Evidence map›Paper›PMID 42720082›Full record

ReviewJournal of food science2026

Image-Based Pore Space and Pore Network Characterization: A Review of 2D/3D Workflow in Foods.

Bobby Shekarau Luka, Abdul'alim Gambo Ibrahim, Ibrahim Binni Muhammed, Bello Mohammed Yunusa, Mohammed Haris Siddiqui, Khwaja Osama

Abstract readReview
In one paragraph

Review in Journal of food science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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.

Bobby Shekarau LukaDepartment of Agricultural Engineering, Federal University, Wukari, Taraba State, Nigeria.ORCID https://orcid.org/0000-0002-4410-5934
Abdul'alim Gambo IbrahimDepartment of Chemical Engineering, Federal University, Wukari, Taraba State, Nigeria.
Ibrahim Binni MuhammedDepartment of Agricultural Engineering, Federal University, Wukari, Taraba State, Nigeria.ORCID https://orcid.org/0000-0002-1241-2067
Bello Mohammed YunusaDepartment of Food Science and Technology, Federal University, Wukari, Taraba State, Nigeria.
Mohammed Haris SiddiquiDepartment of Bioengineering, Integral University, Lucknow, India.
Khwaja OsamaDepartment of Bioengineering, Integral University, Lucknow, India.

Funding

Integral University Lucknow, IndiaTertiary Education Trust Fund, Nigeria
6 · The paper itself

Abstract

Food microstructure plays an important role in governing mass transfer and textural properties during processing; hence, its characterization is essential for process optimization and product quality improvement. In this review, the application of image processing techniques for the characterization of pore spaces and pore networks in foods was examined. The workflow comprises image acquisition, preprocessing, segmentation, reconstruction, 2D/3D visualization, and quantitative analysis. Potentials and limitations of scanning electron microscopy (SEM) and X-ray micro-computed tomography (X-ray micro-CT) were elucidated. Published studies were analyzed to evaluate how image resolution, image quality, and segmentation methods influenced the results of pore space and pore network characterization. The reviewed literature showed that segmentation algorithms and imaging resolution are the two most critical factors influencing the accuracy of pore space and pore network characterization. SEM provides high-resolution surface information; X-ray micro-CT offers non-destructive 3D visualization of internal pore structures. This demonstrates an important trade-off between the two techniques. The relationship between image-based pore structure, food texture, and mass transfer processes in foods was elucidated. The state-of-the-art, challenges, emerging trends, and future research directions were identified and discussed. These include the lack of validation or benchmark datasets and the need for benchmark datasets and the need for a focus on AI-assisted/explainable/interpretable AI-based segmentation algorithms and multiscale imaging approaches. These developments will offer new opportunities for improving the accuracy and deployment of image-based pore characterization, thereby supporting the design of optimized food processing operations, improving texture prediction and mass transfer, and advancing quality control in food engineering.

Indexed as

Food AnalysisImage Processing, Computer-AssistedImaging, Three-DimensionalAlgorithmsFood HandlingMicroscopy, Electron, ScanningPorosityWorkflowX-Ray Microtomographyfoodsimage processingpore networkpore space

Identifiers

PMID42720082
PMCPMC13559874

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.