Food Control最新文献_第8页

Post-harvest grain storage: Methods, factors, and eco-friendly solutions

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-17 DOI: 10.1016/j.foodcont.2025.111236

Pagidi Madhukar , Lalit M. Pandey , Uday S. Dixit

{"title":"Post-harvest grain storage: Methods, factors, and eco-friendly solutions","authors":"Pagidi Madhukar , Lalit M. Pandey , Uday S. Dixit","doi":"10.1016/j.foodcont.2025.111236","DOIUrl":"10.1016/j.foodcont.2025.111236","url":null,"abstract":"<div><div>Agriculture contributes about 17˗18 % of India's gross domestic product (GDP). However, infestations (pests including insects and rodents), microbial infections, and mycotoxin formation during the storage process result in a loss of about 10 % of total food grain production in India. This article explains various grain storage techniques, structures (short and long-term storage), traditional methods, and modern techniques' role in developing nations. Different grain storage issues, storage conditions, and physical, biological, and socio-economic factors have been explained. The toxic aflatoxins (AFs), which develop during grain storage and cause various health issues in livestock, are discussed. Advanced storage technologies for real-time monitoring of environmental parameters are summarized. The impact of chemical pesticide usage and the benefits of natural bio-pesticides in grain storage are presented. Natural plant species against major and minor insect pests are highlighted. A decision-making problem is implemented using the analytic hierarchy process (AHP) technique from the available plants in order to identify and use them for effective grain storage. This article provides insights to explore natural resources in the integration of technological interventions i.e. nanotechnology for the sustainable storage of grains. Ultimately, this is expected to enhance food security and human health.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"174 ","pages":"Article 111236"},"PeriodicalIF":5.6,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of epsilon-poly-L-lysine treatment on swelling, microbial growth and physicochemical quality of vacuum-packed lotus root

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-17 DOI: 10.1016/j.foodcont.2025.111238

Qianlong Shi , Yixuan Wang , Cong Han , Xingfeng Guo , Maorun Fu , Subo Tian , Xiaofei Xin

{"title":"Effect of epsilon-poly-L-lysine treatment on swelling, microbial growth and physicochemical quality of vacuum-packed lotus root","authors":"Qianlong Shi , Yixuan Wang , Cong Han , Xingfeng Guo , Maorun Fu , Subo Tian , Xiaofei Xin","doi":"10.1016/j.foodcont.2025.111238","DOIUrl":"10.1016/j.foodcont.2025.111238","url":null,"abstract":"<div><div>Vacuum-packed lotus roots are prone to swelling and quality deterioration when stored at temperatures above 15 °C. Our study aimed to investigate the impacts of ε-poly-L-lysine (ε-PL) application (0.35 and 0.7 g/L) on swelling, microbial proliferation and quality characteristics of vacuum-packed lotus roots stored at 25 °C for 15 d. Through 16S rDNA amplicon sequencing, the primary bacterial genera responsible for bag swelling were identified as <em>Enterobacter</em>, <em>Klebsiella</em>, and <em>Pantoea</em>. The treatment with 0.7 g/L ε-PL exhibited the strongest inhibitory effect on these genera, effectively preventing swelling. Additionally, ε-PL treatment inhibited browning, suppressed the increase in total acid content, and maintained the levels of soluble sugars, total phenolics, and ascorbic acid. ε-PL assisted in retaining the flavor profile of lotus roots. These findings suggested that ε-PL was effective in preventing swelling, inhibiting microbial growth, and maintaining storage quality in vacuum-packed lotus roots.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"173 ","pages":"Article 111238"},"PeriodicalIF":5.6,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting cadmium accumulation in carrot (Daucus carota L.) using reflectance spectroscopy and machine learning

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-15 DOI: 10.1016/j.foodcont.2025.111226

Ninon Maugeais, Guillaume Lassalle

{"title":"Predicting cadmium accumulation in carrot (Daucus carota L.) using reflectance spectroscopy and machine learning","authors":"Ninon Maugeais, Guillaume Lassalle","doi":"10.1016/j.foodcont.2025.111226","DOIUrl":"10.1016/j.foodcont.2025.111226","url":null,"abstract":"<div><div>Agricultural commodities such as root vegetables are subject to strict regulations regarding Trace Metal Elements (TME) for food safety reasons. Assessing the compliance of these commodities with authorized limits is usually achieved through costly and time-demanding traditional analytical techniques. As an alternative, we propose a new, rapid-and-scalable approach based on reflectance spectroscopy to assess TME content in root vegetables. The latter relies on exploiting the reflectance spectra of root samples to predict either the absolute concentration of TMEs or their compliance with a certain threshold using machine learning regression and classification. Our approach was successfully applied to predicting cadmium accumulation in the roots of two carrot varieties under controlled conditions, achieving up to 95% accuracy by exploiting the reflectance of root cross-sections (<em>R</em><sup>2</sup> = 0.95 and F1-score ≥0.96 in regression and classification, respectively). We also explored non-destructive models using either carrot leaves or unpeeled roots, which achieved moderate to high accuracy for the prediction of root cadmium, respectively (0.48 < <em>R</em><sup>2</sup> < 0.87 and 64 < F1-score <90). Our models showed consistent accuracy against varying cadmium limits and allowed identifying wavelengths in the visible and short-wave infrared regions of the spectrum as main contributors of predictions. Our study thus opens encouraging perspectives to assess TME compliance in agricultural commodities, from the field to harvest.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"173 ","pages":"Article 111226"},"PeriodicalIF":5.6,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-destructive pre-incubation sex determination in chicken eggs using hyperspectral imaging and machine learning

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-15 DOI: 10.1016/j.foodcont.2025.111233

Md Wadud Ahmed , Asher Sprigler , Jason Lee Emmert , Mohammed Kamruzzaman

{"title":"Non-destructive pre-incubation sex determination in chicken eggs using hyperspectral imaging and machine learning","authors":"Md Wadud Ahmed , Asher Sprigler , Jason Lee Emmert , Mohammed Kamruzzaman","doi":"10.1016/j.foodcont.2025.111233","DOIUrl":"10.1016/j.foodcont.2025.111233","url":null,"abstract":"<div><div>Non-destructive sex determination in eggs can enhance animal welfare, improve economic efficiency, reduce environmental impact, and foster technological innovation in sustainable hatchery operations. This study investigates the effectiveness of non-destructive hyperspectral imaging (HSI) and machine learning for pre-incubation sex prediction in chicken eggs. Multiple classification models such as partial least squares discriminant analysis (PLS-DA), Extreme Gradient Boosting (XGBoost), random forest (RF), and Categorical Boosting (CatBoost) were developed across full wavelengths (452–899 nm) and evaluated through external validation. Multiple spectral pre-processing, such as standard normal variate (SNV), multiplicative scatter correction (MSC), and Savitzky-Golay (SG) were assessed for calibration model development. Further, important feature selection and model optimization techniques were evaluated for robust prediction model development. Using 35 important features, the CatBoost model with SG pre-processed spectra achieved the best performance, with an accuracy of 82.9% on the calibration set and 75.5% on the validation set. The study demonstrated the potential of HSI and advanced machine learning to revolutionize sex prediction in chicken eggs before incubation, offering a non-invasive, precise, and efficient solution for the next-generation poultry industry.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"173 ","pages":"Article 111233"},"PeriodicalIF":5.6,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Climate-sensitive biological and chemical preharvest food safety hazards in Canadian agriculture: A scoping review

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-14 DOI: 10.1016/j.foodcont.2025.111225

Brenda Zai , Shefali Panicker , Victoria Ng , Andrew Papadopoulos , Ian Young , Lauren E. Grant

{"title":"Climate-sensitive biological and chemical preharvest food safety hazards in Canadian agriculture: A scoping review","authors":"Brenda Zai , Shefali Panicker , Victoria Ng , Andrew Papadopoulos , Ian Young , Lauren E. Grant","doi":"10.1016/j.foodcont.2025.111225","DOIUrl":"10.1016/j.foodcont.2025.111225","url":null,"abstract":"<div><div>Climate change poses risks to food safety at the preharvest level. Synthesized high-quality evidence on the impacts of meteorological variables —temperature, precipitation, humidity, and extreme weather—on food contamination is essential for informing food safety policy and interventions. This scoping review aimed to synthesize peer-reviewed and grey literature on these effects and identify knowledge gaps. Using a registered <em>a priori</em> protocol, searches were conducted in MEDLINE via Ovid, Web of Science, AGRICOLA, and CAB International and grey literature sources. Two independent reviewers conducted a two-phase screening process on retrieved literature to identify eligible studies that examined meteorological variable impacts on preharvest food contamination specifically in Canada, the United States, or Europe. A total of 45 studies were included, with data extracted and synthesized. This review identified the impacts of meteorological variables on food safety hazards in grains (16/45), livestock (12/45), produce (10/45), and irrigation water (8/45). In grains, changes in precipitation, temperature, and humidity were strongly interconnected and linked with increased mycotoxin contamination. Seasonal changes and higher temperatures elevated biological hazards among livestock. Produce contamination, notably in leafy green vegetables, increased with higher temperatures, precipitation, and flood events. Irrigation water sources demonstrated increased contamination following increased precipitation, primarily. These findings highlight the critical influence of meteorological variables on preharvest food safety, underscoring the need for targeted mitigation and adaptation strategies to safeguard food systems in the face of climate change.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"174 ","pages":"Article 111225"},"PeriodicalIF":5.6,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143478837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stepwise strategy based on untargeted metabolomic 1H NMR fingerprinting and pattern recognition for the geographical authentication of virgin olive oils

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-13 DOI: 10.1016/j.foodcont.2025.111216

Rosa María Alonso-Salces , Gabriela Elena Viacava , Alba Tres , Stefania Vichi , Enrico Valli , Alessandra Bendini , Tullia Gallina Toschi , Blanca Gallo , Luis Ángel Berrueta , Károly Héberger

{"title":"Stepwise strategy based on untargeted metabolomic 1H NMR fingerprinting and pattern recognition for the geographical authentication of virgin olive oils","authors":"Rosa María Alonso-Salces , Gabriela Elena Viacava , Alba Tres , Stefania Vichi , Enrico Valli , Alessandra Bendini , Tullia Gallina Toschi , Blanca Gallo , Luis Ángel Berrueta , Károly Héberger","doi":"10.1016/j.foodcont.2025.111216","DOIUrl":"10.1016/j.foodcont.2025.111216","url":null,"abstract":"<div><div><sup>1</sup>H NMR fingerprinting of virgin olive oils (VOOs) and a collection of binary classification models arranged in a decision tree are presented as a stepwise strategy to determine the geographical origin of a VOO at four levels, i.e. provenance from an EU member state or outside the EU, country and region of origin, and compliance with a geographical indication scheme. This approach supports current EU regulation that makes labelling of the geographical origin mandatory for olive oil. Currently, official methods for its control are still lacking. Partial least squares discriminant analysis (PLS-DA) and random forest for classification afforded robust and stable binary classification models to verify the geographical origin of VOOs; however, the former outperformed the latter in terms of accuracy and robustness. The prediction abilities of the best binary PLS-DA model for each case study were between 80% and 100% for both classes in cross-validation and in external validation. The satisfactory results achieved for the verification of the geographical origin of VOOs, together with those of our previous studies on the discrimination of olive oil categories, the detection of olive oils blended with vegetable oils (Alonso-Salces et al., 2022), and the determination of the stability, freshness, storage time and conditions, and olive oil best−before date (Alonso-Salces et al., 2021), confirm that a single <sup>1</sup>H NMR analysis of an olive oil sample can provide useful information to control several EU regulations related to olive oil marketing standards (Regulation (EU) 2022/2104 and Regulation (EU) 2024/1143).</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"173 ","pages":"Article 111216"},"PeriodicalIF":5.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Combining deep convolutional generative adversarial networks with visible-near infrared hyperspectral reflectance to improve prediction accuracy of anthocyanin content in rice seeds

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-13 DOI: 10.1016/j.foodcont.2025.111218

Xingsheng Bao , Deyao Huang , Biyun Yang , Jiayi Li , Atoba Tolulope Opeyemi , Renye Wu , Haiyong weng , Zuxin Cheng

{"title":"Combining deep convolutional generative adversarial networks with visible-near infrared hyperspectral reflectance to improve prediction accuracy of anthocyanin content in rice seeds","authors":"Xingsheng Bao , Deyao Huang , Biyun Yang , Jiayi Li , Atoba Tolulope Opeyemi , Renye Wu , Haiyong weng , Zuxin Cheng","doi":"10.1016/j.foodcont.2025.111218","DOIUrl":"10.1016/j.foodcont.2025.111218","url":null,"abstract":"<div><div>Anthocyanin is a crucial reference indicator for evaluating the quality of rice varieties, making it significant to rapidly establish a non-destructive detection method for anthocyanin in rice grains. This study constructs a 1D-DCGAN (One-dimensional deep convolutional generative adversarial network) strategy optimized for one dimensional spectral data and a 1D-CNN (One-dimensional convolutional neural network) model, achieving high-quality generated sample effects and more accurate anthocyanin predictions within a limited dataset. The <span>SG</span> (Savitzky-Golay)-1D-CNN significantly outperforms LSR (Least squares regression), SVM (Support vector machine) and BPNN (Backpropagation neural network) in the test set, with R<sup>2</sup> (Determination coefficient), RMSE (Root mean square error) and RPD (Residual predictive deviation) values of 0.83, 10.99, and 2.45, respectively. Furthermore, using DCGAN-generated samples to train the SG-1D-CNN by adding a certain number of generated samples can enhance the model's performance in the test set. When the number of added samples is 60 (75% of the original training set sample size), the SG-DCGAN-1D-CNN (Savitzky-Golay deep convolutional generative adversarial network one dimensional convolutional neural network) exhibits the best performance, with R<sup>2</sup>, RMSE, and RPD reaching 0.87, 9.40, and 2.88, respectively. The DCGAN-1D-CNN (Deep convolutional generative adversarial network one dimensional convolutional neural network) method based on this strategy is expected to provide new insights into precise prediction for multi-variety rice seeds.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"174 ","pages":"Article 111218"},"PeriodicalIF":5.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Thermal stability of deoxynivalenol, zearalenone, and their modified forms during baking in oat biscuits

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-13 DOI: 10.1016/j.foodcont.2025.111223

Irene Teixido-Orries, Francisco Molino, Ángel Aragonés-Millán, Antonio J. Ramos, Sonia Marín

{"title":"Thermal stability of deoxynivalenol, zearalenone, and their modified forms during baking in oat biscuits","authors":"Irene Teixido-Orries, Francisco Molino, Ángel Aragonés-Millán, Antonio J. Ramos, Sonia Marín","doi":"10.1016/j.foodcont.2025.111223","DOIUrl":"10.1016/j.foodcont.2025.111223","url":null,"abstract":"<div><div>The present study aimed to investigate the effects of the baking process on some <em>Fusarium</em> mycotoxins (deoxynivalenol (DON), zearalenone (ZEN), T-2 and HT-2 toxins) and their modified forms (deoxynivalenol-3-glucoside (DON-3G), 15-acetyldeoxynivalenol (15-ADON), 3-acetyldeoxynivalenol (3-ADON), deepoxy-deoxynivalenol (DOM-1), α-zearalenol (α-ZEL), and β-zearalenol (β-ZEL)) in oat biscuits. Their content was analysed using HPLC-DAD and UHPLC-MS/MS to evaluate the impact of temperature, time and initial mycotoxin concentration. Also, metabolite screening (sulphated ZEN metabolites, isoDON and norDONs) was performed to provide new insights into the baking effect on mycotoxins. Results indicated that mycotoxin reduction depended significantly on baking temperature and duration. ZEN exhibited higher thermostability than DON-3G, and DON-3G was more thermostable than DON. Under harsh conditions, 15-ADON decreased while DOM-1 increased. isoDON and norDONs emerged during baking. Initial baking phases showed increased levels of ZEN, α-zearalenol-14-S (α-ZEL-14-S) and β-zearalenol-14-S (β-ZEL-14-S) due to the release of hidden mycotoxins, raising safety concerns. T-2 and HT-2 toxins were not found in any oat-based product. The final edible biscuits for each temperature exhibited similar DON and DON-3G concentrations, with higher ZEN levels than initially. Degradation kinetic analysis revealed zero-order kinetics for DON and DON-3G and first-order kinetics for ZEN, offering a predictive tool for mycotoxin levels in biscuits.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"173 ","pages":"Article 111223"},"PeriodicalIF":5.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Direct visual detection for methicillin-resistant Staphylococcus aureus in milk based on the RPA-Cas12a-LFS method

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-13 DOI: 10.1016/j.foodcont.2025.111209

Yixiang Sun , Liren Zhang , Huimin Wu , Hongjun Chen , Huijie Hu , Chongyu Zhang , Xiaoqiang Li , Yuan Li , Yimai Wang , Liqiang Luo , Yizhi Song

{"title":"Direct visual detection for methicillin-resistant Staphylococcus aureus in milk based on the RPA-Cas12a-LFS method","authors":"Yixiang Sun , Liren Zhang , Huimin Wu , Hongjun Chen , Huijie Hu , Chongyu Zhang , Xiaoqiang Li , Yuan Li , Yimai Wang , Liqiang Luo , Yizhi Song","doi":"10.1016/j.foodcont.2025.111209","DOIUrl":"10.1016/j.foodcont.2025.111209","url":null,"abstract":"<div><div>Methicillin-resistant <em>Staphylococcus aureus</em> (MRSA) has emerged as a significant pathogen of global concern, presenting substantial public health risks through foodborne transmission and contributing to elevated morbidity and mortality rates worldwide. The critical need for precise and timely identification of MRSA in food matrices has become increasingly paramount for effective public health protection. While numerous CRISPR-based detection platforms for MRSA have been recently developed, their widespread implementation has been hindered by intricate multi-step protocols and dependency on sophisticated instrumentation. In this study, we developed a direct, accurate and visual detection method for MRSA — the RPA-Cas12a-LFS method. This method comprises two main components: (1) the direct one-pot RPA-Cas12a system, which integrates bacterial lysis, RPA nucleic acid amplification, and CRISPR-Cas12a nucleic acid detection into a single step performed simultaneously at a constant temperature, and (2) the streptavidin-gold nanoparticles (SA-AuNP)-based CRISPR-specific lateral flow strip (LFS). By eliminating the need for nucleic acid extraction, this method significantly simplifies the experimental procedure and reduces the risk of cross-contamination. Through systematic optimization, this method demonstrated exceptional performance, enabling direct and specific identification of MRSA at remarkably low concentrations (10 CFU/mL) within 60 min in various milk samples. This advanced detection method, characterized by its direct sample processing, exceptional accuracy, visual interpretability, cost-efficiency, and minimal equipment requirements, is particularly suitable for on-site and real-time monitoring of pathogenic bacteria in the food industry.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"173 ","pages":"Article 111209"},"PeriodicalIF":5.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel cascaded reflective temperature-independent fiber-optic biosensor for trace vanillin concentration detection enhanced specificity with molecularly imprinted polymer

IF 5.6 1区农林科学

Food Control Pub Date : 2025-02-12 DOI: 10.1016/j.foodcont.2025.111217

Dandan Sun , Ze Xu , Li Jin , Bowen Yang , Wenwen Wang , Yukun Yang , Jie Ma

{"title":"A novel cascaded reflective temperature-independent fiber-optic biosensor for trace vanillin concentration detection enhanced specificity with molecularly imprinted polymer","authors":"Dandan Sun , Ze Xu , Li Jin , Bowen Yang , Wenwen Wang , Yukun Yang , Jie Ma","doi":"10.1016/j.foodcont.2025.111217","DOIUrl":"10.1016/j.foodcont.2025.111217","url":null,"abstract":"<div><div>A cascade structured reflective sensor consisting of a microfiber interferometer (MFI) and a gold-coated tilted fiber Bragg grating (TFBG) is proposed. A molecularly imprinted polymers (MIPs) specific recognition layer is coated on the MFI surface with pore sites complementary in shape and size to vanillin (VA), which in turn enables the trapping of VA, causing a change in the refractive index of the MFI surface. This process can be translated into a change in intensity difference. The sensor is capable of detecting VA in the range of 0.1–200 μM with a sensitivity of 2.58 dB/(μM) and a detection limit of 0.07 μM. The proposed sensor utilizes a sensitivity matrix that can eliminate temperature cross-sensitivity. Further the performance validation shows that the sensor has high selectivity. The recoveries in real sample detection ranged from 92 to 118%, which demonstrates its high accuracy and reliability in practical applications. Therefore, this new cascade structure reflectance sensor provides an efficient and reliable tool for the detection of VA in the food industry, which is of great significance for food safety and quality control.</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"173 ","pages":"Article 111217"},"PeriodicalIF":5.6,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0