Biorefinery for a circular carbon paradigm: process benefits to the use of dryland CAM crops for anaerobic volatile fatty acid production

Background

Anaerobic digestion (AD) or acidogenic fermentation (AF) of biomass can generate either biogas fuel or C₂ ‒ C₈ volatile fatty acids (VFAs) as feedstocks for synthesis of other petrochemical products. Typical AD feedstocks require large amounts of land that could otherwise be used for food production. Unlike these traditional bioenergy crops, plants using the crassulacean acid metabolism pathway (CAM), such as cacti and succulents, may be cultivated on degraded or semi-arid land that cannot support conventional agriculture. This could allow significant biorefinery feedstock to be sourced with minimal impact on existing agriculture or biodiversity. Several economically important CAM crops (e.g. pineapple, agave, prickly pear) are cultivated globally, with waste biomass that could be valorised as a biorefinery feedstock.

Results

Here, we investigate the fermentation kinetics of this novel feedstock class (CAM plants) against traditional bioenergy crops with two contrasting inocula: AD sludge and rumen fluid. Fermentations were performed under the influence of a methanogenesis inhibitor (bromoethane sulfonate) to isolate the acidogenic fermentation processes. CAM and non-CAM substrates in this study demonstrated distinct degradation kinetics (yields and degradation rates). We demonstrate that regardless of the inoculum type, CAM crops show higher hydrolysis rates for VFA production. Moreover, yields of VFAs from three CAM crops (0.41 ± 0.01 – 0.48 ± 0.02 g/g_vs) were higher than for the three non-CAM crops (0.21 ± 0.01 – 0.38 ± 0.01 g/g_vs) when AD sludge was used as the inoculum. This superior performance appeared to correlate with a higher abundance of soluble material and lower structural carbohydrate content in CAM biomass.

Conclusions

At industrial scale, the observed kinetic advantages of VFA production from CAM-plant feedstocks could translate into process enhancements that would greatly improve the cost-competitiveness of anaerobic biorefinery. Assuming comparable biomass productivities of CAM and non-CAM crops, this high yield could allow higher VFA production per unit of cultivated land, improving the environmental credentials of CAM biorefinery.

Graphical abstract

Urgent decarbonisation of the energy and petrochemical sectors is required to mitigate the increasingly extreme effects of anthropogenic climate change. While the reliance on crude oil for energy and transportation is predicted to stabilise and then decline over the coming decades [1] its exploitation in the petrochemical sector looks set to buck this trend, with robust growth expected to at least 2040 [2]. Full transition to a renewable economy would demand that these petrochemical needs also be met with carbon from other sources. The current low cost of crude oil, and its established place in industrial chemistry, renders this sector relatively resistant to decarbonisation. Acidogenic fermentation (AF), a variant form of anaerobic digestion (AD), is one means by which part of this demand may be met sustainably. AF is the controlled anaerobic fermentation of biomass to produce a suite of volatile fatty acids (VFA) from which high-value products including chemicals and plastics can be synthesised. In 2023, the global annual market annual total for VFAs (acetic, propionic, butyric, and valeric acids), was estimated to be over $41 billion (USD) [3]. Currently, 90% of the market demand for VFA is met through petrochemical synthesis, with the remainder produced via biological methods [4]. Increased deployment of AF offers an opportunity to directly substitute this existing source of petrochemical demand. Moreover, VFA can be used as a feedstock for synthesis of multiple other products currently produced via petrochemical routes, including polyhydroxyalkanoate bioplastics (PHAs), food additives, and pharmaceuticals [5]. The availability of a price-competitive source of renewable VFA is a major factor in determining whether these alternative synthesis methods might be a viable alternative to petrochemical synthesis of these products.

The availability of adequate input feedstock is a major constraint to AF, along with other biomass-dependent processes, as any large-scale cultivation of biomass crops would typically compete for arable land currently dedicated to food production [6, 7]. Currently, ~ 40% of global land area is characterised as drylands [8]. This figure looks likely to increase due to changing climate and land degradation, leading to uncertainty for future crop production [9].

Much like traditional C₃ and C₄ agricultural crops, plants that utilise the crassulacean acid metabolism (CAM) pathway for carbon fixation may also be used as a bioenergy crop for AD. Because CAM plants can conduct most of their gas exchange with the atmosphere at night, rather than during the daytime, and can store large amounts of water in their succulent tissues, they show a higher efficiency of water-use and greater resilience to drought than C₃ or C₄ plants [10]. Thus, unlike traditional crops, CAM species can survive on marginal, degraded, and semi-arid land that cannot be reliably used for food production [7, 11]. CAM plants require as little as ~ 20% of the water needed to cultivate C₃ and C₄ crops [10], while still yielding comparable biomass [7, 12], suggesting that CAM-based biorefinery might impose lower societal and environmental externalities such as water stress, food cost inflation, and deforestation than a paradigm based on conventional C₃ and C₄ crops.

CAM plants also offer process-level benefits. The rate-limiting step in AD and AF is often hydrolysis, and the lignin content of plant biomass can impede hydrolysis through occlusion of digestible carbohydrates (cellulose and hemicellulose) and by adsorption of hydrolytic enzymes [13, 14]. Many CAM species are notable for their low lignin content: ~ 1 to ~ 16% of total solids (TS) for Opuntia ficus-indica, compared with 11–26% for wheat straw (Triticum aestivum; C₃) [15] literature values for maize (Zea mays; C₄) residue lignin vary widely, from as low as 3.4%VS [16], or 3.1 and 8.0%TS for leaves and stalks [17], to as high as 21.7%TS for maize stalk [18]. CAM biomass has been demonstrated as a suitable substrate for biomethane production via AD [19, 20], with yields comparable to widely used feedstocks such as Miscanthus spp.[21], and agricultural residues such as maize stover and wheat straw [22, 23], though its application to VFA production has been less extensively investigated.

To characterise their potential for anaerobic VFA production, three globally economically important CAM species were included in this study: Ananas comosus (hereafter referred to as pineapple), Opuntia ficus-indica (Opuntia), and Agave angustifolia (Agave). A total of 29.6 million tons of pineapples—one of the most important fruit plants cultivated in the tropics and subtropics after banana—were harvested globally in 2023 in over 90 countries worldwide [24]. Annual production of pineapple fruit and associated leaf-waste in Thailand, for example, is estimated to be 1.7 million tonnes and 2.7 million tonnes, respectively, a ratio of leaves to fruit of ~ 1.6, suggesting pineapple residues could represent a significant opportunity if properly valorised [25].

Opuntia produces edible fruits and cladodes, and although less widely cultivated than pineapple is nonetheless an important crop in its native Mexico, as well as in Mediterranean regions of Africa and Europe [26]. Opuntia is one of the most widely investigated CAM crops for biorefinery and biogas production [19, 27,28,29,30]. As for other CAM plants, its water-use efficiency (WUE) is greater than that of C₃ and C₄ plants [12, 31], and its low percentage of lignocellulosic material as a proportion of total biomass [27, 32, 33] makes it a favourable candidate feedstock.

Various Agaves are cultivated for production of beverages and fibre. Agave angustifolia is grown to produce mezcal liquor [34] and is the wild progenitor of both the tequila Agave, Agave tequilana [35], and Agave fourcroydes, whose leaves are used to produce henequen fibre for rope, twine and paper [34]. Agave sisalana (a hybrid of A. angustifolia and A. kewensis) is also a major commercial fibre Agave. Agave angustifolia was thus selected as a representative of commercial Agaves used in both fibre and liquor industries.

This study aimed to draw conclusions as to the suitability of CAM feedstocks as AF substrates. Given the hypothesis that any performance advantage of CAM would be due to its lower lignin content, fermentations were performed with two distinct inocula, both with different properties. An industrial standard AD sludge from a commercial digester and a bovine rumen community were selected to compare a standard versus a non-traditional inoculum [20, 36], that could be expected to be more adapted to degradation of lignocellulosic material. The CAM crops (pineapple, Agave and Opuntia) were tested against two widely used C₄ energy crops, maize stover (Zea mays) and Miscanthus sinensis (hereafter Miscanthus), and an agricultural residue, wheat straw (Triticum aestivum), to assess both their initial rates of hydrolysis and their maximum yield of VFA. This study also examined the composition of the microbial communities present in the two inocula to identify key taxa responsible for the various bioconversion steps in the reactor.

This research is timely due to the increased demand for renewable sources of carbon to produce high-value products, and to replace the need for petrochemical synthesis without exacerbating the “food vs. fuel” dilemma. It has the added benefit of offering a path for economic improvement of degraded lands.

Biomass and inoculum

Plants of pineapple (Ananas comosus (L.) Merr.), Agave (Agave angustifolia Haw.), maize (Zea mays L.), and wheat (Triticum aestivum L.) were grown in glasshouses at the Department of Biology, University of Oxford. Plants were cultivated under natural solar irradiation with supplementary heating to maintain minimum temperatures of 10 °C (night) and 25 °C (day). Live, mature cladodes of Opuntia ficus-indica (L.) Mill. were obtained from Pepe Aromas (Azaruja, Portugal). These were subsequently propagated and grown under the same conditions as above; the new, young cladodes produced were harvested at 2 months of age from the same plant as the mature cladode. Agave fibre was extracted through mechanical decortication of Agave leaves, and the resultant pulp was collected and analysed as a distinct feedstock. Mature Miscanthus sinensis was obtained from Jackson’s Nurseries (Stoke-on-Trent, UK).

All harvested plant biomass material was dried in an oven at 80 °C to a constant mass (Table 1). The dry biomass was ground using a blender (Waring Pro^® Stainless Steel Blender, 550 W) and passed through a 1-mm sieve to ensure a consistent particle size prior to fermentation.

Two distinct inocula were used for the experiment (Table 2). AD sludge was obtained from a local biogas facility (Severn Trent Green Power, Cassington, UK) and stored under anaerobic conditions at 30 °C before use. Rumen fluid was collected from a fistulated cow (The Centre for Dairy Research, University of Reading, UK). To properly incorporate large particulates, the rumen fluid was homogenised by blending and passed through a 1-mm sieve before use.

Anaerobic batch assays

The AF experiment was conducted as a batch assay in 125-ml vials with a working volume of 75 mL. The culture medium was prepared according to Angelidaki and Sanders [42], with the exclusion of sodium sulphide. A master-mix of media, deionised water, and inoculum was prepared to a final concentration of 5 g/L inoculum (on a volatile solids (VS) basis). Methanogenesis was inhibited through the addition of bromoethane sulfonate (10 mM) (BES—Sigma-Aldrich, USA). The bulk pH of the media mixture was adjusted to 8.1 ± 0.1 and 75 mL of the master-mix was added to vials containing the dried substrate. The vials were sealed with rubber septa and aluminium crimp caps and mixed by inversion. The headspace was not purged to remove residual oxygen [43].

The substrate-to-inoculum ratio was set to 1.6:1 (w/w) on a VS-basis. A low substrate-to-inoculum ratio was chosen to ensure that the degradability of the feedstocks would be captured, as too high a ratio (particularly in the rumen inoculated vials) would potentially have led to inhibition by VFA or other compounds [44, 45].

The experiment was performed with each biological substrate in triplicate. A blank control consisting of the inocula and media solution was run in triplicate for each inoculum and was subtracted from treatment conditions to account for any residual volatiles present in the inocula. A positive control with microcrystalline cellulose (Avicel^®, Sigma-Aldrich, USA) was used to monitor inoculum activity. All samples were incubated at 37 °C (mesophilic) under constant agitation at 125 rpm. The experiment was terminated on day 16.

Analytical methods

Determination of total solids (TS) and volatile solids (VS) of biomass material and the inocula was conducted according to standard methodologies [46], though using an oven temperature of 80 °C for total solids determinations. Analysis of lignin, cellulose, and hemicellulose were performed as described previously [47]. At each time point, liquid samples of 600 μL were extracted using a syringe and the pH of the liquid samples measured immediately after sample collection (Thermo Scientific, USA). Samples were frozen at −20 °C ready for VFA, soluble chemical oxygen demand (SCOD), and metagenomic analyses.

For VFA analysis, samples were centrifuged at 15,500 × g for 10 min, and 300 μL of the supernatant was transferred to 1.5-mL GC vials. The supernatant was acidified by 1:1 dilution in 20% (v/v) formic acid. VFA concentrations were measured using a GC device (GC-2010, Shimadzu) with a 30 m × 0.25 mm × 0.25 μm fused-silica column (nitroterephthalic acid-modified polyethylene glycol-phase) (ZB-FFAP) and flame ionisation detector (FID). Injector and detector temperatures were 250 and 350 °C, respectively. The initial oven temperature was set to 100 °C for 2 min, ramped at 8 °C/min to 150 °C, and then held at 150 °C for 2 min. Total VFA (TVFA) was calculated as the sum of acetic, propionic, isobutyric, butyric, isovaleric, valeric, and hexanoic acids, which were quantified against standards.

For determination of initial substrate SCOD, dried substrate samples were resuspended in deionised water and allowed to fully rehydrate; these were then centrifuged at 15,500 × g. The supernatant was then analysed using an LCI400 COD Cuvette Test and DR2800 spectrophotometer (Hach Lange).

Metagenomic analyses

Metagenomic analyses were conducted by an external provider (Genewiz UK Ltd.) according to the following protocol, which has been reproduced with their express permission. DNA was extracted using NucleoMag DNA Microbiome Kit following manufacturer’s instructions (Takara, San Jose, CA, USA). 16S-EZ rDNA next generation sequencing library preparations and Illumina MiSeq sequencing were conducted at Azenta, Inc. (South Plainfield, NJ, USA). Sequencing library was prepared using a MetaVx^™ 16S rDNA Library Preparation kit (Azenta, Inc.). Briefly, the DNA was used to generate amplicons that cover V3 and V4 hypervariable regions of bacteria and archaea16S rDNA. Indexed adapters were added to the ends of the 16S rDNA amplicons by limited cycle PCR. DNA libraries were validated and quantified before loading. The pooled DNA libraries were loaded on an Illumina MiSeq instrument according to manufacturer’s instructions (Illumina, San Diego, CA, USA). The samples were sequenced using a 2 × 250 paired-end (PE) configuration. Image analysis and base calling were conducted by the Illumina Control Software on the Illumina instrument. Raw sequence data (.bcl files) generated from Illumina MiSeq were converted into FASTQ files and de-multiplexed using Illumina’s bcl2fastq 2.17 software.

Statistical analysis and modelling

All experimental data are presented as means ± standard deviation of triplicate biological samples, unless otherwise specified. Errors of model parameters are given as standard errors. Data were processed in Microsoft Excel and GraphPad Prism 9.5.0 [48]. VFA yield curves were fitted with the following first-order kinetic model, as previously used with VFA and biogas data [23, 49]:

in which Y = VFA yield at time ‘t,’ Y_max = maximum theoretical VFA yield, t = time, and k = first-order rate constant. This model was fitted to the mean VFA yield data for each substrate to determine estimates of the potential maximum yield (Y_max) and specific rate constant (k) for each substrate.

Characterisation of feedstock and inocula for VFA production

The data in Table 1 detail the biomass characteristics of both CAM and non-CAM plants investigated as feedstock in this experiment. Agave fibre, though not used as a feedstock, was also characterised separately to allow direct comparison between the whole Agave leaf and decorticated pulp that results as the waste product of commercial Agave fibre extraction.

The total solids (TS) (%) content of the biomass as a percentage of fresh weight (TS/FW) ranged from 7.7 ± 0.3% (young Opuntia cladode) to 93 ± 4% (wheat straw). Due to their high moisture content, all the CAM feedstocks exhibited a lower proportion of TS than the C₃ and C₄ plants, except for the Agave fibre, which had a TS of 39 ± 0.9%. Both young and old Opuntia cladodes had a TS % of under 10% (7.7 ± 0.3% and 8.5 ± 0.5%, respectively). Agave pulp and whole leaf had a TS% of 11.9 ± 0.3% and 18.9 ± 0.7%, respectively, and pineapple had a TS % of 13.7 ± 0.6%. Maize had the lowest TS % of the non-CAM feedstock, at 29 ± 4%, as compared to Miscanthus (55 ± 4%) and wheat straw (93 ± 4%).

The volatile (degradable) fraction of these biomass solids is indicated in Table 1 by the fraction of volatile to total solids (VS/TS). Maize and Miscanthus showed the highest VS/TS ratios at 94.73 ± 0.07% and 93.56 ± 0.06%, respectively. Whole Agave and pineapple had the highest VS/TS ratios of the CAM feedstocks, at 90.87 ± 0.01% and 89.71 ± 0.05%, respectively, while the decorticated Agave pulp had a higher VS/TS% than wheat straw (88.9 ± 0.4% and 85.45 ± 0.03%, respectively). Both old and young Opuntia had the lowest VS/TS ratios of all the feedstocks, with % VS of 79.7 ± 0.5% and 76.60 ± 0.07%, respectively. The Agave fibre had a higher VS/TS than all the feedstocks, at 98.3 ± 0.1%.

There was a high degree of variability in the structural composition (lignin, cellulose, hemicellulose) of the plant species investigated. Maize had the lowest lignin content at just 3.2% of TS. In contrast, both Miscanthus and wheat straw had a lignin content almost four times that of maize, at 12.22% w/w and 11.60%, respectively. However, maize had the highest cellulose content (28.02%TS) of all the feedstocks investigated, whereas pineapple had the highest lignin content of all the feedstock investigated (15.08%). In contrast to the C₃ and C₄ plants, pineapple had a low cellulose content of 10.13%. Overall, the C₃ and C₄ plants had a higher lignin, cellulose, and hemicellulose content than the CAM plants (except for the lignin content of maize). Agave pulp had a higher lignin content than the whole Agave leaf (9.17% and 7.69%, respectively). Removal of the Agave fibre (consisting of 50.60, 17.40, and 3.10% TS cellulose, hemicellulose, and lignin, respectively) appears to account for the compositional differences seen between whole Agave leaf and the decorticated pulp, the latter of which shows a depletion of cellulose and hemicellulose and slight enrichment of lignin relative to whole leaf. As expected, the old Opuntia cladode had a higher proportion of lignin and cellulose (8.73% and 12.65%, respectively) than the young cladodes (6.57% and 8.63%, respectively).

The initial compositions of the two inocula investigated are given in Table 2. The TS fraction of the AD sludge (6.7 ± 0.4%) was over twice that of rumen fluid (3.0 ± 0.1%), although the proportions of VS to TS for the two were comparable at 62.60 ± 0.02% and 67.4 ± 0.6%, respectively. The AD sludge exhibited an alkaline pH (8.00 ± 0.01) and low total VFA concentration of 0.66 ± 0.4 g/L, consistent with conditions of biogas production. Rumen fluid had a lower pH (6.3 ± 0.3) and a higher total VFA concentration of 11.0 ± 0.2 g/L VFA. Rumen fluid was particularly rich in acetic (5.22 ± 0.0 g/L), propionic (3.17 ± 0.07 g/L), and butyric acids (1.65 ± 0.03 g/L). In the AD sludge, C₄–C₆ acids were not detected by gas chromatography flame ionisation detection (GC-FID) analysis.

Metagenomic characterisation of the two anaerobic inocula revealed notable differences between their respective microbial communities. Clostridium was the most abundant genus in sludge and Prevotella the most abundant in rumen, while each only represented a small fraction of the other community. Table 2 provides an approximate assignment of function to these genera based on previous literature. Key AF functions of hydrolysis and fermentation (acidogenesis) are performed by distinct communities in the two inocula. Clostridia and Prevotella represent the most abundant hydrolytic and fermentative communities identified in sludge and rumen, respectively.

VFA yield comparison of two inocula with novel feedstocks

The results of the time series of VFA accumulation from acidogenic fermentation are shown in Fig. 1. Panels A–H represent the VFA yield of each CAM and non-CAM feedstock with the two different inocula, and their associated pH values over the study time course. CAM feedstocks (Fig. 1A–E) exhibited more logarithmic VFA production, with maximal rates of production near time zero. Non-CAM feedstocks, particularly Miscanthus and wheat (Fig. 1F, H), showed an initial lag phase followed by rapid acidification before plateauing. Maize (Fig. 1G) showed logarithmic VFA production with AD sludge but exhibited a lag phase with rumen fluid.

Total VFA yield and pH time-courses for CAM and non-CAM feedstocks with AD sludge. Feedstocks shown are A young Opuntia; B old Opuntia; C pineapple; D whole Agave; E decorticated Agave pulp; F Miscanthus; G maize stover; and H wheat straw. Yields are given on a VS basis (g/g_vs), VFA and pH data are presented as means ± standard deviation of triplicate fermentations

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All CAM feedstocks (Fig. 1A–E) and maize (Fig. 1G) exhibited higher VFA production with AD sludge than with rumen fluid. Acidification curves for Miscanthus (Fig. 1F) and wheat (Fig. 1H) were comparable in both inocula.

Despite yielding less VFA from the feedstocks, rumen-driven conditions demonstrated a greater drop in pH. The VFA data in Fig. 1 are shown as net of the underlying inoculum. Undiluted rumen fluid contained 11.0 ± 0.1 g/L VFA as compared to just 0.66 ± 0.04 g/L VFA in AD sludge (Table 2). While all conditions were started at an initial pH of 8.1, the progression of pH seen in Fig. 1 is a product of both VFA production from biomass, as seen in Fig. 1 yield curves, and the underlying behaviours of these distinct inocula.

First-order models (Fig. 2) fitted to the VFA yield data from Fig. 1 further emphasised the above observations. First-order models of best fit broadly converged to higher maxima for AD sludge (Fig. 2A) than for rumen fluid (Fig. 2B), indicating maximal theoretical yields were higher with AD sludge. CAM and non-CAM feedstocks also clustered into distinct groupings, with CAM feedstocks converging to higher yield maxima than non-CAM, especially with AD sludge inoculum. CAM feedstocks showed a more biphasic VFA production, with a rapid initial phase followed by a plateau, while non-CAM exhibited a gradual convergence to maximum yield.

First-order models of VFA yield data shown in Fig. 1. VFA yield (g/g_vs) curves produced with AD sludge are given in panel A and with rumen fluid in panel B

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Relationship between substrate solubility and acidification rate

The first-order rate constant ‘k’, derived from the first-order models in Fig. 2, provides a measure of the rate of acidification of each substrate (Table 3). It was hypothesised that the highest rates would be observed in feedstocks containing larger amounts of soluble organic matter, which would hydrolyse rapidly. Soluble chemical oxygen demand (SCOD) at time-point zero provided an experimental proxy for substrate solubility. First-order rate constants (Fig. 3A) for each feedstock were found to demonstrate a linear trend (Fig. 3C) when regressed against SCOD (Fig. 3B). With both AD sludge and rumen fluid, linear regression of k against SCOD revealed a positive relationship. R² values of 0.6077 and 0.5177 for AD sludge and rumen fluid, respectively, indicated that about half of the observed variability in k values could be explained by the feedstock’s SCOD content. As CAM feedstocks demonstrated higher SCOD (p < 0.01, by Mann–Whitney test) (Fig. 3B), this solubility argument partially accounts for the higher ‘k’ values seen in CAM-fed fermentations (Fig. 3A).

Comparison of the first-order rate constants of acidification and substrate soluble organics. A First-order rate constants (‘k’) for each substrate with AD sludge and rumen fluid, B soluble chemical oxygen demand (SCOD) of each substrate at time zero (g/L). C Regression rate constant ‘k’(d⁻¹) against SCOD g/L. First-order rate constants in panel A are determined from models of best fit and are shown with their associated standard errors. SCOD data in panel B are shown as means ± standard deviation of triplicate measurements

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Relationship between substrate structural characteristics and total VFA yield

Theoretical maximum yields (Y_max), as calculated from the first-order models, varied between feedstocks and inoculum sources (Fig. 4A, Table 3). With AD sludge, Y_max was highest for Agave pulp (0.48 ± 0.02 g_VFA/g_vs) and lowest for Miscanthus (0.21 ± 0.01 g_VFA/g_vs). Highest and lowest yields for rumen fluid were observed in young Opuntia biomass (0.33 ± 0.02 g_VFA/g_vs) and Miscanthus (0.24 ± 0.07 g_VFA/g_vs), respectively.

Linear least squares regression of VFA yields (from first-order models) against key substrate characteristics. A Theoretical maximum yield (Y_max) of VFA yields (g/g/_vs) ± standard errors. CAM biomass: white = sludge, grey = rumen; non-CAM: light red = sludge, dark red = rumen. B Regression of VFA yield (g/g_vs) vs lignin (%VS), C VFA yield (g/g_vs) vs. cellulose (%VS), D VFA yield (g/g_vs) vs. neutral-detergent fibre (%VS), E VFA yield (g/g_vs) vs. soluble chemical oxygen demand (SCOD, g/L) yield. R² of regression given in each panel

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To place these yield figures within a broader context, VFA yields reported for various lignocellulosic biomass sources, of both CAM and non-CAM origin are given in Table 4. Yields are quoted in the units provided by each study, with a range of values identified.

While VFA yields tended to be higher from AD sludge than those of rumen fluid, VFA yields from wheat and Miscanthus were comparable with both inocula. It was originally hypothesised that the overall degradability of the biomass, and therefore VFA yields, would be determined by lignin content of the biomass. However, linear regressions of Y_max against lignin (%VS) did not find a strong relationship between these variables (Fig. 4B) (model R² values for rumen and sludge were 0.0483 and 0.0410). A stronger trend was also found for regression of Y_max against cellulose content, especially in the samples with AD sludge (model R² = 0.4514) (Fig. 4C).

Single linear regressions of AD sludge Y_max values against neutral-detergent fibre (NDF) (i.e. the sum of cellulose, hemicellulose, and lignin in sample biomass) and SCOD accounted for much of the variability in feedstock yields with AD sludge (with R² of 0.8074 and 0.6280, and p-values of p = 0.0024 and p = 0.0190, respectively), although no significant relationship was found between NDF and rumen fluid yields. This suggests that the greater the ‘structural’ content of the biomass (here the NDF) the lower its degradability by AD sludge. The relative overperformance of CAM feedstocks thus appears to be because of their low structural content, rather than from the increased degradability of these structural components due to lower lignin content.

Multiple linear regression of sludge Y_max against both NDF and SCOD produced no appreciable increase in model R², suggesting no improvement in the explanatory power of the model from inclusion of both variables. This suggests that the two variables (NDF and SCOD) are not independent. This can be explained by considering that SCOD measures soluble material, which will derive from the non-structural components of the biomass: it is thus strongly, but inversely, correlated with structural components, and thereby acts as a negative proxy of NDF, leading to the result observed in Fig. 4E.

Characterisation of VFA yield

From a VFA yield perspective, CAM crops clearly outperform non-CAM feedstocks. Yields are also higher when AD sludge provides the inoculum community. When rumen fluid provides the inoculum, the results show the same trend, but not to the same extent [55, 56].

With AD sludge, CAM feedstocks showed a clear advantage over non-CAM feedstocks. Lueangwattanapong et al. [20] made a similar comparison between CAM crops and maize as feedstocks for biomethane production by AD, but did not find CAM crops to have a higher biomethane potential than maize. Comparison of these yield values to those in the literature is complicated by the limited availability of data collected under comparable experimental conditions. Despite this, some trends seem apparent from the literature values in Table 4, with broadly lower VFA yield values seen in fibrous feedstocks such as Agave bagasse (0.1 g/g_TS) [53], and higher yield values from less fibrous feedstocks such as potato peel (0.6g_COD/g_vs) [50]. VFA yields in this study fall within this range. VFA yields reported by Álvaro et al. [54] for cereal straw (in the range of 29.7–44.3%), appear largely consistent with this study (Table 3); however, unlike the present study, Álvaro et al. [54] did not inhibit methanogenesis, which may have increased VFA yields further.

Hydrolysis rates are faster when CAM biomass is used as a substrate

Apart from Agave pulp and old Opuntia cladodes (Fig. 2, Table 3), the first-order rate constant ‘k’ was higher for CAM crop hydrolysis in the AD sludge than for the rumen inoculum. They were also higher for CAM feedstocks than for non-CAM, in both inocula. Hydrolysis rates are typically determined by the structural complexity and insolubility of the feedstock; this is the rationale behind substrate pre-treatment techniques, which aim to address this process bottleneck by increasing substrate solubility and thereby accessibility to hydrolytic enzymes. It has been demonstrated [57] that ultrasound pre-treatment of algal biomass led to an increase in SCOD, which improved both yields and hydrolysis rates during fermentation. This potential relationship was explored in Fig. 3C, which showed that approximately half of the observed variability in fermentation rates could be accounted for by differences in SCOD.

In CAM plants, due to their high water content and slow lignin accumulation due to delayed secondary thickening, structural support is provided by turgor pressure and the reduced surface area: volume ratio of their shoots, and the quantity of structural carbohydrate is relatively low (Table 1). A greater amount of the biomass volatiles could therefore be expected to be present as soluble sugars and organic acids, which are readily hydrolysed [28, 58]. Consistent with this expectation, CAM feedstocks broadly exhibited higher amounts of SCOD at t = 0 than did non-CAM feedstocks (Fig. 3B).

While initial hydrolysis rates were lower when non-CAM biomass was used as a feedstock, hydrolysis rates in AD sludge were still broadly faster than those in rumen fluid (Figs. 2, 3A) Interestingly, in two studies in which sludge and rumen fluid inocula were compared, both of which found higher product yields with sludge, the authors diverged on the question of reaction rate. Lueangwattanapong et al. [20] found AD sludge to have a higher gas production rate than rumen fluid, whilst Yue et al. [55] reported faster production with rumen fluid. It is important to note, however, that both studies were investigating biogas production, and therefore the experiments were run for longer, in the absence of a methanogen inhibitor, and kinetics were determined via modelling of biomethane potential rather than VFA accumulation.

For both inocula, first-order rate constants were higher for CAM than non-CAM feedstocks. On an industrial scale, a shorter hydraulic retention time (HRT) allows a smaller reactor footprint and construction cost, improving reactor economics. While for rumen fluid the yields for CAM and non-CAM feedstocks were similar, the rates at which they converged to these maxima were different, indicating that even under a rumen fluid-driven system, CAM biomass can offer considerable benefit.

Yield performance of non-CAM crops is inhibited by high neutral detergent fibre (NDF)

It has been argued that the low lignin content of CAM biomass renders it more readily degradable and therefore more amenable as a feedstock for biorefinery [7]. This was one initial hypothesis of this study. While our data support this argument for the superiority of CAM biomass as biorefinery feedstocks over the conventional non-CAM feedstocks tested, our results could not attribute this performance advantage to lignin alone. Regression of VFA yields against key substrate parameters detected no significant relationship between lignin content and VFA yield. In fact, as the regressions in Fig. 4 show, the superior performance of CAM feedstocks, when inoculated with AD sludge, could be best explained by variation in NDF content. While pineapple had a high lignin content, it also had a very low content of structural carbohydrates (cellulose and hemicellulose) and therefore a lower NDF. Thus, in the present study, NDF appears to have been a better predictor than lignin of the overall degradability of a substrate. When considering that the most common application of the NDF measure is in the analysis of the energy density of agricultural feed, a higher NDF will typically correlate negatively with feed digestibility and energy density [58].

In comparison, the non-CAM biomass had an overall higher NDF content, leading to an underperformance when fermented with AD sludge. However, maize performed better, possibly due to its low lignin content, or higher SCOD content [17, 59].

The relationships between yield and NDF seen in AD sludge were not evident when rumen fluid was used as the inoculum (Fig. 4D). As the rumen is one of the few animal digestive organs capable of digesting structural carbohydrate, it would follow that its microbiome would be well adapted to NDF digestion. While AD sludge broadly outperformed rumen fluid in this study, for the two feedstocks with the highest NDF percentages, wheat and Miscanthus, the performance of the two inocula converged (Figs. 1F, H and 4D).

Implications for biorefinery

The results demonstrate that VFA production under the conditions tested was faster from CAM biomass than from non-CAM biomass. This is significant since it potentially enables CAM-fed reactors to be run at shorter hydraulic retention times (HRT) for equivalent yields. Smaller CAM-fed reactors could thus digest the biomass and produce the equivalent VFA of a larger non-CAM reactor. Similar VFA productivities could be achieved for a smaller initial capital outlay, improving the cost-competitiveness of ‘green’ VFA as alternatives to fossil fuels. The greater yields seen with AD sludge also translate to greater productivity of desired end products for a given quantity of organic substrate. This comes with the caveat that CAM biomass did show a higher inorganic content than non-CAM biomass (as seen by the lower VS/TS values in Table 1), suggesting this observed yield outperformance would be slightly less pronounced on a TS basis. Further work should also be conducted on these yields at industrial scale, in continuous digestion modes, and in cofermentation with other feedstocks. Literature on the acidogenic cofermentation of CAM biomass remains very limited [43].

The global market for petrochemicals stands at US$ 585 billion [60], while global markets for renewable chemicals currently remain in the tens of billions [61]. The global pineapple market alone, including fresh and processed fruit, exceeds US$10 billion, generated from an annual global harvest of 29.6 million tonnes of fruit [24]. Assuming the ratio of 1.6 for leaf to fruit biomass calculated earlier, this suggests a possible resource of ~ 47 million tonnes of leaf residue available annually for potential biorefinery application. Applying the biomass composition (13.7% TS, 89.71% VS/TS) and yields (0.43 g_VFA/g_VS) calculated herein, this could represent a source of an additional 2.5 million tonnes of renewable VFA production annually from CAM plants before any additional cultivation and subsequent inputs were required [62]. At a conservative VFA price of $400 per tonne, estimated from historical market prices for acetic acid given by Morales-Vera et al. [63], this waste biomass source alone could represent US$1 billion in annual renewable petrochemicals.

While this would represent a considerable increase in existing biorefinery activity, if the sector is to reach a scale commensurate with the market demand it seeks to meet, a shift is required. Second-generation energy crops such as Miscanthus and switchgrass [64] may be used to supplement seasonal variability, but these compete directly for finite arable land. In contrast, the dedicated, widespread cultivation of stress-tolerant CAM plants on marginal lands not being used for stable food production could facilitate this transition to large-scale biorefinery. Furthermore, life-cycle analysis has shown that cultivation of such plants is at least competitive with, and may even be superior to, the most efficient C₃ and C₄ crops in terms of greenhouse gas emissions [65], and CAM plants can show high productivities when grown at scale with suitable management practices [66].

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Author notes

1. Nichola Austen

   Present address: Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, West Gregory Drive, Urbana, IL, 61801, USA

2. Laura K. Martin

   Present address: Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, CB2 1GA, UK

3. Nicholas A. Tenci and Nichola Austen have contributed equally to the study.

Authors and Affiliations

1. Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK

   Nicholas A. Tenci, Nichola Austen, Laura K. Martin & Ian P. Thompson

2. Department of Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK

   Nichola Austen & J. Andrew C. Smith

Contributions

NAT NA IPT & JACS designed the study. NAT & NA conducted the experimental work with assistance from LKM. NAT & NA analysed the data & wrote the first draft of the manuscript. All authors contributed to and edited the final manuscript.

Corresponding author

Correspondence to Ian P. Thompson.

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Competing interests

The authors declare no competing interests.

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