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  • Published: 31 January 2022

The fundamentals of critically appraising an article

  • Sneha Chotaliya 1  

BDJ Student volume  29 ,  pages 12–13 ( 2022 ) Cite this article

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Sneha Chotaliya

We are often surrounded by an abundance of research and articles, but the quality and validity can vary massively. Not everything will be of a good quality - or even valid. An important part of reading a paper is first assessing the paper. This is a key skill for all healthcare professionals as anything we read can impact or influence our practice. It is also important to stay up to date with the latest research and findings.

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Chambers R, 'Clinical Effectiveness Made Easy', Oxford: Radcliffe Medical Press , 1998

Loney P L, Chambers L W, Bennett K J, Roberts J G and Stratford P W. Critical appraisal of the health research literature: prevalence or incidence of a health problem. Chronic Dis Can 1998; 19 : 170-176.

Brice R. CASP CHECKLISTS - CASP - Critical Appraisal Skills Programme . 2021. Available at: https://casp-uk.net/casp-tools-checklists/ (Accessed 22 July 2021).

White S, Halter M, Hassenkamp A and Mein G. 2021. Critical Appraisal Techniques for Healthcare Literature . St George's, University of London.

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Chotaliya, S. The fundamentals of critically appraising an article. BDJ Student 29 , 12–13 (2022). https://doi.org/10.1038/s41406-021-0275-6

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strengths and weaknesses of a research article

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With the Internet’s ever-expanding repository of information, appraising potential sources has become an increasingly important skill. Evaluating strengths and weaknesses can be a useful tactic to assess potential sources.

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The study design contains a potential for the above selection bias, but the researchers didn’t address this potential in the study.

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A simplified approach to critically appraising research evidence

Affiliation.

  • 1 School of Health and Life Sciences, Teesside University, Middlesbrough, England.
  • PMID: 33660465
  • DOI: 10.7748/nr.2021.e1760

Background Evidence-based practice is embedded in all aspects of nursing and care. Understanding research evidence and being able to identify the strengths, weaknesses and limitations of published primary research is an essential skill of the evidence-based practitioner. However, it can be daunting and seem overly complex.

Aim: To provide a single framework that researchers can use when reading, understanding and critically assessing published research.

Discussion: To make sense of published research papers, it is helpful to understand some key concepts and how they relate to either quantitative or qualitative designs. Internal and external validity, reliability and trustworthiness are discussed. An illustration of how to apply these concepts in a practical way using a standardised framework to systematically assess a paper is provided.

Conclusion: The ability to understand and evaluate research builds strong evidence-based practitioners, who are essential to nursing practice.

Implications for practice: This framework should help readers to identify the strengths, potential weaknesses and limitations of a paper to judge its quality and potential usefulness.

Keywords: literature review; qualitative research; quantitative research; research; systematic review.

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Qualitative vs Quantitative Research Methods & Data Analysis

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Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis.

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

RESEARCH THEMATICANALYSISMETHOD

Key Features

  • Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
  • Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
  • The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
  • The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
  • The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

  • Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
  • The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
  • Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
  • The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

  • Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
  • Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
  • Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
  • Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

  • Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
  • The research aims for objectivity (i.e., without bias) and is separated from the data.
  • The design of the study is determined before it begins.
  • For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
  • Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

  • Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
  • Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
  • Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
  • Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

  • Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
  • Useful for testing and validating already constructed theories.
  • Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
  • Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
  • Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

  • Designing qualitative research
  • Methods of data collection and analysis
  • Introduction to quantitative and qualitative research
  • Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
  • Qualitative research in health care: Analysing qualitative data
  • Qualitative data analysis: the framework approach
  • Using the framework method for the analysis of
  • Qualitative data in multi-disciplinary health research
  • Content Analysis
  • Grounded Theory
  • Thematic Analysis

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What Is Face Validity In Research? Importance & How To Measure

Criterion Validity: Definition & Examples

Criterion Validity: Definition & Examples

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  • v.90(1); 2002 Jan

Editorial Peer Review: Its Strengths and Weaknesses.

Julia f. sollenberger.

1 Edward G. Miner Library University of Rochester Medical Center Rochester, New York

Weller, Ann C. Editorial Peer Review: Its Strengths and Weaknesses. Medford, NJ: Information Today, 2001. (ASIS&T Monograph Series). 342 p. Hardcover. $44.50. ISBN 1-57387-100-1.

Health sciences librarians study and teach the principles of evidence-based medicine (EBM), search evidence-based health care (EBHC) resources, and strive to practice evidence-based librarianship (EBL) [ 1 ]. In this work, Weller extends “EB” awareness to evidence-based scientific publishing. By providing a systematic review of empirical studies on the editorial peer review process from 1945 to 1997, the author assembles the available evidence on the value and validity of that process and its effect on the quality of the published literature. The author presents the strengths and weaknesses of peer review, analyzes the benefits and shortcomings, makes recommendations for further research, and provides information for improving future studies. With perhaps 6,000 to 7,000 scientific articles written every day [ 2 ] and with the review process for just one journal estimated to cost about $1 million a year [ 3 ], questioning the worth of this process is appropriate.

Though most understand what editorial peer review is, or have experienced it firsthand when submitting manuscripts for review, few have considered its diverse aspects in detail. This book provides insight and brings to light nagging questions such as the following: “What is the evidence that the ‘best’ science or scholarly material is published and the ‘worst’ is rejected?” (p. 51); “What is the value of the review process to authors?” (p. 120); “What is known about the overall quality of reviewers' reports?” (p. 158); “To what degree do reviewers agree with each other when evaluating the same manuscript?” (p. 182); “Is the submission versus acceptance rate for manuscripts different depending on the gender or ethnicity of the author?” (p. 227); and “What kind of statistical errors have been identified through studies of published articles?” (p. 255). Editorial Peer Review offers analyses of research studies that may answer these and other questions. For each question, the author methodically states the criteria for study inclusion, appraises the validity of the studies that address that issue, and, finally, proposes recommendations and draws conclusions based upon the evidence.

The preface of this book succinctly states its purpose and its methodology and describes the structure of the book. It is important to understand this before plunging into the substance of the work. Following the introductory chapter, which includes a brief history of the topic and the process used to compile the relevant studies, chapters appear on rejection rates, editors and editorial boards, authors and authorship, role of reviewers and quality of their reviews (including review agreement and bias), and statistical review of manuscripts. Each of these sections is extensive and substantive. One chapter addresses peer review in an electronic environment, and the final one presents key conclusions and recommendations.

Because the literature covered in the work does not extend beyond 1998, Weller's chapter entitled “Peer Review in an Electronic Environment” is necessarily limited. The rapidity of change in this arena requires conjecture rather than analysis, as few relevant studies are either completed or in progress. The author was obliged to address the electronic aspects of scholarly publishing, because she previously had given the transition from print to electronic as one of the primary reasons for undertaking this project. “As publication moves from print to electronics and the editorial peer review process may undergo change as a result, now is an excellent time to examine the cumulated information on editorial peer review and critically evaluate the entire process” (p. 3). This reviewer looks forward to the author's future investigation and analysis of peer review in a digital world, as the process of electronic publishing matures and a new area of research emerges.

For all other topics covered in this work, the number of studies cited and the depth of analysis are astounding, so much so that the more casual reader may be overwhelmed by the sheer number of references, author names, and study descriptions. Although tables are used effectively throughout the work to present salient characteristics and findings of a large number of research studies, the reader without knowledge of research design or not already familiar with the literature of peer review could find it challenging to digest. Such a reader would do well to attack each chapter in the following manner: (1) read the introductory and background sections, (2) note the research questions and study inclusion criteria, and, (3) finally, move to the recommendations and conclusions. The detail that is included, though necessary for a systematic review of this nature, will be most useful to those who are designing research studies to address the issues of peer review or to journal editors attempting to improve the process. The core elements of the work are of interest to a wide range of readers concerned with scholarly communication, from reviewers, to publishers, writers, and librarians.

There is a simple reason for the complexity of fields of study that encompasses peer review and the volume of the literature included in this systematic review—editorial peer review is not limited to a single discipline. Although the field of medicine has apparently produced a large number of the studies, Weller points out that “Since editorial peer review is not a discipline-specific field, literature on the subject could and does exist in almost every scholarly field with a journal publication outlet” (p. 8). The need to cover disciplines that range from medicine, nursing, education, agriculture, and management science has resulted in an in-depth and extensive treatment.

The author of this work is well known for her investigations of the scientific peer review and publishing process. She is also a highly regarded and active member of the Medical Library Associations' Research Section. Using a clear and precise writing style and declaring her own fascination with the topic, she compares the process of tracking down relevant studies to the design of a mystery novel. In the preface, she reveals that “a strategy somewhat akin to Sherlock Holmes' methodology was needed to identify and locate all studies in this field. With an eagerness similar to Holmes' enthusiastic, ‘The game is afoot,’ I relentlessly tracked down all leads” (p. xiv). In the end, the author's zeal, knowledge of the field, and skills in writing and analysis lead this reviewer to speculate that, given the time, the author herself just might be able to resolve every one of the hundreds of research questions remaining in the field of editorial peer review! Surely few are more qualified to make the attempt.

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Application of microwave energy to biomass: a comprehensive review of microwave-assisted technologies, optimization parameters, and the strengths and weaknesses.

strengths and weaknesses of a research article

1. Introduction

2. microwave-assisted processes, 2.1. microwave-assisted extraction (mae), 2.2. microwave-assisted pyrolysis (map), 2.3. microwave-assisted hydrothermal treatments (maht), 2.4. microwave-assisted acid hydrolysis (maah), 2.5. microwave-assisted organosolv (mao), 3. previous designs for microwave-assisted processes, 4. added-value products from biomass via microwave-assisted processes, 5. strengths and weaknesses of microwave-assisted processes, 6. future directions, 7. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest.

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Vegetal Matter (VM)MAE ConditionsSolvent Used and Volumes AddedValorized ProductYieldRef.
Rhodomyrtus tomentosa204.84 s, 400 W,
ΔT = 26.8 °C–115 °C
Ethanol 10 g fruit, 150 mL ethanolFlavonoids Anthocyanin1.68% (v/w)[ ]
Chlorella vulgaris300 W, 50
°C, 30 min
1 g algae, 100 mL chloroform:methanol (1:1)DW lipid31.9%[ ]
Mixed microalgal culture2.45 GHz, 10–80 W, 60 °C, 45 min5 g algae, KFCaO catalyst, 40 mL methanolBiodiesel58.12%[ ]
Stigeoclonium sp.;
Monoraphidium sp.;
Nitzchia sp.; and
Navicula sp.
2.45 GHz, 900 W, 3 minWet biomass, no solvent added. 150 mL algal biomassCarbohydrates, proteins915 mg/L soluble carbohydrates; 127.7 mL/g volatile solids and 193 mg/L protein[ ]
Haematococcus pluvialis2.45 GHz, 60% of 1200 W output, 75 °C, 5 min0.1 g algae, 10 mL acetonePigments74% astaxanthin recovery[ ]
Cucurbita pepo var. styriaca1200 W, 10 min, 102.2 °C1 g pumpkin, 50 mL waterPectin7.3%[ ]
Rhizopus oryzae NRRL1526300 W, 22 min1 g fungus, 50 mL NaOH 1 NChitosan13.43%[ ]
Spirulina (Arthrospira) platensis434 W, 20 min2.6 g of biomass to 80 mL of ethanolPolysacaridesg 127 ± 5 mg of carbohydrate/g of biomass[ ]
FeedstockMAP ConditionsValorized ProductYieldRef.
Oil palm biomass300 W, 2.45 GHz, quartz reactor, 17 min, N systemSolid char
Liquid
Gas
27.6%[ ]
Soapstock800 W at a frequency of 2450 MHz, N system, 550 °C and 6 g/minAlkenes, cycloalkenes, alkadienes, alkynes, aromatics65%[ ]
Rice straw2.45 GHz, 300 W, N system, 600–700 °C, 30 minGas fractionH (50.67 vol%), CO (22.56 vol%), CO (16.09 vol%), and CH (7.42 vol%)[ ]
Sewage sludge400 W, 6 min, 500 °C, 2450 MHzBio-oil49.8 wt.%[ ]
Mixture of plastics5 kW, quartz vesselBio-oil and biochar-[ ]
Plastic Waste1 kW, m 400 to 450 °C, 2450 MHzCombustible fuels and carbon nanotubes80%[ ]
Moringa seed800 W, 13 min, 450 °CKaranja bio-oil10.6%[ ]
FeedstockMicrowave ConditionsValorized ProductYieldRef.
Grass silage2.45 GHz, 1600 W, 0.7 g of dried feedstock/14 mL water, 30 min, 180 °CHydrochar, biogasHydrochar: f 0.79 g/g Biogas: 68.7 mL/g[ ]
Chicken carcassesTemperature 240 °C, time (2 h), power (400 W), biomass loading (20/45 g/mL)Biocrude59.41%[ , ]
Pineapple pealTime (9 m), power (900 W), biomass loading (100 g/L)Sugars80.2%[ ]
BagasseTemperature (105 °C), time (30 min), biomass loading (1:15), catalysts H SO , CH COOHLignin78.69%[ ]
BambooTemperature (180 °C), time (3 min), power (550 W), biomass loading (1:4)Nanofibrillated cellulosic fiber56.41%[ ]
Pine nut shellsTemperature (190 °C), time (60 min), biomass loading (1:3), 2450 MHzOligosaccharides1.59%[ ]
FeedstockMicrowave ConditionsProductYieldRef.
Myoglobin800 W, 60 Hz, 1 h, 30–100 °C, 2% formic acidSmall peptide fragments-[ ]
Whole moosebone140 °C, formic acid and acetic acid, 30 minPeptides70.16%[ ]
Brown seaweedH SO (0.01–0.4 M), temperature (120–180 °C), biomass loading (solid/liquid ratio: 0.6–6%, w/v), time (0–30 min)Monosaccharides, ethanol127 mg/g monosaccharides, 20.8 mg/g ethanol[ ]
Konjac flourDiluted sulfuric acid, 135 °C, 600 W, 45 min, 0.25 M H SO Glucomannan80%[ ]
Sago pith0.5 M H2SO4Ethanol0.361%[ ]
FeedstockMicrowave conditionsProductYieldRef.
Coconut shell2.45 GHz, 500 W, 100 mL of acetic acid/water solution (9/1, v/v), 110 °C, 20 minLignin3.82%[ ]
Sawmill60:40 ethanol-water, 175 °C, 0.25% H SO Cellulose82%[ ]
Triticale straw800 W, 83–167 °C, 30 min Lignin91%[ ]
Rubberwood2450 MHz, 200 W, 30 min, ethanol or isopropanol Ethanol/Lignin6.26%[ ]
Pine wood480 W, 150 °C, 10 min Levoglucosan55.87%[ ]
Coffee ResidueHemicellulose (%)Cellulose (%)Lignin (%)
Coffee Cherry12.527.613.7
Pulp3.625.8820.07
Husk7439
SCG12.123.617.8
FeedstockMicrowave-Assisted ProcessConditionsProduct and YieldSource
SCGMAE60–120 W, 75 °C, 1 g SGC/15 mL Ethanol (60%), 3–6 min Total polyphenols content: 175.08 mg/g[ ]
ParchmentMAPSingle-mode microwave oven at 500, 800, and 1000 °C, 15 min, quartz reactor, N 60 mL/min, 130, 270, and 420 WHydrogen rich fuel gas: 68.72%, Oil: 8.58%, Char: 22.70%[ ]
HuskMAAH2.5 g in 50 mL Citric acid solution, 100–800 W, 5–26 min, 50–100 °C, quartz reactor Pectin: 40.2%[ ]
SCGMAO50 Hz, choline chloride: glycerol (ChCl:Glyc), 60–120 °C, 5–15 min/(ethanol-water 25:75, v/v), 60 °C, 15 minAntioxidants: 0.48 mg GAE/SCG (TPC)
81 kg butanol t SCG
[ ]
SCGMA-HTLQuartz vessels, N atmosphere, 270 °C, 200 rpm, 3 g SCG, Multi-wave PRO MW, 20 minBiocrude: 30.1 wt.%
Solid: 28.6 wt.%
Aqueous Phase: 28.0 wt.%,
Gas: 13.3 wt.%
[ ]
Toasted coffeeMAE1–10 min, 120–180 °C, 2–6 g/mL, 1 kW, 2.45 GHz, MicroSYNTH LabstationCarbohydrate (18–43% w/w)
Caffeine (4–7% w/w)
5-caffeoylquinic acid (1–2% w/w)
[ ]
Defective coffee beansMAHT800 W (Panasonic NN6460A), 3 min, 15 g, quartz reactor Absorbent: 54%[ ]
Microwave-Assisted ProcessAdvantagesDisadvantagesSources
MAEHigher yield, selectivity, extraction efficiency, reduced time and solvent consumption, less environmental pollution, and reduced degradation of thermolabile constituents.Not robust to outliers, bigger error terms are not punished, not feasible for reaction monitoring, expensive equipment, non-differentiable nature of graphs, penalizes underestimates more than overestimates, and limited choice of solvents.[ , , , ]
MAPUniform heating of large particulate sizes of feed, no requirement of fluidization, fast switching on and off controls, time and energy savings, and fewer ashes in the liquid product.Complexity of the microwave heating phenomena, need for proper heating control devices, limited feedstock options, limited scale-up potential, and high capital cost.[ , , , ]
MHTHigh efficiency and productivity in the hydrothermal process, uniform distribution of heat during the pretreatment process, rapid heat generation leading to shorter treatment times, energy efficiency and rapid heat generation in the pretreatment process, and potential for higher yields of products with lower operating costs.Low penetration of radiation in bulk products during microwave heating, complexity of the microwave heating phenomena leading to challenges in control, agitation problems with high loading substrate in the microwave reactor, and not suitable for all types of feedstock, limiting its versatility.[ , ]
MAAHHigh uniformity and selectivity, short process time, and lower energy requirements compared to traditional heating methods.Degradation of glucose into toxic compounds, need of neutralization of hydrolysates, and no notable enhancement in protein hydrolysis.[ , , ]
MAOHigh efficiency and productivity, uniform distribution, easy recovery and reuse of organic solvents, fast heating rates, and high temperatures.High capital investment equipment, unsuitable for scaling up, and not feasible for monitoring. [ , , ]
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Share and Cite

Lozano Pérez, A.S.; Lozada Castro, J.J.; Guerrero Fajardo, C.A. Application of Microwave Energy to Biomass: A Comprehensive Review of Microwave-Assisted Technologies, Optimization Parameters, and the Strengths and Weaknesses. J. Manuf. Mater. Process. 2024 , 8 , 121. https://doi.org/10.3390/jmmp8030121

Lozano Pérez AS, Lozada Castro JJ, Guerrero Fajardo CA. Application of Microwave Energy to Biomass: A Comprehensive Review of Microwave-Assisted Technologies, Optimization Parameters, and the Strengths and Weaknesses. Journal of Manufacturing and Materials Processing . 2024; 8(3):121. https://doi.org/10.3390/jmmp8030121

Lozano Pérez, Alejandra Sophia, Juan José Lozada Castro, and Carlos Alberto Guerrero Fajardo. 2024. "Application of Microwave Energy to Biomass: A Comprehensive Review of Microwave-Assisted Technologies, Optimization Parameters, and the Strengths and Weaknesses" Journal of Manufacturing and Materials Processing 8, no. 3: 121. https://doi.org/10.3390/jmmp8030121

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