We thank Dr. Jim Young of Respirometer Systems and Applications for the discussion concerning the development of this protocol.

1. Preparation of substrate
<ol>
	<li>Collect ~1.5 L of primary effluent, ~1 L of waste-activated sludge (WAS). 
	NOTE: WAS samples should be taken immediately prior to the experiment; however, WAS can be stored for up to 48 h at 4 &#176;C prior to the experiment with no discernable impact on its use as a substrate15,16,17.</li>
	<li>Acquire 2 L of anaerobic culture immediately prior to the experiment and maintain the culture at 35 &#176;C. Limit contact with air as much as possible during the transfer from the anaerobic digester to the collection bottle. 
	NOTE: The anaerobic culture used in this study was obtained from a WWTP treating 8.5 MGD (38,640 m3/d) with anaerobic digestion of wastewater primary sludge. A best practice is to maintain anaerobic conditions by flushing the collection bottle with nitrogen gas prior to acquiring an anaerobic culture13 and maintaining anaerobic conditions during transport and storage.</li>
	<li>Gather food waste and store it for up to 48 h prior to the experiment at 4 &#176;C. 
	NOTE: depending on the experimental design, care should be taken to identify food wastes with the target proportions of carbohydrates, proteins, etc. Target proportions of organics in food waste will likely vary by experiment. The fraction of carbohydrates, proteins, and fats in the food gathered can be estimated from published literature or evaluated using established protocols (e.g., gas chromatography).</li>
</ol>
2. Preparation of nutrient supplements
<ol>
	<li>Prepare mineral base solution #1 by mixing 800 mL of deionized (DI) water with CoCl2&#183;6H2O (0.25 g), FeCl3&#183;6H2O (5 g), MnCl2&#183;4H2O (0.05 g), NaMoO4&#183;2H2O (0.005 g), NiCl2&#183;6H2O (0.025 g), CuCl2&#183;2H2O (0.007 g), ZnCl2 (0.025 g), H3BO3 (0.025 g), and Na2SeO4 (0.025 g). Dilute up to 1 L with deionized (DI) water.</li>
	<li>Prepare mineral base solution #2 by mixing 800 mL of DI water with CaCl2 (27.7 g) and MgCl2&#183;4H2O (101 g). Dilute up to 1 L with DI water.</li>
	<li>Prepare a nutrient base by mixing 800 mL of DI water with NH4Cl (38.2 g) and Na2SO4 (15 g). Adjust pH to 7.0 using 3.64 N NaOH in DI water and dilute up to 1 L with DI water.</li>
</ol>
3. Sample preparation
<ol>
	<li>Combine food waste (Table 2) in a blender (Figure 1) to create a mixture. Ensure that the mixture is free of large particles of food waste. Dilute the food waste with DI water to aid in blending. Annotate the quantity of dilution water for use when calculating Chemical Oxygen Demand (COD) measurements. This diluted food waste is known as &#39;working waste&#39;. Place working waste in a 1 L plastic bottle and store it at 4 &#176;C.</li>
	<li>Label four 2 L beakers according to Table 1. Place beakers on a stir plate and add a large stir bar. Combine food waste, WAS, and dilution (DI water for control and primary effluent for treatments) according to Table 1 in the 2 L beakers.</li>
	<li>Add 12 mL each of mineral base solution #1, mineral base solution #2, and nutrient base.</li>
	<li>Add 2.4 g of NaHCO3 (powder) to each beaker and stir for 30 s. Label eight respirometry bottles according to Table 1 and add a magnetic stir bar. 
	NOTE: This will create duplicates of the control and three treatments at different F:M ratios.</li>
	<li>Add anaerobic culture to each 2 L beaker according to Table 1 and stir. Immediately measure 500 mL of a mixture from the beaker with a graduated cylinder and transfer it into a labeled respirometer bottle, flush with nitrogen gas, then cap immediately. 
	NOTE: Care should be taken to limit contact of anaerobic microbiota with atmospheric oxygen (If available, an anaerobic chamber should be used for the transfer).</li>
</ol>
4. Quantification of initial conditions
<ol>
	<li>Use the remaining sample from section 3 (~200 mL) to measure pH, total COD (tCOD), soluble COD (sCOD), total suspended solids (TSS), and volatile suspended solids (VSS) for each sample18.
	<ol>
		<li>If necessary, dilute samples with DI water based on the detection limits of the measurement equipment. 
		NOTE: Manufacturer&#39;s procedures were used for COD measurements.</li>
	</ol>
	</li>
</ol>
5. Respirometer setup
<ol>
	<li>Set the respirometer (Figure 2) to the low anaerobic setting.</li>
	<li>Push the reset button and the power-on button simultaneously. 
	NOTE: This is specific to the model used in this study.</li>
	<li>Set the chiller (Figure 3) at 35.5 &#176;C.</li>
	<li>Fill each CO2 and moisture scrubber (Figure 4 and Figure 5) with a 50/50 mix of CaSO4 and KOH pellets in the center, surrounded by glass wool on each side.</li>
	<li>Connect the tubes and needles from the sample bottles to the scrubber and then from the scrubber to the gas inlet (Figure 6).</li>
	<li>On the respirometer laptop, run the respirometer program RSA-8-v2.0. 
	NOTE: This step is specific to the model used in this study.</li>
	<li>Select all bottles in the program and select Edit &#62; Data Labels. Name all bottles. 
	NOTE: This step is specific to the model used in this study.</li>
	<li>Begin measuring gas production by activating the Start Button in the program. Set the program to measure data at the end of every half hour. Monitor gas production by selecting Rate Chart or Volume Chart. 
	NOTE: This step is specific to the model used in this study.</li>
	<li>After the experiment (~7 days), stop the run in the program, turn off the chiller, and turn off the RSPF module. Save the data file as a CSV file, then convert it to an MS Excel document. 
	NOTE: This step is specific to the model used in this study.</li>
</ol>
6. Post-respiration measurements
<ol>
	<li>Measure pH, TSS, VSS, and COD on the final samples as done in section 4.</li>
</ol>

Respirometry Protocol for Anaerobic Digestion of Food Waste and Sludge

<ol>
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The authors have nothing to disclose.

The methods provided in this protocol can help researchers and practitioners determine the biomethane potential of anaerobically digesting organic waste streams using respirometry. In this protocol, we demonstrate methane generation from co-digestion of a typical food scrap waste stream coupled with WAS from a WWTP over a range of F:M ratios. This protocol adds to the literature by providing a step-by-step respirometry approach for continuous measurement of methane production and determination of biokinetic parameters using first-order kinetic modeling. Several other studies have employed microcosm experiments that measure methane production at discrete points in time10,22, while others have measured methane using flowmeters attached to long-running continuous-flow bench- or pilot-scale bioreactors14,23. Respirometry offers the advantage of measuring methane production on a continuous basis over a variety of experimental conditions. As respirometry experiments do not require the construction of a bioreactor, the experimental conditions can be modified with relative frequency compared to some bench- or pilot-scale experiments. Due to this advantage, respirometry experiments can be used to determine methane production from co-digesting numerous combinations of organic wastes in a relatively short period of time. For example, as a next step to the protocol presented in this study, fats, oils, and grease, which are very dense in chemical energy relative to WAS, could be co-digested with food scraps to quantify likely increases in methane generation over time. The application of this approach can continue to build the body of literature concerning methane generation rates and biokinetic parameters across multiple substrate combinations in co-digestion schemes. Further, in addition to determining optimal substrate combinations, methane production results and biokinetic parameters can be used to inform performance modeling in existing programs, such as those designed for wastewater treatment, or to predict how co-digestion schemes will perform when scaled up from bench or pilot-scale to full-scale24,25.
Additionally, this protocol could be amended to apply a tailored substrate feed for the anaerobic microbial consortium. For example, if a researcher wanted to examine the impacts of providing only carbohydrates or only proteins to anaerobic microbiota, then the feedstock in this protocol could be altered accordingly. Alternatively, if a researcher wanted to test the impact of adding a specific fraction of COD (e.g., only soluble COD, or only particulate COD) or high concentrations of a particular substrate (e.g., acetate, volatile fatty acid, and intermediate product of the anaerobic metabolism) on methane production, a variation of this protocol could be used. An observed best practice when modifying substrate or alternating the F:M of a particular substrate is to maintain the same mass of anaerobic microbiota for each sample while adjusting only the mass of the substrate (mass-to-mass ratios should be employed). In addition to modifying substrates, researchers can use this protocol with other analyses to obtain a better understanding of substrate use and methane production. For example, a researcher could use this protocol in conjunction with microbial community analyses (e.g., 16S rRNA gene sequencing or metagenomics) to better relate community structure to function.
Despite the usefulness of this methodology, there are several limitations. Respirometers and biomethane potential tests are most frequently configured as batch reactors; however, full-scale anaerobic co-digesters are normally operated as continuous flow systems with sludge retention times upwards of 10 days1. Accordingly, the data gleaned from respirometry experiments are useful for estimating methane generation rates and developing biokinetic parameters, but these data should be validated in the field using larger-scale digesters operated over time when feasible.
Additionally, care must be taken in selecting and preparing samples prior to respirometry. Large food scrap particles will skew VSS and COD measurements and can provide inaccurate results. If food scrap waste is used as a substrate, the blend should be well macerated and free of large food particles - an approach akin to maceration at food scrap receiving pits at full-scale digesters. Dilution with DI water can help with the blending process and is similar to the addition of water commonly used when food scraps are macerated at a larger scale. However, every effort should be taken to ensure that dilutions are properly measured and that the target moisture content is achieved. Dilution can readily be a source of error, especially if inexperienced students are executing this protocol.
As the microbial consortia existing in co-digestion contain obligate anaerobes, special care must be taken to eliminate (or greatly reduce) exposure to oxygen during the transfer and sample preparation processes. Oxygen can be removed from sample bottles via nitrogen flushing. Further, if available, the work of transferring anaerobic culture between collection bottles and respirometer sample bottles should be conducted in an anaerobic chamber. As the respirometer provides consistent results (methane production volumes and rates), any deviation from expected results, e.g., an unviable microbial consortium, can be easily identified towards the beginning of the test. The use of a duplicate or triplicate sample can further help identify faulty tests.

Researchers study microbial activity at the bench scale using a variety of approaches, including batch studies, microcosms, and respirometry, amongst others. Respirometers can be used to measure cellular respiration through the growth and/or decay phases of a microbial community by observing substrate consumption and end-product production under controlled conditions1. The results from bench-scale respirometer studies can also be used to estimate biokinetic parameters for process model construction2. Respirometers have been used to examine both aerobic and anaerobic microbial activity; however, studies using respirometry to measure the biomethane potential (BMP), especially of mixed organic substrates, is an area of ongoing research3,4.
Organics in domestic wastewater are recognized as a viable renewable source of chemical energy5. Anaerobic digestion of wastewater sludges (i.e., primary sludge and waste-activated sludges, WAS) has been used to produce methane-rich biogas at wastewater treatment plants (WWTPs) for well over a century6. However, the digestion of multiple organic waste streams, such as food scrap waste with WAS, has become prevalent only in recent years and is still an active area of research. Food scrap waste is a consistent waste stream of high-density organic material in many developed countries, accounting for approximately 25% of landfill mass in the US7. Aside from diverting a portion of food scraps from disposal in landfills, the combination of food scraps and WAS in a co-digestion scenario is advantageous due to the increased volume of biogas produced (relative to a single organic waste stream). Biogas typically contains 60%-70% methane, 30%-40% carbon dioxide, and trace amounts of other gases (e.g., hydrogen sulfide)8. The biogas can be cleaned and combusted onsite at WWTPs using a combined heat and power technology to offset some of the electrical and heat energy requirements9.
Several studies have examined the biomethanation potential and biokinetic parameters of anaerobic microbiota co-digesting organic wastes1. Available studies in the literature have used batch assays in serum bottles where methane production is measured at discrete points throughout the experiment, while others have measured methane production using flowmeters connected directly to bench- or pilot-scale bioreactors2,10,11. Continuous measurement of methane production using a respirometer, such as the one described in this protocol, can provide continuous and precise methane measurements from a large number of samples run under a variety of experimental conditions1,12. While several studies have measured methane production from co-digestion of WAS coupled with other organic substrates, such as biowaste, fats, oils, grease, and agricultural wastes10,13,14, significant work remains to identify methane production rates from the large variety of co-digestion scenarios. Further, to date, no available protocol provides an in-depth, step-by-step approach using visual depictions for the measurement of methane production from the co-digestion of food scraps and WAS. Accordingly, this study presents a respirometer protocol to measure methane production and derive biokinetic parameters using a mix of dilute wastewater, WAS, and food scrap waste as substrates. Different food-to-microorganism ratios (F:M) were used to help elucidate changes in methane production. Other measurements include volatile suspended solids (VSS), chemical oxygen demand (COD), and pH of each sample. This protocol describes respirometer setup, sample creation, and critical measurements.

<table><tbody><tr><td>103 &amp;deg;C Oven Isotemp</td><td>Fisher Scientific</td><td>13-247-737F</td><td>Model: 737F, Force Air Oven</td></tr><tr><td>550 &amp;deg;C Vulcan Oven</td><td>Neytech (Manufacturer) / Cole Palmer (Vendor)</td><td>9493308</td><td>Model: 3-550</td></tr><tr><td>Aerobic/Anaerobic Respirometer</td><td>Respirometer System and Applications (RSA)</td><td>PF-8000</td><td>Model: PF-8000</td></tr><tr><td>Analytical Balance</td><td>Mettler Toledo</td><td>30029075</td><td>Model: ME204E, Detection Limit: 0.1 mg</td></tr><tr><td>Smoothie Blender with 56 oz Plastic Jar</td><td>Hamilton Beach</td><td>50190F</td><td>Model: 50190F</td></tr><tr><td>COD Vials TNT Plus Vial Test</td><td>HACH</td><td>TNT821</td><td>TNT 821, 3&amp;ndash;150 mg/L COD</td></tr><tr><td>COD Vials TNT Plus Vial Test</td><td>HACH</td><td>TNT822</td><td>TNT 822, 20&amp;ndash;1500 mg/L COD</td></tr><tr><td>Dessicator</td><td>SP Bel-Art</td><td>942070050</td><td>Model: SP Scienceware</td></tr><tr><td>Dionized Water System</td><td>Milli-Q</td><td>ZIQ7010T0C</td><td>IQ 7010 Pure &amp;amp; Ultrapure Water Purification System</td></tr><tr><td>Anhydrous CaSO&lt;sub&gt;4&lt;/sub&gt;</td><td>W.A. Hammond Drierite Company</td><td>13001</td><td>8 Mesh, 1 lb</td></tr><tr><td>Glass Fiber Filters</td><td>Whatman (Manufacturer) / Cole-Parmer (Vendor)</td><td>1827-150</td><td>Model: 934-AH</td></tr><tr><td>Heat Digestor Block</td><td>HACH</td><td>DRB200-02</td><td>DRB 200</td></tr><tr><td>Hot Plate Stirrer</td><td>Corning</td><td>6795-620D</td><td>Model: PC-620D</td></tr><tr><td>Industrial-Grade Nitrogen (Compressed Cylinder)</td><td>Air Gas</td><td>NI UHP300</td><td>300 cubic feet</td></tr><tr><td>Pellets (KOH)</td><td>Fisher Scientific</td><td>AC134062500</td><td>500 g</td></tr><tr><td>pH Meter</td><td>Fisher Scientific</td><td>13-636-AP115</td><td>AP115, Accumet pH meter</td></tr><tr><td>UV Spectrophotometer</td><td>HACH</td><td>LPV400.99.00012</td><td>DR 3900</td></tr><tr><td>Vaccum Pump</td><td>GAST</td><td>1HAB-25-M100X</td><td></td></tr></tbody></table>

measuring biomethane potential of food scrap waste anaerobically co&#45;digested with waste&#45;activated sludge using respirometry

The use of respirometry to study the biokinetics of microbiota treating wastewater or digesting wastewater sludges has become more prevalent over the last few decades. The use of respirometry to examine the biokinetics of anaerobic microbiota co-digesting organic waste streams such as wastewater sludge and food scrap is an area of active research. To date, no visualized protocol has been published on the topic. Accordingly, in this protocol, we configured a respirometer to measure methane production and flow rate over time using three different food-to-microorganism (F:M) ratios and food scrap waste and waste-activated sludge as substrates. The resulting data, coupled with substrate utilization measurements, provides the basis for understanding how different substrate concentrations influence the rate at which anaerobic microbiota produce methane. Additionally, this protocol presents a method to develop biokinetic parameters (e.g., methane production rate constant and yield). Others can use this respirometry protocol to examine organic degradation under anaerobic conditions and develop microbial parameters.

Food waste composition 
Food waste used in this study consisted of five different food types typically served at a college dining facility. Each food sample had varying amounts of fats, carbohydrates, and proteins, which are listed in Table 2.19 The blended food scrap waste was 44% carbohydrates, 36% proteins, 16% fats, and 4% other materials. An approximate equal mass of each food type (56 g to 86 g) was used to provide a representative dining facility organic substrate for anaerobic co-digestion. The mass of food scrap waste was subsequently varied to achieve the desired F:M for each scenario examined (0.3, 0.7, and 1.1).
Volatile suspended solid and organic measurements 
Results for initial and final VSS and initial and final oxygen demand are found in Table 3. Oxygen demand is presented as BOD5, which was converted from COD using the accepted conversion ratio (COD = 1.6BOD5)8. As shown, initial VSS concentrations (also portrayed by mass in Table 3) increased from the control to the largest F:M ratio (1.1). Each F:M examined exhibited VSS destruction, or anaerobic conversion of organics to gaseous end-products of methane and carbon dioxide. Due to the conversion, the concentration of VSS decreased from initial measurements to final measurements taken at the end of the experiment. The amount of VSS destroyed increased from the control to larger F:M ratios. Unexpectedly, VSS destruction for the F:M = 0.7 scenario exceeded the F:M = 1.1 scenario, perhaps due to inhibition in the F:M of 1.1 scenario.
Measured initial oxygen demand concentrations followed the same trend as VSS, i.e., increased from the control to the largest F:M ratio (Table 3). Similar to VSS destruction, BOD5 concentrations decreased between initial and final concentrations, with the exception of the control. The oxygen demand increased in the control, likely due to endogenous decay. Unlike VSS destruction, the reduction in oxygen demand from the initial to the final measurement was relatively low for each sample, ranging between 1 and 3%, and showing no trend by F:M ratio. A possible reason for this trend is the conversion of particulate organic matter to soluble organics, which takes place over long timeframes and is often a rate-limiting step in the metabolism of the anaerobic microbial consortia20.
Methane production 
Quantities and rates of methane production varied over the range of F:M ratios during the 190-hour study period. Experimental results revealed that higher F:M ratios yielded increased overall volumes of methane (Figure 7). The control, to which no substrate was added, produced a small amount of methane (~72 mL) likely due to the relatively small amount of soluble BOD5 in the sludge and/or endogenous decay. As anticipated, the addition of substrate in other scenarios increased methane production relative to the control. The F:M of 0.3 scenario yielded five times more methane, by volume (~354 mL), than the control. Increasing the F:M ratio to 0.7 yielded 1.6 times more methane (~574 mL) than the F:M of 0.3 scenario. Similarly, increasing the F:M ratio to 1.1 yielded 1.9 times more methane (~1098 mL) than the F:M of 0.7 scenario. Maximum observed volumetric methane production values (Ymax) for each F:M ratio examined are listed in Table 4. The rate of methane produced over time also changed with the F:M ratios examined. As shown in Figure 8, the rate of methane production, as well as the length of time during the study that methane was produced, increased as the F:M increased. For example, in the F:M of 0.3 scenario, there was no observed methane production after 129 h of study (with a max of 354 mL), while the F:M of 1.1 scenario was still producing a small amount of methane at the end of the study. In all scenarios, the rate of methane produced decreased over time due to reduced substrate availability. While there was still abundant oxygen demand available at the end of the study (Table 3), it may not have been in a bioavailable form, or there may have been limited remaining electron acceptor (e.g., carbon dioxide) for the anaerobic microbiota. Last, a comparison of methane produced (mL) per observed VSS destroyed (mg) shows that the values for F:M of 0.3 and 0.7 provided a range of 1.3 to 1.6 mL/mg, while the F:M of 1.1 produced more methane per unit VSS destroyed (3.7 mL/mg) (Table 4). Tchobanoglous et al. (2014) provides typical ranges for gas yield per unit solids destroyed for common feedstocks, to include fats (~1.4 mL/mg), grease (~1.1 mL/mg), and protein (~0.7 mL/mg)8. Mata-Alvarez et al. (2014) reviewed studies co-digesting wastewater sludge with a variety of substrates, and different substrate ratios (e.g., different ratios of WAS and FOG), in bench-scale and pilot-scale bioreactors10. They found that reported methane production per unit VSS destroyed varied substantially with the substrates co-digested, as well as the ratio of substrates, ranging from 0.2 mL to 1.1 mL of biogas per mg VS destroyed. Representative results from this study, especially for F:M of 0.3 and 0.7 compare favorably to results of comparison studies.
Biokinetic parameters 
Methane production over time can be used to determine several important biokinetic parameters. These biokinetic parameters can be further leveraged to predict methane production in similar scenarios without the use of the respirometer. The methane production rate constant, k, can be derived using a logarithmic least square fitting to observed respirometer data for each F:M ratio examined (i.e., those shown in Figure 8). A representative logarithmic function for the F:M of 0.3 scenario is y = 93.465ln(X) - 175.91. Here, the value of 93.465 is in units of hours, which must be converted to days and then inversed, giving a k = 0.257. Rate constants (k) and the coefficient of determination (R2) for each F:M ratio examined are found in Table 4.
The rate constant can then be leveraged to determine the yield of methane at any given time for each F:M ratio. The rate of methane produced over time from the organic substrate can be modeled using the following equation [1]21:
(1)&#160; &#160; &#160;&#160;<img alt="Equation 1" src="/files/ftp_upload/66485/66485eq01.jpg" style="margin: auto;" />
Integrating the above equation between the limits t = 0 to t = t, gives the following [2]:
(2)&#160; &#160; &#160;&#160;<img alt="Equation 2" src="/files/ftp_upload/66485/66485eq02.jpg" style="margin: auto;" />
Where, Y = methane yield at any time [mL]; Ymax = maximum observed methane yield from the respirometer study [mL]; k = methane production rate constant [d-1]; t = time [d]
While the first-order approach used to develop biokinetic parameters presented above provides a very reasonable fit to the experimental data (as indicated by R2 values in Table 4), other studies have reported the use of other models to fit methane production data, to include the Modified Gompertz model, two-substrate model, and the Cone model2.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66485/66485fig01.jpg" /> 
Figure 1: Food waste blender. Standard blender used to combine food waste. <a href="https://www.jove.com/files/ftp_upload/66485/66485fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/66485/66485fig02.jpg" /> 
Figure 2: Respirometer. Complete respirometer setup to measure methane production. <a href="https://www.jove.com/files/ftp_upload/66485/66485fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/66485/66485fig03.jpg" /> 
Figure 3: Sample bottle in respirometer chiller. Interior view of respirometer chiller with eight sample bottles. <a href="https://www.jove.com/files/ftp_upload/66485/66485fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/66485/66485fig04.jpg" /> 
Figure 4: Respirometer scrubber. Close view of respirometer scrubber. <a href="https://www.jove.com/files/ftp_upload/66485/66485fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/66485/66485fig05.jpg" /> 
Figure 5: Respirometer scrubber to control module. Respirometer image of the control module and scrubber setup. <a href="https://www.jove.com/files/ftp_upload/66485/66485fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/66485/66485fig06.jpg" /> 
Figure 6: Respirometer scrubber line setup. Close view of scrubber line setup between sample bottles and the respirometer. <a href="https://www.jove.com/files/ftp_upload/66485/66485fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/66485/66485fig07.jpg" /> 
Figure 7: Total methane production using different F:M ratios. Methane production for each F:M (0.3, 0.7, 1.1) is depicted over time (0 h to 190 h). <a href="https://www.jove.com/files/ftp_upload/66485/66485fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/66485/66485fig08.jpg" /> 
Figure 8: Methane production rate using different F:M ratios. Methane production rate for each F:M (0.3, 0.7, 1.1) is depicted over time (0 h to 190 h). <a href="https://www.jove.com/files/ftp_upload/66485/66485fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Table 1: Sample Bottle Constituents with Food-to-Microbe Ratios. Constituent mass, concentration, and volume for each F:M (0.3, 0.7, 1.1) and the blank bottles. <a href="https://www.jove.com/files/ftp_upload/66485/3_JoVE_Table 1.xlsx" target="_blank">Please click here to download this Table.</a>
Table 2: Sample Organic Substrate Composition. Food waste mass and percent composition by food&#160;and proportion of carbohydrates, proteins, and fats. <a href="https://www.jove.com/files/ftp_upload/66485/3_JoVE_Table 2.xlsx" target="_blank">Please click here to download this Table.</a>
Table 3: Sample Volatile Suspended Solid and Oxygen Demand Result (&#177; Standard Deviation). VSS and COD for each F:M (0.3, 0.7, 1.1). <a href="https://www.jove.com/files/ftp_upload/66485/3_JoVE_Table 3v2.xlsx" target="_blank">Please click here to download this Table.</a>
Table 4: Sample Kinetic Parameters. Calculated kinetic parameters based on methane yield. <a href="https://www.jove.com/files/ftp_upload/66485/3_JoVE_Table 4v2.xlsx" target="_blank">Please click here to download this Table.</a>

Read this Scientific Article Protocol about Author Spotlight: Advancing Anaerobic Microbiota Research Using a Novel Respirometry Protocol at JoVE.com

Author Spotlight: Advancing Anaerobic Microbiota Research Using a Novel Respirometry Protocol

This protocol describes a best practice for determining methane production and microbial kinetic parameters using respirometry for anaerobic microbiota co-digesting food scrap waste and waste-activated sludge.

Measuring Biomethane Potential of Food Scrap Waste Anaerobically Co&#45;Digested with Waste&#45;Activated Sludge Using Respirometry

The use of respirometry to study the biokinetics of microbiota treating wastewater or digesting wastewater sludges has become more prevalent over the last ...

measuring-biomethane-potential-food-scrap-waste-anaerobically-co

Research

JoVE Journal

Environment

1.1K Views.  United States Military Academy. This protocol describes a best practice for determining methane production and microbial kinetic parameters using respirometry for anaerobic microbiota co-digesting food scrap waste and waste-activated sludge.

Video: Author Spotlight: Advancing Anaerobic Microbiota Research Using a Novel Respirometry Protocol

Waste Water Derived Electroactive Microbial Biofilms: Growth, Maintenance, and Basic Characterization

The growth of anodic electroactive microbial biofilms from waste water inocula in a fed-batch reactor is demonstrated using a three-electrode setup controlled by a potentiostat. Thereby the use of potentiostats allows an exact adjustment of the electrode potential and ensures reproducible microbial culturing conditions. During growth the current production is monitored using chronoamperometry (CA). Based on these data the maximum current density (jmax) and the coulombic efficiency (CE) are discussed as measures for characterization of the bioelectrocatalytic performance. Cyclic voltammetry (CV), a nondestructive, i.e. noninvasive, method, is used to study the extracellular electron transfer (EET) of electroactive bacteria. CV measurements are performed on anodic biofilm electrodes in the presence of the microbial substrate, i.e. turnover conditions, and in the absence of the substrate, i.e. nonturnover conditions, using different scan rates. Subsequently, data analysis is exemplified and fundamental thermodynamic parameters of the microbial EET are derived and explained: peak potential (Ep), peak current density (jp), formal potential (Ef) and peak separation (&#916;Ep). Additionally the limits of the method and the state-of the art data analysis are addressed. Thereby this video-article shall provide a guide for the basic experimental steps and the fundamental data analysis.

Chronoamperometric growth of anodic electroactive microbial biofilms in a fed-batch reactor using a three-electrode setup, controlled by a potentiostat, is demonstrated. The extracellular electron transfer is characterized using cyclic voltammetry in the presence of the electron donor and in the absence of the electron donor. Fundamental data analysis is demonstrated.

The growth of anodic electroactive microbial biofilms from waste water inocula in a fed-batch reactor is demonstrated using a three-electrode setup ...

Methods for Facilitating Microbial Growth on Pulp Mill Waste Streams and Characterization of the Biodegradation Potential of Cultured Microbes

The kraft process is applied to wood chips for separation of lignin from the polysaccharides within lignocellulose for pulp that will produce a high quality paper. Black liquor is a pulping waste generated by the kraft process that has potential for downstream bioconversion. However, the recalcitrant nature of the lignocellulose resources, its chemical derivatives that constitute the majority of available organic carbon within black liquor, and its basic pH present challenges to microbial biodegradation of this waste material. Methods for the collection and modification of black liquor for microbial growth are aimed at utilization of this pulp waste to convert the lignin, organic acids, and polysaccharide degradation byproducts into valuable chemicals. The lignocellulose extraction techniques presented provide a reproducible method for preparation of lignocellulose growth substrates for understanding metabolic capacities of cultured microorganisms. Use of gas chromatography-mass spectrometry enables the identification and quantification of the fermentation products resulting from the growth of microorganisms on pulping waste. These methods when used together can facilitate the determination of the metabolic activity of microorganisms with potential to produce fermentation products that would provide greater value to the pulping system and reduce effluent waste, thereby increasing potential paper milling profits and offering additional uses for black liquor.

Industrial wastes can be collected and modified to analyze microbial growth. Lignocellulose extraction techniques provide components to analyze specific biodegradation ability. Gas chromatography-mass spectrometry identifies fermentation products of microorganisms grown on pulping waste. These methods determine the metabolic capacity of microorganisms to degrade pulping waste.

The kraft process is applied to wood chips for separation of lignin from the polysaccharides within lignocellulose for pulp that will produce a high ...

Tracking Microbial Contamination in Retail Environments Using Fluorescent Powder - A Retail Delicatessen Environment Example

Cross contamination of foodborne pathogens in the retail environment is a significant public health issue contributing to an increased risk for foodborne illness. Ready-to-eat (RTE) processed foods such as deli meats, cheese, and in some cases fresh produce, have been involved in foodborne disease outbreaks due to contamination with pathogens such as Listeria monocytogenes. With respect to L. monocytogenes, deli slicers are often the main source of cross contamination. The goal of this study was to use a fluorescent compound to simulate bacterial contamination and track this contamination in a retail setting. A mock deli kitchen was designed to simulate the retail environment. Deli meat was inoculated with the fluorescent compound and volunteers were recruited to complete a set of tasks similar to those expected of a food retail employee. The volunteers were instructed to slice, package, and store the meat in a deli refrigerator. The potential cross contamination was tracked in the mock retail environment by swabbing specific areas and measuring the optical density of the swabbed area with a spectrophotometer. The results indicated that the refrigerator (i.e. deli case) grip and various areas on the slicer had the highest risk for cross contamination. The results of this study may be used to develop more focused training material for retail employees. In addition, similar methodologies could also be used to track microbial contamination in food production environments (e.g.&#160;small farms), hospitals, nursing homes, cruise ships, and hotels.

The overall goal of this study was to demonstrate the potential cross contamination mechanism of foodborne pathogen Listeria monocytogenes in a retail deli setting. This methodology may be applied to a variety of different environments to track pathogen contamination. &#160;

Cross contamination of foodborne pathogens in the retail environment is a significant public health issue contributing to an increased risk for foodborne ...

Evaluation of Integrated Anaerobic Digestion and Hydrothermal Carbonization for Bioenergy Production

Lignocellulosic biomass is one of the most abundant yet underutilized renewable energy resources. Both anaerobic digestion (AD) and hydrothermal carbonization (HTC) are promising technologies for bioenergy production from biomass in terms of biogas and HTC biochar, respectively. In this study, the combination of AD and HTC is proposed to increase overall bioenergy production. Wheat straw was anaerobically digested in a novel upflow anaerobic solid state reactor (UASS) in both mesophilic (37 &#176;C) and thermophilic (55 &#176;C) conditions. Wet digested from thermophilic AD was hydrothermally carbonized at 230 &#176;C for 6 hr for HTC biochar production. At thermophilic temperature, the UASS system yields an average of 165 LCH4/kgVS&#160;(VS: volatile solids) and 121 L CH4/kgVS&#160;at mesophilic AD over the continuous operation of 200 days. Meanwhile, 43.4 g of HTC biochar with 29.6 MJ/kgdry_biochar was obtained from HTC of 1 kg digestate (dry basis) from mesophilic AD. The combination of AD and HTC, in this particular set of experiment yield 13.2 MJ of energy per 1 kg of dry wheat straw, which is at least 20% higher than HTC alone and 60.2% higher than AD only.

A novel Upflow Anaerobic Solid State (UASS) reactor was used for biogas production from fibrous feedstock. Digestate from UASS reactor was hydrothermally carbonized into HTC biochar in a pressurized batch reactor. The integration of the two bioenergy concepts was applied in this study to increase overall bioenergy production.

Lignocellulosic biomass is one of the most abundant yet underutilized renewable energy resources. Both anaerobic digestion (AD) and hydrothermal ...

Development of Sulfidogenic Sludge from Marine Sediments and Trichloroethylene Reduction in an Upflow Anaerobic Sludge Blanket Reactor

The importance of microbial sulfate reduction relies on the various applications that it offers in environmental biotechnology. Engineered sulfate reduction is used in industrial wastewater treatment to remove large concentrations of sulfate along with the chemical oxygen demand (COD) and heavy metals. The most common approach to the process is with anaerobic bioreactors in which sulfidogenic sludge is obtained through adaptation of predominantly methanogenic granular sludge to sulfidogenesis. This process may take a long time and does not always eliminate the competition for substrate due to the presence of methanogens in the sludge. In this work, we propose a novel approach to obtain sulfidogenic sludge in which hydrothermal vents sediments are the original source of microorganisms. The microbial community developed in the presence of sulfate and volatile fatty acids is wide enough to sustain sulfate reduction over a long period of time without exhibiting inhibition due to sulfide. 
This protocol describes the procedure to generate the sludge from the sediments in an upflow anaerobic sludge blanket (UASB) type of reactor. Furthermore, the protocol presents the procedure to demonstrate the capability of the sludge to remove by reductive dechlorination a model of a highly toxic organic pollutant such as trichloroethylene (TCE). The protocol is divided in three stages: (1) the formation of the sludge and the determination of its sulfate reducing activity in the UASB, (2) the experiment to remove the TCE by the sludge, and (3) the identification of microorganisms in the sludge after the TCE reduction. Although in this case the sediments were taken from a site located in Mexico, the generation of a sulfidogenic sludge by using this procedure may work if a different source of sediments is taken since marine sediments are a natural pool of microorganisms that may be enriched in sulfate reducing bacteria.

Microbial sulfate reduction is a process of great importance in environmental biotechnology. The success of the sulfidogenic reactors depends among other factors on the microbial composition of the sludge. Here, we present a protocol to develop sulfidogenic sludge from hydrothermal vents sediments in a UASB reactor for reductive dechlorination purposes.

The importance of microbial sulfate reduction relies on the various applications that it offers in environmental biotechnology. Engineered sulfate ...

How to Create Conditioned Taste Aversion for Grazing Ground Covers in Woody Crops with Small Ruminants

Conditioned taste aversion (CTA) is a learning behavior process where animals are trained to reject certain feed after gastrointestinal discomfort has been produced. Lithium chloride (LiCl) is the preferred agent used in livestock to induce CTA because it specifically stimulates the vomit center. In addition, LiCl is commercially available, and easy to prepare and administer using a drenching gun. Nevertheless, some factors have to be considered to obtain an effective long-lasting CTA, which allows small ruminants to graze during the cropping season. A key aspect is to use animals with no previous contact with the target plant (the plant chosen to be avoided; new feed). Due to their native neophobic feeding behavior, small ruminants can easily associate the negative feedback effects with the new feed, resulting in a strong and persistent CTA. The recommended doses are 200 and 225 mg LiCl/kg body weight (BW) for goats and sheep, respectively. To induce CTA, 100 g of the target plant should be individually offered for at least 30 min, and LiCl administered thereafter if the intake is greater than 10 g. Each time the animal eats the target plant without negative consequences, the CTA becomes weaker. Consequently, to minimize the risk of target plant consumption, it is essential to have sufficient palatable ground cover available. The presence of an alternative feed (of quality and quantity) prevents the accidental consumption of the target plant. A close monitoring of the flock is recommended to remove and re-dose any animal consuming more than 4 bites or 10 g of the target plant. At the beginning of each grazing season, check the CTA status of each animal before moving them to the crop.

Feeding behavior preferences in livestock can be modified to implement a grazing management plan in woody crops. Here, we present a protocol to show a lithium chloride dose after eating a new plant that induces conditioned taste aversion.

Conditioned taste aversion (CTA) is a learning behavior process where animals are trained to reject certain feed after gastrointestinal discomfort has ...

Continuously-stirred Anaerobic Digester to Convert Organic Wastes into Biogas: System Setup and Basic Operation

Anaerobic digestion (AD) is a bioprocess that is commonly used to convert complex organic wastes into a useful biogas with methane as the energy carrier 1-3. Increasingly, AD is being used in industrial, agricultural, and municipal waste(water) treatment applications 4,5. The use of AD technology allows plant operators to reduce waste disposal costs and offset energy utility expenses. In addition to treating organic wastes, energy crops are being converted into the energy carrier methane 6,7. As the application of AD technology broadens for the treatment of new substrates and co-substrate mixtures 8, so does the demand for a reliable testing methodology at the pilot- and laboratory-scale.
Anaerobic digestion systems have a variety of configurations, including the continuously stirred tank reactor (CSTR), plug flow (PF), and anaerobic sequencing batch reactor (ASBR) configurations 9. The CSTR is frequently used in research due to its simplicity in design and operation, but also for its advantages in experimentation. Compared to other configurations, the CSTR provides greater uniformity of system parameters, such as temperature, mixing, chemical concentration, and substrate concentration. Ultimately, when designing a full-scale reactor, the optimum reactor configuration will depend on the character of a given substrate among many other nontechnical considerations. However, all configurations share fundamental design features and operating parameters that render the CSTR appropriate for most preliminary assessments. If researchers and engineers use an influent stream with relatively high concentrations of solids, then lab-scale bioreactor configurations cannot be fed continuously due to plugging problems of lab-scale pumps with solids or settling of solids in tubing. For that scenario with continuous mixing requirements, lab-scale bioreactors are fed periodically and we refer to such configurations as continuously stirred anaerobic digesters (CSADs).
This article presents a general methodology for constructing, inoculating, operating, and monitoring a CSAD system for the purpose of testing the suitability of a given organic substrate for long-term anaerobic digestion. The construction section of this article will cover building the lab-scale reactor system. The inoculation section will explain how to create an anaerobic environment suitable for seeding with an active methanogenic inoculum. The operating section will cover operation, maintenance, and troubleshooting. The monitoring section will introduce testing protocols using standard analyses. The use of these measures is necessary for reliable experimental assessments of substrate suitability for AD. This protocol should provide greater protection against a common mistake made in AD studies, which is to conclude that reactor failure was caused by the substrate in use, when really it was improper user operation 10.

Laboratory-scale anaerobic digesters allow scientists to research new ways of optimizing existing applications of anaerobic biotechnology and to evaluate the methane producing potential of various organic wastes. This article introduces a generalized model for the construction, inoculation, operation, and monitoring of a laboratory-scale continuously stirred anaerobic digester.

Anaerobic digestion (AD) is a bioprocess that is commonly used to convert complex organic wastes into a useful biogas with methane as the energy carrier ...

Bioengineering

Medium Preparation for the Cultivation of Microorganisms under Strictly Anaerobic/Anoxic Conditions

In contrast to aerobic organisms, strictly anaerobic microorganisms require the absence of oxygen and usually a low redox potential to initiate growth. As oxygen is ubiquitous in air, retaining O2-free conditions during all steps of cultivation is challenging but a prerequisite for anaerobic culturing. The protocol presented here demonstrates the successful cultivation of an anaerobic mixed culture derived from a biogas plant using a simple and inexpensive method. A precise description of the entire anoxic culturing process is given including media preparation, filling of cultivation flasks, supplementation with redox indicator and reducing agents to provide low redox potentials as well as exchanging the headspace to keep media free from oxygen. Furthermore, a detailed overview of aseptically inoculating gas tight serum flasks (by using sterile syringes and needles) and suitable incubation conditions is provided. The present protocol further deals with gas and liquid sampling for subsequent analyses regarding gas composition and volatile fatty acid concentrations using gas chromatography (GC) and high performance liquid chromatography (HPLC), respectively, and the calculation of biogas and methane yield considering the ideal gas law.

As obligate anaerobic organisms are unable to grow upon oxygen exposure, the use of anaerobic culturing techniques is indispensable. Here, we demonstrate a simple and effective method to cultivate a mixed culture derived from a biogas plant from media preparation to gas and volatile fatty acid quantification.

In contrast to aerobic organisms, strictly anaerobic microorganisms require the absence of oxygen and usually a low redox potential to initiate growth. As ...

Biochemistry

Microalgal Cultivation for Biomethane Obtention from Swine Waste Biogas

Biogas Purification through the use of a Microalgae-Bacterial System in Semi-Industrial High Rate Algal Ponds

In recent years, a number of technologies have emerged to purify biogas into biomethane. This purification entails a reduction in the concentration of polluting gases such as carbon dioxide and hydrogen sulfide to increase the content of methane. In this study, we used a microalgal cultivation technology to treat and purify biogas produced from organic waste from the swine industry to obtain ready-to-use biomethane. For cultivation and purification, two 22.2 m3 open-pond photobioreactors coupled with an absorption-desorption column system were set up in San Juan de los Lagos, Mexico. Several recirculation liquid/biogas ratios (L/G) were tested to obtain the highest removal efficiencies; other parameters, such as pH, dissolved oxygen (DO), temperature, and biomass growth, were measured. The most efficient L/Gs were 1.6 and 2.5, resulting in a treated biogas effluent with a composition of 6.8%vol and 6.6%vol in CO2, respectively, and removal efficiencies for H2S up to 98.9%, as well as maintaining O2 contamination values of less than 2%vol. We found that pH greatly determines CO2 removal, more so than L/G, during cultivation because of its participation in the photosynthetic process of microalgae and its ability to vary pH when solubilized due to its acidic nature. DO, and temperature oscillated as expected from the light-dark natural cycles of photosynthesis and the time of day, respectively. Biomass growth varied with CO2 and nutrient feeding as well as reactor harvesting; however, the trend remained primed for growth.

Author Spotlight: Scaling Microalgal Biotechnology for Enhanced Biomethane Production 

Air pollution impacts the quality of life of all organisms. Here, we describe the use of microalgae biotechnology for the treatment of biogas (simultaneous removal of carbon dioxide and hydrogen sulfide) and the production of biomethane through semi-industrial open high-rate algal ponds and subsequent analysis of treatment efficiency, pH, dissolved oxygen, and microalgae growth.

In recent years, a number of technologies have emerged to purify biogas into biomethane. This purification entails a reduction in the concentration of ...

Analysis of Interactions between Endobiotics and Human Gut Microbiota Using In Vitro Bath Fermentation Systems

Human intestinal microorganisms have recently become an important target of research in promoting human health and preventing diseases. Consequently, investigations of interactions between endobiotics (e.g., drugs and prebiotics) and gut microbiota have become an important research topic. However, in vivo experiments with human volunteers are not ideal for such studies due to bioethics and economic constraints. As a result, animal models have been used to evaluate these interactions in vivo. Nevertheless, animal model studies are still limited by bioethics considerations, in addition to differing compositions and diversities of microbiota in animals vs. humans. An alternative research strategy is the use of batch fermentation experiments that allow evaluation of the interactions between endobiotics and gut microbiota in vitro. To evaluate this strategy, bifidobacterial (Bif) exopolysaccharides (EPS) were used as a representative xenobiotic. Then, the interactions between Bif EPS and human gut microbiota were investigated using several methods such as thin-layer chromatography (TLC), bacterial community compositional analysis with 16S rRNA gene high-throughput sequencing, and gas chromatography of short-chain fatty acids (SCFAs). Presented here is a protocol to investigate the interactions between endobiotics and human gut microbiota using in vitro batch fermentation systems. Importantly, this protocol can also be modified to investigate general interactions between other endobiotics and gut microbiota.

Described here is a protocol to investigate the interactions between endobiotics and human gut microbiota using in vitro batch fermentation systems.

Human intestinal microorganisms have recently become an important target of research in promoting human health and preventing diseases. Consequently, ...

Measuring Biomethane Potential of Food Scrap Waste Anaerobically Co-Digested with Waste-Activated Sludge Using Respirometry

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