Food Waste Composting and Microbial Community Structure Profiling
Abstract
:1. Introduction
1.1. Organic Food Waste Composting
1.2. Factors Affecting the Organic Waste Compost
1.3. Compost Methods
2. Microbial Community Structure During Composting
3. Stages of Composting
3.1. First Stage
3.2. Second Stage
Compost Stage | Group | Genus | Microbial Species | Reference |
---|---|---|---|---|
Amycolicicoccus | Amycolicicoccus subflavus | [67] | ||
Bacillus | Bacillus badius, Bacillus cereus, Bacillus flexus, Bacillus subtilis, Bacillus polymyxa, Bacillus pumilus, Bacillus spp. | [55,67,68,69,70] | ||
Brevibacillus | Brevibacillus brevis | [68,69,71] | ||
Enterobacter | Enterobacter sakazakii | [69] | ||
Mesophilic | Bacteria | Klebsiella | Klebsiella pneumoniae | [68,69,71] |
Mycobacterium | Mycobacterium xenopi, Mycobacterium thermoresistibile | [67] | ||
Serratia | Serratia marcescens | [69] | ||
Staphylococcus | Staphylococcus aureus, Staphylococcus sciuri, Staphylococcus xyloseus, Staphylococcus sp. | [68,69] | ||
Aspergillus | Aspergillus flavus, Aspergillus niger | [68] | ||
Fusarium | Fusarium moniliforme, Fusarium oxysporum, Fusarium sp | [68] | ||
Mesophilic | Fungi | Streptomyces | Streptomyces antibioticus, Streptomyces cinnaborinus, Streptomyces griseuss, Streptomyces roseus | [68] |
Rhizopus | Rhizopus nigricans | [68] | ||
Penicillium | Penicillium citrinum | [68] | ||
Acidorax | Acidovorax sp. | [69] | ||
Amycolicicoccus | Amycolicicoccus subflavus | [67] | ||
Anoxybacillus | Anoxybacillus flavithermus | [71] | ||
Thermophilic | Bacteria | Bacillus | Bacillus benzoevorans, Bacillus coagulans, Bacillus flexus, Bacillus megaterium, Bacillus nealsonii, Bacillus pumilus, Bacillus stearothermophilus, Bacillus subtilis, Bacillus sp. | [55,68,69,70,71] |
Brevibacillus | Brevibacillus brevis | [68,69,71] | ||
Clostridium | Clostridium acidurici, Clostridium thermocellum, Clostridium sp. | [55,71] | ||
Comamonas | Comamonas kerstersii | [69] | ||
Gemmatimonas | Gemmatimonas aurantiaca | [71] | ||
Geobacillus | Geobacillus sp. WCH70, Geobacillus sp. Y4.1MC1, Geobacillus thermodenitrificans | [71] | ||
Thermophilic | Bacteria | Klebsiella | Klebsiella pneumoniae | [68,69,71] |
Kocuria | Kocuria flavus | [69] | ||
Krypidia | Kyrpidia tusciae | [71] | ||
Lysinibacillus | Lysinibacillus fusiformis, Lysinibacillus sphaericus | [69,71] | ||
Mahella | Mahella australiensis | [71] | ||
Mycobacterium | Mycobacterium thermoresistibile, Mycobacterium xenopi | [67] | ||
Paenibacillus | Paenibacillus mucilaginosus, Paenibacillus sp. JDR-2 | [71] | ||
Pseudomonas | Pseudomonas mendocina, Pseudomonas putida, Peseudomonas sp. | [68,70,71] | ||
Rhodothermus | Rhodothermus marinus | [71] | ||
Solibacillus | Solibacillus silvestris | [71] | ||
Sorangium | Sorangium cellulosum | [71] | ||
Sphaerobacter | Sphaerobacter thermophilus | [71] | ||
Streptosporangium | Streptosporangium roseum | [71] | ||
Thermophilic | Bacteria | Symbiobacterium | Symbiobacterium thermophilum | [71] |
Thermaerobacter | Thermaerobacter marianensis | [71] | ||
Thermobacillus | Thermobacillus composti | [71] | ||
Thermobifida | Thermobifida fusca | [71] | ||
Thermobispora | Thermobispora bispora | [71] | ||
Thermomonospora | Thermomonospora curvata | [67,71] | ||
Thermosediminibacter | Thermosediminibacter oceani | [71] | ||
Thermus | Thermus sp. | [68] | ||
Terribacillus | Terribacillus halophilus | [69] | ||
Aspergillus | Aspergillus fumigatus, Aspergillus fumigates var. elpticus | [68] | ||
Talaromyces | Talaromyces thermophilus, Talaromyces sp. | [68] | ||
Thermophilic | Fungi | Thermocyces | Thermomyces sp. | [55,68] |
Thermatinomyces | Thermactinomyces sp. | [68] | ||
Thermo | Thermo dichotomicus, Thermo vulgaris, Thermo sp. | [68] | ||
Amycolicicoccus | Amycolicicoccus subflavus | [67] | ||
Cooling or maturation | Bacteria | Bacillus | Bacillus circulans, Bacillus composteris, Bacillus southcampusis, Bacillus licheniformis, Bacillus subtilis, Bacillus pumilus | [68,69] |
Mycobacterium | Mycobacterium xenopi, Mycobacterium thermoresistibile | [67] |
3.3. Third Stage
4. Compost Microbial Community Structure Profiling Techniques
4.1. Biochemical Approach
4.2. Microarray Analysis
- Phylogenetic Oligonucleotide Arrays (POAs)POAs utilized a small-subunit of identified ribosomal RNA (rRNA) as the array probes. The specific region of rRNA exists in all organisms but the specificity of the conserved and variable regions of one organism is rarely transferred to or in between organisms making them convenient as genetic markers.
- Functional Gene Arrays (FGAs)FGAs measure the genes involved in a certain process. The probe array on FGAs are usually genes encoding some part of the process of interest, such as enzymes or proteins in a metabolic process. FGAs are not only able to measure expression levels of these genes, but also some degree of genetic classification and gene capacity.
- Community Genome Arrays (CGAs)CGAs are a novel prototype array that contain probes representing a subset of or the entire genomic DNA of an organism in a naturally occurring microbial community. CGAs are used as a comparative tool to relate microbial communities across different samples.
- Metagenomic arrays (MGAs)MGAs are the combination between microarrays and metagenomics. A MGA contains cosmid library inserts along with control rRNA probes. This enables MGAs to be used as high-throughput screening technique, although MGAs are still in the early stage of development.
- Whole-genome ORF arrays (WGAs)WGA utilize all the open reading frames (ORFs) in the genome as the probes. WGAs are used mainly in studying genomic response in different environments or the microevolution of a particular organism.
4.3. Genotyping and Fingerprinting
4.3.1. Terminal Restriction Fragment Length Polymorphism (T-RFLP)
4.3.2. Denaturing Gradient Gel Electrophoresis (DGGE)
4.3.3. Single-Strand Conformation Polymorphism (SSCP)
4.4. Next Generation Sequencing
5. Benefits of Composting
5.1. Environmental Benefits
5.2. Stakeholders of the Food Value Chain
6. Global Trend of Composting
7. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
MDPI | Multidisciplinary Digital Publishing Institute |
DOAJ | Directory of open access journals |
TLA | Three letter acronym |
LD | linear dichroism |
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Composting [24] | |
---|---|
Benefits | Drawbacks |
Able to reduce and reuse organic waste | Time and money required initially to start up |
Conserve space and extending life of the landfill | Expensive to store and transport due to bulky product |
Improve nutrient properties of soil | Land requirement for compost site |
Compost product are saleable and provide profit | Possibility of odor emission |
Reduce waste odor | Weather influence to compost process |
Improves waste and manure management | Marketing necessary to sell compost product |
Reduce cost of waste management | Inconsistent and low nutrient value compare to chemical fertilizer |
Reduce the risk of pollution, methane emission and soil erosion | Slow-release of nutrients as fertilizer compared to chemical fertilizer |
Remediate hazardous waste | |
Suppress pathogen and soil-borne diseases | |
Excellent bedding substitute |
Factors Affecting the Organic Waste Compost [29,30] | ||
---|---|---|
Parameter | Acceptable Range | Preferred Range |
Carbon to nitrogen (C:N) ratio | 20:1 or 40:1 | 25:1 or 30:1 |
Moisture Content | 40 to 65% | 50 to 60% |
Oxygen concentrations | ≥5% | >5% |
Particle size (Diameter in inches) | 1/8 to 1/2 | Varies |
pH value | 5.5 to 9.0 | 6.5 to 8.0 |
Temperature (°C) | 43 to 65 | 54 to 60 |
Composting System | ||||
---|---|---|---|---|
Characteristics | Vermi-Composting | Windrow | Aeratic Static Pile | In-Vessel |
Preferred waste input | Wastes mixed with manure such as cow, goat and poultry manure | Wastes with less emission of odor such as plant-based | Waste with more homogeneity, consistency and those required bulking agent | Easily degraded wastes such as food waste |
Compost capacity | 2 to 3 tons of wastes | More than 10 tons of waste | More than 10 tons of waste | 1 to 5 tons of wastes |
Land requirement | Low | High | Medium | Low |
Site selection | Anywhere equipment can be placed | Away from populated area | Away from populated area | Anywhere equipment can be placed |
Cost of waste transportation | High | High | High | Low |
Composting period | Short | Long | Long | Short |
Amendment | Addition of bulking agent, animal manure and microbial additives; consistent temperature | Addition of bulking agent, chemical additives and microbial additives; increase of aeration | Addition of chemical additives, and microbial additives; increase of aeration | Increase the in-vessel temperature, pressure and turning rate |
Amendment effects on compost | Increase in production of biomass by more than 20% | Reduce the total composting period by 30% | Reduce the total composting period by more than 30% | Reduce the total composting period by more than 30% |
Compost quality | Good | Medium | Medium | Good |
References | [35] | [37] | [38] | [38] |
Bulking Agent | |||||||
---|---|---|---|---|---|---|---|
Parameter | Wheat Straw | Wood Shaving | Wood Chips | Pruning Waste | Pruning Waste | Saw Dust | Bio-Char |
Compost Type | Organic | Organic | Organic | Organic (Home) | Organic (Industry) | Organic | In-vessel |
Bulking Agent Ratio | 5:1 (wt/wt) 1 | 1:1 (v/v) 1 | 1:3-4 (wt/wt) 1 | 0.8:1 (v/v) 1 | 2.6:1 (wt/wt) 1 | – | – |
pH | 8 | 7.9 | 8.6 | 7.83 | 7.88 | 6.38 | 8.6 |
TOM (%) | 39 | 25 | 58.6 | 47.96 | 55.33 | – | 64.2 |
TOC (%) | 22 | 14.5 | 34 | – | – | 45.56 | 35.7 |
TKN (%) | 3.72 | 0.8 | 2 | 1.71 | 2.04 | 0.49 | – |
C/N ratio | 6 | 19 | 17 | – | – | 92.36 | – |
Moisture | 35 | – | 31 | 43.63 | 31.85 | – | 54.4 |
P as P2O5 (%) | 0.29 | – | – | – | – | – | – |
K as K2O (%) | 3.09 | – | – | – | – | – | – |
Mg as MgO (%) | 0.52 | – | – | – | – | – | – |
EC (mS/cm) | 24.85 | – | – | 4.30 | 4.90 | – | – |
Ash (%) | 52.95 | – | – | – | – | 17.98 | 35.7 |
Cu (ppm) | – | – | – | 44 | 47 | – | – |
Zn (ppm) | – | – | – | 156 | 150 | – | – |
Reference | [45] | [46] | [47] | [48] | [48] | [49] | [50] |
Characteristic of Different Microarrays [87] | |||
---|---|---|---|
Type of Microarray | Probes Used | Probe Length | Information Target |
POA | Ribosomal rRNA | 18–25 nt | Phylogenetic |
FGA | Functional genes | 50–70 nt or 200–1000 nt (PCRP) | Functional |
CGA | Whole genomes of multiple organisms | Whole genome | Phylogenetic |
MGA | Environmetal DNA | 1000+ nt | Functional |
WGA | Open reading frames in whole genome | 23 nt or 200–3000 ny (PCR) | Phylogenetic and functional |
Method | Size Separation | Information Provided | Cost and Requirement | Reference |
---|---|---|---|---|
T-RFLP | 20–517 bp | Fragment quantification | High, requires fluorescent primers, restriction enzymes, DNA sequencer | [100] |
DGGE | 550 bp | Microbial identification | Medium, requires GC clamp, primers, markers, gradient gel formula | [101] |
SSCP | 150–400 nt | Microbial identification | Low, only requires specific primers | [101] |
Compost Substrate | Target | NGS Platform | Sequencing Approach | Summary | Reference |
---|---|---|---|---|---|
Sewage sludge (gelatin industry, municipal) | Bacteria | Illumina | Amplicon, 16S, V3 (bacteria) and 18S, ITS (fungi) | 8 bacterial, 2 fungal phyla throughout compost | [75] |
Corn straw and cow manure | Bacteria, Fungi | Illumina | Amplicon, 16S (bacteria) and ITS (fungi) | 272 bacterial OTU and 321 fungal OTU | [79] |
Food waste | Bacteria | Illumina | Amplicon, 16S, V4 | 5 dominant phyla, >40 species detected | [113] |
Food waste | Bacteria | Illumina | Amplicon, 16S, V3-V4 | 29 bacteria strains detected | [114] |
Chicken manure | Fungi | Illumina | Amplicon, ITS | 526 OTUs classified into 4 fungi phyla | [115] |
Rice husk and dewatered sludge | Bacteria | Illumina | Amplicon, 16S, V4-V5 | 29 OTUs and 11 genus identificed | [116] |
Maize straw | Bacteria | Illumina | Amplicon, 16S, V3-V4 | 16 bacterial phyla obtained. Four phyla accounted for 92.2% all sequences | [117] |
Food waste and wastewater | Bacteria | Roche 454 | Amplicon, 16S, V5-V9 | 116 OTUs, 16 genera | [118] |
Food waste and seed sludge | Bacteria | Roche 454 | Amplicon, 16S, V1-V3 | 8 archaeal, 12 bacterial population | [119] |
Maize straw | Fungi | Roche 454 | Amplicon, 16S, V3-V4 (bacteria), ITS (fungi) | 412 fungal OTUs, 1 major phyla and 8535 bacterial OTUs, 24 phyla | [120] |
Green waste and barley grain | Bacteria | Roche 454 | Amplicon, 16S, V1-V2 | 20 bacterial genera at all experimental phases | [121] |
Spent mushroom waste | Bacteria | Roche 454 | Amplicon, 16S, V5-V8 | 19 phyla,33 classes, 48 orders, 85 families and 129 genera of bacteria detected | [122] |
Olive mill waste | Bacteria | Roche 454 | Amplicon, 16S, V4-V5 | 10 dominant genera in mesophilic, thermophilic stage, 8 genera in maturation | [123] |
Food waste and cattle manure | Bacteria, Virus | Ion Torrent | Metagenomic, de novo assembly | Proteobacteria constituting almost 65% reads. 5 pathogenic species detected, Phages constituted the main viral group, mostly insect viruses. | [124] |
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Palaniveloo, K.; Amran, M.A.; Norhashim, N.A.; Mohamad-Fauzi, N.; Peng-Hui, F.; Hui-Wen, L.; Kai-Lin, Y.; Jiale, L.; Chian-Yee, M.G.; Jing-Yi, L.; et al. Food Waste Composting and Microbial Community Structure Profiling. Processes 2020, 8, 723. https://doi.org/10.3390/pr8060723
Palaniveloo K, Amran MA, Norhashim NA, Mohamad-Fauzi N, Peng-Hui F, Hui-Wen L, Kai-Lin Y, Jiale L, Chian-Yee MG, Jing-Yi L, et al. Food Waste Composting and Microbial Community Structure Profiling. Processes. 2020; 8(6):723. https://doi.org/10.3390/pr8060723
Chicago/Turabian StylePalaniveloo, Kishneth, Muhammad Azri Amran, Nur Azeyanti Norhashim, Nuradilla Mohamad-Fauzi, Fang Peng-Hui, Low Hui-Wen, Yap Kai-Lin, Looi Jiale, Melissa Goh Chian-Yee, Lai Jing-Yi, and et al. 2020. "Food Waste Composting and Microbial Community Structure Profiling" Processes 8, no. 6: 723. https://doi.org/10.3390/pr8060723
APA StylePalaniveloo, K., Amran, M. A., Norhashim, N. A., Mohamad-Fauzi, N., Peng-Hui, F., Hui-Wen, L., Kai-Lin, Y., Jiale, L., Chian-Yee, M. G., Jing-Yi, L., Gunasekaran, B., & Razak, S. A. (2020). Food Waste Composting and Microbial Community Structure Profiling. Processes, 8(6), 723. https://doi.org/10.3390/pr8060723