Evidence map›Paper›PMID 39272453›Full record

ReviewFoods (Basel, Switzerland)2024

Recent Advances in Light Penetration Depth for Postharvest Quality Evaluation of Fruits and Vegetables.

Yuping Huang, Jie Xiong, Ziang Li, Dong Hu, Ye Sun, Haojun Jin, Huichun Zhang, Huimin Fang

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

8 authors.

Yuping HuangCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.
Jie XiongCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.
Ziang LiCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.
Dong HuCollege of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China.ORCID 0000-0003-2417-119X
Ye SunCollege of Food Science and Light Industry, Nanjing Tech University, Nanjing 211816, China.
Haojun JinSchool of Flexible Electronics (Future Technologies) and Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing 211816, China.
Huichun ZhangCollege of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.
Huimin FangSchool of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0001-9533-1504

Funding

A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions NO. PAPD-2023-87he Postgraduate Research & Practice Innovation Program of Jiangsu Province Grant No. KYCX23_1134the National Natural Science Foundation of China No. 32101615 and 32171790
6 · The paper itself

Abstract

Light penetration depth, as a characteristic parameter reflecting light attenuation and transmission in biological tissues, has been applied in nondestructive detection of fruits and vegetables. Recently, with emergence of new optical detection technologies, researchers have begun to explore methods evaluating optical properties of double-layer or even multilayer fruit and vegetable tissues due to the differences between peel and pulp in the chemical composition and physical properties, which has gradually promoted studies on light penetration depth. A series of demonstrated research on light penetration depth could ensure the accuracy of the optical information obtained from each layer of tissue, which is beneficial to enhance detection accuracy for quality assessment of fruits and vegetables. Therefore, the aim of this review is to give detailed outlines about the theory and principle of light penetration depth based on several emerging optical detection technologies and to focus primarily on its applications in the field of quality evaluation of fruits and vegetables, its future applicability in fruits and vegetables and the challenges it may face in the future.

Indexed as

applicationslight penetration depthoptical detection techniquesoptical propertiesquality evaluation

Identifiers

PMID39272453
PMCPMC11394095

What OpenQuestion holds

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LicenceCC BY
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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.