cell permeability, resulting in bacterial death. PHMG has been documented in food safety and health-care sectors. It serves as an antimicrobial film component in food packaging to extend the shelf life of meat products [29]. Structurally optimized variants (e.g., through guanidine/alkane ratio modulation) exhibit a superior antibacterial efficacy against clinically resistant pathogens, including methicillin-resistant Staphylococcus areus (MRSA) and Pseudomonas aeruginosa [30]. When cage-like PtNPs are complexed with PHMG, the resulting compound is low-toxic, non-harmful, and non-corrosive [31], thereby achieving a synergistic antibacterial effect [32]. MCFA is a type of saturated fatty acids that has carbon chain lengths ranging from 6 to 12 carbon atoms. It functions as a bio-based non-ionic surfactant, creating gaps in cell membranes and causing leakage of intracellular substances [33,34]. Once inside, MCFA releases hydrogen ions, forcing bacteria to expend energy on H⁺-ATPase pumps for pH stability, disrupting their metabolism and leading to death [35]. As a low-corrosive, bio-derived feed additive [36], MCFA has been extensively used in the livestock industry for poultry, piglets, and dairy cows [35,37,38].

Here, our study first explored environmental microbiome differences between conventional and mechanized silkworm-rearing environments. Subsequently, we systematically compared the efficacy of three disinfectants (HClO, Pt-PHMG, and MCFA), whose comparative performance in mechanized sericulture remains underexplored. This evaluation framework provides critical insights for enhancing large-scale silkworm rearing efficiency and advancing industrialized sericulture practices.

2. Materials and Methods

2.1. Experimental Setup and Sampling

Samples were collected from both the conventional and mechanized silkworm-rearing environments at Nanxun Xunhe Agricultural Development Co., Ltd. in Huzhou City, Zhejiang Province, China (30°46′ N, 120°15′ E). The conventional environment was equipped with several small rearing shelves and trays (Figure 1a). Conventional disinfection had been conducted before this study. The mechanized environment housed four large automated silkworm-rearing machines (Figure 1b), labeled as O/A/B/C. Machine O, similar to the conventional environment, had undergone conventional disinfection before this study, whereas machines A/B/C had just completed a silkworm-rearing cycle and had not yet undergone disinfection (Figure A1 and A2, tables and figures prefixed with ‘A’ are provided in the Appendix A).

In this study, we conducted five comparisons of bacterial communities for different purposes. The first comparison examined the differences between conventional and mechanized environments (Section 3.1). In the ‘Conventional’ group, a total of 6 samples were taken on the tray and shelf of the conventional environment, with 3 replicates collected from each. The ‘Mechanized’ group involved 6 samples from machine O. Samples 1 and 2 were located on the control panel, while samples 3 and 4 were on the tray, and samples 5 and 6 were on the frame (hereafter referred to as the six-point sampling method). The second comparison assessed the initial state of the mechanized environment and the state after being left for 72 h, labeled ‘0 h’ and ‘72 h’, both using the six-point sampling method on machine O (Section 3.2), with a total of 6 samples collected per group. The third comparison evaluated the effectiveness of conventional disinfection in the mechanized environment (Section 3.3). The first set of 18 samples was taken using the six-point method on machines A/B/C, which had not undergone disinfection. For comparison and statistical analysis, each 3 samples from the same sampling point (of different machines) were integrated to create a distinct control group labeled ‘CK’, comprising 6 merged samples in total. Then, using the six-point method, the second set of 6 samples was taken from machine O, which had previously undergone conventional disinfection, and labeled ‘CD’. The fourth comparison analyzed the efficacy of three disinfectants under mechanized conditions (Section 3.4). Four areas were selected on the side frame of machine O, where H₂O, HClO, Pt-PHMG, and MCFA disinfectants were sprayed (Figure A2, group set 4). Samples (6 replicates per group) were collected from each area 72 h later and labeled as ‘CK’, ‘HClO’, ‘Pt-PHMG’, and ‘MCFA’, respectively. It should be clarified that although Machine O had undergone conventional disinfection, this occurred well before our study. This machine had remained devoid of silkworm rearing activities during the interim period. Thus, it represents a standard mechanized environment, ensuring no residual interference with the experimental outcomes in this comparative analysis. The fifth comparison tested the effectiveness of these disinfectants after mechanized mass silkworm rearing (Section 3.5). Initially, samples were taken using the six-point method from the undisinfected machines A/B/C, combined into the ‘CK’ group, same as the third comparison. Subsequently, HClO, Pt-PHMG, and MCFA disinfectants were applied to machines A/B/C, respectively. Samples were taken again 72 h later using the six-point method, labeled as ‘HClO’, ‘Pt-PHMG’, and ‘MCFA’, with a total of 6 samples collected in each group. The grouping and sampling information are detailed in Figure A2, with each group color-coded. To maintain traceability, samples originating from the same batch shared identical color identifiers when analyzed across multiple comparative groups. It is important to note that there are three groups named ‘CK’ in this study, but they actually refer to different samples in different comparisons. The three disinfectants were used at the recommended application concentrations as specified in their commercial product manuals: HClO contains 10% available chlorine, Pt-PHMG contains 3.6–4.4 g/L of the active ingredient, and MCFA contains 0.1–1 mL/L of the active ingredient. The disinfectants were all applied using a hand pump sprayer, ensuring that each surface was uniformly and thoroughly sprayed. The two environments were required not to conduct routine cleaning and disinfection during the 72 h for maintaining bacterial community. Samples were collected using sterilized swabs premoistened with double distilled H₂O for 5 s, wiping a 50 cm² surface. The swabs were stored in sterile, nuclease-free 1.5 mL Eppendorf tubes (Sangon Biotech Co., Ltd., Shanghai, China) and preserved at −80 °C until DNA extraction.

2.2. DNA Extraction and High-Throughput Sequencing

Genomic DNA isolation from swab specimens was performed with the MagBind bacterial DNA 96 kit (Omega Bio-tek, Inc., Norcross, GA, USA) following the supplier’s guidelines. The obtained DNA was immediately aliquoted, with one portion used for high-throughput sequencing, and the other stored at −80 °C for other experiments. DNA quantification and purity assessment were conducted using a NanoDrop 2000 UV-Vis spectrophotometer (Thermo Fisher Scientific Inc., Waltham, MA, USA). To verify bacterial DNA integrity, a PCR amplification of the 16S rRNA gene was executed with universal primers 27F/1492R (

Table 1. Primer sequences list.

Primer Name	Sequences (5′–3′)
27F	AGAGTTTGATCCTGGCTCAG
1492R	GGCTACCTTGTTACGACTT
515modF	GTGCCAGCMGCCGCGGTAA
806modR	GGACTACHV GGGTWTCTAAT
DB200F	CGGYCCAGACTCCTACGGG
DB200R	TTACCGCGGCTGCTGGCAC

), followed by electrophoretic validation on 1% agarose gels [39]. In this study, four samples failed the quality inspection due to low DNA concentrations, which is common for environmental surface samples. These samples are as follows: sample 6 of HClO and samples 5/6 of MCFA in group set 4, and sample 6 of HClO in group set 5.

For high-throughput sequencing, an amplification of the V4 hypervariable region was performed using target-specific primers 515modF/806modR (Table 1) [40]. The PCR reactions (20 μL total volume) contained 10 μL of 2 × ProTaq HS PCR Master Mix ver2 AG11307 (Accurate Biology Co., Ltd., Changsha, Hunan, China), 0.8 μL of each primer (5 μM), and <200 ng of template DNA on GeneAmp^® PCR System 9700 (Thermo Fisher Scientific Inc., Waltham, MA, USA) [41]. The cycling protocol comprised the following: the initial denaturation (95 °C, 3 min); 30 cycles of denaturation (95 °C, 30 s), annealing (55 °C, 30 s), and extension (72 °C, 45 s); and the final extension (72 °C, 10 min). Amplified products were resolved on 2% agarose gels, excised, and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences Inc., Union City, CA, USA). DNA quantification was subsequently performed with the QuantiFluor™-ST system (Promega Corporation Inc., Madison, WI, USA) per manufacturer protocols [41]. Equimolar concentrations of purified amplicons were pooled and subjected to paired-end sequencing on an Illumina NovaSeq platform (San Diego, CA, USA) through Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China), adhering to their standardized workflows [42]. Negative controls consisted of ddH₂O-moistened swabs exposed to ambient air for 10 s, which underwent identical processing steps to monitor potential reagent or environmental contamination [43].

2.3. Data Processing

The processing of 16S rRNA amplicon sequencing data was conducted using the LotuS2 pipeline [44]. The initial processing involved demultiplexing, quality filtering, and the dereplication of raw reads through a streamlined demultiplexing approach. High-quality sequences were then denoised to obtain amplicon sequence variants (ASVs) using the DADA2 plugin in the LotuS2 pipeline.

2.4. Bacterial Quantification

Absolute quantification of the total bacterial 16S rRNA gene copies was performed using a real-time quantitative PCR (qPCR) assay with the Roche LightCycler 480 system (Roche, Basel, Switzerland). Sample DNA aliquots underwent tenfold dilution prior to amplification with primer DB200 (Table 1) [41]. Triplicate reactions (10 μL each) were prepared containing the following: 5 μL of 5× Taq Pro Universal SYBR qPCR Master Mix (Vazyme Biotech, Nanjing, China), 0.2 μL per primer, and 1 μL diluted DNA template. Thermal cycling parameters included the following: an initial denaturation (95 °C, 5 min); 40 cycles of denaturation (95 °C, 10 s), annealing (60 °C, 10 s), and extension (72 °C, 10 s); followed by a melt curve step (65–95 °C ramp at 0.11 °C/s). Standard curves were constructed using serial tenfold dilutions (10²–10⁸) of full-length 16S rRNA amplicons generated with primers 27F/1492R (Table 1). The purification of amplification products was performed with the E.Z.N.A. Gel Extraction Kit (Omega, GA, USA) following manufacturer protocols, with DNA concentrations verified by a NanoDrop 2000 UV-vis spectrophotometer (Thermo Scientific, Waltham, MA, USA). Gene copy numbers per reaction were calculated based on standard curve regression analysis.

2.5. Bioluminescence-Based ATP Assay

The suppression of disinfectants on environmental microorganisms was assessed using ATP swabs (Lvbang, Ningbo, Zhejiang, China) and the SystemSURE Plus™ (Hygiena LLC, Camarillo, CA, USA). An even surface on the frame of the automated silkworm machine was selected and divided into four equal parts. Sterile water and the three disinfections (HClO, Pt-PHMG, and MCFA) were evenly smeared on four of the sections using sterilized swabs, ensuring a consistent dosage. The concentrations of each disinfectant were consistent with those applied in Section 2.1. ATP swabs were applied thoroughly to each area after the disinfectant had dried, and the fluorescence intensity was immediately measured according to the manufacturer’s instructions. The results expressed in relative light units (RLUs) were then converted to values per square centimeter for statistical analysis.

2.6. Statistical Analyses

Quantitative PCR data, and antibacterial and ATP assay results, were statistically analyzed through GraphPad Prism 9. Group comparisons employed Student’s t-test for unpaired data, while multi-group differences were evaluated via one-way ANOVA with Tukey’s post-hoc correction [45]. The results are presented as the means ± standard error of the mean (SEM), with a statistical significance threshold set at p < 0.05.

Microbiome analysis was implemented in the R (v4.3.3). Alpha-diversity metrics included the taxonomic richness index (the number of observed ASVs) and the Shannon index (Figure A3), whereas the beta-diversity assessment utilized Bray–Curtis dissimilarity matrices. Community structure differences were statistically verified through PERMANOVA (999 permutations), with dimensional reduction visualization achieved by NMDS ordination [46]. As described in Section 2.1, samples from machine A/B/C, which had not undergone disinfection, were integrated one-to-one to create a distinct group, for ensuring the correspondence of sampling points between groups and preventing data redundancy. Differences in spatial positions in community composition were statistically tested by PERMANOVA using the adonis2 function from the vegan package. For the detection of genera enriched in the conventional or mechanized environment (with abundance significantly higher than the other), DESeq2 comparison analysis was performed. Specific bacterial pathogens data were obtained from GlobalRPh (Pathogenic Bacteria Database) and compared with data from this study. The ComplexHeatmap package was used to generate a heat map of the enriched bacteria. Ecological processes were quantified using a method named Infer Community Assembly Mechanisms by Phylogenetic-bin-based null model (iCAMP) [47,48]. The pathogenic bacteria of silkworms were plotted and analyzed in GraphPad Prism 9. The data were calculated based on the absolute quantification result and relative abundances of each pathogen. Note that although the results for the four bacteria were presented in one graph, statistical analyses were conducted and labeled only within each bacterial group, without comparisons across different bacteria.

3. Results and Discussion

3.1. Environmental Microbiome Differences Between Conventional and Mechanized Silkworm Rearing

To understand the impact of mechanized sericulture on environmental microbiomes, we first conducted a comparative analysis of bacterial communities in the two environments. Both environments were disinfected and kept free of silkworms before sample collection (Figure A1). A qPCR analysis was conducted to explore the differences in bacterial load between the two environments. Notably, the results indicated a marginally higher bacterial biomass in the mechanized environment compared to the conventional environment, albeit with no statistical significance (Figure 3a). Moreover, we observed significant differences in bacterial richness and β-diversity (Figure 3b,c). The bacterial richness under the mechanized environment was significantly lower than that under the conventional one (Figure 3b), indicating that the mechanized environment tends to favor a few specific bacterial species occupying a majority of the ecological niche. As illustrated in Figure 3c, there were substantial differences in the overall bacterial composition between the conventional and mechanized environments.

The bacterial community composition was further examined at the genus level (Figure 3d). The bacteria in the conventional environment varied greatly among different sampling sites, showing a slightly higher relative abundance of Acinetobacter. Acinetobacter are widely found in soil and aquatic environments, on plant surfaces, as well as on animal skin and in the intestinal tract, suggesting their strong adhesion properties [49]. To ensure environmental representativeness, sampling targeted both silkworm-rearing trays and shelves—the key equipment in conventional sericulture systems (Figure A2, group set 1). Compared to shelves, trays demonstrate a substantially greater exposure to operational contacts and mulberry leaves, which may result in a higher likelihood of Acinetobacter adhesion. The mechanized environment exhibited distinct bacterial community profiles compared to the conventional environment, with Staphylococcus and Enterococcus demonstrating significantly higher relative abundances (Figure 3d). Consistent with the environmental representativeness assessment, the six-point sampling method (Section 2.1) was applied to the rearing equipment (Figure A2). Notably, divergent bacterial communities at points 5–6 were likely associated with spatial segregation and less anthropogenic exposure.

We further conducted a differential abundance analysis to identify bacterial genera that were significantly more abundant in each environment (Figure 3e). The upper part of the heatmap illustrates genera with a significantly higher abundance in the mechanized environment compared to the conventional one, while the lower part shows the opposite trend. Staphylococcus and Enterococcus exhibited marked enrichment in the mechanized environment. Staphylococcus is widely distributed in the natural environment as well as inside and outside organisms [50]. It is also a potential pathogen of silkworms. Silkworms that consume Staphylococcus might exhibit a reduced appetite, uneven development, and in severe cases, could develop secondary bacterial infections leading to failed cocooning or death [51]. Enterococcus thrives in alkaline environments and maintains a stable presence in the silkworm gut (pH > 10.5) [52]. However, when the intestinal pH dropped to 9–10 due to factors such as improper handling during silkworm rearing, Enterococcus proliferated quickly. This proliferation might result in a reduced appetite, slow growth, uneven development; and in extreme cases, enterococci lead to gut diseases such as shriveling, empty gut, diarrhea, and silkworms often failure to cocoon. High abundances of Staphylococcus and Enterococcus under mechanized silkworm-rearing conditions warrant attention.

Pathogen screening via GlobalRPh database annotation identified additional taxa (Figure A4). Subsequently, we focused on specific silkworm pathogens [15], including Enterococcus [53], Bacillus [54], Staphylococcus [51], and Aeromonas [55], and their absolute abundances were calculated (Figure 3f). The four potential pathogenic bacteria were found in both environments, with only Aeromonas showing a significant decrease under the mechanized silkworm-rearing environment. An overgrowth of Aeromonas can lead to bacterial septicemia in silkworms [56]. However, these bacteria are more commonly found in aquatic environments, various fish, and crustaceans, with fewer detections in soils, plants, and terrestrial animals [57,58]. Consistently, Aeromonas had a relatively low distribution and abundance in both environments in this study, indicating a lower disease risk in silkworms. Hence, a greater attention should be focused on the other three pathogenic bacteria.

Next, we applied iCAMP to predict the assembly process of bacterial communities in both environments (Figure A5a) [47]. In this context, ‘dispersal limitation’, ‘drift and others’, and ‘homogenizing dispersal’ are categorized as stochastic processes, while ‘selection’ is categorized as a deterministic process. Both environments were predominantly characterized by stochastic processes, with a higher relative importance of deterministic processes in the mechanized environment. This suggests that sericulture modernization increased the influence of selection on bacterial community assembly, but stochastic processes still played the dominant role. Notably, silkworm-related pathogens were still present, underscoring the necessity for targeted disinfection protocols with a minimal corrosive impact.

3.2. The Bacterial Community Structure Is Stable in the Mechanized Silkworm-Rearing Environment

To determine the stability of microbiota in the mechanized silkworm-rearing environment, we compared the bacterial communities at 0 h and 72 h. When no silkworms were raised and no disinfections were conducted, there were no significant changes in either the bacterial load or α/β-diversity after a three-day vacancy (Figure 4a–c). Community composition analysis revealed that the bacterial compositions at 0 h and 72 h were quite similar (Figure 4d). Staphylococcus was the predominant bacteria on the control panels and silkworm trays with more human activities, while the machine frames showed a higher bacterial richness and a more even distribution. Also, pathogen and community assembly analyses indicated no significant changes (Figure 4e and Figure A5b). Previous studies have demonstrated that bacterial communities can remain stable over the long term in a stable indoor environment [59,60,61]. Our findings align with these studies. Particularly in the mechanized environment, pathogens adhering to machinery can persist in the environment if there is no timely and effective disinfections.

3.3. Only Small Bacterial Changes Occur After Conventional Disinfection Is Applied in the Mechanized Silkworm-Rearing Environment

Conventionally, strict sanitation and hygienic procedures are used when raising silkworms. For example, chlorine-based agents with an available chlorine content of 30–38% (bleach) are often applied by water-soluble spraying, followed by ventilation and drying. This method is relatively effective in conventional silkworm rearing, capable of eliminating most of the environmental microorganisms harmful to silkworms. After drying, residual bleach powders remain on the surface of sericulture equipment, providing long-lasting disinfection.

To determine the applicability and effectiveness of this conventional method in mechanized silkworm rearing, we compared the samples collected from rearing machines after the conventional disinfection (CD) with the control (CK, samples collected from machines without any disinfections). Surprisingly, there were no significant bacterial differences between them (Figure 5a–c). Both the bacterial load and species richness showed only a slight downward trend after the conventional disinfection treatment (Figure 5a,b), which indicates that the conventional disinfection method was not particularly effective under the mechanized silkworm-rearing environment. Upon further investigation of the bacterial composition, we found that there were no significant differences in the various bacterial genera (Figure 5c,d) or potential silkworm pathogens (Figure 5e) either. Community assembly analysis (Figure A5c) suggested that the conventional disinfection killed some microorganisms, creating a microbial negative pressure space and resource redundancy. Subsequently, other microorganisms transferred almost indiscriminately from the surrounding environment into the rearing machines through a stochastic process, forming a relatively stable bacterial community structure. In the CK group, silkworms were raised on the machine before sampling. Due to the high sensitivity of silkworms to environmental changes, the use of disinfectants may cause a feeding cessation. Consequently, disinfection was avoided during the rearing period, lasting approximately two or three weeks. This allowed the environment to remain relatively undisturbed, during which microorganisms underwent competitive interactions, eventually establishing a relatively stable community structure, indicating a deterministic process.

Notably, there were no significant changes in potential bacterial pathogens (Figure 5e). This implies that conventional chlorine-based disinfectants were relatively ineffective for sterilizing microorganisms in mechanized silkworm rearing, leaving high risks of bacterial diseases. Moreover, the main components of bleaching powder are calcium hydroxide (Ca(OH)₂), calcium chloride (CaCl₂), and calcium hypochlorite (Ca(ClO)₂). Research over the past few decades has consistently shown that these substances are highly corrosive to metal machinery and can cause severe contamination with repeated use. Their residues and volatiles have long-term adverse effects on human health and the surrounding environment [62,63,64]. Overall, there is an urgent need for new, more suitable disinfection strategies that are safe, effective, and long-lasting when used in mechanized silkworm rearing.

3.4. The Effect of Three Disinfectants Used in Mechanized Silkworm Rearing

Next, the effect of three potential disinfectants, namely HClO, Pt-PHMG, and MCFA, was evaluated when used in the mechanized silkworm-rearing environment. All of the three disinfectants effectively suppressed environmental bacteria in terms of bacterial load; after 72 h of application, bacterial numbers at the sites treated with them were significantly lower compared to the control treated with sterile water. Particularly, Pt-PHMG and MCFA showed better inhibitory effects than HClO (Figure 6a). The same trend was observed in the α-diversity analysis, where the species richness significantly decreased after the application of Pt-PHMG and MCFA disinfectants, while the HClO-exposed samples showed a decreasing trend without statistical significance (Figure 6b). The β-diversity analysis revealed highly significant differences among bacterial communities in each treatment, with the MCFA-treated samples showing the greatest dissimilarity compared to the other three treatments (Figure 6c).

Gram-negative genera such as Ralstonia, Acinetobacter, Methylobacterium, and Sphingomonas collectively account for approximately 70% of the total relative abundance (Figure 6d). Compared to the control, the HClO-exposed samples showed relatively minor changes in the relative abundance of bacterial genera. This indicated that HClO has bacteriostatic effects in the mechanized environment, but with a less pronounced selectivity towards high-abundance Gram-negative bacteria. In the Pt-PHMG-exposed sites, the abundance of Acinetobacter and Sphingomonas was lower, whereas in the MCFA-exposed positions, Acinetobacter and Methylobacterium showed a reduced abundance. This suggests that Pt-PHMG and MCFA disinfectants may have potent inhibitory effects on these specific bacteria.

Based on the absolute quantification results (Figure 6a) and the relative abundance of typical environmental pathogenic bacteria (Figure A4d), the absolute quantity of potential pathogenic bacteria in the mechanized environment was calculated (Figure 6e). The Pt-PHMG disinfectant significantly reduced the numbers of Enterococcus, Bacillus, and Staphylococcus, while the MCFA disinfectant only led to a significant decrease in Bacillus. HClO did not significantly eliminate any of the potential pathogenic bacteria. None of the disinfectants except for HClO caused significant changes in the abundance of Aeromonas species in this environment. Given the inherently low abundance of Aeromonas, their threat to silkworms might be minimal. This discrepancy in predicted community assembly processes compared to other machine sampling points (Figure A5a–c,e) may stem from substrate heterogeneity across sampling sites and spatially dependent variations in human intervention patterns. Collectively, for mechanized silkworm rearing, Pt-PHMG and MCFA showed a better effectiveness to ensure the hygiene of silkworms, with Pt-PHMG demonstrating a superior inhibition against potential silkworm pathogens.

3.5. The Performance of Three Disinfectants After Mechanized Mass Silkworm Rearing

Finally, we tested the performance of the three disinfectants after mechanized mass silkworm rearing. In contrast to the evaluation in 3.4 (before silkworm rearing), the environmental microbiome changed after mass silkworm rearing. After the application of the three disinfectants, the total bacterial load significantly decreased compared to the untreated control (Figure 7a), indicating that all three disinfectants have antibacterial properties in such a dirty environment and offer lasting effects. Microbial ATP detection also validated this result (Figure 7b).

Despite none of the three disinfectants causing a significant change in microbial α-diversity (Figure 7c), the β-diversity showed significant differences (Figure 7d). This may be due to the different inhibition efficiencies of the disinfectants on different bacteria. The three disinfectants increased the relative abundance of bacteria such as Acinetobacter and Ralstonia to varying degrees. In addition, both HClO and MCFA disinfectants reduced the relative abundance of Staphylococcus (Figure 7e).

To gain deeper insights into the inhibitory effects of disinfectants on silkworm pathogens in this environment, we calculated the absolute quantities of four potential silkworm pathogens using the method described previously, combining absolute quantification results (Figure 7a) and the relative abundance of pathogens (Figure A4e). The three disinfectants exhibited different inhibitory effects on silkworm pathogens (Figure 7f). Pt-PHMG demonstrated a significant inhibition of Enterococcus, Staphylococcus, and Aeromonas. MCFA exhibited a notable suppression against Staphylococcus and Aeromonas. HClO showed significant inhibitory effects exclusively against Bacillus.

After the application of disinfectants, the relative importance of the community assembly process of Pt-PHMG was similar to that of the CK group, with only a slight decrease in the relative importance of deterministic processes (Figure A5e). In contrast, the groups treated with HClO and MCFA showed an increased relative importance of drift and other processes, while the relative importance of selection processes decreased. These shifts occurred because the disinfectants caused mortality among environmental microbiota at the application site, resulting in a decreased bacterial abundance compared to the surrounding environment and thus creating ecological niches with some vacancies. This led to a bacterial diffusion gradient from the surrounding environment, allowing various bacteria to naturally migrate and settle, constituting stochastic processes. Overall, after mechanized mass silkworm rearing, Pt-PHMG shows the best long-term antibacterial effect for preventing bacterial diseases in silkworms, followed by MCFA and HClO.

Based on results before and after mechanized mass silkworm rearing, we do not recommend using HClO for disinfection due to its poor pathogen inhibition. While Pt-PHMG and MCFA demonstrated a higher efficacy in reducing bacterial loads and suppressing key silkworm pathogens, their limitations necessitate cautious application. Pt-PHMG’s incomplete inhibition of persistent Gram-negative genera (e.g., Ralstonia) may inadvertently promote microbial community instability. Similarly, MCFA’s variable suppression of pathogens like Enterococcus and Staphylococcus may pose a potential threat from residual pathogenic bacteria. Given these limitations, alternative or complementary disinfection strategies may offer viable solutions. For instance, UV-C irradiation and ozone treatment can be used as adjuncts [65]. Integrating these approaches with mechanized systems could improve automation, meet disinfection demands, and enhance long-term biosecurity in sericulture.

Based on the comparison of obtained data, the effectiveness of disinfection after silkworm rearing is generally lower than before rearing. This may be due to various factors. Firstly, even after bacterial death, their DNA can still be detected due to its relatively stable molecular structure, which takes time to degrade. This residual genomic DNA can lead to false positive microbial signals [66,67]. Evidences suggest that environmental DNA (eDNA) can persist for extended periods, leading to the detection in locations where organisms are no longer present [68,69]. Our study was limited to the sequencing of DNA. Therefore, the potential impact of dead bacteria on the analysis results cannot be excluded. Although these bacteria are no longer viable, their DNA may persist in the environment and be detected as false positives. Unlike DNA, RNA released into the environment typically degrades quickly [70]. Future work will require a simultaneous extraction of bacterial RNA from sampling sites, followed by reverse transcription and sequencing, to ensure that the data reflect live bacteria. Additionally, the post-rearing environment had approximately 25% more bacterial species than the pre-rearing environment (Figure 6b and Figure 7c), indicating that the diversity and complexity of the mechanized environment increased after mass silkworm rearing. An increase in microbial diversity may signify a greater environmental stability [71,72]. Therefore, an increase in microbial diversity after mechanized mass silkworm rearing indicates a high disinfection pressure. There is no doubt that the post-rearing environment requires more intensive disinfection. We suggest an increase in the concentration of disinfectants, an application of larger quantities, or the implementation of periodic and repeated applications. The development of specific sanitation and hygienic procedures need further research.

4. Conclusions and Future Directions

The mechanization in sericulture results in the changes of environmental microbiomes, which differ significantly from those in conventional silkworm-rearing environment. Mechanized environments maintain relatively stable microbial conditions, underscoring the need for tailored disinfection strategies. Our evaluation identified Pt-PHMG as the most effective disinfectant for pathogen suppression in this context, outperforming other agents. Crucially, post-rearing bacterial complexity escalates dramatically, demanding proactive disinfection protocols. This study provides practical insights for sericulture farmers in the mechanized system. Integrating routine microbiome monitoring with targeted disinfection enhances sustainable disease prevention, ensuring both yield stability and long-term environmental safety in industrial sericulture.

In addition to bacterial pathogens, silkworms can also be infected by viruses, fungi, and microsporidia, leading to disease outbreaks. Future studies should further explore environmental management and disinfection strategies in modern sericulture. Specifically, metagenomic and metatranscriptomic analyses need to be implemented. These approaches will enable a comprehensive evaluation of both the practical efficacy of various disinfectants in silkworm-rearing environments and their preventive capabilities against diverse silkworm diseases. Furthermore, a composite disinfection strategy is also worth considering. The continuing development of effective disinfection strategies will facilitate sericulture mechanization and ensure sustainable silk and pupa production.