\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[ngerman,greek,english]{babel}



\usepackage{float}








\begin{document}

\title{Anaerobic digestion concert of agro-food wastes and the correlated microbial population dynamics under suboptimal, well-performed and disturbed states}



\author[1]{Dong-min  Yin }%
\author[2]{Dr. Ahmed Mahdy}%
\author[1]{Yue-ling  Liu}%
\author[3]{Camilla  Negri }%
\author[3]{Davide  Bianchi }%
\author[4]{Fabrizio Adani}%
\author[1]{Wei  qiao}%
\author[1]{Renjie Dong}%
\affil[1]{China Agricultural University}%
\affil[2]{Zagazig University}%
\affil[3]{University of Milan}%
\affil[4]{Universita degli Studi di Milano}%


\vspace{-1em}



  
  \date{May 04, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
The comparison among microbial interactions during the stable
performance of anaerobic digestion (AD) and the process disturbances is
still lack and could limit the prediction of process failure and the
possible recovery. This study aimed at characterizing the process
performance and microbial communities' profiles during the stable and
disturbed states of long-term thermophilic AD process fed with agro-food
wastes. The disturbances were induced in two stages, firstly under a
stepwise increase of organic loading rate (OLR), and then through the
reduction in hydraulic retention time (HRT). Volatile fatty acids (VFAs)
only accumulated (4730 mg L-1) when OLR increased to 17 g VS L-1 d-1,
and consequently methane yield deteriorated by 47\%, implying process
overloading and thus AD process was partially inhibited. Process
disturbances led to 30\% reduction in relative abundance of Defluviitoga
and Methanoculleus which were partially displaced by Clostridium and
Methanomassiliicoccus, implying that the process acidification
immediately reflected on microbial profile and the microbes were
functionally redundant. Microorganisms' washout was the main reason
behind methane yield drop under finite digestion time (1.5d). Microbial
profiles shaping showed the robustness of AD process due to the
functionally redundant microorganisms and could be strategically used to
control and optimize AD process.%
\end{abstract}%



\sloppy


\par\null

\begin{enumerate}
\tightlist
\item
  \textbf{Introduction}
\end{enumerate}

Since the time of the industrial revolution, the utilization of fossil
fuels has severe environmental pollution which was the direct cause of
global warming (GW) because of the emission of greenhouse gases
(GHG)\emph{.} Therefore, the `road map' indicates that by 2050,
according to internal energy agencies (REN21 report, 2013), about 75\%
of the global primary energy supply ought to be renewable. Agro-food
wastes provide huge amounts of biodegradable materials which can be
recycling to recover energy or commercial products as bio-refinery
processes. In china alone, for example, the annual production of food
waste and crop straw are about 30 and 600 million tons, respectively
(Chen et al., 2012; Dongyan et al., 2014). Numerous negative
environmental aspects, such as aquatic life toxicity, altered soil
quality, phyto-toxicity, GHG and mal odor may be emerged because of
improper practices of such wastes (Nayak and Bhushan 2019). As a
consequence, it is crucial to develop a specific, efficient and
sustainable approach for treatment of agro-food wastes.

Anaerobic digestion, a microbial-based process where the microorganisms
play a pivotal role in degrading organic pollutants to biogas, is one of
the most efficient waste management strategies worldwide and thus
``two-in-one'' advantage of waste disposal and energy production could
be achieved. AD is divided to four interdepended processes namely,
hydrolysis, acidogenesis, acetogenesis and methanogenesis where the
products of one stage are the substrate of the other stage until the
biogas is produced. The syntrophic relationship among the microorganisms
(bacteria and archaea) involved in these stages is the key for the
process stability.

Mechanisms of microbial assemblage in anaerobic digestion process remain
unclear. However, temperature, substrate composition, OLR and HRT
represented most important operating conditions, affecting structure of
anaerobic microbiome (Cho et al., 2017; Nag et al., 2019). The
disturbances in such parameters were reported to play a crucial role in
the microbial profiles shaping as a result of accumulation of some
intermediate products such as VFAs. The methanogens, for instance, are
the most sensitive to process disturbances and thus result in unbalance
between VFAs producers and consumers. As a matter of fact, there are
three basic behaviors could be distinguished in the microbial dynamics
under harsh conditions, namely, 1) resistance in which microbes can deal
with changes and thus no composition variation will take place, 2)
resilience in which microorganisms able to recover after upset and 3)
redundant in which new microbes have the ability to replace the
disturbed populations (Carballa et al., 2015). Even though
microorganisms involved in different AD stages are functionally
redundant (De Vrieze et al., 2017; Zhang et al., 2019), the distinct
members that are able to replace each other upon operational
disturbances need more investigation.

Since operational disturbances such as temperature fluctuation or over
feeding may accidently occur during the industrial-scale operation.
Therefore, it is essential to clarify the effect of the disturbances in
process performance and link it to microbial population. Indeed, the
impacts of operating parameters disturbances on process stability were
frequently investigated with regard to their effects on biodegradability
efficiency and biogas production (Mahdy et al., 2015). A sharp drop in
methane yield and high VFAs concentration (9000 mg/L) were observed when
OLR increased up to 6 g VS/ L/d (Li et al., 2015). However, kinetics
synergies among interdependent reactions and its correlating to
microbial dynamic and function under stable and harsh conditions still
so far unclear and require more investigation. Some investigations have
revealed microbial community composition in many healthy anaerobic
digesters to enhance the process management (Li et al., 2016; Li et al.,
2019). Other studies have even linked harsh conditions (extreme ammonia,
HRT, temperature and OLR disturbances) with microbial profiles in
healthy AD process. For instance, Tian et al., (2018) studied population
dynamics in digesters with step-wise increase in ammonia concentration
up to 10 g NH4/L with stable methane production (more than 95\% on
uninhibited phase). Jiang et al. (2019) revealed the stability of
process performance and microbial structure under ambient temperature.
Mahdy et al., (2019a) demonstrated microbial community shifts in the
digesters with different OLRs and HRT under stable-state conditions. A
very few studies have taken the deteriorative phase into accounts.
Furthermore, although it is well accepted that high loading rate with
short retention time, for instance, could increase the process capacity
of the plant, the processes under such conditions have to be handled
carefully and the entire process management including the response of
the AD microbiome should be fully assumed.

Therefore, this study aimed to compare the process performance and the
population profiles that were stablished at optimal OLR and HRT in AD
process fed with agro-food wastes with that attained under organic
overloading and finite digestion time. To achieve this goal, 5 different
OLRs were investigated and meanwhile HRTs were shortenings down to 1.5
day, during which methane yield, methane production and major
intermediates were evaluated as well as phylogenic analyses targeting
16S rRNA sequences and quantitative polymerase chain reaction (qPCR)
were performed to monitor microbial communities of each state. Overall,
the objective of this study was the highlighting attempt to reveal how
processes respond to varying exterior effects and how the performance of
AD microorganism can be reacted and thus the comparison between
well-performed and disturbed microorganism could be used for
knowledge-based process control.

\textbf{2. Materials and methods}

\textbf{2.1 Summarize of raw materials and inoculum}

Food waste was sampled from the students' canteen during lunchtime in
China Agricultural University every 2-3 weeks. Unsuitable materials,
including bones, plastic, and chopsticks etc, were picked out by hand in
laboratory and then the food waste was shattered with a blender (Joyoung
JYLC012, China) for 5 minutes and stored in plastic bottles at 4\selectlanguage{ngerman}°C.
Maize straw was crushed by a small grinder (HC-1000Y2, China), sieved
using a 40 mm sieve and stored. The inoculum was initially collected
from an operated anaerobic plant with feedstock of cornstalk under
thermophilic condition. The basic characteristics of food waste, maize
straw and inoculum are shown in Table (1).

\textbf{2.2 Experimental design and operation}

A continuous stirred tank reactor (CSTR) was setup with a whole volume
of 2.5 L (2 L of working volume) under thermophilic conditions (55±1°C).
The reactor was stirred automatically every 2 h for 10 min at a speed of
50-90 rpm and a thermostatic circulating water tank (HH-60, China) was
employed to keep the set-up temperature. The reactor was fed with a mix
of straw and food waste (1:1 on dry matter basis) for 270d in two
stages. During the first stage (1-218 days), the reactor was operated by
a stepwise OLR-increase program, i.e. from 2.6 to 5.4, 7.9, 10.2 and
17.1 g VS L-1 d-1. A peristaltic pump (BT300N-YZ1515x, China) was
applied for 4 times feeding per day and controlled by a timer and a
relay. The process upset in the first stage was temporary and was
resolved by stop feeding until the accumulated VFAs from the previous
period were depredated (from 219-230 day). During the recovery period,
the accumulated VFAs reduced from 3725 down to 295 mg L-1. Once process
stability was restored by day 230 of operation, the second stage
(231-270 days) was designed with a stepwise HRT decrease from 5 to 3 and
finally to 1.5 with the best OLR obtained in first stage (Table 2). The
feedstock was fed into into the reactor 6 times per day by the timer and
a peristaltic pump. The daily effluent of the reactor was withdrawn
before the influent addition by a peristaltic pump.

\textbf{2.3 Chemical analyses}

Effluent samples were taken from the reactor every 1-3 days under
different stages. The total solids (TS), volatile solids (VS) of the
substrates and effluent were measured with dry methods to a constant
weight at 105°C for 24 h in an electric heating air-blowing drier and at
600°C for 2 h in a muffle stove, respectively (Sluiter et al., 2005).
Total and soluble chemical oxygen demand (TCOD and SCOD), and ammonium
nitrogen were sampled every three days, and then measured with standard
methods (APHA 2005). Contents of C, H, O, N, S were measured through a
Macro Element Analyzer. The biogas (CH4 and CO2) composition, volume,
VFAs and pH were determined as previously described (Mahdy et al.,
2019b). One-way analysis of variance (ANOVA, \emph{p}\textless{}0.05)
was applied to identify the statistical significance.

\textbf{2.4 16S rRNA sequences}

Samples were collected directly from anaerobic digester within
steady-state conditions (the 200th and 213th days) for microbial
community analyses at OLR of 10.2 and 17.1 g VS L-1 d-1, respectively
(first stage). In addition, the microbial samples were also obtained
during the shortening of the HRT from 5 to 1.5d (second stage) after 3
HRTs during process stability. Samples were stored at -20°C until being
analysed. DNA extraction, 16S rRNA amplification, PCR procedures and
sequencing libraries were operated according to previous studies (Yin et
al, 2018). Representative sequences were filtered for each operational
taxonomic unit (OUT). Three alpha diversity i.e. Chao1 (microbial
richness), Shannon and Simpson (microbial diversity) were calculated
with rarified OTU table.

Total bacteria and three abundant methanogen orders, Methanobacteriales,
Methanosarcinales and Methanomicrobiales, were detected by using
Quantitative polymerase chain reaction (qPCR) to analyze the microbial
community dynamics when shortening the HRT from 5 to 1.5d. Primers were
designed according to the 16s rRNA gene sequence as a previous study
(Shi et al., 2018). Slurry sample at HRT of 5d was amplified by PCR
using four sets of primers. The fragments were recovered from the gel,
ligated to the PUC-T vector, and then transformed into \emph{E.
coli}DH5a for cultivation. Positive clones were selected to extract
plasmids, and nucleic acid detectors were used to determine the
concentration and purity. The concentrations were converted to copies
and serially diluted. The purified PCR products were then sequenced, and
verified. Real Time PCR system (EDC-810, China) was performed as qPCR. A
qPCR mixture (20\selectlanguage{greek}μ\selectlanguage{english}L) containing 1\selectlanguage{greek}μ\selectlanguage{english}L of slurry sample, 0.4\selectlanguage{greek}μ\selectlanguage{english}L of each
forward and reverse primer (10\selectlanguage{greek}μ\selectlanguage{english}mol/L), 10\selectlanguage{greek}μ\selectlanguage{english}L of 2\selectlanguage{ngerman}×sybr MIX (with ROX),
sterile water to a total of 20\selectlanguage{greek}μ\selectlanguage{english}L, and Power SYBR Green (Baygene
BG-Power600, China) were used to prepare template DNA (20ng). The
amplification processes of the total bacteria and the order
Methanobacteriales were as follows: A cycle consisted of 3 min at 94\selectlanguage{ngerman}°C;
94°C for 15s with totally 40 cycles, 20s at 60°C, 72°C for 20s, 2 min at
72°C; and extension at 72°C for 20s. The additional steps for the orders
Methanosarcinales and Methanomicrobiales were carried out at 94°C for
15s with 40 cycles, i.e. 52°C, 72°C and 72°C for 20s 30s and 2 min,
respectively; and extension at 20s at 72°C. For each primer and probe
set, a control without the equivalent template DNA was consisted in
every qPCR assay. Triplicate standard samples were constructed for each
primer set, of which one was selected to draw a standard curve.

\textbf{3. Results and discussion}

The data presented in Table 1 demonstrates the characteristics of food
wastes and maize straw before being mixed to be used as substrate for
anaerobic digestion process. The predominant macromolecule of food
wastes was lipid, exhibited 37.4\% of total macromolecules. The protein
fraction was approximately 21\% of total macromolecules. Both
macromolecules summed up 60\% of total food wastes macromolecules,
mediating C/N ration to be relatively low (14). Opposite, the prevailing
content of C-rich molecules in maize straw mediated a higher C/N ratio
to be 53, which acts as a limiting factor for the regular growth of
bacteria. Macromolecules distribution and elemental analyses attained
for food wastes and maize straw is in good agreement with literature
(Algapani et al., 2016; Peng et al., 2016). The characteristic results
of both substrates indicated that both substrates were far away of ideal
C/N ratio for anaerobic digestion i.e. 20 to 30 (Nayak and Bhushan 2019)
and this ratio thus needs to be adjusted. In this study, the mixture of
N-rich food waste and C-rich maize straw by (1:1) had a balanced C/N
ratio of 33.

\textbf{3.1 Process performance under stable and disturbed states
targeting OLR}

As shown in Fig. 1a, in the first stage, when the OLR was promoted from
2.6 to 5.4, 7.9 and 10.2 g VS L-1 d-1, the biogas production gradually
increased from 0.9 to 3.0, 4.6, and 5.7 L L-1 d-1, respectively.
However, an additional increase in OLR (17.1 g VS L-1 d-1) resulted in a
sharp decrease in the biogas production. The highest specific methane
yield measured under a steady-state was 393±25 mL-CH4 g VSin-1 at 7.9 g
VS L-1 d-1 of OLR. No-significant (\emph{p} \textgreater{}0.05)
reduction was observed with the OLR promoted to 10.2 g VS L-1 d-1 (i.e.
385±25 mL g VSin). Contrary, the specific methane yield significantly
(\emph{p} \textless{}0.05) decreased down to 348±59 mL g VSin at 5.4 g
VS L-1 d-1. Results reported in previous studies were less than that
attained in current study in both the thermophilic and mesophilic AD
processes of agro-food wastes (Hobbs et al., 2019; Shi et al., 2018)
which may be more likely related to the C/N balance and/or a good
synergistic of such substrates. Remarkably, the specific methane yield
dropped suddenly at 17.1 g VS L-1 d-1 of OLR (Fig. 1b), implying process
overloading and thus AD process was partially inhibited. These results
indicated that the capacity of the process could be increased with
increasing OLR up to 10 g VS L-1 d-1 without affecting the process
stability, however a closer look into common intermediates could be
helpful to elucidate the reason behind the observed methane yield
reduction at highest OLR.

In Fig. 1c, the total VFAs content in the reactor varied between 124-398
mg L-1 under different OLRs up to 10.2 g VS L-1 d-1. All VFAs values
were much lower than 1000 mg L-1, the threshold reported as the levels
in which acid suppression becomes evident (Chen et al., 2012), implying
that the activity of anaerobic microbiome (acidogens, acetogens and
methanogens) was balanced and consequently, proper operation concert was
achieved. Nevertheless, the OLR of 2.6 and 5.4 g VS L-1 d-1 were not
enough for an efficient performance and thus their methane yields were
lower than higher OLR. On contrary, once the OLR reached 17.1 g VS L-1
d-1, the VFAs accumulated sharply to 4730 mg L-1 which triggered the
cessation of the methane production (Table 2 and Fig. 1). It seems
likely that additional increase in OLR over than 10.2 g VS L-1 d-1 led
to organic matters overload and accordingly, unbalance equilibrium
between acidogenesis/acetogenesis and methanogenesis took place. These
results signified that different microbial groups might be influenced
differently at variable OLRs. The acetate is the main driver for the
overall methane production, nevertheless, the accumulation of acetate
(1,411 mg L-1 in this study with an OLR of 17.1 g VS L-1 d-1) could
hamper not only acetogenic bacteria but also the degradation of
propionate (Wagner et al., 2014). By this way, the propionate/acetate
ration could serve as a reliable indicator for bacteria stress in
overloaded digesters and impending failure (Marchaim and Krause 1993).
In this study, the VFA composition for AD carried out at OLR of 17.1 g
VS L-1 d-1 was quite different compared to the steady-state period
(OLR\selectlanguage{english}[?]10.2 g VS L-1 d-1) during which acetic and propionic acid were at
an average concentration of lower than 340 and 50 mg L-1, respectively.
In fact, propionate (2213 mg L-1) tended to dominate the VFAs
(accumulated to 4730 mg L-1) at OLR of 17.1 g VS L-1 d-1 (Fig. 1c),
implying a lower substrate utilization by acetogens. The fluctuation in
the VFA content was in accordance with the specific methane yield (Fig
1b, c), indicating a close relationship between VFAs concentration and
methane yield and consequently, an overloading of the system and
subsequent reduction in methane production were attained.

Interestingly, despite the main reason of inhibition associated with
VFAs being the creation of a pH decline, the pH values (Fig. 1b)
registered under acceptable levels for AD process regardless OLR levels.
The pH values for all OLRs were between 7.2 and 7.6 throughout the first
stage of the experiment (OLR 2.6-17.1 g VS L-1 d-1). The volatile solids
removal calculated under different OLRs was 60\% +-7\% except at 17.1 VS
L-1 d-1 of OLR (continuously decreasing) (Fig. 1d). Specifically, VS
removal efficiency with OLR of 17 g VS L-1 d-1 decreased 2-fold when the
value was compared to data attained with other OLRs. These values are in
good agreement with the values attained for methane yields which were
sharply declined, leading the process to be crashed. The data was in
agreement with previous investigation that OLR is a deterministic
parameter affecting the process performance by shaping the microbial
profile in the digesters (Mahdy et al., 2019a). Consequently, both OLR
of 7.9 and 10.2 g VS L-1 d-1 which demonstrated highest methane yields
with stable performance could be considered as optimal ORL threshold
when treating agro-food wastes and thus both values are recommended for
process optimization.

\textbf{3.2 Microbial communities under well-performed and disturbed
states targeting OLR}

Linking the microbial dynamics to process perturbations is fundamental
in order to understand and deal with process instability. Therefore, two
OLRs were chosen in order to investigate the microbial community
structure, i.e. during process stability at 10.2 g VS L-1 d-1, and
subsequent process disturbances (17 g VS L-1 d-1). In Fig. 2, bacterial
community compositions slightly changed under the two OLR conditions
although the abundances were different.\emph{Thermotogae} (phyla
\emph{Thermotogae} ) were the predominant bacterial class, followed by
\emph{Clostridia} (phyla \emph{Firmicutes} ) and \emph{Synergistia}
(phyla \emph{Synergistetes} ) at both OLRs. It has been reported that a
significant number of members belonging to phylum\emph{Thermotogae}
frequently seem to be higher in thermophilic digesters (Shi et al.,
2018). This phenomenon may be attributed to their ability to encode
thermo-stable enzymes that play a role in conversion processes (Conners
et al., 2006). At an OLR of 10.2 g VS L-1 d-1,
\emph{Defluviitoga}(79.7\%) dominated the microbial genera (Fig. 2a). At
an OLR of 17.1 g VS L-1 d-1, \emph{Defluviitoga} decreased to 49.8\% but
there were significant increases in \emph{Clostridium}
and\emph{Anaerobaculum} (Fig. 2b), implying that these microorganisms
were functionally redundant. Accordingly, it was obvious that the
increase in OLR resulted in alternation of the microbial abundant during
the experiment. Furthermore, the decline in relative abundance
of\emph{Defluviitoga} was associated with process failure, signifying
its significant role in substrate metabolism and process
stability.\emph{Defluviitoga} spp. are able to utilize a wide range of
carbohydrate as electron donors (Hania et al., 2012), thus the C-rich
straw in the substrate mixture might promote the enrichment of this
genus. \emph{Defluviitoga} spp. frequently exists not only in
thermophilic AD (Hania et al., 2012), but also in metabolic association
with hydrogenotrophic methanogens (Maus et al., 2016).

In this study, genera \emph{Tepidanaerobacter, Clostridium}
and\emph{Syntrophaceticus} , which were three possible syntrophic
acetate oxidation bacteria (SAOB), were detected at an OLR of 10.2 and
17.1 g VS L-1 d-1. As depicted in Table 3,\emph{Clostridium} sp.
represented 2.8\% and 11\% of total bacterial at 10.2 and 17.1g VS-1 L-1
d-1 of OLR, respectively. Consequently, the reduction in the relative
abundance of most dominant carbohydrate-fermenting species
(\emph{Defluviitoga} ) might be linked to simultaneous increase in
relative abundance of \emph{Clostridium} sp. and meanwhile promoted
carbohydrate availability in digester. The increased presence of SAOB
indicated the existence of SAOB combined with a hydrogenotrophic
methanogenesis (HM) pathway for methane formation\emph{.} SAOB of
genera\emph{Tepidanaerobacter} and \emph{Syntrophaceticus} were also
detected even though they were at less than 0.5\% during the two
OLRs.\emph{Syntrophomonas} , which is known to function as a syntrophic
microbe to degrade complex organic matters to simple fatty acids (Hansen
et al., 1999), was detected with little change in its relative abundance
with the OLRs of 10.2 and 17.1 g VS L-1 d-1 (0.7\% and 1\%,
respectively).

Hydrogenotrophic methanogens (including the genera
\emph{Methanoculleus}and \emph{Methanothermobacter)} represented 88.2\%
and 53.5 \% of all archaea population for OLRs of 10.2 and 17.1 g VS
L-1d-1, respectively (Fig. 2c, and 2d). The genus \emph{Methanoculleus}
clearly dominated at OLR of 10.2 g VS L-1d-1 (86.9\%) and OLR of 17.1 g
VS L-1d-1 (52.8\%).\emph{Methanoculleus} has been reported to be a very
efficient hydrogen-utilizing methanogen during the thermophilic AD of
chicken manure (Bayrakdar et al., 2017) and it acts as an important
partner with\emph{Clostridium ultunenes} (Yin et al., 2018)\emph{.} The
increased OLR to 17.1 g VS L-1d-1, as previously stated, reduced the
presence of \emph{Methanoculleus} , and coincided with the VFA
accumulation and the reduction of methane production (Fig. 1a and 1c).
Methylotrophic \emph{Methanomassiliicoccus}were represented at
relatively low levels at the two OLRs, however, their relative abundance
was obviously enhanced at highest OLR.\emph{Methanomassiliicoccus} is a
H2-dependent methanogen which can consume methylated compounds to
produce methane (Liu et al., 2016)\emph{.} Nevertheless, it has still
not been identified to act as a hydrogenotrophic partner for SAO and it
needs to be further verified (Westerholm et al., 2016). In fact, the
important role of both \emph{Methanoculleus} and
\emph{Methanomassiliicoccus} have been previously reported in AD of
lignocellulosic biomass (Li et al., 2018a). The acetoclastic
methanogens, \emph{Methanosarcina} accounted for only 2\% and 4\% of the
total archaea at an OLR of 10.2 and 17.1 g VS L-1d-1, respectively (Fig.
2). In this study, the high abundance of hydrogenotrophic methanogens,
and a low representation of acetoclastic methanogens at OLR of 10.2 g VS
L-1d-1, alongside a low concentration of acetate (338 mg L-1), strongly
indicated that the acetate conversion may be a two-stage process.

\textbf{3.3 Process performance under stable and disturbed states
targeting HRT}

During the HRT shortening stage (Fig. 3), the volumetric biogas
production registered was stable at around 4.4 L L-1 d-1 under 5 d HRT
(Fig. 3a). The specific methane yield was 354+-27 mL CH4 g-1 VS-1, and it
represented the 65\% v/v of the biogas (Table 2). This result fell
within the range reported, i.e. 182-368 mL CH4 g-1 VS-1, in previous
studies treating straw and food waste in batch reactors (Liu et al.,
2018); however, it was higher than that reported for the mono digestion
of food waste at longer HRT under thermophilic conditions (Kim et al.,
2006), implying a synergistic effect of the co-digestion strategy. The
methane yields declined by 29\% (251+-63 mL CH4 g VSin-1) alongside with
the decrease of the HRT to 3 and by 78\% (78+-12 mL CH4 g VSin-1) with
HRT shortened to 1.5 d, respectively.

With the decrease in the HRT, the propionate concentration only slightly
changed while the acetate concentration accumulated from 333+-197 mg L-1
to 951+-577 and 2533+-496 mg L-1 at HRT of 5, 3 and 1.5 d, respectively
(Fig. 3c and Table 1). The concentration of propionate at HRT of 1.5d
was stable at about 224+-75mg L-1 and so it was 2-fold lower than that
reported in HRT of 5d. It was therefore obvious that the consumption
rate of acetate was the primary rate-limiting factor at HRTs of 3 and
1.5 d. Although the concentration of VFAs sharply increased during the
shortest HRTs, it was much lower than VFAs concentration at OLR of 17.1
g-1 VS L-1 d-1 in the first stage of current study. Therefore, the
reason behind the reduction in gas production rate at this stage was
most probably due to the excessive microbial washout caused by the
shortest HRTs, and partially because of the impact of VFA accumulation
on methanogens activity. The phenomena of the washout effects and the
inhibition of VFA have been previously reported under HRT shortened to
5d (Algapani et al., 2016).

The VS removal efficiency with the shortening of the HRT was consistent
with the methane production results and this further verified the VFA
accumulation. Alongside with the decrease of the HRT, the removal
efficiency of VS decreased down to 5.2\% at the end of experiment, which
was 11-fold less than the removal efficiency attained at an 8d HRT. The
variation of pH between different HRTs was negligible and varied between
7.2 and 7.3. To conclude, the low methane production during the shortest
HRT can be explained by i) the finite digesting time; ii) the microbiome
washout effect; and iii) methanogenesis inhibition by VFA accumulation.

\textbf{3.4 The washout of microbial communities at a very short HRT}

In Table 4, the microbial (bacteria and archaea) richness and diversity
were obviously higher at a 5d-HRT and this gradually decreased with HRT
shortening. To be specific, OTUs of Chao1 estimations decreased by 26\%
and 33\% in bacteria and 23\% and 29\% in archaea when accompanied by a
decrease in the HRT from 5 to 3 and 1.5d, respectively. The same trend
was observed with Shannon and Simpson values although the reduction of
archaea diversity was greater than bacteria. However, all richness and
diversity scores observed in this study during the shortest HRT (1.5d)
were quite similar to data observed with different substrate (cow
manure) at a longer HRT (25 d) while bacteria richness in the current
study was obviously higher (Sun et al., 2015).

qPCR was performed during the reducing of HRTs. Genes of total bacteria
sharply decreased from 2.17x106 copies \selectlanguage{greek}μ\selectlanguage{english}L-1 at HRT of 5d down to
1.55\selectlanguage{ngerman}×104 copies \selectlanguage{greek}μ\selectlanguage{english}L-1 at HRT of 1.5d. This data was much lower than that
previously reported for an AD process dealing with food waste at HRT of
20d and OLR of 8.21 g-COD\selectlanguage{ngerman}·L-1, i.e. 1.2×107 copies \selectlanguage{greek}μ\selectlanguage{english}L-1 (Jang et al.,
2016). The trend of the three most abundant archaeal populations during
the HRT decreasing showed a pattern close to that of the
bacterial/archaeal ratio (Fig. 4), i.e. for HRT of 5, 3 and 1.5d, the
total archaeal population sharply decreased from 3.47\selectlanguage{ngerman}×105 to 3.4×104 and
then to 0.9×104 copies \selectlanguage{greek}μ\selectlanguage{english}L-1. Correspondingly, the bacterial/archaeal
ratio showed its steepest decline when the HRT dropped from 3d to 1.5d,
accompanied by the decline of the methane yield from 223 to 51 mL-1 g-1
VS. This indicated that the methanogenic population had declined
significantly and was unable to support a remarkable methane production
at HRT between 3d to 1.5d. Moreover, the significant decrease of VS
removal efficiency occurred (from 39.4\% to 5.2\%, Fig. 3d) together
with the accumulation of the VFA level (Fig. 3c). This thus indicated
that HRT of 1.5d was too short and led to a fast-microbial washout which
reduced the process performance (Table 2). Three major methanogenic
orders at HRTs of 5, 3 and 1.5 d were also quantified. The order
\emph{Methanobacteriales} significantly decreased from 4.76\selectlanguage{ngerman}×104 to
0.84×104 copies \selectlanguage{greek}μ\selectlanguage{english}L-1 when passing from HRT of 5d to 1.5d.
Orders\emph{Methanosarcinales} and \emph{Methanemicrobiales} were
2.49\selectlanguage{ngerman}×104 and 2.75×105 copies \selectlanguage{greek}μ\selectlanguage{english}L-1 at 3d HRT, and both decreased to
0.05\selectlanguage{ngerman}×104 copies \selectlanguage{greek}μ\selectlanguage{english}L-1 when the HRT was shortened to 1.5d (Fig. 4). The
results indicated that a very short HRT cannot sustain the thermophilic
AD operation although the thermophilic bacterial had a faster growth
rate.

\textbf{3.5 Microbial community under suboptimal and disturbed states
targeting HRT}

In the second stage (231-270 days), the bacterial genera were mainly
consisted of \emph{S1} (\emph{Thermotogae} phyla),\emph{Cellulosibacter}
(\emph{Firmicutes} phyla) and \emph{Clostridium}(\emph{Firmicutes}
phyla) (Fig.5 a-c). These results corresponded with those reported
previously in similar substrates, i.e. food waste and/or rain tree leaf
with a longer HRT (20 days) (Ratanatamskul and Manpetch 2016; Zamanzadeh
et al., 2017). It was previously shown that the genus\emph{S1} was
probably SAOB (Li et al., 2018b) but it has not yet been identified. In
the present study, possible SAOB (genera\emph{Tepidanaerobacter} and
\emph{Clostridium} ) (Tachaapaikoon et al., 2012) were detected at HRTs
of 5, 3, and 1.5 day (Table 3). The total percentage of potential SAOB
increased from 6\% to 11\% as the HRT was shortened from 5d to 1.5d. The
abundance of genus\emph{Tepidanaerobacter} was 0.8\% at HRT of 5d
(Fig.5a), which significantly increased to 2.9\% and 4.2\% when the HRT
decreased to 3 and 1.5d, respectively (Fig.5b and 5c). A species within
genus\emph{Tepidanaerobacter} , i.e. \emph{Tepidanaerobacter
acetatoxydans} , has previously been proved as a SAO bacterium
(Westerholm et al., 2011) and \emph{Tepidanaerobacter syntrophicus} was
isolated from thermophilic (55\selectlanguage{ngerman}°C) AD fed with either municipal solid
waste or sewage sludge (Sekiguchi et al., 2006). SAOB genus
\emph{Clostridium} did not change significantly with the decrease in the
HRT from 5d to 1.5d (Fig. 5a-c). The detected increase of SAOB indicated
the presence of a SAO-HM pathway, which was promoted with the stepwise
decrease of the HRT.

The archaeal community contained only hydrogenotrophic methanogens and
strongly differed between the different HRTs (Fig. 5 a-c). When the HRT
was decreased from 5d to 3d and then to 1.5d, the community richness and
diversity decreased as depicted in former section (Table 4).
Genus\emph{Methanoculleus} dominated with 57\% at an HRT of 5d (Fig.5a),
and when the HRT was shortened to 3d, the
genus\emph{Methanothermobacter} became the most dominate archaea
(93.8\%) (Fig.5b), which accompanied by an increase in its co-culture
SAOB \emph{Tepidanaerobacter syntrophicus} .\emph{Methanosarcia}
gradually decreased 1.7- and 2.4- fold along with shortening the HRT
from 5 to 3 and 1.5 day, respectively. The doubling time of
\emph{Methanothermobacterium} sp. was around 1.8h (Huber et al., 1982),
which was much shorter than the doubling time of\emph{Methanoculleus}
sp. (12h) (Seely and Fahrney 1983)\emph{.} In addition, the doubling
time of genus \emph{Methanosarcina} and\emph{Methanosaeta} were reported
to be at least 36h (Westerholm et al., 2011). During short HRT stages (5
to 1.5d), the faster growing hydrogenotrophic methanogens tend to
dominate and revealed its functionally redundant properties which may
syntrophically metabolize acetate with SAOB. In this study, the methane
formation under the short HRT condition was therefore possibly through
the SAO-HM pathway.

\textbf{4. Conclusions}

The current study revealed that thermophilic agro-food wastes could be
operated at OLR of 10.2 g VS L-1 d-1 and HRT 5-8d with satisfactory
stability and high methane yield. Process disturbances due to organic
over loading and/or finite digestion time led to imbalance among
interdepended reactions and thus digester acidification and subsequent
process disturbances were experienced. The shaping in microbial profiles
among stable and disturbed states suggested the occurrence of functional
redundancy within AD microbiome. Conclusively, even though increasing
OLR with shortening HRT is a feasible strategy for increasing process
capacity at existing plants, the threshold of both parameters that
guarantee the process stability should be carefully determined to avoid
process disturbances. Since existence of disturbances is unavoidable in
real systems, microbial community could be utilized as a pivotal
bio-indicator to control AD process performance and stability.

\textbf{Acknowledgements}

The current study was supported partially by the Ministry of Science and
Technology of China within the China-Italy Cooperation on FW Energy
Utilization (SQ2013ZOA000017), and the Beijing Municipal Natural Science
Foundation (No.6182017). The visits of David Bianchi and Camilla Negri
in China Agricultural University were supported by the project
(SQ2013ZOA000017). Dr. Ahmed Mahdy would like to thank for the financial
support from State Administration of Foreign Experts Affairs P.R.,
China. (Project No. WQ20180011).

\par\null

\emph{The summary of bacterial and archaeal communities for the first
and second stages (class level) are shown in Support Information Table
S1.}

\textbf{References}

\begin{enumerate}
\tightlist
\item
  Algapani, D.E., Qiao, W., Su, M., Di, P.F., Wandera, S.M., Adani, F.
  \& Dong, R. (2016). Biohydrolysis and bio-hydrogen production from
  food waste by thermophilic and hyperthermophilic anaerobic process.
  Bioresour. Technol. 216,768-777.
  http://dx.doi.org/10.1016/j.biortech.2016.06.016.
\item
  APHA (2005). Standard Methods for the Examination of Water and
  Wastewater, American Public Health Association (APHA), Washington, DC,
  USA.
\item
  Bayrakdar, A., Sürmeli, R.Ö. \& Çalli, B. (2017). Dry anaerobic
  digestion of chicken manure coupled with membrane separation of
  ammonia. Bioresour. Technol. 244,816-823.
  https://doi.org/10.1016/j.biortech.2017.08.047.
\item
  Carballa, M., Regueiro, L., Lema, J.M. (2015). Microbial management of
  anaerobic digestion: exploiting the microbiome-functionality nexus.
  Curr. Opin. Biotech.
  33,103-111.https://dio.org/10.1016/j.copbio.2015.01.008
\item
  Chen, T., Jin, Y., Liu, F., Meng, X., Li, H. \& Nie, Y. (2012). Effect
  of hydrothermal treatment on the levels of selected indigenous
  microbes in food waste. J. Environ. Manage. 106,17-21.
  https://doi.org/10.1016/j.jenvman.2012.03.045.
\item
  Cho, K., Shin, S.G., Kim, W., Lee, J., Lee, C. \& Hwang, S. (2017).
  Microbial community shifts in a farm-scale anaerobic digestion
  treating swine waste: Correlations between bacteria communities
  associated with hydrogenotrophic methanogens and environmental
  conditions. Sci. Total Environ. 601-602,
  167-176.http://dx.doi.org/10.1016/j.scitotenv.2017.05.188
\item
  Conners, S.B., Mongodin, E.F., Johnson, M.R., Montero, C.I., Nelson,
  K.E. \& Kelly, R.M. (2006). Microbial biochemistry, physiology, and
  biotechnology of hyperthermophilic \emph{Thermotoga} species. FEMS
  Microbiol, Rev. 30,872-905.
  https://doi.org/10.1111/j.1574-6976.2006.00039.x.
\item
  De Vrieze, J., Christiaens, M.E.R., Walraedt, D., Devooght, A., Ijaz,
  U.Z. \& Boon, N. (2017). Microbial community redundancy in anaerobic
  digestion drives process recovery after salinity exposure. Water Res.
  111, 109-117. https://doi.org/10.1016/j.watres.2016.12.042
\item
  Dongyan, Y., Yunzhi, P., Hairong, Y., Shulin, C., Jingwei, M. \&
  Liang, Y. (2014). Enhancing biogas production from an anaerobically
  digested wheat straw through ammonia pretreatment. Chin. J. Chem. Eng.
  22,576-582. https://doi.org/10.1016/S1004-9541(14)60075-6
\item
  Hania, W.B., Godbane, R., Postec, A., Hamdi, M., Ollivier, B. \&
  Fardeau, M.L. (2012). \emph{Defluviitoga tunisiensis} gen. Nov., sp.
  Nov., a thermophilic bacterium isolated from a mesothermic and
  anaerobic whey digester. Int. J. Syst. Evol. Microbiol. 62,1377-1382.
  https://doi.org/10.1099/ijs.0.033720-0.
\item
  Hansen, K.H., Ahring, B.K. \& Raskin, L. (1999). Quantification of
  syntrophic fatty acid beta-oxidizing bacteria in a mesophilic biogas
  reactor by oligonucleotide probe hybridization. Appl, Environ.
  Microbiol. 65(11), 4767-4774.
\item
  Hobbs, S.R., Landis, A.E., Rittmann, B.E., Young, M.N. \&
  Parameswaran, P. (2019). Enhancing anaerobic digestion of food waste
  through biochemical methane potential assays at different substrate:
  inoculum ratios. Waste Manage. 71, 612-617.
  http://dx.doi.org/10.1016/j.wasman.2017.06.029.
\item
  Huber, H., Thomm, M., König, H., Thies, G. \& Stetter, K.O.
  (1982).\emph{Methanococcus thermolithotrophicus} , a novel
  thermophilic lithotrophic methanogen. Arch. Microbiol.132,47-50.
  https://doi.org/10.1007/BF00690816.
\item
  Jang, H.M., Ha, J.H., Kim, M.S., Kim, J.O., Kim, Y.M. \& Park, J.M.
  (2016). Effect of increased load of high-strength food wastewater in
  thermophilic and mesophilic anaerobic co-digestion of waste activated
  sludge on bacterial community structure. Water Res. 99, 140-148.
  https://doi.org/10.1016/j.watres.2016.04.051.
\item
  Jiang, M., Qiao, W., Ren, Z., Mahdy, A., Wandera, S.M., Li, Y. \&
  Dong, R. (2019). Influence of operation conditions on methane
  production from swine wastewater treated by a self-agitation anaerobic
  reacto. Int. Biodeter. Biodegr. 143,104710.
  https://doi.org/10.1016/j.ibiod.2019.05.027
\item
  Kim, J.K., Oh, B.R., Chun, Y.N. \& Kim, S.W. (2006). Effects of
  temperature and hydraulic retention time on anaerobic digestion of
  food waste. J. Biosci. Bioeng. 102, 328-332.
  https://doi.org/10.1263/jbb.102.328.
\item
  Li, D., Ran, Y., Chen, L., Cao, Q., Li, Z. \& Liu, X. (2018b).
  Instability diagnosis and syntrophic acetate oxidation during
  thermophilic digestion of vegetable waste. Water Res. 139, 263-271.
  https://doi.org/10.1016/j.watres.2018.04.019.
\item
  Li, W., Khalid, H., Zhu, Z., Zhang, R., Liu, G., Chen, C. \& Thorin,
  E. (2018a). Methane production through anaerobic digestion:
  participation and digestion characteristics of cellulose,
  hemicellulose and lignin. Appl. Energy 226, 1219-1228.
  https://doi.org/10.1016/j.apenergy.2018.05.055
\item
  Li, L., He, Q., Ma, Y., Wang, X. \& Peng, X. (2015). Dynamics of
  microbial community in a mesophilic anaerobic digester treating food
  waste: relationship between community structure and process stability.
  Bioresour. Technol. 189, 113-120.
\item
  Li, L., He, Q., Ma, Y., Wang, X. and Peng, X. (2016). A mesophilic
  anaerobic digester for treating food waste: process stability and
  microbial community analysis using pyrosequencing. Microb. Cell Fact.
  15,65. https://doi.org/10.1186/s12934-016-0466-y
\item
  Li, L., Qin, Y., Kong, Z., Wu, J., Kubota, K. \& Li, Y-Y (2019).
  Characterization of microbial community and main functional groups of
  prokaryotes in thermophilic anaerobic cod-digestion of food waste and
  paper waste. Sci. Total Environ. 652, 709-717.
  https://doi.org/10.1016/j.scitotenv.2018.10.292
\item
  Liu, J.F., Mbadinga, S.M., Sun, X.B., Yang, G.C., Yang, S.Z., Gu, J.D.
  \& Mu, B,Z. (2016). Microbial communities responsible for fixation of
  co2 revealed by using mcra, cbbm, cbbl, fthfs, fefe-hydrogenase genes
  as molecular biomarkers in petroleum reservoirs of different
  temperatures. Int. Biodeter. Biodegr. 114,164-175.
  https://doi.org/10.1016/j.ibiod.2016.06.019.
\item
  Liu, P., Ji, J., Wu, Q., Ren, J., Wu, G., Yu, Z., Xiong, J., Tian, F.,
  Zafar, Y. \& Li, X. (2018). \emph{Klebsiella pneumoniae} sp lzu10
  degrades oil in food waste and enhances methane production from
  co-digestion of food waste and straw. Int. Biodeter. Biodegr.
  126,28-36. https://doi.org/10.1016/j.ibiod.2017.09.019.
\item
  Mahdy, A., Wandera, S.M., Bi, S., Song, Y., Qiao, W. \& Dong, R.
  (2019a). Response of the microbial community to the methanogenic
  performance of biologically hydrolyzed sewage sludge with variable
  hydraulic retention times. Bioresour. Technol. 288, 121581.
  https://doi.org/10.1016/j.biortech.2019.121581
\item
  Mahdy, A., Mendez, L., Ballesteros, M. \& Gonzalez-Fernandez, C.
  (2015). Protease pretreated \emph{Chlorella vulgaris} biomass
  bioconversion to methane via semi-continuous anaerobic digestion. Fuel
  158, 35-41.
\item
  Mahdy, A., Wandera, S.M., Qiao, W. \& Dong, R. (2019b). Biostimulation
  of sewage sludge solubilization and methanization by
  hyper-thermophilic pre-hydrolysis stage and the shifts of microbial
  structure profiles. Sci. Total Environ.
  https://doi.org/10.1016/j.scitotenv.2019.134373.
\item
  Marchaim, U. \& Krause, C. (1993). Propionic to acetic acid ratios in
  overloaded anaerobic digestion. Bioresour. Technol.43, 195-203.
  https://doi.org/10.1016/0960-8524(93)90031-6.
\item
  Maus, I., Koeck, D.E., Cibis, K.G., Hahnke, S., Kim, Y.S., Langer, T.,
  Kreubel, J., Erhard, M., Bremges, A., Off, S., Stolze, Y., Jaenicke,
  S., Goesmann, A., Sczyrba, A., Scherer, P., König, H., Schwarz, W.H.,
  Zverlov, V.V., Liebl, W., Pühler, A., Schlüter, A. \& Klocke, M.
  (2016). Unraveling the microbiome of a thermophilic biogas plant by
  metagenome and meta transcriptome analysis complemented by
  characterization of bacterial and archaeal isolates. Biotechnol.
  Biofuels 9, 171-198. https://doi.org/10.1186/s13068-016-0581-3.
\item
  Nag, R., Auer, A., Markey, B.K., Whyte, P., Nolan, S., O'flaherty, V.,
  Russell, L., Declan, B., Fenton, O., Richards, K. \& Cummins, E.
  (2019). Anaerobic digestion of agricultural manure and biomass-
  Critical indicators of risk and knowledge gaps. Sci. Total Environ.
  690, 460-479.
\item
  Nayak, A. \& Bhushan, B. (2019). An overview of the recent trends on
  the waste valorization technologies for food wastes. J. Environ.
  Manage. 233, 352-370. https://doi.org/10.1016/j.jenvman.2018.12.041
\item
  Peng. X., Nges, I.A. \& Liu, J. (2016). Improving methane production
  form wheat straw by digestate liquor recirculation in continuous
  stirred tank processes. Renew. Energy 5,12-8.
  https://doi.org/10.1016/j.renene.2015.06.023
\item
  Ratanatamskul. C. \& Manpetch, P. (2016). Comparative assessment of
  prototype digester configuration for biogas recovery from anaerobic
  co-digestion of food waste and rain tree leaf as feedstock. Int.
  Biodeter. Biodegr. 13,367-374.
  http://dx.doi.org/10.1016/j.ibiod.2016.05.008.
\item
  Seely, R.J. \& Fahrney, D.E. (1983). A novel diphospho-p,p'-diester
  from \emph{Methanobacterium thermoautotrophicum} . J. Biol. Chem. 258,
  10835-10838. https://doi.org/10.1159/000177690
\item
  Sekiguchi, Y., Imachi, H., Susilorukmi, A., Muramatsu, M., Ohashi, A.,
  Harada, H., Hanada, S. \& Kamagata, Y. (2006). \emph{Tepidanaerobacter
  syntrophicus} gen. nov. sp. nov. an anaerobic, moderately
  thermophilic, syntrophic alcohol- and lactate-degrading bacterium
  isolated from thermophilic digested sludges. Int. J. Syst. Evol.
  Microbiol. 56,1621-1629. https://doi.org/10.1002/jps.20638.
\item
  Shi, X., Guo, X., Zuo, J., Wang, Y. \& Zhang, M. (2018). A comparative
  study of thermophilic and mesophilic anaerobic co-digestion of food
  waste and wheat straw: process stability and microbial community
  structure shifts. Waste Manage. 75,261-269.
  http://doi.org/10.1016/j.wasman.2018.02.004.
\item
  Sluiter, A., Hames, B., Ruiz, R., Scarlata, C., Sluiter, J. \&
  Templeton, D. (2005). Determination of Ash in biomass. Standard
  Biomass Analytical Procedures. National Laboratory of the U.S.
  Determent of Energy, Office of Energy Efficiency \& Renewable Energy,
  United States.
\item
  Sun. L., Pope, P.B., Eijsink, V.G.H. \& Schnurer, A. (2015).
  Characterization of microbial community structure during continuous
  anaerobic digestion of straw and cow manure. Microbial Biotechnol. 8,
  815-827. https://doi.org/10.1111/1751-7915.12298.
\item
  Tachaapaikoon, C., Kosugi, A., Pason, P., Waeonukul, R.,
  Ratanakhanokchai, K., Kyu, K.L., Arai, T., Murata, Y. \& Mori, Y.
  (2012). Isolation and characterization of a new
  cellulosome-producing\emph{Clostridium thermocellum} strain.
  Biodegradation 23(1), 57-68.
  https://doi.org/10.1007/s10532-011-9486-9.
\item
  Tian, H., Fotidis, I.A., Mancini, E., Treu, L., Mahdy, A.,
  Ballesteros, M., González-Fernández, C. \& Angelidaki, I. (2018).
  Acclimation to extremely high ammonia levels in continuous
  biomethanation process and the associated microbial community
  dynamics. Bioresour. Technol. 247, 616-623.
  http://dx.doi.org/10.1016/j.biortech.2017.09.148
\item
  Wagner, A.O., Reitschuler, C. \& Illmer, P. (2014). Effect of
  different acetate:propionate ratios on the methanogenic community
  during thermophilic anaerobic digestion in batch experiments. Biochem.
  Eng. J. 90, 154-161. https://doi.org/10.1016/j.bej.2014.05.014.
\item
  Westerholm, M., Moestedt, J. \& Schnürer, A. (2016). Biogas production
  through syntrophic acetate oxidation and deliberate operating
  strategies for improved digester performance. Appl. Energy 179,
  124-135. https://doi.org/10.1016/j.apenergy.2016.06.061.
\item
  Westerholm, M., Roos, S. \& Schnürer, A.
  (2011).\emph{Tepidanaerobacter acetatoxydans} sp. nov. an anaerobic,
  syntrophic acetate-oxidizing bacterium isolated from two
  ammonium-enriched mesophilic methanogenic processes. Syst. Appl.
  Microbiol. 34, 260-266. https://doi.org/10.1016/j.syapm.2010.11.018.
\item
  Yin, D.M., Westerholm, M., Qiao, W., Bi, S.J., Wandera, S.M., Fan, R.,
  Jiang, M. \& Dong, R. (2018). An explanation of the methanogenic
  pathway for methane production in anaerobic digestion of nitrogen-rich
  materials under mesophilic and thermophilic conditions. Bioresour.
  Technol. 264, 42-50. https://doi.org/10.1016/j.biortech.2018.05.062.
\item
  Zamanzadeh, M., Hagen, L.H., Svensson, K., Linjordet, R. \& Horn, S.J.
  (2017). Biogas production from food waste via co-digestion and
  digestion- effects on performance and microbial ecology. Sci. Rep. 7,
  17664-17676. https://doi.org/10.1038/s41598-017-15784-w.
\item
  Zhang, Q., Wang M., Ma, X., Gao, Q., Wang, T., Shi, X., Zhou, J., Zuo,
  J. \& Yang, Y. (2019). High variations of methanogenic microorganisms
  drive full-scale anaerobic digestion process. Environ. Int. 126,
  543-551. https://doi.org/10.1016/j.envint.2019.03.005
\end{enumerate}

\emph{}

Table 1. Characteristics of substrates and inoculum\selectlanguage{english}
\begin{longtable}[]{@{}lllllllllll@{}}
\toprule
Parameters & Units & Food Waste & Food Waste & Food Waste & Straw &
Straw & Straw & Inoculum & Inoculum & Inoculum\tabularnewline
\midrule
\endhead
& & Average & SD (\selectlanguage{ngerman}±) & n & Average & SD (\selectlanguage{ngerman}±) & n & Average & SD (\selectlanguage{ngerman}±) &
n\tabularnewline
TS & \% & 15.4 & 1.4 & 14 & 95.5 & 0.12 & 2 & 8.4 & 0.1 &
2\tabularnewline
VS & \% & 13.9 & 1.2 & 14 & 84.7 & 0.1 & 2 & 5.3 & 0.1 &
2\tabularnewline
VS/TS & \% & 90.3 & 0.7 & 14 & 88.7 & / & / & 63 & 0.2 &
2\tabularnewline
TCOD & g kg-1 & 185 & 42.5 & 14 & 1.2* & 0.1 & 2 & 21 & 0.4 &
3\tabularnewline
SCOD & gL-1 & 100 & 15.2 & 14 & / & / & 2 & 17.9 & 0.5 &
3\tabularnewline
Carbohydrates & TS\% & 24 & 9.1 & 14 & / & / & / & / & / &
/\tabularnewline
Protein & TS\% & 12 & 7.0 & 14 & / & / & / & / & / & /\tabularnewline
Fat & TS\% & 21.5 & 5.8 & 14 & / & / & / & / & / & /\tabularnewline
C & TS\% & 51.1 & 1.3 & 2 & 58.2 & 0.1 & 2 & / & / & /\tabularnewline
N & TS\% & 3.6 & 0.4 & 2 & 1.1 & 0 & 2 & / & / & /\tabularnewline
O & TS\% & 37.9 & 0.7 & 2 & 34.4 & 0.1 & 2 & / & / & /\tabularnewline
H & TS\% & 5.1 & 0.1 & 2 & 4.8 & 0.1 & 2 & / & / & /\tabularnewline
S & TS\% & 2.4 & 0.9 & 2 & 0.9 & 0.1 & 2 & / & / & /\tabularnewline
C/N & / & 14.2 & 1.1 & 2 & 52.9 & 0.3 & 2 & / & / & /\tabularnewline
\bottomrule
\end{longtable}

Notes: TS: total solids; VS: volatile solids; VFAs: volatile fatty
acids; TCOD: total chemical oxygen demand; SCOD: soluble chemical oxygen
demand; SD: standard deviation; n means testing frequency; '/': data not
available. *: g COD g TS-1.

Table 2 Summary of long term CSTR process performances under stable and
disturbed states\selectlanguage{english}
\begin{longtable}[]{@{}lllllllllll@{}}
\toprule
Duration & Days* & 1-47 & 48-110 & 111-160 & 161-202 & 203-218 & 219-230
& 231-252 & 253-264 & 265-270\tabularnewline
\midrule
\endhead
Feeding VS & g L-1 & 79.1\selectlanguage{ngerman}±4.5 & 80.8\selectlanguage{ngerman}±5.4 & 79.4\selectlanguage{ngerman}±4.8 & 81.2\selectlanguage{ngerman}±4.4 &
85.1\selectlanguage{ngerman}±5.4 & Stop feeding & 40.1\selectlanguage{ngerman}±0.2 & 20.3\selectlanguage{ngerman}±0.1 & 11.6\selectlanguage{ngerman}±0.2\tabularnewline
OLR & g VS L-1 d-1 & 2.6\selectlanguage{ngerman}±0.2 & 5.4\selectlanguage{ngerman}±0.4 & 7.9\selectlanguage{ngerman}±0.5 & 10.2\selectlanguage{ngerman}±0.6 & 17.1\selectlanguage{ngerman}±1.1 &
/ & 8.1\selectlanguage{ngerman}±0.1 & 7.4\selectlanguage{ngerman}±0.1 & 7.7\selectlanguage{ngerman}±0.1\tabularnewline
HRT & Days & 30 & 15 & 10 & 8 & 5 & / & 5 & 3 & 1.5\tabularnewline
pH & / & 7.6\selectlanguage{ngerman}±0.1 & 7.5\selectlanguage{ngerman}±0.1 & 7.4\selectlanguage{ngerman}±0.3 & 7.4\selectlanguage{ngerman}±0.2 & 7.2\selectlanguage{ngerman}±0.3 & / & 7.2\selectlanguage{ngerman}±0.1 &
7.3\selectlanguage{ngerman}±0.3 & 7.2\selectlanguage{ngerman}±0.1\tabularnewline
Biogas yield & L L-1 d-1 & 0.9\selectlanguage{ngerman}±0.2 & 3.0\selectlanguage{ngerman}±0.7 & 4.6\selectlanguage{ngerman}±0.5 & 5.7\selectlanguage{ngerman}±0.7 &
9.1-6.1 & / & 4.4\selectlanguage{ngerman}±0.3 & 2.6\selectlanguage{ngerman}±0.8 & 0.9\selectlanguage{ngerman}±0.1\tabularnewline
CH4 & \% & 63\selectlanguage{ngerman}±3 & 61\selectlanguage{ngerman}±4 & 61\selectlanguage{ngerman}±3 & 61\selectlanguage{ngerman}±3 & 61\selectlanguage{ngerman}±9 & / & 65\selectlanguage{ngerman}±4 & 67\selectlanguage{ngerman}±6 &
56\selectlanguage{ngerman}±6\tabularnewline
CO2 & \% & 29\selectlanguage{ngerman}±2 & 32\selectlanguage{ngerman}±4 & 33\selectlanguage{ngerman}±3 & 34\selectlanguage{ngerman}±3 & 31\selectlanguage{ngerman}±7 & / & 35\selectlanguage{ngerman}±4 & 33\selectlanguage{ngerman}±3 &
44\selectlanguage{ngerman}±6\tabularnewline
Specific methane yield & mL g VSin-1 & 284\selectlanguage{ngerman}±74 & 348\selectlanguage{ngerman}±59 & 393\selectlanguage{ngerman}±25 & 385\selectlanguage{ngerman}±43
& 306-205 & / & 354\selectlanguage{ngerman}±27 & 251\selectlanguage{ngerman}±63 & 78\selectlanguage{ngerman}±12\tabularnewline
NH4+-N & mg L-1 & 835\selectlanguage{ngerman}±103 & 732\selectlanguage{ngerman}±12 & 644\selectlanguage{ngerman}±92 & 667\selectlanguage{ngerman}±92 & 550\selectlanguage{ngerman}±13 & / &
0.8\selectlanguage{ngerman}±0.2 & 659\selectlanguage{ngerman}±66 & 710\selectlanguage{ngerman}±112\tabularnewline
Bicarbonate alkalinity & g CaCO3 L-1 & 3.5\selectlanguage{ngerman}±0.4 & 4.4\selectlanguage{ngerman}±0.3 & 4.1\selectlanguage{ngerman}±0.4 &
4.1\selectlanguage{ngerman}±0.3 & 3.7-2.1 & / & 2.8\selectlanguage{ngerman}±0.4 & 3.3\selectlanguage{ngerman}±0.5 & 2.5\selectlanguage{ngerman}±0.6\tabularnewline
Acetate & mg L-1 & 83\selectlanguage{ngerman}±42 & 212\selectlanguage{ngerman}±41 & 204\selectlanguage{ngerman}±31 & 338\selectlanguage{ngerman}±185 & 242-1411 & / &
333\selectlanguage{ngerman}±197 & 951\selectlanguage{ngerman}±577 & 2533\selectlanguage{ngerman}±496\tabularnewline
Propionate & mg L-1 & 22\selectlanguage{ngerman}±14 & 21\selectlanguage{ngerman}±12 & 8\selectlanguage{ngerman}±4 & 46\selectlanguage{ngerman}±28 & 17-2213 & / &
558\selectlanguage{ngerman}±296 & 310\selectlanguage{ngerman}±111 & 224\selectlanguage{ngerman}±75\tabularnewline
Butyrate & mg L-1 & 20\selectlanguage{ngerman}±10 & 7\selectlanguage{ngerman}±3 & 14\selectlanguage{ngerman}±5 & 10\selectlanguage{ngerman}±3 & 13-507 & / & 266\selectlanguage{ngerman}±248 &
47\selectlanguage{ngerman}±26 & 135\selectlanguage{ngerman}±48\tabularnewline
Total VFAs & mg L-1 & 124\selectlanguage{ngerman}±100 & 226\selectlanguage{ngerman}±52 & 214\selectlanguage{ngerman}±34 & 398\selectlanguage{ngerman}±28 & 362-4730 & /
& 916\selectlanguage{ngerman}±463 & 1307\selectlanguage{ngerman}±575 & 2903\selectlanguage{ngerman}±617\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{ngerman}

Notes: HRT: hydraulic retention time; TS: total solid; OLR: organic
loading rate; Total VFAs: volatile organic acids, sum of acetate,
propionate, iso-butyrate, butyrate, iso-valerate, valeric and caproate;
'/': data not available. All data is shown in average±SD (standard
deviation); `\selectlanguage{english}-' means the performance range, not stable.

*: First stage: 1-218 days; Recovery stage: 219-230 days; Second stage:
231-252 days

Table 3 Percentage of potential SAOB and HM partners at genus level\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
& OLR (g VS L-1 d-1) & 10.2 & 17.1 & 8.1 & 7.4 & 7.7\tabularnewline
\midrule
\endhead
& HRT (days) & 8 & 5 & 5 & 3 & 1.5\tabularnewline
Possible SAOB & \emph{Tepidanaerobacter} & 0.02\% & 0.4\% & 1\% & 3\% &
4\%\tabularnewline
& \emph{Clostridium} & 2\% & 11\% & 5\% & 4\% & 7\%\tabularnewline
& \emph{Syntrophaceticus} & / & 0.1\% & / & / & /\tabularnewline
& Total & 3\% & 12\% & 6\% & 7\% & 11\%\tabularnewline
HM Partners & \emph{Methanothermobacter} & 1\% & 1\% & 24\% & 75\% &
84\%\tabularnewline
& \emph{Methanoculleus} & 87\% & 53\% & 56\% & 0.1\% &
1\%\tabularnewline
& \emph{Methanomassiliicoccus} & 3\% & 7\% & 4\% & 0.2\% &
1\%\tabularnewline
& Total & 91\% & 61\% & 84\% & 75\% & 86\%\tabularnewline
\bottomrule
\end{longtable}

Notes: `/' was not detected. SAOB: syntrophic acetate oxidation
bacterial; HM: hydrogenotrophic methanogenic.

Table 4 Microbial richness and diversity indices of bacterial (genus
level) and archaeal (species level) under HRT 5-1.5d\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
HRT (d) & Bacterial & Bacterial & Bacterial & Bacterial & Archaeal &
Archaeal & Archaeal & Archaeal\tabularnewline
\midrule
\endhead
& Chao1 & Shannon & Simpson & Coverage & Chao1 & Shannon & Simpson &
Coverage\tabularnewline
5 & 2978 & 6.76 & 0.97 & 0.93 & 28 & 1.17 & 0.97 & 0.99\tabularnewline
3 & 2213 & 6.66 & 0.96 & 0.93 & 21.5 & 0.76 & 0.88 & 0.99\tabularnewline
1.5 & 1989 & 6.32 & 0.95 & 0.90 & 20 & 0.65 & 0.72 & 0.99\tabularnewline
\bottomrule
\end{longtable}

Notes: all indices were calculated based on OTU level\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/Picture1}

\end{center}
\end{figure}

\textbf{Fig. 1} CSTR performance in long-term operation under stable and
disturbed states targeting OLR: (a) volumetric methane production, (b)
methane yield and pH, (c) total VFAs, acetate and propionate and (d) VS
in, out and removal\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Fig. 2} Relative abundance of bacteria and archaea at genus
taxonomic level under well-performed (a and c) and disturbed (b and d)
states.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Fig 3.} CSTR performance under stable and disturbed states
targeting HRT: (a) volumetric methane production, (b) methane yield and
pH, (c) total VFAs, acetate and propionate and (d) VS in, out and
removal\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Fig. 4} Wash out of microorganisms with reducing HRTs.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Fig. 5} Relative abundance of bacteria (a, b and c) and archaea
(a', b' and c') at genus taxonomic level under stable and disturbed
states targeting HRT.

\textbf{Hosted file}

\verb`Graphical abstract.docx`  available at \url{https://authorea.com/users/287467/articles/412222-anaerobic-digestion-concert-of-agro-food-wastes-and-the-correlated-microbial-population-dynamics-under-suboptimal-well-performed-and-disturbed-states}

\selectlanguage{english}
\FloatBarrier
\end{document}

