Food Analytical Methods最新文献

{"title":"Metal-Organic Frameworks (MOFs) Materials Employment in Solid-Phase Extraction of Residues in Food Samples","authors":"Oya Irmak Şahin,&nbsp;Jülide Hızal","doi":"10.1007/s12161-026-03279-2","DOIUrl":"10.1007/s12161-026-03279-2","url":null,"abstract":"<div><p>Food contamination, which arises as a result of rapid industrial progress, has serious adverse effects on food quality and safety. The reduced food quality threatens our health. Thus, the residues, additives, and other constituents of the food matrix, as well as the adulteration and the application of preservatives, must be quantitatively determined to ensure food safety standards are met. Considering the impact of the matrix is crucial for detecting food analytes, as metal-organic frameworks (MOFs) are important due to their ability to alleviate this effect. The rather high surface area and porosity of the MOFs enhance the selectivity and sensitivity of the method utilized. Furthermore, the outstanding properties, such as adjustable pore and surface structures, availability for modifications, and shorter processing time, make them preferred materials for SPE applications. This study examines the MOFs’ utilization in residue, additives, and other component analyses in foods by discussing the benefits in sensitivity and detectable quantity in terms of LOD and LOQ.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986666","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":"A Bifunctional Naphthalimide Fluorescent Probe for the Detection and Application of Methylglyoxal and Nitrite","authors":"Xiaoming Wu,&nbsp;Shaoxiang Yang,&nbsp;Hongyu Tian,&nbsp;Baoguo Sun","doi":"10.1007/s12161-026-03281-8","DOIUrl":"10.1007/s12161-026-03281-8","url":null,"abstract":"<div><p>A naphthalimide fluorescent probe (probe DPDP) for the detection and adsorption of methylglyoxal (MGO) and nitrite was developed. The concentration of MGO was linearly correlated with the fluorescence intensity of probe DPDP. The solution's color steadily shifted from light blue to vivid blue. In an acetic acid water system, the probe DPDP's fluorescence intensity and nitrite have a linear relationship, with the fluorescence intensity increase as the nitrite concentration rises. Combined with the RGB analysis of the images with smartphone, the quantitative relationship between the fluorescence intensity and the measured object was established. It can be converted into the corresponding color heat map, which can be used to evaluate the concentration of the measured substance in the solution. Ultimately, the MGO and nitrite in the solution were successfully adsorbed and removed using the probe hydrogel. Collectively, probe DPDP represents a feasible analytical approach for practical detection scenarios.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148987082","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":"Magnetic Deep Eutectic Solvent-Based Vortex-Assisted Liquid-Phase Microextraction for Mercury Determination in Seafood Samples","authors":"Rosivan dos Santos de Assis,&nbsp;Luana Bastos Santos,&nbsp;Márcio Souza Santos,&nbsp;Alexilda Oliveira de Souza,&nbsp;Valfredo Azevedo Lemos","doi":"10.1007/s12161-026-03272-9","DOIUrl":"10.1007/s12161-026-03272-9","url":null,"abstract":"<div><p>This study aimed to develop and validate a vortex-assisted liquid-phase microextraction (VA-LPME) method based on a magnetic deep eutectic solvent (MDES) for the determination of mercury in seafood samples by cold vapor atomic absorption spectrometry (CV-AAS). The MDES was prepared from menthol and octanoic acid, and Fe₃O₄ nanoparticles were incorporated to impart magnetic responsiveness, enabling rapid phase separation without centrifugation. Experimental conditions were optimized using a univariate approach, including DES composition (menthol:octanoic acid, 1:3), nanoparticle mass (75 mg Fe₃O₄), agitation mode (vortex), extraction time (50 s), extraction solvent volume (100 µL), and pH (4.2). Under the optimized conditions, the proposed method achieved a detection limit of 0.09 µg L⁻¹ and an enrichment factor of 51. Accuracy was confirmed by the analysis of certified reference materials, with measured values in good agreement with the certified values. The method was successfully applied to the determination of mercury in shellfish, sea bass, oyster, and crab samples, demonstrating its suitability for complex food matrices. The proposed procedure combines good analytical performance with low solvent consumption, simple operation, and a moderate green profile (AGREEprep = 0.54), supporting its potential for routine mercury monitoring in seafood.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12161-026-03272-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148987081","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":"Green Spectroscopic and One-Class Classification Approach for Robust Authentication of Tahini","authors":"Nevra Kucukcelebioglu,&nbsp;Yagmur Bilge Karakas,&nbsp;Cagri Cavdaroglu,&nbsp;Banu Ozen","doi":"10.1007/s12161-026-03268-5","DOIUrl":"10.1007/s12161-026-03268-5","url":null,"abstract":"<div><p>Ensuring tahini authenticity is essential because of its high nutritional value, economic importance, and susceptibility to adulteration. This study investigated the detection of peanut and sunflower oil adulteration in tahini using attenuated total reflectance Fourier-transform infrared (ATR-FTIR) and UV–Vis spectroscopy coupled with one-class classification (OC) models. Oil fractions obtained by centrifugation served as authentic markers, and forty-five tahini samples were adulterated with peanut or sunflower oil at levels ranging from 3 to 50% (v/v). Spectral data were preprocessed using scatter-correction algorithms, derivative transformations, and smoothing filters before analysis with Data-Driven Soft Independent Modeling of Class Analogies (DD-SIMCA) and one-class Support Vector Machine (OC-SVM) models. Following the rigorous framework for OC, model performance was primarily evaluated using validation sensitivity for the authentic class, whereas specificity was assessed only against the selected challenge adulterants. ATR-FTIR coupled with DD-SIMCA provided the best authentication performance, achieving validation sensitivity of up to 0.86, while UV–Vis data reached validation sensitivities of up to 0.94 but showed lower ability to reject the challenge adulterants. OC-SVM models exhibited greater variability and generally lower robustness than DD-SIMCA. Authenticity thresholds of 10.78% and 13.36% adulteration were established from the predicted values of authentic samples using ATR-FTIR and UV–Vis data, respectively. These findings demonstrate that ATR-FTIR combined with DD-SIMCA, together with solvent-free sample preparation and green analytical principles, provides a rapid, reliable, and sustainable strategy for authenticity screening of tahini and related food products.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986667","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":"Maize Variety Identification at the Seedling Stage Based on Near-Infrared Spectroscopy and the XGBoost Model","authors":"Jiafan Li,&nbsp;Xiaodan Ma,&nbsp;Haiou Guan,&nbsp;Jiao Yang,&nbsp;Yi Yao","doi":"10.1007/s12161-026-03237-y","DOIUrl":"10.1007/s12161-026-03237-y","url":null,"abstract":"<div><p>To address the difficulty in field variety identification and precision management arising from the phenotypic similarity among different maize varieties at the seedling stage, this study proposes a seedling-stage maize variety identification method that integrates near-infrared (NIR) spectroscopy, interval random frog (IRF)-based feature selection, and the XGBoost model. First, a partial least squares discriminant analysis (PLS-DA) classification model was used to compare different preprocessing methods, among which Savitzky-Golay (SG) smoothing showed superior overall classification performance. Subsequently, the IRF algorithm was applied only to the training set to select 124 feature wavelengths from 228 effective wavelength variables, reducing the number of variables by 45.61%. The selected wavelengths were then used as inputs to the XGBoost model for variety identification. The results showed that the SG-IRF-XGBoost model achieved an accuracy of 95.83%, a macro-average F1-score of 95.07%, and a macro-average precision of 97.30% on the independent test set, with a single-sample prediction time of 0.6460 ms. This study demonstrates that NIR spectroscopy combined with IRF-based feature selection and the XGBoost model can serve as a technical reference for the rapid and non-destructive identification of maize varieties at the seedling stage.</p><h3>Graphical Abstract</h3>\u0000<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986602","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":"Post-mortem Analytical Methods for Tuberculosis Detection in Livestock and Selected Game Species for Human Consumption: A Systematic Review","authors":"Handreza Junqueira Cobra,&nbsp;Leonor Orge,&nbsp;Paula Mendonça,&nbsp;Paulo Carvalho,&nbsp;Madalena Vieira-Pinto","doi":"10.1007/s12161-026-03263-w","DOIUrl":"10.1007/s12161-026-03263-w","url":null,"abstract":"<div><p>Tuberculosis (TB), caused by members of the <i>Mycobacterium tuberculosis</i> complex (MTBC), remains a relevant zoonotic and food safety concern in livestock and game species intended for human consumption. Reliable post-mortem detection is essential for slaughterhouse surveillance, laboratory confirmation, and control programs. This systematic review evaluates analytical and diagnostic methods used for post-mortem TB detection in cattle, water buffaloes, small ruminants, swine, wild boar, and cervids. A systematic search of LILACS, PubMed, Scopus, and Web of Science was conducted according to PRISMA principles to identify peer-reviewed studies published between 2014 and 2024. The included studies were grouped into three categories: lesion-based assessment, immunological assays, and etiological confirmation by bacteriological and molecular methods. Molecular assays, particularly PCR-based methods, were the most frequently reported approaches and showed advantages in speed and analytical specificity, whereas bacteriological culture remained the reference method despite long turnaround times. Gross inspection and histopathology continued to play an important role in routine surveillance, but their performance was insufficient when used alone. Across species and analytical settings, no single method consistently achieved optimal post-mortem detection. The available evidence supports integrated workflows combining carcass inspection with confirmatory laboratory testing to improve reliability, support official surveillance, and strengthen food safety monitoring in animals for human consumption.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986664","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":"A High-Capacity Molecularly Imprinted Polydopamine Stir-Bar Platform for Efficient Removal of Ethyl Carbamate and Structural Analogs in Whiskeys","authors":"Tabkrich Khumsap,&nbsp;Achirapon Puttawong,&nbsp;Pubate Soikaew,&nbsp;Suwussa Bamrungsap","doi":"10.1007/s12161-026-03271-w","DOIUrl":"10.1007/s12161-026-03271-w","url":null,"abstract":"<div><p>Ethyl carbamate (EC), a Group 2A carcinogen naturally occurring in fermented products, poses significant health risks due to its colorless and odorless properties. Conventional removal techniques often lack selectivity or degrade sensory quality. This study introduces a high-capacity molecularly imprinted polydopamine (MIP-PDA) stir-bar that transforms traditional sorptive extraction into a practical tool for the efficient adsorptive removal of EC. Synthesized via a sustainable, aqueous surface-initiated self-polymerization approach, the MIP-PDA exhibited a uniform granular structure. This morphology enhanced the effective surface area, facilitating rapid mass transfer and achieving adsorption equilibrium within 30 min. Adsorption isotherms followed the Langmuir model, demonstrating a superior maximum capacity (Q_m) of 110.79 mg/g, which is 2.37 times higher than the non-imprinted polymer (NIP). The platform demonstrated preferential binding affinity toward carbamates alongside high matrix tolerance, five-week storage stability, and reliable reusability. Practical validation for efficient removal was conducted across three distinct commercial whiskey matrices. Quantitative analysis via GC–MS yielded high recovery rates of from 98.25 to 110.86%. These results highlight the MIP-PDA stir-bar as a robust and highly efficient tool for efficient decontamination, advancing sustainable processing and enhancing the safety of fermented beverages.</p><h3>Graphical Abstract</h3>\u0000<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986603","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":"Convenient Determination of Trace Free Fatty Acids in Edible, Expired and Gutter Oils through Catalytic Esterification with Trimethylsilyl Diazomethane and Gas Chromatography–Mass Spectrometry Analysis","authors":"Yunna Li,&nbsp;Xueliang Li,&nbsp;Yuming Chang,&nbsp;Fan Qi,&nbsp;Lingxia An,&nbsp;Kezhi Jiang","doi":"10.1007/s12161-026-03277-4","DOIUrl":"10.1007/s12161-026-03277-4","url":null,"abstract":"<div><p>The content of free fatty acids (FAs) is a critical safety indicator for edible oils. However, the current GC–MS analysis of FAs is not satisfactory due to their inefficient derivatization under mild conditions. In this study, we achieved efficient methylation of fatty acids within 10 min by derivatization with trimethylsilyldiazomethane (TMSD) catalyzed trimethyl chlorosilane (TMSC). Then, an efficient methylation of FAs was achieved within 10 min through derivatization with trimethylsilyldiazomethane under the catalysis of trimethylchlorosilane, and a convenient method for the determination of 33 free fatty acids in oil samples has been developed by methylation in combination with extraction with methanol and GC–MS analysis. The method exhibited good reproducibility, sensitivity, and recovery. The determined content range of several free FAs (e.g. palmitoleic acid, α-linolenic acid, linoleic acid, elaidic acid, and arachidic acid) in edible oils was significantly lower than that in expired edible oils (or gutter oil). Furthermore, the content of γ-linolenic acid, which is prone to oxidation, was below the LOQ (0.40 ng/g) in gutter oil, suggesting it as an indicator of severe oxidative degradation. This method was characterized by its ease of operation and good reproducibility, presenting significant potential for oil quality control.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986601","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 Detection of Escherichia coli O157:H7 and Salmonella in Raw Meat Using Membrane Filtration and Handheld Real‐time qPCR","authors":"Niu Gao,&nbsp;Yumei Huo,&nbsp;Jiaxuan Hao,&nbsp;Jingjing Xu,&nbsp;Daijing Yu,&nbsp;Xiangjie Guo,&nbsp;Jinding Liu,&nbsp;Jiangwei Yan","doi":"10.1007/s12161-026-03275-6","DOIUrl":"10.1007/s12161-026-03275-6","url":null,"abstract":"<div><p>Foodborne pathogens, including <i>Escherichia coli</i> O157:H7 and <i>Salmonella</i>, remain leading causes of foodborne illness worldwide, underscoring the urgent need for rapid detection strategies. Herein, we assessed the feasibility of integrating membrane filtration with a handheld real‐time quantitative polymerase chain reaction (qPCR) platform (CarryOn P1000Q) to enable rapid detection of <i>E. coli</i> O157:H7 and <i>Salmonella</i> in raw meat. Key filtration parameters influencing bacterial concentration—including filter membrane material, membrane pore size, elution buffer, elution strategy, and filtration volume—were systematically optimized. Results demonstrated that a 0.22‐µm polytetrafluoroethylene membrane combined with a 30-mL sample volume, phosphate‐buffered saline (pH 7.40), and repeated aspiration elution yielded the optimal overall performance. Using the optimized filtration protocol, the CarryOn P1000Q handheld qPCR assay exhibited consistent amplification performance, achieving an analytical limit of detection (LOD) of 200 genomic copies per reaction. When applied to artificially contaminated raw meat samples, the complete workflow demonstrated a practical LOD of 10⁵ colony-forming units/25 g for <i>E. coli</i> O157:H7 and <i>Salmonella</i>. The total sample-to-result assay time was ~ 50 min, involving bacterial concentration, DNA extraction, and qPCR amplification. Although the workflow enabled rapid detection without microbial enrichment and may serve as a useful reference for the development of portable foodborne pathogen detection strategies, its current practical sensitivity remains inadequate for routine food safety monitoring or for ruling out low‐level contamination. Consequently, further optimization is required to improve its detection performance in complex food matrices.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986175","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-Based Digital Image Analysis (DIA) for Rapid Determination of Pyraclostrobin in Water and Vegetable Samples","authors":"Naruesorn Samanpong,&nbsp;Ajchara Imkum Putkham,&nbsp;Sakunna Wongsaipun,&nbsp;Wanwisa Janrungroatsakul,&nbsp;Anchalee Sirikulkajorn,&nbsp;Mrigendra Dubey,&nbsp;Wipharat Chuachuad Chaiyasith","doi":"10.1007/s12161-026-03273-8","DOIUrl":"10.1007/s12161-026-03273-8","url":null,"abstract":"<div><p>An efficient and user-friendly smartphone-based digital image analysis (DIA) method was developed for the determination of pyraclostrobin residues in water and vegetable samples. The proposed method is based on a diazotization–coupling reaction, in which pyraclostrobin has been converted into a stable azo dye, enabling quantitative analysis by both conventional UV–Vis spectrophotometry and smartphone-assisted DIA. The developed approach offers a practical alternative for rapid pesticide residue screening, particularly for field-based and resource-limited applications. The analytical performance of both methods was systematically evaluated in terms of linearity, limit of detection (LOD), limit of quantification (LOQ), precision, and recovery. The UV–Vis spectrophotometric method showed a linear response over the concentration range of 0.21–1.00 mg L⁻¹, with LOD and LOQ values of 0.06 and 0.21 mg L⁻¹, respectively, and excellent repeatability with a minimum %RSD of 0.93%. The smartphone-based DIA method, using the green (G) color channel for quantification, achieved LOD and LOQ values of 0.09 and 0.32 mg L⁻¹, respectively, with satisfactory precision (%RSD = 2.88%). The applicability of the proposed methods was validated using real samples, including surface water, tap water, drinking water, and vegetable matrices. Recovery values ranged from 86.0 to 104.0% for the UV–Vis method and 95.0–120.0% for the smartphone-based DIA method. These results demonstrate that the proposed smartphone-assisted DIA method provides a reliable, portable, cost effective and accessible platform for rapid pyraclostrobin residue primary screening in environmental and food samples, showing strong potential for on-site monitoring and food safety applications.</p><h3>Graphical Abstract</h3>\u0000<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986600","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}