Valorization of food waste by anaerobic digestion: A bibliometric and systematic review focusing on optimization

Assis, Tatiana Izato; Gonçãlves, Ricardo Franci

doi:10.1016/j.jenvman.2022.115763

Cited by 44 publications

(21 citation statements)

References 141 publications

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“…The stability of anaerobic digestion is influenced by many factors, among them pH, alkalinity, and VFA concentration. VFA accumulation is associated with interruption in microbial metabolism, as a result, an ineffective digestion performance and even process failure was observed 40 . VFA accumulation in this process it is discussed further in the next subsection.…”

Section: Resultsmentioning

confidence: 96%

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Methane production by anaerobic co‐digestion of dairy manure and cassava wastes for energy recovery

Martins

Fonseca

Faria

et al. 2022

J of Chemical Tech & Biotech

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BACKGROUND: In this study, the anaerobic co-digestion of cassava wastewater (CW), cassava bagasse (CB), and dairy manure (DM) was investigated to produce biogas with energy recovery. Mixture experimental design was performed to establish the proportion of each substrate, on the basis of total weight (%wt). The digestion was carried out under mesophilic conditions (35 °C) using a batch test. RESULTS:The best methane yields were 150.33 NmLCH 4 gVS −1 (114.46 NmLCH 4 gCOD −1 ) for the condition with 100% CW (C/N ratio = 14.04) and 130.43 normal mililiters of methane per gram of volatile solid (NmLCH 4 gVS −1 ) and 93.84 normal mililiters of methane per gram of chemical oxygen demand (NmLCH 4 gCOD −1 ) obtained with 66.7% DM, 16.7% CB and 16.7% CW (C/N ratio = 34.84). Experimental conditions containing high proportions of CB (above 33%) yielded high C/N ratios (above 52), resulting in low pH and high volatile fatty acid production, mainly acetic and butyric acids. Kinetics of methane production under optimal conditions were best described by Groot's multi-stage model.CONCLUSION: An energy balance for the best conditions were performed, leading to 452.86 MJ ton substrate −1 for a high DM content mixture experiment (DM = 66.7%, CB = 16.7%, CW = 16.7%); thereby showing that anaerobic co-digestion can replace 22.5% of the energy demanded by cassava processing industry.

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Section: Resultsmentioning

confidence: 96%

“…VFA accumulation is associated with interruption in microbial metabolism, as a result, an ineffective digestion performance and even process failure was observed. 40 VFA accumulation in this process it is discussed further in the next subsection.…”

Section: Biochemical Methane Potentialmentioning

confidence: 99%

Methane production by anaerobic co‐digestion of dairy manure and cassava wastes for energy recovery

Martins

Fonseca

Faria

et al. 2022

J of Chemical Tech & Biotech

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“…The purpose of this system is to allow food waste which the previous steps could not eliminate to be valorized. Food waste is considered organic waste which can be valorized by anaerobic digestion for the production of energy (for example, production of biohydrogen or biomethane) [23], or by composting which can be carried out either to recover nutrients or as a carbon sequestration process, through the formation of humic substances [24].…”

Section: Waste Sortingmentioning

confidence: 99%

Development of a food waste prevention strategy: a case study in a hotel in Eastern Morocco

et al. 2023

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The present work concerns the development of a food waste prevention strategy in a restaurant operating within a hotel in the city of Saidia in Eastern Morocco. The food service sector was chosen for this study because it is the second highest contributing sector to food waste on the global scale. Therefore, the role it plays in environmental pollution should not be neglected. The food waste prevention strategy adopted in this work consisted in performing a food waste audit at first. Then, the purchasing, storage, and handling conditions of food were improved. Finally, waste sorting was performed. The average daily food waste generated by the case study restaurant was 320.3 kg/day. The highest amount of average daily food waste (166.7 kg/day) was generated during food preparation, while storage waste had the lowest amount (30.1 kg/day). The most wasted food commodities were vegetables (50.8 kg/day), fruits (47.1 kg/day), sauces (39.9 kg/day), and cereals (38.4 kg/day). While the least wasted food commodities were eggs (10.2 kg/day) and dairy products (11.7 kg/day). The majority of the food waste generated in this study was avoidable, and fish and seafood were the food commodities with the lowest Eco-efficiency (high cost – high waste). The food waste percentage decreased from 35% to 20% within approximately 4 months following the execution of the food waste prevention strategy.

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“…Nonetheless, greater acidification can happen if there is no adequate system alkalinization, and it can happen in the presence of an uneven substrate availability or organic an overload [ 6 ]. Hence, anaerobic digestion (AD) is identified as an option that can provide an efficient and long-term solution for the buildup of these wastes, while also generating biogas (methane) [ 8 , 9 , 10 ]. CM was frequently utilized as a substrate for the AD system, and it is evident that CM is an efficient feedstock for AD [ 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Influence of Molasses Residue on Treatment of Cow Manure in an Anaerobic Filter with Perforated Weed Membrane and a Conventional Reactor: Variations of Organic Loading and a Machine Learning Application

et al. 2023

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This study highlighted the influence of molasses residue (MR) on the anaerobic treatment of cow manure (CM) at various organic loading and mixing ratios of these two substrates. Further investigation was conducted on a model-fitting comparison between a kinetic study and an artificial neural network (ANN) using biomethane potential (BMP) test data. A continuous stirred tank reactor (CSTR) and an anaerobic filter with a perforated membrane (AF) were fed with similar substrate at the organic loading rates of (OLR) 1 to OLR 7 g/L/day. Following the inhibition signs at OLR 7 (50:50 mixing ratio), 30:70 and 70:30 ratios were applied. Both the CSTR and the AF with the co-digestion substrate (CM + MR) successfully enhanced the performance, where the CSTR resulted in higher biogas production (29 L/d), SMP (1.24 LCH4/gVSadded), and VS removal (>80%) at the optimum OLR 5 g/L/day. Likewise, the AF showed an increment of 69% for biogas production at OLR 4 g/L/day. The modified Gompertz (MG), logistic (LG), and first order (FO) were the applied kinetic models. Meanwhile, two sets of ANN models were developed, using feedforward back propagation. The FO model provided the best fit with Root Mean Square Error (RMSE) (57.204) and correlation coefficient (R2) 0.94035. Moreover, implementing the ANN algorithms resulted in 0.164 and 0.97164 for RMSE and R2, respectively. This reveals that the ANN model exhibited higher predictive accuracy, and was proven as a more robust system to control the performance and to function as a precursor in commercial applications as compared to the kinetic models. The highest projection electrical energy produced from the on-farm scale (OFS) for the AF and the CSTR was 101 kWh and 425 kWh, respectively. This investigation indicates the high potential of MR as the most suitable co-substrate in CM treatment for the enhancement of energy production and the betterment of waste management in a large-scale application.

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Valorization of food waste by anaerobic digestion: A bibliometric and systematic review focusing on optimization

Cited by 44 publications

References 141 publications

Methane production by anaerobic co‐digestion of dairy manure and cassava wastes for energy recovery

Methane production by anaerobic co‐digestion of dairy manure and cassava wastes for energy recovery

Development of a food waste prevention strategy: a case study in a hotel in Eastern Morocco

Influence of Molasses Residue on Treatment of Cow Manure in an Anaerobic Filter with Perforated Weed Membrane and a Conventional Reactor: Variations of Organic Loading and a Machine Learning Application

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