ReviewFoods (Basel, Switzerland)2024
Research Progress on Methods for Improving the Stability of Non-Destructive Testing of Agricultural Product Quality.
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.
What it found
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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.
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.
Who cites it
11 citing papers in PubMed.
- Identification and Detection of AflatoxigenicToxins · 2026Review
- Research on the spectral detection effect and data fusion of small white apricot quality based on different detection distances.Scientific reports · 2026Article
- Mycotoxin detection in food and feed: bridging conventional analytical methods with emerging sensor-based technologies.Mycotoxin research · 2026Review
- Nondestructive Detection of Eggshell Thickness Using Near-Infrared Spectroscopy Based on GBDT Feature Selection and an Improved CatBoost Algorithm.Foods (Basel, Switzerland) · 2026Article
- Novel estimation of tomato soluble solids content using linearly transformed reflectance-based spectral indices.Frontiers in plant science · 2026Article
- HyperVision-HSI: a classification-guided spectral-spatial decoupling framework for adaptive multi-category fruit SSC detection.Frontiers in plant science · 2026Article
- Hybrid AI Pipeline for Laboratory Detection of Internal Potato Defects Using 2D RGB Imaging.Journal of imaging · 2025Article
- Research Progress on Non-Destructive Testing Technology and Equipment for Poultry Eggshell Quality.Foods (Basel, Switzerland) · 2025Review
- Research Progress and Technological Application Prospects of Comprehensive Evaluation Methods for Egg Freshness.Foods (Basel, Switzerland) · 2025Review
- LiSA-MobileNetV2: an extremely lightweight deep learning model with Swish activation and attention mechanism for accurate rice disease classification.Frontiers in plant science · 2025Article
- A review of ultrasound monitoring applications in agriculture.Frontiers in plant science · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
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.
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What OpenQuestion holds
Registered trials
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.