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Foods
Special Issues
New Technology for Food Quality and Safety Analysis
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New Technology for Food Quality and Safety Analysis

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Analytical Methods".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 7018

Special Issue Editor

Dr. Xinai Zhang

E-Mail Website
Guest Editor
School of Food and Biological Engineering, Jiangsu University, Zhenjiang, China
Interests: electrochemcial sensor; fluorescence sensing; colorimetric sensing; nanozyme; nanotechnology; food pollutant monitoring; nutrient analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Food analytical techniques are imperative to understand food components and also protect public health against potential pollution exposure. However, the development of facile and sensitive means for food quality and safety analysis is still challenging in diverse food matrices. Benefiting from the development of the Internet and electronic information technology, portable sensing strategies, independent of special instruments and laboratories bound, have become attractive candidates for on-site detection in a portable and user-friendly mode. Therefore, optical/electric-based new analytical technologies integrating with nanozymes, carbon-based nanomaterials, biomimetic catalysis and guest-host recognition have attracted more attention in food quality and safety analysis. In this Special Issue, the user-friendly methods will have the superiority of temporariness, easy operation, minimize analytical residues, environmental protection, portability and reliability. Moreover, we encourage the submission of manuscripts focused on point-of-use tracking of food processing, complex components, and hazardous substances with the merits of broad potential applications, eventually bringing benefits to public protection in resource-deficient settings.

Dr. Xinai Zhang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • food pollutant monitoring
  • nutrient analysis
  • portable sensing
  • biomimetic catalysis
  • nanozymes
  • guest-host recognition
  • point-of-use tracking

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

22 pages, 9838 KiB  
Article
Design of an Artificial Intelligence of Things-Based Sesame Oil Evaluator for Quality Assessment Using Gas Sensors and Deep Learning Mechanisms
by Hao-Hsiang Ku, Ching-Fu Lung and Ching-Ho Chi
Foods 2023, 12(21), 4024; https://doi.org/10.3390/foods12214024 - 3 Nov 2023
Cited by 1 | Viewed by 1966
Abstract
Traditional oil quality measurement is mostly based on chemical indicators such as acid value, peroxide value, and p-anisidine value. This process requires specialized knowledge and involves complex steps. Hence, this study designs and proposes a Sesame Oil Quality Assessment Service Platform, which [...] Read more.
Traditional oil quality measurement is mostly based on chemical indicators such as acid value, peroxide value, and p-anisidine value. This process requires specialized knowledge and involves complex steps. Hence, this study designs and proposes a Sesame Oil Quality Assessment Service Platform, which is composed of an Intelligent Sesame Oil Evaluator (ISO Evaluator) and a Cloud Service Platform. Users can quickly assess the quality of sesame oil using this platform. The ISO Evaluator employs Artificial Intelligence of Things (AIoT) sensors to detect changes in volatile gases and the color of the oil during storage. It utilizes deep learning mechanisms, including Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) to determine and evaluate the quality of the sesame oil. Evaluation results demonstrate that the linear discriminant analysis (LDA) value is 95.13. The MQ2, MQ3, MQ4, MQ7, and MQ8 sensors have a positive correlation. The CNN combined with an ANN model achieves a Mean Absolute Percentage Error (MAPE) of 8.1820% for predicting oil quality, while the LSTM model predicts future variations in oil quality indicators with a MAPE of 0.44%. Finally, the designed Sesame Oil Quality Assessment Service Platform effectively addresses issues related to digitization, quality measurement, supply quality observation, and scalability. Full article
(This article belongs to the Special Issue New Technology for Food Quality and Safety Analysis)
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14 pages, 5527 KiB  
Article
A Novel Strategy for Accelerating Pumpable Ice Slurry Production with Ozone Micro–Nano Bubbles and Extending the Shelf Life of Larimichthys polyactis
by Roujia Zhang, Zhiming Cheng, Yuting Liang, Xuetao Hu, Tingting Shen, Yanxiao Li, Zhi Han, Xinai Zhang and Xiaobo Zou
Foods 2023, 12(11), 2206; https://doi.org/10.3390/foods12112206 - 31 May 2023
Cited by 8 | Viewed by 2305
Abstract
In this study, a novel strategy for accelerating the production of pumpable ice slurry (PIS) by using ozone micro–nano bubbles (O3-MNBs) was proposed. The effect of PIS containing sodium alginate (SA) and O3-MNBs on the preservation of small yellow [...] Read more.
In this study, a novel strategy for accelerating the production of pumpable ice slurry (PIS) by using ozone micro–nano bubbles (O3-MNBs) was proposed. The effect of PIS containing sodium alginate (SA) and O3-MNBs on the preservation of small yellow croaker (Larimichthys polyactis) was investigated. The results indicate that using SA solution containing O3-MNBs instead of only SA solution resulted in quicker production of PIS by promoting ice nucleation and eliminating supercooling. The distribution and positive effect of O3-MNBs as a nucleation agent on freezing characteristics were discussed. Microbial concentrations, pH, total volatile basic nitrogen, and thiobarbituric acid reactive substance content were also examined. Storage in novel PIS (containing O3-MNBs) had higher performance than storage in flake ice or conventional PIS due to the strong bacteriostatic ability of O3. Therefore, O3-MNBs injection can be used as a novel method for PIS production and the preservation of fresh marine products. Full article
(This article belongs to the Special Issue New Technology for Food Quality and Safety Analysis)
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15 pages, 4331 KiB  
Article
Rapid and Sensitive Fluorescence Detection of Staphylococcus aureus Based on Polyethyleneimine-Enhanced Boronate Affinity Isolation
by Yujia Xu, Hongwei Zheng, Jianxin Sui, Hong Lin and Limin Cao
Foods 2023, 12(7), 1366; https://doi.org/10.3390/foods12071366 - 23 Mar 2023
Cited by 4 | Viewed by 1980
Abstract
There are increasing demands for fast and simple detection of pathogens in foodstuffs. Fluorescence analysis has demonstrated significant advantages for easy operation and high sensitivity, although it is usually hindered by a complex matrix, low bacterial abundance, and long-term bacterial enrichment. Effective enrichment [...] Read more.
There are increasing demands for fast and simple detection of pathogens in foodstuffs. Fluorescence analysis has demonstrated significant advantages for easy operation and high sensitivity, although it is usually hindered by a complex matrix, low bacterial abundance, and long-term bacterial enrichment. Effective enrichment procedures are required to meet the requirements for food detection. Here, boronate-functionalized cellulose filter paper and specific fluorescent probes were combined. An integrated approach for the enrichment of detection of Staphylococcus aureus was proposed. The modification of polyethyleneimine demonstrated a significant effect in enhancing the bacterial enrichment, and the boronate affinity efficiency of the paper was increased by about 51~132%. With optimized conditions, the adsorption efficiency for S. aureus was evaluated as 1.87 × 108 CFU/cm2, the linear range of the fluorescent analysis was 104 CFU/mL~108 CFU/mL (R2 = 0.9835), and the lowest limit of detection (LOD) was calculated as 2.24 × 102 CFU/mL. Such efficiency was validated with milk and yogurt samples. These results indicated that the material had a high enrichment capacity, simple operation, and high substrate tolerance, which had the promising potential to be the established method for the fast detection of food pathogens. Full article
(This article belongs to the Special Issue New Technology for Food Quality and Safety Analysis)
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