3.1. Batch fermentation
The growth kinetics of E. mundtii QU 25 on glucose, cellobiose, and xylose were studied by batch experiments. The batch fermentations were conducted using medium supplemented with varying concentrations of sugars (10, 20, 50, 100 and 150 g∙L-1) and the growth kinetic parameters were determined during the early exponential growth phase with no product inhibition. The optimized values of the kinetic parameters determined by nonlinear regression are listed in Table 1. The maximum growth rates (mmax) of the studied strain were 1.20 h-1, 0.99 h-1, and 0.62 h-1 for glucose, cellobiose, and xylose, respectively, which were within similar range for other lactic acid producing strains using different substrates [23-28]. The mmax and Ks values for glucose were higher than xylose and cellobiose, implying that glucose is the preferred carbon source of strain QU 25, which was further confirmed by the residual sugars in CSFTR.
Table 1 Kinetic parameters from different batch studies and this work (E. mundtii QU 25)
Substrates
|
Microorganism
|
a
|
b
|
c
|
d
|
Yla e
|
YX f
|
Ref.
|
h-1
|
g·L-1
|
g·L-1
|
g·L-1
|
g·g-1
|
g·g-1
|
Glucose
|
L. amylophilus
|
0.32
|
-
|
-
|
-
|
0.62-0.89
|
-
|
[31]
|
Lactose
|
L. plantarum
|
0.29
|
45.0
|
-
|
-
|
0.96
|
0.25
|
[32]
|
Lactose
|
L. bulgaricus
|
1.14
|
3.36
|
119
|
-
|
0.90
|
0.10
|
[33]
|
Glucose
|
Sporolactobacillus CASD
|
0.13
|
-
|
-
|
-
|
-
|
-
|
[34]
|
Glucose
|
L. lactis NZ133
|
1.10
|
1.32
|
304
|
1.39
|
0.93
|
-
|
[35]
|
Molasses
|
E. faecealis RKY1
|
1.60
|
0.89
|
167.46
|
-
|
0.9-0.99
|
0-0.37
|
[36]
|
Glucose
|
E. mundtii QU 25
|
1.20
|
55.6
|
108.3
|
1.8
|
0.950
|
0.038
|
This study
|
Cellobiose
|
E. mundtii QU 25
|
0.99
|
8.9
|
526.8
|
1.5
|
1.015
|
0.028
|
Xylose
|
E. mundtii QU 25
|
0.62
|
20.1
|
254.2
|
3.3
|
0.925
|
0.056
|
|
|
|
|
|
|
|
|
|
|
|
|
|
a maximum specific growth rate; b half saturation concentration; c inhibition coefficient of substrate; d inhibition coefficient of product; e yield of lactic acid production; and f yield of cell production.
Cell growth and lactic acid formation were critically affected by product inhibition (Kip), while the substrate inhibition (Kis) had relatively small adverse impacts on the studied sugars. A linear relationship was determined between substrate consumption and lactic acid formation with a yield coefficient of 1.0025 for all three sugars (details not shown); this result was similar to the calculated yield of lactic acid based on stoichiometry. The yield of lactic acid was determined from the stoichiometric equations and batch kinetic data with values of 0.950 g·g-1 for glucose, 1.015 g·g-1 for xylose, and 0.925 g·g-1 for cellobiose. The cell yields were in the low range (0.028-0.056 g·g-1) which could be reasonable if considering the high product yields (0.925‒1.015 g·g-1). The model parameters were determined by fitting the simulation results with the experimental data. The results of sugar utilization, lactic acid production, and cell growth from three single sugars in the batch system are shown in Fig.3. After careful adjustment of the parameters the simulation results (lines) all fit well with the experimental results (symbols). The values of root mean square errors (RMSE), regression coefficient (R2) bias factor (BF) and accuracy factor (AF) of the model were presented in Table S1 (supplementary information), suggesting a high consistency between the model simulation and experimental results. The validated growth kinetics, such as the maximum growth rate and the half saturation concentrations, were applied in the other simulations for the continuous fermentation processes.
In addition, dynamic simulations were also carried out on batch fermentation with mixed sugars (Fig.4). The impacts of CCR were clearly shown in G100X50 (Fig.4(a)), and the majority of xylose was not consumed, as glucose was the preferential carbon source for the synthetic hydrolysate. A large amount of xylose remained in the fermentation broth even when glucose was almost completely converted into lactic acid and cell biomass. On the other hand, CCR was not observed when C100X50 was applied (Fig.4(b)) as both sugars were utilized by the fermentation strain simultaneously during fermentation. However, a large amount of cellobiose was not utilized during the testing period when a similar amount of cells was produced in the batch system. The lactic acid concentration was slightly higher in C100X50 than in G100X50.
The simulation results of the dual sugar batch systems showed reasonable fits with the experimental results. The simulation of C100X50 was carried out by the dynamic model described in the methodology section and without the inclusion of any inhibiting factor from the co-fermenting sugars. In order to characterize CCR, the simulation of G100X50 was carried out by introducing an inhibiting coefficient from glucose to xylose in Equation (6). This simulation approach was designed only for this application, as the specific range of glucose concentrations to induce CCR was not clarified. The sensitivity of the inhibiting functions needs to be validated with more comprehensive experiments, which is beyond the scope of this study. As the main focus of this work is to investigate the fermentation of cellobiose and xylose, we tend to study the inhibiting kinetics of CCR in greater detail elsewhere.
3.2. Continuous co-fermentation
This feature of the continuous co-fermentation process for the complete utilization of hexose and pentose were investigated. G100X60 and C100X50 were initially tested at a dilution rate of 0.2 h-1 for process control and comparison (Table 2). For G100X60, when continuous fermentation reached a steady state, a cell concentration of 1.99 g·L-1 was achieved, and a much higher amount of glucose was consumed than xylose (27.5 g·L-1 over 2.64 g·L-1, respectively). The ratio of consumed xylose to consumed glucose (X/G) was 0.096, which exhibited an obvious CCR for xylose utilization. E. mundtii QU 25 growing on G100X60 produced 24.2 g·L-1 lactic acid with a yield of 0.803 g·g-1 and productivity of 4.84 g·L-1·h-1, and a small amount of by-product (0.151 g·L-1 acetic acid) was detected. When glucose was replaced by cellobiose (C100X60) at the same dilution rate of 0.20 h-1, the cell concentration increased to 2.42 g·L-1 at steady state. A cellobiose consumption of 21.8 g·L-1 was achieved with a higher xylose consumption of 11.7 g·L-1, than with G100X50. The ratio of consumed xylose to the consumed cellobiose (X/C) increased to 0.538, suggesting the relief of CCR for xylose consumption. The continuous fermentation process with C100X60 demonstrated a homofermentative lactic acid production of 27.5 g·L-1 with a yield of 0.820 g·g-1 and productivity of 5.49 g·L-1·h-1.
To confirm the beneficial effects of co-fermentation with C100X60 over that with G100X60, the sugar mixture was changed back to G100X60 after C100X50 was tested. Similar parameters were obtained comparing with the first cycle (Table 2). The sugar combination should be the decisive factor in continuous co-fermentation. Feeding with C100X60 achieved simultaneous sugar utilization in continuous co-fermentation with a high productivity.
Table 2 Continuous l-lactic acid production by E. mundtii QU 25 using different sugar mixtures in feeding media (G100X60 or C100X60) at dilution rate of 0.2 h-1
Mixed sugarsa
|
Xb
|
Sgluc
|
Sceld
|
Sxyle
|
X/Hf
ratios
|
Slag
|
Saah
|
Ylai
|
Plaj
|
g·L-1
|
g·L-1
|
g·L-1
|
g·L-1
|
g·L-1
|
g·L-1
|
g·g-1
|
g·L-1·h
|
G100X60
|
1.99 ± 0.05
|
75.4 ± 1.5
|
-
|
57.7 ± 1.3
|
0.096
|
24.2 ± 1.8
|
0.151 ± 0.068
|
0.803
|
4.84
|
C100X60
|
2.42 ± 0.11
|
-
|
79.4 ± 1.7
|
49.7 ± 0.8
|
0.538
|
27.5 ± 0.5
|
0.383 ± 0.022
|
0.820
|
5.49
|
G100X60
|
2.06 ± 0.14
|
72.7 ± 1.0
|
-
|
57.6 ± 0.6
|
0.103
|
25.4 ± 1.3
|
0.134 ± 0.017
|
0.812
|
5.08
|
a compositions of fed medium, i.e., G100X60, 100 g·L-1 glucose and 60 g·L-1xylose; C100X60, 100 g·L-1 cellobiose and 60 g·L-1xylose; b cell concentration; c effluent glucose concentration; d effluent cellobiose concentration; e effluent xylose concentration; f the ratio of consumed xylose to consumed hexoses (glucose or cellobiose); g lactic acid concentration; h acetic acid concentration; i yield of lactic acid production; and j lactic acid productivity.
3.3. Effects of dilution rates on continuous co-fermentation
The dilution rate is a critical control parameter for maximizing productivity in continuous fermentation process. In this study, continuous co-fermentation of C100X60 was performed at dilution rates increasing from 0.05 to 0.25 h-1 (0.05 h-1, intervals), and the results are presented in Table 3 (top). The cell formation increased when the dilution rate was between 0.05 h-1 to 0.20 h-1, and a maximum value of 2.57 g·L-1 was achieved at 0.20 h-1. Further increasing in the dilution rate to 0.25 h-1 decreased cell concentration to 1.74 g·L-1. Total sugar consumption ranged from 28.5-33.7 g·L-1, and lactic acid production was 20.8-27.9 g·L-1 at all dilution rates. The X/C ratio was higher than 0.508, among which it increased to 0.543 at a dilution rate of 0.20 h-1. The highest productivity of 5.37 g·L-1·h-1 with 26.9 g·L-1 lactic acid was obtained at a dilution rate of 0.20 h-1, which was considered optimal for C100X60 utilization by E. mundtii QU 25 in continuous mode. The highest productivity obtained in this study was much higher than 0.635 g·L-1·h-1 in batch experiments [14]. However, high residual cellobiose of 77.2 g·L-1 and xylose of 50.3 g·L-1 were observed, and hence, further investigations were carried out to decrease the residual sugars.
C50X30 was investigated in similar fashion as continuous co-fermentation for increasing dilution rates of 0.05-0.35 h-1, as presented in Table 3 (bottom). The cell concentration increased with the dilution rate from 1.06 g·L-1 (at D=0.05 h-1) to 2.42 g·L-1 (at D=0.25 h-1), but a further increase in the dilution rates to 0.30 h-1 and 0.35 h-1 resulted in lower cell concentrations of 2.29 and 2.16 g·L-1, respectively. The limiting cell retention time (inverse of the dilution rates) of the strain in the CFSTR, or the CRT for zero cell production may be lower than 2 hours. The X/C ratios were almost similar at dilution rates of 0.05-0.20 h-1 ranged 0.412-0.465, respectively. When the dilution rate was higher than 0.20 h-1, the X/C ratio decreased dramatically from 0.461 (at D=0.20 h-1) to 0.303 (at D=0.25 h-1), implying a critical condition among cell concentration, sugar compositions, and increased CCR for xylose utilization. The lactic acid productivity increased with the increasing dilution rate until D=0.30 h-1, and a maximum value of 6.52 g·L-1·h-1 was reached. {Abdel‐Rahman, 2020 #104}
Table 3 Effect of dilution rates on lactic acid production in CSFTR
|
Db
|
Xc
|
Sceld
|
Sxyle
|
X/C
ratiof
|
Slag
|
Saah
|
Ylai
|
Plaj
|
|
h-1
|
g·L-1
|
g·L-1
|
g·L-1
|
g·L-1
|
g·L-1
|
g·g-1
|
g·L-1·h-1
|
C100X60a – CFSTR
|
D1
|
0.05
|
1.03 ± 0.01
|
86.6 ± 4.1
|
44.8 ± 1.4
|
0.980
|
25.5 ± 0.3
|
0.381 ± 0.080
|
0.887
|
1.28
|
D2
|
0.10
|
1.43 ± 0.01
|
82.5 ± 3.8
|
46.7 ± 2.2
|
0.671
|
24.1 ± 0.8
|
0
|
0.780
|
2.41
|
D3
|
0.15
|
2.53 ± 0.03
|
79.0 ± 1.1
|
48.1 ± 0.8
|
0.508
|
27.9 ± 0.7
|
0.260 ± 0.039
|
0.844
|
4.18
|
D4
|
0.20
|
2.57 ± 0.02
|
77.2 ± 3.7
|
50.3 ± 2.5
|
0.543
|
26.9 ± 1.2
|
0.201 ± 0.031
|
0.823
|
5.37
|
D5
|
0.25
|
1.74 ± 0.05
|
83.4 ± 1.9
|
48.2 ± 1.7
|
0.575
|
20.8 ± 0.9
|
0.116 ± 0.023
|
0.730
|
5.21
|
C50X30a – CFSTR
|
D1
|
0.05
|
1.06 ± 0.03
|
29.3 ± 0.4
|
20.9 ± 0.4
|
0.441
|
32.7 ± 0.5
|
0.559 ± 0.018
|
1.09
|
1.64
|
D2
|
0.10
|
1.43 ± 0.05
|
28.1 ± 0.5
|
21.5 ± 0.5
|
0.412
|
27.1 ± 1.3
|
0.380 ± 0.043
|
0.881
|
2.71
|
D3
|
0.15
|
1.52 ± 0.08
|
30.9 ± 1.2
|
20.7 ± 0.7
|
0.465
|
22.1 ± 1.5
|
0.276 ± 0.058
|
0.770
|
3.31
|
D4
|
0.20
|
2.18 ± 0.16
|
31.3 ± 0.9
|
22.7 ± 0.2
|
0.461
|
22.9 ± 0.9
|
0.415 ± 0.011
|
0.871
|
4.57
|
D5
|
0.25
|
2.42 ± 0.02
|
26.7 ± 0.4
|
22.9 ± 0.6
|
0.304
|
23.4 ± 0.5
|
0.651 ± 0.064
|
0.763
|
5.85
|
D6
|
0.30
|
2.29 ± 0.08
|
29.5 ± 0.7
|
23.7 ± 0.1
|
0.303
|
21.7 ± 0.9
|
0.650 ± 0.031
|
0.798
|
6.52
|
D7
|
0.35
|
2.16 ± 0.12
|
30.4 ± 0.5
|
23.9 ± 0.3
|
0.312
|
18.0 ± 0.7
|
0.570 ± 0.032
|
0.695
|
6.29
|
C50X30a – CF/CR
|
D0
|
0.20
|
33.6 ± 1.9
|
0.32 ± 0.2
|
4.71 ± 0.9
|
0.521
|
65.2 ± 3.5
|
1.97 ± 0.21
|
0.854
|
13.03
|
a compositions of fed medium, i.e., C100X60, 100g·L-1 cellobiose and 60 g·L-1 xylose; C50X30, 50g·L-1 cellobiose and 30 g·L-1 xylose; b dilution rates; c cell concentration; d effluent cellobiose concentration; e effluent xylose concentration; f ratios of consumed xylose over consumed cellobiose; g lactic acid concentration; h acetic acid concentration; i yields of lactic acid production; and j lactic acid productivity.
As the co-fermentation experiments were carried out continuously, and the influent conditions were adjusted over well-controlled retention time, the experimental results served well as examples of dynamic simulations of the mathematical model. The dynamic records of the experiments and the corresponding simulation results are presented in Fig.5. Effluent cellobiose, xylose, lactic acid, and cell concentrations are shown in four different rows of the subfigures; and the two columns represent the influent sugars combinations of C100X50 (left) and C50X30 (right). D1 - D7 represent the tested dilution rates (0.05 – 0.35 h-1) and the multiple symbols represent the experimental data when steady state was achieved at the tested dilution rates.
In general, the model described reasonably well the dynamic status of the measured parameters, especially on the predictions of immediate changes of substrate and product concentrations between batch and continuous modes. However, some limitations were also discovered for further improvement of the experiments and model structure. In the experiments, cellobiose, xylose, and lactic acid concentrations were at relatively constant levels after the first dilution rate (D1), but obvious increases of cell concentration were observed from D1 to D4 (onward) for both experiments. Before the cell started to be diluted, regional peaks could be found at specific dilution rates, i.e., at the end of D4 for C100X50 and D5 for C50X30. In fact, sugar consumption and lactic acid production also followed this pattern but the covered ranges were less significant. The changes in cell concentrations over dilution rates were not predicted by the simulation.
Based on Monod kinetics, cell concentrations increase with the related consumption of the substrate. This increase is compensated by cell decay and “wash-out” effects due to high dilution rates in CSFTR. As the cell yield coefficients determined in the batch system were quite low, the simulated cell concentration in the process should be a continuously decrease with the increase in dilution rate. This uncertainty between the model and experimental results may be due to the incomplete cell suspension in the fermentation broth or other uncharacterized factors in the model. The fermentor used in this study is a typical cylindrical column container with a mechanical stirrer installed through the reactor from the top. The CSFTR was controlled by pumping the same amount of liquid in and out of the system. The cell samples were collected through a sampling pipe extending to the bottom of the reactor. When performing long-term continuous experiments, the fermenting cells may not be completely suspended in the fermentation broth, or consistently discharged with the liquid effluent. A slightly higher cell concentration may exist in the bottom part of the jar, which results in inconsistency. Regardless, clarification of this issue requires further investigation and was not significant when the fermentation cells were completely retained in the fermentation process, as detailed in the next section.
3.4. Continuous fermentation with cell recycling (CF/CR)
Controlling cell concentration through cell recycling has been demonstrated to be an efficient technique to obtain high cell density and lactic acid productivity in continuous fermentation with a single carbon source, i.e., glucose [23] and starch [24]. The CF/CR process was performed after receiving concentrated cell concentration from a 4-L reactor, with mMRS medium containing C50X30 at pH 7.0 [14, 21] and a dilution rate of 0.2 h–1 (Fig.6). Approximately 15-fold higher cells (33.6 g·L-1) and 2-fold lower residual xylose concentration (4.71 g·L-1) in the fermentation broth were achieved in comparison to the processes without cell recycling. The X/C ratio was 0.521 in the CF/CR process compared to 0.461 in the conventional mode under the same dilution rate. A high optically pure (≥99.8%) l-lactic acid concentration of 65.2 g·L-1 and productivity of 13.03 g·L-1·h-1 were obtained with slightly lower lactic acid yield over the consumed sugars (0.854 g·g-1), compared to 22.9 g·L-1, 4.57 g·L-1·h-1, and 0.871 g·g-1 without cell recycling, respectively. Only minimal by-products of 0.02-1.97 g·L-1 acetic acid, 0.26-1.93 g·L-1 formic acid, and 0-1.65 g·L-1 ethanol produced from the undesirable pK pathway were measured [7], further confirming our hypothesis in model development. The significant benefits of cell recycle were further clarified when the lactic acid yields were expressed based on the feeding sugars instead of the consumed sugars. In the CF/CR process, almost all the feeding sugars were utilized by the fermentation strain, and the lactic acid yield was 0.801 g·g-1-feeding sugars; while in the process without cell recycling, the yield of lactic acid was 0.285 g·g-1-feeding sugars at the same dilution rate of 0.2 h-1. The fermentation strategy demonstrated outstanding productivity, end-product concentration, and consumption of mixed sugars for more feasible applications.
The experiment results of the CF/CR process for lactic acid production were compared with the data of the most recent publications in Table S2 (Supplementary information). Lactic acid fermentation is a product- and substrate- specific process, and the applied microorganisms and operation conditions play significant roles. The target of the lignocellulosic biomass biorefinery is to increase the product conversion yield from various carbon sources. Continuous fermentation is an attractive concept toward industrialization, and hence has been widely studied recently. The CFSTR operation with free cells suffers from the unbalanced limiting growth rate and metabolic characteristics over short HRTs (high dilution rates), and hence are not feasible in continuous fermentation. Immobilization and cell recycling using hollow fiber microfiltration module have been widely applied to increase the cell density in the bioreactor, and hence further improve the productivity and stability of the process. This concept was confirmed by the experimental results in this study, as the productivity of lactic acid and fermentation titer were both at the high range compared to other studies. Among the references, Tashiro [23] and Ma et al. [25] provided the only two cases with higher productivities than this work. With similar experimental set-up, the former study was conducted at an extremely low influent sugar concentration (glucose 20 g/L); and the later one used an outstanding thermophilic strain (B. coagulans NBRC 12714) in a well-constructed biorefinery process, i.e., modified pretreatment process and solid background of sequencing fermentation data.
In addition to the productivity, other critical information shown in the table of process performance is the inconsistent relationship between the dilution rate and the production yield. It is widely known that the strain characteristics and experimental set-ups both play important roles in the fermentation processes, therefore many quantitative measures, i.e., product concentration, yield, productivity, and dilution rate, have been introduced in the studies to support the cross-comparison. However, it should be also noted that the CRT is also a critical parameter but has not been reported throughout the cited literatures. Theoretically, the cell activity is a function of many parameters including the cell aging in the reactor. With the cell metabolism, the productivity and the final product should increase rapidly at the beginning of fermentation, and then reach a plateau before the final decline over time. However, since there is no discharge control of the excessive cells, the CRTs of the reported CF/CR experiments are equal to the running time, which may not directly reflect to this process condition. A standardized index and operational procedure may be needed to support the comparison among the CF/CR studies.
The dynamic change in cellobiose, xylose, lactic acid, and cell concentrations in the CF/CR process (symbols, including the operation in batch mode) and the simulation results (lines) are presented in Fig.6(a) through Fig.6(d), respectively. Significant consumptions of cellobiose and xylose were shown at the beginning phase of the batch system (from 0 to 24th hour), which was associated with the corresponding increase in lactic acid production and a slightly increase in cell concentration. Xylose was not completely utilized, and approximately 10 g·L-1 residual sugar in the effluent of the system from 24th-36th hour before cell injection. The concentrated cells were introduced 15 hours before the process was changed to continuous mode. The CF/CR functioned properly with consistent reduction in residual sugars and increase in lactic acid/cell concentrations.
The simulation results showed outstanding characterization of the process conditions over the whole experiment. It accurately predicted the consumption of cellulose at batch mode and the overall statuses of the components in continuous mode. While no measurements were conducted during the transition period (from the 39th to the 54th hours), the model simulated the degradation of sugars due to a significant increase in cells, as no additional sugars were introduced in the reactor. During the transition period, the cell concentration declined considerably due to decay, and then increased again in the continuous process when sugars were again introduced in the CF/CR process. Although the CCR on the xylose consumption during the batch mode was not simulated (Fig.6(b), hours 24-36), this model showed high sensitivity in handling the flow condition changes, cell growth, and cell retention problems.
3.5. Importance of cell retention time (CRT)
In summary of all the experimental results collected in this study for C50X30, including the relationships of cellobiose, xylose, lactic acid, and cell concentrations, are plotted in Fig.7. CRTs did show critical impacts on the continuous process. With the increase in CRT, the fermentation strain with a high density was more effective in utilizing the sugars and may be more robust, reflecting the changing properties of the hydrolysate. The benefits of the high cell density fermentation and the CRT control have been demonstrated in many biological systems, i.e., increase in xylose utilization for high biofuel productivity [26], regulation of the consumption rates of various carbon sources [27], and real-time gas phase monitoring for optimal cells metabolism [28].
Meanwhile, the difference in the commonly applied control parameter dilution rate (1/HRT) used in the conventional fermentation process over the factor for cell retention (1/CRT) should be emphasized. As the cells have been recovered from the liquid stream, the CRT of the CF/CR must be longer than the HRT, and this expression applies to all other biological systems such as bioaugmentation or fed-batch fermentation.
To better visualize the potential applications of the long CRT operation, the dynamic model was simplified to steady state expressions as the numerical strategy used in Leu et al. [27]. The expressions were derived by eliminating the accumulation terms (i.e., dX/dt and dS/dt) in Equations (7) and (8), and followed by a series of algebraic operations as presented in supplementary information (Equations (S1) to (S12)). The sugar and cell concentrations as functions of the key control parameters are presented in the following equations: (see Equations 10 and 11 in the Supplementary FIles)
The results of the steady state expressions were plotted against the experimental results in Fig.7, which also summarizes the potential benefits and issues of the model. The model clearly demonstrated the possibility of CF/CR operation for process control and optimization. For instance, the important wash-out period at low CRT operation on residual sugars and delayed cell growth was shown in the model, suggesting a potential issue of continuous operation that was not observed in the batch experiments. As the fermentation experiments at short CRT were prepared with the well-inoculated seed strains, the challenges of low CRT operation were not observed in this work. The cell bleeding and complete consumption of xylose at extremely long CRT has not been characterized because the study have targeted and designed experiments for a high productivity. The experiments were discontinued after 117 hours of operation when the maximum lactic acid concentration 65.15 g·L-1 was reached at 108 hours and the cell concentration was at the maximum at 105 hours. In the simulation model, the cell bleeding and endogenous respiration were all included in the decay term through the first-order reaction kinetics, which may be recorded more clearly if longer and well-controlled CRTs are conducted. The impacts of rapid sugar uptake and delayed growth, or CCR were not characterized due to the current model structure and limited simulation parameters. These uncertain points require further investigations of the system in the future works.