bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2020.05.21.106468

Comparison of analytical methods for rapid & reliable quantification of plant-based carbohydrates for the quintessential bioenergy educator

Chundawat, S. P. S.
View original source ↗Export metadata ↓

Abstract

Biochemical conversion of plant-based insoluble carbohydrate polymers, such as starch from corn grains or cellulose-hemicellulose from corn stover, into soluble fermentable sugars (e.g., glucose and xylose) for bioenergy production has seen tremendous research activity and commercial-scale biorefineries deployment over the last three decades, particularly in regions around the world that have a dominant agricultural-based economy. Therefore, educators in schools and universities have developed various hands-on experimental activities to engage the general public and students either in outreach events or lab/classroom-based settings to instruct students on various inter-disciplinary concepts relevant to bioenergy and biochemicals production. One of the limitations of most available protocols is the lack of systematic and comprehensive comparison of educator-friendly analytical tools and protocols for quantitative analysis of water-soluble carbohydrates commonly encountered in a biorefinery backdrop during the biochemical conversion of lignocellulosic biomass to biofuels/biochemicals. Here, we systematically compare and validate findings from four leading analytical approaches for detection and quantification of lignocellulosic biomass derived soluble carbohydrates. We compare these assay methods based on the overall ease of use, detection accuracy/sensitivity, commercial availability, analytical cost per assay run, and suitability for use by instructors in biorefining specific hands-on activity protocols. Next, we provide a detailed instructional protocol that utilizes one of these validated soluble sugar assays as part of a ∼90 min hands-on bioenergy focused activity (called ‘Grass-to-Gas!’) conducted at Rutgers University with pre-university high school students. ‘Grass-to-Gas!’ activity involves students running biochemical assays that helps them understand the various facets of cellulosic biomass hydrolysis by commercial cellulase enzymes and monitoring the total glucose product released using our validated sugar assays to finally estimate the fractional conversion of cellulose-to-glucose. Lastly, we further demonstrate how such carbohydrate-based analytical methods can be used by instructors to help university students explore and understand various chemistry, biochemistry, and chemical engineering concepts relevant to other advanced operations involved in lignocellulose biorefining. These activity protocols would greatly aid educators teaching interdisciplinary science and engineering concepts to students in the backdrop of lignocellulose biorefining.Competing Interest StatementThe authors have declared no competing interest.View Full Text

Explore related subjects

scientific communication and educationPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Chundawat, S. P. S.. 2020-05-23. Comparison of analytical methods for rapid & reliable quantification of plant-based carbohydrates for the quintessential bioenergy educator. https://doi.org/10.1101/2020.05.21.106468

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Evaluating Large Language Models as Tools to Navigate Researchers in Rapidly Evolving Research Landscapes: A Case Study in Cancer Drug Response Prediction

Large Language Models (LLMs) have emerged as promising tools for assisting researchers in automating and accelerating the synthesis of literature reviews. However, their reliability is a significant concern due to issues like factual inaccuracies and hallucinations. The key question is whether LLMs can reliably provide comprehensive, up-to-date overviews and analyses. This study evaluates the performance of three leading LLMs (OpenAI's ChatGPT, Google's Gemini, and DeepSeek) on the complex task of generating a comprehensive survey paper on deep learning for cancer Drug Response Prediction (DRP). By testing both standard and Deep Research (DR) / Deep Think (DT) modes of LLMs with prompts of varying detail, this paper assesses key academic dimensions, including reference management, content quality, and analytical depth. Key findings reveal that while DR modes of LLMs significantly improve reliability by eliminating hallucinations, performance variations exist across models and prompts. A trade-off between reference quantity and integration quality was observed, and even the best-performing models lacked the analytical depth of human experts, often requiring extensive human supervision. The study concludes that LLMs currently serve as powerful assistive tools but still cannot replace the critical validation and synthesis provided by human researchers. Choosing the best LLM to use depends on the task in hand, while several strategies can be implemented to improve the produced output.

scientific communication and education↗
bioRxiv2021

Applying And Promoting Open Science In Ecology - Surveyed Drivers And Challenges

Open Science (OS) comprises a variety of practices and principles that are broadly intended to improve the quality and transparency of research, and the concept is gaining traction. Since OS has multiple facets and still lacks a unifying definition, it may be interpreted quite differently among practitioners. Moreover, successfully implementing OS broadly throughout science requires a better understanding of the conditions that facilitate or hinder OS engagement, and in particular, how practitioners learn OS in the first place. We addressed these issues by surveying OS practitioners that attended a workshop hosted by the Living Norway Ecological Data Network in 2020. The survey contained scaled-response and open-ended questions, allowing for a mixed-methods approach. Out of 128 registered participants we obtained survey responses from 60 individuals. Responses indicated usage and sharing of data and code, as well as open access publications, as the OS aspects most frequently engaged with. Men and those affiliated with academic institutions reported more frequent engagement with OS than women and those with other affiliations. When it came to learning OS practices, only a minority of respondents reported having encountered OS in their own formal education. Consistent with this, a majority of respondents viewed OS as less important in their teaching than in their research and supervision. Even so, many of the respondents suggestions for what would help or hinder individual OS engagement included more knowledge, guidelines, resource availability and social and structural support; indicating that formal instruction can facilitate individual OS engagement. We suggest that the time is ripe to incorporate OS in teaching and learning, as this can yield substantial benefits to OS practitioners, student learning, and ultimately, the objectives advanced by the OS movement.

scientific communication and education↗
bioRxiv2021

An exploratory analysis of 4844 withdrawn articles and their retraction notes.

The objective of our study was to obtain an updated image of the dynamic of retractions and retraction notes, retraction reasons for questionable research and publication practices, countries producing retracted articles, and the scientific impact of retractions by studying 4844 PubMed indexed retracted articles published between 2009 and 2020 and their retraction notes. RESULTSMistakes/inconsistent data account for 32% of total retractions, followed by images(22,5%), plagiarism(13,7%) and overlap(11,5%). Thirty countries account for 94,79% of 4844 retractions. Top five are: China(32,78%), United States(18,84%), India(7,25%), Japan(4,37%) and Italy(3,75%). The total citations number for all articles is 140810(Google Scholar), 96000(Dimensions). Average exposure time(ET) is 28,89 months. Largest ET is for image retractions(49,3 months), lowest ET is for editorial errors(11,2 months). The impact of retracted research is higher for Spain, Sweden, United Kingdom, United States, and other nine countries and lower for Pakistan, Turkey, Malaysia, and other six countries, including China. CONCLUSIONSMistakes and data inconsistencies represent the main retraction reason; images and ethical issues show a growing trend, while plagiarism and overlap still represent a significant problem. There is a steady increase in QRP and QPP article withdrawals. Retraction of articles seems to be a technology-dependent process. The number of citations of retracted articles shows a high impact of papers published by authors from certain countries. The number of retracted articles per country does not always accurately reflect the scientific impact of QRP/QPP articles. The country distribution of retraction reasons shows structural problems in the organization and quality control of scientific research, which have different images depending on geographical location, economic development, and cultural model.

scientific communication and education↗