# Thermal and non-thermal effects of microwave pretreatment on horse dung microbial communities used as inoculum for acidogenic fermentation

Korantin Pipereau, Eric Trably, Gaelle Santa-Catalina, Diana Garcia-Bernet,

Hélène Carrere

► To cite this version:

Korantin Pipereau, Eric Trably, Gaelle Santa-Catalina, Diana Garcia-Bernet, Hélène Carrere. Thermal and non-thermal effects of microwave pretreatment on horse dung microbial communities used as inoculum for acidogenic fermentation. Bioresource Technology, 2025, 427, pp.132407. 10.1016/j.biortech.2025.132407. hal-05045247

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Submitted on 24 Apr 2025

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# Thermal and non-thermal effects of microwave pretreatment on horse dung microbial communities used as inoculum for acidogenic fermentation☆

Korantin Pipereau, Eric Trably, Gaelle Santa-Catalina ID, Diana García-Bernet, Hélène Carrere *ID

INRAE, Université de Montpellier, LBE, 102 avenue des Étangs, 11100 Narbonne, France

## HIGHLIGHTS

* Higher severity factor applied to the inoculum increased the total metabolite yield.

* Same metabolite profiles after 95 °C microwave and thermal pretreatments.

* Microwave treatment at 40 °C is comparable to the control for metabolite production.

* Significantly higher *Ruminiclostridium* abundance for both 95 °C treatments.

* α-diversity richness index significantly enhanced with 40 °C microwave pretreatment.

## GRAPHICAL ABSTRACT

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

**Keywords:**

Microwave irradiation

Wheat straw

Lignocellulosic biomass

Manure

Bacterial diversity

## ABSTRACT

This study focuses on thermal and non-thermal effects of microwave pretreatment on horse dung as indigenous inoculum before xylose and wheat straw fermentation, emphasizing metabolite production and microbial community changes. Two horse dung microwave pretreatments (MW40°C and MW95°C) were compared with a conventional thermal pretreatment (Th95°C) and an unpretreated condition (Ctrl). Microwave heating pretreatment (MW95°C) leads to similar production as a conventional thermal pretreatment (Th95°C) for xylose and wheat straw fermentation while MW40°C treatment was similar to the control. The two thermal pretreatments (MW95°C and Th95°C) produced respectively 19 % and 45 % more than the Ctrl and MW40°C conditions. Nonetheless, for wheat straw, microwave irradiation without heating affected the microbial community by increasing the alpha diversity richness. The *Ruminiclostridium* genus, known for its hydrolytic activity, represented at least 25 % of the total relative abundance after fermentation with thermal shock pretreatment, potentially explaining the enhancement of the metabolite production from straw.

<footnote>* This article is part of a special issue entitled: 'IWA AD18 (2024)' published in Bioresource Technology.</footnote>

<footnote>* Corresponding author.
E-mail address: helene.carrere@inrae.fr (H. Carrere).</footnote>
# 1. Introduction

Volatile Fatty Acids (VFA) are used as platform molecules serving in a wide range of domains in green chemistry, such as the formulation of chemicals, or in the energy sector (Ramos-Suarez et al., 2021). Today, a vast majority of VFAs are produced by the oil industry. Still, the environmental context could reverse this trend in the near future to produce more sustainable bio-based VFAs. They can be produced through the fermentation process, which is a natural process involving different types of microorganisms (Ramos-Suarez et al., 2021). In this context, the use of lignocellulosic biomass as renewable resources for VFA production has gained significant attention in recent years due to its high abundance, low cost, and high potential to mitigate environmental impacts compared to conventional fossil sources (Mujtaba et al., 2023). However, the use of a lignocellulosic biomass implies addressing new challenges such as breaking down the complex sugar-based structures that compose most of the biomass (Bichot et al., 2021). Indeed, the production of these carboxylic acids relies on several stages carried out by various micro-organisms which need to access simple organic matter (amino acids, carbohydrates, fatty acids) (Ramos-Suarez et al., 2021). Numerous pretreatment techniques have recently emerged to enhance the accessibility of cellulose and hemicellulose before microbial fermentation. Only few studies have looked at the impact of various pretreatment (aeration, freezing, thawing, acid, alkali, thermal, thermal + CO₂, thermo-acid, electric shock, addition of inhibitory compounds, cell wash out) on fermentation inoculums such as anaerobic seed sludge, methanogenic granular sludge, digestate of anaerobic reactor, activated sludge (Cisneros-Pérez et al., 2017; Luo et al., 2022; Dessi et al., 2018; Hidalgo et al., 2023). However, very little is known about the impact of microwave pretreatment (having both thermal and irradiation impacts), in particular on less conventional inoculum such as horse dung performing VFA production. Using the endogenous microorganisms coming directly from the substrate in fermentation appears to be a good solution to simplify and optimize the biomass conversion. Recent studies showed that endogenous microorganisms present very similar production yields compared to external inoculum in fermentation (Dauptain et al., 2020).

Among pretreatment techniques, the microwave is an unconventional pretreatment method favoring the deconstruction of biomass materials through both thermal and non-thermal effects (Kubo et al., 2020). Microwaves are electromagnetic waves with a frequency ranging between 300 MHz and 300 GHz and a wavelength between 1 cm and 1 m (Vermeiren et al., 2024). They are classified as non-ionizing radiations, as these waves do not have sufficient energy to ionize molecules or atoms (Kubo et al., 2020). Two main microwave heating mechanisms can occur according to the frequency used: ionic conduction and dipolar rotation (Fan et al., 2024). Ionic conduction is caused by the oscillatory migration of ions under the action of a high-frequency electric field, leading to collisions between the ions and other molecules. This results in the conversion of the kinetic energy of the ions into thermal energy (Horikoshi et al., 2024). Dipolar rotation occurs when an oscillating electromagnetic field is generated. Polar molecules tend to realign along the direction of the electric field causing internal friction between the molecules and heating of the product (Horikoshi et al., 2024). The microwave process can be seen as a good alternative to conventional thermal heating for two reasons. First, microwave shows usually faster heating kinetics than thermal heating which relies on the principles of thermal conductivity and diffusion, with poor constants in many products (Goyal et al., 2022). Second, microwave heating is usually considered more uniform than thermal heating (Chandrasekaran et al., 2013).

In addition, microwave pretreatment could lead to non-thermal effects, i.e. effects that cannot be explained by macroscopic temperature increases, time-temperature histories, or temperature gradients (Kubo et al., 2020; Goyal et al., 2022). Non-thermal effects were previously shown to modify chemical, biochemical, or physical behaviors of systems as a result of exposure to microwaves. For example, Rougier et al., (2014) reported alterations of the microbial cell membrane even at low

temperatures, at power of 400 W and higher. Other studies pointed out various effects of non-thermal effects of microwaves on microorganisms (Escherichia coli, Staphylococcus aureus or Clostridium sporogenes) such as cell morphology damage (Shaw et al., 2021; Guo et al., 2020). However, in some studies, an absence of non-thermal effect of microwaves was reported (Kubo et al., 2020; Hammarin et al., 2024). Thus, no scientific consensus has been found on the non-thermal effects of microwave irradiation on microorganisms (Kubo et al., 2020).

Whereas conventional thermal pretreatment at 95 °C is commonly applied to inoculum used in dark fermentation, the objective of this study was to investigate both thermal and non-thermal effects of microwave pretreatment on horse dung microorganisms used as inoculum for acidogenic fermentation of xylose and wheat straw. Metabolite yields from both substrates were compared to controls using conventional thermal pretreated and unpretreated horse dung as inoculum. Thanks to the microbial community analyses after straw fermentation, it was possible to highlight the main biomarkers, to link fermentation performances with community changes depending on pretreatment, and to identify some resilient taxa. This study provides new insights concerning horse manure that has never been used in the context of acidogenic fermentation using solely indigenous microbial community as an inoculum source. Furthermore, this paper brings more knowledge concerning the irradiation impact of microwave pretreatment on microbial communities. There is still a debate ongoing concerning this subject and the current paper brings new elements to the debate.

# 2. Materials and methods

## 2.1. Inoculum and substrates

Horse dung was used as an inoculum to mimic indigenous microorganisms of horse manure. Wheat straw was used in the same way as a source of substrate to mimic horse manure lignocellulosic compound in the fermentation process. An easier fermentable substrate, xylose, was also used to confirm the capacity of horse dung as inoculum for acidogenic fermentation. Horse dung was collected at Narbonne Equitation horse riding center (Narbonne, 11100, France). Wheat straw was bought from Fabre Garden shop (Narbonne, 11100, France), and D-(+)-Xylose (≥99 % purity) was purchased from Merck (Merck Millipore Quantum TEX).

After collection, horse dung was freeze-dried and finely ground using an IKA MF 10 basic knife grinder equipped with a 1 mm grid. Wheat straw was milled with the same grinder using a 10 mm grid. Freeze-dried and milled samples were kept in closed boxes at ambient temperature before use. Total solids (TS) and volatile solids (VS) of both horse dung and wheat straw were measured in triplicates according to the APHA standard method (APHA, 1999), results are shown in Table 1.

## 2.2. Horse dung inoculum pretreatment

Microwave pretreatment tests of horse dung (the sole source of inoculum) were performed using the microwave at 200 W for 15 min under two conditions: a first condition with a maximum temperature set at 95 °C (MW 95 °C). A second condition was applied with a maximum temperature of 40 °C (MW 40 °C) using a bath cooling system to cool

<table><caption>**Table 1**

Substrate and inoculum characteristics.</caption><thead><tr><th>Substrate</th><th>Preprocess</th><th>TS (g/g)</th><th>VS (g/g)</th></tr></thead><tbody><tr><td>Wheat straw</td><td>Milled at 10 mm</td><td>0.922 ±<br>0.000</td><td>0.859 ±<br>0.013</td></tr><tr><td>Horse dung</td><td>Freeze-dried and milled at 1 mm</td><td>0.921 ±<br>0.002</td><td>0.707 ±<br>0.028</td></tr><tr><td>Horse dung</td><td>Raw</td><td>0.267 ±<br>0.011</td><td>0.211 ±<br>0.026</td></tr></tbody></table>
down the glass reactor. This setup was used to dissociate thermal and non-thermal microwave effects.

The maximum temperature of 95 °C was selected to deactivate *Archaea* and select spore-forming bacteria (Dauptain et al., 2020). The maximum temperature of 40 °C was selected not to damage mesophilic proteins and microbial membranes (Vieille and Zeikus, 2001).

Tests were conducted in a Minilabotron 200 (Sairem, France) operated at 2.45 GHz with a maximum power of 2 kW. An optic fiber linked to the microwave device was used to monitor the temperature in real-time inside the glass reactor while operating pretreatment. Incident and reflected powers were registered every 3 s during pretreatment. The absorbed energies based on the incident and reflected power were calculated following the procedure described by Bichot et al. (2021). The absorbed energy values were 3.0 Wh/gVS for MW 40 °C and 3.44 Wh/gVS for MW 95 °C.

In both conditions, 8.7 g of freeze-dried and milled horse dung were added to 180 mL of tap water solution in a borosilicate glass reactor giving a solid/liquid (S/L) ratio of 0.05 (w/w). The mixture was homogenized for 30 min with magnetic stirring before treatment. After microwave treatment, 11.14 g of the mixture was sampled for each fermentation test corresponding to 0.33 g VS of inoculum.

Conventional thermal treatment (Th 95 °C) was performed to compare microwave and conventional heating performed at the same temperature deactivating *Archaea* and selecting spore-forming bacteria. The test was carried out on a ceramic heating plate with magnetic stirring (IKA C-MAG HS 7) at 95 °C for 15 min using identical conditions of S/L ratio of horse dung/tap water as in microwave pretreatment. Temperature was measured every 3 s for both microwave conditions as well as conventional thermal pretreatment.

## 2.3. Experimental setup of fermentation tests

Fermentation tests were carried out in 1000 mL glass bottles with a 500 mL headspace using either 2.5 g VS of xylose or 5 g VS of wheat straw as substrate as well as 0.33 g VS of pretreated (MW 95 °C; MW 40 °C or Th 95 °C) or un-pretreated (Ctrl) horse dung acting as inoculum. A pH buffer (100 mM of 2-(*N*-morpholino)ethanesulfonic acid [MES]) was added to maintain the pH at 6 during fermentation. Moreover, 2.5 mL of a trace element solution whose composition is given by Chatellard et al. (2016) were added, as well as 0.8 g/L of NH₄Cl and 0.5 g/L of K₂HPO₄. A condition with 0.33 g VS of horse dung and no substrate was performed and the endogenous metabolite production (0.004 ± 0.002 gCOD/gVS) was subtracted to the other conditions. Finally, bottles

were sealed with a rubber septum and locked with a screw cap. The headspace of the bottles was purged with nitrogen gas to ensure strict anaerobic conditions. Tests were conducted in quadruples, in a batch mode, at 35 °C and without stirring. Fermentation tests were conducted for 7 days to reach a maximum amount of metabolites without converting them to methane. Sampling of the liquid phase for further analysis and measures of headspace compositions and pressures were performed along the fermentation process.

A summary of the experimental setup of the fermentation tests can be found in Fig. 1.

## 2.4. Chemical analysis

The pressure inside fermentation bottles was manually measured with a Keller LEO 2 manometer (KELLER AG, Winterthur, Switzerland). Gas analysis was carried out on a Perkin Elmer Clarus 580 GC equipped with RT-Q-Bond and RT-Msieve 5Å columns with a TCD allowing the quantification of H₂, CO₂, N₂, O₂, and CH₄ with Ar as carrier gas. Before analysis, samples were centrifuged at 13 000 g for 15 min and filtrated at 0.2 µm using a nylon filter. The analysis of acetate (C2), propionate (C3), butyrate (C4), isobutyrate (iC4), valerate (C5), isovalerate (iC5), caproate (C6) and isocaproate (iC6) was performed by Gas Chromatography (GC), as described elsewhere (Noguer et al., 2022). The Perkin Elmer Clarus 580 GC was equipped with an Alltech-FFAP EC™ 1000 column coupled to a flame ionization detector (FID) set at 280 °C. N₂ was used as carrier gas with a flow rate of 6 mL/min. Other metabolites (ethanol, butanol, succinate, lactate, formate) and residual sugars (glucose, xylose, fructose, arabinose) were analyzed after fermentation by High-Performance Liquid Chromatography (HPLC) (Noguer et al., 2022). The HPLC was equipped with a protective precolumn (Microguard cation H refill cartridges, Biorad), an HPX-87H column (300 × 7.8 mm, Biorad) running at 35 °C, with a 0.004 M H₂SO₄ solution as eluent (0.3 mL.min⁻¹), and a refractive index detector (Waters R410) running at 45 °C.

## 2.5. Microbiology analysis

Concerning microbiological analysis, only the microbial community of the wheat straw fermentation tests was investigated because this condition is as close as possible to horse manure. For each quadruplicate, microbial communities of three fermentation bottles were analyzed on day seven and compared between pretreatment conditions thanks to the following protocol. In addition, the horse dung community at the initial

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Summary of the experimental setup for the fermentation tests using un- or pretreated horse dung as indigenous inoculum source and xylose or wheat straw as substrate.</figcaption></figure>
time was also sequenced. First, a sample of the fermentation medium was incorporated into a 2 mL Eppendorf tube and centrifuged at 13,000 g for 15 min. DNA extraction was performed with a PowerSoil™ DNA isolation sample kit (MP biomedicals, LCC, California, USA) according to the manufacturer's instructions. Afterward, DNA amount and purity were measured by spectrophotometry (Infinite NanoQuant M200, Tecan) and extracted DNA was stored at -20 °C before use. The V3 region of the 16S rRNA genes was amplified using universal primers for bacteria as mentioned by Carmona-Martínez et al. (2015). PCR products were purified and sequenced using Illumina MiSeq technology at the Genotoul life science network in Toulouse, France (get.genotoul.fr). All sequences were obtained after applying a bioinformatic pipeline as described by Carmona-Martínez et al. (2015). Sequencing results were analyzed with bioinformatic tools. Mothur version 1.48.0 was used for sequence cleaning, assembling, and control. Sequence matching and taxonomic assignment were performed on SILVA version 132 with Operational Taxonomic Unit (OTU) within a 3 % dissimilarity level. Sequences were submitted to GenBank, with accession No. SRX25273391 to No. SRX25273402.

## 2.6. Severity factor calculation

To accurately compare the pretreatment methods based on their thermal impacts, a severity factor was calculated and expressed as Eq. (1). This factor was developed from the formula of the lignocellulosic pretreatment by steam-explosion (Overend and Chornet, 1987). Some modifications were applied to fit with the data of the present study. The first constant (i.e. 20, in °C) was correlated to the basic pretreatment temperature, which corresponds to the temperature of the water before pretreatment (Ruiz et al., 2021). The second constant (i.e. 6.1) corresponds to the typical activation energy value for the cleavage of the glycosidic bond carbohydrates and temperature (Ruiz et al., 2021) related to horse manure in the present study (Chong et al., 2019).

$$R_0 = \int_0^f \exp \left[ \frac{T(t) - 20}{6.1} \right] dt \quad (1)$$

where $R_0$ is the severity factor and $T(t)$ is the temperature in °C vs the time profile.

## 2.7. Statistical and bioinformatic analysis

The results are given as the average ± standard deviation for descriptive statistics. All statistical tests were carried out using R software (version 4.3.1). A one-factor analysis of variance (ANOVA) was first carried out using the anova_test function of the rstatix package to determine whether there was a statistical difference in metabolite production between fermentation tests. If a significant p-value (< 0.05) was found, a Tukey test was then carried out using the tukey_hsd function from rstatix package. Principal component analysis was performed using the res.pca function of the factomineR package and the biplot was plotted using the fviz_pca function of the factoextra package. β-diversity index was calculated after a filtration step, using the cal betadiv function of the microeco package. α-diversity was provided by the cal alphadiv function of the microeco package after a rarefaction step. In addition, trans beta and cal ordination functions of the microeco package were used to plot NMDS using the Bray-Curtis index. Barplots were drawn using the ggbarplot function of the ggpubr packages. Before calculating the permutational analysis of variance (PERMANOVA) statistical test, a homogeneity of multivariate dispersions (PERMDISP) test was performed. Both tests were performed using the microeco package with respectively the cal betadisper and the cal manova function. Finally, LEfSe (linear discriminant analysis effect size) analysis was performed to compare bacterial communities between pretreatment conditions based on statistical tests (Kruskall-Wallis; Wilcoxon and Linear discriminant analysis) to distinguish significant differences

between groups and identify biomarkers according to Segata et al., (2011). The trans_diff function of the microeco package was used to perform the analysis using the alpha index of 0.05 as a discriminant.

# 3. Results and discussion

## 3.1. Impact of inoculum pretreatment on the performance of xylose fermentation

To better understand the influence of microwave pretreatment and decipher the thermal and non-thermal effects of microwaves on fermentation yield and metabolic profile, different types of pretreatments were tested on horse dung as an inoculum before xylose fermentation. Fermentation results of xylose are presented in Table 2 showing the severity factor as well as the metabolite production associated with every inoculum pretreatment at day seven. Acetate (C2) and butyrate (C4) selectivities were calculated based on the metabolite production (C2 or C4) divided by the overall production. No residual

<table><caption>**Table 2**

Horse dung pretreatments conditions and fermentation metabolites at day seven for both wheat straw and xylose as substrates.</caption><thead><tr><th>Dung pretreatment</th><th></th><th>Ctrl</th><th>MW 40 °C</th><th>MW 95 °C</th><th>Th 95 °C</th></tr></thead><tbody><tr><td>Severity factor</td><td></td><td>0</td><td>4.36E + 02</td><td>8.87E + 05</td><td>2.60E + 06</td></tr><tr><td colspan="6" style="text-align: center;">Metabolites (gCOD/gVS)</td></tr><tr><td rowspan="12">Xylose</td><td>C2</td><td>0.348 ± 0.139<sup>a</sup></td><td>0.364 ± 0.102<sup>a</sup></td><td>0.242 ± 0.17<sup>a</sup></td><td>0.150 ± 0.096<sup>a</sup></td></tr><tr><td>C3</td><td>0.031 ± 0.016<sup>ab</sup></td><td>0.058 ± 0.004<sup>a</sup></td><td>0.050 ± 0.028<sup>a</sup></td><td>0.012 ± 0.003<sup>b</sup></td></tr><tr><td>C4</td><td>0.129 ± 0.072<sup>b</sup></td><td>0.112 ± 0.027<sup>b</sup></td><td>0.331 ± 0.151<sup>ab</sup></td><td>0.478 ± 0.227<sup>a</sup></td></tr><tr><td>Su</td><td>0.030 ± 0.044<sup>a</sup></td><td>0 ± 0<sup>a</sup></td><td>0.023 ± 0.033<sup>a</sup></td><td>0.066 ± 0.103<sup>a</sup></td></tr><tr><td>EtOH</td><td>0.100 ± 0.115<sup>a</sup></td><td>0.114 ± 0.057<sup>a</sup></td><td>0.070 ± 0.032<sup>a</sup></td><td>0.120 ± 0.044<sup>a</sup></td></tr><tr><td>H<sub>2</sub></td><td>0.104 ± 0.016<sup>a</sup></td><td>0.102 ± 0.009<sup>a</sup></td><td>0.086 ± 0.023<sup>a</sup></td><td>0.118 ± 0.038<sup>a</sup></td></tr><tr><td>CH<sub>4</sub></td><td>0.001 ± 0.000<sup>a</sup></td><td>0 ± 0<sup>a</sup></td><td>0 ± 0<sup>a</sup></td><td>0 ± 0<sup>a</sup></td></tr><tr><td>Total</td><td>0.756 ± 0.076<sup>b</sup></td><td>0.782 ± 0.031<sup>b</sup></td><td>0.810 ± 0.017<sup>ab</sup></td><td>0.943 ± 0.043<sup>a</sup></td></tr><tr><td>C2 selectivity (%)</td><td>46 ± 18<sup>a</sup></td><td>47 ± 13<sup>a</sup></td><td>30 ± 21<sup>a</sup></td><td>16 ± 10<sup>a</sup></td></tr><tr><td>C4 selectivity (%)</td><td>17 ± 10<sup>b</sup></td><td>14 ± 3<sup>b</sup></td><td>41 ± 19<sup>ab</sup></td><td>51 ± 24<sup>a</sup></td></tr><tr><td>Final pH</td><td>5.45 ± 0.05<sup>a</sup></td><td>5.49 ± 0.14<sup>a</sup></td><td>5.25 ± 0.14<sup>a</sup></td><td>5.38 ± 0.13<sup>a</sup></td></tr><tr><td rowspan="12">Wheat straw</td><td>C2</td><td>0.101 ± 0.006<sup>a</sup></td><td>0.110 ± 0.022<sup>a</sup></td><td>0.131 ± 0.028<sup>a</sup></td><td>0.123 ± 0.016<sup>a</sup></td></tr><tr><td>C3</td><td>0.006 ± 0.001<sup>b</sup></td><td>0.009 ± 0.002<sup>ab</sup></td><td>0.008 ± 0.003<sup>ab</sup></td><td>0.016 ± 0.007<sup>a</sup></td></tr><tr><td>C4</td><td>0.013 ± 0.002<sup>b</sup></td><td>0.027 ± 0.005<sup>a</sup></td><td>0.028 ± 0.007<sup>a</sup></td><td>0.026 ± 0.009<sup>ab</sup></td></tr><tr><td>Su</td><td>0.004 ± 0.001<sup>a</sup></td><td>0.004 ± 0.000<sup>a</sup></td><td>0.004 ± 0.001<sup>a</sup></td><td>0.004 ± 0.000<sup>a</sup></td></tr><tr><td>EtOH</td><td>0.003 ± 0.001<sup>b</sup></td><td>0.001 ± 0.002<sup>b</sup></td><td>0.006 ± 0.003<sup>ab</sup></td><td>0.015 ± 0.010<sup>a</sup></td></tr><tr><td>H<sub>2</sub></td><td>0 ± 0<sup>a</sup></td><td>0.001 ± 0.000<sup>a</sup></td><td>0.001 ± 0.000<sup>a</sup></td><td>0.002 ± 0.001<sup>a</sup></td></tr><tr><td>CH<sub>4</sub></td><td>0 ± 0<sup>a</sup></td><td>0.004 ± 0.000<sup>a</sup></td><td>0 ± 0<sup>a</sup></td><td>0 ± 0<sup>a</sup></td></tr><tr><td>Total</td><td>0.126 ± 0.009<sup>b</sup></td><td>0.154 ± 0.027<sup>ab</sup></td><td>0.181 ± 0.031<sup>a</sup></td><td>0.186 ± 0.011<sup>a</sup></td></tr><tr><td>C2 selectivity (%)</td><td>80 ± 10<sup>a</sup></td><td>71 ± 14<sup>a</sup></td><td>72 ± 15<sup>a</sup></td><td>66 ± 9<sup>a</sup></td></tr><tr><td>C4 selectivity (%)</td><td>10 ± 1<sup>b</sup></td><td>18 ± 3<sup>a</sup></td><td>15 ± 4<sup>a</sup></td><td>14 ± 5<sup>ab</sup></td></tr><tr><td>Final pH</td><td>5.45 ± 0.05<sup>a</sup></td><td>5.49 ± 0.14<sup>a</sup></td><td>5.18 ± 0.03<sup>a</sup></td><td>5.38 ± 0.13<sup>a</sup></td></tr></tbody></table>
sugars were detected on HPLC and no isobutyrate, isovalerate, valerate, isocaproate, caproate and lactate were produced at the end of the fermentation test. The severity factor was calculated to compare all pretreatments on the same basis, i.e. the temperature factor. The Ctrl condition had a severity factor of 0, while microwave pretreatments had very different values (4.36E + 02 for MW 40 °C and 8.87E + 05 for MW 95 °C) even though the energy of their pretreatment (irradiation part) was similar (0.23 Wh/L). Both MW 95 °C and Th 95 °C severity factors were close (8.87E + 05 and 2.60E + 06, respectively) compared with the difference between MW 40 °C and MW 95 °C. The severity factor difference between thermal conditions (MW 95 °C and Th 95 °C) could be explained by the heating time to reach 95 °C which was longer with the conventional heating (Th 95 °C).

Propionate (C3), butyrate (C4) as well as total metabolite production were the only parameters significantly different among horse dung pretreatment conditions according to the ANOVA and Tukey test. Th 95 °C total metabolite production (0.943 ± 0.043 g COD/g VS) was reported non-significantly different from MW 95 °C (0.810 ± 0.017 g COD/g VS) but significantly different both Ctrl (0.756 ± 0.076 g COD/g VS) and MW 40 °C (0.782 ± 0.031 g COD/g VS) conditions. The same conclusions were observed with C4 production and C4 selectivity, which were the highest with Th 95 °C and MW 95 °C. With xylose fermentation, both C4 and total metabolite production parameters seemed to be correlated to the severity factor. The higher the severity factor, the better the C4 and total production. C3 production was the highest with both microwave pretreatment conditions reaching up to 0.058 ± 0.004 g COD/g VS for MW 40 °C. The two MW conditions were significantly different from Th 95 °C. It can be concluded that the thermal impact of the pretreatments could select sporulating bacteria that produce metabolites (Wang and Yin, 2017) with increased kinetics. Moreover, thermal treatments (Th 95 °C and MW 95 °C) lead to the same fermentation yield and the same metabolic production. Microwave pretreatment can be used to replace a conventional thermal pretreatment on indigenous inoculum to achieve the same fermentation performance under the conditions tested.

## 3.2. Impact of inoculum pretreatment on the performance of wheat straw fermentation

Wheat straw was used as a complex and lignocellulosic substrate to capture the impact of pretreatments on horse dung communities, including hydrolytic microorganisms. Table 2 also shows the metabolite profile and the conversion yield for the wheat straw fermentation concerning every pretreatment inoculum at day seven. No residual sugars were detected on HPLC and no isobutyrate, isovalerate, valerate, isocaproate, caproate, lactate, and butanol were produced at the end of the fermentation test.

The ANOVA test performed on total metabolite productions gives significant differences among groups as shown in Table 2. Thus, the Ctrl with the lowest severity factor (i.e. 0) showed the lowest total metabolite accumulation with only 0.126 ± 0.009 gCOD/gVS. This value is significantly different from the thermal conditions (i.e. MW 95 °C and Th 95 °C), with 0.181 ± 0.031 and 0.186 ± 0.011 gCOD/gVS, respectively. Microwave and thermal pretreatments at 95 °C lead to the same metabolite production without any CH₄ production, supporting that both conditions are suitable for inoculum pretreatment before fermentation. The fermentation test of the MW 40 °C condition has an intermediate value with 0.154 ± 0.027 gCOD/gVS.

The metabolites produced were similar between the conditions tested with a majority of acetate (ranging from 66 ± 9 to 80 ± 10 % for C2 selectivity). The accumulation of propionate, ethanol, and butyrate was statistically different between the conditions. The highest production of both propionate and ethanol was related to the Th 95 °C condition (0.016 ± 0.007 and 0.015 ± 0.010 gCOD/gVS for propionate and ethanol respectively). However, the highest butyrate production was related to the MW 95 °C condition with 0.028 ± 0.007 gCOD/gVS.

Butyrate production was statistically more abundant in the fermentation bottles of the three pretreatment conditions than in Ctrl. This effect was even more pronounced by focusing on C4 selectivity, accounting for 18 ± 3 % with MW 40 °C, the highest selectivity but only significantly different from the control which accounts for 10 ± 1 %. MW 95 °C and Th 95 °C pretreatment conditions led to a C4 selectivity of 15 ± 4 % and 14 ± 5 %, respectively.

According to Table 2, the final pH was inversely correlated to the total metabolite production, which seems coherent because VFA accumulation is linked to pH drop. Finally, no methane production was observed in the Ctrl condition probably due to the high substrate-to-inoculum ratio (i.e. 15) and the short duration of the experiment. Preliminary tests (data not shown) revealed the presence of methane at 7 days during unpretreated horse dung fermentation. These preliminary results suggested pretreatment to inhibit methane production, which were done for the fermentation tests of both xylose and wheat straw. In this fermentation test, a very small and non-significant methane production was quantified at day seven only for the MW 40 °C condition confirming the necessity of heat treatment to completely deactivate *Archaea*.

A principal component analysis (PCA) was drawn (Fig. 2) to display correlations between metabolites and parameters such as final pH or severity factor for all conditions with wheat straw fermentation. In addition to the parameters already present in Table 2, an irradiation factor was calculated based on the absorbed energy delivered by microwave pretreatments in Wh/L. It also shows the distribution of the replicates and gives information on homogeneity between the conditions. The two axes of the PCA represent 74.2 % of the total variance with the data provided. Interestingly, the Ctrl replicates were found to be homogeneously represented on the PCA. In contrast, the representation of pretreated inoculum replicates was less homogeneous. On one hand, the production of propionate (C3) and ethanol (EtOH) appeared to be correlated to the severity factor with arrows representing propionate and ethanol production in the same direction as the severity factor, as shown in Fig. 2. On the other hand, the final pH was found to be inversely correlated to the total metabolites and the butyrate (C4) production. In summary, the higher the severity factor of the inoculum pretreatment, the better the conversion yield. A positive impact of inoculum pretreatment on metabolite production was observed, as already seen on the dark fermentation of wax gourd, with a cow dung inoculum pretreated with microwaves (Singhal and Singh, 2014). It can be concluded that thermal treatments, i.e. Th 95 °C and MW 95 °C, lead to the same fermentation yield as well as the same metabolic productions and were more likely to reach higher total metabolite production which was also pointed out with xylose fermentation.

## 3.3. Influence of pretreatment on microbial communities after wheat straw fermentation

First, a barplot representing the relative abundance distribution of the bacterial community with class and family composition found in each pretreatment condition is presented in Fig. 3. At the initial time, the horse dung community was mostly dominated by the Bacilli class and especially by the Planococcaceae family, accounting for 68 to 77 % of the total relative abundance depending on the replicates. Unfortunately, the metabarcoding analysis was not able to provide more information concerning the genus identification of the Planococcaceae family. Some taxa of the Clostridia and Gammaproteobacteria classes were also present in a minority. At day 7, the barplot of Ctrl as well as MW 40 °C, MW 95 °C, and Th 95 °C conditions showed a strong decrease in the abundance of Planococcaceae. Shivaji et al., (2014) reported that some members of this family are either spore-forming and non-spore-forming bacteria and ranging from aerobe to facultative anaerobe. Since the strong decrease of this taxon occurred in every condition including the control at day 7, its disappearance does not lie in its inability to form spores. However, this could be explained by the selection pressure of the
<figure><img src="image_5.png" /><figcaption>Fig. 2. Principle component analysis of wheat straw fermentation test with different pretreatment conditions at day seven.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Fig. 3. Barplot distribution of the bacterial community with class and family composition at T0 (control sample) and after seven days (Tfinal) of wheat straw fermentation with untreated (control) and pretreated inoculum.</figcaption></figure>

abiotic factors of the fermentation test, referred to as environmental filtering in ecology.

The strong emergence of the Clostridia taxa was reported at day 7 for every condition compared with the control at T0. A similar composition of the Clostridia class was reported with Clostridiaceae, Lachnospiraceae, Pepetococcaceae, and Ruminococcaceae. The Ctrl and both microwave pretreatment conditions were found replicable with no major changes within triplicates. However, the thermal condition (Th 95 °C) showed poor replicability with the presence of the Bacteroidaceae family found in replicate 1 (Rep. 1) only. *Bacteroides* sp. was found to be the only genus from the Bacteroidaceae family in this replicate. This genus is known to form an important part of the intestinal microbiota,

but is unable to sporulate and is commonly found at a temperature of 37 °C (Claros et al., 2022). Moreover, a major difference between Lachnospiraceae (from 3 to 46 % relative abundance) and Ruminococcaceae (from 25 to 47 % relative abundance) abundances among the Th 95 °C replicates was observed. Concerning the Ruminococcaceae family, a higher relative abundance was reached in both MW 95 °C and Th 95 °C conditions and a lower proportion of Lachnospiraceae was found in the same conditions. Some members of the Ruminococcaceae family are known to be spore-forming bacteria (Tanaka et al., 2020), which could explain why they were more likely to be found in thermal pretreatment conditions. Among the Ruminococcaceae family, the *Caproicproducens* genus was the most abundant, especially in both Ctrl
and MW 40 °C conditions. A higher diversity inside the Ruminococcaceae family was reported for both thermal conditions (data not shown). The *Mobilitalea* genus accounts for more than 80 % of the Lachnospiraceae abundance in every condition and is known for its ability to use plant-derived polysaccharides as its carbon source in anaerobic conditions (Thieme et al., 2021). However, this genus is not known for being able to resist thermal shock, which could explain why the Lachnospiraceae family was less abundant in both 95 °C conditions. The presence of the Enterobacteriaceae family in every condition, with *Klebsiella* and *Escherichia-Shigella* being the two most abundant genera, was correlated with the origin of the inoculum. The presence of the *Klebsiella* genus in horse dung has been well documented (Wareth and Neubauer, 2021) and some species of *Klebsiella* have also been used in dark fermentation (Liu and Fang, 2007). The equal abundance of the Enterobacteriaceae between pretreatments conditions is surprising because this family is known for being a part of the intestinal microbiota and not being sporulating, even though some Enterobacteriaceae were found to be heat resistant (Wang et al., 2018). However, there is a strong difference between conditions by looking at genus, with a vast majority (up to 95 %) of *Escherichia-Shigella* genus in the Ctrl and an increase of *Klebsiella* genus with the increase of severity factor for pretreatment conditions.

To conclude, Th 95 °C pretreatment led to a higher heterogeneity in the microbial community within replicates compared to MW conditions. One of the benefits of using microwave technology relies on a more uniform heating compared to classical thermal pretreatment, already pointed out (Chandrasekaran et al., 2013) and is confirmed in this study.

Alpha diversity indexes were calculated for wheat straw fermentation after different pretreatment conditions and are presented in Table 3. Both observed and chao1 indexes showed statistical differences among the conditions. The thermal conditions (MW 95 °C and Th 95 °C) belong to the same group with the lowest value, mainly due to the harsh conditions reached in both cases selecting mostly sporulating bacteria or thermophilic microorganisms. MW 40 °C fermentation test showed the highest observed richness amongst pretreatment with a value of 256 ± 9, which is significantly different from the thermal group. The Ctrl belongs to both thermal and MW 40 °C groups with 217 ± 8. An increase in the richness was observed at 40 °C, and could be related to the non-thermal effects of the microwaves. Rougier et al., (2014) reported previously that 2.45 GHz microwave pretreatment caused slight alteration of the cell membranes through non-thermal effects on *Escherichia coli*. They reported alteration of cell membranes only at a power of 400 W or higher which is different from the conditions tested here with a power of 200 W. It can be hypothesized that alteration of the cell membranes could lead to the loss of some cell components which could further be used by other microorganisms that cannot use lignocellulosic biomass to grow, explaining the increase of richness in these conditions. The same phenomenon was not observed with the microwave pretreatment at 95 °C condition because of the effect of the heat shock temperature on the cells. In contrast, the Shannon and Simpson indexes were not significantly different between the conditions, indicating a similar distribution of OTU abundance among the conditions.

A LEFSe analysis was performed on the bacterial community of wheat straw fermentation to point out the most significant genera amongst conditions with an alpha index of 0.05 (Fig. 4). LEFSe analysis is a statistical method used to determine the features (here the bacterial genera) that could explain differences between parameters (here the

<table><caption>**Table 3**
Alpha-diversity index of wheat straw fermentation at day seven.</caption><thead><tr><th rowspan="2">α-diversity index</th><th colspan="4">Wheat straw</th></tr><tr><th>Ctrl</th><th>MW 40 °C</th><th>MW 95 °C</th><th>Th 95 °C</th></tr></thead><tbody><tr><td>Observed</td><td>217 ± 8<sup>ab</sup></td><td>256 ± 9<sup>a</sup></td><td>189 ± 10<sup>b</sup></td><td>204 ± 39<sup>b</sup></td></tr><tr><td>Chao1</td><td>282 ± 13<sup>ab</sup></td><td>326 ± 10<sup>a</sup></td><td>235 ± 27<sup>b</sup></td><td>251 ± 54<sup>b</sup></td></tr><tr><td>Shannon</td><td>3.0 ± 0.2<sup>a</sup></td><td>3.1 ± 0.1<sup>a</sup></td><td>2.9 ± 0.2<sup>a</sup></td><td>2.8 ± 0.3<sup>a</sup></td></tr><tr><td>Simpson</td><td>0.90 ± 0.02<sup>a</sup></td><td>0.89 ± 0.02<sup>a</sup></td><td>0.88 ± 0.05<sup>a</sup></td><td>0.86 ± 0.05<sup>a</sup></td></tr></tbody></table>

inoculum pretreatment) by coupling standard tests for statistical significance with additional tests encoding biological consistency and effect relevance (Segata et al., 2011). In Fig. 4. A, the abundance and standard deviation of the 10 most significant biomarkers (genera) detected by LEFSe are represented for every condition. In Fig. 4. B the linear discriminant analysis (LDA) score for the same 10 most significant genera is used to estimate the effect size of each differentially abundant feature: the higher the score, the stronger the effect.

Two members of the *Ruminiclostridium* genus (*Ruminiclostridium* and *Ruminiclostridium_1*) were highlighted as statistically significant. This genus was found to be very abundant in both thermal conditions with a relative abundance of up to 25 ± 6 % and 35 ± 4 % for Th 95 °C and MW 95 °C respectively and less than 10 ± 4 % of the total bacterial relative abundance for Ctrl and MW 40 °C. Moreover, the LDA scores for *Ruminiclostridium* genera are amongst the highest of the 10 most significant biomarkers with a LDA of 5.2 for *Ruminiclostridium_1* (ranked 1st) and 4.2 for *Ruminiclostridium* (ranked 5th). According to the literature, this genus is known for its hydrolytic activity and the ability to create cellulosomes (Ravachol et al., 2016). Cellulosomes are multi-enzyme extracellular complexes produced to degrade polysaccharides such as cellulose, which account for a major part of sugars found in wheat straw (Liu et al., 2005). The high relative abundance of this genus could contribute to a better hydrolytic stage which is known to be a crucial limiting step (Menzel et al., 2020) in anaerobic digestion and fermentation, and therefore could improve the kinetics of fermentation for both thermal conditions (MW 95 and Th 95 °C). Members of the *Ruminiclostridium* genus are known for their ability to produce mainly acetate as well as ethanol, H₂, and CO₂ from carbohydrates (Rettenmaier et al., 2021; Wu and Cheng, 2021). The higher the severity factor was, the lower *Escherichia-Shigella* relative abundance was, as shown in Fig. 4. A. *Klebsiella* genus is correlated to the severity factor because it is found in all conditions except Ctrl. This microbial genus has been reported in the literature to produce C₂, ethanol as well as H₂, and CO₂ (Liu and Fang, 2007). *Fonticella* genus, known for its ability to produce mainly C₂ but also ethanol, and formate in the acidogenesis stage (Fraj et al., 2013) was present in both Ctrl and MW 40 °C conditions but absent (MW 95 °C) or in lower abundance (Th 95 °C) in other conditions. Furthermore, this genus was reported to have a growth range of 45–70 °C which could explain the statistical difference concerning the relative abundance of this genus with pretreatment at 95 °C (Fraj et al., 2013). Thus, acetate was always the major fermentation product in the fermentation test because there were always microbial genera capable of producing this fermentation product no matter the pretreatment used.

Based on the LEFSe analysis, MW 95 °C and Th 95 °C conditions showed the same tendency with equivalent relative abundance, probably linked to similar thermal effects.

To better visualize the distribution of the bacterial communities between pretreatment conditions as well as the reproducibility between replicates for each condition, a non-metric multidimensional scaling (NMDS) of the microbial community was performed and is represented in Fig. 5. In addition to the NMDS, a boxplot of all replicates of each condition was plotted for both axes, and an ANOVA test was performed. The NMDS is a graphic solution for representing similarity between samples in two dimensions, using the Bray-Curtis beta-diversity index as the measure distance. The NMDS representation is considered excellent with a score of 0.04. Both Ctrl and MW 95 °C condition triplicates are homogeneous in their representation of the NMDS. However, MW 40 °C and Th 95 °C replicates had a heterogeneous distribution on the NMDS. This lack of homogeneity could be explained by non-uniform heating selecting different populations between replicates, which is consistent with the literature (Chandrasekaran et al., 2013) for the Th 95 °C. Boxplot and statistical analysis of the MDS1 axis reflects a significant difference amongst conditions resulting in two groups. First, a thermal group composed of Th 95 °C and MW 95 °C and second, a non-thermal group composed of MW 40 °C and Ctrl conditions. No significant difference was detected with the MDS2 axis.
<figure><img src="image_7.png" /><figcaption>Fig. 4. LEfSe analysis of bacterial community for every pretreatment condition after wheat straw fermentation using $\alpha = 0.05$.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 5. Non-metric multidimensional scaling of microbial community after various pretreatment conditions and wheat straw fermentation using Bray-Curtis index.</figcaption></figure>

To verify the potential impact of the pretreatment on microbial communities given by NMDS 1 boxplot and statistical analysis in Fig. 5, a PERMANOVA was performed. The PERMANOVA statistical analysis gives a significant difference between pretreatment groups. The “Pretreatment” parameter explains 58 % of the total variance in the composition of the multivariate communities, and this parameter is statistically significant with a p-value of 0.004.

This study aimed to quantify the impact of microwave irradiation on the microbial communities of horse manure during microwave pretreatment before acidogenic fermentation. A positive impact of the pretreatment severity factor applied to the inoculum was recorded

concerning total metabolite yield. Indeed, both conventional heat treatment and microwave treatment at 95 °C led to equivalent metabolite yields and a significantly higher *Ruminiclostridium* abundance. On the other hand, the MW 40 °C pretreatment (assuming to induce mainly an irradiation phenomenon) had no impact on metabolite production but could be linked to a slight enhancement of the $\alpha$-diversity richness index. Further works are needed to support these results and possibly link them with non-thermal effects.

Extensive investigations on functional properties according to microbial diversity of horse dung would be needed for further research. Tools such as metagenomics could help to understand better the
dynamic changes, as well as the functional diversity and the metabolic pathways involved. Moreover, to better understand the impact of microbial indigenous communities on fermentation, it would be interesting to take into account the indigenous community of wheat straw as reported by Alvarez-Guzmán et al. (2025). Continuous fermentation process would also be interesting to verify whether the inactivation of archaea is maintained under these conditions over a long operation time. Such reactors would be useful to carry out a techno-economic analysis to determine whether it would be worthwhile to replace conventional heat treatment by microwave. Finally, investigating the microbial community drift along the fermentation would be of great interest to better understand the effects of pretreatment over time, and the dynamics of the microbial community emergence.

## 4. Conclusion

The effect of microwave pretreatment on horse dung microorganisms was investigated before the acidogenic fermentation of wheat straw. Heating horse dung inoculum with microwaves showed the same fermentation performances as a conventional thermal pretreatment. Nonetheless, conventional pretreatment induced a higher heterogeneity in the microbial community compared to microwaves, suggesting that MW was more suitable for bacterial selection. Moreover, non-thermal effects of 40 °C microwave pretreatment could explain an enhancement of the alpha-diversity richness index. This study opens up new possibilities for the use of microwaves as a treatment for microbial indigenous community selection.

## CRediT authorship contribution statement

**Korantin Pipereau:** Writing – original draft, Visualization, Investigation, Formal analysis, Conceptualization. **Eric Trably:** Writing – review & editing, Validation, Supervision, Conceptualization. **Gaelle Santa-Catalina:** Formal analysis. **Diana García-Bernet:** Writing – review & editing, Validation, Supervision, Conceptualization. **Hélène Carrere:** Writing – review & editing, Validation, Supervision, Funding acquisition, Conceptualization.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

This project was funded through Labex AGRO-2011-LABX-002, project 2201-39 (I-site Muse framework) coordinated by Agropolis foundation. The authors would like to acknowledge INRAE Bio2E Facility (Bio2E, INRAE,2018. Environmental Biotechnology and Bio refinery Facility (DOI: 10.15454/1.557234103446854E12) where experiments were conducted.

## Data availability

Data will be made available on request.

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