Impact of corn stover particle size and C/N ratio on reactor performance in solid-state anaerobic co-digestion with dairy manure

Figures & data

Table 1. Characteristics of corn stover, dairy manure and inoculum used in this study.

Parameters	Corn stover	Dairy manure	Inoculum
Dry matter (%)	94.9 ± 0.67	94.1 ± 0.06	97.7 ± 0.67
Ash content (%)	5.7 ± 0.40	15.8 ± 0.74	67.1 ± 0.05
Cellulose (%)	77.6 ± 0.64	26.4 ± 0.28	36.9 ± 0.01
Hemicellulose (%)	34.2 ± 0.23	20.9 ± 0.49	14.1 ± 0.02
Lignin (%)	5.1 ± 0.23	9.5 ± 0.47	4.1 ± 0.00
*pH	5.6 ± 0.09	7.8 ± 0.62	6.8 ± 0.88
Carbon (%)	41.4 ± 0.38	40.3 ± 0.89	19.0 ± 0.31
Nitrogen (%)	0.8 ± 0.06	2.8 ± 0.29	2.7 ± 0.22
Ammonia (g/L)	0.0 ± 0.00	2.9 ± 0.39	0.5 ± 0.06
*Alkalinity (g/L)	5.5 ± 0.10	8.8 ± 0.34	1.5 ± 0.05
Crude protein (%)	4.8 ± 0.36	17.6 ± 0.59	16.8 ± 0.39
*Volatile fatty acids (g/L)	ND	7.7 ± 1.20	0.0 ± 0.00-

Notes. Mean values and the respective standard deviation are reported. All analyses were on dry basis, however, those with wet basis are indicated with *. ND denotes not detected.

Table 2. Co-digestion substrate mix proportion based on total solids.

Treatment	Quantity of dairy manure (%)	Quantity of corn stover (%)	Quantity of inoculum (%)	C/N
DMCS24S	34.6	32.2*	33.2	24
DMCS24L	34.6	32.2	33.2	24
DMCS28L	38.4	17.5	44.1	28
DMCS32L	29.4	60.5	10.1	32

Notes. *Indicates corn stover with 0.18–0.42 mm particle size, also denoted with S in the treatment, while others used (0.42– 0.84 mm) particle size. The notation DMCS24S(L) stands for Dairy Manure + Corn Stover + C/N ratio + Particle size (S – small and L – large).

Figure 1. Process flowchart and the SEM image surface profile analysis strategy. (a) Overall flowchart of the developed ImageJ plugin showing sequence of image processing operations for profile classification of the corn stover particle sizes, (b) demonstration of the surface profile analysis on a portion of SEM image showing 10 rectangular sub-ROIs used for profile values extraction, and (c) illustration of grayscale profile generation for one sub-ROI by averaging gray pixels along hsROI vertically and proceeding along LsROI horizontally.

Figure 2. Sample SEM images of ground corn stover at two particle sizes (0.14–0.42 mm and 0.42–0.84 mm) showing the selected replication regions along with their surface profile from sub-ROIs. The black rectangles in Rep #2 represent the sub-ROIs used for generating the respective profile given below the SEM image.

Table 3. Details of the kinetic models used in this study.

Kinetic Model	Mathematical expression	Source
First order	$Y\left(t\right)=Y\mathrm{m}\mathrm{x}\times \left(1-e^{-kt}\right)$
Modified First order	$Y\left(t\right)=Y\mathrm{m}\mathrm{x}\left[\left(1-Y\right)-\left(1-Y\right)\times e^{-kt}\right)]$
Cone	$Y\left(t\right)=Y\mathrm{m}\mathrm{x}/\left(1+{\left(pt\right)}^{-n}\right)$	Syaichurrozi (2018)
Modified Gompertz	$Y\left(t\right)=Y\mathrm{m}\mathrm{x}\mathrm{e}\mathrm{x}\mathrm{p}${$-\mathrm{e}\mathrm{x}\mathrm{p}\left[\frac{\mu j}{Y\mathrm{m}\mathrm{x}}\left(\lambda -t_h\right)+1\right]\}$	Syaichurrozi (2018)
Fitzhugh (Chapman)	$Y\left(t\right)=Y\mathrm{m}\mathrm{x}\times {\left(1-e^{-kt}\right)}^n$	Yuan et al. (2019)
Page	$Y\left(t\right)={\left(e^{-kt}\right)}^n$
Exponential	$Y\left(t\right)=e^{-kt}$
Peleg	$Y\left(t\right)=Y\mathrm{m}\mathrm{x}+\mathrm{t}/\left(k+vt\right)$
Logistic growth	$Y\left(t\right)=Y\mathrm{m}\mathrm{x}/(1+z{e}^{-kt}$)

Notes. Y(t) is stimulated or cumulative methane yield at the cessation of the experiment (mL/gVS); Ymx is the methane potential of the ingestate (mL/gVS); k is the methane production rate constant or first order rate constant (1/day); t is the digestion time in days; p is the hydrolysis rate constant for the cone model (1/day); Y is the non-biodegradable fraction of the treatment; n is the shape factor (dimensionless); µ is the maximum methane production rate (mL/gVS/day), λ is the lag phase time in hours; j is the Euler’s number (2.71821828); v represents the kinetic rate constant (1/day); z is the integrated constant related to the initial methane yield and t_h is digestion time in hours.

Table 4. Characteristics of pre- and post-digestion samples under different treatments.

Parameter	DMCS24S		DMCS24L		DMCS28L		DMCS32L
	Ingestate	Digestate	Ingestate	Digestate	Ingestate	Digestate	Ingestate	Digestate
Alkaline (g/L)	3.68 ± 0.00	8.06 ± 0.02	4.24 ± 0.01	8.72 ± 0.02	2.50 ± 0.18	2.55 ± 0.33	4.13 ± 0.09	1.61 ± 0.68
VFA (g/L)	7.33 ± 0.02	12.39 ± 0.09	7.92 ± 0.02	4.46 ± 0.02	2.10 ± 0.00	16.59 ± 0.04	2.41 ± 0.00	30. 2 ± 0.08
Ammonia (g/L)	1.63 ± 0.09	4.69 ± 0.29	1.53 ± 0.01	4.80 ± 0.65	0.65 ± 0.00	1.85 ± 0.05	0.31 ± 0.01	1.26 ± 0.05
pH	7.56 ± 0.06	7.36 ± 0.30	7.37 ± 0.02	7.63 ± 0.05	7.52 ± 0.00	5.19 ± 0.01	6.78 ± 0.10	5.13 ± 0.04
ORP (mV)	−383.0 ± 0.10	−257.4 ± 3.50	−344.2 ± 0.20	−328.0 ± 1.20	−358.4 ± 0.00	158.2 ± 13.9	− 314.4 ± 0.90	110.5 ± 10.5
Crude protein (%)	11.85 ± 0.18	11.44 ± 0.48	10.33 ± 0.09	12.42 ± 0.25	9.90 ± 0.09	7.70 ± 0.21	7.15 ± 0.00	6.36 ± 0.12
Dry matter (%)	96.76 ± 0.00	96.48 ± 0.25	96.88 ± 0.00	95.89 ± 0.01	94.52 ± 0.04	97.40 ± 0.00	95.05 ± 0.00	93.77 ± 0.02
Ash (%)	14 .74 ± 0.00	18.65 ± 0.77	12.01 ± 0.00	19.33 ± 0.18	8.61 ± 0.08	8.88 ± 0.00	9.40 ± 0.00	10.32 ± 0.47

Notes. Treatment description for this table is presented in Table 2, VFA is volatile fatty acids, ORP is redox potential Crude protein and dry matter are represented in dry matter, alkalinity, VFA, and ammonia, are in wet basis. The values presented are mean of composition and their respective standard deviation.

Figure 3. VFA concentration of the treatments at the pre- and post-digestion stage (error bar = 1 std. dev).

Table 5. Process parameter for each treatment used in this study.

Treatment	VFA/Alkalinity	VFA/Ammonia	P/A ratio
DMCS24S	1.54	2.64	0.46
DMCS24L	0.51	0.93	0.74
DMCS28L	6.51	8.97	0.53
DMCS32L	18.76	23.97	0.52

Notes. P/A represents ratio of propionic to acetic acid. Treatment description for this table is presented in Table 2.

Figure 4. Cellulose, hemicellulose, and substrate biodegradability under different treatments (error bar = 1 std. dev).

Figure 5. Total and volatile solids reduction under different treatments (TS, VS; error bar = 1 std. dev).

Figure 6. Methane composition over time for different treatments.

Figure 7. Hydrogen sulfide concentration trends under different treatments.

Figure 8. Overall biogas and methane yield for different treatments.

Figure 9. Volumetric methane production and total methane energy for treatments with a C/N ratio of 24(error bar = 1 std. dev).

Figure 10. Mean and standard deviation values of the profile features from 10 sub-ROIs of each replication (based on polygonal ROI) from the milled corn stover SEM images discriminating the particle sizes.

Figure 11. Cumulative methane production with different treatments over the time studied.

Table 6. Kinetic model and validation for treatment with C/N ratio of 24.

Kinetics model	Data	Parameter a	Parameter b	Parameter c	r	R^2	Adj R^2	RMSE	NRME (%)	AIC	Rank	Observed 60 d	Pred. 60 d	Pred. 90 d	Pred. 120 d	Shape
First order	DMCS24S	1.0302E+03	7.7749E-04		0.9937	0.9660	0.9655	2.305	4.385	281.22	7	52.59	46.95	69.62	91.77	Inc – linear
Modified first order	DMCS24S	1.0929E+01	−2.5846E+02	2.8026E-04	0.9940	0.9690	0.9680	2.234	4.249	279.59	6	52.59	47.28	70.63	93.78	Inc – linear
Exponential	DMCS24S		−2.2482E-02		0.9659	0.6348	0.6348	5.296	10.073	380.55	9	52.59	38.94	45.64	49.05	Exp – low
Page	DMCS24S		−1.1309E-03	1.8306E+00	0.9890	0.9781	0.9777	2.314	4.402	281.69	8	52.59	45.72	51.86	52.55	Sig – low
Peleg	DMCS24S	1.6280E+00	−7.8442E-03		0.9973	0.9944	0.9943	1.126	2.141	193.74	1	52.59	50.50	80.51	110.30	Up – nonlin
Cone	DMCS24S	6.8187E+02	2.2829E-03	1.2706E+00	0.9969	0.9940	0.9938	1.198	2.278	203.52	3	52.59	50.37	79.45	107.44	Inc – linear
Modified Gompertz	DMCS24S	3.2192E+01	3.6978E-01	4.1093E+01	0.9953	0.9901	0.9898	1.485	2.824	229.78	4	52.59	50.28	70.42	80.37	Sig – right
Firzhugh	DMCS24S	6.5605E+02	2.3806E-03	1.2717E+00	0.9970	0.9940	0.9938	1.192	2.266	202.91	2	52.59	50.49	80.91	111.68	Inc – linear
Logistics growth	DMCS24S	1.6136E+01	6.9492E-02	6.2124E+01	0.9929	0.9840	0.9834	1.855	3.528	256.91	5	52.59	49.72	60.25	61.89	Sig – right
First order	DMCS24L	2.8427E+03	6.0552E-04		0.9894	0.9019	0.9003	7.847	7.405	430.65	6	105.98	101.42	150.77	199.23	Inc – linear
Modified first order	DMCS24L	1.2181E+01	−6.0605E+02	2.3153E-04	0.9896	0.9068	0.9035	7.752	7.315	431.38	7	105.98	102.01	152.49	202.62	Inc – linear
Exponential	DMCS24L		−6.4887E-02		0.8543	−0.9999	−0.9999	26.248	24.770	575.83	9	105.98	51.52	52.44	52.57	Sig – low
Page	DMCS24L		−7.7956E-06	3.7023E+00	0.9251	−0.7524	−0.7821	22.746	21.464	560.49	8	105.98	52.59	52.59	52.59	Sig – low
Peleg	DMCS24L	7.7284E-01	−4.0305E-03		0.9884	0.9641	0.9635	5.925	5.591	396.37	5	105.98	113.00	219.47	414.98	Up – nonlin
Cone	DMCS24L	1.3503E+02	2.6315E-02	2.5749E+00	0.9988	0.9974	0.9974	1.839	1.736	255.86	2	105.98	103.20	121.80	128.38	Sig – right
Modified Gompertz	DMCS24L	4.3841E+01	9.8259E-01	2.8720E+01	0.9989	0.9978	0.9977	1.687	1.592	245.32	1	105.98	102.70	116.36	118.72	Sig – right
Firzhugh	DMCS24L	1.2776E+02	4.8060E-02	3.6538E+00	0.9986	0.9971	0.9970	1.973	1.862	264.41	3	105.98	103.53	121.69	126.31	Sig – right
Logistics growth	DMCS24L	3.8519E+01	1.1409E-01	1.0335E+02	0.9981	0.9958	0.9957	2.238	2.111	279.78	4	105.98	99.28	103.21	103.34	Sig – low

Notes. Treatment description for this table is presented in Table 2. The model parameter “a” corresponds to the kinetic model parameter “Ymx” presented in Table 3; the model parameter “b” corresponds to the kinetic model parameter “k” presented in Table 3; the model parameter “b” also corresponds to the kinetic model parameter “p” for cone model presented in Table 3. Other parameters are stated in Table 3. Pred. is predicted methane yield at specified days after digestion. Shapes of the kinetic models determined after plotting the predicted methane yields well beyond the observed end (60 d) of the experiment: Inc – linear (increasing linearly), Exp – low (exponential growth but low), Sig – low, – right (sigmoid and -low and -correct predictions), and Up – nonlin (upward nonlinear growth).

Syaichurrozi, I. 2018. Biogas production from co-digestion Salvinia molesta and rice straw and kinetics. Renew. Energy 115:76–86. doi:10.1016/j.renene.2017.08.023.

 Web of Science ®Google Scholar

Yuan, H., Y. Lan, J. Zhu, A. C. Wachemo, X. Li, and L. Yu. 2019. Effect on anaerobic digestion performance of corn stover by freezing–thawing with ammonia pretreatment. Chin. J. Chem. Eng. 27 (1):200–07. doi:10.1016/j.cjche.2018.04.021.

 Web of Science ®Google Scholar