Pretreatment Field Guide

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Particle length distributions fits for different samples j S1, k S2, l S3, at different EH times m 0 h, n 16 h, o h. Scale bar is 5 mm. The normalized PLD are presented in Figure 3. In Table 2 the results of PLD fits are presented. In Figure 3, the evolution of these populations with EH time is presented. The evolution of particle length based on EH time for each pretreatment is presented in Figures 3 j— 3 l and cross comparison between pretreatments is presented in Figures 3 m— 3 o.

In sample S1 Fig. In S2 Fig. Apart from particle length, also population size can be investigated by examining the area parameters a 1 and a 2. In S1, small particles contribution increased from 0. For S2, corresponding contribution was 0. This demonstrates that at the end of EH the small particles population in S1 did not increase to the same degree as in S2 and S3 and this can be also visualized in graphs Figure 3o , where the curves of small and big particles of S2 and S3 tend to fuse at h whereas in S1 large and small particles curves remained well separated and distinct.

All these observations indicate that EH and consequently pretreatment were not as efficient for S1 as it was for S2 and S3, even if the same enzyme cocktail was used.

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Interestingly, large particles with lengths in the order of mm, were still present at the end of EH Fig. Therefore, these particles do not contribute to the cellulose conversion, limiting the efficiency of the overall process of ethanol production. Future detailed studies on such particles could provide information on the limitation of pretreatment and EH.

Chemical composition analysis on single samples showed that insoluble glucan and xylan declined while glucose and xylose increased during EH Supplementary Table 2. The gold standard method for characterization and chemical quantification of biomass bioconversion to monosugars is HPLC Sluiter et al. Although powerful, it does not provide morphological information of the particles of a sample.

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Morphological information, acquired through imaging, is important for understanding the process of EH and more importantly for studying recalcitrance, since it has emerged as an important hindering factor in bioconversion Zeng et al. In this study, we pursued to demonstrate that morphological information can be used to not only investigate the local morphology of a particle but also to fully characterize a sample. This was accomplished with the LFOV methodology.

We showed that a two-population particle length model is adequate to characterize a biomass sample with good precision. Particle length was shown to be dependent on the severity of pretreatment Fig. Particle length was also shown to be dependent on EH time. For all three pretreatment conditions S1, S2, and S3 particle length shifted significantly to smaller values in the first 16 h of EH, while the size shift for the remaining EH period h was still significant but at a slower rate.

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Similar observations have been made on the chemical composition of hydrolyzed corn stover Zeng et al. Change in chemical composition is reflected in morphology and this was quantified by measuring particle length. Several models have been proposed for describing the effect of pretreatment and EH on the plant cell wall Chapple et al. In this study, we have visualized morphology and quantified key morphological characteristics of pretreated hydrolyzed corn stover biomass. By examining the evolution of this two-population particle size model we were able to monitor the evolution of particle size under different conditions and compare the results.

Particle length decreased significantly in the first 16 h of EH Based on chemical analysis Supplementary Table 2 glucan decreased Although, as expected, numbers regarding particle length and glucan content do not match exactly, they do indeed show a very similar trend, a big decrease at initial stages of EH and a smaller decrease at later stages, therefore they are related.

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What is different regarding particle length and glucan content is that glucan content decreased more in S3 during EH, compared to S1, while particle length decreased more in S1 compared to S3. Since bigger particles are contained in S1, the mechanical stress of stirring in the EH reactor could be greater compared to the smaller particles in S3, therefore a fraction of the particle length decrease could be attributed to mechanical stress and not to particle degradation due to EH. However, it is difficult to decouple the two processes, as particles during EH are degraded and therefore prone to mechanical damage.

In addition, length change does not account for total volume change. On the other hand, PLD analysis provides information that is not attainable with chemical composition analysis. Particle length at the end of EH is defined by the severity of pretreatment Table 2. Particle length provides information on the size of recalcitrant particles. The size of big population particles offers information on how many big particles are still left in the sample with the possibility of being hydrolyzed even further.

Optimal EH would be achieved when the two populations large and small particles fuse into a single population, this would indicate that particles cannot be further degraded. In this study, it was shown that in S the two populations were clearly distinct, therefore leading to increased recalcitrant mass, while in S the two populations almost fused which is an indication that EH is close to its maximum capacity. Determination of the optimal condition for maximizing the glucose yield while minimizing the severity of pretreatment would require further investigation. Apart from particle length quantification we were also able to extract qualitative information on particle characteristic morphologies.

Most particles appeared with an elongated, almost cylindrical, morphology. After pretreatment, there were several particles showing signs of degradation as one or both ends of the particle were dissociating for the main body. It was also observed that several structures, which we characterized as particle complexes, were present is all sample in the beginning of EH Figs. The frequency of these particles appeared to be higher in the less severe pretreatment cases.

However, a common observation was that these structures were completely absent after 16 h of EH, which is an indication that were easily and fast hydrolyzed.

These structures could belong to parts of the plant that have been shown to hydrolyze faster Zeng et al. At the end of EH small particles were observed in all cases, although in more severe pretreated samples S3 particle size was smallest. In this study, we provided a proof of concept of the imaging capabilities of the LFOV method as a tool for biomass characterization. Particle size investigation has been restricted in the analysis of particle length, a feature that is visible in the images acquired.

Particle thickness was not investigated because brightfield microscopy has limited axial resolution, thus thickness cannot be measured.

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Such measurement would be possible with more advanced optical microscopy techniques that offer sectioning capabilities, such as confocal or two-photon microscopy. Information on the particle volume could be then related to particle mass and this information could be directly related to the chemical composition of the sample. However, such techniques, although powerful, are rather slow, especially when considering that millions of particles need to be analyzed to extract reliable statistics, therefore high throughput investigation would not be practical.

The developed LFOV methodology was successful in imaging the wide dynamic range of pretreated corn stover particles lengths, and in identifying characteristic structures. Based on the high number of particles analyzed, whole sample characterization was possible with good accuracy. Therefore, this methodology was useful for quantifying the effect of pretreatment on particle size and further able to follow the dynamics of particle size distribution at different stages of EH.

The developed methodology could be used to quantify the effect of different pretreatments and EH and use it as a guide for optimization purposes. This work was supported by an Enabling Technologies B. Microsc Microanal 24 5 , — National Center for Biotechnology Information , U. Microscopy and Microanalysis. Cambridge University Press. Microsc Microanal. Boogers , 3 Maaike M.

Appeldoorn , 3 Mirjam A. Kabel , 4 Joachim Loos , 2 and Marc A. Van Zandvoort 5, 6. Ilco A. Maaike M. Mirjam A. Marc A. Van Zandvoort.

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Author information Article notes Copyright and License information Disclaimer. Key words: biomass, enzymatic hydrolysis, large field of view, particle length distribution. Introduction The production of biofuels from biomass is a field that has developed significantly during the last decade Ragauskas et al. Sample Pretreatment conditions Hydrolysis time h S 0 S 0. Open in a separate window. Particle Size Analysis LFOV images were processed with a median filter to remove noise and segmented based on intensity thresholding.

Figure 1. Figure 2. Figure 4. Particle Length Quantification During Enzymatic Hydrolysis In the previous section, it was shown that particle size depends on acidic pretreatment.

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Figure 3. Discussion The gold standard method for characterization and chemical quantification of biomass bioconversion to monosugars is HPLC Sluiter et al. Conclusions The developed LFOV methodology was successful in imaging the wide dynamic range of pretreated corn stover particles lengths, and in identifying characteristic structures. Acknowledgments This work was supported by an Enabling Technologies B. Conflict of interest A. Thank You! Sports Women sports wear Men sportswear Women athlatic shoes Men athlatic shoes.

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