• Feedstocks Analysed at Celignis
    Switchgrass

Background on Switchgrass

Switchgrass (Panicum virgatum L.) is an American C4 grass that is established from seeds, an advantage over Miscanthus which has to be propagated. The temperature for germination varies with clonal variety; from 5.5 to 10.9 degrees Celsius. The crop should be sown in May or June, flowering will probably occur in the late summer, and senescence in the autumn.

Switchgrass does well on a wide variety of soil types. It is drought tolerant and grows well on shallow rocky soils. It is also tolerant to wet areas. It can grow on sand to clay loam soils and tolerates soils with pH values ranging from 4.9 to 7.6.

There are various reports that switchgrass shows no response to N fertilizer or only to the first 50 kg. In fertile sites switchgrass may require little or no fertilisation, and, generally, will require less fertilisation than Miscanthus. Weeds, however, can be a major problem in establishment, and it is important that these are controlled in the first year, and totally removed before establishment. Insects can also decrease the effectiveness of establishment and result in a longer period needed before ceiling yields are obtained. There are also diseases that may decrease yields, for example the Panicum mosaic virus, or various leaf rusts (Puccinia spp.).

As with reed canary grass, conventional hay harvesting equipment can be used to harvest switchgrass. The crop usually needs to be harvested after senescence to prevent lodging losses, although such losses tend to be less than with reed canary grass. The effects of a delayed harvest on yields and chemical composition are likely to be less than those for Miscanthus, given that Switchgrass does not shed its leaves to the extent that Miscanthus x giganteus does.

While the crop can be harvested twice a year, a single harvest tends to give higher yields in temperate climates and will be more economic. Switchgrass yields generally increase yearly for the first three years before levelling-off in most varieties.

Analysis of Switchgrass at Celignis



Celignis Analytical can determine the following properties of Switchgrass samples:



Lignocellulosic Properties of Switchgrass

Cellulose Content of Switchgrass

Switchgrass tends to have a similar composition to Miscanthus, with cellulose being the main mass constituent. The cellulose content will be dependent on the productivity of the crop; shorter plants tend to have lower cellulose contents than taller, more productive, plants

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Hemicellulose Content of Switchgrass

As with Miscanthus, arabinoxylan is the main hemicellulose in switchgrass with xylose the most abundant hemicellulosic sugar.

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Lignin Content of Switchgrass

The lignin content of switchgrass will depend on what particular clonal variety is being grown as well as on the productivity of the crop. Smaller plants tend to have a greater leaf:stem mass ratio than taller plants and this means that the lignin and cellulose contents are typically lower whilst the extractives and ash contents are higher.

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Starch Content of Switchgrass

The starch content of switchgrass varies between the different anatomical components of the plant. Typically it is highest in the leaves, where photosynthesis takes place, and lower in the stems. The starch content can also vary according to the maturity of the plant.

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Uronic Acid Content of Switchgrass

Uronic acids are present in the hemicelluloses in switchgrass and are typically more abundant in the early-stages of growth. Furthermore, the concentrations of uronic acids tends to be greatest in the nodes, lower in the internodes, and at intermediate levels in the leaves.

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Enzymatic Hydrolysis of Switchgrass

We can undertake tests involving the enzymatic hydrolysis of Switchgrass. In these experiments we can either use a commercial enzyme mix or you can supply your own enzymes. We also offer analysis packages that compare the enzymatic hydrolysis of a pre-treated sample with that of the native original material.

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Bioenergy Properties of Switchgrass

Ash Content of Switchgrass

The ash content of switchgrass will vary according to the clonal variety and plant productivity.

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Heating (Calorific) Value of Switchgrass

Switchgrass can have an attractive heating value, however the effective heating value will depend on the moisture content of the crop.

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Ash Melting Behaviour of Switchgrass

Ash melting, also known as ash fusion and ash softening, can lead to slagging, fouling and corrosion in boilers which may reduce conversion efficiency. We can determine the ash melting behaviour of Switchgrass using our Carbolite CAF G5 BIO ash melting furnace. It can record the following temperatures:

Ash Shrinkage Starting Temperature (SST) - This occurs when the area of the test piece of Switchgrass ash falls below 95% of the original test piece area.

Ash Deformation Temperature (DT) - The temperature at which the first signs of rounding of the edges of the test piece occurs due to melting.

Ash Hemisphere Temperature (HT) - When the test piece of Switchgrass ash forms a hemisphere (i.e. the height becomes equal to half the base diameter).

Ash Flow Temperature (FT) - The temperature at which the Switchgrass ash is spread out over the supporting tile in a layer, the height of which is half of the test piece at the hemisphere temperature.



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Major and Minor Elements in Switchgrass

Examples of major elements that may be present in Switchgrass include potassium and sodium which are present in biomass ash in the forms of oxides. These can lead to fouling, ash deposition in the convective section of the boiler. Alkali chlorides can also lead to slagging, the fusion and sintering of ash particles which can lead to deposits on boiler tubes and walls.

We can also determine the levels of 13 different minor elements (such as arsenic, copper, and zinc) that may be present in Switchgrass.

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Analysis of Switchgrass for Anaerobic Digestion



Biomethane potential (BMP) of Switchgrass

At Celignis we can provide you with crucial data on feedstock suitability for AD as well as on the composition of process residues. For example, we can determine the biomethane potential (BMP) of Switchgrass. The BMP can be considered to be the experimental theoretical maximum amount of methane produced from a feedstock. We moniotor the volume of biogas produced allowing for a cumulative plot over time, accessed via the Celignis Database. Our BMP packages also involve routine analysis of biogas composition (biomethane, carbon dioxide, hydrogen sulphide, ammonia, oxygen). We also provide detailed analysis of the digestate, the residue that remains after a sample has been digested. Our expertise in lignocellulosic analysis can allow for detailed insight regarding the fate of the different biogenic polymers during digestion.



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Physical Properties of Switchgrass



Bulk Density of Switchgrass

At Celignis we can determine the bulk density of biomass samples, including Switchgrass, according to ISO standard 17828 (2015). This method requires the biomass to be in an appropriate form (chips or powder) for density determination.



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Particle Size of Switchgrass

Our lab is equipped with a Retsch AS 400 sieve shaker. It can accommodate sieves of up to 40 cm diameter, corresponding to a surface area of 1256 square centimetres. This allows us to determine the particle size distribution of a range of samples, including Switchgrass, by following European Standard methods EN 15149- 1:2010 and EN 15149-2:2010.



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Publications on Switchgrass By The Celignis Team

Hayes, D. J. M. (2011) Analysis of Lignocellulosic Feedstocks for Biorefineries with a Focus on The Development of Near Infrared Spectroscopy as a Primary Analytical Tool, PhD Thesis832 pages (over 2 volumes)

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The processing of lignocellulosic materials in modern biorefineries will allow for the production of transport fuels and platform chemicals that could replace petroleum-derived products. However, there is a critical lack of relevant detailed compositional information regarding feedstocks relevant to Ireland and Irish conditions. This research has involved the collection, preparation, and the analysis, with a high level of precision and accuracy, of a large number of biomass samples from the waste and agricultural sectors. Not all of the waste materials analysed are considered suitable for biorefining; for example the total sugar contents of spent mushroom composts are too low. However, the waste paper/cardboard that is currently exported from Ireland has a chemical composition that could result in high biorefinery yields and so could make a significant contribution to Irelandís biofuel demands.

Miscanthus was focussed on as a major agricultural feedstock. A large number of plants have been sampled over the course of the harvest window (October to April) from several sites. These have been separated into their anatomical fractions and analysed. This has allowed observations to be made regarding the compositional trends observed within plants, between plants, and between harvest dates. Projections are made regarding the extents to which potential chemical yields may vary. For the DIBANET hydrolysis process that is being developed at the University of Limerick, per hectare yields of levulinic acid from Miscanthus could be 20% greater when harvested early compared with a late harvest.

The wet-chemical analysis of biomass is time-consuming. Near infrared spectroscopy (NIRS) has been developed as a rapid primary analytical tool with separate quantitative models developed for the important constituents of Miscanthus, peat, and (Australian) sugarcane bagasse. The work has demonstrated that accurate models are possible, not only for dry homogenous samples, but also for wet heterogeneous samples. For glucose (cellulose) the root mean square error of prediction (RMSEP) for wet samples is 1.24% and the R2 for the validation set ( ) is 0.931. High accuracies are even possible for minor analytes; e.g. for the rhamnose content of wet Miscanthus samples the RMSEP is 0.03% and the is 0.845. Accurate models have also been developed for pre-treated Miscanthus samples and are discussed. In addition, qualitative models have been developed. These allow for samples to be discriminated for on the basis of plant fraction, plant variety (giganteus/non-giganteus), harvest-period (early/late), and stand-age (one-year/older).

Quantitative NIRS models have also been developed for peat, although the heterogeneity of this feedstock means that the accuracies tend to be lower than for Miscanthus. The development of models for sugarcane bagasse has been hindered, in some cases, by the limited chemical variability between the samples in the calibration set. Good models are possible for the glucose and total sugars content, but the accuracy of other models is poorer. NIRS spectra of Brazilian bagasse samples have been projected onto these models, and onto those developed for Miscanthus, and the Miscanthus models appear to provide a better fit than the Australian bagasse models.

Zambare, V. P., Zambare, A. V., Muthukumarappan, K., Christopher, L. P. (2011) Potential of thermostable cellulases in the bioprocessing of switchgrass to ethanol, BioResources 6(2): 2004-2020

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Switchgrass (Panicum virgatum), a perennial grass native to North America, is a promising energy crop for bioethanol production. The aim of this study was to optimize the enzymatic saccharification of thermo-mechanically pretreated switchgrass using a thermostable cellulase from Geobacillus sp. in a three-level, four-variable central composite design of response surface methodology. Different combinations of solids loadings (5 to 20%), enzyme loadings (5 to 20 FPU g-1 DM), temperature (50 to 70 oC), and time (36 to 96 h) were investigated in a total of 30 experiments to model glucose release from switchgrass. All four factors had a significant impact on the cellulose conversion yields with a high coefficient of determination of 0.96. The use of higher solids loadings (20%) and temperatures (70 oC) during enzymatic hydrolysis proved beneficial for the significant reduction of hydrolysis times (2.67-times) and enzyme loadings (4-times), with important implications for reduced capital and operating costs of ethanol production. At 20% solids, the increase of temperature of enzymatic hydrolysis from 50 oC to 70 oC increased glucose concentrations by 34%. The attained maximum glucose concentration of 23.52 g L-1 translates into a glucose recovery efficiency of 46% from the theoretical yield. Following red yeast fermentation, a maximum ethanol concentration of 11 g L-1 was obtained, accounting for a high glucose to ethanol fermentation efficiency of 92%. The overall conversion efficiency of switchgrass to ethanol was 42%.





Examples of Other Feedstocks Analysed at Celignis



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