Effect of semi-continuous replacements of compost materials after inoculation on the performance of heat preservation of low temperature composting

Effect of semi-continuous replacements of compost materials after inoculation on the performance of heat preservation of low temperature composting

Bioresource Technology 279 (2019) 50–56 Contents lists available at ScienceDirect Bioresource Technology journal homepage: www.elsevier.com/locate/b...

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Bioresource Technology 279 (2019) 50–56

Contents lists available at ScienceDirect

Bioresource Technology journal homepage: www.elsevier.com/locate/biortech

Effect of semi-continuous replacements of compost materials after inoculation on the performance of heat preservation of low temperature composting

T

Qinghong Suna,b, Jian Chenc, Yuquan Weid, Yue Zhaoa, Zimin Weia, , Haiyang Zhange, Xintong Gaoa, Junqiu Wua, Xinyu Xiea ⁎

a

College of Life Science, Northeast Agricultural University, Harbin 150030, China School of Resources and Environment Science, Wuhan University, Wuhan 430079, China Beijing Tongzhou Agriculture Products Quality Inspection & Testing Center, Beijing 101149, China d School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China e College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China b c

GRAPHICAL ABSTRACT

ARTICLE INFO

ABSTRACT

Keywords: Semi-continuous replacements of compost materials after inoculation Low temperature composting Bio-heat generation Heat preservation Structural equation model

Development of cold-adapted microbial agent is an efficient approach for composting in low temperature. The study was conducted to evaluate the effect of semi-continuous replacements of compost materials after inoculation (SRMI) on the heat preservation of low temperature composting derived from chicken manure. Results revealed that SRMI could significantly improve the heat preservation of the pile, although the time of start-up in two inoculation groups was approximately the same. Due to the increase in the number of replacements of materials led to the changes in microbial community structures and enzyme activity. Non-metric multidimensional and colorimetric methods indicated that microbial community structures and enzyme activity was completely different in SRMI. Structural equation model was constructed by key factors involved in diversity of the microbial community, enzyme activity, temperature and bio-heat generation. In summary, SRMI decidedly increase the heat preservation time of the pile and start-up efficiency of the low temperature composting.



Corresponding author. E-mail addresses: [email protected], [email protected] (Z. Wei).

https://doi.org/10.1016/j.biortech.2019.01.090 Received 6 December 2018; Received in revised form 18 January 2019; Accepted 22 January 2019 Available online 23 January 2019 0960-8524/ © 2019 Elsevier Ltd. All rights reserved.

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1. Introduction

Table 1 The basic physical-chemical characteristics for composting raw materials.

Aerobic composting is an environmentally friendly and economically viable alternative method for treating solid organic wastes, especially in the treatment of livestock and poultry manure (He et al., 2015; Jiang et al., 2015; Xi et al., 2016). As for an effective composting process, environmental factors, such as temperature and C/N, organic matter and so on, play crucial roles. The temperature is one of the important parameters to characterize the aerobic composting process in numerous studies (Bongochgetsakul and Ishida, 2008; He et al., 2018; Zambra et al., 2011a; 2011b), particularly in the low temperature environment, which is more significantly related to a successful composting process (Zhao et al., 2012). In order to ensure the normal progress of composting in the low temperature, a lot of methods for pile heating have been used to maintain composting temperature, such as wrapped by insulation cotton (Yu et al., 2015), gas heating (Xu et al., 2010), cover cropping (Dabney et al., 2007), etc. These heating methods mainly aimed at enhancing the microbial activity and preventing heat loss during low temperature composting. However, in the view of practical composting production, these methods are not energy-saving and economical enough for practical composting production. Previous studies showed that inoculation with cold-adapted microbial agents (CAMA) can overcome such environmental problems (Sun et al., 2017; Zeng et al., 2018; Zhang et al., 2018). Many literatures reported that the internal environment of the piles, such as enzyme activities and substrate availability, could be altered after inoculation (Garcia et al., 2000; Zeng et al., 2010). Nevertheless, a key question of inoculation is difficult to effectively resolve, that is, only a short-term rise in temperature caused by inoculation. When microbes were inoculated at the initial stage of composting, their activities gradually increased with the composting (Kato and Miura, 2008). However, as the composting continues and substrate consumes, microbial activity and the temperature of the pile will gradually decrease. Previous studies have shown that the metabolism of microorganism could be slowed down or even stopped if the temperature of pile and environment were below 20 °C (Tateda et al., 2002). To ensure the number and activity of microorganisms inside the pile during composting, the way of inoculation in different stages of composting was carried out in which the indigenous microbial community can be successfully improved (Zhao et al., 2016). Even so, there are two disadvantages in this way. One is the large demand for inoculum, and the other is not easy to be operated. Besides, in cold climates, to reach high temperatures for composting would be difficult due to a lack of available substance and microorganism to retain heat. Therefore, further investigation of continuous heat preservation of pile based on inoculating cold-adapt strains in composting under low ambient temperature is of high interest for the practical production and application. Previous study showed the key role of inoculation in increasing the bio-energy generation for accelerating the startup composting process under low ambient temperature (Xie et al., 2017). Therefore, considering that CAMA can be used as effective heat-catalyzer, semi-continuous replacements of compost materials after inoculation of CAMA (SRMI) were applied in low temperature composting in this study. Differences between the inoculated pile and SRMI were evaluated. The objectives are to: (1) compare the influence of different composting methods on heat preservation for piles; (2) analyze the effect of SRMI on bacteria density and community structure; and (3) identify the bioheat generation affecting the heat preservation by SRMI method. This research can provide a useful heat preservation strategy for the low temperature composting process.

Raw materials

TOC (g/kg)

TKN (g/kg)

C/N

pH

Chicken manure Sawdust

296.5 ± 0.41 466.2 ± 1.58

26.5 ± 0.04 6.8 ± 0.24

11.15 ± 0.25 68.55 ± 1.48

7.5 ± 0.01 7.6 ± 0.01

Results are the average of three repeats ± standard deviation.

2. Methods 2.1. Raw material preparation and inoculum Fresh chicken manure and sawdust were used to be composed as the composting raw materials. Fresh chicken manure and sawdust were collected from College of Veterinary Medicine, Northeast Agricultural University (Harbin, China) and timber mill, respectively. Both materials were air dried for several weeks before composting. Sawdust as bulking agent was added to adjust the C/N ratio. The basic indicators for composting materials are shown in Table 1. The inoculum was the blend of four strains, including Psychrobacter sp. b110-1 (HQ698582), Arthrobacter sp. TSBY-50 (DQ173010), Psychrobacter pulmonis strain LMG 1012 (HQ698582) and Arthrobacter sp. G8 (HQ111068), which were screened from composting of chicken manure in low temperature and mixed in LB medium with a ratio of 1:1. 2.2. Composting experiment The composting process was carried out in lab-scale composting reactors which have been described previously by Xie et al. (2017). The capacity of reactors was 56.7 L (length: 360 mm and width: 350 mm; height: 450 mm). Different groups were composted separately in a constant temperature incubator at 10 °C for 100 h, and all of the treatments were replicated in triplicate. During composting, the initial C/N ratio was 25, moisture content was maintained in the range of 60–65%, and the ventilation rate was 0.5 L/min kg·organic matter. A certain amount of oxygen concentration inside the composts was ensured by turning over the stack. The weight ratio of chicken manure to sawdust is 5:1 (dry weight). CK was the control with no inoculation and no replacements of materials. The test group 1 (T) was only inoculated, and the test group 2 (T1) was semi-continuous replacements of materials after inoculation. When the pile’s temperature reached 25 °C, the replacements of materials was started. At first, half of the material was removed. Then another portion of fresh materials (mixture of sawdust and chicken manure) was combined with the material that was already being transformed. After the heating time of T1 was prolonged, the replacements of materials was stopped. During the entire process of composting, the replacements of materials was conducted eight times. Temperature changes were observed for the whole process. The samples were collected at different stages of composting including start-up stage (10–25 °C), heating stage (25–45 °C), thermophilic stage (45–55 °C) and cooling stage (55–10 °C). A portion of each sample was air dried and through a 100-mesh sieve after milled for measuring organic matter concentration and basic physical-chemical indexes, and the other was stored in a refrigerator at −20 °C for bacterial analysis. 2.3. Determination of physical and chemical indexes Samples of each compost were collected for organic matter (OM), urease (UA) (EC 3.5.1.5), protease (PRT) (EC 3.4.2.21–24), β-glucosidases (β-Glu) (EC 3.2.1.21), and invertase (IA) (EC 3.2.1.26) analyses. Details of analytical methods have been reported by Sun et al. (2017). The heat energy generated by the microorganisms during composting was measured by the biodegradable OM content and the calorific value of the compost materials (H) using Eq. (1) (Ahn et al., 2007).

Qbio = M H 51

(1)

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where Q bio (kJ/h) is the amount of biological heat, ΔM (kg) is the dry weight of consumed biodegradable OM, H (MJ/kg) is the calorific value of the biodegradable OM. The calorific value (H) of chicken manure was 16.4 MJ/kg (Komilis and Kletsas, 2012) in this study.

temperature of T1 increases to 25 °C, which successfully passes the detonation stage in 12 h. After that, half of the materials were replaced, and the participation of fresh materials resulted in the fluctuant changes of temperature in T1, ranging from 25 °C to 45 °C. It revealed that the added CAMA might have stable activity to maintain the fluctuant enhancement of temperature. On the other hand, when the temperature was increased in 12 h, the native microbes might also be adapted to the internal environment of compost and contribute to the fluctuant increase in composting temperature. However, the heating rate of T1 was decreased after replacements of materials. The phenomenon might be related to the participation of fresh materials, which not only caused a decrease in the amount of CAMA in the pile but also changed the microenvironment of the pile. Meanwhile, indigenous microorganisms needed to re-adapt to the new environment, resulting in a gradual decrease in the heating rate. In the T1, the piles temperature reached its peak at 86 h (the tenth sampling) and then decreased. Compared with T1, temperature in T had lower capability of heat preservation after 30 h in spite of similar start-up time. This is because T is in the cooling period, and T1 is in the heating period due to the replacements of materials. However, the temperature of T is higher than that of T1 in 12–30 h, which might be caused by that T had reached the thermophilic stage, but T1 has re-entered to the heating stage. In CK, the pile temperature was about 18 °C and did not start the fermentation process. Therefore, in this study, SRMI could be used as an optimized catalyst by increasing the temperature and accelerating startup of composting at the low temperature. Considering that the heat energy have significantly positive effects on piles’ temperature (Xie et al., 2017), it is important to study the generation of heat energy for regulating piles’ temperature during composting. The changes of the generated bio-heat energy were displayed in Fig. 1b. In the initial stage, biological heat generation of T1 was the highest among different treatments, and reached the maximum in the thermophilic stage. However, bio-heat generation began to decline as the increase in the number of replacements of materials. This tendency was similar to the change in the temperature. During the whole composting process, the heat yield of T was significantly lower than that in T1. This is because T1 performed the operation of replacements of materials, which disturbed the pile and supplemented the raw materials to make it heat up more quickly. The bio-heat generation of T raised rapidly after the start-up stage, but began to decline gradually after the thermophilic period. In the cooling period (86 h − 100 h), the bio-heat generation both T1 and T was obvious decreased, while the bio-heat generation in CK was higher than the test groups. This may be due to the earlier warming caused by enhanced microbial activity in T1 and T, which accelerated the consumption of substrates. After stopping the replacements of materials, there was insufficient substrates for microbial utilization at the later stage of composting. Therefore, the bio-heat generation of the piles was decreased.

2.4. DNA extraction and PCR-DGGE Total DNA was extracted using an Omega soil DNA kit. The extracted DNA was verified by agarose gel electrophoresis. The purified DNA of 16S rDNA genes were amplified by a touchdown PCR approach. The bacterial universal primer set 357f (5′-CCTACGGGAGGCAG CAG-3′) and 534r (5′-ATTACCGCGGCTGCTGG-3′) were used. A GC clamp at the 5′ end of 357f (5′-CGCCCGGG-GCGCGCCCCGGGCGGGG CGGGGGCACGGGGGG-3′) was used to improve the amplification and ensure to better separation of the DGGE band (Muyzer et al., 1993). The PCR mixture system (25 μL) and cycling conditions for amplifying were carried out according to Xie et al. (2017). PCR products were analyzed by denaturing gradient gel electrophoresis (DGGE). PCR samples were applied to 8% (w/v) polyacrylamide gels and a linear denaturing gradient of 35–60%. Electrophoreses were performed at 60 °C and 80 V for 11 h. SYBR Green I was used to nucleic acid gel stain (Molecular Probes, Carlsbad, CA, USA) for 30 min. The digital images were scanned by a Gel Imaging System to facilitate a better analysis of the bacterial community structure in composting samples. 2.5. Statistical analysis The DGGE image was analyzed by Quantity One 4.5 software (Zhang et al., 2011). Basic physical-chemical indexes were processed by SPSS 19.0 and ORIGIN pro 8.0. Non-metric multidimensional (NMDS) was conducted to analyze the differences in bacteria community during composting in different treatments. The redundancy analysis (RDA) was performed to analyze the relationship between environment factors, bacterial community composition (BCC) and bio-heat generation. Structural Equation Model (SEM) was constructed by the IBM SPSS AMOS 23.0. The variance analysis was used to analyze the differences between treatments, and the LSD was performed for multiple comparisons. 3. Results and discussion 3.1. Evolution of temperature and the Bio-heat generation during composting There is a close relationship between temperature enhancement and energy generation during composting (Kirschbaum, 1995). The temperature of piles increased along with the generation of energy, which was due to the degradation of OM by microorganisms. In Fig. 1a, the

Fig. 1. Changes in (a) pile temperature and (b) bio-heat generation in different treatment groups. 52

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fluctuating, and the highest enzyme activities was observed in the thermophilic phase. The changes of UA activity was consistent with the temperature changes, which had an obviously positive correlation. When the raw material in composting was replaced, the pile temperature declined firstly and then continued to rise. Therefore, the activity of UA had a decrease in a short time firstly and then increased. In T, the UA activity reached the maximum at thermophilic stage and then decreased gradually. However, PRT activity had no significant differences in different composting, and the changes of enzyme activities might be due to the influence of NH3 released during composting (Fig. 2d). Ammonia could act as an inhibitor since it is the product of the hydrolytic reactions catalyzed by urease and proteases (Ros et al., 2006). In T1, the increased concentration of enzyme activities promoted the degradation process of organic matter, with more energy of the available substrate being transferred to pile by microorganism. Therefore, much heat was accumulated at pile, especially in the process of semicontinuous replacements of materials.

Compared with T1, the bio-heat generation of T significantly reduced during the whole composting process. At the same time, the bio-heat generation of CK was almost negligible compared with T1. This result indicated that the entire pile temperature could be effectively preserved by semi-continuous replacements of materials after inoculation without external heating. The above results suggested that SRMI could effectively produce heat for maintaining the temperature of the pile and prolong the time of piles heating stage, meanwhile, SRMI might be also a potentially useful way for heat preservation of composting at low temperature. 3.2. Effect of SRMI on enzyme activity during low temperature composting Microorganisms play a crucial role in composting, and enzyme activity can directly reflect microbial activity (Nannipieri et al., 2002). In this study, β-Glu, IA, UA and PRT were determined. These four enzymes are involved in carbon and nitrogen conversion. β-Glu could hydrolyze cellobiose into glucose, and IA is related to the degradation of disaccharide to glucose. Organic nitrogen is decomposed into small molecular nitrogen components by UA, and PRT participates in the hydrolysis of protein forming polypeptides. The results of the enzymes activities determined for different compost are shown in Fig. 2. The enzyme activities in the composts were quite variable. The activity of βGlu had significant differences in different treatments, and there was a visible of fluctuating in T1 (Fig. 2a). The activity of β-Glu was decreased significantly after the heating period, which may be due to the semi-continuous replacements of materials at the heating stage. Each replacements of materials provided the corresponding simple carboncontaining substrates for microorganisms in the whole pile, leading to the fluctuated activity of β-Glu. The decrease of enzyme activities at thermophilic stage might be due to the weakening of microbial activity or the change of material, and the shortage of substrate after the termination of replacements of materials. The changes of enzyme activities in T was consistent with temperature and finally reached to the same level of T1. Nevertheless, β-Glu activity had no obvious changes in CK. Furthermore, the change of IA was determined (Fig. 2b), whose changes were similar to β-Glu. This was probably because β-Glu and IA could actually hydrolyze the same substrates containing carbon. And the changes of UA activity is shown in Fig. 2c. The activity of UA in T1 was

3.3. Changes in bacterial community during low-temperature composting by SRMI The temperature of the pile is directly affected by changes of microbial community structure (Wei et al., 2019; Zhou et al., 2015). In order to explore the influence of SRMI composting methods on the heat preservation of the pile, it is necessary to investigate the differences of bacterial community among various methods. In this study, the diagram of dynamic changes in bacterial community by DGGE fingerprint during composting has been measured. The NMDS of bacteria community showed that the changes of bacterial community structure in three composting groups are obviously different (Fig. 3). The bacteria community do not change significantly during the composting of CK (Fig. 3a). In T1, bacterial community was in the same category during 40 h before the whole composting process, but was clustered in another class during 49–100 h. This revealed that SRMI could influence the bacterial community structure in the early stage of composting, which might be caused by the low temperature inhibited partial microbial activity. The growth of a large number of mesophilic microbes was initiated when CAMA were added. This might also be the cause of the disturbance of the semi-continuous replacements of materials on the

Fig. 2. Dynamics of enzymatic activity of (a) β-glucosidease, (b) invertase, (c) urease, (d) protease in different composting. Vertical bars represent the standard error (n = 3). 53

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Fig. 3. Nonmetric multidimensional scaling (NMDS) ordination of 16S rDNA gene DGGE fingerprint. All the DGGE data were analyzed by NMDS. Different colors represent different treatments (CK: blue; T: yellow; T1: green). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

NMDS Axis 2 had a significantly positive correlation with β-Glu (p < 0.01). This indicated that β-Glu activity was closely related to bacterial community. Moreover, during composting, β-Glu is essential for the hydrolysis of various forms of carbon-containing substrates. Dynamic changes in the content of organic carbon in these forms could lead to changes for the activity and content of β-Glu. These results showed that the process of transformation of carbon-containing substrates was closely related to bacterial community. Compared with CK and T, the bacterial community in T1 affected the temperature and bio-heat generation indirectly by affecting the enzyme activity, and the activity of some enzymes also directly affected the changes of temperature and bio-heat production (Fig. 4c). Axis 1 and Axis 2 of NMDS affected the activity of IA, UA and PRT, respectively. The activity of the microorganism significantly affected the changes of enzyme activity; however, the activity of the microorganism was too low to production sufficient enzymes. NMDS Axis 1 had a significantly indirectly positive influence on biological heat through influencing OM and temperature. The relationship between β-Glu and bio-heat production was extremely significant, indicating that the concentration of β-Glu activity could directly affect the amount of bioheat generation inside the piles. Temperature was another important factor to affect the heat generation. Suitable temperature is crucial to microbial growth and reproduction. The low temperature of the pile will inhibit the normal growth and metabolism of microorganisms and further impede the composting process (Castaldi et al., 2008). Other factors, such as OM, could indirectly affect bio-heat by changing the temperature of composting environment under the degradation of microorganisms. The OM content which is the basis of microbial activity also affects their growth activity and metabolic rate (Denef et al., 2001). The study showed that OM content and temperature played a crucial role in the succession of microbial communities during composting (Kang et al., 2017). In addition, further analysis was performed with RDA to investigate the relationships between environment factors, BCC and bio-heat generation for T1 (Fig. 5). Each species had its own correlation on different environment factors to participate in the degradation of OM and bioheat generation. Positive correlations were found between the majority of bands and OM, indicating that raw substances were more likely to be utilized by the most of bacterial species. Most positive bands associated with OM in RDA were also positively associated with β-Glu, including bands 1, 3, 4, 5, 6, 12, 13, 14. This result showed that microorganisms had a significant effects on degrading OM, which further indicated that β-Glu had an important effect on the degradation of OM (Juhasz et al., 2005). However, a part of microorganisms had no significant effects on OM degradation, because it was difficult for microorganisms to utilize complex carbonaceous materials such as cellulose, hemicellulose and lignin directly. In addition, IA and UA, PRT and temperature had positive correlations with bio-heat generation simultaneously, which

internal microenvironment of the pile, which could affect the microbial community structure by increasing the availability of organic carbon (Frenk et al., 2018). Compared to T1, the bacterial community distribution of T appeared to be less susceptible, but the bacterial community structure still had obvious differences during composting (Fig. 3b). At the beginning of composting, the two treatments clustered together, but the distribution of bacterial community in the T was dispersed as the composting was carried out. After the high temperature period, the two groups of bacterial community clustered together again, this was mainly caused by semi-continuous replacements of materials brought native microorganism and CAMA, and part of the microorganisms were in active or dead after thermophilic stage. Therefore, the combination of SRMI effectively affected the bacterial community structure during composting, but did not affect the microbial population structure at the end of composting. 3.4. The possible mechanism of SRMI affecting bio-heat generation SEM is a transcendental approach by fitting data into a model representing a causal hypothesis, so that it has the ability to provide a causal relationship between visual variables (Hu et al., 2016). Meanwhile, SEM is a good model used to explore the casual relationships between key environmental factors (e.g., temperature, OM, β-Glu, IA, UA and PRT), bio-heat generation and BCC (NMDS Axis1, 2 and 3). Based on the above results, we inferred that SRMI might indirectly influence bio-heat generation mediated by the key environmental factors and BCC. Moreover, considering that the environmental factors might be the most manageable factors affecting bio-heat generation, we proposed a microbial regulating method to promote the heat of generation based on the factors directly or indirectly related to the bio-heat generation. SEM models were individually performed for each environmental factor (Temperature, OM, β-Glu, IA, UA and PRT). But the data only with appropriate value of χ2, P and df were presented in SEM. Therefore, some environmental factors data and BCC that cannot be fitted by the SEM were not shown in the SEM. These optimized results showed that 73% and 65% of the total variance of the bio-heat generation and temperature patterns could be explained by SEM, respectively. The SEM of different composting groups is shown in Fig. 4. It can be seen that there are significant differences between each group. For CK, NMDS Axis 3 has a significantly indirectly positive influence on biological heat by influencing UA (Fig. 4a). The influence of other factors was not significant for biological heat. The relationship between various factors was not complex. For T, bacterial abundance has no significant effect on the activity of IA and PRT (Fig. 4b). It indicated that the change of bacterial abundance in the compost system could obviously lead to partial change of enzyme activities, but the effects of these enzymes on the total microbial population were not significant. 54

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Fig. 4. Effects of OM, enzyme activity and microbial community on bio-heat generation in (a) CK, (b) T, (c) T1. Red and blue arrows indicate positive and negative relationships, respectively. Solid line and short dash line indicate significant and non-significant relationships (p < 0.05). Numbers adjacent to arrows are standardized path coefficients (relative regression weights), which indicates the effect size of the relationship. Arrow width is proportional to the strength of the relationship. * p < 0.05, ** p < 0.01, *** p < 0.001. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.5. Implication of SRMI operation in heat preserve during low temperature composting How to improve the efficiency of composting in low-temperature areas is an obvious technical challenge, which has attracted increasing attention. Our results showed that SRMI operation could influence bioheat generation through changing OM content, enzyme activity and BCC in low temperature composting. However, in the whole semicontinuous replacements of materials process, only one-time CAMA was inoculated at the initial stage. Due to the physiological limitation of the strain, the microbial activity gradually weakened with the increasing number of replacements of materials. Therefore, the number of semicontinuous replacements of materials might be limited. The results indicated that SRMI operation could not only indirectly influence bioheat generation through changing OM content, enzyme activity and BCC, but also improved the efficiency of heat preservation, which was much higher than that of the only inoculation. As indicated by the standard total effects from SEMs (Fig. 6). For T1, the bio-heat generation was directly influenced by temperature and bacterial community (NMDS Axis 1 and 2) (Fig. 6c). In T and CK, the factors affecting bioheat generation were not as intense and complex as that in T1 (Fig. 6a and b). These results suggested that we could control bio-heat generation through regulating microbial community and substances (i.e., control the replacements of material). Understanding the effects of SRMI operation on composting in the low temperature environment could promote the development and design of management strategies. Therefore, great attention should be paid to the SRMI operation to reduce the effects of low temperature on composting. Overall, this study indicated that SRMI might be used as a potentially effective way for biological heat preservation, which provided theoretical foundation for composting in cold regions.

Fig. 5. Redundancy analyses of the correlation between different environmental factors and remarkable bacteria community from DGGE bands data. Numbers indicate the bacteria bands. The black numbers represent DGGE bands derived from bacteria and green numbers represent CAMA. Red, green and blue arrows represent environmental factors, bio-heat generation and bacterial bands, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

indicated the important roles of environment factors in bio-heat generation. Bands 3, 6, 8 and 9 were cold-adapted microbial agent, only part of them had a positive correlation with biogenic heat, but indirectly affected bio-heat through influencing other environmental factors. We concluded that the microbial population structure in T1 could indirectly influence bio-heat generation through semi-continuous replacements of materials, although microbial population structure could influence enzyme activities. Therefore, enzyme activities also could affect bio-heat generation directly (Fig. 4c).

4. Conclusions This study revealed how SRMI operation influenced bio-heat generation in low temperature. The results from multidirectional approaches illustrated that SRMI operation had direct and indirect effects on bio-heat by changing OM, enzyme activity and microbial community structure during the low temperature composting. Moreover, the CAMA could also survive well after the initial inoculation at low temperature, and thus promoted the increase of the temperature of the pile. The method of SRMI could be used as an optimized method for heat preservation and temperature promotion in low temperature composting 55

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Fig. 6. Standardized total effects (direct plus indirect effects) derived from the structural equation modeling (SEM). These include the effects of organic matter (OM), temperature, enzyme activity, NMDS Axis1, NMDS Axis2, and NMDS Axis3 on bio-heat generation in (a) CK, (b) T, (c) T1.

process.

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