Effect of Lipid Type on the Acidogenic Performance of Food Waste

Abstract

Due to its high lipid content and intricate constitution, food waste poses a considerable challenge for biotreatment. This research aims to investigate the potential influence of diverse lipid species on anaerobic fermentation, induced by the varying dietary patterns observed in distinct regions. The investigation involved incorporating 5% (w/w) of beef tallow, mutton fat, soybean oil, peanut oil, and rapeseed oil, separately, into simulated food waste, and subjected it to batch mode acidogenic fermentation. The inclusion of unsaturated fatty acids resulted in a redirection of the metabolic pathway from the lactic acid type to the ethanol, acetic acid, and butyric acid types. The succession of the acidogenic metabolic pathway was highly correlated with the lipid types; beef tallow, mutton fat, soybean oil, and peanut oil delayed the metabolic process by 1, 2, 3, and 8 d, respectively, whereas rapeseed oil accelerated it by 2 d. The lipids contained within the food waste did not facilitate the buildup of soluble substances, resulting in a decrease of 14.0~59.7%. Notwithstanding, valeric acid was exclusively generated during the beef tallow and peanut oil treatments, whereas the production of lactic acid in peanut oil showed a 35.9% increase in comparison to the control.

1. Introduction

Food waste, encompassing restaurant waste, market waste, and household kitchen waste, etc., constitutes the largest component of municipal solid waste, accounting for approximately 30–50% of the total amount [1,2,3]. According to the United Nations Food and Agriculture Organization’s statistics, one third of the world’s food is squandered during the food system’s supply process [2,3,4]. It has been estimated that the volume of food waste in Asian nations will surge from 2.78 billion tons to 4.16 billion tons by the year 2025 [5].

In particular, within China, as urbanization and economic prosperity continue to advance swiftly, the rate of increase in food waste has surpassed 10% [6]. As outlined in the China Statistical Yearbook (2021), in the year 2020, China generated approximately 352.1 million metric tons of municipal solid waste. Food waste contains lipids, proteins, and carbohydrates, which can easily deteriorate and grow pathogens and bacteria. Therefore, finding an effective technology to process food waste is important for waste reduction, emission reduction, and resource utilization.

Composting, biological fermentation, biological drying, incineration, feed, and sanitary landfills are the current prevailing technologies utilized for treating food waste [7,8]. Nonetheless, these methodologies are still encumbered with certain inadequacies. For instance, providing untreated food waste to animals may make them more susceptible to infection. Composting and sanitary landfill processes may require a large portion of valuable land and emit greenhouse gases [9,10]. Owing to the high moisture content of food waste, incineration may face challenges with regards to energy tension and instability [11]. In comparison to other treatment technologies, anaerobic digestion has demonstrated a great deal of promise in terms of integrating organic waste management and bioenergy recovery [12]. Anaerobic digestion has been employed to reduce food waste and harness energy from it. Because of different culinary habits, cooking techniques, and cultural norms, Chinese food waste differs from that of other countries, typically featuring high oil content, high salinity, high moisture content, and high organic matter content [13].

Food waste contains a significant amount of oil, derived from both plant and animal sources, in the form of triglycerides and fatty acids. Animal oils are primarily composed of monounsaturated fatty acids, while vegetable oils consist of polyunsaturated fatty acids. The concentration range of oil in food waste is typically between 20.0 to 30.0 g/L, and the content of waste edible oil may range from 1 to 5% (wet basis) [14]. In comparison to protein and carbohydrates, oil has the highest biochemical methane potential in food waste. However, long-chain fatty acids (LCFAs) in food waste can impede biodegradation, resulting in toxicity to microorganisms and biological adsorption [15]. Studies revealed that food waste with lipid content exceeding 35% may lead to an extended lag period and lower first-order degradation constant during the anaerobic process [16].

During anaerobic digestion, large organic molecules are broken down into smaller molecules that can be used by bacteria. These bacteria then convert the organic matter into various compounds, such as LCFAs, sugars, and amino acids. Oils and fats are broken down by hydrolytic bacteria into LCFAs and glycerol. The process ultimately produces short-chain fatty acids and fermentation products like H₂, CO₂, and CH₄ [17,18]. The biodegradability and hydrolysis rate of lipids, proteins, and carbohydrates differ, with lipids having the lowest rate. Consequently, lipid degradation is considered a rate-limiting step in the anaerobic digestion of food waste [19]. A high content of lipids in food waste not only hinders the digestion rate, but also leads to the accumulation of residues in the anaerobic digestion system. Thus, lipid degradation is indispensable for the effective transformation of food waste [20].

Previous research has documented numerous concentrations of lipids that exhibit inhibitory effects, such as chemical oxygen demand and volatile solids. Additionally, it has been demonstrated that the inhibitory impact induced by LCFAs varies depending on the specific raw materials utilized [21]. For example, the outcomes revealed that palmitic acid (16:0), a representative saturated acid, constitutes a considerable proportion in rapeseed oil [22]. The typical fatty acid composition of lipids present in food waste is shown in Table 1.

Sobon-Muhlenbrock et al. [23] conducted a study on anaerobic digestion of food waste with varying fat content and found that higher fat content did not strongly affect biogas production under low loading conditions, but significantly impeded it under high loading conditions. Zhu et al. [24] found that mixed long-chain fatty acids (LCFAs), derived from soybean oil, hindered the process of anaerobic digestion of organic waste by adsorbing to the cell wall or cell membrane of methanogenic bacteria, disrupting their transport or defense functions, and impeding digestion of other substances. The accumulation of LCFAs and volatile fatty acids, particularly propionic acid and butyric acid, can disrupt the original metabolic balance and cause anaerobic system disruption, including system paralysis [25]. However, these studies did not compare the effects of different oil types on anaerobic digestion and acid production. The majority of research has concentrated on investigating the impact of particular oils on anaerobic methane generation from food waste.

Therefore, our investigation aims to examine the influence of various oils and fats on anaerobic acid production and the conversion characteristics of food waste. Through scrutiny of the alterations in the chemical oxygen demand (COD) and VFAs, the effect of different types of lipids present in food waste on its acidogenic fermentation procedure was assessed. Moreover, through meticulous examination of the fluctuations in the VFAs, the generation of acid during the anaerobic digestion process of food waste was explored. This work is anticipated to present fresh insights into the anaerobic digestion of greasy food waste, with the eventual aim of facilitating resource recovery from food waste.

Table 1. Typical fatty acid composition of lipids in food waste.

Origin		Saturated Fatty Acid (%)								Unsaturated Fatty Acid (%)						Refs.
		14:0	16:0	17:0	18:0	20:0	22:0	24:0	Total	16:1	18:1	18:2	18:3	20:1	Total
Animal origin	Beef tallow	2–6	20–37	0–1	16–40				40–55	2–8	35–50	0.5–6			45–60	[22,26,27,28]
	Muttonfat	3–6	25–28	1–2	30–34				60–70	1–2	30–35	1–2			30–40	[27,28]
Plant origin	Soybean oil		10–14		2–5				13–19		22–26	47–57	7–8		80–85	[22,29,30,31]
	Peanutoil		9–14		2–5	1–2	2–3	1–2	17–20		45–55	23–33	0–2	0–1	>80	[22,26,29,32]
	Rapeseed oil		0–5		0–2				7–8		60–65	15–20	5–10	1–2	>90	[22,29,32]

Table 1. Typical fatty acid composition of lipids in food waste.

Origin		Saturated Fatty Acid (%)								Unsaturated Fatty Acid (%)						Refs.
		14:0	16:0	17:0	18:0	20:0	22:0	24:0	Total	16:1	18:1	18:2	18:3	20:1	Total
Animal origin	Beef tallow	2–6	20–37	0–1	16–40				40–55	2–8	35–50	0.5–6			45–60	[22,26,27,28]
	Muttonfat	3–6	25–28	1–2	30–34				60–70	1–2	30–35	1–2			30–40	[27,28]
Plant origin	Soybean oil		10–14		2–5				13–19		22–26	47–57	7–8		80–85	[22,29,30,31]
	Peanutoil		9–14		2–5	1–2	2–3	1–2	17–20		45–55	23–33	0–2	0–1	>80	[22,26,29,32]
	Rapeseed oil		0–5		0–2				7–8		60–65	15–20	5–10	1–2	>90	[22,29,32]

2. Materials and Methods

2.1. Substrate and Inoculum

Simulated food waste was utilized as the substrate. The food waste was created by combining bread, cabbage, meat, and rice in mass fractions of 35%, 25%, 15%, and 25%, respectively, as reported by Yan et al. [10]. The seed sludge employed in the experiment was obtained from the digester inoculated with rumen liquid cultures. The inoculum was acclimatized through a stepwise increase in the nutrient solution in the laboratory and enriched at a constant temperature of 35 ± 2 °C. The nutrient solution was composed of C₆H₁₂O₆·H₂O 4.00 g/L, CH₃COONa 2.80 g/L, NH₄Cl 0.22 g/L, and KH₂PO₄ 0.05 g/L (~5600 mg COD/L, C:N:P = 200:5:1). The inoculum was cultivated to reach a methane content of over 60% while maintaining a stable pH range of 6.8–7.2 and COD of 500–1000 mg/L in the effluent. Prior to use, the inoculum was acclimated with a two-week feeding of nutrient solution, without oligo elements, and a starvation phase, resulting in VFA < 500 mg/L and total alkalinity < 600 mg/L. The inoculum was collected through natural settling, without centrifugation or filtration, and was a mixture of sediment and water.

Table 2. Characteristics of inoculum and food waste.

Parameters	Food Waste	Inoculum
pH	5.79 ± 0.14	6.86 ± 0.10
VS (%)	43.40 ± 0.95	2.26 ± 0.11
TS (%)	44.70 ± 0.34	2.96 ± 0.15
TOC (%)	40.25 ± 1.43	8.50 ± 0.31
TN (%)	2.13 ± 0.32	0.21 ± 0.08

presents the fundamental characteristics of the seed sludge and food waste.

2.2. General Procedure and Experimental Design

This study utilized a batch experiment design, with 500 mL serum bottles serving as the acidogenic reactors. Six treatments were established, namely, blank (CK), beef tallow (T1), mutton fat (T2), soybean oil (T3), peanut oil (T4), and rapeseed oil (T5). The digestion reactor was packed with 80 g of food waste, 100 g of inoculum, 400 mL of working volume, and 4 g of a specific oil or fat. The solid content of the anaerobic digestion feed was approximately 9%, while the organic load was approximately 83 g/L. Prior to the commencement of the experiment, nitrogen was introduced into the reaction device for 30 min to eliminate the air above the liquid level and establish an anaerobic environment, as reported by He et al. [33]. The experiment was conducted at a consistent temperature of 35 ± 2 °C for 20 d in an incubator device. A volume of 20 mL of the digestion solution in the anaerobic bottle was extracted daily, and an equal volume of deoxygenated deionized water, with a 0.5M NaHCO₃ solution (used to balance the pH of the fermentation system to approximately 6 in the initial stage), was supplied to maintain the volume of the entire system at 400 mL. After each sampling event, the reactor underwent a 10 min purging process with nitrogen to maintain optimal anaerobic conditions.

2.3. Analytical Methods

The procedures for determining total solids (TS), volatile solids (VS), total organic carbon (TOC), and total nitrogen (TN) were adopted from Yan et al. [10] and Liu et al. [34]. The pH value of the liquid solution was measured using a pH meter (FIveGo F2, Shanghai Mettler Toledo, Shanghai, China). The COD was determined by the potassium dichromate concentrated sulfuric acid oxidation method, in accordance with the Standard Method. The biogas composition was analyzed utilizing gas chromatography (7890PLUS, Shandong LunanRuihong, Tengzhou, China) with a packed column (Carbon molecular sieve TDX-01, Shandong LunanRuihong, Tengzhou, China). The gas chromatography was equipped with a thermal conductivity detector and operated under the following conditions: a bridge current of 60 mA, a detector temperature of 120 °C, and a column temperature of 80 °C. The volume of gas was measured using a wet gas flow meter. The soluble products, including total VFAs (acetate, propionate, iso-and n-butyrate, iso-and n-valerate, and caproate), alcohol (ethanol, propanol, and butanol), solvents (acetone), and lactic acid, were determined by high-performance liquid chromatography (LC-20A, Shimadzu, Kyoto, Japan) with an Aminex HPX-87H column (300 × 7.8 mm, Bio-Rad, CA, USA). Both ultraviolet and differential detectors were used for soluble product analysis. The operational parameters of the high-performance liquid chromatography were as follows: a column temperature of 55 °C, a mobile phase of 5 mM H₂SO₄, and a flow rate of 0.5 mL/min. The standard deviation of the data presented in the graphs is not visible, with the vast majority of relative deviations not exceeding 5%; thus, error bars were uniformly omitted to optimize the figures.

3. Results and Analysis

3.1. Effect of Different Lipid Types on the Variations of pH and Chemical Oxygen Demand

Figure 1 reveals that the pH variations of the six treatments manifest a comparable pattern during the acidogenic phase. The dynamic trend exhibits an initial rise, followed by a decline, and then an upswing once again. The swift acidification of food waste accounts for the high acidity (with pH ≈ 4.00 in day 1) during the early stage of fermentation. The primary reason for pH fluctuations is the adjustment measures and the metabolism of soluble products. The pH predominantly oscillates below 5.50 from day 0 to 8, whereas during day 8 to 20, it mostly fluctuates between 6.00 and 7.00. T5 treatment experiences a more rapid pH increase compared to the other treatments, and the pH value of T5 reaches a pinnacle of 6.55 ± 0.17 on day 7. Moreover, T5 treatment’s pH tends to stabilize after 10 d, while CK treatment’s pH tends to stabilize after 13 d. From T1 to T4, the pH stabilization time takes approximately 17, 16, 18, and 19 d, respectively. From CK to T4, the time for the initial peak of pH is 8, 13, 11, and 10 d, respectively. This turning point in pH changes plays a crucial role and has a certain correlation with product metabolism.

According to Figure 2a, a downward trend in COD was observed among the six treatments, indicating the utilization, transformation, and degradation of organic matter during the process. On day 20, the COD of each treatment from CK to T5 was 30.15 ± 0.66bc, 31.58 ± 0.85a, 29.87 ± 0.39bc, 29.19 ± 0.66c, 31.03 ± 0.62ab, and 26.35 ± 0.75d g/L, respectively. The COD of the six treatments exhibited a slow downward trend during 0–8d, ranging from about 50.00 g/L to about 45.00 g/L. Subsequently, daily COD changes were divided into three categories. The first type, represented by T5, exhibited a rapid decline, while the second type, represented by CK, T2, and T3, declined at a moderate speed. Finally, the third type, represented by T1 and T4, exhibited a slow decline. These COD decline trends may be closely linked to the metabolic transformation and consumption of organic matter. The rate of COD loss from CK to T5 was 38.63%, 36.70%, 38.58%, 40.59%, 35.27%, and 45.25%, respectively.

As depicted in Figure 2b, the cumulative COD in 20 d from CK to T5 was 1049 ± 30.78ab, 1085 ± 43.75a, 1045 ± 47.91ab, 1049 ± 34.05ab, 1054 ± 38.67ab, and 1001 ± 42.68b g/kg VS_added, respectively. Due to the addition of oil and fat, the added substrate contained a large amount of LCFAs that were difficult to utilize, and COD in the treatments with the addition of lipids was generally lower than that in the control. Among them, T5 had the lowest COD conversion rate, but it was also possible that the metabolic consumption was the highest, resulting in a reduction of COD retention into the liquid phase.

3.2. Effect of Different Lipid Types on the Production of Soluble Products

It is evident from Figure 3 that lactic acid, acetic acid, propionic acid, butyric acid, and ethanol are the predominant soluble products. The conversion of metabolic pathways from lactic acid to ethanol, acetic acid, or butyric acid types was comparable among all treatments. Initially, all treatments mainly generated lactic acid, and the primary reason for lactic acid’s dominance was the low pH value during the reaction’s initial stages. This discovery is consistent with the conclusions presented in previous literature, where low pH values were commonly correlated with increased yields and held significant importance in establishing the dissemination of soluble intermediates and metabolic pathways [16]. The time required for lactate-type fermentation to decline from CK to T5 was 10, 10, 11, 12, 16, and 7 d, respectively. This means that the proportion of lactic acid gradually decreases and falls below 50%, and it is gradually replaced by acetic acid, butyric acid, and ethanol. The transformation of metabolic pathways leads to changes in product composition and is also the key factor influencing the environment of acidogenic fermentation systems. Furthermore, valeric acid was only present in T2 on 13–19 d and T5 on 13–18 d. Valeric acid is typically metabolized from six-carbon sugars and can be further metabolized into propionic acid and acetate. T5 has a shorter lactic acid production time than CK and T1–T4, with T5 ceasing lactic acid production on day 8, after which the pH value peaks. The addition of 5% soybean oil to T4 resulted in the longest lactic acid production time of 18 d. Notably, the addition of soybean oil significantly inhibited changes in the metabolic pathway of acidogenic fermentation of food waste.

Based on previous research [35] and the results of this experiment, the metabolic pathway of soluble products can be proposed, as shown in Figure 4. Initially, the proteins, sugars, and lipids present in food waste are hydrolyzed into monosaccharides, while unsaturated fatty acids in oil undergo oxidation to form saturated fatty acids. In the subsequent step, monosaccharides, such as glucose, are swiftly utilized, leading to their conversion into lactic acid and the production of H₂ and CO₂. In the third step, a considerable amount of lactic acid is metabolized into various end products, such as ethanol, acetic acid, butyric acid, and propionic acid. Additionally, the monosaccharides provided by the continuous hydrolysis of the substrate are metabolized to valeric acid, which is subsequently transformed into acetate and propionate. This represents the primary metabolic pathway observed in this study.

According to the analysis of acid production accumulation, as illustrated in Figure 5, the highest accumulation of lactic acid was observed in T4 (359.7 ± 14.26a), followed by T1 (318.3 ± 13.76b), T2 (305.3 ± 14.80b), CK (282.1 ± 7.66c), T3 (268.6 ± 9.11c), and T5 (240.1 ± 11.69d, g COD/kg VS_added). These findings imply that none of the treatments were conducive to the accrual of soluble substances. Compared to CK, the percentage change from T1 to T5 was 12.82%, 8.22%, −4.77%, 27.50%, and −14.88%, respectively. Valeric acid accumulation was only observed in T2 and T4, at 23.39 ± 0.67a and 18.52 ± 0.48b g COD/kg VS_added, respectively. An addition of fat or oil was found to reduce the production of propionic acid, with a decrease of 56.56%, 43.81%, 46.74%, 80.71%, and 71.42% observed from T1 to T5, respectively. The order of acetic acid production in all treatments was T5 > T1 > T2 = T3 > CK > T4 (see Figure 3), and T1 exhibited the highest accumulation of acetic acid (29.05 ± 0.87a > CK = 24.40 ± 0.85b g COD/kg VS_added). Moreover, T1 showed the second-highest accumulation of ethanol (121.0 ± 3.78b g COD/kg VS_added) after the control (135.1 ± 5.15a g COD/kg VS_added).

The principal aim of anaerobic digestion is to transmute organic matter into biomass energy. Gas production serves as a crucial parameter for evaluating the efficacy of this process. In Figure 6a, we observe the cumulative H₂ production during the acidogenic fermentation of food waste, featuring diverse types of oils and fats. The total H₂ production for CK to T5 was 17.27 ± 0.57b, 13.36 ± 0.57c, 8.16 ± 0.57d, 14.16 ± 0.57c, 20.14 ± 0.57a, and 19.35 ± 0.57a L/kg VS_added, sequentially. Notably, distinct treatments exhibited distinctive H₂ production peak times, revealing that metabolic discrepancies within the acidogenic fermentation system were noticeable. CK and T5 displayed analogous rules for H₂ production and cumulative H₂ production. Moreover, it is meaningful to note that the time for the rise in hydrogen production was proximate to the point in time when lactate consumption occurred. T3–T5’s cumulative H₂ production with vegetable oil surpassed that of T1–T2, which utilized animal oil. Concerning the cumulative CO₂ production from CK to T5 (Figure 6b), the values were 17.12 ± 0.48a, 13.13 ± 0.62c, 12.06 ± 0.26d, 11.96 ± 0.27d, 7.92 ± 0.15e, and 15.63 ± 0.15b L/kg VS_added, sequentially.

4. Discussion

4.1. Effect of Lipid Type on the Acidogenic Fermentation Process of Food Waste

The primary factors that influence the acidogenic process are temperature, substrate, and pH. In this study, the experimental conditions are mesophilic, which is the most commonly utilized and optimal choice for transforming LCFAs into metabolites [36]. The fat content in food waste ranges from 2% to 10%, which is mainly determined by local dietary habits. Although the oil content in food waste is relatively low, it nevertheless plays a notable role in anaerobic biological treatment processes [37,38,39]. This is mainly due to three factors: (1) LCFAs in oils require longer metabolic processes, particularly unsaturated LCFAs, which primarily depend on the rate-limiting step of β-oxidation; (2) LCFAs can be utilized as substrates for microbial growth and development, but a certain amount of LCFAs can hinder the transfer of nutrients and substrates by adsorbing onto the surface of microorganisms; and (3) LCFAs require specific microbial populations for metabolism, which can, in turn, impact the microbial community structure in the reaction system. pH is the key factor in anaerobic processes, as it influences the primary metabolic pathways by affecting microbial activity [40]. However, VFA accumulation can lead to a decrease in pH within the reactor (pH < 4.0), which can inhibit hydrolysis and disrupt the anaerobic system’s equilibrium. To prevent process failure due to an acid crisis, 0.5M NaHCO₃ was used for pH adjustment, similar to the control group. The anaerobic process is more stable with a pH value around 6, and optimal acid production performance is achieved [4]. Changes in pH during the acidogenic process have a significant relationship with the composition of dissolved organic matter (Figure 3). When the pH rises to the first peak, the proportion of lactate declines rapidly due to the high levels of lactic acid. Additionally, the pH drop of T1 and T4 coincides with the production of valeric acid, which may indicate a new stage of substrate metabolism. Excessive monosaccharides can promote valeric acid production, which can lead to a decrease in acidity. The pH is stable when the composition of ethanol, acetic acid, propionic acid, and butyric acid is stable.

4.2. Effect of Lipid Type on the Generation of Acidogenic Product

Amani et al. [41] identified propionate as an unfavorable intermediate, due to its toxicity to common anaerobic bacteria. Propionic acid is present throughout the entire reaction process in each treatment, and the control group produced the most propionic acid, posing the greatest potential threat to the anaerobic reaction. In contrast, T5 and T4 produced the lowest amount of propionic acid, likely due to the excess of unsaturated LCFAs that force microorganisms to slow down the metabolism of substrates, thereby reducing propionic acid production. Rapeseed oil contains the highest proportion of unsaturated LCFAs among all types of oils in this experiment, which may explain the fastest rise in pH, the lowest cumulative conversion of COD, and the lowest cumulative production of soluble products observed in T5. However, T5 and T4 had the highest cumulative H₂ production (Figure 6), possibly because unsaturated LCFAs inhibited the hydrolysis and acidification of the substrate, accelerating the conversion of soluble products. As the pH rises, ethanol, acetic acid, and butyric acid begin to be produced in large quantities.

Pervez et al. [4] and Wang et al. [42] suggested that a pH range of 5.0–6.0 is beneficial to the production of butyrate. According to Figure 3, the pH values of the six treatment groups were all stable above 5.0, and most of them maintained stable pH values above 5 from 7d to 18d. Acetate and ethanol are common intermediates in the acidogenic fermentation of organic matter, often combined during fermentation to produce hydrogen [16]. Acetate can be derived not only from pyruvate via the acetyl-CoA pathway, but also from eutrophic oxidation of ethanol or long-chain fatty acids, such as propionate and butyrate. The large amount of acetate in acetate fermentation is closely related to functional enzymes in the acetyl-CoA pathway and co-nutrient oxidation [43]. Ethanol is a prevalent byproduct of the fermentation of glucose or other organic substances. Enterobacteriaceae requires three steps to convert pyruvate to ethanol, with acetyl-CoA and acetaldehyde as intermediates, while some other bacteria convert pyruvate to ethanol with only two key steps [44]. Among the components of food waste, oils and fats have a higher potential for gas production. Hydrogen is a by-product during the hydrolysis/acidification of organic compounds, involved in many major biochemical reactions. During anaerobic acid production, H₂ accumulates at the top of the reactor, inhibiting further acid degradation and releasing H₂ by directly inhibiting the hydrogenase reaction [45].

Furthermore, due to the lack of unified standards in acidification research, it is difficult to compare the conversion rates of fermentation products, energy recovery rates, and other results. Therefore, similar anaerobic acid production tests should be encouraged and promoted to follow standardization, similar to biochemical methane potential testing [46,47], as well as to conduct exergy-based analyses [48,49].

5. Conclusions and Prospects

In this work, general performance of food waste digestion in terms of pH, COD, H₂ production, VFAs distribution and concentration, and acidogenic metabolic pathways were analyzed. Lipids hindered the hydrolysis and acidification of food waste and caused a shift in metabolic pathways. There was a shift in the metabolic pathway from the lactic acid type to the ethanol, acetic acid, and butyric acid types. The level of interference differed among different types of lipids. Beef tallow, mutton fat, soybean oil, and peanut oil delayed the metabolic process by 1, 2, 3, and 8 d, respectively, whereas rapeseed oil accelerated it by 2 d. Although the metabolic pathways were similar among food wastes, the progress of metabolic processes were significantly affected by the types of lipids. Therefore, lipid content and type should be paid attention to when using anaerobic conversion of food waste. Different regions have distinct culinary traditions, which affect the primary dietary oils and fats employed. As a result, the influence of these oils and fats on anaerobic digestion processes for local food waste is frequently disregarded. By prioritizing the effects of disparate oils and fats on anaerobic fermentation processes, we can facilitate the establishment of anaerobic digestion protocols for local food waste to each region. Furthermore, despite the considerable attention afforded to acidification research, the applied methodologies and conditions are variable and inconsistent, which impedes from comparing and analyzing the results of different studies. Therefore, it is imperative to standardize the biochemical acidification testing, akin to the existing standardization for biochemical methane potential test.