Research in the Food Safety and Quality Management Techniques

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Food Science and Technology".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 1054

Special Issue Editors

1. College of Food Science and Technology, Jilin University, Changchun 130012, China
2. State Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130012, China
Interests: food safety; food quality; surface-enhanced Raman scattering (SERS); mass spectroscopy (MS); food pollutants; antioxidant
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
College of Plant Protection, Jilin Agricultural University, Changchun 130118, China
Interests: insect chemical ecology; pest control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Consumer demand for food quality and safety has increased as the world's population and the popularity of healthy eating have grown. This demand has led to researchers developing advanced analytical methods and management techniques that enable the assessment of food safety and quality. It is important to use highly sensitive analytical methods at the levels required by current legislation and good quality management to control the risk of contaminants affecting food quality. It is also noteworthy that food contaminants can adversely affect non-target organisms and human health. In recent years, varied new technologies and approaches (physical, chemical, and biological) have been applied in the fields of food growing, management, harvesting, storing, transportation, processing, and sales. This Special Issue will focus on such advanced food safety and quality management techniques, including, but not being limited to, these topics: infrared spectroscopy, Raman spectroscopy, electronic nose and electronic tongue, good agricultural practices, good manufacturing practices, hazard analysis, critical control points, pre- and post-harvest studies of pests and diseases, and quality and safety control. Papers that discuss novel approaches to sensor data analysis based on strategies such as big data and deep learning are also welcome.

Dr. Menglei Xu
Dr. Yu Gao
Guest Editors

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. Applied Sciences 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 2400 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 quality management
  • chromatography
  • spectroscopy
  • food policy
  • pesticide
  • food contaminants
  • pest and disease control
  • good manufacturing practice
  • hazard analysis and critical control points
  • good agricultural practice

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

12 pages, 7284 KiB  
Article
Simultaneous SERS Detection of Multiple Amino Acids Using ZIF-8@AuNPs as Substrate: Classified with 1D Convolutional Neural Network
by Mengping Huang, Shuai Ma, Jinrong He, Wei Xue, Xueyan Hou, Yuqi Zhang, Xiaofeng Liu, Heping Bai and Ran Li
Appl. Sci. 2024, 14(5), 2118; https://doi.org/10.3390/app14052118 - 04 Mar 2024
Viewed by 548
Abstract
Amino acids found in minor coarse cereals are essential for human growth and development and play a crucial role in efficient and rapid quantitative detection. Surface-enhanced Raman spectroscopy (SERS) enables nondestructive, efficient, and rapid sample detection. Traditional SERS detection efficiency is constrained by [...] Read more.
Amino acids found in minor coarse cereals are essential for human growth and development and play a crucial role in efficient and rapid quantitative detection. Surface-enhanced Raman spectroscopy (SERS) enables nondestructive, efficient, and rapid sample detection. Traditional SERS detection efficiency is constrained by the use of a single target. In this study, three different amino acids (cysteine, valine, and tryptophan) were detected simultaneously using a ZIF-8@AuNPs composite substrate. The linear range of detection was 10−3 to 10−1 M, with limits of detection (LODs) of 2.40 × 10−4 M, 2.24 × 10−4 M, and 1.55 × 10−4 M, respectively. Same linear ranges and LODs were achieved with a one-dimensional convolutional neural network method. Furthermore, this substrate enabled the effective detection of amino acids in millet and efficient detection of cysteine in health products. This study presents a novel method for simultaneous detection of multiple analytes. Full article
(This article belongs to the Special Issue Research in the Food Safety and Quality Management Techniques)
Show Figures

Figure 1

Back to TopTop