Forecasting of reducing sugar yield from corncob after ultrafine grinding pretreatment based on GM(1,N) method and evaluation of biohydrogen production potential

Li, Yameng; Zhang, Zhiping; Jing, Yanyan; Liu, Tao; Fan, Xiaoni; Zhu, Shengnan; Jiang, Danping; Lu, Chaoyang; Zhang, Huan; Yue, Jianzhi; Zhang, Yang; Yao, Zhun; Petracchini, Francesco; Li, Defeng; Zhang, Quanguo

doi:10.1016/j.biortech.2022.126836

Cited by 9 publications

(4 citation statements)

References 24 publications

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“…The maximum reducing sugar concentration of 49.83 g/L was achieved at a pretreatment duration of 12 h, which was 6.29 times higher than that of untreated corncob. Moreover, the 49.83 g/L (996.60 mg/g) of reducing sugar from DES-pretreated corncob was higher than that obtained from corncob with ultrafine grinding pretreatment (752.22 mg/g) for 2 h and a ball: powder weight of 20:1 [ 42 ]. The total reducing sugar concentration of corncob pretreated for 15 h was 49.39 g/L, which was only 0.44 g/L less than that of corncob pretreated for 12 h. The reason may be that cellulose reservation and lignin removal were almost the same when corncob was pretreated for 12 h and 15 h ( Table 1 ); therefore, the upper limit of cellulase adsorption sites was reached and the reaction tended to be stable in both cases.…”

Section: Resultsmentioning

confidence: 99%

“…The hydrogen yields of corn stalk pretreated by 2% NaOH [ 5 ] and corncob pretreated thermochemically by 2% H 2 SO 4 [ 25 ] were similar to the yields obtained in the present study. However, the best hydrogen yield from corncob was achieved with ultrafine grinding pretreatment [ 42 ] was best. The delay period of hydrogen production reflected the efficiency of the PFHP system [ 51 ].…”

Section: Resultsmentioning

confidence: 99%

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Effect of deep eutectic solvent pretreatment on biohydrogen production from corncob: pretreatment temperature and duration

Zhou,

Li,

et al. 2023

Bioengineered

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Deep eutectic solvent pretreatment with different temperatures and durations was applied to corncob to increase hydrogen yield via photo-fermentation. The correlation of composition, enzymatic hydrolysis, and hydrogen production in pretreated corncobs, as well as energy conversion was evaluated. Deep eutectic solvent pretreatment effectively dissolved lignin, retained cellulose, and enhanced both enzymatic hydrolysis and hydrogen production. The maximum cumulative hydrogen yield obtained under a pretreatment condition of 50°C and 12 h was 677.45 mL; this was 2.72 times higher than that of untreated corncob, and the corresponding lignin removal and enzymatic reduction of sugar concentration were 79.15% and 49.83 g/L, respectively; the highest energy conversion efficiency was 12.08%. The hydrogen production delay period was shortened, and the maximum shortening time was 18.9 h. Moreover, the cellulose content in pretreated corncob was positively correlated with both reducing sugar concentration and hydrogen yield and had the strongest influence on hydrogen production.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Effect of deep eutectic solvent pretreatment on biohydrogen production from corncob: pretreatment temperature and duration

Zhou,

Li,

et al. 2023

Bioengineered

Self Cite

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“…Guo and Li (2022) respectively adopted the traditional GM(1,N) model, background value optimization GM(1,N) model, and expression optimization GM(1,N) model for forecasting the carbon emission of the logistics industry in Hubei Province. Li et al . (2022) established the improved GM(1,N) model based on the observed experimental data to accurately forecast the reduced sugar yield of corncob in the ultrafine grinding pretreatment system.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting Chinese carbon emission intensity based on the interactive effect GM(1,N) power model

Wang,

2023

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PurposeThis study aims to predict China's carbon emission intensity and put forward a set of policy recommendations for further development of a low-carbon economy in China.Design/methodology/approachIn this paper, the Interaction Effect Grey Power Model of N Variables (IEGPM(1,N)) is developed, and the Dragonfly algorithm (DA) is used to select the best power index for the model. Specific model construction methods and rigorous mathematical proofs are given. In order to verify the applicability and validity, this paper compares the model with the traditional grey model and simulates the carbon emission intensity of China from 2014 to 2021. In addition, the new model is used to predict the carbon emission intensity of China from 2022 to 2025, which can provide a reference for the 14th Five-Year Plan to develop a scientific emission reduction path.FindingsThe results show that if the Chinese government does not take effective policy measures in the future, carbon emission intensity will not achieve the set goals. The IEGPM(1,N) model also provides reliable results and works well in simulation and prediction.Originality/valueThe paper considers the nonlinear and interactive effect of input variables in the system's behavior and proposes an improved grey multivariable model, which fills the gap in previous studies.

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“…In recent years, the grey theory has been utilized in various sectors [21][22][23][24], especially in the prediction model, and its accuracy in predicting outcomes in certain domains is comparable to or even exceeds that of the neural network technique [25][26][27]. GM (1, N), for instance, was proven to be applicable to forecast the pollution on insulators in circumstances of insufficient information with less data for the building model, according to the research that was published in the literature [23].…”

Section: Introductionmentioning

confidence: 99%

Transmission line ice disaster early warning method based on ice thickness prediction using GM(1, 6) model

et al. 2024

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The operation of the electricity system faces the difficulty of minimizing ice damage to transmission lines. Due to the uncertainty of transmission line icing thickness, accurate prediction of icing thickness is very important to guide transmission line planning and power grid anti-icing design effectively. Scientific and reasonable early warning assessment of conductor icing is also helpful to make timely and accurate response measures to the possible freezing disaster risk, so as to effectively ensure the safe and stable operation of power grid and reduce the occurrence of the freezing disaster. Based on this, this paper proposes a multi-factor prediction model based on GM (1, 6) grey theory, which considers the transmission line conductor icing model under the influence of multiple meteorological factors. Based on the conductor icing model, the conductor icing degree can be predicted in real time according to meteorological parameters, so as to realize the purpose of transmission line conductor icing disaster risk early warning. It is worth noting that the paper improves the traditional grey model by adding random data functions, which makes the model solve the problem of inaccurate prediction of small samples. Finally, a case study is carried out, and the icing disaster risk is divided into five levels. It is found that the maximal prediction error of icing thickness based on GM (1, 6) grey theory multi-factor prediction model is 10.06%(The average value is only 4.22%), and the accuracy of transmission line conductor icing disaster risk early warning is 88.9%. In addition, a certain safety margin value is added to the predicted value near the critical value of icing thickness, reducing the probability of judging the high-risk level as low-risk. Applying risk early warning method in ice areas can guide the antiice work of transmission line.

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Forecasting of reducing sugar yield from corncob after ultrafine grinding pretreatment based on GM(1,N) method and evaluation of biohydrogen production potential

Cited by 9 publications

References 24 publications

Effect of deep eutectic solvent pretreatment on biohydrogen production from corncob: pretreatment temperature and duration

Effect of deep eutectic solvent pretreatment on biohydrogen production from corncob: pretreatment temperature and duration

Forecasting Chinese carbon emission intensity based on the interactive effect GM(1,N) power model

Transmission line ice disaster early warning method based on ice thickness prediction using GM(1, 6) model

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