High Throughput Screening Technologies in Biomass Characterization

Frontiers in Energy Research

Happs, Renee M.¹  Decker, Stephen R.²  Harman-Ware, Anne E.³  Wolfrum, Edward J.⁴ 

[1] Department of Civil Engineering, Morgan State University, United States;National Renewable Energy Laboratory, Biosciences Center, United States;Oak Ridge National Laboratory, Biosciences Division, United States;The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, United States

关键词: Biomass recalcitrance;    Biomass compositional analysis;    High throughput analysis;    neural networks;    biomass conversion;   

DOI  :  10.3389/fenrg.2018.00120

学科分类：能源（综合）

来源: Frontiers

【 摘 要 】

Biomass analysis is a slow and tedious process and not solely due to the long generation time for most plant species. Screening large numbers of plant variants for various geno-, pheno-, and chemotypes, whether naturally occurring or engineered in the lab, has multiple challenges. Plant cell walls are complex, heterogeneous networks that are difficult to deconstruct and analyze. Macroheterogeneity from tissue types, age, and environmental factors makes representative sampling a challenge and natural variability generates a significant range in data. Using high throughput (HTP) methodologies allows for large sample sets and replicates to be examined, narrowing in on more precise data for various analyses. This review provides a comprehensive survey of high throughput screening as applied to biomass characterization, from compositional analysis of cell walls by NIR, NMR, mass spectrometry, and wet chemistry to functional screening of changes in recalcitrance via HTP thermochemical pretreatment coupled to enzyme hydrolysis and microscale fermentation. The advancements and development of most high-throughput methods have been achieved through utilization of state-of-the art equipment and robotics, rapid detection methods, as well as reduction in sample size and preparation procedures. The computational analysis of the large amount of data generated using high throughput analytical techniques has recently become more sophisticated, faster and economically viable, enabling a more comprehensive understanding of biomass genomics, structure, composition and properties. Therefore, methodology for analyzing large datasets generated by the various analytical techniques is also covered.

【 授权许可】

CC BY