Evidence map›Paper›PMID 42991117›Full record

ArticleFood science & nutrition2026

Quantitative and Qualitative Control of Wheat Flour Dough's Mechanical Properties via Dietary Protein Addition.

Jingxian An, Owen Jones, Senay Simsek, Kristin Whitney, Bruce Hamaker, Yuan Yao

Abstract read
In one paragraph

Article in Food science & nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jingxian AnWhistler Center for Carbohydrate Research, Department of Food Science Purdue University West Lafayette Indiana USA.ORCID https://orcid.org/0000-0003-3578-2279
Owen JonesWhistler Center for Carbohydrate Research, Department of Food Science Purdue University West Lafayette Indiana USA.
Senay SimsekWhistler Center for Carbohydrate Research, Department of Food Science Purdue University West Lafayette Indiana USA.ORCID https://orcid.org/0000-0003-0238-5947
Kristin WhitneyWhistler Center for Carbohydrate Research, Department of Food Science Purdue University West Lafayette Indiana USA.ORCID https://orcid.org/0000-0003-4498-6273
Bruce HamakerWhistler Center for Carbohydrate Research, Department of Food Science Purdue University West Lafayette Indiana USA.ORCID https://orcid.org/0000-0001-6591-942X
Yuan YaoWhistler Center for Carbohydrate Research, Department of Food Science Purdue University West Lafayette Indiana USA.ORCID https://orcid.org/0000-0001-8370-5548

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dietary protein fortification enhances bakery nutrition, but its impact on dough mechanics remains unclear. To address this, 432 formulations were designed using eight proteins (up to 70.6% substitution), seven lipid configurations, and salt, with water adjusted (38%-159% baker's percentage). Texture profile analysis (10 mm compression distance) and dynamic rheometry (0.1-80 Hz at 0.5% strain) yielded 19 continuous and tertile-discretized mechanical target variables. Parallel regression and classification workflows were developed to predict continuous values and tertile-defined categories (low, medium, and high). Models included Ridge regression for continuous prediction, logistic regression for classification, and Random Forest and Gradient Boosting for both tasks, with performance evaluated using five-fold cross-validation. Both paradigms generally predicted rheological properties with higher accuracy (

Indexed as

dietary proteinmechanical propertiespermutation importancePlant‐Based Proteinregression and classification modelswheat flour dough

Identifiers

PMID42991117
PMCPMC13736157

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.