- Open Access
Rheology of transgenic switchgrass reveals practical aspects of biomass processing
© The Author(s) 2018
- Received: 12 September 2017
- Accepted: 21 February 2018
- Published: 1 March 2018
Mechanical properties of transgenic switchgrass have practical implications for biorefinery technologies. Presented are fundamentals for simple (thermo)mechanical measurements of genetically transformed switchgrass. Experimental basics are provided for the novice, where the intention is to promote collaboration between plant biologists and materials scientists.
Stem sections were subjected to two stress modes: (1) torsional oscillation in the linear response region, and (2) unidirectional torsion to failure. Specimens were analyzed while submerged/saturated in ethylene glycol, simulating natural hydration and allowing experimental temperatures above 100 °C for an improved view of the lignin glass transition. Down-regulation of the 4-Coumarate:coenzyme A ligase gene (reduced lignin content and altered monomer composition) generally resulted in less stiff and weaker stems. These observations were associated with a reduction in the temperature and activation energy of the lignin glass transition, but surprisingly with no difference in the breadth and intensity of the tan δ signal. The results showed promise in further investigations of how rheological methods relate to stem lignin content, composition, and functional properties in the field and in bioprocessing.
Measurements such as these are complicated by small specimen size; however, torsional rheometers (relatively common in polymer laboratories) are well suited for this task. As opposed to the expense and complication of relative humidity control, solvent-submersion rheological methods effectively reveal fundamental structure/property relationships in plant tissues. Demonstrated are low-strain linear methods, and also nonlinear yield and failure analysis; the latter is very uncommon for typical rheological equipment.
- Glass transition
- Switchgrass (Panicum virgatum)
Switchgrass (Panicum virgatum), a perennial warm season grass native to North America, has been identified as important for development into an herbaceous biomass fuel crop [1–3]. Such crops should efficiently release sugars from cell wall polysaccharides through (bio)chemical conversion. Lignin has complex associations with polysaccharides, and its presence limits the accessibility of plant cell wall polysaccharides to chemical, enzymatic and microbial digestion [1–3]. The lignin content of feedstocks has been proposed as one key agronomic trait affecting biofuel production from lignocellulosic biomass. To improve biomass fermentability, genetic modifications aiming to lower lignin content and modify lignin structure have been extensively developed [4–7]. Besides sugar accessibility, such modifications could impact plant viability as well as the practical aspects of biomass handling and processing [1, 5, 8]. In light of these issues, it is appropriate to develop rheological methods that reveal how plant tissue mechanical properties are affected in genetically modified switchgrass with reduced lignin content.
Rheology is the study of deformation and flow in materials, both liquids and solids. Carefully measured deformations reveal insights about molecular structure, hierarchical organization, and aspects of material processing . Dynamic mechanical analysis (DMA) is one common rheological method involving application of an oscillating stress or strain, and measurement of the resulting strain or stress. The DMA response in polymeric materials is viscoelastic; it is simultaneously elastic like a spring, and viscous like flowing water. However, in viscoelastic solids, the viscous response is not macroscopic liquid flow, but rather localized flow as when lignin segments rub and slip past one another in dissipation of mechanical energy. If carefully conducted, the DMA of lignocellulose may be used to reveal insights about the structure and organization of cellulose, hemicelluloses, and lignin. Most of this type of research has been devoted to wood, with examples such as [10–14]. Given the variety of polymers and the complexity of their organization in lignocellulose, it is interesting to note that lignocellulose exhibits only one major thermomechanical softening transition, a glass-to-rubber transition attributed to lignin . The in situ lignin glass transition is quite sensitive to moisture levels, meaning that moisture control is a very practical experimental concern . In the present work, switchgrass specimens were analyzed while immersed/saturated in ethylene glycol. This approach simulates natural hydration in the living plant, provides a broader experimental temperature range (compared to water), and is quite simple in comparison to relative humidity control . Chowdhury et al. demonstrated that the thermorheological response of switchgrass stem is quite similar to that of wood, and tissue maturity effects are easily detected . The objectives of this paper are to demonstrate solvent-submersion rheological methods that reveal whole-tissue mechanical properties that reflect genetic lignin modifications, and to provide experimental details that help biologists collaborate with materials scientists. The intention is to address practical experimental challenges that help those interested in biomass rheology. Others have studied the rheological properties of transgenic lignocellulose using tension or bending stress modes [15–18]. We suggest that the torsional stress mode (torsional axis parallel to the plant stem, and specimen clamped under a minor tensile stress) offers advantages for the analysis of small lignocellulose samples. This so-called tensile–torsion analysis was discussed in . In the work described here, switchgrass specimens were subjected to DMA that was carefully restricted to the linear viscoelastic region. Additionally, a novel unidirectional continuous stress-ramp was imposed such that switchgrass stem sections underwent yielding and failure. The properties measured could have implications for plant viability in the field, and for aspects of biomass processing.
Selection of RNAi:4CL transgenic switchgrass plants
Tissue collection and stem sample preparation
Tillers with an elongation stage of four internodes were freshly harvested from all switchgrass plants at soil level and then divided into different parts according to the location of the internodes . The internode closest to the soil was labeled as the first internode. The second internode, which is positioned adjacent to the first one and second from soil level, was selected for analysis. Within the second internode, the stem was sectioned into small pieces with lengths of 2–3 cm. The 2- to 3-cm-long sections (hollow cylinders) were cut along the stem length and subsequently cut into rectangular shapes with widths between 3 and 5 mm. The thicknesses of the specimens ranged from 0.7 to 1.0 mm. For each plant specimen, at least three tillers (second internode) were obtained from three individual plants, and rectangular sections from a single plant were randomized into one batch. After rectangular sections were prepared, they were immediately transferred into ethylene glycol, vacuum-treated (20 Torr) for 30 min, followed by vacuum release and solvent immersion at atmospheric pressure for at least 48 h. After this solvent saturation, all specimens were stored at 12 °C.
Great care was exerted to ensure that dynamic (oscillatory) experiments were conducted within the linear viscoelastic response (LVR). More elaboration appears later, but the LVR is the low-strain response region where the stress and strain exhibit a linear relationship. At much higher strains, the stress/strain response becomes nonlinear. The LVR is typically defined using frequency sweep experiments (fixed stress applied over a range of oscillation frequencies) and stress sweep experiments (fixed oscillation frequency applied over a range of stress). In the present case, this typically involved numerous frequency sweep and stress sweep experiments conducted (on sacrificial specimens) at the temperature extremes, 25 and 120 °C. Frequency sweeps were typically conducted from 0.01 to 10 Hz; stress sweeps were typically conducted from 5000 to 60,000 Pa. Dynamic stress/strain plots were fitted to a line and the LVR stress limit was defined as the stress beyond which the correlation coefficient (R2 for the least squares fit) was less than 0.99995.
Once typical LVR behavior was established, separate specimens were subjected to temperature ramp experiments as follows: (1) equilibrate, 25 °C, 5 min, (2) stress sweep, 5000–50,000 Pa, 0.5 Hz, 25 °C, (3) heat, 25–120, 2 °C/min, 0.5 Hz, 50,000 Pa, (4) equilibrate, 120 °C, 5 min, (5) stress sweep, 5000–50,000 Pa, 0.5 Hz, 120 °C, (6) cool, 120–25, 2 °C/min, 0.5 Hz, 50,000 Pa. Stress sweeps were conducted at the temperature extremes before and after the temperature ramps to further verify that all analyses were conducted within the LVR.
Time–temperature superposition (TTS)
TTS experiments were conducted as a series of isothermal frequency sweeps as follows: (1) rapidly heat to 120 °C; equilibrate 5 min, (2) cool, 120–25, 2 °C/min, 50,000 Pa, 0.5 Hz, (3) rapidly heat to 120 °C; equilibrate 5 min, (4) isothermal frequency sweep, 0.05–0.5 Hz, 50,000 Pa, 120 °C, (5) reduce temperature by 5 °C; equilibrate 5 min; isothermal frequency sweep, 0.05–0.5 Hz, 50,000 Pa, (6) repeat step 5 to obtain isothermal frequency sweeps from 110 to 25 °C, (7) rapidly heat to 120 °C; equilibrate 5 min, (8) cool, 120–25, 2 °C/min, 50,000 Pa, 0.5 Hz. Note that cooling ramps were conducted before and after the sequential isothermal frequency sweeps as a means to determine if any substantial thermal degradation occurred during this analysis.
Torsional shear strength
Unidirectional torsional stress ramps were conducted until specimen failure. During analysis, the specimen was clamped in a similar fashion as above, but without solvent submersion (specimens were saturated in ethylene glycol as above). All experiments were conducted at ambient temperature (~ 22 °C). The AR-G2 rheometer was operated in continuous unidirectional displacement with a shear stress increasing from 100,000 to 100,000,000 Pa, using linear mode data acquisition over a 33-min period collecting 300 data points.
JMP® software was employed for pair-wise non-parametric Wilcoxon analysis.
In DMA, a specimen is subjected to an oscillatory stimulus (stress or strain) and the corresponding mechanical response (strain or stress) is measured. In plant tissues and other viscoelastic materials, the oscillatory response contains two components: the storage modulus and the loss modulus. The former relates to elastic energy storage as in a Hookean spring, and the latter deals with viscous energy dissipation as in a dashpot filled with a simple Newtonian liquid [20, 21]. A principal concern in DMA is verified operation within the linear viscoelastic response (LVR), the low-strain region where stress and strain are linearly related, where results are independent of input levels (stress or strain) and mathematical descriptions of the raw data are well understood [20–22]. Operating within the LVR allows an accurate accounting of energy storage and energy loss phenomena upon which structural models and structure/property relationships are confidently developed.
The LVR limit was arbitrarily defined as the maximum stress in which a linear fit to the stress/strain plot provided a correlation coefficient (R2) not less than 0.99995. Figure 4 demonstrates that this criterion was very conservative; in other words for this specimen, a safely linear response extended beyond the LVR limit defined here. The maximum oscillation frequency (0.5 Hz) and maximum oscillation stress (50,000 Pa) settings used in this work were conservatively restricted to assure operation within the LVR and therefore provide confidence in data interpretation among all plants studied. Others might safely select less conservative acquisition parameters. As a practical matter, DMA signal-to-noise tends to increase with increasing stress levels. Consequently, one would wish to operate at the highest possible stress level that remains within the LVR. However, the LVR behavior of biomass can be highly variable as demonstrated in Liriodendron tulipifera wood by . Consequently, we elected to remain conservatively within the LVR and at times this resulted in poor signal-to-noise, as will be discussed later.
Probability values (p values) from the transgene (+) and the transgene (−) pooled intergroup comparison of storage moduli (25 and 120 °C); number of observations = 20–25
p value (+) vs (−)
Average glass transition (Tg), tan δ maxima (tan δ max), and width of the tan δ signal at half-maximum (width) for pooled (+) and (−) samples (determined through curve fitting as described); number of measurements n = 9–12, standard deviations in parentheses
tan δ max
p value (+) vs (−)
Activation energy associated with the glass transition for specimens 40+ (n = 6) and 18− (n = 4)
Activation energy (kJ/mol)
Yield stress and shear strength for samples 18− (n = 4) and 40+ (n = 3)
Yield stress (Pa)
Shear strength (Pa)
6.35 × 106
3.14 × 107
(1.53 × 106)
(8.13 × 106)
1.67 × 106
1.28 × 107
(6.17 × 105)
(1.88 × 106)
As mentioned, RNAi:Pv4CL1 transgene positive plants were previously shown to yield more fermentable sugar, and this was attributed to a reduced content and altered monomer composition of lignin . The corresponding thermomechanical effects were detected as reductions in stiffness, strength, and also as reductions in the temperature and activation energy of the lignin glass transition. Surprisingly, the intensity (tan δ max) and breadth (width) of the glass transition in transgene positive and negative plants were not significantly different, perhaps because the RNAi:Pv4CL1 transgene did not affect the number of lignin/polysaccharide covalent attachments. This hypothesis requires testing, but any hypothesis must be grounded upon rigorous satisfaction of the LVR criterion where simple Hookean springs and Newtonian dashpots can be confidently equated to hypothetical molecular features of the cell wall. Repeated emphasis of the LVR criterion is perhaps tiresome for experienced rheologists, but this point is rarely emphasized in the literature. More importantly, the lesson is invaluable for beginners, and for collaborations among materials scientists and plant biologists, who should remind the rheologist that LVR behavior in plant tissues is highly variable .
Even experienced rheologists will appreciate the novelty of specimen yielding and failure analysis (strength testing) conducted here (Fig. 12), and this speaks to the unique suitability of rotational rheometers for the analysis of small plant tissues. The torsional stress mode has an unlimited strain capacity, and the small switchgrass specimens were weak enough to load through yielding and failure. Combined with linear DMA, this nonlinear strength testing provides much more information from one simple approach. Furthermore, a quick change to the parallel-plate geometry allows one to analyze specimens that lack mechanical integrity, such as fibrous mats resulting from biomass pretreatment . Stress-controlled torsional rheometers are also easily fashioned with solvent-submersion capabilities, whereas traditional bending/tensile-mode DMA machines require more specialized equipment. Solvent-submersion analysis is one convenient way to address the need for maintaining specimen moisture (or plasticizer) control. Whereas relative humidity control is more expensive and less convenient, but absolutely required for certain purposes.
The examples presented herein demonstrate that lignin alterations (that improve glucose accessibility) are associated with changes in the lignin glass transition, as well as reductions in tissue stiffness and strength. These effects could possibly reduce energy requirements for milling plant tissues prior to chemical pretreatments. The corresponding impact on lodging and plant viability is unknown. However, antisense 4CL poplar (Populus sp.) lines exhibited wood with reduced stiffness and strength; and field-grown plants that were not staked were phenotypically smaller than wild-type plants . Obviously, the relationships between rheological behavior determined here and the actual impacts on plant viability and energy requirements for biomass milling need to be determined. Touched upon here are lignocellulose structure/property relationships that will impact biorefinery technologies, and the need to refine these methods and actually correlate them to practical concerns is apparent. Once these correlations are established, we believe that these rheological methods could help accelerate the development of biorefinery technologies.
Rheology of plant tissues is extremely valuable to help molecular biologists understand the thermomechanical effects resulting from the genetic transformations they devise. In this example, down-regulation of Pv4CL1 caused lignin modifications that increased fermentable sugar yields; and this was associated with reductions in the lignin glass transition temperature and activation energy, as well as reductions in plant stem stiffness and strength. Fundamental experimental details were outlined to benefit newcomers to plant tissue rheology, and to help plant biologists master the simple yet critical questions they should ask when collaborating with polymer rheologists. Data quality and rigorous adherence to linear viscoelastic analysis were emphasized so that plant cell wall molecular models are created on a sound theoretical foundation. A novel nonlinear analysis was demonstrated that provides yielding and failure data (strength testing) that is atypical for highly sensitive rheological equipment. This novelty was attributed to the torsional rheometer, and a strong case was made for the unique suitability of the torsional rheometer for rheology of very small plant tissues.
TF provided switchgrass specimens under BZ’s supervision. CF supervised GW, who developed all rheological methods, collected 70% of the data, and supervised JJ, NSF REU student, who collected 30% of the data described herein. GW and CF wrote the manuscript. All authors read and approved the final manuscript.
The project was supported by USDA-NIFA Grant Number 2011-67009-30133 and by the National Science Foundation (REU: Bioprocess Engineering for Sustainability; award #1156645). Partial support was provided by the Wood-Based Composites Center, a National Science Foundation Industry/University Cooperative Research Center (Award #1035009). Partial funding was also supplied by the Virginia Agricultural Experiment Station and the McIntire Stennis Program of the National Institute of Food and Agriculture, US Department of Agriculture. Open access fees were provided by Virginia Tech’s Open Access Subvention Fund.
The authors declare that they have no competing interests.
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