Food Analytical Methods最新文献

{"title":"Ultrasound-Assisted Supramolecular Deep Eutectic Solvent Extraction for HPLC–UV Determination of γ-Aminobutyric Acid in Tea","authors":"Nan Li,&nbsp;Shuo Li,&nbsp;Peng Sun","doi":"10.1007/s12161-026-03221-6","DOIUrl":"10.1007/s12161-026-03221-6","url":null,"abstract":"<div><p>In this work, a sensitive ultrasound-assisted extraction method based on a supramolecular deep eutectic solvent (SUPRADES) was developed for the determination of γ-aminobutyric acid (GABA) in tea.In this approach, 2-hydroxypropyl-β-cyclodextrin (2-HP-β-CD) served as the hydrogen-bond acceptor and malonic acid as the hydrogen-bond donor for the preparation of the DES, while ultrasound assistance was employed to intensify mass transfer. The DES composition was first screened, and preliminary univariate experiments were then performed to define reasonable ranges for the key process variables. Final optimization was carried out using a Box-Behnken design-based response surface methodology (BBD-RSM), with DES dosage, ultrasonication time, solid-to-liquid ratio, K₂HPO₄ addition level, and derivatization time included as variables. The obtained model was highly significant (<i>p</i> &lt; 0.0001), with a non-significant lack of fit (<i>p</i> = 0.9994), affording an R² of 0.9995.Under the optimized conditions, excellent linearity was achieved over 0.5–500 μg/mL (R² = 0.9995), with a limit of detection (LOD) and limit of quantification (LOQ) of 0.27 μg/mL and 1.25 μg/mL, respectively. Using derivatized GABA standard solutions, the intra- and inter-day RSDs were 1.5–2.1% and 1.9–3.1%, respectively. Recoveries for spiked tea samples after the complete sample-preparation procedure ranged from 82.3% to 106.9%.The greenness of the developed method was assessed using two quantitative green metrics, namely the Analytical Eco-Scale and AGREE. The proposed method obtained an Eco-Scale score of 75, indicating an acceptable greenness profile within the Eco-Scale framework, whereas the AGREE assessment gave an overall score of 0.50, suggesting moderate overall greenness and revealing remaining limitations related to derivatization, organic solvent use, waste generation, and workflow integration.The proposed method was successfully applied to real tea samples and exhibited a limited matrix effect, offering a practical sample-preparation strategy for other complex food matrices.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148782679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Explainable Multimodal Learning for Genotype Classification Using Image-Based and Biochemical Features: A Case Study on Black Cumin (Nigella sativa L.)","authors":"Sevim Akçura","doi":"10.1007/s12161-026-03231-4","DOIUrl":"10.1007/s12161-026-03231-4","url":null,"abstract":"","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148782680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smartphone-Assisted Microfluidic Paper Coordination Array for On-Site Screening of Multiple Heavy Metal Ions","authors":"Wei-Ping Niu,&nbsp;Peng-Fei Ye,&nbsp;Li-Hong Yu,&nbsp;Xiao-Fang Shen","doi":"10.1007/s12161-026-03220-7","DOIUrl":"10.1007/s12161-026-03220-7","url":null,"abstract":"<div><p>On-site detection of heavy metal ions remains challenging, especially for environmental monitoring and food safety. Herein, we present a paper-based microfluidic coordination array for the portable detection of Hg²⁺, Pb²⁺, Cd²⁺, and Cu²⁺. The device requires only 20 µL of sample solution to completely fill six channel reservoirs, and color changes are produced by coordination of heavy metal ions with chelating ligands. The color responses were captured using a smartphone under controlled LED illumination and converted into digital red–green–blue (RGB) signals. The device distinguished Hg²⁺, Pb²⁺, Cd²⁺, and Cu²⁺ in spiked water and canned juice at 2 µM; linear discriminant analysis (LDA) achieved 100% prediction accuracy for unknown single-ion samples and 93.3% for unknown mixed-ion samples. Clear clustering was obtained for tap water, lake water, and three canned juice matrices. At 500 µM, under the tested conditions, no obvious response to common potentially interfering ions was observed except for Zn²⁺. This paper-based microfluidic coordination array enables portable and rapid preliminary screening of heavy metals, showing potential for environmental monitoring and food safety applications.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148782516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Classification of Raw Açai (Euterpe oleracea Mart.) Fruits from Upland and Lowland Environments Using Portable Near-Infrared Spectroscopy","authors":"Hervé Rogez,&nbsp;João Paulo Silva e Silva,&nbsp;Risaldo Amaral Junior,&nbsp;Lorena Modesto Caldeira,&nbsp;Vincent Baeten,&nbsp;Neirivaldo Cavalcante da Silva","doi":"10.1007/s12161-026-03224-3","DOIUrl":"10.1007/s12161-026-03224-3","url":null,"abstract":"<div><p>Near-infrared (NIR) spectroscopy combined with chemometrics was applied to classify <i>Euterpe oleracea</i> (açai) fruits according to their soil environment. Raw fruit samples were analyzed using a handheld NIR spectrometer. Compositional differences between soil environments were confirmed by reference data and the most discriminative NIR regions were related to moisture, phenolics, and lipids. Discriminant models outperformed one-class models. Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machines Discriminant Analysis (SVM-DA) provided perfect or near-perfect classifications (F1 = 0.97–1.00), confirming the generalization ability of latent-variable and kernel-based strategies. Variable selection improved model interpretability without compromising accuracy. One-class models, Soft Independent Modelling by Class Analogy (SIMCA and DD-SIMCA) and One-class partial least squares (OCPLS), exhibited broader variability for upland fruits, reflecting greater intra-class chemical diversity. Handheld NIR combined with multivariate classification provides a rapid, reliable, and sustainable analytical approach for discriminating açai fruits by soil environment, offering a promising tool for origin verification and quality control in the açai production chain.</p><h3>Graphical Abstract</h3><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12161-026-03224-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148782106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Migration of Metals and Metalloids from Plastic Food Containers under Realistic Use Conditions and Associated Human Health Risk Assessment in South Korea","authors":"Yujin Han,&nbsp;Hyun-Jung Chung","doi":"10.1007/s12161-026-03229-y","DOIUrl":"10.1007/s12161-026-03229-y","url":null,"abstract":"<div><p>Widespread use of disposable plastic food containers has raised concerns regarding the migration of trace metals and metalloids into foods. This study developed and applied analytical methods for the determination of nine metals and metalloids (Pb, Sb, Cd, Ge, Co, Mn, Sn, As, Hg) released from polypropylene (PP), polyethylene terephthalate (PET), and polystyrene (PS) food containers commonly used in South Korea. Migration tests were conducted using 4% acetic acid and deionized water at 70 °C and 100 °C, with storage periods of up to 48 h under realistic use conditions. The concentrations of target analytes were determined by inductively coupled plasma–mass spectrometry and a direct mercury analyzer. The analytical methods were validated in terms of linearity, limits of detection, and limits of quantification, with correlation coefficients exceeding 0.99 for all analytes. Migration behavior varied according to polymer type and test conditions. PET exhibited consistently higher Sb migration, PP showed relatively greater release of Pb, Cd, and Mn, and PS showed relatively higher As migration levels under prolonged storage conditions. Estimated daily intake and target hazard quotient (THQ) calculations indicated that most exposures were within acceptable limits, although elevated potential health risks were observed for Pb, Sb, and As under specific acidic conditions. The validated analytical approach provides a useful tool for monitoring metal migration from food contact materials and for supporting food safety assessments.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148782420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electrochemical Tracking of Nitrite Depletion in Additive-Rich Cured Meats Using a Polymer@Peroxomolybdate/MXene-Modified Electrode","authors":"Asiye Aslıhan Avan,&nbsp;Hayati Filik","doi":"10.1007/s12161-026-03230-5","DOIUrl":"10.1007/s12161-026-03230-5","url":null,"abstract":"<div><p>Monitoring toxic nitrite (NO₂⁻) depletion in complex food matrices is crucial for food safety, yet challenging due to interfering matrices. Herein, we report a high-performance electrochemical sensor fabricated by decorating a highly conductive MXene (Ti₃C₂T_x) nanomaterial with a newly synthesized polymer-supported peroxomolybdate (PMo) composite. Structural and morphological properties of the PDDA@PMo/MXene composite were systematically validated using FTIR, XRD, SEM, TEM, and EDX. The modified sensor exhibited exceptional electrocatalytic activity, enabling simultaneous and sensitive quantification of both NO₂⁻ and ascorbic acid (AA). The same sensor was successfully applied to monitor nitrate (NO₃⁻) levels following its chemical reduction to NO₂⁻ using a spongy Zn@Cd catalyst. Specifically, NO₂⁻ was detected across two wide linear ranges (2.0–100 μM and 100–1000 μM) with a low detection limit (LOD) of 0.39 μM, while AA quantification spanned 10–1200 μM with an LOD of 2.0 μM. Furthermore, the sensor effectively monitored NO₂⁻ depletion in cured meat samples containing nitrates and AA. The results demonstrated a strong correlation with standard laboratory methods, underscoring the robust practical applicability of the PDDA@PMo/MXene platform for advanced food safety monitoring.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148782217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Standardized Classification of Tea Species and Grades Based on Electronic Nose and Optimized Support Vector Machine Algorithms","authors":"Zeyu Xu,&nbsp;Jingwen Zhu,&nbsp;Congli Mei,&nbsp;Hui Jiang","doi":"10.1007/s12161-026-03222-5","DOIUrl":"10.1007/s12161-026-03222-5","url":null,"abstract":"<div><p>Rapid and accurate identification of tea species and grade classification are crucial for regulating tea market transactions and advancing the standardized and intelligent development of the tea industry. This study innovatively achieves efficient classification and detection of tea species and grades through a self-developed portable electronic nose technology, combined with data preprocessing methods and multiple optimized pattern recognition algorithms. Firstly, four representative varieties of black tea and green tea, covering 26 grades, are selected as research objects. Volatile aroma characteristic signals of tea are collected using an electronic nose sensor array, and the differences in these signals originate from variations in sensory evaluation, which lays a feasible foundation for the classification tasks in this study. Subsequently, multiple classification models are compared. Results demonstrate that the AW-FA-SVM model exhibits the optimal performance, effectively resolving the identification dilemma caused by overlapping features of adjacent grade teas. The technical scheme proposed herein realizes the standardization, automation, and rapidity of the classification process, efficiently overcoming the shortcomings of strong subjectivity in traditional sensory evaluation and time-consuming complexity in physicochemical analysis. It provides new insights and practical basis for the future development of intelligent and portable online detection platforms for tea quality.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148752331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid Electrochemical Screening of Chloramphenicol in Milk Using a Carbon Black Modified Glassy Carbon Electrode","authors":"Déborah Oliveira Lopes,&nbsp;Felipe Magalhães Marinho,&nbsp;Jéssica Rocha Camargo,&nbsp;Nelson Luis Gonçalves Dias de Souza,&nbsp;Bruno Campos Janegitz,&nbsp;Geiser Gabriel Oliveira","doi":"10.1007/s12161-026-03223-4","DOIUrl":"10.1007/s12161-026-03223-4","url":null,"abstract":"<div><p>Chloramphenicol is a broad-spectrum antibiotic that poses a significant risk to public health and the environment. Exposure to this compound has been associated with serious adverse effects, including aplastic anemia and genotoxic/carcinogenic concerns. Therefore, the development of a reliable method to detect chloramphenicol in food samples is essential. However, its determination in complex food matrices remains challenging because of possible matrix effects, low analyte concentration, and the need for sensitive and selective methods. To this end, we developed a highly sensitive electrochemical sensor to detect chloramphenicol in milk samples. The sensor was based on the modification of a glassy carbon electrode surface with carbon black. Electroanalytical analyses were performed using cyclic voltammetry and differential pulse voltammetry, and the results revealed that the sensor has high sensitivity for chloramphenicol determination. Under optimal conditions, the sensor showed a linear response over the range of 0.05 to 87.0 μmol L⁻¹, with a detection limit of 0.0012 μmol L⁻¹ and a sensitivity of 0.07 μA L μmol⁻¹ for chloramphenicol detection in Britton–Robinson buffer (0.04 mol L⁻¹, pH 7.00). The recovery rates in milk samples ranged from 91.7% to 106.7%. The sensor demonstrated excellent stability and reliability in real sample analyses, highlighting its practicality for chloramphenicol detection in milk samples and supporting further studies aimed at expanding its application to other food matrices.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12161-026-03223-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Manganese Dioxide Nanoflower-Based Aptananozyme (MnO2 NFs@Apt): A Novel Colorimetric/Fluorescent Dual-Mode Platform for Aflatoxin B1 Detection","authors":"Yi Zhi,&nbsp;Tingting Ren,&nbsp;Yinhe Zhao,&nbsp;Lei Lv,&nbsp;Zhijun Guo","doi":"10.1007/s12161-026-03225-2","DOIUrl":"10.1007/s12161-026-03225-2","url":null,"abstract":"<div><p>To address the limitations of conventional aflatoxin B₁ (AFB₁) detection methods, including high-performance liquid chromatography (HPLC) and enzyme-linked immunosorbent assay (ELISA), which are characterized by complex operation and high cost, this study proposes a dual-mode aptasensor constructed on MnO₂ nanoflowers (MnO₂ NFs). This sensor integrates colorimetric and fluorescent detection strategies, leveraging the high catalytic activity and fluorescence quenching properties of MnO₂ NFs to enhance detection sensitivity. Key assay parameters, including MnO₂ NFs concentration, aptamer concentration, pH, and incubation time, were optimized to improve analytical performance. The method eliminates the need for complex nanomaterials or DNA amplification, offering operational simplicity and low cost. The proposed strategy was demonstrated to be effective for food safety monitoring, while also highlighting the potential of MnO₂ nanomaterials in advanced biosensing applications.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Studies of Different Extraction Processes on Litsea cubeba Kernel Oil: Effect on Physicochemical Properties, Fatty Acid Composition, Active Components, Antioxidant Capacity, and Volatile Aroma Compounds","authors":"Xinsheng Xiao,&nbsp;Xinyu Sun,&nbsp;Yandong Zhang,&nbsp;Zhenfeng Jiang,&nbsp;Jinhua Shao,&nbsp;Hongyu Jiang,&nbsp;Liyan Jiang","doi":"10.1007/s12161-026-03219-0","DOIUrl":"10.1007/s12161-026-03219-0","url":null,"abstract":"<div><p>The kernels of <i>Litsea cubeba</i> seeds are the primary byproduct after essential oil extraction, rich in oils. Their efficient utilization and quality enhancement are crucial to achieving comprehensive, high-value development of all <i>Litsea cubeba</i> components. The objective of this study is to investigate the effects of traditional methods (Cold Pressing (CP), Hot Pressing (HP), Soxhlet Extraction (SE)) and a novel method (Ultrasonic-Assisted Extraction (UAE)) on the oil yield, physicochemical properties, active components, antioxidant capacity, and volatile constituents of <i>Litsea cubeba</i> kernel oil (LCKO). Results indicate that the fatty acid composition of LCKO after steam distillation is dominated by linoleic acid and lauric acid, with unsaturated fatty acids accounting for over 50%. SE yielded the highest oil content (18.01%), HP exhibits the highest squalene content (4.55 mg/kg), while CP demonstrates the highest total phenolic content (185.92 mg/100 g) and the best oxidative stability. UAE maintains a favorable oil yield while effectively preserving most active components. Additionally, CP maximally retains key terpenoid flavor compounds such as limonene and myrcene, while UAE demonstrates exceptional performance in releasing aldehydes and certain terpenes. Overall, UAE is an effective method for producing high-quality LCKO, achieving a favorable balance in extraction efficiency, nutritional content, and flavor quality.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}