Evidence map›Paper›PMID 37835194›Full record

ArticleFoods (Basel, Switzerland)2023

A Reliable Method for Determining the Degree of Orientation of Fibrous Foods Using Laser Transmission and Computer Vision.

Jingpeng Li, Xu Xia, Cuizhu Shi, Xiaoqing Chen, Hao Tang, Li Deng

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Jingpeng LiKey Laboratory of Agricultural and Animal Products Storage and Processing of Guizhou Province, School of Liquor and Food Engineering, Guizhou University, Guiyang 550025, China.
Xu XiaKey Laboratory of Agricultural and Animal Products Storage and Processing of Guizhou Province, School of Liquor and Food Engineering, Guizhou University, Guiyang 550025, China.
Cuizhu ShiKey Laboratory of Agricultural and Animal Products Storage and Processing of Guizhou Province, School of Liquor and Food Engineering, Guizhou University, Guiyang 550025, China.
Xiaoqing ChenKey Laboratory of Agricultural and Animal Products Storage and Processing of Guizhou Province, School of Liquor and Food Engineering, Guizhou University, Guiyang 550025, China.
Hao TangKey Laboratory of Agricultural and Animal Products Storage and Processing of Guizhou Province, School of Liquor and Food Engineering, Guizhou University, Guiyang 550025, China.
Li DengKey Laboratory of Agricultural and Animal Products Storage and Processing of Guizhou Province, School of Liquor and Food Engineering, Guizhou University, Guiyang 550025, China.

Funding

Guizhou Provincial Basic Research Program QKHJC-ZK[2022]066Guizhou Provincial Key Technology R&D Program QKHZC[2021]177Guizhou Provincial Key Technology R&D Program QKHZC[2022]022Guizhou Provincial Key Technology R&D Program QKHZC[2023]066Guizhou University Talent Research Project GDRJHZ(2020)4HNational Natural Science Foundation of China 32260642National Natural Science Foundation of China 32260644
6 · The paper itself

Abstract

The degree of organised alignment of fibre structures, referred to as the degree of orientation, significantly influences the textural properties and consumer acceptance of fibrous foods. To develop a new method to quantitatively characterise the fibre structure of such foods, a laser transmission imaging system is constructed to capture the laser beam spot on a sample, and the resulting image undergoes a series of image processing steps that use computer vision to translate the light and dark variations of the original images into distinct ellipses. The results show that the degree of orientation can be reasonably calculated from the ellipse obtained by fitting the outermost isopixel points. To validate the reliability of the newly developed method, we determine the degree of orientation of typical fibrous foods (extruded beef jerky, pork jerky, chicken jerky, and duck jerky). The ranking of the measured orientation agrees with the results of pseudocolour maps and micrographs, confirming the ability of the method to distinguish different fibrous foods. Furthermore, the relatively small coefficients of variation and the strong positive correlation between the degree of organisation and the degree of orientation confirm the reliability of this newly developed method.

Indexed as

computer visiondegree of orientationextruded jerkyfibrous foodsimage processinglaser transmissionmethod developmentmethod verification

Identifiers

PMID37835194
PMCPMC10572238

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Registered trials

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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.