ArticleSensors (Basel, Switzerland)2020
Evaluation of Salmon, Tuna, and Beef Freshness Using a Portable Spectrometer.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Meat Freshness Monitoring in the Modern Supply Chain: Analytical Advances, Smart Packaging, and Digital Integration.Food science & nutrition · 2026Review
- The Authentication of Gayo Arabica Green Coffee Beans with Different Cherry Processing Methods Using Portable LED-Based Fluorescence Spectroscopy and Chemometrics Analysis.Foods (Basel, Switzerland) · 2023Article
- Determination of Freshness of Mackerel (Foods (Basel, Switzerland) · 2023Article
- Microbiological Quality Estimation of Meat Using Deep CNNs on Embedded Hardware Systems.Sensors (Basel, Switzerland) · 2023Article
- Portable NIR spectroscopy: the route to green analytical chemistry.Frontiers in chemistry · 2023Review
- Use of industry 4.0 technologies to reduce and valorize seafood waste and by-products: A narrative review on current knowledge.Current research in food science · 2023Review
- A Review of Machine Learning for Near-Infrared Spectroscopy.Sensors (Basel, Switzerland) · 2022Review
- The Feasibility of Two Handheld Spectrometers for Meat Speciation Combined with Chemometric Methods and Its Application for Halal Certification.Foods (Basel, Switzerland) · 2021Article
- Determining Sonication Effect onSensors (Basel, Switzerland) · 2021Article
- Monitoring the Processing of Dry Fermented Sausages with a Portable NIRS Device.Foods (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
There has been strong demand for the development of an accurate but simple method to assess the freshness of food. In this study, we demonstrated a system to determine food freshness by analyzing the spectral response from a portable visible/near-infrared (VIS/NIR) spectrometer using the Convolutional Neural Network (CNN)-based machine learning algorithm. Spectral response data from salmon, tuna, and beef incubated at 25 °C were obtained every minute for 30 h and then categorized into three states of "fresh", "likely spoiled", and "spoiled" based on time and pH. Using the obtained spectral data, a CNN-based machine learning algorithm was built to evaluate the freshness of experimental objects. In addition, a CNN-based machine learning algorithm with a shift-invariant feature can minimize the effect of the variation caused using multiple devices in a real environment. The accuracy of the obtained machine learning model based on the spectral data in predicting the freshness was approximately 85% for salmon, 88% for tuna, and 92% for beef. Therefore, our study demonstrates the practicality of a portable spectrometer in food freshness assessment.
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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.