Evidence map›Paper›PMID 39682989›Full record

ReviewFoods (Basel, Switzerland)2024

Research Progress on Methods for Improving the Stability of Non-Destructive Testing of Agricultural Product Quality.

Sai Xu, Hanting Wang, Xin Liang, Huazhong Lu

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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
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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

4 authors.

Sai XuInstitute of Facility Agriculture, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China.
Hanting WangSchool of Life Sciences, South China Normal University, Guangzhou 510631, China.
Xin LiangInstitute of Facility Agriculture, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China.
Huazhong LuGuangdong Academy of Agricultural Sciences, Guangzhou 510640, China.

Funding

the Innovation Fund Industry Special Project of Guangdong Academy of Agricultural Science grant no.202306the International Science and Technology Cooperation Project of Guangdong Province no.2023A0505050129the National Key Research and Development Program of China no. 2022YFD2002203the Special Fund for Rural Revitalization of Guangdong Province no. 2024TS-1-2the Special Training Project for Science and Technology Innovation Strategy of Guangdong Academy of Agricultural Sciences (Construction of Main Agricultural Research Force) R2023PY-QN002
6 · The paper itself

Abstract

Non-destructive testing (NDT) technology is pivotal in the quality assessment of agricultural products. In contrast to traditional manual testing, which is fraught with subjectivity, inefficiency, and the potential for sample damage, NDT technology has gained widespread application due to its advantages of objectivity, speed, and accuracy, and it has injected significant momentum into the intelligent development of the food industry and agriculture. Over the years, technological advancements have led to the development of NDT systems predicated on machine vision, spectral analysis, and bionic sensors. However, during practical application, these systems can be compromised by external environmental factors, the test samples themselves, or by the degradation and noise interference inherent in the testing equipment, leading to instability in the detection process. This instability severely impacts the accuracy and efficiency of the testing. Consequently, refining the detection methods and enhancing system stability have emerged as key focal points for research endeavors. This manuscript presents an overview of various prevalent non-destructive testing methodologies, summarizes how sample properties, external environments, and instrumentation factors affect the stability of testing in practical applications, organizes and analyzes solutions to enhance the stability of non-destructive testing of agricultural product quality based on current research, and offers recommendations for future investigations into the non-destructive testing technology of agricultural products.

Indexed as

agriculture productalgorithm improvementhardware system improvementnon-destructive testingsystem stability

Identifiers

PMID39682989
PMCPMC11640820

What OpenQuestion holds

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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.