Food Analytical Methods最新文献

{"title":"GC–IMS for Muscle-Based Prepared Foods: Volatile Flavor Chemistry from Raw Material Screening to Processing, Storage, and Reheating","authors":"Mengchao Lv,&nbsp;Qi Zhang,&nbsp;Yuling Wang,&nbsp;Jicai Bi,&nbsp;Xingqi Ou,&nbsp;Hong-Ju He","doi":"10.1007/s12161-026-03262-x","DOIUrl":"10.1007/s12161-026-03262-x","url":null,"abstract":"<div><p>Volatile flavor instability is a critical bottleneck hindering the quality standardization of muscle-based ready-to-eat and ready-to-heat foods. To define the current state of the field, relevant literature was retrieved from four databases (Scopus, PubMed, Google Scholar, and X-MOL), with priority given to studies published from 2020 to 2026. A total of 59 gas chromatography–ion mobility spectrometry (GC–IMS) application studies were synthesized in the evidence map. The evidence was organized across four major stages of the industrial chain: raw material screening and traceability, processing and flavor regulation, storage and cold-chain quality assessment, and reheating-related flavor deterioration. The synthesis indicates that GC–IMS has progressed from static volatile fingerprinting toward dynamic monitoring of flavor trajectories, enabling process-endpoint identification, early spoilage warning, cold-chain abnormality evaluation, and warmed-over flavor diagnosis. Chemometric modeling, multi-sensor data fusion, and sensory calibration further strengthen the translation of spectral fingerprints into quality-control decisions. Major barriers remain in quantitative calibration, cross-instrument transferability, and industrial validation. Collectively, current evidence supports GC–IMS as a promising PAT-compatible analytical platform for whole-chain flavor governance, while routine inline industrial deployment remains prospective.</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":"148986514","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":"Stabilization of Conventional Cathepsin L Activity Assay in Crude Herring Muscle Extracts by NaCl Addition","authors":"Mariusz Szymczak","doi":"10.1007/s12161-026-03261-y","DOIUrl":"10.1007/s12161-026-03261-y","url":null,"abstract":"<div><p>The proteolytic activity of cathepsins plays a key role in post-mortem changes in fish muscle, affecting texture, flavour development and overall product quality. Reliable determination of cathepsin B and L activities in crude fish muscle extracts is challenging because of limited substrate specificity and strong matrix effects. The classical differential method is based on Z‑Arg‑Arg‑AMC (cathepsin B) and Z‑Phe‑Arg‑AMC (cathepsin B + L) with subsequent subtraction (L = (B + L) − B). However, differences in the catalytic efficiencies of cathepsin B against these two substrates and interference from other protease classes can lead to even negative calculated values for cathepsin L in crude extracts. In this study, extraction conditions and inhibitor profiling of purified cathepsins D, B and L from Baltic herring muscle were evaluated. The experiments revealed substantial interdependence between protease classes and demonstrated that the classical differential approach for cathepsin L determination may fail under crude‑extract conditions. Purified enzymes showed distinct NaCl sensitivities: cathepsins B and D were strongly inhibited at 3–5 g/100 g NaCl, whereas cathepsin L activity increased under the same conditions. These differences in salt sensitivity enabled the use of NaCl for functional enrichment of cathepsin L contribution to activity in crude extracts. The NaCl‑addition assay reduced non-specific protease contributions and eliminated subtraction-derived artefacts without the need for selective synthetic inhibitors. The proposed NaCl-addition approach retains the classical two-substrate framework while improving robustness and interpretability in complex fish muscle matrices. The approach can be readily adopted by laboratories without purchasing new substrates or inhibitors.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12161-026-03261-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986498","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":"Ultrabright AIE-MOF-based Lateral Flow Immunoassay for Rapid Detection of Burkholderia gladioli","authors":"Huiya Wei,&nbsp;Jinbo Cao,&nbsp;Lu Han,&nbsp;Xianglong Xu,&nbsp;Qixuan Jin,&nbsp;Xiaoya Li,&nbsp;Hui Yu,&nbsp;Xiujin Chen,&nbsp;Zhaozhou Li,&nbsp;Yao Wang,&nbsp;Hui Chen","doi":"10.1007/s12161-026-03276-5","DOIUrl":"10.1007/s12161-026-03276-5","url":null,"abstract":"<div><p><i>Burkholderia gladioli</i> (<i>B. gladioli</i>), a foodborne pathogen, poses a significant threat to global food safety because of its adverse effects on human health. Conventional detection methods are often labor-intensive, time-consuming, and costly, highlighting the urgent need for rapid, simple, and sensitive detection strategies. Lateral flow immunoassay (LFIA) has been widely adopted for point-of-care testing (POCT) owing to its simplicity, portability, and rapid response. In this study, an aggregation-induced emission metal–organic framework (AIE-MOF)-based LFIA (AIE-MOF-LFIA) was developed for the rapid on-site detection of <i>B. gladioli</i>. The proposed assay achieved a detection limit of 72 CFU/mL, representing an approximately 25-fold improvement in sensitivity over conventional gold-nanoparticle-based LFIA (AuNP-LFIA). No cross-reactivity was observed with eight common foodborne pathogens, and both intra- and inter-batch coefficients of variation (CVs) remained below 10%. Recoveries from wood ears, yellow corn flour, and wet rice noodles samples ranged from 83.92% to 113.75%. Moreover, distinct fluorescent signals were generated within 10 min, enabling rapid visual detection. The proposed assay features simple operation, supporting both naked-eye qualitative analysis and instrument-assisted quantitative detection, together with good analytical performance. It provides a practical platform for rapid on-site screening of <i>B. gladioli</i> in high-risk foods and facilitates early food safety risk assessment and intervention.</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":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986499","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":"Two-step Authentication of Argentinian Rice Cultivars by Near-infrared Spectroscopy Combined with One-class and Discriminant Chemometric Methods","authors":"Melisa J. Hidalgo,&nbsp;Michael Pérez-Rodríguez,&nbsp;Pamela M. Dirchwolf,&nbsp;Adriano Araújo Gomes,&nbsp;Héctor C. Goicoechea,&nbsp;Roberto G. Pellerano","doi":"10.1007/s12161-026-03274-7","DOIUrl":"10.1007/s12161-026-03274-7","url":null,"abstract":"<div><p>Authenticity verification of rice cultivars in Argentina is essential for ensuring genetic quality, international competitiveness, and market confidence, especially since the country exports cultivars recognized for their yield and industrial quality. Among the cultivars, IRGA-424 is the most widely cultivated due to its high yield potential and strong disease resistance. This study introduces a fast, and nondestructive strategy to authenticate the IRGA-424 cultivar by combining near-infrared spectroscopy with a two-step chemometric approach (one-class and discriminant methods). A total of 196 rice samples from four cultivars, long-grain rice (IRGA-424, IC-109, and SCS-121) and medium-grain rice (Fortuna), were analyzed. In the first authentication step, one-class models were developed using one-class partial least squares (OC-PLS) and data-driven soft independent modeling of class analogy (DD-SIMCA). Initially, all long-grain cultivars were defined as the target class and medium-grain cultivars as the non-target class. The DD-SIMCA model achieved the best performance, with sensitivity and specificity of 98.2% and 100%, respectively, and accuracy of 98.5%. In a subsequent step, the model was refined by designating IRGA-424 as the target class, enabling its differentiation from the remaining long-grain cultivars. The DD-SIMCA model yielded sensitivity, specificity, and accuracy values of 91.3%, 95.1%, and 94.4%, respectively. In the second step, a support vector machine (SVM) was employed to develop and validate a multiclass model that discriminated IRGA-424 from other long-grain cultivars, achieving 100% classification accuracy. In conclusion, NIR spectroscopy integrated with a two-step chemometric approach provides a powerful tool for authenticating rice cultivars produced in Argentina.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986412","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":"Development and Validation of a Monoclonal Antibody-Based Lateral Flow Immunochromatographic Assay Using Gold Nanoparticles for Rapid Detection of Vibrio vulnificus in Seafood","authors":"Pradit Wangman,&nbsp;Chalinan Pengsuk,&nbsp;Siwaporn Longyant","doi":"10.1007/s12161-026-03266-7","DOIUrl":"10.1007/s12161-026-03266-7","url":null,"abstract":"<div><p><i>Vibrio vulnificus</i> is a highly virulent marine bacterium associated with seafood-borne infections and represents a significant public health concern. Conventional detection methods are often labor-intensive and time-consuming, highlighting the need for a simple, rapid, and reliable detection approach. In this study, we developed a monoclonal antibody-based gold nanoparticle lateral flow immunochromatographic assay (LFIA) for the rapid visual detection of <i>V. vulnificus</i>. Two hybridoma-derived monoclonal antibodies, <i>VV-213</i> and <i>VV-301</i>, were generated and characterized and exhibited different immunoreactivity patterns. These antibodies were integrated into a sandwich-format LFIA, wherein <i>VV-213</i> was employed as the gold-conjugated detection antibody, while <i>VV-301</i> was immobilized on the test line as the capture antibody. The developed assay demonstrated 100% specificity across 20 <i>V</i><i>. vulnificus</i> isolates, with no observed cross-reactivity against other tested <i>Vibrio</i> species or non-<i>Vibrio</i> Gram-negative bacteria. When evaluated directly in application buffer, the analytical detection limit was determined to be 6.25 × 10⁶ CFU/mL. The feasibility of the developed LFIA was evaluated in artificially contaminated oyster homogenates, and the assay achieved a detection limit of 10 CFU/mL following 6 h of pre-enrichment, which was comparable to PCR under similar conditions. Notably, the LFIA yielded visually interpretable results within 15 min, without requiring specialized instrumentation, thereby enhancing its field applicability. Furthermore, the assay remained functional after accelerated aging, indicating an estimated shelf life of at least 2 years under ambient conditions. Overall, these findings suggest that the developed LFIA represents a simple and practical tool for the rapid screening of <i>V. vulnificus</i> in seafood samples and may support routine seafood safety surveillance.</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":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986429","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":"Impact of False Positives, Atypical Strains, and New Listeria Species on Listeria monocytogenes Analysis in Europe: Overview and Perspectives","authors":"Nathalie Gnanou Besse,&nbsp;Alexandre Leclercq,&nbsp;Sylvia Kleta,&nbsp;Catharine Carlin,&nbsp;Bertrand Lombard,&nbsp;Adrien Asséré,&nbsp;Corinne Danan,&nbsp;Léna Barre","doi":"10.1007/s12161-026-03259-6","DOIUrl":"10.1007/s12161-026-03259-6","url":null,"abstract":"<div><p>Listeriosis, one of the most severe foodborne diseases, remains a leading cause for hospitalization and patient mortality. Recent unconfirmed alerts to <i>Listeria monocytogenes</i> in France have shown that the combination of rapid alternative detection or enumeration chromogenic-based methods with simplified verification tests was not adequate to unequivocally diagnose listeriosis, as some non-<i>Listeria</i> microorganisms may adopt a morphology typical of <i>L. monocytogenes</i>. Added to the risk of false negative results due to rare atypical <i>L. monocytogenes</i> strains, finally, the recent expansion of the <i>Listeria</i> genus generated confusion about species relevant for food safety and the scope of analytical methods. The European Union Reference Laboratory (EURL), the French National Reference Laboratory (NRL) for <i>L. monocytogenes</i> and the WHO Collaborating Centre and National Reference Centre for <i>Listeria</i>, decided to conduct an overview of the impact of L. monocytogenes in France and in Europe. In 2025, an enquiry was launched to collect some feedback from the NRLs of the EU Members States and French official control laboratories. The outcome of this survey revealed the need for revision of the scope and some notes of the EN ISO 11290 Standards, as well as the necessity to collect additional information from both official laboratories’ networks and certification agencies overseeing commercial methods. Specifically, it underlined the potential value of introducing new rules in EN ISO 16140-2 standard, such as adding strains’ specific characteristics in the validation studies and including new foods in the categories of food products.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986428","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":"Integrated LC–MS/MS and GC–MS/MS Approach for Multiresidue Pesticide Determination in Fruits and Vegetables","authors":"Aditya Kumar Singh,&nbsp;Naveen Shivanna,&nbsp;Phani Kumar Garlapati,&nbsp;Kumar Ranganathan","doi":"10.1007/s12161-026-03267-6","DOIUrl":"10.1007/s12161-026-03267-6","url":null,"abstract":"<div><p>A validated analytical method was established for quantitative assessment of multiresidue pesticides in tomato utilizing tandem mass spectrometry coupled with liquid chromatography (LC–MS/MS) and gas chromatography (GC–MS/MS) techniques, selected according to their analytical suitability. Sample treatment involved a modified Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) extraction protocol to obtain clean extracts prior to analysis. The developed method exhibited high selectivity and satisfactory linear responses across all analytes, as reflected by coefficients of determination (<i>R</i>²) consistently exceeding 0.99. The method provided satisfactory accuracy, as evidenced by recoveries within 70–120% and acceptable precision, with coefficient of variation (CV) ≤ 20%. For all pesticides included in the study, quantification limits were established at 10 µg/kg. Seven different categories of fruits and vegetables (brinjal, okra, tomato, capsicum, chilli, apple, and guava) were selected to assess the applicability of the developed method. The achieved performance facilitates adherence to acceptable range recommended by the SANTE/11312/2021 guidelines. Overall, the validated procedure showed good sensitivity and reliability, making it suitable for routine surveillance and regulatory enforcement of pesticide residues in fruits and vegetables.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927630","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 Sulfur-Doped Bimetallic Nanozyme for Colorimetric Detection of Chlorogenic Acid in Homologous Medicinal and Edible Plants","authors":"Jiayi Jiang,&nbsp;Yifeng Zhou,&nbsp;Liling Wang","doi":"10.1007/s12161-026-03256-9","DOIUrl":"10.1007/s12161-026-03256-9","url":null,"abstract":"<div><p>Chlorogenic acid (CGA) is a ubiquitous phenolic compound with extensive bioactivity, and is widely distributed in homologous medicinal and edible plants. This study developed a colorimetric detection platform based on a sulfur-doped bimetallic nanozyme (FePd₂S₄) for the detection of CGA in medicinal plants. FePd₂S₄ demonstrates peroxidase-like activity, which enables it to oxidize 3,3′,5,5′-tetramethylbenzidine (TMB) into a blue oxidation product (oxTMB). The introduction of CGA enhances the redox characteristics of the nanozyme, strengthening the blue signal of oxTMB and significantly increasing the corresponding ultraviolet–visible (UV–vis) absorption intensity. Based on this phenomenon, an UV–vis detection model was established for CGA, achieving a linear range of 1–50 μg/mL, with a limit of detection (LOD) of 0.15 μg/mL. To further enhance practicality, a smartphone-integrated colorimetric sensing platform for the detection of CGA was constructed with RGB values by the “Color Grab” application. This model is also applicable to the detection of CGA within the linear range of 1–50 μg/mL, with a LOD of 0.45 μg/mL. Furthermore, the dual-modal detection platform was successfully employed in the actual detection of CGA in herbs. In comparison with the UV–vis detection mode, the smartphone-integrated colorimetric platform presents the advantages of straightforward operation, portability, rapidity, and low cost. This work provides a novel colorimetric approach for utilizing a sulfur-doped bimetallic nanozyme as a precise tool for the detection of CGA, which has a significant potential for application in food quality and pharmaceutical analysis.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927202","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":"Hyperspectral Imaging-Based Adulteration Detection of Edible Oil using Optimized Machine Learning Models","authors":"Muhammad Aqeel,&nbsp;Muhammad Iqbal,&nbsp;Areesha Gull,&nbsp;Khan Bahadar Khan,&nbsp;Yiming Deng","doi":"10.1007/s12161-026-03246-x","DOIUrl":"10.1007/s12161-026-03246-x","url":null,"abstract":"<div><p>Oil adulteration poses a significant risk to public health and compromises food quality and authenticity, necessitating reliable and rapid detection methods. This study proposes a non-destructive method for detecting edible oil adulteration using hyperspectral imaging integrated with spectral feature optimization and machine learning techniques. A total of 480 samples, comprising pure oils (tea tree, rose, turmeric, and rosehip oil) and adulterated variants (orange, vitamin E, lemon, and garlic oil), were analyzed using a Specim FX10 camera system. The Savitzky–Golay filter was used to preprocess spectral data, remove noise, and improve spectral smoothness. The spectral features were then optimized and used to train and test various machine learning models, such as Linear Discriminant Analysis, CatBoost, Gradient Boosting Machine, and Extreme Gradient Boosting Machine. The best-performing model among the evaluated models was the Extreme Gradient Boosting Machine, with 99.98% training accuracy, 98.2% testing and validation accuracy, high precision, recall, F1-score, and balanced accuracy (98.3%), Jaccard Index (96.7%), and low log loss (5%) and Hamming loss (2%). The experimental results point to the usefulness of the proposed method in providing accurate, fast, and non-invasive oil adulteration detection. This study indicates the possibility of using hyperspectral imaging with optimized machine learning algorithms to achieve high food quality measurements and real-time applications in the industrial sector of food safety and quality control.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12161-026-03246-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927188","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":"Caffeine Determination in Coffee Samples by Smartphone Application-Based Thin-Layer Chromatography Combined with Multivariate Image Analysis","authors":"Gabriel Teixeira Malacarne,&nbsp;Bruno Quirino Araújo,&nbsp;Miguel Abner Ferreira de Araújo Almeida,&nbsp;Danieli Grancieri Debona,&nbsp;Eustáquio Vinícius Ribeiro de Castro,&nbsp;Paulo Rogério Garcez de Moura,&nbsp;Paulo Roberto Filgueiras","doi":"10.1007/s12161-026-03233-2","DOIUrl":"10.1007/s12161-026-03233-2","url":null,"abstract":"<div><p>The consumption of caffeine-containing products such as energy drinks, coffee, and tears needs to be regulated due to health risks. Caffeine content is standardized in decaffeinated coffee products, which must comply with a maximum of 0.1 wt%. A thin-layer chromatography (TLC) method and partial least squares regression (PLS) were developed for the quantification of caffeine in decaffeinated coffee and arabica coffee beans. Initially, caffeine standard was evaluated on three elution solvents on TLC analysis. The TLC plates (5 × 20 cm) were placed on UV viewing cabinet at 254 nm and recorded using smartphone camera. TLC plates were eluted using ethyl acetate with 0.1% acetic acid, which presents a retention factor (<i>R</i>_f) of 0.33. Caffeine contents were predicted based on sample spots and standard analytical curve from 0.8 to 7.2 μg band^–1. The region of interest (ROI) from caffeine spots was selected by a free smartphone app, which employs PLS and red-green-blue (RGB) extraction from image for data processing and caffeine content prediction. For caffeine determination in decaffeinated coffee, an extraction with methanol was carried out with spiked samples, and the conformity was evaluated based on a default value. Green and roasted arabica coffee beans had a high value with 2.86 and 2.84 μg of caffeine per band, respectively. The smartphone application-thin layer chromatography (app–TLC) method showed precision and accuracy (coefficient of variation &lt; 3.5%) with an average recuperation of 104%. The app–TLC was useful, fast and precise for the determination of caffeine in coffee products, certification of conformity, and comparable to GC–MS.</p></div>","PeriodicalId":561,"journal":{"name":"Food Analytical Methods","volume":"19 11","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12161-026-03233-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927126","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}