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Advanced Analytical Methods for Food Safety and Composition Analysis
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Advanced Analytical Methods for Food Safety and Composition Analysis

A Special Issue of Foods (ISSN 2304-8158) belonging to the section "Food Analytical Methods".

Deadline for manuscript submissions: 16 October 2026 | Viewed by 9249

Editors

Dr. Zhen Yan

E-Mail Website
Guest Editor
Institute of Urban Agriculture, Chinese Academy of Agricultural Sciences, Chengdu 610000, China
Interests: food quality and safety; nutritional quality; high-throughput rapid detection technology; risk monitoring; metabolomics
Dr. Yang Cheng

E-Mail Website
Guest Editor
Research Institute of Pomology, Chinese Academy of Agricultural Sciences/Laboratory of Quality & Safety Risk Assessment for Fruit (Xingcheng), Ministry of Agriculture and Rural Affairs/Supervision & Test Center of Fruit and Nursery Stocks Quality (Xingcheng), Ministry of Agriculture and Rural Affairs, Xingcheng 125100, China
Interests: molecularly imprinted nanomaterials; chemosensors and fluorescence probe; separation and purification methods; chromatographic analysis; food quality and safety
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ensuring food safety and accurately determining food composition are critical for public health, regulatory compliance, and quality control in the food industry. With the expansion of the global food trade and the continuous emergence of new food products, consumers and regulatory bodies are increasingly demanding high-quality, reliable analytical methods.

The complexity of food matrices, the presence of various contaminants (both known and emerging), and the need to precisely determine nutritional and bioactive components pose challenges to traditional analytical techniques. Thus, there is an urgent call for the development and application of advanced analytical methods in the food science field.

This Special Issue aims to gather the latest research on innovative analytical methods for accurately determining food composition and assessing food safety.

We invite anyone working in related areas to contribute with a study, communication, or review article.

Potential Topics include the following:

  • Next-generation spectroscopic techniques;
  • High-resolution mass spectrometry (HRMS);
  • Biosensors and nanotechnology-based detection;
  • Advanced chromatographic methods;
  • Omics approaches;
  • Emerging contaminants analysis;
  • Standardization and validation of novel analytical methods;
  • Sustainable and green analytical chemistry;
  • Advanced molecular imprinting technology (MIT);
  • Advanced chemosensors and fluorescence probes.

Dr. Zhen Yan
Dr. Yang Cheng
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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 safety
  • nutritional quality
  • analytical methods
  • mass spectrometry
  • nanotechnology
  • metabolomics
  • separation, extraction, and purification
  • molecularly imprinted polymers

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Published Papers (6 papers)

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Research

17 pages, 11238 KB  
Article
A High-Performance Fe@N-S-O-C Nanocomposite-Based Electrochemical Sensor for Dopamine Detection in Pork Samples
by Luyao Wang, Xuelian Wu, Yizi Mahai, Wenjing Ma, Lin Zhou, Jing Zhang, Xinhui Wang and Jing Li
Foods 2026, 15(16), 2886; https://doi.org/10.3390/foods15162886 - 18 Aug 2026
Viewed by 266
Abstract
Monitoring dopamine (DA) in pork can provide useful information for assessing meat freshness and quality deterioration. In this work, an Fe@N-S-O-C nanocomposite was fabricated as an electrode modifier for DA determination. The Fe@N-S-O-C nanocomposite was synthesized via precipitation followed by calcination using melamine [...] Read more.
Monitoring dopamine (DA) in pork can provide useful information for assessing meat freshness and quality deterioration. In this work, an Fe@N-S-O-C nanocomposite was fabricated as an electrode modifier for DA determination. The Fe@N-S-O-C nanocomposite was synthesized via precipitation followed by calcination using melamine and ferrous sulfate as precursors. The crystal structure, surface chemical composition, and morphology were characterized by XRD, XPS, SEM, and TEM. The Fe@N-S-O-C-modified glassy carbon electrode (Fe@N-S-O-C/GCE) was then evaluated for its electrocatalytic performance toward DA. Under the optimized conditions (pH 6.0), the sensor showed linear responses to DA over 1–65 and 65–220 μM. The sensitivities for these two ranges were 4.357 and 1.685 μA μM−1 cm−2, respectively, with an LOD of 40 nM. In addition, the Fe@N-S-O-C/GCE showed excellent reproducibility, good repeatability, and strong anti-interference capability against common coexisting substances. After 30 days of storage, 82.74% of the initial current response was retained by the same electrode. Practical applicability of the sensor was verified in pork samples, with recoveries of 95.97–106.73%. These results demonstrate that the Fe@N-S-O-C/GCE sensor offers a reliable and effective platform for DA detection in complex food matrices. Full article
(This article belongs to the Special Issue Advanced Analytical Methods for Food Safety and Composition Analysis)
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17 pages, 1376 KB  
Article
Gas-Assisted Steam Explosion Enables Targeted Regulation of Nutritional and Flavor Quality in Pleurotus eryngii via Microstructural Remodeling and Metabolite Modulation
by Dandan Fu, Li He, Yingqi Hu, Jinping Li, Yuyun Lu, Jianzhao Qi, Xinlong Mao, Yanli Huo, Xiangxin Li and Jiayu Dong
Foods 2026, 15(12), 2126; https://doi.org/10.3390/foods15122126 - 12 Jun 2026
Viewed by 415
Abstract
Gas-assisted steam explosion (GASE) disrupts raw material structures and promotes active release, but its effects on the nutritional quality and flavor of edible fungi remain unclear. Therefore, this study assessed the influence of GASE on the nutritional quality and flavor characteristics of Pleurotus [...] Read more.
Gas-assisted steam explosion (GASE) disrupts raw material structures and promotes active release, but its effects on the nutritional quality and flavor of edible fungi remain unclear. Therefore, this study assessed the influence of GASE on the nutritional quality and flavor characteristics of Pleurotus eryngii. Using the sample as the raw material, we selected the GASE process parameters through single-factor experiments combined with response surface methodology and confirmation experiments. Subsequently, changes in nutrient contents and volatile/non-volatile flavor profiles were quantitatively characterized under these processing conditions. The results indicated that the selected parameters effectively disrupted the cell wall structure of the sample, resulting in a loose and porous microstructure. Consequently, the levels of protein, polysaccharides, amino acids and vitamins were significantly altered. In terms of flavor, this process modified the relative odor activity values of key aroma compounds, including volatile aldehydes and pyrazines, while also affecting the distribution of non-volatile metabolites. This led to the enrichment of flavor compounds such as nucleotides and their derivatives, and organic acids. This study confirmed that GASE technology can effectively enhance the nutritional quality and flavor characteristics of the mushroom by regulating its microstructure and metabolite composition. Full article
(This article belongs to the Special Issue Advanced Analytical Methods for Food Safety and Composition Analysis)
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22 pages, 13923 KB  
Article
Use of Machine Learning Techniques for Fertilization Traceability Discrimination via Core Quality Indicators of Korla Fragrant Pear Fruits
by Junkai Zeng, Haixia Wang, Mingyang Yu, Yan Chen and Jianping Bao
Foods 2026, 15(11), 2003; https://doi.org/10.3390/foods15112003 - 4 Jun 2026
Cited by 1 | Viewed by 466
Abstract
Rational fertilization directly affects the fruit quality of the Korla fragrant pear. However, the variation patterns of fruit appearance and texture indicators under different N-P2O5-K2O ratios are complex, and redundancy among high-dimensional indicators restricts the practical application [...] Read more.
Rational fertilization directly affects the fruit quality of the Korla fragrant pear. However, the variation patterns of fruit appearance and texture indicators under different N-P2O5-K2O ratios are complex, and redundancy among high-dimensional indicators restricts the practical application of quality discrimination and fertilization traceability. In this study, Korla fragrant pear fruits harvested under eight fertilization treatments (including the control) were selected as research materials. Significant differences existed in nutrient composition and application rate among treatments: no N-P2O5-K2O was applied in the CK treatment; for treatments H1–H7, nitrogen (N) application rate ranged from 396.36 to 524.2 g·plant−1, phosphorus (P2O5) from 326.08 to 652.17 g·plant−1, and potassium (K2O) from 450.67 to 1200.08 g·plant−1, with the most prominent differences observed in P-K ratios and application rates. On this basis, 12 appearance and flesh texture indicators were determined, including single-fruit weight, longitudinal diameter, transverse diameter, fruit shape index, pericarp thickness, sclereid content, hardness, adhesiveness, cohesiveness, springiness, gumminess and chewiness. Three machine-learning algorithms, namely Random Forest (RF), Extreme Learning Machine (ELM) and K-Nearest Neighbor (KNN), were used to construct fruit quality discriminant models. The results showed that the RF model achieved the optimal discriminative performance, with accuracy values of 0.876 and 0.865 for the training and validation sets, respectively. Seven core quality indicators, including sclereid content and longitudinal diameter, were screened via feature-importance intersection analysis. The reconstructed RF model based on this indicator set exhibited nearly no loss in discriminative accuracy despite a ~42% reduction in indicator quantity, providing theoretical and technical support for quality grading, fertilization traceability and precision fertilization of Korla fragrant pear. Full article
(This article belongs to the Special Issue Advanced Analytical Methods for Food Safety and Composition Analysis)
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15 pages, 512 KB  
Article
A Rapid Method for the Simultaneous Analysis of Tocopherols and Tocopherol Quinones in Edible Oils Using Normal-Phase High-Performance Liquid Chromatography
by Hongyan Guo, Zengde Zhang, Sameh A. Korma, Taha Mehany, Tao Zhang and Liyou Zheng
Foods 2026, 15(10), 1767; https://doi.org/10.3390/foods15101767 - 17 May 2026
Viewed by 516
Abstract
A normal-phase high-performance liquid chromatography (HPLC) method with UV spectrophotometric detector (SPD) detection was established for the simultaneous analysis of four tocopherol (TP) homologues and their corresponding tocopherol quinones (TQs). Separation was performed on a Sepax Technologies silica column (4.6 mm × 250 [...] Read more.
A normal-phase high-performance liquid chromatography (HPLC) method with UV spectrophotometric detector (SPD) detection was established for the simultaneous analysis of four tocopherol (TP) homologues and their corresponding tocopherol quinones (TQs). Separation was performed on a Sepax Technologies silica column (4.6 mm × 250 mm, 5 μm) using a mobile phase consisting of n-hexane, isopropanol, and tetrahydrofuran, allowing the eight target compounds to be effectively separated within 15 min. Method validation was conducted using standard solutions prepared in n-hexane, providing a direct evaluation of the chromatographic performance under a relatively clean solvent system. The method showed satisfactory linearity, with R2 values of 0.9850–0.9996. The limit of detection (LOD) and limit of quantification (LOQ) ranges were 0.140–0.371 and 0.467–1.235 μg/mL for TP homologues and 0.0564–0.0856 and 0.1708–0.2595 μg/mL for TQ homologues, respectively. Precision was acceptable, with intra-day and inter-day relative standard deviations (RSD) below 2.69% and 3.78%, respectively. To further evaluate its applicability in oil matrices, recovery experiments were performed in peanut oil and camellia oil, yielding recoveries of 91.7–105.8% and 90.9–97.7% for TP homologues and 82.8–98.7% and 79.5–101.8% for TQ homologues, respectively. The method was further applied to edible oil samples. The results showed that the major TP homologues and detectable TQ homologues were determined, while some homologues were below the detection limits. Overall, the proposed method offers a simple and practical approach for the simultaneous analysis of TP and TQ homologues, thereby supporting further investigation of tocopherol oxidation in edible oils. Full article
(This article belongs to the Special Issue Advanced Analytical Methods for Food Safety and Composition Analysis)
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14 pages, 6195 KB  
Article
Dual-Mode Detection of Perfluorooctanoic Acid Using Up-Conversion Fluorescent Silicon Quantum Dots–Molecularly Imprinted Polymers and Smartphone Sensing
by Hongli Ye, Xinran Wang, Xiangqian Xu, Hongyang Xu, Rui Yuan and Ping Cheng
Foods 2026, 15(2), 331; https://doi.org/10.3390/foods15020331 - 16 Jan 2026
Cited by 3 | Viewed by 1017
Abstract
Perfluorooctanoic acid (PFOA) is a persistent and bioaccumulative hazardous pollutant, presenting substantial threats to the environment and human health. The dual-mode, portable, sensitive, low-background, and cost-effective detection methods for PFOA were developed by integrating up-conversion fluorescent silicon quantum dot–molecularly imprinted polymer (MIPs) with [...] Read more.
Perfluorooctanoic acid (PFOA) is a persistent and bioaccumulative hazardous pollutant, presenting substantial threats to the environment and human health. The dual-mode, portable, sensitive, low-background, and cost-effective detection methods for PFOA were developed by integrating up-conversion fluorescent silicon quantum dot–molecularly imprinted polymer (MIPs) with a smartphone-based sensing system. The interaction between PFOA and MIPs resulted in a fluorescence quenching with a range of 2–20 µmol/L and a limit of detection (LOD) of 37.5 nmol/L for the low-background up-conversion fluorescence detection of PFOA, whereas the portable smartphone sensing platform enabled the detection of PFOA with a linear range of 0–5 µmol/L and a LOD of 73.9 nmol/L. Furthermore, the established methods were successfully applied to the detection of PFOA in environmental waters and food samples. This study provides the dual-mode, portable, novel, practical and low-background approaches for the detection of PFOA in the environment and food products. Full article
(This article belongs to the Special Issue Advanced Analytical Methods for Food Safety and Composition Analysis)
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Graphical abstract

20 pages, 2222 KB  
Article
Comprehensive Evaluation of Quality and Antioxidant Capacity of Highbush Blueberries (Vaccinium corymbosum)
by Xiaoli Liu, Jia Zhang, Yindi Di, Haoliang Wan, Kunyu Wang and Jiyun Nie
Foods 2025, 14(18), 3251; https://doi.org/10.3390/foods14183251 - 19 Sep 2025
Cited by 9 | Viewed by 3290
Abstract
Blueberries, widely recognized for their antioxidant capacity, have driven rapid growth in China’s blueberry industry owing to their significant health benefits and economic value. However, a comprehensive evaluation for blueberry quality traits and antioxidant capacity remains lacking in China’s domestic research. This study [...] Read more.
Blueberries, widely recognized for their antioxidant capacity, have driven rapid growth in China’s blueberry industry owing to their significant health benefits and economic value. However, a comprehensive evaluation for blueberry quality traits and antioxidant capacity remains lacking in China’s domestic research. This study systematically evaluated 26 highbush blueberry cultivars with consistent tree age and cultivation practices, which can better reflect cultivar-dependent trait variation. Key findings revealed Earliblue exhibited the highest soluble solid content (SSC) and the lowest titratable acidity (TA), while Bluechip had the most abundant vitamin C (VC). Glucose and fructose were the main components of soluble sugars in highbush blueberries, accounting for over 97% of the total sugars. Citric acid was the dominant organic acid in nearly all cultivars. Malvidin 3-O-galactoside, delphinidin 3-O-galactoside, delphinidin 3-O-arabinoside, malvidin 3-O-arabinoside and petunidin 3-O-galactoside were the most abundant anthocyanins. The 26 blueberry cultivars were graded into high-, medium- and low-anthocyanin content groups. Correlation analysis divided the 14 anthocyanins into two types: antioxidant-related anthocyanins and other anthocyanins. The five cultivars with the highest comprehensive evaluation scores were Sunrise, Bluegold, Elliott, Amblue and Briteblue. These results may establish empirical selection criteria for the selection and efficient utilization of high-quality blueberry cultivars. Full article
(This article belongs to the Special Issue Advanced Analytical Methods for Food Safety and Composition Analysis)
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