how to write good journal paper

How to Write and Publish a Research Paper for a Peer-Reviewed Journal

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Published: 30 April 2020
Volume 36 , pages 909–913, ( 2021 )

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Clara Busse ORCID: orcid.org/0000-0002-0178-1000 1 &
Ella August ORCID: orcid.org/0000-0001-5151-1036 1 , 2

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Communicating research findings is an essential step in the research process. Often, peer-reviewed journals are the forum for such communication, yet many researchers are never taught how to write a publishable scientific paper. In this article, we explain the basic structure of a scientific paper and describe the information that should be included in each section. We also identify common pitfalls for each section and recommend strategies to avoid them. Further, we give advice about target journal selection and authorship. In the online resource 1 , we provide an example of a high-quality scientific paper, with annotations identifying the elements we describe in this article.

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Introduction

Writing a scientific paper is an important component of the research process, yet researchers often receive little formal training in scientific writing. This is especially true in low-resource settings. In this article, we explain why choosing a target journal is important, give advice about authorship, provide a basic structure for writing each section of a scientific paper, and describe common pitfalls and recommendations for each section. In the online resource 1 , we also include an annotated journal article that identifies the key elements and writing approaches that we detail here. Before you begin your research, make sure you have ethical clearance from all relevant ethical review boards.

Select a Target Journal Early in the Writing Process

We recommend that you select a “target journal” early in the writing process; a “target journal” is the journal to which you plan to submit your paper. Each journal has a set of core readers and you should tailor your writing to this readership. For example, if you plan to submit a manuscript about vaping during pregnancy to a pregnancy-focused journal, you will need to explain what vaping is because readers of this journal may not have a background in this topic. However, if you were to submit that same article to a tobacco journal, you would not need to provide as much background information about vaping.

Information about a journal’s core readership can be found on its website, usually in a section called “About this journal” or something similar. For example, the Journal of Cancer Education presents such information on the “Aims and Scope” page of its website, which can be found here: https://www.springer.com/journal/13187/aims-and-scope .

Peer reviewer guidelines from your target journal are an additional resource that can help you tailor your writing to the journal and provide additional advice about crafting an effective article [ 1 ]. These are not always available, but it is worth a quick web search to find out.

Identify Author Roles Early in the Process

Early in the writing process, identify authors, determine the order of authors, and discuss the responsibilities of each author. Standard author responsibilities have been identified by The International Committee of Medical Journal Editors (ICMJE) [ 2 ]. To set clear expectations about each team member’s responsibilities and prevent errors in communication, we also suggest outlining more detailed roles, such as who will draft each section of the manuscript, write the abstract, submit the paper electronically, serve as corresponding author, and write the cover letter. It is best to formalize this agreement in writing after discussing it, circulating the document to the author team for approval. We suggest creating a title page on which all authors are listed in the agreed-upon order. It may be necessary to adjust authorship roles and order during the development of the paper. If a new author order is agreed upon, be sure to update the title page in the manuscript draft.

In the case where multiple papers will result from a single study, authors should discuss who will author each paper. Additionally, authors should agree on a deadline for each paper and the lead author should take responsibility for producing an initial draft by this deadline.

Structure of the Introduction Section

The introduction section should be approximately three to five paragraphs in length. Look at examples from your target journal to decide the appropriate length. This section should include the elements shown in Fig. 1 . Begin with a general context, narrowing to the specific focus of the paper. Include five main elements: why your research is important, what is already known about the topic, the “gap” or what is not yet known about the topic, why it is important to learn the new information that your research adds, and the specific research aim(s) that your paper addresses. Your research aim should address the gap you identified. Be sure to add enough background information to enable readers to understand your study. Table 1 provides common introduction section pitfalls and recommendations for addressing them.

The main elements of the introduction section of an original research article. Often, the elements overlap

Methods Section

The purpose of the methods section is twofold: to explain how the study was done in enough detail to enable its replication and to provide enough contextual detail to enable readers to understand and interpret the results. In general, the essential elements of a methods section are the following: a description of the setting and participants, the study design and timing, the recruitment and sampling, the data collection process, the dataset, the dependent and independent variables, the covariates, the analytic approach for each research objective, and the ethical approval. The hallmark of an exemplary methods section is the justification of why each method was used. Table 2 provides common methods section pitfalls and recommendations for addressing them.

Results Section

The focus of the results section should be associations, or lack thereof, rather than statistical tests. Two considerations should guide your writing here. First, the results should present answers to each part of the research aim. Second, return to the methods section to ensure that the analysis and variables for each result have been explained.

Begin the results section by describing the number of participants in the final sample and details such as the number who were approached to participate, the proportion who were eligible and who enrolled, and the number of participants who dropped out. The next part of the results should describe the participant characteristics. After that, you may organize your results by the aim or by putting the most exciting results first. Do not forget to report your non-significant associations. These are still findings.

Tables and figures capture the reader’s attention and efficiently communicate your main findings [ 3 ]. Each table and figure should have a clear message and should complement, rather than repeat, the text. Tables and figures should communicate all salient details necessary for a reader to understand the findings without consulting the text. Include information on comparisons and tests, as well as information about the sample and timing of the study in the title, legend, or in a footnote. Note that figures are often more visually interesting than tables, so if it is feasible to make a figure, make a figure. To avoid confusing the reader, either avoid abbreviations in tables and figures, or define them in a footnote. Note that there should not be citations in the results section and you should not interpret results here. Table 3 provides common results section pitfalls and recommendations for addressing them.

Discussion Section

Opposite the introduction section, the discussion should take the form of a right-side-up triangle beginning with interpretation of your results and moving to general implications (Fig. 2 ). This section typically begins with a restatement of the main findings, which can usually be accomplished with a few carefully-crafted sentences.

Major elements of the discussion section of an original research article. Often, the elements overlap

Next, interpret the meaning or explain the significance of your results, lifting the reader’s gaze from the study’s specific findings to more general applications. Then, compare these study findings with other research. Are these findings in agreement or disagreement with those from other studies? Does this study impart additional nuance to well-accepted theories? Situate your findings within the broader context of scientific literature, then explain the pathways or mechanisms that might give rise to, or explain, the results.

Journals vary in their approach to strengths and limitations sections: some are embedded paragraphs within the discussion section, while some mandate separate section headings. Keep in mind that every study has strengths and limitations. Candidly reporting yours helps readers to correctly interpret your research findings.

The next element of the discussion is a summary of the potential impacts and applications of the research. Should these results be used to optimally design an intervention? Does the work have implications for clinical protocols or public policy? These considerations will help the reader to further grasp the possible impacts of the presented work.

Finally, the discussion should conclude with specific suggestions for future work. Here, you have an opportunity to illuminate specific gaps in the literature that compel further study. Avoid the phrase “future research is necessary” because the recommendation is too general to be helpful to readers. Instead, provide substantive and specific recommendations for future studies. Table 4 provides common discussion section pitfalls and recommendations for addressing them.

Follow the Journal’s Author Guidelines

After you select a target journal, identify the journal’s author guidelines to guide the formatting of your manuscript and references. Author guidelines will often (but not always) include instructions for titles, cover letters, and other components of a manuscript submission. Read the guidelines carefully. If you do not follow the guidelines, your article will be sent back to you.

Finally, do not submit your paper to more than one journal at a time. Even if this is not explicitly stated in the author guidelines of your target journal, it is considered inappropriate and unprofessional.

Your title should invite readers to continue reading beyond the first page [ 4 , 5 ]. It should be informative and interesting. Consider describing the independent and dependent variables, the population and setting, the study design, the timing, and even the main result in your title. Because the focus of the paper can change as you write and revise, we recommend you wait until you have finished writing your paper before composing the title.

Be sure that the title is useful for potential readers searching for your topic. The keywords you select should complement those in your title to maximize the likelihood that a researcher will find your paper through a database search. Avoid using abbreviations in your title unless they are very well known, such as SNP, because it is more likely that someone will use a complete word rather than an abbreviation as a search term to help readers find your paper.

After you have written a complete draft, use the checklist (Fig. 3 ) below to guide your revisions and editing. Additional resources are available on writing the abstract and citing references [ 5 ]. When you feel that your work is ready, ask a trusted colleague or two to read the work and provide informal feedback. The box below provides a checklist that summarizes the key points offered in this article.

Checklist for manuscript quality

Data Availability

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Vetto JT (2014) Short and sweet: a short course on concise medical writing. J Cancer Educ 29(1):194–195

Brett M, Kording K (2017) Ten simple rules for structuring papers. PLoS ComputBiol. https://doi.org/10.1371/journal.pcbi.1005619

Lang TA (2017) Writing a better research article. J Public Health Emerg. https://doi.org/10.21037/jphe.2017.11.06

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Acknowledgments

Ella August is grateful to the Sustainable Sciences Institute for mentoring her in training researchers on writing and publishing their research.

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Clara Busse & Ella August

Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI, 48109-2029, USA

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Busse, C., August, E. How to Write and Publish a Research Paper for a Peer-Reviewed Journal. J Canc Educ 36 , 909–913 (2021). https://doi.org/10.1007/s13187-020-01751-z

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Published : 30 April 2020

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DOI : https://doi.org/10.1007/s13187-020-01751-z

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How to Write and Publish a Research Paper for a Peer-Reviewed Journal

Clara busse.

1 Department of Maternal and Child Health, University of North Carolina Gillings School of Global Public Health, 135 Dauer Dr, 27599 Chapel Hill, NC USA

Ella August

2 Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109-2029 USA

Associated Data

Electronic supplementary material

The online version of this article (10.1007/s13187-020-01751-z) contains supplementary material, which is available to authorized users.

Introduction

Select a Target Journal Early in the Writing Process

Identify Author Roles Early in the Process

Structure of the Introduction Section

The introduction section should be approximately three to five paragraphs in length. Look at examples from your target journal to decide the appropriate length. This section should include the elements shown in Fig. 1 . Begin with a general context, narrowing to the specific focus of the paper. Include five main elements: why your research is important, what is already known about the topic, the “gap” or what is not yet known about the topic, why it is important to learn the new information that your research adds, and the specific research aim(s) that your paper addresses. Your research aim should address the gap you identified. Be sure to add enough background information to enable readers to understand your study. Table Table1 1 provides common introduction section pitfalls and recommendations for addressing them.

An external file that holds a picture, illustration, etc.
Object name is 13187_2020_1751_Fig1_HTML.jpg

The main elements of the introduction section of an original research article. Often, the elements overlap

Common introduction section pitfalls and recommendations

Methods Section

The purpose of the methods section is twofold: to explain how the study was done in enough detail to enable its replication and to provide enough contextual detail to enable readers to understand and interpret the results. In general, the essential elements of a methods section are the following: a description of the setting and participants, the study design and timing, the recruitment and sampling, the data collection process, the dataset, the dependent and independent variables, the covariates, the analytic approach for each research objective, and the ethical approval. The hallmark of an exemplary methods section is the justification of why each method was used. Table Table2 2 provides common methods section pitfalls and recommendations for addressing them.

Common methods section pitfalls and recommendations

Results Section

Tables and figures capture the reader’s attention and efficiently communicate your main findings [ 3 ]. Each table and figure should have a clear message and should complement, rather than repeat, the text. Tables and figures should communicate all salient details necessary for a reader to understand the findings without consulting the text. Include information on comparisons and tests, as well as information about the sample and timing of the study in the title, legend, or in a footnote. Note that figures are often more visually interesting than tables, so if it is feasible to make a figure, make a figure. To avoid confusing the reader, either avoid abbreviations in tables and figures, or define them in a footnote. Note that there should not be citations in the results section and you should not interpret results here. Table Table3 3 provides common results section pitfalls and recommendations for addressing them.

Common results section pitfalls and recommendations

Discussion Section

An external file that holds a picture, illustration, etc.
Object name is 13187_2020_1751_Fig2_HTML.jpg

Major elements of the discussion section of an original research article. Often, the elements overlap

Finally, the discussion should conclude with specific suggestions for future work. Here, you have an opportunity to illuminate specific gaps in the literature that compel further study. Avoid the phrase “future research is necessary” because the recommendation is too general to be helpful to readers. Instead, provide substantive and specific recommendations for future studies. Table Table4 4 provides common discussion section pitfalls and recommendations for addressing them.

Common discussion section pitfalls and recommendations

Follow the Journal’s Author Guidelines

After you have written a complete draft, use the checklist (Fig. (Fig.3) 3 ) below to guide your revisions and editing. Additional resources are available on writing the abstract and citing references [ 5 ]. When you feel that your work is ready, ask a trusted colleague or two to read the work and provide informal feedback. The box below provides a checklist that summarizes the key points offered in this article.

An external file that holds a picture, illustration, etc.
Object name is 13187_2020_1751_Fig3_HTML.jpg

Checklist for manuscript quality

(PDF 362 kb)

Acknowledgments

Ella August is grateful to the Sustainable Sciences Institute for mentoring her in training researchers on writing and publishing their research.

Code Availability

Not applicable.

Data Availability

Compliance with ethical standards.

The authors declare that they have no conflict of interest.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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How to Write and Publish a Research Paper in 7 Steps

What comes next after you're done with your research? Publishing the results in a journal of course! We tell you how to present your work in the best way possible.

This post is part of a series, which serves to provide hands-on information and resources for authors and editors.

Things have gotten busy in scholarly publishing: These days, a new article gets published in the 50,000 most important peer-reviewed journals every few seconds, while each one takes on average 40 minutes to read. Hundreds of thousands of papers reach the desks of editors and reviewers worldwide each year and 50% of all submissions end up rejected at some stage.

In a nutshell: there is a lot of competition, and the people who decide upon the fate of your manuscript are short on time and overworked. But there are ways to make their lives a little easier and improve your own chances of getting your work published!

Well, it may seem obvious, but before submitting an academic paper, always make sure that it is an excellent reflection of the research you have done and that you present it in the most professional way possible. Incomplete or poorly presented manuscripts can create a great deal of frustration and annoyance for editors who probably won’t even bother wasting the time of the reviewers!

This post will discuss 7 steps to the successful publication of your research paper:

Check whether your research is publication-ready
Choose an article type
Choose a journal
Construct your paper
Decide the order of authors
Check and double-check
Submit your paper

1. Check Whether Your Research Is Publication-Ready

Should you publish your research at all?

If your work holds academic value – of course – a well-written scholarly article could open doors to your research community. However, if you are not yet sure, whether your research is ready for publication, here are some key questions to ask yourself depending on your field of expertise:

Have you done or found something new and interesting? Something unique?
Is the work directly related to a current hot topic?
Have you checked the latest results or research in the field?
Have you provided solutions to any difficult problems?
Have the findings been verified?
Have the appropriate controls been performed if required?
Are your findings comprehensive?

If the answers to all relevant questions are “yes”, you need to prepare a good, strong manuscript. Remember, a research paper is only useful if it is clearly understood, reproducible and if it is read and used .

2. Choose An Article Type

The first step is to determine which type of paper is most appropriate for your work and what you want to achieve. The following list contains the most important, usually peer-reviewed article types in the natural sciences:

Full original research papers disseminate completed research findings. On average this type of paper is 8-10 pages long, contains five figures, and 25-30 references. Full original research papers are an important part of the process when developing your career.

Review papers present a critical synthesis of a specific research topic. These papers are usually much longer than original papers and will contain numerous references. More often than not, they will be commissioned by journal editors. Reviews present an excellent way to solidify your research career.

Letters, Rapid or Short Communications are often published for the quick and early communication of significant and original advances. They are much shorter than full articles and usually limited in length by the journal. Journals specifically dedicated to short communications or letters are also published in some fields. In these the authors can present short preliminary findings before developing a full-length paper.

3. Choose a Journal

Are you looking for the right place to publish your paper? Find out here whether a De Gruyter journal might be the right fit.

Submit to journals that you already read, that you have a good feel for. If you do so, you will have a better appreciation of both its culture and the requirements of the editors and reviewers.

Other factors to consider are:

The specific subject area
The aims and scope of the journal
The type of manuscript you have written
The significance of your work
The reputation of the journal
The reputation of the editors within the community
The editorial/review and production speeds of the journal
The community served by the journal
The coverage and distribution
The accessibility ( open access vs. closed access)

4. Construct Your Paper

Each element of a paper has its purpose, so you should make these sections easy to index and search.

Don’t forget that requirements can differ highly per publication, so always make sure to apply a journal’s specific instructions – or guide – for authors to your manuscript, even to the first draft (text layout, paper citation, nomenclature, figures and table, etc.) It will save you time, and the editor’s.

Also, even in these days of Internet-based publishing, space is still at a premium, so be as concise as possible. As a good journalist would say: “Never use three words when one will do!”

Let’s look at the typical structure of a full research paper, but bear in mind certain subject disciplines may have their own specific requirements so check the instructions for authors on the journal’s home page.

4.1 The Title

It’s important to use the title to tell the reader what your paper is all about! You want to attract their attention, a bit like a newspaper headline does. Be specific and to the point. Keep it informative and concise, and avoid jargon and abbreviations (unless they are universally recognized like DNA, for example).

4.2 The Abstract

This could be termed as the “advertisement” for your article. Make it interesting and easily understood without the reader having to read the whole article. Be accurate and specific, and keep it as brief and concise as possible. Some journals (particularly in the medical fields) will ask you to structure the abstract in distinct, labeled sections, which makes it even more accessible.

A clear abstract will influence whether or not your work is considered and whether an editor should invest more time on it or send it for review.

4.3 Keywords

Keywords are used by abstracting and indexing services, such as PubMed and Web of Science. They are the labels of your manuscript, which make it “searchable” online by other researchers.

Include words or phrases (usually 4-8) that are closely related to your topic but not “too niche” for anyone to find them. Make sure to only use established abbreviations. Think about what scientific terms and its variations your potential readers are likely to use and search for. You can also do a test run of your selected keywords in one of the common academic search engines. Do similar articles to your own appear? Yes? Then that’s a good sign.

4.4 Introduction

This first part of the main text should introduce the problem, as well as any existing solutions you are aware of and the main limitations. Also, state what you hope to achieve with your research.

Do not confuse the introduction with the results, discussion or conclusion.

4.5 Methods

Every research article should include a detailed Methods section (also referred to as “Materials and Methods”) to provide the reader with enough information to be able to judge whether the study is valid and reproducible.

Include detailed information so that a knowledgeable reader can reproduce the experiment. However, use references and supplementary materials to indicate previously published procedures.

4.6 Results

In this section, you will present the essential or primary results of your study. To display them in a comprehensible way, you should use subheadings as well as illustrations such as figures, graphs, tables and photos, as appropriate.

4.7 Discussion

Here you should tell your readers what the results mean .

Do state how the results relate to the study’s aims and hypotheses and how the findings relate to those of other studies. Explain all possible interpretations of your findings and the study’s limitations.

Do not make “grand statements” that are not supported by the data. Also, do not introduce any new results or terms. Moreover, do not ignore work that conflicts or disagrees with your findings. Instead …

Be brave! Address conflicting study results and convince the reader you are the one who is correct.

4.8 Conclusion

Your conclusion isn’t just a summary of what you’ve already written. It should take your paper one step further and answer any unresolved questions.

Sum up what you have shown in your study and indicate possible applications and extensions. The main question your conclusion should answer is: What do my results mean for the research field and my community?

4.9 Acknowledgments and Ethical Statements

It is extremely important to acknowledge anyone who has helped you with your paper, including researchers who supplied materials or reagents (e.g. vectors or antibodies); and anyone who helped with the writing or English, or offered critical comments about the content.

Learn more about academic integrity in our blog post “Scholarly Publication Ethics: 4 Common Mistakes You Want To Avoid” .

Remember to state why people have been acknowledged and ask their permission . Ensure that you acknowledge sources of funding, including any grant or reference numbers.

Furthermore, if you have worked with animals or humans, you need to include information about the ethical approval of your study and, if applicable, whether informed consent was given. Also, state whether you have any competing interests regarding the study (e.g. because of financial or personal relationships.)

4.10 References

The end is in sight, but don’t relax just yet!

De facto, there are often more mistakes in the references than in any other part of the manuscript. It is also one of the most annoying and time-consuming problems for editors.

Remember to cite the main scientific publications on which your work is based. But do not inflate the manuscript with too many references. Avoid excessive – and especially unnecessary – self-citations. Also, avoid excessive citations of publications from the same institute or region.

5. Decide the Order of Authors

In the sciences, the most common way to order the names of the authors is by relative contribution.

Generally, the first author conducts and/or supervises the data analysis and the proper presentation and interpretation of the results. They put the paper together and usually submit the paper to the journal.

Co-authors make intellectual contributions to the data analysis and contribute to data interpretation. They review each paper draft. All of them must be able to present the paper and its results, as well as to defend the implications and discuss study limitations.

Do not leave out authors who should be included or add “gift authors”, i.e. authors who did not contribute significantly.

6. Check and Double-Check

As a final step before submission, ask colleagues to read your work and be constructively critical .

Make sure that the paper is appropriate for the journal – take a last look at their aims and scope. Check if all of the requirements in the instructions for authors are met.

Ensure that the cited literature is balanced. Are the aims, purpose and significance of the results clear?

Conduct a final check for language, either by a native English speaker or an editing service.

7. Submit Your Paper

When you and your co-authors have double-, triple-, quadruple-checked the manuscript: submit it via e-mail or online submission system. Along with your manuscript, submit a cover letter, which highlights the reasons why your paper would appeal to the journal and which ensures that you have received approval of all authors for submission.

It is up to the editors and the peer-reviewers now to provide you with their (ideally constructive and helpful) comments and feedback. Time to take a breather!

If the paper gets rejected, do not despair – it happens to literally everybody. If the journal suggests major or minor revisions, take the chance to provide a thorough response and make improvements as you see fit. If the paper gets accepted, congrats!

It’s now time to get writing and share your hard work – good luck!

If you are interested, check out this related blog post

[Title Image by Nick Morrison via Unsplash]

David Sleeman

David Sleeman worked as Senior Journals Manager in the field of Physical Sciences at De Gruyter.

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Writing for an academic journal: 10 tips

1) Have a strategy, make a plan

Why do you want to write for journals? What is your purpose? Are you writing for research assessment? Or to make a difference? Are you writing to have an impact factor or to have an impact? Do you want to develop a profile in a specific area? Will this determine which journals you write for? Have you taken their impact factors into account?

Have you researched other researchers in your field – where have they published recently? Which group or conversation can you see yourself joining? Some people write the paper first and then look for a 'home' for it, but since everything in your article – content, focus, structure, style – will be shaped for a specific journal, save yourself time by deciding on your target journal and work out how to write in a way that suits that journal.

Having a writing strategy means making sure you have both external drivers – such as scoring points in research assessment or climbing the promotion ladder – and internal drivers – which means working out why writing for academic journals matters to you. This will help you maintain the motivation you'll need to write and publish over the long term. Since the time between submission and publication can be up to two years (though in some fields it's much less) you need to be clear about your motivation.

2) Analyse writing in journals in your field

Take a couple of journals in your field that you will target now or soon. Scan all the abstracts over the past few issues. Analyse them: look closely at all first and last sentences. The first sentence (usually) gives the rationale for the research, and the last asserts a 'contribution to knowledge'. But the word 'contribution' may not be there – it's associated with the doctorate. So which words are used? What constitutes new knowledge in this journal at this time? How can you construct a similar form of contribution from the work you did? What two sentences will you write to start and end your abstract for that journal?

Scan other sections of the articles: how are they structured? What are the components of the argument? Highlight all the topic sentences – the first sentences of every paragraph – to show the stages in the argument. Can you see an emerging taxonomy of writing genres in this journal? Can you define the different types of paper, different structures and decide which one will work best in your paper? Select two types of paper: one that's the type of paper you can use as a model for yours, and one that you can cite in your paper, thereby joining the research conversation that is ongoing in that journal.

3) Do an outline and just write

Which type of writer are you: do you always do an outline before you write, or do you just dive in and start writing? Or do you do a bit of both? Both outlining and just writing are useful, and it is therefore a good idea to use both. However, make your outline very detailed: outline the main sections and calibrate these with your target journal.

What types of headings are normally used there? How long are the sections usually? Set word limits for your sections, sub-sections and, if need be, for sub-sub-sections. This involves deciding about content that you want to include, so it may take time, and feedback would help at this stage.

When you sit down to write, what exactly are you doing:using writing to develop your ideas or writing to document your work? Are you using your outline as an agenda for writing sections of your article? Define your writing task by thinking about verbs – they define purpose: to summarise, overview, critique, define, introduce, conclude etc.

4) Get feedback from start to finish

Even at the earliest stages, discuss your idea for a paper with four or five people, get feedback on your draft abstract. It will only take them a couple of minutes to read it and respond. Do multiple revisions before you submit your article to the journal.

5) Set specific writing goals and sub-goals

Making your writing goals specific means defining the content, verb and word length for the section. This means not having a writing goal like, 'I plan to have this article written by the end of the year' but 'My next writing goal is to summarise and critique twelve articles for the literature review section in 800 words on Tuesday between 9am and 10.30'. Some people see this as too mechanical for academic writing, but it is a way of forcing yourself to make decisions about content, sequence and proportion for your article.

6) Write with others

While most people see writing as a solitary activity, communal writing – writing with others who are writing – can help to develop confidence, fluency and focus. It can help you develop the discipline of regular writing. Doing your academic writing in groups or at writing retreats are ways of working on your own writing, but – if you unplug from email, internet and all other devices – also developing the concentration needed for regular, high-level academic writing.

At some point – ideally at regular intervals – you can get a lot more done if you just focus on writing. If this seems like common sense, it isn't common practice. Most people do several things at once, but this won't always work for regular journal article writing. At some point, it pays to privilege writing over all other tasks, for a defined period, such as 90 minutes, which is long enough to get something done on your paper, but not so long that it's impossible to find the time.

7) Do a warm up before you write

While you are deciding what you want to write about, an initial warm up that works is to write for five minutes, in sentences, in answer to the question: 'What writing for publication have you done [or the closest thing to it], and what do you want to do in the long, medium and short term?'

Once you have started writing your article, use a variation on this question as a warm up – what writing for this project have you done, and what do you want to do in the long, medium and short term? Top tip: end each session of writing with a 'writing instruction' for yourself to use in your next session, for example, 'on Monday from 9 to 10am, I will draft the conclusion section in 500 words'.

As discussed, if there are no numbers, there are no goals. Goals that work need to be specific, and you need to monitor the extent to which you achieve them. This is how you learn to set realistic targets.

8) Analyse reviewers' feedback on your submission

What exactly are they asking you to do? Work out whether they want you to add or cut something. How much? Where? Write out a list of revision actions. When you resubmit your article include this in your report to the journal, specifying how you have responded to the reviewers' feedback. If your article was rejected, it is still useful to analyse feedback, work out why and revise it for somewhere else.

Most feedback will help you improve your paper and, perhaps, your journal article writing, but sometimes it may seem overheated, personalised or even vindictive. Some of it may even seem unprofessional. Discuss reviewers' feedback – see what others think of it. You may find that other people – even eminent researchers – still get rejections and negative reviews; any non-rejection is a cause for celebration. Revise and resubmit as soon as you can.

9) Be persistent, thick-skinned and resilient

These are qualities that you may develop over time – or you may already have them. It may be easier to develop them in discussion with others who are writing for journals.

10) Take care of yourself

Writing for academic journals is highly competitive. It can be extremely stressful. Even making time to write can be stressful. And there are health risks in sitting for long periods, so try not to sit writing for more than an hour at a time. Finally, be sure to celebrate thoroughly when your article is accepted. Remind yourself that writing for academic journals is what you want to do – that your writing will make a difference in some way.

These points are taken from the 3rd edition of Writing for Academic Journals .

Rowena Murray is professor in education and director of research at the University of the West of Scotland – follow it on Twitter @UniWestScotland

This content is brought to you by Guardian Professional . Looking for your next university role? Browse Guardian jobs for thousands of the latest academic, administrative and research posts

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How to Write a Journal: 6 Tips to Get Started

by Pamela Hodges | 61 comments

Writers are collectors of ideas, and where do we keep them? On scraps of paper, napkins, the notes app of our phones, and sometimes in journals. But as anyone who's started a journal can attest, sometimes it's hard to begin and even harder to keep one going. So how to write a journal? What to write in a journal? Let's look at some simple ways to start capturing ideas.

There are a number of ways to capture ideas, from keeping a gratitude journal, to a reading journal, to a project journal. No matter what type of journal you keep, let me share with you some tips from my journaling experience for how to keep a journal and why a journaling habit pays off for writers.

4 Advantages of Keeping a Journal

Julia Cameron, acclaimed author of The Artist's Way and more recently a 6-week program outlined in a book called Write for Life, begins the writing and artistic life with a practice she calls morning pages. In essence, she suggests writing three pages each morning to explore ideas and life, and to clear the mind.

The benefits of journaling this way are numerous. Writers who establish regular journaling time may find it helps them clear their minds and explore new ideas.

There are many reasons why it is a good idea to keep a journal. I want to share four big reasons this daily habit may help you with your writing process and develop your writing skills.

1. Remember details

When I traveled to Europe in 1978, I kept a journal of my daily life. I have notes from the trip to Greece where I wiped out on a moped, weeded sugar beets on Kibbutz Reshafim in Israel, and hitchhiked through occupied territory in the south of Israel.

There were several details of my trip that I had completely forgotten until I re-read my personal journals.

Recording the details of your life can enrich your stories. One year when for The Spring Writing Contest at The Write Practice, I wrote a story about when the IRS called me to say I owed money.

In my first draft, I wrote that the amount they said I owed was, $638. After I had completed the first draft I went back to the notes I had written in my journal, and the correct amount was over six thousand dollars: $6,846.48 to be exact. Well, maybe there are some things we don't want to remember.

Thankfully, I didn't send the money. It wasn't the real IRS. But it was even better than a writing prompt for a story idea.

2. Find old friends

Keeping a journal can help you find old friends. One of the women I met on November 26th, 1978, wrote down her address. I found her on Facebook and just sent her a message. (Social media and Google can also help, but the journal did remind me of her name.)

We'll see if she responds to my Facebook message. It has been almost forty years since she lent me a pair of gloves when I scraped my hand on the pavement when I fell off my moped.

3. Help process feelings and ideas

When you keep thoughts in your head it can be hard to know how you think and feel. Writing down how you feel will help you process your emotions , as feelings become words, which can be then be edited.

Processing your feelings and ideas can lead to personal growth and peace, but that's not all. Expressive writing can be therapeutic, but it can also help you flesh out characters later.

4. Preserve the writer's history

When you are dead and a famous writer, your journals will give your readers insight into your life, thoughts, and process.

You may never sell more than one hundred copies of your book, you may never publish your writing, or your journals may only be read by the mice that crawl through your basement. Or your journals will be read by zombies after the zombie apocalypse, sharing insight into your life and daily routines.

If you don't want anyone to read your journal, keep it in a locked box and swallow the key. (Please don't really swallow the key. It would be unpleasant to have to find it again, and you might choke.) Put the key in a safe spot, and then remember where you put it.

6 Tips for How to Keep a Journal (and What to Write in a Journal!)

Now you know why journaling can be helpful. But how should you journal? It is very personal, and you should do what works best for you. But I will give you some tips to help you get started on a journaling practice.

1. Choose your kind of journal

You have several options for how to keep your journal.

A book, where you write with a pen or pencil onto paper: Write in a book that is not so pretty you are afraid to write in it. Keep the size small enough you don't mind carrying it in your messenger bag, and big enough you can read your handwriting. Do not try journaling at night when the only paper you have on your bedside table is a bandaid. The next morning I couldn't read my writing on the band-aid, and the idea I wanted to journal was lost.

The advantage of pen to paper is you can write without having to be plugged into an electronic device. You don’t have to worry about a dead battery, and you can write even when the sun is bright or the airline makes you turn off your electronic devices.

The disadvantage to a paper journal is if you lose the journal and you didn’t make a copy of it, you have lost all of the writing. But either way, the journal writing helps you pay attention and record the moments of everyday life that will fade with time otherwise.

Software: There are several software applications and journaling apps on the market you can use to keep a digital journal. Be sure they sync to the cloud, as you don’t want to lose your entries because you fry your computer's hard-drive.

Journey and Day One can add photographs and text, and export all of your entries into a PDF. You can also journal in Google Docs, Microsoft Word, or Scrivener and save your files to a cloud-based program that will keep your files safe if you lose your computer or pour water on your keyboard.

2. Date your entry

You think you will remember when it happened, but without a written date, you might forget. Make it a part of your journal writing routine to date the entry.

3. Tell the truth

The journal is a record of how you felt and what you did. Telling the truth will make you a reliable storyteller.

If you haven’t cleaned the seven litter boxes for a week, don’t write that you clean them every day simply because you want your readers one hundred years from now to think you had good habits. The beauty of journal writing is that you can record things honestly for yourself that you might not otherwise record or share.

4. Write down details

Record details like the time, location, who you were with, and what you were wearing. Details will help bring the memory alive when you record using your five senses .

To this day, if I smell a certain kind of Japanese soup, I can remember vividly the day I flew to Korea to renew my Japanese visa, only to discover the Japanese embassy was closed for a traditional Japanese holiday.

5. Write down what you felt

What you were thinking? Were you mad? Sad? Happy? Write down why.

6. Write a lot or a little

A journal entry doesn’t have to be three pages long. It can be a few words that describe what happened, a few sentences about the highlight of your day, or it can be a short description of an event from your day, where you describe details to help you remember what happened. What time of day was it? What sound do you remember?

Your journal entry might be a drawing, a poem, or a list of words or cities you drove through. It is your journal, and you have the freedom to be creative.

You can use journal writing prompts or simply tap into a memory that floats into your mind.

Bonus tip: How to write a journal entry

Aside from the date, you can write your journal entry in a number of ways. You can write stream-of-consciousness, try bullet points written rapid fire, you can use various art materials, or any form that speaks to you. Try a list or a mix of writing and doodling, or even dialogue exchanges.

The most important thing is just to take the journaling time and make a regular habit of it, even if it isn't on a daily basis. The words will show up when you do.

When to Journal

There is no right or wrong time to write in a journal. Write when you will remember to do it. Do you always brush your teeth before you go to bed? Have writing in your journal be part of your bedtime routine. Perhaps put it on your bedside table, or beside your hammock, or on the floor beside your futon.

If you are a morning person, consider keeping your journal on the table where you drink your morning coffee, tea, water, milk, or orange juice.

These are only suggestions. You don’t have to write down your feelings or why you felt a certain way. I hate being told what to do. Even if it is a good idea. But I hope you'll give it a try and see if you find it unlocks your own writing.

Do you write in a journal? Why is keeping a journal a valuable practice? Please tell us in the comment s.

Do you write in a journal? Do you think writing in a journal is a good idea for a writer, or a bad idea? Please tell us why in the comments .

Write for fifteen minutes about some aspect of your day as though you were writing in a journal. Your journal entry might be a drawing, a poem, a list of words, or a list of cities you drove through.

Please share your writing in the Pro Practice Workshop here and leave feedback on someone else’s practice today. We learn by writing and by reading.

Pamela Hodges

Pamela writes stories about art and creativity to help you become the artist you were meant to be. She would love to meet you at pamelahodges.com .

Join over 450,000 readers who are saying YES to practice. You’ll also get a free copy of our eBook 14 Prompts :

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Education and Communications
Journal Writing

How to Write a Journal

Last Updated: March 21, 2024 Fact Checked

This article was co-authored by Catherine Boswell, PhD . Dr. Catherine Boswell is a Licensed Psychologist and a Co-Founder of Psynergy Psychological Associates, a private therapy practice based in Houston, Texas. With over 15 years of experience, Dr. Boswell specializes in treating individuals, groups, couples, and families struggling with trauma, relationships, grief, and chronic pain. She holds a Ph.D. in Counseling Psychology from the University of Houston. Dr. Bowell has taught courses to Master’s level students at the University of Houston. She is also an author, speaker, and coach. There are 9 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 239,895 times.

Journal writing is a creative form of recording your feelings free from the fear of judgement or criticism. Writing in a journal can allow you to work through complex issues in your life, exploring them thoroughly and candidly. It can also be a way of relieving stress, rather than inadvertently taking out your unexplored feelings on someone else. See Step 1 below to start writing your own journal.

Journal Entry Template

Starting Your Own Journal

Step 1 Find something to contain your journal entries.

If you're looking at computer-based options for your journal, you might want to consider starting a blog - essentially an online journal that other people can read . A variety of free blog sites exist, some of which allow you to control who can and cannot read your blog.

Step 2 Start your first entry by setting the scene.

If you're writing a blog, you may want to begin by addressing your readers.

As an exception to this rule, if you're writing a blog, while you'll want to be open with your emotions, consider your audience. You may want to consider censoring your most intense and/or personal thoughts.

Many journal-writers like to add an entry every night before bed. This is a healthy routine because it allows the writer to relax and unwind at the end of the day by "letting out" any lingering emotions. Be sure to write honestly, don't overthink it, and stay focused.

Step 5 Re-read your past entries for insights.

Use your past entries to reflect on your life. As you read, ask yourself questions like, "Am I the same person who wrote this entry?", "Is my life going the way I want it to?", and "How can I work to solve any problems that may have been troubling me when I wrote this entry?"

Step 6 Give your journal some personal style.

The experiences you have while travelling can be some of the most influential ones in your life. Discovering the beauty of nature, making a friend in a far-off place, and even simply leaving your home can shape you, so document these things!

If you're using a digital journal, like a blog, try adding photographs to your posts, including links, and choosing colorful templates.

Writing Great Journal Entries

Step 1 Think of your journal as a safe place to express yourself.

If you're having trouble turning off your filter, try writing "free form" as an exercise - scrawling your thoughts down in a stream-of-consciousness form the moment they come to you, whether they make sense or not.

For instance, were you in a miserable mood when you wrote yesterday, but are now feeling better? Comment on this! By doing so, you may start to understand why you felt this way in the first place.

Step 4 Use writing prompts when you're bereft of ideas.

You may find that, by pursuing a prompt, your writing ventures into interesting new areas you might otherwise never have explored. Be adventurous and pursue these new topics to your heart's content!

The diary of Samuel Pepys
The Diary of a Young Girl (Anne Frank's diary)
The diary of Jemima Conduct
The diary of Franz Kafka
Bridget Jones's Diary
Diary of a Wimpy Kid
The Color Purple
Flowers for Algernon
Gentlemen Prefer Blondes

Expert Q&A

Reader Videos

Share a quick video tip and help bring articles to life with your friendly advice. Your insights could make a real difference and help millions of people!

Find a secluded and familiar place to write (for example, your bedroom with the door locked), but other secluded places are good too. (Your backyard.) Thanks Helpful 7 Not Helpful 0
It's best to write with a pen because pencil can fade. Thanks Helpful 8 Not Helpful 3
It's best if it is a secret. It's better if no one reads about your feelings and your secrets. Thanks Helpful 6 Not Helpful 3

Always keep it in a safe no-one-knows box of secrets after writing. It's best if it has a lock. Thanks Helpful 85 Not Helpful 7
If this person does and reads it, confront them and tell them you absolutely do not want them to read it. Then take necessary precautions, such as getting a notebook with a lock. Thanks Helpful 77 Not Helpful 7
Your secrets may be posted around the net if you don't lock it. (This is for blog authors only.) Thanks Helpful 60 Not Helpful 8
Someone could find out about your journal. Thanks Helpful 67 Not Helpful 15

Things You'll Need

A cheap but good composition notebook.
A working pen or pencil.
Colouring in pens or pencils.

↑ https://docs.google.com/
↑ https://psychcentral.com/blog/ready-set-journal-64-journaling-prompts-for-self-discovery
↑ https://www.psychologytoday.com/us/blog/mindful-musings/201611/3-reasons-let-yourself-feel-your-emotions
↑ Catherine Boswell, PhD. Licensed Psychologist. Expert Interview. 29 December 2020.
↑ https://www.writersdigest.com/whats-new/7-writing-routines-that-work
↑ https://www.theguardian.com/lifeandstyle/2014/mar/22/how-to-start-journal-writing-drawing
↑ https://www.washingtonpost.com/travel/tips/travel-photos-journal-memories-/
↑ https://www.urmc.rochester.edu/encyclopedia/content.aspx?ContentID=4552&ContentTypeID=1
↑ https://psychcentral.com/blog/ready-set-journal-64-journaling-prompts-for-self-discovery#the-journal-prompts

About This Article

To write a journal entry, start by writing down the date, time, and location where you're writing. Then, let your emotions flow and write about your feelings, like your family life, crush, or dreams. Try not to overthink it by writing things down as soon as they come into your head. You can also use writing prompts. To make your entries as useful as possible, get into a routine of writing regularly. Then, review your past entries to assess your feelings with the benefit of hindsight. To see a list of some famous journal writers and get tips on how to decorate your journal, read on! Did this summary help you? Yes No

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How to Journal

Your complete guide to getting started with journaling.

Do you want to learn how to journal, but are unsure where to start? Or you want to know what to write in a journal? Maybe you’ve heard of creative journaling and are curious what it is? Perhaps you’re a writer and want to journal to deepen your craft?

This comprehensive “How to Journal” article will answer all of your questions about journal writing. For example, what journal writing is, how you can use it, and what benefits you can experience from this type of writing. It also includes many journal writing prompts to help you get started. Lastly, while journal writing is typically a solitary act, you don’t have to journal alone or in isolation. This article will tell you where you can get some help and support for your journal writing, including being part of a journal writing community or group.

This Article Covers:

What is Journal Writing?

What can i use journaling for.

How to Journal – What are the Benefits?
Getting Started with Journaling
Creating a Journal Writing Ritual
How to Journal – What To Write?
How Often Should I Write in my Journal?

Do You Need to Write Regularly in a Journal?

How To Journal Consistently – Creating the Journaling Habit
How to Journal – What Help and Support Can I Get?
In Conclusion

Before we talk about how to journal, let’s look at what journaling is.

Journal Writing is the practice of taking time for yourself to write and reflect on your thoughts, feelings and life experiences. There are many suggestions for how to journal and what to write about. However, the beauty of journal writing is you can do it in your own way. This means you can really make it your own creative and life enhancing practice.

There are lots of people who write in a journal. I recently heard that 16% of the world’s population regularly writes in a journal. You could loosely test this claim yourself by asking a group of friends or family if they write in a journal and see what percentage say yes.

Each person will give a slightly different answer when asked, “What is journaling?” But in essence, journaling is the simple and profound act of capturing and understanding our lives through expressive writing and story. Expressive writing includes writing about our thoughts and feelings while gaining self-awareness and new discoveries along the way. Journaling is all about exploring and enriching life through narrative, words and creative self-expression through writing.

Journaling is…

a powerful tool for personal growth, self-discovery, improved health and creative self-expression
a fun and creative life enhancing practice
used by many successful people, including Oprah and Jack Canfield (author of Chicken Soup for the Soul books), to achieve success in life and work

“Journal writing is one of the rare forms of writing in which freedom of form and content support each other magically.” – Stephanie Dowrick

You can use journal writing to get to know yourself better, solve problems, make life decisions, improve your health and increase feelings of gratitude and joy. Journaling can also help you heal from stressful life circumstances, deal with grief and loss, or other life transitions. Or just journal for the pure love it!

Journaling is a fun, nourishing and creative practice that simply requires something to write with and write on. Whether it’s a pen and notebook, loose paper, cue cards, you get to choose your journaling tools!

People use journal writing in different ways for a variety of reasons. One person might journal to heal a broken heart writing an unsent letter sharing what they wish they’d said to that person. Someone else might journal to celebrate their accomplishments and make a list of their recent successes in their journal.

There are also a wide variety of journaling methods and techniques to get the most out of your journaling. You can use it for whatever matters most to you at this time in your life.

How to Journal – What are the Benefits?

There are many evidence-based benefits of journal writing from over 30 years of research in the expressive writing field. Yes, journal writing is a field of work!

People use the journaling process for many reasons, including to:

stimulate a healthier mind and body
vent and express thoughts and feelings in a healthy, constructive manner
increase self-awareness
create clarity for decision-making
track progress and personal growth
celebrate successes
heal emotional pain and trauma
increase self-care
manage stress and prevent burnout
gain broader and multiple perspectives
practice writing in a non-judgmental setting
improve creative thinking
preserve memories
get closer to God or a divine energy source

Today, journaling is widely accepted as a means for cultivating wellness as part of a whole person health approach. This includes the emotional, physical, psychological and spiritual dimensions of well-being. Journaling is also being used across various disciplines, such as education, psychology, leadership, business, health, creative writing, coaching and counselling fields, as a powerful tool for learning and growth.

How to Journal – Getting Started

Get organized.

One of the first things to do when you start a journal is get your journaling tools organized.

It can be fun to pick out your favourite pen and an inspiring journal. Look online or go into any book, stationary or office supply store and you’ll find all kinds of journals, pens, markers and other things you might like to use in your journal such as stickers or other creative touches.

So over time, you can experiment with your journaling tools. Do you like blank pages or lined? Would you prefer a small journal or a large sketchbook style journal? Would you use the same style journal or mix it up and try something new each time you begin a new one?

Sometimes people use loose leaf paper and put their journaling pages in a binder, or write small entries on cue cards. And some people even use big 18 x 24 pages of paper for larger visual journaling entries. You can create a mixed media art journal and much more.

Image of hand starting to write in journal

Just Write!

The key is to pick some simple journaling tools to start with – a pen and notebook – and just start writing.

Your writing will teach you what you need. For example, I used to write in a small lined journal and over the years, my writing longed for larger, open, clear spaces to fill. Now I use an 8 ½ by 11 blank page sketchbook, spiral bound and I keep my pilot pen in the spine of the journal.

Find your own tools and make your own way as you write. The only way to journal, is to write. And then write some more.

Whether you’re an avid journal writer, someone who journaled in the past, or have never written in a journal before:

“There is a Spanish proverb which says: there is no road, we make the road as we walk. I would say the same thing about journal writing: we make the path as we write.” Christina Baldwin

How to Journal – Creating Writing Rituals

What is a journaling writing ritual.

Dr. James Pennebaker, author of Writing to Heal: A Guided Journal for Recovering from Trauma & Emotional Upheaval , suggests some conditions that help enhance the expressive writing process. His research shows that creating a journal writing ritual is very beneficial.

Being focused, non-judgmental, and connected to your interior world fosters deeper writing. But, it’s not a frame of mind that everyone can simply switch on and off.

The idea behind creating a ritual is to create a unique environment and/or behavior which helps you sink into the best journal writing mindset possible. The purpose of the ritual is to take you away from everyday life. Your ritual contains the cues you create for yourself which help you become relaxed, alert, and reflective.

How do you Create a Journal Writing Ritual?

Here are some suggestions, but remember, the ritual you create to transition into deeper journal writing is uniquely yours.

Select some music that creates a sense of serenity. Play it for five minutes, focusing on simply listening to the music. Consider closing your eyes. Do not read your mail or straighten out your desk! You may want to have just one piece of music you use each time as your centering pre-writing ritual. Or choose three or four pieces you love for some variety.
Begin with several minutes of a meditation or a prayer. You can write just for the occasion or create something spontaneously each time.
Brew a cup of tea or coffee, or pour yourself some fresh juice. Perhaps a glass of wine? Spend a few minutes holding the cup, feeling the warmth, smelling the aromas of your drink and deeply enjoy those sensations.

Write in an environment that’s inspiring for your journal writing

This could be by a bright and sunny window or a softly lit corner nestled in a cozy chair.
Light a candle and while lighting the candle say an affirmation, your intention or make a wish.

Journal at approximately the same time each day

This doesn’t have to be at the same hour each day, but it’s helpful if it’s at the same time in your daily routine. For example half an hour before bed, which will work whether you go to bed at 10pm or at midnight.

The trick, of course, is to find the cues that help you settle in quickly. Initially, experiment with different rituals to see which feels best and then stick with the practice once you’ve found one you like. Remember to use as many of your senses (smell, sight, touch, hearing and taste) as you can when creating your centering ritual.

Image of woman journaling to create a ritual for how to journal article

How to Journal – What To Write

You can write about anything you want to write about. For example write about your day including your thoughts, feelings, problems, challenges, upsets, joys, successes and dreams. Here are some journaling prompts to help you get started:

Right now, I am feeling…
In the moment, I notice…
Currently, I am thinking about…
So far, the best part about my week is…

You can also write about what you don’t want to write about—and explore your resistance!

Resistance offers you information about where you’re feeling stuck, perhaps procrastinating, or simply not quite sure how to proceed. Here are some journaling prompts to play with around resistance:

At the moment, I don’t really want to write about (and then write about it anyways)…
I am feeling resistant because…
If I wasn’t feeling resistant, what might be different in my life right now…

You can free write (simply go to the page and start writing) or you can do more structured journal writing activities such as using prompts.

There are many other journal writing techniques and methods such as mind maps, cluster drawings, dialogue writing, captured moments, poetic writing and more that you can learn about and use to keep your journal writing fresh and interesting.

Access our free 7 Servings of Journal Juice for new ideas on what to write about in your journal. And you’ll also receive journal writing prompts, exercises, tips and our inspiring Journaling Museletter .

How To Journal – How Often Should I Write

There are no rules about how often you should write in your journal. Like anything, the more often you do something that’s good for you, the more benefits you get from it. I doubt you would go for one walk around the block and expect to experience significant health benefits from it.

The same is true for journaling. While that one walk would have offered you ‘in the moment’ benefits like time to relax, feeling good from moving your body, fresh air and more, the same is true for journaling.

You could gain a sense of relief, renewal and replenishment from just 10 minutes of writing about your thoughts, feelings and life observations.

Journal Regularly

Much like any other activity that’s good for you like brushing your teeth, meditating or eating a healthy diet, journaling can also be done regularly. Journaling makes a great healthy daily habit.

Set a Timer

I often facilitate timed journal writing exercises in workshops and retreats that I offer. It’s a core part of my Transformational Writing for Wellness Salon , a 6 week group coaching program that takes people into the heart and art of transformational journaling.

So often people say, “I can’t believe how much I wrote in just 5 minutes” or “I can’t believe I gained new insights when I just wrote for 7 minutes!”

Journaling to Cope

Many people only write in their journals when they are going through difficult times. Then once things are going better, they stop writing. This is also a valuable way to use your journal as a life companion to help you cope during stressful or troubled times.

The key is not to get too caught up in “shoulds”: I should journal today, I should journal more often. That’s because ‘shoulds’ can open the door for negative self-talk and feelings of inadequacy and shame. Instead, your journaling practice is best treated like a kind friend. You journal because you want to, and because it’s an enjoyable, or at least helpful, relaxing experience.

It’s a question that most journal writers face at some point. Does it matter if you write often in your journal? Well, whether you write regularly depends on your purpose for writing. Is it to preserve memories? To sort out issues? To track physical or emotional, spiritual, or intellectual progress? Track health symptoms?

If journal writing is pleasurable, then writing is its own reward. If journal writing becomes a task you “should” do, rather than something you enjoy, then you’ll write less consistently.

So part of the issue can be reframed by asking, ”How do I make journal writing pleasurable?” The answer to this question will help you find your own way to make journaling a consistent and enjoyable habit.

How To Journal Consistently – Creating the Journaling Habit

Think of writing a journal entry as the lowest cost and highest benefit way of taking care of your health. Remember that writing about meaningful events or activities in your life has been proven to positively impact your overall health without major cost of time or money and without having to leave your home!

If you do want to write in your journal on a regular basis and truly create the journaling habit, here are a few ideas to help you keep writing consistently:

Make your journal writing more upbeat

Review the good things that have happened in your day—your attitude, your progress toward a goal, a minor victory, even a two-minute interaction with someone that went well.
Remind yourself about the good stuff in your life and your good qualities.

Write when you have difficult issues in your life that need to be resolved

Who doesn’t experience difficult times? Consider the time that you write in your journal as an oasis of self-nurturing in your day. It’s a time to vent, rant, reflect, and process just for you.

If possible, write at the same time every day

Incorporate your writing practice into a daily routine.

Make it short and fun!

Write a one-word journal entry that captures your day.
It’s a challenge to come up with that one word. You can think about it while you are doing some mindless life maintenance activity—like flossing your teeth, taking out the garbage, or folding clothes.
Then once you’ve determined that word, writing your journal entry takes almost no time.

Back to the question: Does it really matter that you write consistently?

Writing consistently helps you maintain your journaling practice. It means that when you re-read your journal, there are enough entries to have meaning and flow.

Your ability to write consistently in your journal will be determined by how you feel and doing what’s right for you. So, while you’re writing and when you finish, notice how you feel.

Did you like the process?
Were you feeling relaxed and soothed during or after writing?
Did you feel at times frustrated, angry, confused, despairing?

This whole spectrum of emotions is simply part of the process of journal writing. I know that I feel better most of the time after I write – like I’ve released a burden or relived a pleasurable part of my day.

How to Journal – What Help and Support Can I Get?

One of the best ways to learn more about how to journal is with the support of a like minded community. When we join with fellow journal writers there are regular opportunities to connect, learn and be inspired about journaling. People who like yoga connect in yoga communities, and the same is true for meditation, scrapbooking, running and more. There is a human instinct to find supportive communities who share our passion or interest, so we can learn and grow together.

At the IAJW, our journal writing community is for extroverts and introverts alike. Perhaps you want the inspiration and support of a community, but would rather sit back quietly and take it all in. Or maybe you want to chat with fellow journal writers live on our monthly Zoom Chats with guest experts. You can gain regular help and support for your unique approach to journal writing.

People journal writing in group for how to journal article

Join our Online Journal Writing Community

We know there is power in community. So come join fellow journal writers in the International Association for Journal Writing ! We offer a learning and inspirational community for journal writers worldwide. Access monthly online writing circles, interviews with guest experts in the field of journaling and expressive writing, courses, journaling tools, e-books and much more.

We also have our Journal Writing Facebook group . Connect with fellow journal writers, receive journal writing tips and prompts to support you on your unique journal writing journey. Everyone is welcome!

Treat Yourself to a Journal Writing Retreat

Lastly, you might want to join one of our virtual Renew You Writing Retreats . Take 3 hours for yourself to journal in a guided and nourishing way. Whether you want to kick-start or reinvigorate your journaling practice, this retreat gives you time for creative self-care and renewal!

“Wow! What an awesome experience! I must admit I was a tad bit skeptical about an online retreat. But woah! Was I wrong! The Renew You Writing Retreat was so invigorating, uplifting, therapeutic, inspirational….just plain awesomesauce. Have you ever had an experience like that? You go in a little skeptical and come out blown away? Have you had the experience of being deeply inspired through writing and sharing with others? If not, you’re missing out! Thank you, Lynda, for creating such a wonderful space and experience.” Airial W. Dandridge, Certified Life Coach

How to Journal – In Conclusion

If you’ve read this far, I know you’re passionate (or at least curious about) the many benefits of journal writing. Journaling is an empowering experience because you’re always the expert of your own life. Journaling helps you explore both your inner and outer worlds and make sense of your life experience.

As a Registered Social Worker and Certified Co-Active Life Coach, I have been immersed in human transformation, growth, change and wellness for the past 30 years. I’ve learned many different tools and techniques for self-care, healing and growth through my studies and first-hand experience. Journaling is my go to practice that helps me live an intentional, healthy and happy life. And it has helped many people to do the same! Including you, perhaps?

There is only one way to experience the many benefits of journal writing—pick up your pen and write!

“Writing was the healing place where I could collect bits and pieces, where I could put them together again…written words change us all and make us more than we could ever be without them.” bell hooks

May your journaling support you to live an incredible life!

Authors : Lynda Monk, Director of IAJW and Ruth Folit, Founder of IAJW , partnered to write this How to Journal article, attempting to answer some of the most common questions that new and, in some cases, even seasoned journal writers have.

23 Comments

Such a wonderful article. Thank you for sharing!

Thanks, Diana!

I went to write lots bits to remember and copied it almost word for word in my common place book,but I love to write and am trying to get back into it,I’m writing for recovery from am 8yr relationship with a covert gaslighting narcissist,and I couldn’t write,let alone relax,I have been out for almost 2yrs,and when I start to feel joy or something didn’t work out and I’m hard on myself,I swear I can feel his presence in my house,he doesn’t know where I am,I left him and moved 2hr away in a different state,the feeling is almost overwhelming

Hi Dixie, personal writing can help heal from painful relationships. It’s great you are getting back into it!

Thank you both Lynda and Ruth for this wonderfully informative resource. Never too old to learn something new! Thank you both for bringing this to us.

Thanks, Lyn. Glad it offered some new ideas!

Great article Lynda! You’ve covered so many bases – lots of work, and very informative and knowledgeable as always :) Emma-Louise

Hi Emma, thanks for your kind feedback!

You two put together a beautiful and accessible piece here. It’s filled with all the vast experience and love you have for journaling. Thanks, Beth

Thanks so much, Beth! Your feedback means a lot to us.

Lynda, a beautiful gift to receive, words combing thoughts, insightful expressions and creative suggestions. Thank you for sharing a writing world held in heart, pen or typing starts journaling what is seen, felt or sensed from a human inner essence. Whole ❤️ Namaste.

Thank you, Denise! Namaste.

My name is Jacki Smallwood. I have been watching your sight on Facebook, and all the various gifts you have given while on the sight. I have been in a nursing home for 3 years and in quarantine for the past 11 months, not leaving my room, no guests, no funerals or graduation s. To keep my sanity u journal, I share my journaling with other residents through Messenger to help others cope. I don’t have access to copy machine nor anyone to take it out to staples. I am asking if anyone of your organization would donate material that would help me so much and then share with others. I get 45.00 a month from SS and need every penny for my needs. Anything you can do would be so helpful.

Seniors are a special group often ignored through this Covid.

Thank you for anything you could for me.

Jacky Smallwood

Hi Jacky, thank you for your note and request. I removed your mailing address from your original comment before publishing it for your privacy. I will reach out to you by email. I am glad journaling is helping you during this difficult time. More to follow, Lynda

Lynda, I’m very grateful to have ran across this article. I used to journal a lot when I was younger and I write poetry and music pretty consistently for the last few years. I have been told journaling could be amazing for me to get over some of my past pains and nasty relationships and getting to know myself, growing into a stronger (as well as better person), and just for my general mental health. So, as I begin to journal this very day, I was writing down many things that I want to include and accomplish with this journal inside the front pages of my book and I happened to run across your article! Now I just want to give you a big thank you BECAUSE I attained a lot of information, ideas, and format to include in my new journaling experience! I’m very excited to embark and I just wanted to let you know again I’m grateful for running across your words.

Chelsea Venice, Florida

Hi Chelsea, thanks for your note and for sharing some of your journaling hopes! I love the serendipity that you found our journaling website. We have lots of free journaling resources, including journaling prompts, that might be helpful along the way. You can find them here if you are interested: https://iajw.org/free-journaling-resources/ Happy journaling!

Thanks for your article esp the prompts to change the language and freshen up what I usually write.

wonderful article

Thank you so much for this article! When I was in my deepest months I would always journal but then once I got better I stopped journaling. I really want to get back into it but instead of writing about the bad in my life, I am going to focus on the good.

thank you for this article!

You’re welcome, Gwen. Thanks for reading.

I love the ideas for making journaling more appealing in order to journal more consistently. Sometimes I get so caught up in the “should do’s” that I forget that there really are no rules!

Very informative article on journaling! I’ve found journaling to be a wonderful practice for self-discovery and personal growth.

CEE Comm Lab helps first-year undergraduates present scientific research

The following is a modified excerpt from the MIT News article, “ First-year MIT students gain hands-on research experience in supportive peer community ” by Callie Ayoub.

During MIT’s Independent Activities Period (IAP) this January, first-year students interested in civil and environmental engineering (CEE) participated in a four-week undergraduate research opportunities program known as the mini-UROP (1.097). The six-unit subject pairs first-year students with a CEE graduate student or postdoc mentor, providing them with an inside look at the research being conducted in the department. The program culminates with a presentation event open to the entire CEE community.

Overall, eight labs in the department opened their doors to the 2024 cohort, who were eager to take advantage of the opportunity to collaborate with current students and build a community around their interests. The interdisciplinary nature of the department’s research offered participants a wide range of projects to work on, from redefining autonomous vehicle deployment to mitigating the effects of drought on crops.

Mini-UROP participant Iraira Rivera Rojas works in the Marelli Lab in CEE.

Throughout the duration of the mini-UROP, participants attended three workshops led by Jared Berezin , the manager of the Civil and Environmental Engineering Communication Lab (CEE Comm Lab). The communication lab is a free resource to undergraduates, graduates, and postdocs in the CEE community, providing one-on-one coaching and interactive workshops. Held on Fridays during IAP, the workshops focused on visual and oral communication strategies to help students contextualize their projects, explain scientific concepts, describe their methodologies, and present their results.

“Students were fortunate to have research mentors in the lab, and my goal was to provide communication mentorship outside of the lab,” says Berezin. “Our weekly workshops focused on scientific communication strategies, but perhaps more importantly I’d prompt them to talk about their projects, ask questions, and brainstorm together. They really embraced the opportunity to foster a supportive peer community, which I think is a core part of the CEE experience.”

Mini-UROP participants present their research to fellow students, staff, and faculty.

A significant challenge students face while completing the program is condensing their research down to a clear and concise two-minute presentation. To assist with this task, the workshops also featured presentations by CEE Communication Fellows Ignacio Arzuaga and Matthew Goss , providing students with a preview of how their own presentations may take shape. Before the final presentation event, students also had the option to meet with Comm Fellows to receive feedback, rehearse their talks, and practice responding to questions about their work.

“The final talks were impressive, and I was proud of the students for approaching both their research and communication challenges with such curiosity and thoughtfulness,” Berezin remarks.

To learn more about the experiences of students and mentors during the 2024 mini-UROP, you can read the full MIT News article .

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Student Opinion

Do You Keep a Journal?

What does journaling do for you?

By Jeremy Engle

Do you have a journal or a diary? If so, what do you like to write about in it, and why? Do you use it to process your feelings or rant about your friends and family? Or do you write to ruminate on your crushes and worries? Do you detail your dreams — both literal and figurative?

If you don’t journal, have you ever thought about starting but just didn’t know how?

In a guest essay, “ An Analog Library of All the Lives I’ve Lived ,” Josephine Sittenfeld writes about the power of journals — and the stories they tell about us:

After a routine iPhone update, a new Journal app recently appeared. Intrigued, I tapped it, which led to the instruction “Enable journaling suggestions.” If I agreed, my phone promised to give prompts like “Take a moment to write about something special in your life you’ve been taking for granted” and “Take a look around you and take a picture of something you’ve overlooked. What do you notice about it?” Apple is attempting to lure me into the world of Journaling 2.0, complete with the help of artificial intelligence. The app promises meaningful reflection, apparently gleaned from my phone usage, that I can share with people around me via Bluetooth. In the multipage permissions, the creepiest line explained that all I would have to do is tap a button for the app to utilize “information about your workouts, media use, communications and photos,” which would “create meaningful suggestions for you.” This isn’t the first time outside forces have suggested I reflect on my life. About 34 years ago, when I was 9, a family member gave me a “Ramona Quimby Diary.” The spiral-bound book contained a page of stickers that said, “Extra special!” and “Private! Keep out!” as well as leading prompts like, “This month I was really happy when …” and “The nicest person in my class is ….” Around then, a friend of my parents gave me another journal, with the title “My Private World.” That cover has a pensive, apron-wearing, barefoot girl seated under a sinewy tree, nestled alongside a dog, two cats and a book, with rolling mountains in the distance. I’ve never felt a connection to the girl, blissfully lost in thought in her bucolic setting. But the journal’s title? That spoke to me. It still does. I’ve kept a journal ever since. I have an oversize Tupperware bin in my basement containing dozens of musty diaries. Each is filled with anecdotes from my life, scrawled in sloppy handwriting, riddled with misspellings. They’re filled with rants about friends, family and feelings. They contain my shames and terrors, my crushes, my dreams (both literal and figurative), my worries and mundane accounts of more than 30 years of my life.

Ms. Sittenfeld concludes her essay by comparing the power of analog journals to digital ones:

I recently photographed my diaries set against sentimental garments: delicate, pint-size floral dresses my mom saved from the 1980s and stretched-out extra-large T-shirts from the 1990s. By making these photographs, I entered a portal to my youth, simultaneously connecting with my angsty, decorative, teenage self and appreciating her from afar. They remind me of who I was, who I’ve always been and, to some extent, who I still am. Whether or not it’s healthy, on some level, holding on to the stuff of my youth makes it more bearable to swallow the fact that time is always, incessantly, marching on. Which brings me back to that iPhone update. I still don’t fully understand Apple’s new Journal app. If it weren’t for the eerie fact that it mines phone usage to prompt reflection, I would be open to trying it. Regardless, I’m curious what changes when journaling moves into the cloud. Paging through an old diary is an emotional, time-travel experience. If a teenager today uses the Journal app, what will her experience be decades from now? Assuming the technology exists to retrieve her writing, will revisiting an online journal have the same power to transport her back in time? What’s her online equivalent of me holding the crispy, lined pages of my spiral-bound books from decades ago, touching the stickers, seeing my childhood handwriting and doodles in the margins?

Students, read the entire essay and then tell us:

Do you keep a diary or a journal? If so, what do you like to write about?

If you don’t journal, why not? Did reading the article persuade you to try? What else do you do to process or chronicle each day?

What do you see as the benefits of journaling? What advice would you give to others who are hesitant to keep a diary or are not sure what to write about?

Journals are a kind of time capsule for world events and your own life. Of rereading and photographing her collection of more than 30 years, Ms. Sittenfeld writes: “Paging through the diaries now. I’m startled to realize how far I’ve come and also how little I’ve changed.” If you were to look at your journals 20 or 30 years from now, what story do you think they would tell? What do you think you could learn about yourself?

At the end of Ms. Sittenfeld’s essay, she wonders what is lost when journaling moves into a digital space and diaries are saved on the cloud: “Paging through an old diary is an emotional, time-travel experience. If a teenager today uses the Journal app, what will her experience be decades from now?” What do you think of digital journals? Can they ever capture the magic of analog ones? Would you ever consider using a digital journal?

Students 13 and older in the United States and Britain, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public and may appear in print.

Find more Student Opinion questions here. Teachers, check out this guide to learn how you can incorporate these prompts into your classroom.

Jeremy Engle joined The Learning Network as a staff editor in 2018 after spending more than 20 years as a classroom humanities and documentary-making teacher, professional developer and curriculum designer working with students and teachers across the country. More about Jeremy Engle

LSU coach Kim Mulkey's feuding with the Washington Post. Here's what we know so far

As it turns out, the madness of March extends past the confines of the court.

LSU women's head basketball coach Kim Mulkey spent four minutes of a Saturday press conference going after her next opponent: the Washington Post .

Mulkey, who led the Tigers back to the NCAA tournament one year after winning a national title, accused the Post of writing an upcoming article framed as a "hit piece" about her. According to Mulkey, the Post's reporter has been working on the piece for the last two years and contacted multiple former coaches and players.

"I’ve hired the best defamation law firm in the country, and I will sue The Washington Post if they publish a false story about me," Mulkey said. "Not many people are in a position to hold these kinds of journalists accountable but I am, and I’ll do it."

A Washington Post spokesperson declined a comment request from USA TODAY on Saturday.

FOLLOW THE MADNESS: NCAA basketball bracket, scores, schedules, teams and more.

On Sunday, Mulkey had more to say when asked about her team's slow start against No. 11 Middle Tennessee State Tigers. While LSU eventually won handily, 83-56, the sluggish first half begged the question of whether the team was distracted.

“No. Listen, we’re not going to let one sleazy reporter distract us from what we’re trying to do. Absolutely not,” Mulkey said.

Here's everything we know so far about the upcoming article.

March Madness picks: Our Sunday bracket predictions for 2024 NCAA women's tournament

Rumors about a Kim Mulkey article surfaced on Friday

Pat Forde, a writer for Sports Illustrated, reported via social media platform X (formerly Twitter) on Friday that he heard about a "big Washington Post story in the works." According to Forde, the piece may come out as early as next week.

The Washington Post reporter has covered LSU in the past

According to Mulkey, the reporter in question, Kent Babb, had previously written an article about Brian Kelly for the Post. She "didn't appreciate" the story and refused to sit down with him as a result.

Mulkey said the writer sent LSU "more than a dozen questions" on Tuesday with a deadline to respond on Thursday, "right before we’re scheduled to tip-off." (LSU's women's basketball team played their first game of the tournament against Rice on Friday afternoon. They won, 70-60.)

She went on to say she believed the timing of the questioning and deadline were intentional, an attempt to distract her and her team from their current postseason run.

"It ain’t gonna work, buddy," Mulkey said.

"This is exactly why people don’t trust journalists and the media anymore. It’s these kinds of sleazy tactics and hatchet jobs that people are just tired of."

Women's March Madness games: Schedule, how to watch Sunday's NCAA Tournament games

Kent Babb has responded to Mulkey's comments

Though both Babb and the Post have declined most requests for comment from multiple outlets, Babb did confirm to the Associated Press he is working on a Mulkey profile. He also seemingly responded to Mulkey's press conference allegations and lawsuit threats in a Saturday post on X.

"Hit piece?" the post read with a link to Babb's aforementioned 2022 article on Brian Kelly.

It is so far unclear when the Washington Post will publish the upcoming story.

More From Forbes

Keep a daily “wins journal” to increase stamina and motivation.

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starting a wins journal

When pursuing an important long-term goal, it’s helpful to notice and appreciate the small accomplishments along the way. Acknowledging little victories boosts energy and motivation, increasing stamina for the long haul. Of course, small successes may also bring benefits themselves. Meeting a quarterly sales goal not only makes you more likely to hit your annual sales objective but also increases customers and revenue now .

Good managers help teams track successes and acknowledge small wins, but not everyone has a good manager. Some people, such as freelancers and solopreneurs, have no manager at all. If you don’t have anyone tracking your daily or weekly accomplishments—or even if you do, but still find yourself focusing on what you haven’t done while brushing off what you have—it may be time to make a practice of noticing little victories yourself.

One good way to track triumphs: keep a “wins journal.”

Write Your Way Forward

We’ve all read by now about the power of writing a gratitude journal (and maybe even seen articles on how to start one, such as this post on the Greater Good Science Center ). As studies show, shifting our focus from what we lack to what we’re grateful for can increase happiness and decrease depression. A “wins journal” is similar to a gratitude diary in that it has a specific focus—but with a different goal: helping you notice and record your victories; no success is too small.

Expressive and reflective writing in general have been shown to help release anxiety and stress, increase clarity and focus, and even improve your sleep. A study of a six-week journaling intervention for people who had experienced upheaval concluded that the practice “increases resilience, and decreases depressive symptoms, perceived stress, and rumination.” All of these benefits make personal writing a good habit to develop when it comes to supporting your career success. As this recent article in Forbes notes, “Journaling has emerged as a potent instrument for enhancing productivity, self-awareness, and success in the professional realm.”

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Recording wins can be a particularly powerful career-enhancement tool because it puts you in a progress mindset. As an article in Harvard Business Review puts it, “The more frequently people experience a feeling of progress, the more likely they are to be creatively productive in the long run. Whether they are trying to solve a major scientific mystery or simply produce a high-quality product or service, everyday progress—even a small win—can make all the difference in how they feel and perform.”

Helping Employees Harness the Power of Journaling

If you’re a manager, you can help employees track wins by giving them a journal expressly for this purpose—such as this Wins Journal by Jacqueline Kademian, or one from this selection of wins journals in different colors and patterns. Or, you could work writing into their weekly routine. Laura Hume, an Austin-based HR and human capital consultant, previously at Ernst and Young and IBM, instituted a weekly journaling practice for her direct reports at IBM. She instructed them to record three “big rocks” from each week by end-of-day Friday. (An idea borrowed from Stephen Covey, author of The 7 Habits of Highly Effective People , a “big rock” is anything someone considers important, including wins). She then referred to each person’s journal in weekly one-on-ones.

Hume initially wasn’t focused on tracking small wins to motivate employees, but rather to make meetings more efficient. “On the other hand”, she noted, “I would say that the documenting helps. We were looking at it as a team and we were having the accountability of a leader looking at it too.” The journal created a record of effort. “Looking back over it, I think I noticed - and they noticed - what we hadn’t done. That motivated us.”

Hume has been journaling since she was 11. “I love journals. I have all kinds of journal books.” Her employees didn’t share her love of writing, at least, not at first. But, “A couple of them came back afterward, during their annual reviews, and said it was incredibly helpful.”

Put Perfectionism In Its Place

Tracking small victories provides a daily boost of positive reinforcement, even from projects not yet finished or goals partially met. Acknowledging incremental progress can be a particularly helpful habit for people who hold themselves to extremely, or excessively, high standards. “We can get into a rut where we focus on what we want and don’t see what we have ,” says Ruth Klein, an author and executive coach who specializes in communications, productivity and mindset. “We don’t see the wins unless it’s like a million dollars. To achieve at a high degree is excellent, but to focus on perfection is being hard on oneself and not nurturing,”

Klein began encouraging clients to record small wins after trying it herself. “I’m a recovering perfectionist. There was a time when I felt that everything could be better. I’d get accolades, and it just wasn’t enough.” Klein started recording small victories, even bringing a notebook with her when she went out. “I began to see wins all over the place.”

Klein now uses wins journaling in “momentum groups” she leads, six-month-long accountability groups focusing on a range of topics from time management to courageousness. She has seen the practice pay off in increased confidence, momentum, and drive. “The way to be productive is to look for our wins, not dismiss them.” Making more calls? Getting one product feature right? Finding a coding bug? Resolving client issues? Each one is a win. “Catching the wins is in the center of everything.”

Notice How Work Victories Enhance Your Non-Career Life

While a wins journal can be helpful at work, it also can enhance your appreciation for successes outside of your career. Making a point to stop and record the roses—the small, pleasurable successes—can enhance your overall sense of contentment and joy. A personal small win might be a connection you made for someone else, a daily fitness goal achieved, or even an organizational task begun.

Or, in the case of a freelance writer in LA, tracking daily wins highlighted new ways in which her career contributed to her non-work life. “I used my writing and interviewing skills to help a dying family member start a legacy journal about her life, and then I shared some of her words at a memorial service, which turned out to be a powerful way to bring her spirit there. In another case, I tapped my professional network to get a top-notch editor for a musician friend working on a book. She said no one had ever done anything quite so supportive for her before. When writing down these wins, I realized how the years I’ve devoted to my career let me support others outside the competitive world of writing. It really gave me a new appreciation for the value of work, outside of work.”

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Published: 26 March 2024

Predicting and improving complex beer flavor through machine learning

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Metabolomics
Taste receptors

The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we combine extensive chemical and sensory analyses of 250 different beers to train machine learning models that allow predicting flavor and consumer appreciation. For each beer, we measure over 200 chemical properties, perform quantitative descriptive sensory analysis with a trained tasting panel and map data from over 180,000 consumer reviews to train 10 different machine learning models. The best-performing algorithm, Gradient Boosting, yields models that significantly outperform predictions based on conventional statistics and accurately predict complex food features and consumer appreciation from chemical profiles. Model dissection allows identifying specific and unexpected compounds as drivers of beer flavor and appreciation. Adding these compounds results in variants of commercial alcoholic and non-alcoholic beers with improved consumer appreciation. Together, our study reveals how big data and machine learning uncover complex links between food chemistry, flavor and consumer perception, and lays the foundation to develop novel, tailored foods with superior flavors.

BitterSweet: Building machine learning models for predicting the bitter and sweet taste of small molecules

Rudraksh Tuwani, Somin Wadhwa & Ganesh Bagler

Sensory lexicon and aroma volatiles analysis of brewing malt

Xiaoxia Su, Miao Yu, … Tianyi Du

Predicting odor from molecular structure: a multi-label classification approach

Kushagra Saini & Venkatnarayan Ramanathan

Introduction

Predicting and understanding food perception and appreciation is one of the major challenges in food science. Accurate modeling of food flavor and appreciation could yield important opportunities for both producers and consumers, including quality control, product fingerprinting, counterfeit detection, spoilage detection, and the development of new products and product combinations (food pairing) 1 , 2 , 3 , 4 , 5 , 6 . Accurate models for flavor and consumer appreciation would contribute greatly to our scientific understanding of how humans perceive and appreciate flavor. Moreover, accurate predictive models would also facilitate and standardize existing food assessment methods and could supplement or replace assessments by trained and consumer tasting panels, which are variable, expensive and time-consuming 7 , 8 , 9 . Lastly, apart from providing objective, quantitative, accurate and contextual information that can help producers, models can also guide consumers in understanding their personal preferences 10 .

Despite the myriad of applications, predicting food flavor and appreciation from its chemical properties remains a largely elusive goal in sensory science, especially for complex food and beverages 11 , 12 . A key obstacle is the immense number of flavor-active chemicals underlying food flavor. Flavor compounds can vary widely in chemical structure and concentration, making them technically challenging and labor-intensive to quantify, even in the face of innovations in metabolomics, such as non-targeted metabolic fingerprinting 13 , 14 . Moreover, sensory analysis is perhaps even more complicated. Flavor perception is highly complex, resulting from hundreds of different molecules interacting at the physiochemical and sensorial level. Sensory perception is often non-linear, characterized by complex and concentration-dependent synergistic and antagonistic effects 15 , 16 , 17 , 18 , 19 , 20 , 21 that are further convoluted by the genetics, environment, culture and psychology of consumers 22 , 23 , 24 . Perceived flavor is therefore difficult to measure, with problems of sensitivity, accuracy, and reproducibility that can only be resolved by gathering sufficiently large datasets 25 . Trained tasting panels are considered the prime source of quality sensory data, but require meticulous training, are low throughput and high cost. Public databases containing consumer reviews of food products could provide a valuable alternative, especially for studying appreciation scores, which do not require formal training 25 . Public databases offer the advantage of amassing large amounts of data, increasing the statistical power to identify potential drivers of appreciation. However, public datasets suffer from biases, including a bias in the volunteers that contribute to the database, as well as confounding factors such as price, cult status and psychological conformity towards previous ratings of the product.

Classical multivariate statistics and machine learning methods have been used to predict flavor of specific compounds by, for example, linking structural properties of a compound to its potential biological activities or linking concentrations of specific compounds to sensory profiles 1 , 26 . Importantly, most previous studies focused on predicting organoleptic properties of single compounds (often based on their chemical structure) 27 , 28 , 29 , 30 , 31 , 32 , 33 , thus ignoring the fact that these compounds are present in a complex matrix in food or beverages and excluding complex interactions between compounds. Moreover, the classical statistics commonly used in sensory science 34 , 35 , 36 , 37 , 38 , 39 require a large sample size and sufficient variance amongst predictors to create accurate models. They are not fit for studying an extensive set of hundreds of interacting flavor compounds, since they are sensitive to outliers, have a high tendency to overfit and are less suited for non-linear and discontinuous relationships 40 .

In this study, we combine extensive chemical analyses and sensory data of a set of different commercial beers with machine learning approaches to develop models that predict taste, smell, mouthfeel and appreciation from compound concentrations. Beer is particularly suited to model the relationship between chemistry, flavor and appreciation. First, beer is a complex product, consisting of thousands of flavor compounds that partake in complex sensory interactions 41 , 42 , 43 . This chemical diversity arises from the raw materials (malt, yeast, hops, water and spices) and biochemical conversions during the brewing process (kilning, mashing, boiling, fermentation, maturation and aging) 44 , 45 . Second, the advent of the internet saw beer consumers embrace online review platforms, such as RateBeer (ZX Ventures, Anheuser-Busch InBev SA/NV) and BeerAdvocate (Next Glass, inc.). In this way, the beer community provides massive data sets of beer flavor and appreciation scores, creating extraordinarily large sensory databases to complement the analyses of our professional sensory panel. Specifically, we characterize over 200 chemical properties of 250 commercial beers, spread across 22 beer styles, and link these to the descriptive sensory profiling data of a 16-person in-house trained tasting panel and data acquired from over 180,000 public consumer reviews. These unique and extensive datasets enable us to train a suite of machine learning models to predict flavor and appreciation from a beer’s chemical profile. Dissection of the best-performing models allows us to pinpoint specific compounds as potential drivers of beer flavor and appreciation. Follow-up experiments confirm the importance of these compounds and ultimately allow us to significantly improve the flavor and appreciation of selected commercial beers. Together, our study represents a significant step towards understanding complex flavors and reinforces the value of machine learning to develop and refine complex foods. In this way, it represents a stepping stone for further computer-aided food engineering applications 46 .

To generate a comprehensive dataset on beer flavor, we selected 250 commercial Belgian beers across 22 different beer styles (Supplementary Fig. S1 ). Beers with ≤ 4.2% alcohol by volume (ABV) were classified as non-alcoholic and low-alcoholic. Blonds and Tripels constitute a significant portion of the dataset (12.4% and 11.2%, respectively) reflecting their presence on the Belgian beer market and the heterogeneity of beers within these styles. By contrast, lager beers are less diverse and dominated by a handful of brands. Rare styles such as Brut or Faro make up only a small fraction of the dataset (2% and 1%, respectively) because fewer of these beers are produced and because they are dominated by distinct characteristics in terms of flavor and chemical composition.

Extensive analysis identifies relationships between chemical compounds in beer

For each beer, we measured 226 different chemical properties, including common brewing parameters such as alcohol content, iso-alpha acids, pH, sugar concentration 47 , and over 200 flavor compounds (Methods, Supplementary Table S1 ). A large portion (37.2%) are terpenoids arising from hopping, responsible for herbal and fruity flavors 16 , 48 . A second major category are yeast metabolites, such as esters and alcohols, that result in fruity and solvent notes 48 , 49 , 50 . Other measured compounds are primarily derived from malt, or other microbes such as non- Saccharomyces yeasts and bacteria (‘wild flora’). Compounds that arise from spices or staling are labeled under ‘Others’. Five attributes (caloric value, total acids and total ester, hop aroma and sulfur compounds) are calculated from multiple individually measured compounds.

As a first step in identifying relationships between chemical properties, we determined correlations between the concentrations of the compounds (Fig. 1 , upper panel, Supplementary Data 1 and 2 , and Supplementary Fig. S2 . For the sake of clarity, only a subset of the measured compounds is shown in Fig. 1 ). Compounds of the same origin typically show a positive correlation, while absence of correlation hints at parameters varying independently. For example, the hop aroma compounds citronellol, and alpha-terpineol show moderate correlations with each other (Spearman’s rho=0.39 and 0.57), but not with the bittering hop component iso-alpha acids (Spearman’s rho=0.16 and −0.07). This illustrates how brewers can independently modify hop aroma and bitterness by selecting hop varieties and dosage time. If hops are added early in the boiling phase, chemical conversions increase bitterness while aromas evaporate, conversely, late addition of hops preserves aroma but limits bitterness 51 . Similarly, hop-derived iso-alpha acids show a strong anti-correlation with lactic acid and acetic acid, likely reflecting growth inhibition of lactic acid and acetic acid bacteria, or the consequent use of fewer hops in sour beer styles, such as West Flanders ales and Fruit beers, that rely on these bacteria for their distinct flavors 52 . Finally, yeast-derived esters (ethyl acetate, ethyl decanoate, ethyl hexanoate, ethyl octanoate) and alcohols (ethanol, isoamyl alcohol, isobutanol, and glycerol), correlate with Spearman coefficients above 0.5, suggesting that these secondary metabolites are correlated with the yeast genetic background and/or fermentation parameters and may be difficult to influence individually, although the choice of yeast strain may offer some control 53 .

Spearman rank correlations are shown. Descriptors are grouped according to their origin (malt (blue), hops (green), yeast (red), wild flora (yellow), Others (black)), and sensory aspect (aroma, taste, palate, and overall appreciation). Please note that for the chemical compounds, for the sake of clarity, only a subset of the total number of measured compounds is shown, with an emphasis on the key compounds for each source. For more details, see the main text and Methods section. Chemical data can be found in Supplementary Data 1 , correlations between all chemical compounds are depicted in Supplementary Fig. S2 and correlation values can be found in Supplementary Data 2 . See Supplementary Data 4 for sensory panel assessments and Supplementary Data 5 for correlation values between all sensory descriptors.

Interestingly, different beer styles show distinct patterns for some flavor compounds (Supplementary Fig. S3 ). These observations agree with expectations for key beer styles, and serve as a control for our measurements. For instance, Stouts generally show high values for color (darker), while hoppy beers contain elevated levels of iso-alpha acids, compounds associated with bitter hop taste. Acetic and lactic acid are not prevalent in most beers, with notable exceptions such as Kriek, Lambic, Faro, West Flanders ales and Flanders Old Brown, which use acid-producing bacteria ( Lactobacillus and Pediococcus ) or unconventional yeast ( Brettanomyces ) 54 , 55 . Glycerol, ethanol and esters show similar distributions across all beer styles, reflecting their common origin as products of yeast metabolism during fermentation 45 , 53 . Finally, low/no-alcohol beers contain low concentrations of glycerol and esters. This is in line with the production process for most of the low/no-alcohol beers in our dataset, which are produced through limiting fermentation or by stripping away alcohol via evaporation or dialysis, with both methods having the unintended side-effect of reducing the amount of flavor compounds in the final beer 56 , 57 .

Besides expected associations, our data also reveals less trivial associations between beer styles and specific parameters. For example, geraniol and citronellol, two monoterpenoids responsible for citrus, floral and rose flavors and characteristic of Citra hops, are found in relatively high amounts in Christmas, Saison, and Brett/co-fermented beers, where they may originate from terpenoid-rich spices such as coriander seeds instead of hops 58 .

Tasting panel assessments reveal sensorial relationships in beer

To assess the sensory profile of each beer, a trained tasting panel evaluated each of the 250 beers for 50 sensory attributes, including different hop, malt and yeast flavors, off-flavors and spices. Panelists used a tasting sheet (Supplementary Data 3 ) to score the different attributes. Panel consistency was evaluated by repeating 12 samples across different sessions and performing ANOVA. In 95% of cases no significant difference was found across sessions ( p > 0.05), indicating good panel consistency (Supplementary Table S2 ).

Aroma and taste perception reported by the trained panel are often linked (Fig. 1 , bottom left panel and Supplementary Data 4 and 5 ), with high correlations between hops aroma and taste (Spearman’s rho=0.83). Bitter taste was found to correlate with hop aroma and taste in general (Spearman’s rho=0.80 and 0.69), and particularly with “grassy” noble hops (Spearman’s rho=0.75). Barnyard flavor, most often associated with sour beers, is identified together with stale hops (Spearman’s rho=0.97) that are used in these beers. Lactic and acetic acid, which often co-occur, are correlated (Spearman’s rho=0.66). Interestingly, sweetness and bitterness are anti-correlated (Spearman’s rho = −0.48), confirming the hypothesis that they mask each other 59 , 60 . Beer body is highly correlated with alcohol (Spearman’s rho = 0.79), and overall appreciation is found to correlate with multiple aspects that describe beer mouthfeel (alcohol, carbonation; Spearman’s rho= 0.32, 0.39), as well as with hop and ester aroma intensity (Spearman’s rho=0.39 and 0.35).

Similar to the chemical analyses, sensorial analyses confirmed typical features of specific beer styles (Supplementary Fig. S4 ). For example, sour beers (Faro, Flanders Old Brown, Fruit beer, Kriek, Lambic, West Flanders ale) were rated acidic, with flavors of both acetic and lactic acid. Hoppy beers were found to be bitter and showed hop-associated aromas like citrus and tropical fruit. Malt taste is most detected among scotch, stout/porters, and strong ales, while low/no-alcohol beers, which often have a reputation for being ‘worty’ (reminiscent of unfermented, sweet malt extract) appear in the middle. Unsurprisingly, hop aromas are most strongly detected among hoppy beers. Like its chemical counterpart (Supplementary Fig. S3 ), acidity shows a right-skewed distribution, with the most acidic beers being Krieks, Lambics, and West Flanders ales.

Tasting panel assessments of specific flavors correlate with chemical composition

We find that the concentrations of several chemical compounds strongly correlate with specific aroma or taste, as evaluated by the tasting panel (Fig. 2 , Supplementary Fig. S5 , Supplementary Data 6 ). In some cases, these correlations confirm expectations and serve as a useful control for data quality. For example, iso-alpha acids, the bittering compounds in hops, strongly correlate with bitterness (Spearman’s rho=0.68), while ethanol and glycerol correlate with tasters’ perceptions of alcohol and body, the mouthfeel sensation of fullness (Spearman’s rho=0.82/0.62 and 0.72/0.57 respectively) and darker color from roasted malts is a good indication of malt perception (Spearman’s rho=0.54).

Heatmap colors indicate Spearman’s Rho. Axes are organized according to sensory categories (aroma, taste, mouthfeel, overall), chemical categories and chemical sources in beer (malt (blue), hops (green), yeast (red), wild flora (yellow), Others (black)). See Supplementary Data 6 for all correlation values.

Interestingly, for some relationships between chemical compounds and perceived flavor, correlations are weaker than expected. For example, the rose-smelling phenethyl acetate only weakly correlates with floral aroma. This hints at more complex relationships and interactions between compounds and suggests a need for a more complex model than simple correlations. Lastly, we uncovered unexpected correlations. For instance, the esters ethyl decanoate and ethyl octanoate appear to correlate slightly with hop perception and bitterness, possibly due to their fruity flavor. Iron is anti-correlated with hop aromas and bitterness, most likely because it is also anti-correlated with iso-alpha acids. This could be a sign of metal chelation of hop acids 61 , given that our analyses measure unbound hop acids and total iron content, or could result from the higher iron content in dark and Fruit beers, which typically have less hoppy and bitter flavors 62 .

Public consumer reviews complement expert panel data

To complement and expand the sensory data of our trained tasting panel, we collected 180,000 reviews of our 250 beers from the online consumer review platform RateBeer. This provided numerical scores for beer appearance, aroma, taste, palate, overall quality as well as the average overall score.

Public datasets are known to suffer from biases, such as price, cult status and psychological conformity towards previous ratings of a product. For example, prices correlate with appreciation scores for these online consumer reviews (rho=0.49, Supplementary Fig. S6 ), but not for our trained tasting panel (rho=0.19). This suggests that prices affect consumer appreciation, which has been reported in wine 63 , while blind tastings are unaffected. Moreover, we observe that some beer styles, like lagers and non-alcoholic beers, generally receive lower scores, reflecting that online reviewers are mostly beer aficionados with a preference for specialty beers over lager beers. In general, we find a modest correlation between our trained panel’s overall appreciation score and the online consumer appreciation scores (Fig. 3 , rho=0.29). Apart from the aforementioned biases in the online datasets, serving temperature, sample freshness and surroundings, which are all tightly controlled during the tasting panel sessions, can vary tremendously across online consumers and can further contribute to (among others, appreciation) differences between the two categories of tasters. Importantly, in contrast to the overall appreciation scores, for many sensory aspects the results from the professional panel correlated well with results obtained from RateBeer reviews. Correlations were highest for features that are relatively easy to recognize even for untrained tasters, like bitterness, sweetness, alcohol and malt aroma (Fig. 3 and below).

RateBeer text mining results can be found in Supplementary Data 7 . Rho values shown are Spearman correlation values, with asterisks indicating significant correlations ( p < 0.05, two-sided). All p values were smaller than 0.001, except for Esters aroma (0.0553), Esters taste (0.3275), Esters aroma—banana (0.0019), Coriander (0.0508) and Diacetyl (0.0134).

Besides collecting consumer appreciation from these online reviews, we developed automated text analysis tools to gather additional data from review texts (Supplementary Data 7 ). Processing review texts on the RateBeer database yielded comparable results to the scores given by the trained panel for many common sensory aspects, including acidity, bitterness, sweetness, alcohol, malt, and hop tastes (Fig. 3 ). This is in line with what would be expected, since these attributes require less training for accurate assessment and are less influenced by environmental factors such as temperature, serving glass and odors in the environment. Consumer reviews also correlate well with our trained panel for 4-vinyl guaiacol, a compound associated with a very characteristic aroma. By contrast, correlations for more specific aromas like ester, coriander or diacetyl are underrepresented in the online reviews, underscoring the importance of using a trained tasting panel and standardized tasting sheets with explicit factors to be scored for evaluating specific aspects of a beer. Taken together, our results suggest that public reviews are trustworthy for some, but not all, flavor features and can complement or substitute taste panel data for these sensory aspects.

Models can predict beer sensory profiles from chemical data

The rich datasets of chemical analyses, tasting panel assessments and public reviews gathered in the first part of this study provided us with a unique opportunity to develop predictive models that link chemical data to sensorial features. Given the complexity of beer flavor, basic statistical tools such as correlations or linear regression may not always be the most suitable for making accurate predictions. Instead, we applied different machine learning models that can model both simple linear and complex interactive relationships. Specifically, we constructed a set of regression models to predict (a) trained panel scores for beer flavor and quality and (b) public reviews’ appreciation scores from beer chemical profiles. We trained and tested 10 different models (Methods), 3 linear regression-based models (simple linear regression with first-order interactions (LR), lasso regression with first-order interactions (Lasso), partial least squares regressor (PLSR)), 5 decision tree models (AdaBoost regressor (ABR), extra trees (ET), gradient boosting regressor (GBR), random forest (RF) and XGBoost regressor (XGBR)), 1 support vector regression (SVR), and 1 artificial neural network (ANN) model.

To compare the performance of our machine learning models, the dataset was randomly split into a training and test set, stratified by beer style. After a model was trained on data in the training set, its performance was evaluated on its ability to predict the test dataset obtained from multi-output models (based on the coefficient of determination, see Methods). Additionally, individual-attribute models were ranked per descriptor and the average rank was calculated, as proposed by Korneva et al. 64 . Importantly, both ways of evaluating the models’ performance agreed in general. Performance of the different models varied (Table 1 ). It should be noted that all models perform better at predicting RateBeer results than results from our trained tasting panel. One reason could be that sensory data is inherently variable, and this variability is averaged out with the large number of public reviews from RateBeer. Additionally, all tree-based models perform better at predicting taste than aroma. Linear models (LR) performed particularly poorly, with negative R 2 values, due to severe overfitting (training set R 2 = 1). Overfitting is a common issue in linear models with many parameters and limited samples, especially with interaction terms further amplifying the number of parameters. L1 regularization (Lasso) successfully overcomes this overfitting, out-competing multiple tree-based models on the RateBeer dataset. Similarly, the dimensionality reduction of PLSR avoids overfitting and improves performance, to some extent. Still, tree-based models (ABR, ET, GBR, RF and XGBR) show the best performance, out-competing the linear models (LR, Lasso, PLSR) commonly used in sensory science 65 .

GBR models showed the best overall performance in predicting sensory responses from chemical information, with R 2 values up to 0.75 depending on the predicted sensory feature (Supplementary Table S4 ). The GBR models predict consumer appreciation (RateBeer) better than our trained panel’s appreciation (R 2 value of 0.67 compared to R 2 value of 0.09) (Supplementary Table S3 and Supplementary Table S4 ). ANN models showed intermediate performance, likely because neural networks typically perform best with larger datasets 66 . The SVR shows intermediate performance, mostly due to the weak predictions of specific attributes that lower the overall performance (Supplementary Table S4 ).

Model dissection identifies specific, unexpected compounds as drivers of consumer appreciation

Next, we leveraged our models to infer important contributors to sensory perception and consumer appreciation. Consumer preference is a crucial sensory aspects, because a product that shows low consumer appreciation scores often does not succeed commercially 25 . Additionally, the requirement for a large number of representative evaluators makes consumer trials one of the more costly and time-consuming aspects of product development. Hence, a model for predicting chemical drivers of overall appreciation would be a welcome addition to the available toolbox for food development and optimization.

Since GBR models on our RateBeer dataset showed the best overall performance, we focused on these models. Specifically, we used two approaches to identify important contributors. First, rankings of the most important predictors for each sensorial trait in the GBR models were obtained based on impurity-based feature importance (mean decrease in impurity). High-ranked parameters were hypothesized to be either the true causal chemical properties underlying the trait, to correlate with the actual causal properties, or to take part in sensory interactions affecting the trait 67 (Fig. 4A ). In a second approach, we used SHAP 68 to determine which parameters contributed most to the model for making predictions of consumer appreciation (Fig. 4B ). SHAP calculates parameter contributions to model predictions on a per-sample basis, which can be aggregated into an importance score.

A The impurity-based feature importance (mean deviance in impurity, MDI) calculated from the Gradient Boosting Regression (GBR) model predicting RateBeer appreciation scores. The top 15 highest ranked chemical properties are shown. B SHAP summary plot for the top 15 parameters contributing to our GBR model. Each point on the graph represents a sample from our dataset. The color represents the concentration of that parameter, with bluer colors representing low values and redder colors representing higher values. Greater absolute values on the horizontal axis indicate a higher impact of the parameter on the prediction of the model. C Spearman correlations between the 15 most important chemical properties and consumer overall appreciation. Numbers indicate the Spearman Rho correlation coefficient, and the rank of this correlation compared to all other correlations. The top 15 important compounds were determined using SHAP (panel B).

Both approaches identified ethyl acetate as the most predictive parameter for beer appreciation (Fig. 4 ). Ethyl acetate is the most abundant ester in beer with a typical ‘fruity’, ‘solvent’ and ‘alcoholic’ flavor, but is often considered less important than other esters like isoamyl acetate. The second most important parameter identified by SHAP is ethanol, the most abundant beer compound after water. Apart from directly contributing to beer flavor and mouthfeel, ethanol drastically influences the physical properties of beer, dictating how easily volatile compounds escape the beer matrix to contribute to beer aroma 69 . Importantly, it should also be noted that the importance of ethanol for appreciation is likely inflated by the very low appreciation scores of non-alcoholic beers (Supplementary Fig. S4 ). Despite not often being considered a driver of beer appreciation, protein level also ranks highly in both approaches, possibly due to its effect on mouthfeel and body 70 . Lactic acid, which contributes to the tart taste of sour beers, is the fourth most important parameter identified by SHAP, possibly due to the generally high appreciation of sour beers in our dataset.

Interestingly, some of the most important predictive parameters for our model are not well-established as beer flavors or are even commonly regarded as being negative for beer quality. For example, our models identify methanethiol and ethyl phenyl acetate, an ester commonly linked to beer staling 71 , as a key factor contributing to beer appreciation. Although there is no doubt that high concentrations of these compounds are considered unpleasant, the positive effects of modest concentrations are not yet known 72 , 73 .

To compare our approach to conventional statistics, we evaluated how well the 15 most important SHAP-derived parameters correlate with consumer appreciation (Fig. 4C ). Interestingly, only 6 of the properties derived by SHAP rank amongst the top 15 most correlated parameters. For some chemical compounds, the correlations are so low that they would have likely been considered unimportant. For example, lactic acid, the fourth most important parameter, shows a bimodal distribution for appreciation, with sour beers forming a separate cluster, that is missed entirely by the Spearman correlation. Additionally, the correlation plots reveal outliers, emphasizing the need for robust analysis tools. Together, this highlights the need for alternative models, like the Gradient Boosting model, that better grasp the complexity of (beer) flavor.

Finally, to observe the relationships between these chemical properties and their predicted targets, partial dependence plots were constructed for the six most important predictors of consumer appreciation 74 , 75 , 76 (Supplementary Fig. S7 ). One-way partial dependence plots show how a change in concentration affects the predicted appreciation. These plots reveal an important limitation of our models: appreciation predictions remain constant at ever-increasing concentrations. This implies that once a threshold concentration is reached, further increasing the concentration does not affect appreciation. This is false, as it is well-documented that certain compounds become unpleasant at high concentrations, including ethyl acetate (‘nail polish’) 77 and methanethiol (‘sulfury’ and ‘rotten cabbage’) 78 . The inability of our models to grasp that flavor compounds have optimal levels, above which they become negative, is a consequence of working with commercial beer brands where (off-)flavors are rarely too high to negatively impact the product. The two-way partial dependence plots show how changing the concentration of two compounds influences predicted appreciation, visualizing their interactions (Supplementary Fig. S7 ). In our case, the top 5 parameters are dominated by additive or synergistic interactions, with high concentrations for both compounds resulting in the highest predicted appreciation.

To assess the robustness of our best-performing models and model predictions, we performed 100 iterations of the GBR, RF and ET models. In general, all iterations of the models yielded similar performance (Supplementary Fig. S8 ). Moreover, the main predictors (including the top predictors ethanol and ethyl acetate) remained virtually the same, especially for GBR and RF. For the iterations of the ET model, we did observe more variation in the top predictors, which is likely a consequence of the model’s inherent random architecture in combination with co-correlations between certain predictors. However, even in this case, several of the top predictors (ethanol and ethyl acetate) remain unchanged, although their rank in importance changes (Supplementary Fig. S8 ).

Next, we investigated if a combination of RateBeer and trained panel data into one consolidated dataset would lead to stronger models, under the hypothesis that such a model would suffer less from bias in the datasets. A GBR model was trained to predict appreciation on the combined dataset. This model underperformed compared to the RateBeer model, both in the native case and when including a dataset identifier (R 2 = 0.67, 0.26 and 0.42 respectively). For the latter, the dataset identifier is the most important feature (Supplementary Fig. S9 ), while most of the feature importance remains unchanged, with ethyl acetate and ethanol ranking highest, like in the original model trained only on RateBeer data. It seems that the large variation in the panel dataset introduces noise, weakening the models’ performances and reliability. In addition, it seems reasonable to assume that both datasets are fundamentally different, with the panel dataset obtained by blind tastings by a trained professional panel.

Lastly, we evaluated whether beer style identifiers would further enhance the model’s performance. A GBR model was trained with parameters that explicitly encoded the styles of the samples. This did not improve model performance (R2 = 0.66 with style information vs R2 = 0.67). The most important chemical features are consistent with the model trained without style information (eg. ethanol and ethyl acetate), and with the exception of the most preferred (strong ale) and least preferred (low/no-alcohol) styles, none of the styles were among the most important features (Supplementary Fig. S9 , Supplementary Table S5 and S6 ). This is likely due to a combination of style-specific chemical signatures, such as iso-alpha acids and lactic acid, that implicitly convey style information to the original models, as well as the low number of samples belonging to some styles, making it difficult for the model to learn style-specific patterns. Moreover, beer styles are not rigorously defined, with some styles overlapping in features and some beers being misattributed to a specific style, all of which leads to more noise in models that use style parameters.

Model validation

To test if our predictive models give insight into beer appreciation, we set up experiments aimed at improving existing commercial beers. We specifically selected overall appreciation as the trait to be examined because of its complexity and commercial relevance. Beer flavor comprises a complex bouquet rather than single aromas and tastes 53 . Hence, adding a single compound to the extent that a difference is noticeable may lead to an unbalanced, artificial flavor. Therefore, we evaluated the effect of combinations of compounds. Because Blond beers represent the most extensive style in our dataset, we selected a beer from this style as the starting material for these experiments (Beer 64 in Supplementary Data 1 ).

In the first set of experiments, we adjusted the concentrations of compounds that made up the most important predictors of overall appreciation (ethyl acetate, ethanol, lactic acid, ethyl phenyl acetate) together with correlated compounds (ethyl hexanoate, isoamyl acetate, glycerol), bringing them up to 95 th percentile ethanol-normalized concentrations (Methods) within the Blond group (‘Spiked’ concentration in Fig. 5A ). Compared to controls, the spiked beers were found to have significantly improved overall appreciation among trained panelists, with panelist noting increased intensity of ester flavors, sweetness, alcohol, and body fullness (Fig. 5B ). To disentangle the contribution of ethanol to these results, a second experiment was performed without the addition of ethanol. This resulted in a similar outcome, including increased perception of alcohol and overall appreciation.

Adding the top chemical compounds, identified as best predictors of appreciation by our model, into poorly appreciated beers results in increased appreciation from our trained panel. Results of sensory tests between base beers and those spiked with compounds identified as the best predictors by the model. A Blond and Non/Low-alcohol (0.0% ABV) base beers were brought up to 95th-percentile ethanol-normalized concentrations within each style. B For each sensory attribute, tasters indicated the more intense sample and selected the sample they preferred. The numbers above the bars correspond to the p values that indicate significant changes in perceived flavor (two-sided binomial test: alpha 0.05, n = 20 or 13).

In a last experiment, we tested whether using the model’s predictions can boost the appreciation of a non-alcoholic beer (beer 223 in Supplementary Data 1 ). Again, the addition of a mixture of predicted compounds (omitting ethanol, in this case) resulted in a significant increase in appreciation, body, ester flavor and sweetness.

Predicting flavor and consumer appreciation from chemical composition is one of the ultimate goals of sensory science. A reliable, systematic and unbiased way to link chemical profiles to flavor and food appreciation would be a significant asset to the food and beverage industry. Such tools would substantially aid in quality control and recipe development, offer an efficient and cost-effective alternative to pilot studies and consumer trials and would ultimately allow food manufacturers to produce superior, tailor-made products that better meet the demands of specific consumer groups more efficiently.

A limited set of studies have previously tried, to varying degrees of success, to predict beer flavor and beer popularity based on (a limited set of) chemical compounds and flavors 79 , 80 . Current sensitive, high-throughput technologies allow measuring an unprecedented number of chemical compounds and properties in a large set of samples, yielding a dataset that can train models that help close the gaps between chemistry and flavor, even for a complex natural product like beer. To our knowledge, no previous research gathered data at this scale (250 samples, 226 chemical parameters, 50 sensory attributes and 5 consumer scores) to disentangle and validate the chemical aspects driving beer preference using various machine-learning techniques. We find that modern machine learning models outperform conventional statistical tools, such as correlations and linear models, and can successfully predict flavor appreciation from chemical composition. This could be attributed to the natural incorporation of interactions and non-linear or discontinuous effects in machine learning models, which are not easily grasped by the linear model architecture. While linear models and partial least squares regression represent the most widespread statistical approaches in sensory science, in part because they allow interpretation 65 , 81 , 82 , modern machine learning methods allow for building better predictive models while preserving the possibility to dissect and exploit the underlying patterns. Of the 10 different models we trained, tree-based models, such as our best performing GBR, showed the best overall performance in predicting sensory responses from chemical information, outcompeting artificial neural networks. This agrees with previous reports for models trained on tabular data 83 . Our results are in line with the findings of Colantonio et al. who also identified the gradient boosting architecture as performing best at predicting appreciation and flavor (of tomatoes and blueberries, in their specific study) 26 . Importantly, besides our larger experimental scale, we were able to directly confirm our models’ predictions in vivo.

Our study confirms that flavor compound concentration does not always correlate with perception, suggesting complex interactions that are often missed by more conventional statistics and simple models. Specifically, we find that tree-based algorithms may perform best in developing models that link complex food chemistry with aroma. Furthermore, we show that massive datasets of untrained consumer reviews provide a valuable source of data, that can complement or even replace trained tasting panels, especially for appreciation and basic flavors, such as sweetness and bitterness. This holds despite biases that are known to occur in such datasets, such as price or conformity bias. Moreover, GBR models predict taste better than aroma. This is likely because taste (e.g. bitterness) often directly relates to the corresponding chemical measurements (e.g., iso-alpha acids), whereas such a link is less clear for aromas, which often result from the interplay between multiple volatile compounds. We also find that our models are best at predicting acidity and alcohol, likely because there is a direct relation between the measured chemical compounds (acids and ethanol) and the corresponding perceived sensorial attribute (acidity and alcohol), and because even untrained consumers are generally able to recognize these flavors and aromas.

The predictions of our final models, trained on review data, hold even for blind tastings with small groups of trained tasters, as demonstrated by our ability to validate specific compounds as drivers of beer flavor and appreciation. Since adding a single compound to the extent of a noticeable difference may result in an unbalanced flavor profile, we specifically tested our identified key drivers as a combination of compounds. While this approach does not allow us to validate if a particular single compound would affect flavor and/or appreciation, our experiments do show that this combination of compounds increases consumer appreciation.

It is important to stress that, while it represents an important step forward, our approach still has several major limitations. A key weakness of the GBR model architecture is that amongst co-correlating variables, the largest main effect is consistently preferred for model building. As a result, co-correlating variables often have artificially low importance scores, both for impurity and SHAP-based methods, like we observed in the comparison to the more randomized Extra Trees models. This implies that chemicals identified as key drivers of a specific sensory feature by GBR might not be the true causative compounds, but rather co-correlate with the actual causative chemical. For example, the high importance of ethyl acetate could be (partially) attributed to the total ester content, ethanol or ethyl hexanoate (rho=0.77, rho=0.72 and rho=0.68), while ethyl phenylacetate could hide the importance of prenyl isobutyrate and ethyl benzoate (rho=0.77 and rho=0.76). Expanding our GBR model to include beer style as a parameter did not yield additional power or insight. This is likely due to style-specific chemical signatures, such as iso-alpha acids and lactic acid, that implicitly convey style information to the original model, as well as the smaller sample size per style, limiting the power to uncover style-specific patterns. This can be partly attributed to the curse of dimensionality, where the high number of parameters results in the models mainly incorporating single parameter effects, rather than complex interactions such as style-dependent effects 67 . A larger number of samples may overcome some of these limitations and offer more insight into style-specific effects. On the other hand, beer style is not a rigid scientific classification, and beers within one style often differ a lot, which further complicates the analysis of style as a model factor.

Our study is limited to beers from Belgian breweries. Although these beers cover a large portion of the beer styles available globally, some beer styles and consumer patterns may be missing, while other features might be overrepresented. For example, many Belgian ales exhibit yeast-driven flavor profiles, which is reflected in the chemical drivers of appreciation discovered by this study. In future work, expanding the scope to include diverse markets and beer styles could lead to the identification of even more drivers of appreciation and better models for special niche products that were not present in our beer set.

In addition to inherent limitations of GBR models, there are also some limitations associated with studying food aroma. Even if our chemical analyses measured most of the known aroma compounds, the total number of flavor compounds in complex foods like beer is still larger than the subset we were able to measure in this study. For example, hop-derived thiols, that influence flavor at very low concentrations, are notoriously difficult to measure in a high-throughput experiment. Moreover, consumer perception remains subjective and prone to biases that are difficult to avoid. It is also important to stress that the models are still immature and that more extensive datasets will be crucial for developing more complete models in the future. Besides more samples and parameters, our dataset does not include any demographic information about the tasters. Including such data could lead to better models that grasp external factors like age and culture. Another limitation is that our set of beers consists of high-quality end-products and lacks beers that are unfit for sale, which limits the current model in accurately predicting products that are appreciated very badly. Finally, while models could be readily applied in quality control, their use in sensory science and product development is restrained by their inability to discern causal relationships. Given that the models cannot distinguish compounds that genuinely drive consumer perception from those that merely correlate, validation experiments are essential to identify true causative compounds.

Despite the inherent limitations, dissection of our models enabled us to pinpoint specific molecules as potential drivers of beer aroma and consumer appreciation, including compounds that were unexpected and would not have been identified using standard approaches. Important drivers of beer appreciation uncovered by our models include protein levels, ethyl acetate, ethyl phenyl acetate and lactic acid. Currently, many brewers already use lactic acid to acidify their brewing water and ensure optimal pH for enzymatic activity during the mashing process. Our results suggest that adding lactic acid can also improve beer appreciation, although its individual effect remains to be tested. Interestingly, ethanol appears to be unnecessary to improve beer appreciation, both for blond beer and alcohol-free beer. Given the growing consumer interest in alcohol-free beer, with a predicted annual market growth of >7% 84 , it is relevant for brewers to know what compounds can further increase consumer appreciation of these beers. Hence, our model may readily provide avenues to further improve the flavor and consumer appreciation of both alcoholic and non-alcoholic beers, which is generally considered one of the key challenges for future beer production.

Whereas we see a direct implementation of our results for the development of superior alcohol-free beverages and other food products, our study can also serve as a stepping stone for the development of novel alcohol-containing beverages. We want to echo the growing body of scientific evidence for the negative effects of alcohol consumption, both on the individual level by the mutagenic, teratogenic and carcinogenic effects of ethanol 85 , 86 , as well as the burden on society caused by alcohol abuse and addiction. We encourage the use of our results for the production of healthier, tastier products, including novel and improved beverages with lower alcohol contents. Furthermore, we strongly discourage the use of these technologies to improve the appreciation or addictive properties of harmful substances.

The present work demonstrates that despite some important remaining hurdles, combining the latest developments in chemical analyses, sensory analysis and modern machine learning methods offers exciting avenues for food chemistry and engineering. Soon, these tools may provide solutions in quality control and recipe development, as well as new approaches to sensory science and flavor research.

Beer selection

250 commercial Belgian beers were selected to cover the broad diversity of beer styles and corresponding diversity in chemical composition and aroma. See Supplementary Fig. S1 .

Chemical dataset

Sample preparation.

Beers within their expiration date were purchased from commercial retailers. Samples were prepared in biological duplicates at room temperature, unless explicitly stated otherwise. Bottle pressure was measured with a manual pressure device (Steinfurth Mess-Systeme GmbH) and used to calculate CO 2 concentration. The beer was poured through two filter papers (Macherey-Nagel, 500713032 MN 713 ¼) to remove carbon dioxide and prevent spontaneous foaming. Samples were then prepared for measurements by targeted Headspace-Gas Chromatography-Flame Ionization Detector/Flame Photometric Detector (HS-GC-FID/FPD), Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS), colorimetric analysis, enzymatic analysis, Near-Infrared (NIR) analysis, as described in the sections below. The mean values of biological duplicates are reported for each compound.

HS-GC-FID/FPD

HS-GC-FID/FPD (Shimadzu GC 2010 Plus) was used to measure higher alcohols, acetaldehyde, esters, 4-vinyl guaicol, and sulfur compounds. Each measurement comprised 5 ml of sample pipetted into a 20 ml glass vial containing 1.75 g NaCl (VWR, 27810.295). 100 µl of 2-heptanol (Sigma-Aldrich, H3003) (internal standard) solution in ethanol (Fisher Chemical, E/0650DF/C17) was added for a final concentration of 2.44 mg/L. Samples were flushed with nitrogen for 10 s, sealed with a silicone septum, stored at −80 °C and analyzed in batches of 20.

The GC was equipped with a DB-WAXetr column (length, 30 m; internal diameter, 0.32 mm; layer thickness, 0.50 µm; Agilent Technologies, Santa Clara, CA, USA) to the FID and an HP-5 column (length, 30 m; internal diameter, 0.25 mm; layer thickness, 0.25 µm; Agilent Technologies, Santa Clara, CA, USA) to the FPD. N 2 was used as the carrier gas. Samples were incubated for 20 min at 70 °C in the headspace autosampler (Flow rate, 35 cm/s; Injection volume, 1000 µL; Injection mode, split; Combi PAL autosampler, CTC analytics, Switzerland). The injector, FID and FPD temperatures were kept at 250 °C. The GC oven temperature was first held at 50 °C for 5 min and then allowed to rise to 80 °C at a rate of 5 °C/min, followed by a second ramp of 4 °C/min until 200 °C kept for 3 min and a final ramp of (4 °C/min) until 230 °C for 1 min. Results were analyzed with the GCSolution software version 2.4 (Shimadzu, Kyoto, Japan). The GC was calibrated with a 5% EtOH solution (VWR International) containing the volatiles under study (Supplementary Table S7 ).

HS-SPME-GC-MS

HS-SPME-GC-MS (Shimadzu GCMS-QP-2010 Ultra) was used to measure additional volatile compounds, mainly comprising terpenoids and esters. Samples were analyzed by HS-SPME using a triphase DVB/Carboxen/PDMS 50/30 μm SPME fiber (Supelco Co., Bellefonte, PA, USA) followed by gas chromatography (Thermo Fisher Scientific Trace 1300 series, USA) coupled to a mass spectrometer (Thermo Fisher Scientific ISQ series MS) equipped with a TriPlus RSH autosampler. 5 ml of degassed beer sample was placed in 20 ml vials containing 1.75 g NaCl (VWR, 27810.295). 5 µl internal standard mix was added, containing 2-heptanol (1 g/L) (Sigma-Aldrich, H3003), 4-fluorobenzaldehyde (1 g/L) (Sigma-Aldrich, 128376), 2,3-hexanedione (1 g/L) (Sigma-Aldrich, 144169) and guaiacol (1 g/L) (Sigma-Aldrich, W253200) in ethanol (Fisher Chemical, E/0650DF/C17). Each sample was incubated at 60 °C in the autosampler oven with constant agitation. After 5 min equilibration, the SPME fiber was exposed to the sample headspace for 30 min. The compounds trapped on the fiber were thermally desorbed in the injection port of the chromatograph by heating the fiber for 15 min at 270 °C.

The GC-MS was equipped with a low polarity RXi-5Sil MS column (length, 20 m; internal diameter, 0.18 mm; layer thickness, 0.18 µm; Restek, Bellefonte, PA, USA). Injection was performed in splitless mode at 320 °C, a split flow of 9 ml/min, a purge flow of 5 ml/min and an open valve time of 3 min. To obtain a pulsed injection, a programmed gas flow was used whereby the helium gas flow was set at 2.7 mL/min for 0.1 min, followed by a decrease in flow of 20 ml/min to the normal 0.9 mL/min. The temperature was first held at 30 °C for 3 min and then allowed to rise to 80 °C at a rate of 7 °C/min, followed by a second ramp of 2 °C/min till 125 °C and a final ramp of 8 °C/min with a final temperature of 270 °C.

Mass acquisition range was 33 to 550 amu at a scan rate of 5 scans/s. Electron impact ionization energy was 70 eV. The interface and ion source were kept at 275 °C and 250 °C, respectively. A mix of linear n-alkanes (from C7 to C40, Supelco Co.) was injected into the GC-MS under identical conditions to serve as external retention index markers. Identification and quantification of the compounds were performed using an in-house developed R script as described in Goelen et al. and Reher et al. 87 , 88 (for package information, see Supplementary Table S8 ). Briefly, chromatograms were analyzed using AMDIS (v2.71) 89 to separate overlapping peaks and obtain pure compound spectra. The NIST MS Search software (v2.0 g) in combination with the NIST2017, FFNSC3 and Adams4 libraries were used to manually identify the empirical spectra, taking into account the expected retention time. After background subtraction and correcting for retention time shifts between samples run on different days based on alkane ladders, compound elution profiles were extracted and integrated using a file with 284 target compounds of interest, which were either recovered in our identified AMDIS list of spectra or were known to occur in beer. Compound elution profiles were estimated for every peak in every chromatogram over a time-restricted window using weighted non-negative least square analysis after which peak areas were integrated 87 , 88 . Batch effect correction was performed by normalizing against the most stable internal standard compound, 4-fluorobenzaldehyde. Out of all 284 target compounds that were analyzed, 167 were visually judged to have reliable elution profiles and were used for final analysis.

Discrete photometric and enzymatic analysis

Discrete photometric and enzymatic analysis (Thermo Scientific TM Gallery TM Plus Beermaster Discrete Analyzer) was used to measure acetic acid, ammonia, beta-glucan, iso-alpha acids, color, sugars, glycerol, iron, pH, protein, and sulfite. 2 ml of sample volume was used for the analyses. Information regarding the reagents and standard solutions used for analyses and calibrations is included in Supplementary Table S7 and Supplementary Table S9 .

NIR analyses

NIR analysis (Anton Paar Alcolyzer Beer ME System) was used to measure ethanol. Measurements comprised 50 ml of sample, and a 10% EtOH solution was used for calibration.

Correlation calculations

Pairwise Spearman Rank correlations were calculated between all chemical properties.

Sensory dataset

Trained panel.

Our trained tasting panel consisted of volunteers who gave prior verbal informed consent. All compounds used for the validation experiment were of food-grade quality. The tasting sessions were approved by the Social and Societal Ethics Committee of the KU Leuven (G-2022-5677-R2(MAR)). All online reviewers agreed to the Terms and Conditions of the RateBeer website.

Sensory analysis was performed according to the American Society of Brewing Chemists (ASBC) Sensory Analysis Methods 90 . 30 volunteers were screened through a series of triangle tests. The sixteen most sensitive and consistent tasters were retained as taste panel members. The resulting panel was diverse in age [22–42, mean: 29], sex [56% male] and nationality [7 different countries]. The panel developed a consensus vocabulary to describe beer aroma, taste and mouthfeel. Panelists were trained to identify and score 50 different attributes, using a 7-point scale to rate attributes’ intensity. The scoring sheet is included as Supplementary Data 3 . Sensory assessments took place between 10–12 a.m. The beers were served in black-colored glasses. Per session, between 5 and 12 beers of the same style were tasted at 12 °C to 16 °C. Two reference beers were added to each set and indicated as ‘Reference 1 & 2’, allowing panel members to calibrate their ratings. Not all panelists were present at every tasting. Scores were scaled by standard deviation and mean-centered per taster. Values are represented as z-scores and clustered by Euclidean distance. Pairwise Spearman correlations were calculated between taste and aroma sensory attributes. Panel consistency was evaluated by repeating samples on different sessions and performing ANOVA to identify differences, using the ‘stats’ package (v4.2.2) in R (for package information, see Supplementary Table S8 ).

Online reviews from a public database

The ‘scrapy’ package in Python (v3.6) (for package information, see Supplementary Table S8 ). was used to collect 232,288 online reviews (mean=922, min=6, max=5343) from RateBeer, an online beer review database. Each review entry comprised 5 numerical scores (appearance, aroma, taste, palate and overall quality) and an optional review text. The total number of reviews per reviewer was collected separately. Numerical scores were scaled and centered per rater, and mean scores were calculated per beer.

For the review texts, the language was estimated using the packages ‘langdetect’ and ‘langid’ in Python. Reviews that were classified as English by both packages were kept. Reviewers with fewer than 100 entries overall were discarded. 181,025 reviews from >6000 reviewers from >40 countries remained. Text processing was done using the ‘nltk’ package in Python. Texts were corrected for slang and misspellings; proper nouns and rare words that are relevant to the beer context were specified and kept as-is (‘Chimay’,’Lambic’, etc.). A dictionary of semantically similar sensorial terms, for example ‘floral’ and ‘flower’, was created and collapsed together into one term. Words were stemmed and lemmatized to avoid identifying words such as ‘acid’ and ‘acidity’ as separate terms. Numbers and punctuation were removed.

Sentences from up to 50 randomly chosen reviews per beer were manually categorized according to the aspect of beer they describe (appearance, aroma, taste, palate, overall quality—not to be confused with the 5 numerical scores described above) or flagged as irrelevant if they contained no useful information. If a beer contained fewer than 50 reviews, all reviews were manually classified. This labeled data set was used to train a model that classified the rest of the sentences for all beers 91 . Sentences describing taste and aroma were extracted, and term frequency–inverse document frequency (TFIDF) was implemented to calculate enrichment scores for sensorial words per beer.

The sex of the tasting subject was not considered when building our sensory database. Instead, results from different panelists were averaged, both for our trained panel (56% male, 44% female) and the RateBeer reviews (70% male, 30% female for RateBeer as a whole).

Beer price collection and processing

Beer prices were collected from the following stores: Colruyt, Delhaize, Total Wine, BeerHawk, The Belgian Beer Shop, The Belgian Shop, and Beer of Belgium. Where applicable, prices were converted to Euros and normalized per liter. Spearman correlations were calculated between these prices and mean overall appreciation scores from RateBeer and the taste panel, respectively.

Pairwise Spearman Rank correlations were calculated between all sensory properties.

Machine learning models

Predictive modeling of sensory profiles from chemical data.

Regression models were constructed to predict (a) trained panel scores for beer flavors and quality from beer chemical profiles and (b) public reviews’ appreciation scores from beer chemical profiles. Z-scores were used to represent sensory attributes in both data sets. Chemical properties with log-normal distributions (Shapiro-Wilk test, p < 0.05 ) were log-transformed. Missing chemical measurements (0.1% of all data) were replaced with mean values per attribute. Observations from 250 beers were randomly separated into a training set (70%, 175 beers) and a test set (30%, 75 beers), stratified per beer style. Chemical measurements (p = 231) were normalized based on the training set average and standard deviation. In total, three linear regression-based models: linear regression with first-order interaction terms (LR), lasso regression with first-order interaction terms (Lasso) and partial least squares regression (PLSR); five decision tree models, Adaboost regressor (ABR), Extra Trees (ET), Gradient Boosting regressor (GBR), Random Forest (RF) and XGBoost regressor (XGBR); one support vector machine model (SVR) and one artificial neural network model (ANN) were trained. The models were implemented using the ‘scikit-learn’ package (v1.2.2) and ‘xgboost’ package (v1.7.3) in Python (v3.9.16). Models were trained, and hyperparameters optimized, using five-fold cross-validated grid search with the coefficient of determination (R 2 ) as the evaluation metric. The ANN (scikit-learn’s MLPRegressor) was optimized using Bayesian Tree-Structured Parzen Estimator optimization with the ‘Optuna’ Python package (v3.2.0). Individual models were trained per attribute, and a multi-output model was trained on all attributes simultaneously.

Model dissection

GBR was found to outperform other methods, resulting in models with the highest average R 2 values in both trained panel and public review data sets. Impurity-based rankings of the most important predictors for each predicted sensorial trait were obtained using the ‘scikit-learn’ package. To observe the relationships between these chemical properties and their predicted targets, partial dependence plots (PDP) were constructed for the six most important predictors of consumer appreciation 74 , 75 .

The ‘SHAP’ package in Python (v0.41.0) was implemented to provide an alternative ranking of predictor importance and to visualize the predictors’ effects as a function of their concentration 68 .

Validation of causal chemical properties

To validate the effects of the most important model features on predicted sensory attributes, beers were spiked with the chemical compounds identified by the models and descriptive sensory analyses were carried out according to the American Society of Brewing Chemists (ASBC) protocol 90 .

Compound spiking was done 30 min before tasting. Compounds were spiked into fresh beer bottles, that were immediately resealed and inverted three times. Fresh bottles of beer were opened for the same duration, resealed, and inverted thrice, to serve as controls. Pairs of spiked samples and controls were served simultaneously, chilled and in dark glasses as outlined in the Trained panel section above. Tasters were instructed to select the glass with the higher flavor intensity for each attribute (directional difference test 92 ) and to select the glass they prefer.

The final concentration after spiking was equal to the within-style average, after normalizing by ethanol concentration. This was done to ensure balanced flavor profiles in the final spiked beer. The same methods were applied to improve a non-alcoholic beer. Compounds were the following: ethyl acetate (Merck KGaA, W241415), ethyl hexanoate (Merck KGaA, W243906), isoamyl acetate (Merck KGaA, W205508), phenethyl acetate (Merck KGaA, W285706), ethanol (96%, Colruyt), glycerol (Merck KGaA, W252506), lactic acid (Merck KGaA, 261106).

Significant differences in preference or perceived intensity were determined by performing the two-sided binomial test on each attribute.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The data that support the findings of this work are available in the Supplementary Data files and have been deposited to Zenodo under accession code 10653704 93 . The RateBeer scores data are under restricted access, they are not publicly available as they are property of RateBeer (ZX Ventures, USA). Access can be obtained from the authors upon reasonable request and with permission of RateBeer (ZX Ventures, USA). Source data are provided with this paper.

Code availability

The code for training the machine learning models, analyzing the models, and generating the figures has been deposited to Zenodo under accession code 10653704 93 .

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Acknowledgements

We thank all lab members for their discussions and thank all tasting panel members for their contributions. Special thanks go out to Dr. Karin Voordeckers for her tremendous help in proofreading and improving the manuscript. M.S. was supported by a Baillet-Latour fellowship, L.C. acknowledges financial support from KU Leuven (C16/17/006), F.A.T. was supported by a PhD fellowship from FWO (1S08821N). Research in the lab of K.J.V. is supported by KU Leuven, FWO, VIB, VLAIO and the Brewing Science Serves Health Fund. Research in the lab of T.W. is supported by FWO (G.0A51.15) and KU Leuven (C16/17/006).

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These authors contributed equally: Michiel Schreurs, Supinya Piampongsant, Miguel Roncoroni.

Authors and Affiliations

VIB—KU Leuven Center for Microbiology, Gaston Geenslaan 1, B-3001, Leuven, Belgium

Michiel Schreurs, Supinya Piampongsant, Miguel Roncoroni, Lloyd Cool, Beatriz Herrera-Malaver, Florian A. Theßeling & Kevin J. Verstrepen

CMPG Laboratory of Genetics and Genomics, KU Leuven, Gaston Geenslaan 1, B-3001, Leuven, Belgium

Leuven Institute for Beer Research (LIBR), Gaston Geenslaan 1, B-3001, Leuven, Belgium

Laboratory of Socioecology and Social Evolution, KU Leuven, Naamsestraat 59, B-3000, Leuven, Belgium

Lloyd Cool, Christophe Vanderaa & Tom Wenseleers

VIB Bioinformatics Core, VIB, Rijvisschestraat 120, B-9052, Ghent, Belgium

Łukasz Kreft & Alexander Botzki

AB InBev SA/NV, Brouwerijplein 1, B-3000, Leuven, Belgium

Philippe Malcorps & Luk Daenen

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Contributions

S.P., M.S. and K.J.V. conceived the experiments. S.P., M.S. and K.J.V. designed the experiments. S.P., M.S., M.R., B.H. and F.A.T. performed the experiments. S.P., M.S., L.C., C.V., L.K., A.B., P.M., L.D., T.W. and K.J.V. contributed analysis ideas. S.P., M.S., L.C., C.V., T.W. and K.J.V. analyzed the data. All authors contributed to writing the manuscript.

Corresponding author

Correspondence to Kevin J. Verstrepen .

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K.J.V. is affiliated with bar.on. The other authors declare no competing interests.

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Introduction

Select a Target Journal Early in the Writing Process

Identify Author Roles Early in the Process

Structure of the Introduction Section

Methods Section

Results Section

Discussion Section

Follow the Journal’s Author Guidelines

Acknowledgments

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Data Availability

How to Write and Publish a Research Paper in 7 Steps

1. Check Whether Your Research Is Publication-Ready

2. Choose An Article Type

3. Choose a Journal

4. Construct Your Paper

4.1 The Title

4.2 The Abstract

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4.9 Acknowledgments and Ethical Statements

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