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2024 Volume 4
Article Contents
Abstract
Introduction
Structure and distribution of main bioactive constituents of Lonicera
Biosynthesis and regulation of the main bioactive constituents of Lonicera
Biosynthesis of chlorogenic acids and flavonoids
Biosynthesis of iridoids and triterpene saponins
Metabolic engineering of the main bioactive compounds of the Lonicera genus
Metabolic engineering of chlorogenic acid, luteolin and their glycosides
Metabolic engineering of iridoids and triterpene saponins
Pharmacological activities of the main bioactive compounds of Lonicera
Anti-inflammatory effects
Antimicrobial effects
Anti-oxidative stress effect
Hepatoprotection
Other pharmacological effects
Chloroplast genomic and phylogenetic relationships of Lonicera species
Conclusions and future perspectives
Author contributions
Data availability
Acknowledgments
Conflict of interest
Rights and permissions
References
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ARTICLE   Open Access    

Impact of different nitrogen sources, initial pH and varying inoculum size on the fermentation potential of Saccharomyces cerevisiae on wort obtained from sorghum substrate

  • 1.

    Department of Food Science and Technology, Faculty of Science, Delta State University of Science and Technology, Ozoro, Nigeria

  • 2.

    Department of Chemistry, Faculty of Science, Delta State University of Science and Technology, Ozoro, Nigeria

  • 3.

    Department of Chemistry, College of Sciences, Al-Nahrain University, Baghdad, Iraq

  • 4.

    Department of Pharmacy, Faculty of Pharmacy, Near East University, Nicosia, Cyprus

  • 5.

    Department of Biotechnology, Faculty of Science, Delta State University, Abraka, Nigeria

  • 6.

    Operational Research Centre in Healthcare, Near East University, Nicosia, Cyprus

  • 7.

    Department of Petroleum Chemistry, Faculty of Science, Delta State University of Science and Technology, Ozoro, Nigeria

  • 8.

    Department of Health Informatics, Faculty of Art, Design & Information Technology, George Brown College, Toronto, Canada

  • 9.

    Department of Nursing, Faculty of Health Sciences, Cyprus International University, Nicosia, Turkey

More Information
  • The influence of different nitrogen sources, initial pH, and varied inoculum size on the fermentation capacity of Saccharomyces cerevisiae on sorghum wort substrate was investigated. The parameters analyzed included ethanol concentration, pH, specific gravity, and total soluble sugars after 72 h fermentation period using standard methods such as specific gravity (bottle) method, refractometer method, and pH meter. Four different nitrogen sources which included urea, diammonium phosphate, ammonium sulfate, and ammonium nitrate, were tested individually using two different concentrations of 0.025% w/v, and 0.05% w/v, to study their influence on the fermentation capacity of the yeast strain. The pH and sugars decreased while the alcohol concentration and acidity increased during the fermentation period (p < 0.05). Ammonium sulfate resulted in the highest alcohol and acidity yield (4.47% ± 0.02%, and 3.65% ± 0.03% respectively) at 0.5% w/v after 72 h fermentation period. The yeast strain performed best at an initial pH of 5.5 and gave an optimum alcohol and acidity yield (4.43% ± 0.01%, and 3.88% ± 0.01% respectively) while inoculum size of 1.24 × 108 cells/ml produced the highest alcohol and acidity yield (4.60% ± 0.01%, and 4.18% ± 0.01% respectively) after 72 h. Saccharomyces cerevisiae is a promising candidate for the fermentation of sorghum wort under optimized conditions of nitrogen, initial pH, and yeast cell number.

  • Introduction

    The Lonicera Linn. genus is a constituent member of the Caprifoliaceae family[1]. It is the largest genus in this family and comprises at least 200 species with a notable presence in North Africa, North America, Asia, and Europe[1]. Members of the Lonicera genus possess a wide range of economic benefits from their use as ornamental plants to food and as plants credited with numerous health benefits. Conspicuous among the numerous members of this genus with known medicinal uses are L. japonica, L. macranthoides, L. hypoglauca, L. confusa, and L. fulvotomentosa[2]. Though these species feature prominently in the Chinese Pharmacopoeia, other species such as L. acuminata, L. buchananii, and L. similis are recognized as medicinal resources in certain parts of China[1]. Among the aforementioned species, L. japonica takes precedence over the rest due to its high medicinal and nutritional value[3,4]. For instance, the microRNA MIR2911, an isolate from L. japonica, has been reported to inhibit the replication of viruses[5−7]. Also, the water extract of L. japonica has been used to produce various beverages and health products[8]. The Lonicera genus therefore possesses huge prospects in the pharmaceutical, food, and cosmetic industries as an invaluable raw material[9].

    The main active constituents of the Lonicera genus include organic acids, flavonoids, iridoids, and triterpene saponins. Chlorogenic acids, iridoids, and flavones are mainly credited with the anti-inflammatory, antiviral, anticancer, and antioxidant effects of the various Lonicera species[10−13]. Their hepatoprotective, immune modulatory, anti-tumor and anti-Alzheimer’s effects are for the most part ascribed to the triterpene saponins[14−16]. As stated in the Chinese Pharmacopoeia and backed by the findings of diverse research groups, the plants of the Lonicera genus are known to possess high amounts of organic acids (specifically chlorogenic acid) and pentacyclic triterpenoid saponins[2,17−19]. The flower and flower bud have traditionally served as the main medicinal parts of the Lonicera genus even though there is ample evidence that the leaves possess the same chemical composition[20]. A perusal of the current scientific literature reveals the fact that little attention has been devoted to exploring the biosynthesis of the chemical constituents of the Lonicera genus with the view to finding alternative means of obtaining higher yields. It is therefore imperative that priority is given to the exploration of the biosynthesis of these bioactive compounds as a possible means of resource protection. There is also the need for further research on ways to fully tap the medicinal benefits of other plant parts in the Lonicera genus.

    Here, we provide a comprehensive review of relevant scientific literature covering the structure, pharmacology, multi-omics analyses, phylogenetic analysis, biosynthesis, and metabolic engineering of the main bioactive constituents of the Lonicera genus. Finally, we proffer suggestions on the prospects of fully exploiting and utilizing plants of the Lonicera genus as useful medicinal plant resources.

    Structure and distribution of main bioactive constituents of Lonicera

    A total of at least 400 secondary metabolites have been reported for the Lonicera genus. These metabolites are categorized into four main groups (Fig. 1a), including not less than 50 organic acids, 80 flavonoids, 80 iridoids, and 80 triterpene saponins[21−23]. Organic acids are mainly derivatives of p-hydroxycinnamic acid and quinic acid. Among the organic acids, chlorogenic acids are reported to be the main bioactive compounds in L. japonica[24−26]. The organic acids are most abundant in the leaves, while the least amounts are found in the stem of L. japonica. The flowers of the plant are known to contain moderately high amounts of organic acids[27]. The basic core structure of the flavonoids is 2-phenylchromogen. Luteolin and its glycoside which are characteristic flavonoids of the Lonicera genus are most abundant in L. japonica[28]. On the whole, the flavonoid contents in L. japonica are also highest in the leaves, available in moderate amounts in the flowers, and in lowest amounts in the stem[21]. The core structures of the iridoids are iridoid alcohols, the chemical properties of which are similar to hemiacetal. The iridoids often exist in the form of iridoid glycosides in plants. Secoiridoids glycosides are predominant in the Lonicera genus[25]. In L. japonica, the contents of the iridoids are most abundant in the flowers, moderate in leaves, and lowest in the stem[21]. The characteristic saponins of the Lonicera genus are mainly pentacyclic triterpenoids, including the hederin-, oleanane-, lupane-, ursulane- and fernane-types, etc[22]. The hederin-type saponins are reported in the highest amounts in L. macranthoides[17] (Fig. 1b).

    Figure 1.  Core structures of main secondary metabolites and their distribution in five species of Lonicera. (a) 1 and 2, the main core structures of organic acids; 3, the main core structures of flavonoids; 4, the main core structures of iridoids; 5, the main core structures of triterpene saponins. (b) Comparison of dry weight of four kinds of substances in five species of Lonicera[17,28].
    DownLoad: Full-Size Img PowerPoint

    Biosynthesis and regulation of the main bioactive constituents of Lonicera

    Biosynthesis of chlorogenic acids and flavonoids

    The similarities between chlorogenic acid (CGA) and flavonoids can be traced back to their biosynthesis since p-coumaroyl CoA serves as the common precursor for these compounds[29]. p-coumaroyl CoA is obtained through sequential catalysis of phenylalanine and its biosynthetic intermediates by phenylalanine-ammonia-lyase (PAL), cinnamate 4-hydroxylase (C4H) and 4-coumarate CoA ligase (4CL)[30−33].

    CGA is a phenolic acid composed of caffeic acid and quinic acid and is the most important bioactive compound among the organic acids. Its biosynthesis has been relatively well-established; three main biosynthetic routes have been propounded (Fig. 2a). One route relates to the catalysis of caffeoyl-CoA and quinic acid by hydroxycinnamoyl-CoA quinate transferase (HQT)/hydroxycinnamoyl CoA shikimate/quinate hydroxycinnamoyl transferase (HCT) to produce CGA[34−37]. The HQT-mediated pathway has been deemed the major route for CGA synthesis in in different plant species[38,39]. The second biosynthetic route stems from the biosynthesis of p-coumaroyl quinate through the catalytic effect of HCT/HQT and subsequent hydroxylation of p-coumaroyl quinate under the catalysis of p-coumarate 3'-hydroxylase (C3’H)[34,36,37]. For the third route, caffeoyl glucoside serves as the intermediate to form CGA, a process that is catalyzed by hydroxycinnamyl D-glucose: quinic acid hydroxycinnamyl transferase (HCGQT)[40,41].

    Figure 2.  Biosynthetic pathways of main bioactive constituents of Lonicera. (a) Biosynthetic pathways of chlorogenic acid. (b) Biosynthetic pathways of luteoloside. (c) Biosynthetic pathways of secologanin. (d) Biosynthetic pathways of hederin-type triterpene saponins. PAL, phenylalanine ammonia-lyase; C4H, cinnamate 4-hydroxylase; 4CL, 4-hydroxycinnamoyl CoA ligase; HCT, hydroxycinnamoyl CoA shikimate/quinate hydroxycinnamoyl transferase; C3’H, p-coumaroyl 3-hydroxylase; HQT, hydroxycinnamoyl-CoA quinate transferase; UGCT, UDP glucose: cinnamate glucosyl transferase; CGH, p-coumaroyl-D-glucose hydroxylase; HCGQT, hydroxycinnamoyl D-glucose: quinate hydroxycinnamoyl transferase; CHS, Chalcone synthase; CHI, Chalcone isomerase; FNS, Flavone synthase; F3H, flavonoid 30-monooxygenase/flavonoid 30-hydroxylase; UF7GT, flavone 7-O-β-glucosyltransferase; GPS, Geranyl pyrophosphatase; GES, geraniol synthase; G8O, geraniol 10-hydroxylase/8-oxidase; 8HO, 8-hydroxygeraniol oxidoreductase; IS, iridoid synthase; IO, iridoid oxidase; 7DLGT, 7-deoxyloganetic acid glucosyltransferase; 7DLH, 7-deoxyloganic acid hydroxylase; LAMT, loganic acid O-methyltransferase; SLS, secologanin synthase; FPS, farnesyl pyrophosphate synthase; SS, squalene synthase; SE, squalene epoxidase; β-AS, β-amyrin synthase; OAS, oleanolic acid synthetase.
    DownLoad: Full-Size Img PowerPoint

    The key enzymes in the biosynthesis of p-coumaroyl CoA, and invariably CGA, thus, PAL, C4H, and 4CL have been established in diverse studies such as enzyme gene overexpression/knockdown[42], enzyme activity analysis[33] and transcriptomics[18]. However, the centrality of HQT in the biosynthesis of CGA remains disputable. While some studies have reported a strong correlation between HQT expression level with CGA content and distribution[18,35,39,43,44], others found no such link[45], bringing into question the role of HQT as a key enzyme in CGA biosynthesis.

    Few studies have been conducted on the regulation of CGA biosynthesis in the Lonicera genus. It was found that overexpression of the transcription factor, LmMYB15 in Nicotiana benthamiana can promote CGA accumulation by directly activating 4CL or indirectly binding to MYB3 and MYB4 promoters[46]. LjbZIP8 can specifically bind to PAL2 and act as a transcriptional repressor to reduce PAL2 expression levels and CGA content[47]. Under NaCl stress, increased PAL expression promoted the accumulation of phenolic substances in leaves without oxidative damage, a condition that was conducive to the accumulation of the bioactive compounds in leaves[48].

    Luteolin and its derivative luteolin 7-O- glucoside (luteoloside) are representative flavonoids of the Lonicera genus. Similar to CGA, luteolin is biosynthesized from p-coumaroyl CoA but via a different route. The transition from p-coumaroyl CoA to luteolin is underpinned by sequential catalysis by chalcone synthetase (CHS), chalcone isomerase (CHI), flavonoid synthetase (FNS), and flavonoid 3'-monooxygenase/flavonoid 3'-hydroxylase (F3'H)[45,49,50] (Fig. 2b). Luteoloside is synthesized from luteolin by UDP glucose-flavonoid 7-O-β-glucosyltransferase (UF7GT)[51]. Similar to CGA biosynthesis, the key enzymes of luteolin synthesis include PAL, C4H, and 4CL in addition to FNS[33,45,52]. The content of luteoloside was found to be highly abundant in senescing leaves relative to other tissues such as stem, flowers, and even young leaves[52]. Through transcriptomic analysis, luteoloside biosynthesis-related differentially expressed unigenes (DEGs) such as PAL2, C4H2, flavone 7-O-β-glucosyltransferase (UFGT), 4CL, C4H, chalcone synthase 2 and flavonoid 3'-monooxygenase (F3'H) genes were found to be upregulated in the senescing leaves. Biosynthesis-related transcription factors such as MYB, bHLH, and WD40 were also differentially expressed during leaf senescence[52], while bHLH, ERF, MYB, bZIP, and NAC were differentially expressed during flower growth[53]. Further analysis of the transcription factors revealed that MYB12, MYB44, MYB75, MYB114, MYC12, bHLH113, and TTG1 are crucial in luteoloside biosynthesis[52,53].

    Biosynthesis of iridoids and triterpene saponins

    The biosynthesis of terpenoids mainly involves three stages; formation of intermediates, formation of basic structural skeleton, and modification of basic skeleton[54]. The intermediates of terpenoids are mainly formed through the mevalonate (MVA) and methylerythritol phosphate (MEP) pathways, and eventually converted to the universal isoprenoid precursors, isopentenyl pyrophosphate (IPP) and its isomer dimethylallyl pyrophosphate (DMAPP) through a series of enzyme-catalyzed reactions. Under the catalysis of geranyl pyrophosphatase (GPS), IPP is then converted to geranyl pyrophosphate (GPP). Different terpenoids are subsequently derived from GPP as the intermediate product. For instance, in the formation of secoiridoid, GPP first removes the phosphoric acid group to obtain geraniol, second through a series of reactions such as oxidation and cyclization, the skeleton of iridoid, namely iridodial, can be obtained. Finally, through a series of reactions, the basic carbon skeleton of the secoiridoid, namely secologanin, is obtained[55−61] (Fig. 2c). In the formation of triterpene saponins, the key step lies in the formation of the precursor, 2,3-oxidosqualene, a reaction that is catalyzed by squalene epoxidase (SE). There are many pentacyclic triterpenes in the Lonicera genus, the most important type being the hederin-type saponins with hederagenin as aglycones. Hederin-type saponins are produced after the synthesis of oleanolic acid from β-amyrin and catalyzed by β-starch synthetase (β-AS) and Oleanolic acid synthase (OAS)[62,63]. The skeletal modification of the triterpenoid saponins is mainly achieved via the activities of the CYP450 enzymes and UDP-glycosyltransferase (UGT). Hence, the corresponding aglycones are first obtained via oxidation by the CYP450 enzymes (e.g., CYP72A), and further subjected to glycosylation by the appropriate UGT enzyme[63−65] (Fig. 2d). Skeletal formations of the iridoids and triterpene saponins in general have been well researched, but the same cannot be said about the enzymes involved in biosynthesis of these groups of compounds in the Lonicera genus. To fully utilize the iridoids and triterpene saponins in the Lonicera genus, it is necessary to further explore their biosyntheses with the view to enhancing and optimizing the process.

    Metabolic engineering of the main bioactive compounds of the Lonicera genus

    Given the importance of the bioactive compounds in the Lonicera genus, continual isolation of these compounds using the traditional methods are not only tedious and time-consuming, but also unsustainable. With the development and application of microbial metabolic engineering, different strategies have been introduced to produce these bioactive compounds by heterologous synthesis (Table 1).

    Table 1.  Biosynthesis of Lonicera-specialized metabolites using metabolic engineering.
    Engineering bacteriaOperational methodsProductsYieldRefs
    S. cerevisiaeEliminate the tyrosine-induced feedback inhibition, delete genes involved in competing pathways and overexpress rate-limiting enzymesCaffeic acid569.0 mg/L[69]
    S. cerevisiaeEmploye a heterologous tyrosine ammonia lyase and a 4HPA3H complex composed of HpaB and HpaC derived from different speciesCaffeic acid289.4 mg/L[73]
    S. cerevisiaeSupply and recycle of three cofactors: FADH2, S-adenosyl-L-methion, NADPHCaffeic acid
    Ferulic acid    		Caffeic acid: 5.5 g/L;
    Ferulic acid: 3.8 g/L    		[117]
    E. coliKnocking out competing pathwaysCaffeic acid7,922 mg/L[118]
    E. coliArtificial microbial community, a polyculture of three recombinant Escherichia coli strainsChlorogenic acid250 μM[68]
    Cell-free biosynthesisExtract and purify spy-cyclized enzymes (CFBS-mixture)Chlorogenic acid711.26 mg/L[70]
    S. cerevisiaeThree metabolic engineering modules were systematically optimized: shikimate pathway and carbon distribution, branch pathways, CGA pathway genesChlorogenic acidFlask fermentation: 234.8 mg/L;
    Fed-batch fermentation:
    806.8 mg/L    		[119]
    E. coliUsing modular coculture engineering: construction of the defective strain improves the production and utilization of precursor substancesChlorogenic acid131.31 mg/L[122]
    E. coliIntroduce heterologous UDP-glucose biosynthetic genesLuteolin34 mg/L[120]
    Y. lipolyticaOverexpression of the key genes involved in the mevalonate pathway, the gene encoding cytochrome P450 (CYP716A12) to that encoding NADPH-P450 reductaseOleanolic acid129.9 mg/L[85]
    S. cerevisiaeImprove the pairing efficiency between Cytochrome P450 monooxygenase and reductase and the expression level of key genesOleanolic acid606.9 mg/L[121]
    S. cerevisiaeHeterologous expression and optimization of CrAS, CrAO, and AtCPR1, and regulation of ERG1 and NADPH regeneration systemOleanolic acid433.9 mg/L[123]
     | Show Table
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    Metabolic engineering of chlorogenic acid, luteolin and their glycosides

    Due to the demand for CGA in the food, pharmaceutical, chemical, and cosmetic industries, the traditional means of obtaining the same requires a relatively longer period for plant maturation to obtain low yields of the desired product. This therefore brings into question the sustainability and efficiency of this approach. The alternative and sustainable approach has been to produce CGA using synthetic biology and metabolic engineering.

    Current research has sought to utilize Escherichia coli (and its mutant strain) and Saccharomyces cerevisiae to synthetically generate CGA and other flavonoids[66−73]. For instance, Cha et al. employed two strains of E. coli to produce a relatively good yield of CGA (78 mg/L). Their approach was based on the ability of one strain to generate caffeic acid from glucose and the other strain to use the caffeic acid produced and quinic acid as starting materials to synthesize CGA[66]. Using a bioengineered mutant of E. coli (aroD mutant), Kim et al. increased the yield of CGA to as high as 450 mg/L[67]. Others have sought to increase the yield of CGA by employing a polyculture of three E. coli strains that act as specific modules for the de novo biosynthesis of caffeic acid, quinic acid and CGA. This strategy eliminates the competition posed by the precursor of CGA (i.e., caffeic acid and quinic acid) and generally results in improved production of CGA[68]. Saccharomyces cerevisiae is a chassis widely used for the production of natural substances from plants with an intimal structure that can be used for the expression of cytochrome P450 enzymes that cannot be expressed in E. coli. Researchers have used yeast to increase the production of organic acids[69]. A de novo biosynthetic pathway for the construction of CGA in yeast has been reported new cell-free biosynthetic system based on a mixture of chassis cell extracts and purified Spy cyclized enzymes were adopted by Niu et al. to a produce the highest yield of CGA reported so far up to 711.26 ± 15.63 mg/L[70].

    There are many studies on the metabolic engineering for the synthesis of flavonoids, but few on luteolin and its glycosides. Strains of E. coli have been engineered with specific uridine diphosphate (UDP)-dependent glycosyltransferase (UGT) to synthesize three novel flavonoid glycosides. These glycosides were quercetin 3-O-(N-acetyl) quinovosamine (158.3 mg/L), luteolin 7-O-(N-acetyl) glucosaminuronic acid (172.5 mg/L) and quercetin 3-O-(N-acetyl)-xylosamine (160.8 mg/L)[71]. Since most of the flavonoid glycosides synthesized in E. coli are glucosylated, Kim et al. in their bid to synthesize luteolin-7-O-glucuronide, deleted the araA gene that encodes UDP-4-deoxy-4-formamido-L-arabinose formyltransferase/UDP-glucuronic acid C-4'' decarboxylase in E.coli and were able to obtain a yield of 300 mg/L of the desired product[72].

    Metabolic engineering of iridoids and triterpene saponins

    Terpenoidal saponins are mostly derived from slow-growing plants and usually possess multiple chiral centers[74]. Traditional isolation and even chemical synthesis of the terpenoidal saponins are both tedious and uneconomical for large-scale production. Therefore, it is necessary to find other ways to synthesize these compounds known to have diverse pharmacological functions.

    Heterologous synthesis has become an important way to improve the target products. With the development of synthetic biology, heterologous synthesis of triterpene saponins involves chassis of both plant and microbial origin. In this regard, Nicotiana benthamiana is a model plant species for the reconstruction of the biosynthetic pathways of different bioactive compounds including monoterpenes, hemiterpenes, and diterpenes[59,75−77]. Aside from Nicotiana benthamiana, other plants have also been used as heterologous hosts[78]. Heterologous synthesis using microbial hosts mainly involves Saccharomyces cerevisiae and Escherichia coli[79−81], and other microorganisms[82,83]. Comparatively, plants as biosynthetic hosts have the advantages of an established photosynthetic system, abundant supply of relevant enzymes, and presence of cell compartments, etc. They are however not as fast growing as the microorganisms, and it is also difficult to extract and separate the desired synthesized compounds from them as hosts.

    Although heterologous synthesis has many advantages, the premise of successful construction of synthetic pathway in host is to elucidate the unique structure of the compound and the key enzyme reaction mechanism in the biosynthetic pathway. There is little research on metabolic engineering of the hederin-type pentacyclic triterpene saponins in Lonicera, but there are studies on the heterologous synthesis of its aglycone precursor, oleanolic acid[84,85]. There is a dearth of scientific literature on key enzymes in the biosynthesis of pentacyclic triterpenoid saponins in the Lonicera genus.

    Pharmacological activities of the main bioactive compounds of Lonicera

    Scientific evidence by diverse research groups has linked members of the Lonicera genus to a wide range of pharmacological effects (Fig. 3). These pharmacological effects are elicited by different chemical constituents, much of the underlying mechanisms of which have been elucidated by the omics techniques. Here, we summarize the pharmacological effects and pharmacodynamics of the Lonicera genus in the last 6 years.

    Figure 3.  Schematic summary of four main pharmacological effects (anti-inflammatory, antimicrobial, anti-oxidative and hepatoprotective effects) of the Lonicera genus and the underlying mechanisms of actions.
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    Anti-inflammatory effects

    Bioactive compounds of plants in the Lonicera genus have demonstrated varying degrees of anti-inflammatory actions. In a recent study, Lv et al. showed that lonicerin inhibits the activation of NOD-like receptor thermal protein domain associated protein 3 (NLRP3) through regulating EZH2/AtG5-mediated autophagy in bone marrow-derived macrophages of C57BL/6 mice[86]. The polysaccharide extract of L. japonica reduces atopic dermatitis in mice by promoting Nrf2 activation and NLRP3 degradation through p62[87]. Several products of Lonicera have been reported to have ameliorative effects on DSS-induced colitis. Among them, flavonoids of L. rupicola can improve the ulcerative colitis of C57BL/6 mice by inhibiting PI3K/AKT, and pomace of L. japonica can improve the ulcerative colitis of C57BL/6 mice by improving the intestinal barrier and intestinal flora[88,89]. The flavonoids can also ameliorate ulcerative colitis induced by local enema of 2,4,6-trinitrobenzene sulfonic acid (TNBS) in Wistar rats by inhibiting NF-κB pathway[90]. Ethanol extract from L. Japonica has demonstrated the potential to inhibit the expressions of inflammatory cytokines in serum and macrophages of LPS-induced ICR mice[91]. The water extract of L. japonica and luteolin were found to exhibit their anti-inflammatory effects via the inhibition of the JAK/STAT1/3-dependent NF-κB pathway and induction of HO-1 expression in RAW263.7 cells induced by pseudorabies virus (PRV)[92].

    Antimicrobial effects

    Existing scientific evidence indicates that the extracts of plants in the Lonicera genus exhibit strong inhibition against different pathogenic microorganisms. Phenolic compounds from L. japonica demonstrated a particularly significant inhibitory effect against Staphylococcus aureus and Escherichia coli, in vitro, making these compounds potential food preservatives[93]. Influenza A virus is a serious threat to human health. Recent research has found the ethanol extract of L. japonica to possess a strong inhibitory effect against H1N1 influenza virus-infected MDCK cells and ICR mice[94]. The incidence of the COVID-19 pandemic called to action various scientists in a bid to find safe and efficacious treatment[95]. Traditional Chinese medicines became an attractive alternative in this search. The water extract of the flower bud of L. japonica which has traditionally served as a good antipyretic and antitussive agent attracted the attention of researchers. Scientific evidences have confirmed that the water extract of L. japonica can induce let-7a expression in human rhabdomyosarcoma cells or neuronal cells and blood of lactating mice, inhibiting the entry and replication of the virus in vitro and in vivo[96]. In addition, the water extract of L. japonica also inhibits the fusion of human lung cancer cells Calu-3 expressing ACE2 receptor and BGK-21 cells transfected with SARS-CoV-2 spike protein, and up-regulates the expression of miR-148b and miR-146a[97].

    Anti-oxidative stress effect

    Oxidative stress has been implicated in the pathophysiology of many diseases, hence, amelioration of the same could be a good therapeutic approach[98,99]. In keeping with this therapeutic strategy, various compounds from the Lonicera genus have demonstrated the ability to relieve oxidative stress due to their pronounced antioxidant effects. For instance, the polyphenolic extract of L. caerulea berry was found to activate the expression of AMPK-PGC1α-NRF1-TFAM proteins in the skeletal muscle mitochondria, improve the activity of SOD, CAT and GSH-Px enzymes in blood and skeletal muscle, relieve exercise fatigue in mice by reducing oxidative stress in skeletal muscle, and enhance mitochondrial biosynthesis and cell proliferation[100]. The diverse health benefits of the anthocyanins from L. japonica have been mainly credited to their antioxidant and anti-inflammatory effects. The anthocyanin and cyanidin-3-o-glucoside have been reported to possess the potential to prolong life and delay senescence of Drosophila through the activation of the KEAP1/NRF2 signaling pathway[101].

    Hepatoprotection

    The liver is an essential organ that contributes to food digestion and detoxification of the body. These functions expose the liver to diverse toxins and metabolites. The Lonicera genus is rich in phytochemicals that confer protection on the liver against various toxins. The phenolic compound, 4, 5-di-O-Caffeoylquinic acid methyl ester was shown to be able to improve H2O2-induced liver oxidative damage in HepG2 cells by targeting the Keap1/Nrf2 pathway[102]. Hepatic fibrosis is a complex dynamic process, with the propensity to progress to liver cancer in severe cases. The L. japonicae flos water extract solution increased the cell viability of FL83B cells treated with thioacetamide (TAA), decreased the levels of serum alanine aminotransferase (ALT) and alkaline phosphatase (ALP), inhibited the transformation growth factor β1 (TGF-β1) and liver collagen deposition[103]. Sweroside, a secoiridoid glucoside isolate of L. japonica is known to protect the C57BL/6 mice liver from hepatic fibrosis by up-regulating miR-29a and inhibiting COL1 and TIMP1[104].

    Other pharmacological effects

    Aside from the aforementioned, other pharmacological effects have been ascribed to the Lonicera genus. The ethanolic extract of L. caerulea has been reported to inhibit the proliferation of SMMC-7721 and H22 hepatoma cells, while its anthocyanins induced the apoptosis of tumor cells via the release of cytochrome C and activation of caspase[105]. AMPK/PPARα axes play an important role in lipid metabolism. A chlorogenic acid-rich extract of L. Japonica was found to significantly decrease the early onset of high-fat diet-induced diabetes in Sprague-Dawley rats via the CTRPs-AdipoRs-AMPK/PPARα axes[106]. In a high-fat diet-induced non-alcoholic fatty liver disease in C57BL/6 mice, treatment with L. caerulea polyphenol extract decreased serum inflammatory factors and endotoxin levels and the Firmicutes/Bacteroidetes ratio, an indication of its modulatory effect on the gut microbiota[107]. The iridoid-anthocyanin extract from L. caerulea berry contributed to alleviating the symptoms of intestinal infection with spirochaeta in mice[108].

    Chloroplast genomic and phylogenetic relationships of Lonicera species

    The traditional classification of the Lonicera genus based on the morphology of member plants is further categorized into two subgenera, Chamaecerasus and Periclymenum. The Chamaecerasus includes four categories, Coeloxylosteum, Isika, Isoxylosteum and Nintooa. The Periclymenum includes two categories, Subsect. Lonicera and Subsect. Phenianthi (Supplemental Table S1).

    High-throughput chloroplast genome sequencing of L. japonica found its length to be 155078 bp, which is similar to the structure of the typical angiosperm chloroplast genome. It contains a pair of inverted repeat regions (IRa and IRb, 23774 bp), a large single copy region (LSC, 88858 bp) and a small single copy area (SSC, 18672 bp)[109,110]. However, compared with chloroplast genomes of other plants, the chloroplast genome of L. japonica has a unique rearrangement between trnI-CAU and trnN-GUU[110]. Based on the phylogenetic analysis of the plastid genomes of seven plants in the Lonicera genus, 16 diverging hot spots were identified as potential molecular markers for the development of the Lonicera plants[111]. The phylogeny of Lonicera is rarely researched at the molecular level and the pattern of repetitive variation and adaptive evolution of the genome sequence is still unknown. Chloroplast genome sequences are highly conserved, but insertions and deletions, inversions, substitutions, genome rearrangements, and translocations also occur and have become powerful tools for studying plant phylogeny[112,113].

    We present here the phylogenetic tree of the Lonicera genus based on the published complete chloroplast genome sequences downloaded from the National Center for Biotechnology Information (NCBI) database using the Maximum likelihood method (Fig. 4). Based on our chloroplast phylogenies, we propose to merge L. harae into Sect. Isika and L. insularis into Chamaecerasus, but whether L. insularis belongs to Sect. Isika or Sect. Coeloxylosteum is uncertain. Based on protein-coding regions (CDS) of the chloroplast genome or complete chloroplast genomes, Liu et al. and Chen et al. supported the classification of the two subgenera in Lonicera[111,114]. Sun et al. and Srivastav et al. demonstrated a classification between the two subgenera with more species by using sequences of nuclear loci generated, chloroplast genome, and restriction site-associated DNA sequencing (RADSeq)[115,116]. However, our phylogenetic analysis and that of Sun et al. show relations within the subgenus Chamaecerasus are tanglesome in some respects[116]. Plant traits are affected by the environment to varying degrees. Since evidence of plant speciation is implicit in its genome sequence, comparative analysis at the molecular level provides a relatively accurate depiction of inherent changes that might have occurred over time. These findings suggest the need for more species of the Lonicera genus to be sequenced to provide a more accurate theoretical basis for the evolution of the Lonicera plants and a more effective revision in the classification of the Lonicera genus.

    Figure 4.  Phylogenetic tree of 42 species of the Lonicera genus based on complete chloroplast genome sequence data. The phylogenetic tree was constructed by the maximum likelihood method. Coeloxylosteum, Isika, Isoxylosteum, and Nintooa belong to Chamaecerasus and Subsect. Lonicera belongs to the Periclymenum. Chamaecerasus and Periclymenum are the two subgenera of Lonicera. 'Not retrieved' indicates that the species failed to retrieve a subordinate taxon in the Lonicera.
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    Conclusions and future perspectives

    The Lonicera genus is rich in diverse bioactive compounds with immeasurable prospects in many fields. Members of this genus have been used for thousands of years in traditional Chinese medicine for heat-clearing and detoxification. These plants generally have a good taste and form part of the ingredients of various fruit juices. In cosmetics, they are known to possess anti-aging and moisturizing functions. Plants of the Lonicera genus are also known for their good ecological adaptability and can be used to improve soil and ecological environment. Based on the value of the Lonicera genus, besides researching their use through molecular biological means, their efficient utilization can also be promoted in the following ways: (1) The stems and leaves of the plants could be developed for consumption and use since the chemical profiles of these parts do not differ significantly from the flowers. This way, the wastage of this scarce resource could be minimized or avoided. (2) Most of the Lonicera plants are vines or shrubs and their natural regeneration speed is slow, so the introduction and domestication of species could be strengthened to avoid overexploitation of wild resources.

    At present, only the research on the biosynthesis and efficacy of chlorogenic acid is quite comprehensive and has been used widely in various fields. There is limited research on various aspects of other bioactive compounds and should therefore be given priority in future research goals. Currently, the multi-omics analytical approach has gradually evolved as a reliable and helpful analytical platform. Hence, multi-omics research on the Lonicera genus could lead to discoveries in drug discovery and human health.

    Author contributions

    The authors confirm contribution to the paper as follows: study conception and design, draft manuscript preparation: Yin X, Chen X, Li W, Tran LSP, Lu X; manuscript revision: Yin X, Chen X, Li W, Tran LSP, Lu X, Chen X, Yin X, Alolga RN; data/literature collection: Chen X, Yin X; figure preparation: Chen X, Yin X; figure revision: Alolga RN, Yin X, Chen X, Li W, Tran LSP, Lu X. All authors reviewed the results and approved the final version of the manuscript.

    Data availability

    All data generated or analyzed during this study are included in this published article and its supplementary information file.

    Acknowledgments

    This work was partially supported by the National Natural Science Foundation of China (NSFC, Nos 82173918 and 82373983).

  • The authors declare that they have no conflict of interest. Xiaojian Yin is the Editorial Board member of Medicinal Plant Biology who was blinded from reviewing or making decisions on the manuscript. The article was subject to the journal's standard procedures, with peer-review handled independently of this Editorial Board member and the research groups.

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  • Cite this article

    Akpoghelie PO, Edo GI, Kasar KA, Zainulabdeen K, Yousif E, et al. 2024. Impact of different nitrogen sources, initial pH and varying inoculum size on the fermentation potential of Saccharomyces cerevisiae on wort obtained from sorghum substrate. Food Materials Research 4: e021 doi: 10.48130/fmr-0024-0012
    Akpoghelie PO, Edo GI, Kasar KA, Zainulabdeen K, Yousif E, et al. 2024. Impact of different nitrogen sources, initial pH and varying inoculum size on the fermentation potential of Saccharomyces cerevisiae on wort obtained from sorghum substrate. Food Materials Research 4: e021 doi: 10.48130/fmr-0024-0012
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Impact of different nitrogen sources, initial pH and varying inoculum size on the fermentation potential of Saccharomyces cerevisiae on wort obtained from sorghum substrate

  • 1.

    Department of Food Science and Technology, Faculty of Science, Delta State University of Science and Technology, Ozoro, Nigeria

  • 2.

    Department of Chemistry, Faculty of Science, Delta State University of Science and Technology, Ozoro, Nigeria

  • 3.

    Department of Chemistry, College of Sciences, Al-Nahrain University, Baghdad, Iraq

  • 4.

    Department of Pharmacy, Faculty of Pharmacy, Near East University, Nicosia, Cyprus

  • 5.

    Department of Biotechnology, Faculty of Science, Delta State University, Abraka, Nigeria

  • 6.

    Operational Research Centre in Healthcare, Near East University, Nicosia, Cyprus

  • 7.

    Department of Petroleum Chemistry, Faculty of Science, Delta State University of Science and Technology, Ozoro, Nigeria

  • 8.

    Department of Health Informatics, Faculty of Art, Design & Information Technology, George Brown College, Toronto, Canada

  • 9.

    Department of Nursing, Faculty of Health Sciences, Cyprus International University, Nicosia, Turkey

  • Received: 23 March 2024
  • Revised: 13 May 2024
  • Accepted: 13 June 2024
  • Published online: 12 August 2024
Food Materials Research  4,  Article number: e021  (2024)  |  Cite this article

Abstract: The influence of different nitrogen sources, initial pH, and varied inoculum size on the fermentation capacity of Saccharomyces cerevisiae on sorghum wort substrate was investigated. The parameters analyzed included ethanol concentration, pH, specific gravity, and total soluble sugars after 72 h fermentation period using standard methods such as specific gravity (bottle) method, refractometer method, and pH meter. Four different nitrogen sources which included urea, diammonium phosphate, ammonium sulfate, and ammonium nitrate, were tested individually using two different concentrations of 0.025% w/v, and 0.05% w/v, to study their influence on the fermentation capacity of the yeast strain. The pH and sugars decreased while the alcohol concentration and acidity increased during the fermentation period (p < 0.05). Ammonium sulfate resulted in the highest alcohol and acidity yield (4.47% ± 0.02%, and 3.65% ± 0.03% respectively) at 0.5% w/v after 72 h fermentation period. The yeast strain performed best at an initial pH of 5.5 and gave an optimum alcohol and acidity yield (4.43% ± 0.01%, and 3.88% ± 0.01% respectively) while inoculum size of 1.24 × 108 cells/ml produced the highest alcohol and acidity yield (4.60% ± 0.01%, and 4.18% ± 0.01% respectively) after 72 h. Saccharomyces cerevisiae is a promising candidate for the fermentation of sorghum wort under optimized conditions of nitrogen, initial pH, and yeast cell number.

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    Introduction

    • The nutritional demands of yeasts include sugar sources, assimilable nitrogen, micronutrients, and lipids. All these are necessary for the proper functioning of the yeasts as regards its metabolic activities for the production of alcohol and other metabolites[1]. Nitrogenous compounds are required by yeast cells for their metabolic activities and have a direct correlation with their fermentative capacity especially their rate of ethanol formation from fermentation of sugars[2]. It has been reported that nitrogen either naturally present in the cultivation medium or externally incorporated into the medium has a positive effect on yeast growth and generation of yeast biomass[3]. Yeast cells on their own are capable of synthesizing nitrogenous compounds especially when such essential compounds are lacking in the growth medium[4]. Lack of nitrogen or its inadequacy in the growth medium have been shown to cause sluggish or stuck fermentations and must therefore be put into consideration during the start and course of fermentation processes[5]. Different yeast strains require different nitrogen sources as well as concentration as yeast strains possess specific amino acid profiles[6]. However, several studies seem to suggest that the molecular dynamics controlling the rate of nitrogen metabolism are dominantly preserved in the species Saccharomyces cerevisiae[7]. Some particular isolated strains of Saccharomyces and non-Saccharomyces yeasts have been reported to possess high fermentation capacities[8]. However, the interaction between nitrogenous compounds and beer flavor profiles as well as the fermentation conditions like temperature and pH have been reported to be complicated[9].

      This research aimed to clarify the impact of different nitrogen sources, initial pH and varied inoculum size on the fermentation potential of Saccharomyces cerevisiae B05 on Sorghum wort.

    Materials and methods

      Sample collection

    • The sorghum variety CSR-03H was procured through the collaborative efforts of the National Cereals Research Institute (NCRI), Zaria, Kaduna State, Nigeria and Food and Agro Allied Ltd, Sango-Otta, Ogun State, Nigeria; and transported to the Biotechnology laboratory of the Federal Institute for Industrial Research Oshodi (FIIRO), Lagos State, Nigeria for analysis. Yeast (Saccharomyces cerevisiae Strain B05) and hop extract was supplied by Nigerian Breweries Plc, Iganmu, Lagos State, Nigeria. Also, the reagents and materials used were made available by the Federal Institute for Industrial Research Oshodi (FIIRO), Lagos State, Nigeria, where the research work was carried out.

      Preparation of sorghum for malting

    • The sorghum grains were sorted manually to remove shapeless, broken and immature kernels, dust, stones, and other extraneous materials. Thereafter, the kernels were properly washed in tap water contained in a 40 L bucket. The washed grains were stirred in the water and separated. The separated grains were dried under sunlight and stored in sterile plastic bags.

      Malting and kilning of sorghum seeds

    • Weighed 5 kg of sorghum grains were transferred into a 50 L plastic bucket made up with 40 L of water and steeping was done for 10 h at a temperature of 30 °C. The steeped water was removed and replaced with fresh water every 6 h interval for 48 h. The grains were then blotted with sterile towels to remove surface water and placed on an aluminum tray. The tray was covered with foil papers and germination was allowed for 72 h. During the germination period, the foil papers were partially removed and the kernels were turned periodically at 6 h intervals with their surface sprayed with tap water in the process. Kilning of the resulting seedlings was done in a hot air oven at 60 °C for 48 h. After cooling of the resulting seedlings, rootlets were removed by rubbing vigorously in a sieve of mesh size 1.30 mm[21].

      Milling the malt

    • Dry-milling of 3kg sorghum malt into fine malt flour was done using a Laboratory mill (Quadrumat Jr. Model SM 200 Brabender, Duisburg, Germany).

      Mashing, iodine test, and wort boiling

    • Gelatinization of 200 g of sorghum malt suspended in 400 ml mash liquor was carried out at 80 °C for 20 min. The sample was subjected to a three-mash decoction mashing as described by Endres et al.[10]. The pH of the wort was adjusted to 5.5 before fermentation. The entire process of production of the sorghum wort is shown in Fig. 1.

      Figure 1. 

      Production of sorghum wort.

      Yeast propagation

    • Measured 65 g of Yeast Extract Peptone Dextrose (YEPD) powder was suspended in 1,000 ml of distilled water. The mixture was stirred thoroughly and thereafter boiled for 1 min to dissolve the medium completely. This was sterilized by autoclaving at 15 lbs pressure (121 °C) for 15 min. Culturing and sub-culturing of yeast was done on Yeast Extract Peptone Dextrose (YEPD) medium. The sorghum wort for each experiment was inoculated with 1.24 × 108 CFU/ml of yeast and incubated at 28 ± 2 °C for 72 h[19].

      Effect of different nitrogen sources on fermentation performance of yeast

    • Different nitrogen sources were tested individually to study their effect on the fermentation performance of yeast. The nitrogen sources include urea, diammonium phosphate, ammonium sulfate, and ammonium nitrate. Two different concentrations of 0.025% w/v and 0.05% w/v were used for each nitrogen source in the experimental set-up. A control was set up without any of these nitrogen sources and made up entirely of the substrate. Based on the method of Cadenas et al.[11].

      Effect of varying pH of wort on fermentation performance of yeast

    • Six experimental variables of 50 ml 100% sorghum wort were prepared. Based on the method of Hossain et al.[12], the pH of the portions were adjusted to give pH 4.0, 4.5, 5.0, 5.5, 6.0 and 6.5 respectively using 10% phosphoric acid and 35% calcium hydroxide solution (lime).

      Effect of varying inoculum size on fermentation performance of yeast

    • Six experimental variables of measured 50 ml 100% sorghum wort sample each was used to ascertain the effect of varying inoculum size on the fermentation capacity of the yeast on the wort. Based on the method of Coulibaly et al.[8].

      Parameters analyzed

      pH

    • Measured 10 ml of sorghum wort was transferred into a 100 ml beaker. The pH was determined using a pH meter (Model P 211 Hanna, Salaj, Romania).

      Specific gravity

    • The specific gravities of the sorghum worts were determined using a handheld Stanley and Bellingham refractometer at 28 °C in °Brix. Degrees Brix (°Brix) is a measure of the dissolved solids in the liquid wort.

      Alcohol content

    • The percentage ethanol of the fermented products was determined using the specific gravity (bottle) method[13].

      Total acidity

    • The total acidity was determined using the method of Tsegay[14].

      Total soluble sugar

    • Total soluble sugar was determined using a handheld Bellingham and Stanley refractometer at 28 °C.

      Statistical analysis

    • An average of triplicate readings for each treatment was used for all the determinations. Analysis of variance (ANOVA) was performed using the SPSS statistical package (version 20) to locate significant differences between means of triplicates at p < 0.05.

    Results and discussion

      Effect of different nitrogen sources on S. cerevisiae during beer fermentation

    • The effect of the different nitrogen sources and concentrations on the pH during beer fermentation for 72 h is shown (Table 1). The pH value after 72 h of fermentation decreased (p < 0.05) irrespective of the concentrations and nature of the nitrogen sources even though the values were lower than that of the control and revealed acid values in the range of 3.74 ± 0.01 (for samples containing 0.05% w/v ammonium sulfate) and 3.86 ± 0.01 (for samples containing 0.025% w/v urea). The decrease in the pH and increase in the titratable acidity of the different media from 0 to 72 h fermentation period could be attributed to the degradation of sugars and utilization of the ammonium supplement by the yeast strain to yield organic acids[15]. The medium containing 0.05% w/v ammonium sulfate had the highest fermentation rate compared to other media, as it had the lowest pH after a 72 h fermentation period. Also, significant differences were not observed for the media containing 0.05% w/v ammonium sulfate and 0.025% w/v ammonium sulfate (p < 0.05). This indicates that the yeasts were able to metabolize the inorganic nitrogenous medium containing ammonium sulfate much better than the other nitrogenous media. This also suggests that the amount of ammonium sulfate had minimal effect on the optimal fermentation performance of yeast cells. It has been reported that the use of urea as a nitrogen source could cause an increase in the amount of OH− in the medium which could have been a reason for the higher pH and lower acidity values after 72 h fermentation period obtained in this research work[16].

      Table 1.  Effect of different nitrogen sources on pH of wort during fermentation by S. cerevisiae.

      Nitrogen content (% w/v) Nitrogen source Fermentation period (h)
      0 24 48 72
      0.025 Ammonium nitrate 5.20 ± 0.00 4.86 ± 0.01b 4.29 ± 0.01b 3.85 ± 0.01b
      Ammonium sulfate 5.29 ± 0.00 4.61 ± 0.01a 4.21 ± 0.01a 3.83 ± 0.02b
      Urea 5.39 ± 0.00 4.90 ± 0.01c 4.38 ± 0.01c 3.86 ± 0.01b
      Control 5.90 ± 0.00 5.50 ± 0.01d 4.90 ± 0.01d 4.20 ± 0.01a
      0.05 Ammonium nitrate 5.28 ± 0.00 4.58 ± 0.01c 3.99 ± 0.01b 3.79 ± 0.01
      Ammonium sulfate 5.34 ± 0.00 4.56 ± 0.01c 3.95 ± 0.02c 3.74 ± 0.01
      Urea 5.42 ± 0.00 4.67 ± 0.01b 4.02 ± 0.01b 3.85 ± 0.01
      Control 5.90 ± 0.00 5.50 ± 0.01a 4.90 ± 0.00a 4.20 ± 0.01
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 2 shows the changes in the total soluble sugar values with different nitrogen sources during beer fermentation for 72 h. After 72 h of fermentation, the sample containing 0.025% w/v ammonium nitrate had the highest total soluble sugar of 6.57 ± 0.01 °Brix while the least (4.93 ± 0.02 °Brix) was from the sample containing 0.05% w/v ammonium sulfate. The decrease in total soluble sugars (TSS) and specific gravity (p < 0.05) from 0 to 72 h fermentation period could be due to the consumption of the sugars by yeasts for the formation of ethanol, carbon (IV) oxide, organic acids, and other metabolites[17]. Again, as expected, the medium containing ammonium sulfate having the least TSS value after a 72 h fermentation period gave the best fermentation performance by the yeasts. Once again, it showed that the yeasts were able to metabolize the medium containing ammonium sulfate better than the other nitrogenous sources. Also, significant differences were not observed for media containing 0.05% w/v ammonium sulfate and 0.025% w/v ammonium sulfate (p < 0.05). It showed the concentration of nitrogen had little effect on the decrease in TSS.

      Table 2.  Effect of different nitrogen sources on total soluble sugar ( °Brix) of wort during Fermentation by S. cerevisiae.

      Nitrogen content (% w/v) Nitrogen source Fermentation period (h)
      0 24 48 72
      0.025 Ammonium nitrate 15.80 ± 0.00 12.73 ± 0.01b 9.10 ± 0.02b 6.57 ± 0.01b
      Ammonium sulfate 15.80 ± 0.00 11.50 ± 0.12d 8.40 ± 0.06d 6.10 ± 0.23b
      Urea 15.80 ± 0.00 12.00 ± 0.12c 10.77 ± 0.02c 6.40 ± 0.23b
      Control 15.80 ± 0.00 13.20 ± 0.06a 11.80 ± 0.01a 8.80 ± 0.06a
      0.05 Ammonium nitrate 15.80 ± 0.00 11.90 ± 0.02b 8.73 ± 0.01b 5.77 ± 0.04b
      Ammonium sulfate 15.80 ± 0.00 10.60 ± 0.02c 7.50 ± 0.06c 4.93 ± 0.02b
      Urea 15.80 ± 0.00 11.53 ± 0.22b 8.30 ± 0.06b 5.20 ± 0.06b
      Control 15.80 ± 0.00 13.20 ± 0.01a 11.80 ± 0.06a 8.77 ± 0.04a
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 3 shows the specific gravity values. After 72 h of fermentation, irrespective of concentration, the highest value (1.03 ± 0.00) was from samples containing urea while the least (1.02 ± 0.00) was from samples containing ammonium sulfate and ammonium nitrate. The titratable acidity values are shown in Table 4. After a 72 h fermentation period, the highest value (3.65 ± 0.03) was from samples containing 0.05% w/v ammonium sulfate while the least (3.17 ± 0.02) was from that containing 0.025% w/v urea. Table 5 reveals the values for alcohol content. After a 72 h fermentation period, samples containing 0.05% w/v ammonium sulfate had the highest (4.47% ± 0.02%) while the least (3.77% ± 0.15%) was from sample containing 0.025% w/v urea. Statistical analysis revealed significant differences between the samples for all measured parameters at p < 0.001 confidence level. The rise in the alcohol values from 0 h to 72 h fermentation period showed the activity of the yeast cells in the conversion of the metabolizable sugars in the wort into alcohol. Medium containing ammonium sulfate which gave the highest alcohol concentration after a 72 h fermentation period could be regarded as the media of choice by the yeast strain employed for pitching the wort as they were able to metabolize this nitrogen source better than the others. These lower values for alcohol recorded for the other nitrogen sources could be attributed to the inhibitory effects of the nitrogen sources on the yeast[18]. This also reveals that the amount of ammonium sulfate had minimal effect on ethanol generation by the yeast cells.

      Table 3.  Effect of different nitrogen sources on specific gravity of wort during fermentation by S. cerevisiae.

      Nitrogen content (% w/v) Nitrogen source Fermentation period (h)
      0 24 48 72
      0.025 Ammonium nitrate 1.07 ± 0.00 1.05 ± 0.00b 1.04 ± 0.00b 1.02 ± 0.00c
      Ammonium sulfate 1.07 ± 0.00 1.05 ± 0.00b 1.03 ± 0.00c 1.02 ± 0.00c
      Urea 1.07 ± 0.00 1.05 ± 0.00b 1.04 ± 0.00b 1.03 ± 0.00b
      Control 1.07 ± 0.00 1.06 ± 0.00a 1.05 ± 0.00a 1.04 ± 0.00a
      0.05 Ammonium nitrate 1.07 ± 0.00 1.05 ± 0.00b 1.03 ± 0.00c 1.02 ± 0.00c
      Ammonium sulfate 1.07 ± 0.00 1.04 ± 0.00c 1.03 ± 0.00c 1.02 ± 0.00c
      Urea 1.07 ± 0.00 1.05 ± 0.00b 1.04 ± 0.00b 1.03 ± 0.00b
      Control 1.07 ± 0.00 1.06 ± 0.00a 1.05 ± 0.00a 1.04 ± 0.00a
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 4.  Effect of different nitrogen sources on titratable acidity (%) of wort during fermentation by S. cerevisiae.

      Nitrogen content (% w/v) Nitrogen source Fermentation period (h)
      0 24 48 72
      0.025 Ammonium nitrate 1.45 ± 0.01b 2.27 ± 0.01c 2.83 ± 0.02b 3.26 ± 0.01a
      Ammonium sulfate 1.40 ± 0.00c 2.39 ± 0.01b 2.93 ± 0.02b 3.34 ± 0.02a
      Urea 1.36 ± 0.00d 2.22 ± 0.01d 2.68 ± 0.01c 3.17 ± 0.02b
      Control 1.58 ± 0.00a 2.50 ± 0.01a 3.04 ± 0.02a 3.05 ± 0.03b
      0.05 Ammonium nitrate 1.20 ± 0.00d 2.51 ± 0.01b 3.25 ± 0.03a 3.57 ± 0.01a
      Ammonium sulfate 1.38 ± 0.01b 2.55 ± 0.01a 3.35 ± 0.03a 3.65 ± 0.03a
      Urea 1.34 ± 0.01c 2.42 ± 0.01c 2.97 ± 0.04b 3.17 ± 0.07b
      Control 1.58 ± 0.00a 2.52 ± 0.01b 3.00 ± 0.06b 3.03 ± 0.04c
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 5.  Effect of different nitrogen sources on alcohol content (%) of wort during fermentation by S. cerevisiae.

      Nitrogen content (% w/v) Nitrogen source Fermentation period (h)
      0 24 48 72
      0.025 Ammonium nitrate 0.00 ± 0.00 2.77 ± 0.01a 3.01 ± 0.01b 3.91 ± 0.00b
      Ammonium sulfate 0.00 ± 0.00 2.89 ± 0.01a 3.25 ± 0.03a 4.25 ± 0.03a
      Urea 0.00 ± 0.00 2.73 ± 0.02b 3.10 ± 0.06c 3.77 ± 0.15c
      Control 0.00 ± 0.00 2.48 ± 0.01c 2.82 ± 0.02d 3.43 ± 0.08d
      0.05 Ammonium nitrate 0.00 ± 0.00 2.89 ± 0.01b 3.24 ± 0.02c 4.21 ± 0.01b
      Ammonium sulfate 0.00 ± 0.00 3.05 ± 0.03a 3.55 ± 0.03a 4.47 ± 0.02a
      Urea 0.00 ± 0.00 2.93 ± 0.02b 3.35 ± 0.03b 4.05 ± 0.13c
      Control 0.00 ± 0.00 2.55 ± 0.03c 3.15 ± 0.03c 3.59 ± 0.05c
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Nitrogen is one of the primary nutrients required for yeast growth and optimum ethanol production efficiency[19]. Nitrogen in yeast fermentation plays both anabolic and catabolic roles. The former role involves the biosynthesis of enzymes and nucleic acids, while the latter role involves the development of higher alcohols which serve as flavor congeners[20]. The component of the nitrogenous composition of wort determines yeast growth and fermentation. It is necessary in predicating the quality of beer[21]. Yeasts make use of nitrogen for the production of several metabolites needed for their proliferation and fermentative activities[19]. From the results, it can be observed that the most preferred nitrogen source by the yeast strain is ammonium sulfate. Hence, ammonium sulfate was chosen as the choice nitrogen source in the formulation of the sorghum substrate for beer production.

      The highest ethanol concentration obtained after a 72 h fermentation period using ammonium sulfate is supported by the results of Ferreira & Guido[21]. The use of ammonium sulfate as a nitrogen source has been reported to cause an increase in acidification and could be a part contributor to the higher acidity and lower pH recorded in this research work[23]. The lower values for alcohol recorded when urea and ammonium nitrate were employed as nitrogen sources are contrary to the report of Adejuyitan et al.[24]. The use of urea as an organic nitrogen source supplement for brewery fermentations has been strongly discouraged due to its potential to form the carcinogenic ethyl carbamate[25]. Limitation of nitrogen to yeasts has been linked to a potential loss of enzyme activity[22]. Therefore, the results reveal that relatively higher alcohol can be obtained from the pitching yeast in the presence of an inorganic nitrogen source supplement rather than an organic source.

      Effect of varied pH on S. cerevisiae during beer fermentation

    • Changes in pH were observed during beer fermentation for 72 h (Table 6). After the fermentation period, the highest value (3.76 ± 0.03) was from samples adjusted to an initial pH of 6.50 while the least (3.38 ± 0.01) was from pH 5.50. The values for total soluble sugar are shown in Table 7. After 72 h fermentation, the highest value (8.90 ± 0.06) was from samples with pH 6.50 while the least (4.33 ± 0.09) was from pH 5.50.

      Table 6.  Effect of varied initial pH on pH of wort during fermentation by S. cerevisiae.

      pH Fermentation period (h)
      0 24 48 72
      4.00 4.00 ± 0.00 3.97 ± 0.01c 3.90 ± 0.01b 3.51 ± 0.01b
      4.50 4.50 ± 0.00 4.24 ± 0.02b 3.87 ± 0.01c 3.51 ± 0.01b
      5.00 5.00 ± 0.00 3.97 ± 0.01c 3.67 ± 0.02e 3.43 ± 0.01c
      5.50 5.50 ± 0.00 3.75 ± 0.01c 3.56 ± 0.01f 3.38 ± 0.01a
      6.00 6.00 ± 0.00 4.06 ± 0.04b 3.74 ± 0.01d 3.46 ± 0.01c
      6.50 6.50 ± 0.00 5.37 ± 0.01a 3.92 ± 0.01a 3.76 ± 0.03a
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 7.  Effect of varied initial pH on total soluble sugar ( °Brix) of wort during fermentation by S. cerevisiae.

      pH Fermentation period (h)
      0 24 48 72
      4.00 15.80 ± 0.00 13.57 ± 0.09a 9.70 ± 0.12b 7.83 ± 0.07b
      4.50 15.80 ± 0.00 12.60 ± 0.12b 8.30 ± 0.06c 7.57 ± 0.03b
      5.00 15.80 ± 0.00 11.15 ± 0.29c 7.90 ± 0.06d 6.30 ± 0.06c
      5.50 15.80 ± 0.00 10.33 ± 0.09d 6.80 ± 0.06e 4.33 ± 0.09d
      6.00 15.80 ± 0.00 11.43 ± 0.09c 8.08 ± 0.02c 7.03 ± 0.02b
      6.50 15.80 ± 0.00 13.90 ± 0.06a 11.05 ± 0.03a 8.90 ± 0.06a
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      The specific gravity values are presented in Table 8. After 72 h fermentation, the highest value was from pH 6.50 while samples with initial pH of 4.50, 5.00, 5.50, and 6.00 had the least value of 1.02 ± 0.00. The acidity of the samples is shown in Table 9 with pH 5.50 had the highest value of 3.88 ± 0.01 ml while pH 6.50 had the lowest value of 3.39 ± 0.01 ml, after a 72 h fermentation period.

      Table 8.  Effect of varied initial pH on specific gravity of wort during fermentation by S. cerevisiae.

      pH Fermentation period (h)
      0 24 48 72
      4.00 1.07 ± 0.00 1.06 ± 0.00a 1.04 ± 0.00b 1.03 ± 0.00b
      4.50 1.07 ± 0.00 1.05 ± 0.00b 1.04 ± 0.00b 1.02 ± 0.00c
      5.00 1.07 ± 0.00 1.05 ± 0.00b 1.03 ± 0.00c 1.02 ± 0.00c
      5.50 1.07 ± 0.00 1.04 ± 0.00c 1.03 ± 0.00c 1.02 ± 0.00c
      6.00 1.07 ± 0.00 1.05 ± 0.00b 1.03 ± 0.00c 1.02 ± 0.00c
      6.50 1.07 ± 0.00 1.06 ± 0.00a 1.05 ± 0.00a 1.04 ± 0.00a
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 9.  Effect of varied initial pH on titratable acidity (%) of wort during fermentation by S. cerevisiae.

      pH Fermentation period (h)
      0 24 48 72
      4.00 1.39 ± 0.01d 1.76 ± 0.01d 3.22 ± 0.11b 3.61 ± 0.01b
      4.50 1.52 ± 0.01c 2.26 ± 0.01c 3.27 ± 0.01b 3.76 ± 0.01b
      5.00 2.55 ± 0.03a 2.93 ± 0.09b 3.39 ± 0.01b 3.82 ± 0.01a
      5.50 2.84 ± 0.02a 3.52 ± 0.01a 3.75 ± 0.03a 3.88 ± 0.01a
      6.00 1.78 ± 0.01b 2.48 ± 0.01b 3.29 ± 0.01b 3.79 ± 0.02b
      6.50 1.22 ± 0.01 1.44 ± 0.01e 3.17 ± 0.01b 3.39 ± 0.01c
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      The alcohol content of the samples is presented in Table 10. After 72 h fermentation, the highest value (4.43% ± 0.01%) was from pH 5.50 while the least (3.61% ± 0.01%) was from pH 6.50. Statistical analysis revealed significant differences between the samples for all measured parameters at p < 0.001 confidence level.

      Table 10.  Effect of varied initial pH on alcohol content (%) of wort during fermentation by S. cerevisiae.

      pH Fermentation period (h)
      0 24 48 72
      4.00 0.00 ± 0.00 2.18 ± 0.01b 3.77 ± 0.01a 4.12 ± 0.01a
      4.50 0.00 ± 0.00 2.41 ± 0.01b 3.49 ± 0.00b 4.25 ± 0.03a
      5.00 0.00 ± 0.00 2.60 ± 0.01a 3.33 ± 0.02b 4.38 ± 0.01a
      5.50 0.00 ± 0.00 2.79 ± 0.01a 3.76 ± 0.01a 4.43 ± 0.01a
      6.00 0.00 ± 0.00 2.22 ± 0.01b 3.16 ± 0.01b 4.29 ± 0.01a
      6.50 0.00 ± 0.00 2.19 ± 0.00b 2.89 ± 0.01c 3.61 ± 0.01b
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      The rate of ethanol production by yeast cells is strongly affected by the pH of the fermentation medium[26]. Acidic conditions tend to favor the growth of yeast and inhibit the growth of spoilage bacteria in wort[27]. However, continued increase in acidity slows down the metabolic pathways and growth of the yeast cells[28]. Thus, optimum pH is required for efficient growth of yeasts and concomitantly, the yield of ethanol.

      The medium with an initial pH adjusted to 5.50 gave the best fermentation performance by the yeast strain as it had the greatest decrease in pH and increase in acidity (p < 0.05) after a 72 h fermentation period. This meant that under this pH condition, the yeasts were more suited to carry out their fermentation activities. In this regard, it is noticed that the fermentation efficiency of the yeast cells decreased the more the adjusted initial pH fell below or above the optimum value of 5.50. This trend is also reflected in the TSS and specific gravity values as adjusted initial pH 5.50 also gave the least values showing the greatest utilization of sugars by the yeasts under this pH condition. The medium with initial pH adjusted to 5.50 generating the highest amount of alcohol by the yeasts after a 72 h fermentation period further buttresses the fact that the optimum initial pH required by the yeast strain used in this research work during fermentation is 5.50. Medium with adjusted initial pH of 6.5 was the least desired by the yeasts. Higher final pH, TSS and specific gravity values as well as lower final acidity and ethanol levels after 72 h fermentation period produced at adjusted initial pH values below and above 5.50 in this research work could be as a result of two different reasons. The first is the inactivation of the enzymes as enzymes work efficiently at optimum pH and the second is as a result of an increase in the chemical stress placed on the yeast cells which would have to garner more energy to stabilize their intracellular pH at pH values other than the optimum. In that light, this adjusted initial pH was adopted for the formulation of the cassava/sorghum substrate for beer production.

      The highest ethanol concentration obtained after a 72 h fermentation period for initial pH of 5.50 in this research work is similar to the work of Phong et al.[26]. Also, Sharma et al.[29] reported a medium initial pH of 5.50 as the required pH for optimum ethanol production by yeasts irrespective of the concentration of dissolved solids. They also revealed in their study that a pH of 5.00 to 5.50 will help to minimize the effects of bacterial contamination and maximize ethanol production by yeast. Yeasts have been reported to have optimum pH between 4.00 and 6.00[30]. Stewart[31] suggested a pH range of 4.00−5.00 as the operational limit for ethanol production by yeasts but also reiterated the reports of previous studies which instead suggested a pH range of 5.00−6.00. The required mash pH from the literature is usually within the range of 5.20−6.00[28]. The expected wort pH for sorghum malt is within the range of 5.20−5.80[32]. The pH values often recorded for wort obtained from barley malt range from 5.40 to 5.60 while for beers resulting from barley malt, the values range from 4.20 to 4.50 in the final products[33]. The wort pH of 5.50 is in conformity with the study conducted by Malina et al.[28] using 100% sorghum malt and 100% barley malt who reported a wort pH of 5.20 and 5.40 respectively. The results for wort pH obtained were lower than those reported by Adebo[34] who found that the pH of wort obtained using two Nigerian sorghum varieties (SK5912 and farafara) were 6.20 and 6.30 respectively. The result of wort pH was close to that reported by Xiang et al.[35] for wort produced from malted barley and sorghum adjuncts with pH values ranging from 5.60 to 6.00. Wort pH has a great impact on the activities of the enzymes present in malt. The wort pH obtained will create a positive effect as regards higher ethanol and CO2 production for the beer products due to the generation of higher amounts of soluble sugars by increased enzymatic activities.

      Effect of varying inoculum size on S. cerevisiae during beer fermentation

    • Varying the size of the pitching yeast led to changes in the pH during fermentation (Table 11). After a 72 h fermentation period, the highest value (3.51 ± 0.01) was from sample containing 7.44 × 108 cells/ml, while the least (3.33 ± 0.01) was from that containing 1.24 × 108 cells/ml. The result for total soluble sugar is shown in Table 12. After 72 h fermentation, the sample containing 7.44 × 108 cells/ml had the highest value (6.97 ± 0.12 °Brix) while that containing 1.24 × 108 cells/ml had the least value (6.30 ± 0.06 °Brix). For specific gravity (Table 13), after 72 h fermentation period the highest value (1.04 ± 0.00) was from samples containing 7.44 × 108 cells/ml while the least value (1.02 ± 0.00) was from that containing 1.24 × 108 cells/ml. Varying the inoculum size also led to changes in acidity (Table 14). After 72 h fermentation, the highest value (4.18 ± 0.01 ml) was from sample containing 1.24 × 108 cells/ml while the least value (3.66 ± 0.01 ml) was from samples containing 7.44 × 108 cells/ml. The alcohol content is shown in Table 15. After 72 h fermentation, the highest value (4.60 ± 0.01%) was from samples containing 1.24 × 108 cells/ml while the lowest (3.12% ± 0.01%) was from samples containing 7.44 × 108 cells/ml. Statistical analysis revealed significant differences between the samples for all measured parameters at p < 0.001 confidence level. The amount of inoculum used for pitching of wort plays a major role in influencing the rate of fermentation, growth rate, biomass yield as well as the quality of the final product[36]. Yeast inoculum size has a great effect on the generation of ethanol. The fact that the pH was the lowest after a 72 h fermentation period for medium containing yeast cells at a concentration of 1.24 × 108 cells/ml than at any other higher concentration, showed that fermentation of wort by the yeast cells was most effective at lower inoculum size than at higher concentrations. This fact is further elucidated as the medium containing 1.24 × 108 cells/ml of yeast cells had the least TSS and specific gravity values after a 72 h fermentation period. Also, the optimum ethanol yield for this research work was obtained at an inoculum size of 1.24 × 108 cells/ml. Inoculum sizes above this value gave a relatively lower yield of alcohol. This effectiveness of fermentation by the yeast cells at lower inoculum size than at higher inoculum levels could be due to the accumulation of by-products such as xylitol resulting from repressive fermentations[37]. The results obtained were the rational behind the selection of the optimum pitching size of 1.24 × 108 cells/ml for the pitching of wort obtained from the various formulations of cassava/sorghum substrates for beer production. The decrease in total soluble sugar and the corresponding increase in alcohol (p < 0.05) after a 72 h fermentation period that was observed in this research work are supported by Roca-Mesa et al.[18]. The lower yield in ethanol with higher inoculum sizes is supported by Hawashi et al.[38]. An increase in ethanol concentration has been shown to have a positive correlation with a decrease in total soluble sugars[22]. It has reported that higher inoculum size of yeast has no advantage in terms of ethanol production[20]. This could have been a major factor for the lower yield of alcohol at higher inoculum sizes. Roca-Mesa et al.[18] revealed that increasing the pitching rate led to a decrease in the levels of alcohol generated. However, Phong et al.[26] suggested that increasing inoculum sizes led to a corresponding increase in alcohol production levels during fermentation. Sasmal et al.[16] attributed this contradiction to differences in the strain of yeasts used.

      Table 11.  Effect of varied inoculum size on pH of wort during fermentation by S. cerevisiae.

      Inoculum size
      (cells/ml)      		 Fermentation period (h)
      0 24 48 72
      1.24 × 108 5.50 ± 0.00 3.41 ± 0.01b 3.39 ± 0.01c 3.33 ± 0.01c
      2.48 × 108 5.50 ± 0.00 3.46 ± 0.01b 3.40 ± 0.01b 3.37 ± 0.01b
      3.72 × 108 5.50 ± 0.00 3.50 ± 0.01a 3.45 ± 0.01b 3.41 ± 0.01b
      4.96 × 108 5.50 ± 0.00 3.52 ± 0.01a 3.46 ± 0.01b 3.44 ± 0.01b
      6.20 × 108 5.50 ± 0.00 3.55 ± 0.01a 3.49 ± 0.00b 3.48 ± 0.00b
      7.44 × 108 5.50 ± 0.00 3.58 ± 0.01a 3.52 ± 0.01a 3.51 ± 0.01a
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 12.  Effect of varied inoculum size on total soluble sugar ( °Brix) of wort during fermentation by S. cerevisiae.

      Inoculum size
      (cells/ml)      		 Fermentation period (h)
      0 24 48 72
      1.24 × 108 15.80 ± 0.00 10.47 ± 0.09c 7.17 ± 0.01d 6.30 ± 0.06b
      2.48 × 108 15.80 ± 0.00 10.70 ± 0.06b 7.20 ± 0.12d 6.73 ± 0.07b
      3.72 × 108 15.80 ± 0.00 10.77 ± 0.09b 7.43 ± 0.09c 6.67 ± 0.09b
      4.96 × 108 15.80 ± 0.00 10.90 ± 0.06b 7.63 ± 0.15b 6.80 ± 0.06b
      6.20 × 108 15.80 ± 0.00 11.53 ± 0.03a 7.77 ± 0.09b 6.80 ± 0.00b
      7.44 × 108 15.80 ± 0.00 11.60 ± 0.06a 8.07 ± 0.07a 6.97 ± 0.12a
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 13.  Effect of varied inoculum size on specific gravity of wort during fermentation by S. cerevisiae.

      Inoculum size
      (cells/ml)      		 Fermentation period (h)
      0 24 48 72
      1.24 × 108 1.07 ± 0.00 1.04 ± 0.00b 1.03 ± 0.00b 1.02 ± 0.01c
      2.48 × 108 1.07 ± 0.00 1.04 ± 0.00b 1.03 ± 0.00b 1.03 ± 0.00b
      3.72 × 108 1.07 ± 0.00 1.04 ± 0.00b 1.03 ± 0.00b 1.03 ± 0.00b
      4.96 × 108 1.07 ± 0.00 1.05 ± 0.00a 1.03 ± 0.00b 1.03 ± 0.00b
      6.20 × 108 1.07 ± 0.00 1.05 ± 0.00a 1.03 ± 0.00b 1.03 ± 0.00b
      7.44 × 108 1.07 ± 0.00 1.05 ± 0.00a 1.04 ± 0.00a 1.04 ± 0.00a
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 14.  Effect of varied inoculum size on titratable acidity (%) of wort during fermentation by S. cerevisiae.

      Inoculum size
      (cells/ml)      		 Fermentation period (h)
      0 24 48 72
      1.24 × 108 2.86 ± 0.01a 3.81 ± 0.01a 3.90 ± 0.02a 4.18 ± 0.01a
      2.48 × 108 2.82 ± 0.01a 3.69 ± 0.01b 3.87 ± 0.01a 4.11 ± 0.01a
      3.72 × 108 2.71 ± 0.00c 3.64 ± 0.01b 3.78 ± 0.01a 3.91 ± 0.01b
      4.96 × 108 2.56 ± 0.01d 3.61 ± 0.01b 3.74 ± 0.01a 3.79 ± 0.01b
      6.20 × 108 2.50 ± 0.11d 3.49 ± 0.01c 3.64 ± 0.01b 3.74 ± 0.01b
      7.44 × 108 1.88 ± 0.01a 3.42 ± 0.01c 3.52 ± 0.02b 3.66 ± 0.01b
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).

      Table 15.  Effect of varied inoculum size on alcohol content (%) of wort during fermentation by S. cerevisiae.

      Inoculum size
      (cells/ml)      		 Fermentation period (h)
      0 24 48 72
      1.24 × 108 0.00 ± 0.00 2.74 ± 0.01a 3.73 ± 0.01a 4.60 ± 0.01a
      2.48 × 108 0.00 ± 0.00 2.39 ± 0.01b 3.43 ± 0.02b 4.53 ± 0.01a
      3.72 × 108 0.00 ± 0.00 2.51 ± 0.01b 3.27 ± 0.02b 4.10 ± 0.06b
      4.96 × 108 0.00 ± 0.00 2.33 ± 0.01b 3.18 ± 0.02b 3.88 ± 0.01c
      6.20 × 108 0.00 ± 0.00 2.45 ± 0.01b 3.83 ± 0.01a 3.29 ± 0.01c
      7.44 × 108 0.00 ± 0.00 2.48 ± 0.01b 3.22 ± 0.02b 3.12 ± 0.01c
      Values are expressed as mean ± standard deviation of triplicates. Note: All similar lower case letters within a column show means that are not significantly different (p > 0.05).
    Conclusions

    • From the results of the study, Saccharomyces cerevisiae strain B05 displayed a remarkable ability to ferment sugars present in sorghum wort under varying conditions with the results obtained. Ammonium sulfate gave the highest amount of alcohol after the fermentation period and was chosen as the best nitrogen source. The pH for optimum yeast performance was 5.50 based on the alcoholic content while an inoculum size of 1.24 × 108 cells/ml was chosen as the required size for optimum performance based on the amount of alcohol generated. Under these optimal conditions, the yeast strain Saccharomyces cerevisiae strain B05 could be used as a veritable tool for fermentation of sorghum worts to obtain maximum yield. However, more research still needs to be carried out under fermentation conditions to further study the mechanism of the yeast strain in worts and other substrates especially if it is to be employed for domestic and industrial applications.

    Author contributions

    • The authors confirm contribution to the paper as follows: study conception and design: Akpoghelie PO, Edo GI, Kasar KA, Zainulabdeen K, Yousif E, Mohammed AA, Jikah AN, Ezekiel GO, Owheruo JO, Ugbune U, Umar H, Ekokotu HA, Oghroro EEA, Onyibe PN, Ekpekpo LD, Isoje EF, Agbo JJ; data collection, data analysis and draft manuscript preparation: Akpoghelie PO, Edo GI; study spervision, data analysis, interpretation, and critical revisions: Edo GI, Yousif E. All authors reviewed the results and approved the final version of the manuscript.

    Data availability

    • The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

      Conflict of interest

      • The authors declare that they have no conflict of interest.

      Rights and permissions
      • Copyright: © 2024 by the author(s). Published by Maximum Academic Press on behalf of Nanjing Agricultural University. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (1)  Table (15) References (38)
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    Akpoghelie PO, Edo GI, Kasar KA, Zainulabdeen K, Yousif E, et al. 2024. Impact of different nitrogen sources, initial pH and varying inoculum size on the fermentation potential of Saccharomyces cerevisiae on wort obtained from sorghum substrate. Food Materials Research 4: e021 doi: 10.48130/fmr-0024-0012
    Akpoghelie PO, Edo GI, Kasar KA, Zainulabdeen K, Yousif E, et al. 2024. Impact of different nitrogen sources, initial pH and varying inoculum size on the fermentation potential of Saccharomyces cerevisiae on wort obtained from sorghum substrate. Food Materials Research 4: e021 doi: 10.48130/fmr-0024-0012
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  • Introduction
  • Materials and methods

  • Sample collection

  • Preparation of sorghum for malting

  • Malting and kilning of sorghum seeds

  • Milling the malt

  • Mashing, iodine test, and wort boiling

  • Yeast propagation

  • Effect of different nitrogen sources on fermentation performance of yeast

  • Effect of varying pH of wort on fermentation performance of yeast

  • Effect of varying inoculum size on fermentation performance of yeast

  • Parameters analyzed

  • pH
  • Specific gravity
  • Alcohol content
  • Total acidity
  • Total soluble sugar

  • Statistical analysis

  • Results and discussion

  • Effect of different nitrogen sources on S. cerevisiae during beer fermentation

  • Effect of varied pH on S. cerevisiae during beer fermentation

  • Effect of varying inoculum size on S. cerevisiae during beer fermentation

  • Conclusions
  • Author contributions
  • Data availability
  • Conflict of interest
  • Rights and permissions
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