1
|
Wan F, Li S, Lei Y, Wang M, Liu R, Hu K, Xia Y, Chen W. Two-step machine learning-assisted label-free surface-enhanced Raman spectroscopy for reliable prediction of dissolved furfural in transformer oil. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 321:124571. [PMID: 38950473 DOI: 10.1016/j.saa.2024.124571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 04/28/2024] [Accepted: 05/29/2024] [Indexed: 07/03/2024]
Abstract
Accurate detection of dissolved furfural in transformer oil is crucial for real-time monitoring of the aging state of transformer oil-paper insulation. While label-free surface-enhanced Raman spectroscopy (SERS) has demonstrated high sensitivity for dissolved furfural in transformer oil, challenges persist due to poor substrate consistency and low quantitative reliability. Herein, machine learning (ML) algorithms were employed in both substrate fabrication and spectral analysis of label-free SERS. Initially, a high-consistency Ag@Au substrate was prepared through a combination of experiments, particle swarm optimization-neural network (PSO-NN), and a hybrid strategy of particle swarm optimization and genetic algorithm (Hybrid PSO-GA). Notably, a two-step ML framework was proposed, whose operational mechanism is classification followed by quantification. The framework adopts a hierarchical modeling strategy, incorporating simple algorithms such as kernel support vector machine (Kernel-SVM), k-nearest neighbors (KNN), etc., to independently establish lightweight regression models on each cluster, which allows each model to focus more effectively on fitting the data within its cluster. The classification model achieved an accuracy of 100%, while the regression models exhibited an average correlation coefficient (R2) of 0.9953 and the root mean square errors (RMSE) consistently below 10-2. Thus, this ML framework emerges as a rapid and reliable method for detecting dissolved furfural in transformer oil, even in the presence of different interfering substances, which may also have potentiality for other complex mixture monitoring systems.
Collapse
Affiliation(s)
- Fu Wan
- State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China; National Innovation Center for Industry-Education Integration of Energy Storage Technology, School of Electrical Engineering, Chongqing University, Chongqing, 400044, China.
| | - Shufan Li
- State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Yu Lei
- State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Mingliang Wang
- State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Ruiqi Liu
- State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Kaida Hu
- State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Yaoyang Xia
- State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China
| | - Weigen Chen
- State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China; National Innovation Center for Industry-Education Integration of Energy Storage Technology, School of Electrical Engineering, Chongqing University, Chongqing, 400044, China
| |
Collapse
|
2
|
Song G, Li C, Fauconnier ML, Zhang D, Gu M, Chen L, Lin Y, Wang S, Zheng X. Research progress of chilled meat freshness detection based on nanozyme sensing systems. Food Chem X 2024; 22:101364. [PMID: 38623515 PMCID: PMC11016872 DOI: 10.1016/j.fochx.2024.101364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 03/22/2024] [Accepted: 04/05/2024] [Indexed: 04/17/2024] Open
Abstract
It is important to develop rapid, accurate, and portable technologies for detecting the freshness of chilled meat to meet the current demands of meat industry. This report introduces freshness indicators for monitoring the freshness changes of chilled meat, and systematically analyzes the current status of existing detection technologies which focus on the feasibility of using nanozyme for meat freshness sensing detection. Furthermore, it examines the limitations and foresees the future development trends of utilizing current nanozyme sensing systems in evaluating chilled meat freshness. Harmful chemicals are produced by food spoilage degradation, including biogenic amines, volatile amines, hydrogen sulfide, and xanthine, which have become new freshness indicators to evaluate the freshness of chilled meat. The recognition mechanisms are clarified based on the special chemical reaction with nanozyme or directly inducting the enzyme-like catalytic activity of nanozyme.
Collapse
Affiliation(s)
- Guangchun Song
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
- Laboratory of Chemistry of Natural Molecules, Gembloux Agro-Bio Tech, University of Liege, Passage des déportés 2, B-5030 Gembloux, Belgium
| | - Cheng Li
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
| | - Marie-Laure Fauconnier
- Laboratory of Chemistry of Natural Molecules, Gembloux Agro-Bio Tech, University of Liege, Passage des déportés 2, B-5030 Gembloux, Belgium
| | - Dequan Zhang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
| | - Minghui Gu
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
| | - Li Chen
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
| | - Yaoxin Lin
- National Center for Nanoscience and Technology, Beijing, 100081, China
| | - Songlei Wang
- Department of Food Science and Technology, Ningxia University, Yinchuan 750021, China
| | - Xiaochun Zheng
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
| |
Collapse
|
3
|
Rodríguez‐Sevilla E, Álvarez‐Martínez JU, Castro‐Beltrán R, Morales‐Narváez E. Flexible 3D Plasmonic Web Enables Remote Surface Enhanced Raman Spectroscopy. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2402192. [PMID: 38582528 PMCID: PMC11187956 DOI: 10.1002/advs.202402192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 03/19/2024] [Indexed: 04/08/2024]
Abstract
Nanoplasmonic materials concentrate light in specific regions of dramatic electromagnetic enhancement: hot spots. Such regions can be employed to perform single molecule detection via surface-enhanced Raman spectroscopy. However, this phenomenon is challenging since hot spots are expected to be highly intense/abundant and positioning of molecules within such hot spots is crucial to manage with ultrasensitive SERS. Herein, it is discovered that a 3D plasmonic web embedded within a biohybrid (3D-POWER) exhibits plasmonic transmission, spontaneously absorbs the analyte, and meets these so much needed criteria in ultrasensitive SERS. 3D-POWER is built with nanopaper and self-assembled layers of graphene oxide and gold nanorods. According to in silico experiments, 3D-POWER captures light in a small region and performs plasmonic field transmission in a surrounding volume, thereby activating a plasmonic web throughout the simulated volume. The study also provides experimental evidence supporting the plasmonic field transport ability of 3D power, which operates as a SERS signal carrier (even beyond the apparatus field of view), and the ultrasensitive behavior of this ecofriendly and flexible material facilitating yoctomolar limit of detection. Besides, 3D-POWER is proven useful in food and biofluids analysis. It is foreseen that 3D-POWER can be employed as a valuable platform in (bio)analytical applications.
Collapse
Affiliation(s)
- Erika Rodríguez‐Sevilla
- Centro de Investigaciones en Óptica A. C.Loma del Bosque 115, Lomas del CampestreLeónGuanajuato37150México
| | - Jonathan Ulises Álvarez‐Martínez
- Departamento de Ingeniería FísicaDivisión de Ciencias e IngenieríasUniversidad de GuanajuatoLoma del Bosque 103, Lomas del CampestreLeónGuanajuato37150México
| | - Rigoberto Castro‐Beltrán
- Departamento de Ingeniería FísicaDivisión de Ciencias e IngenieríasUniversidad de GuanajuatoLoma del Bosque 103, Lomas del CampestreLeónGuanajuato37150México
| | - Eden Morales‐Narváez
- Biophotonic Nanosensors LaboratoryCentro de Física Aplicada y Tecnología Avanzada (CFATA)Universidad Nacional Autónoma de México (UNAM)Boulevard Juriquilla 3001Querétaro76230México
| |
Collapse
|
4
|
Rong L, Wang Y, Wang Y, Jiang D, Bai J, Wu Z, Li L, Wang T, Tan H. A fresh-cut papaya freshness prediction model based on partial least squares regression and support vector machine regression. Heliyon 2024; 10:e30255. [PMID: 38707326 PMCID: PMC11068816 DOI: 10.1016/j.heliyon.2024.e30255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 04/19/2024] [Accepted: 04/23/2024] [Indexed: 05/07/2024] Open
Abstract
This study investigated the physicochemical and flavor quality changes in fresh-cut papaya that was stored at 4 °C. Multivariate statistical analysis was used to evaluate the freshness of fresh-cut papaya. Aerobic plate counts were selected as a predictor of freshness of fresh-cut papaya, and a prediction model for freshness was established using partial least squares regression (PLSR), and support vector machine regression (SVMR) algorithms. Freshness of fresh-cut papaya could be well distinguished based on physicochemical and flavor quality analyses. The aerobic plate counts, as a predictor of freshness of fresh-cut papaya, significantly correlated with storage time. The SVMR model had a higher prediction accuracy than the PLSR model. Combining flavor quality with multivariate statistical analysis can be effectively used for evaluating the freshness of fresh-cut papaya.
Collapse
Affiliation(s)
- Liyan Rong
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning 110866, China
| | - Yajing Wang
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning 110866, China
| | - Yanqun Wang
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning 110866, China
| | - Donghua Jiang
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning 110866, China
| | - Jinrong Bai
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning 110866, China
| | - Zhaoxia Wu
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning 110866, China
| | - Lu Li
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning 110866, China
| | - Tianyu Wang
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning 110866, China
| | - Hui Tan
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning 110866, China
| |
Collapse
|
5
|
Lu X, Ma Y, Jiang S, Wang Z, Yu Q, Ji C, Guo J, Kong X. Quantitative monitoring ofloxacin in beef by TLC-SERS combined with machine learning analysis. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 308:123790. [PMID: 38142496 DOI: 10.1016/j.saa.2023.123790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/03/2023] [Accepted: 12/16/2023] [Indexed: 12/26/2023]
Abstract
Ofloxacin is one kind of quinolone antibiotic drugs, the abuse of ofloxacin in livestock and aquaculture may bring bacterial resistance and healthy problem of people. The illegally feeding cattle with ofloxacin will help it keep health, but the sedimentation of ofloxacin could bring problem in food safety. The accurate, simple and instant monitoring ofloxacin from beef by portable sensor was of vital issue in food quality. A simple and reliable method was proposed for instant and quantitative detecting ofloxacin in beef, in which the thin-layer chromatography (TLC) -surface-enhanced Raman scattering (SERS) spectroscopy was in tandem with machine learning analysis base one principal component analysis-back propagation neural network (PCA-BPNN). The TLC plate was composed with diatomite, that was function as the stationary phase to separate ofloxacin from beef. The real beef juice was directly casted onto the diatomite plate for separating and detecting. The directly monitor ofloxacin from beef was achieved and the sensitivity down to 0.01 ppm. The PCA-BPNN was used as reliable model for quantitative predict the concentration of ofloxacin, that shown superior accuracy compared with the traditional model. The results verify that the diatomite plate TLC-SERS combined with machine-learning analysis is an effective, simple and accurate technique for detecting and quantifying antibiotic drug in meat stuff to improve the food safety.
Collapse
Affiliation(s)
- Xiaoqi Lu
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China
| | - Yidan Ma
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China; International Education College, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China
| | - Shangkun Jiang
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China
| | - Zice Wang
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China; International Education College, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China
| | - Qian Yu
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China
| | - Chengcheng Ji
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China; Engineering Training Centre, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China.
| | - Jiaqi Guo
- Jiangsu Co-Innovation Center for Efficient Processing and Utilization of Forest Resources and Joint International Research Lab of Lignocellulosic Functional Materials, Nanjing Forestry University, Nanjing 210037, PR China
| | - Xianming Kong
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China; International Education College, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China.
| |
Collapse
|
6
|
Ding Y, Liu C, Shi Y, Wang LX, Mao ZS, Sun H, Wan H, Chen F, Cao Y. Dual-Mode Separation and SERS Detection of Carbaryl with PA-6/AuNRs@ZIF-8 Films. Anal Chem 2024; 96:1941-1947. [PMID: 38279956 DOI: 10.1021/acs.analchem.3c04090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2024]
Abstract
Appropriate separation and enrichment steps can enhance the performance of SERS assays. For rapid, in-situ detection of carbaryl, a novel PA-6/AuNRs@ZIF-8 film that can be applied to dual-mode separation and SERS detection, has been developed. In the film, PA-6 was used as a TLC substrate for the initial separation of the substance to be measured. ZIF-8 provides chemical enhancement in SERS as well as enrichment and secondary separation of the analytes. Utilizing this film, we have successfully implemented a TLC-SERS rapid detection scheme, resulting in a detection limit for carbaryl as low as 1 × 10-9 M in lake water in 15 min, which is significantly lower than existing standards. Additionally, the manufacturing cost of one PA-6/AuNRs@ZIF-8 film can be kept within the range of $0.20-$0.40 economically, presenting substantial financial advantages. The method is highly promising for pesticide detection as well as forensic in-situ testing.
Collapse
Affiliation(s)
- Yan Ding
- Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, P.R. China
| | - Cheng Liu
- Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, P.R. China
| | - Yang Shi
- School of Pharmacy, Nanjing Medical University, Nanjing 211166, China
| | - Li-Xiang Wang
- Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, P.R. China
| | - Zheng-Sheng Mao
- Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, P.R. China
| | - Hao Sun
- Department of Emergency Medicine. The First Affiliated Hospital of Nanjing Medical University, Nanjing 211166, China
| | - Hua Wan
- Department of Health Management, Sir Run Run Hospital, Nanjing Medical University, Nanjing 211166, China
| | - Feng Chen
- Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, P.R. China
| | - Yue Cao
- Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, P.R. China
| |
Collapse
|
7
|
Pan Y, Xu S, Wang Z, Jiang C, Ma X. Sensitive SERS aptasensor for histamine detection based on Au/Ag nanorods and IRMOF-3@Au based flexible PDMS membrane. Anal Chim Acta 2024; 1288:342147. [PMID: 38220281 DOI: 10.1016/j.aca.2023.342147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 11/26/2023] [Accepted: 12/15/2023] [Indexed: 01/16/2024]
Abstract
BACKGROUND Histamine is a kind of biogenic amine with strong toxicity and potential carcinogenicity. Many traditional methods of detecting histamine have the disadvantages of cumbersome detection steps, expensive equipment, and high professional requirements for staff. In contrast, SERS has become the preferred method for quantitative analysis of histamine because of rich fingerprint information, rapidity and economy. However, most of SERS substrates still have technical problems, such as poor stability, low sample collection rate, and detection efficiency. Therefore, there is a great need for new strategies to develop high-performance SERS substrates based sensors. RESULTS In our study, a sensitive SERS aptasensor for the detection of histamine was synthesized. The assembly was formed between IRMOF-3@Au/PDMS (flexible SERS substrate) and AuNR-DTNB@Ag-HA apt (Raman signal probe with both the target capture ability) via π-π stacking interaction from HA aptamer and IRMOF-3. Consequently, the SERS signal of the assembly derived from DTNB reached highest due to the synergistic enhancement effect by AuNR@Ag and IRMOF-3@Au. Meanwhile, HA aptamer can specifically capture histamine, therefore histamine addition competitively bound to the probe, leading to a corresponding decrease in the DTNB signal value on the SERS substrate. The SERS intensity at 1331 cm-1 presented a good linear relationship towards the logarithmic value of histamine concentrations ranging from 0.0001 mg/L to 400 mg/L (R2 = 0.990) with the LOD of 3.6 × 10-5 mg/L. Furthermore, the application in wine samples demonstrated the accuracy and applicability of the developed sensor. SIGNIFICANCE This method effectively improves substrate stability, detection sensitivity and signal response immediacy to amplify the SERS sensor, thus satisfying the histamine detection requirements of various systems. According to this aptasensor design, our strategy can be extended to create other MOF-based SERS substrates for accurately detecting relative targets to ensure food safety.
Collapse
Affiliation(s)
- Yue Pan
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, 214122, China; School of Food Science and Technology, Jiangnan University, Wuxi, 214122, China; International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, 214122, China
| | - Shan Xu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, 214122, China; School of Food Science and Technology, Jiangnan University, Wuxi, 214122, China; International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, 214122, China
| | - Zhouping Wang
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, 214122, China; School of Food Science and Technology, Jiangnan University, Wuxi, 214122, China; International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, 214122, China
| | - Caiyun Jiang
- Department of Health, Jiangsu Engineering and Research Center of Food Safety, Jiangsu Vocational Institute of Commerce, Nanjing, 211168, China
| | - Xiaoyuan Ma
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, 214122, China; School of Food Science and Technology, Jiangnan University, Wuxi, 214122, China; International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, 214122, China.
| |
Collapse
|
8
|
Zhang B, Zhang J, Lang Y, Wang Z, Cai D, Yu X, Lin X. A sea urchin-shaped nanozyme mediated dual-mode immunoassay nanoplatform for sensitive point-of-care testing histamine in food samples. Food Chem 2024; 433:137281. [PMID: 37659293 DOI: 10.1016/j.foodchem.2023.137281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 08/21/2023] [Accepted: 08/23/2023] [Indexed: 09/04/2023]
Abstract
Rapid detection of histamine remains a challenge due to the complexity of food matrices. Based on the high peroxidase-like activity of sea urchin-shaped Pt@Au NPs (SU-Pt@Au NPs), a novel dual-mode nanoplatform is developed for the sensitive detection of histamine utilizing an indirect competitive enzyme-linked immunosorbent assay. According to the colorimetric-based UV-vis nanoplatform, histamine is sensitively detected with a liner range from 0.5 to 100 ng/mL and a limit of detection (LOD) as low as 0.3 ng/mL. Then, a smartphone-loaded color picker APP can intelligently detect histamine in point-of-care testing (POCT) based on the R/B ratio of the color channels, with a detection range of 0.5 to 1000 ng/mL and a LOD as low as 0.15 ng/mL, significantly expanding the detection range. Such an easy-to-use and sensitive detection system is employed to quantify histamine in Pacific saury, crab, and pork samples, indicating outstanding application potential in protein-rich meat food safety.
Collapse
Affiliation(s)
- Biao Zhang
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou 310018, China
| | - Jingyi Zhang
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou 310018, China
| | - Yihan Lang
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou 310018, China
| | - Zicheng Wang
- Tianjin Sprite Biological Technology, Tianjin 300021, China
| | - Danfeng Cai
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou 310018, China
| | - Xiaoping Yu
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou 310018, China
| | - Xiaodong Lin
- Zhuhai UM Science & Technology Research Institute, Zhuhai 519000, China.
| |
Collapse
|
9
|
Gabbitas A, Ahlborn G, Allen K, Pang S. Advancing Mycotoxin Detection: Multivariate Rapid Analysis on Corn Using Surface Enhanced Raman Spectroscopy (SERS). Toxins (Basel) 2023; 15:610. [PMID: 37888641 PMCID: PMC10610586 DOI: 10.3390/toxins15100610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 10/08/2023] [Indexed: 10/28/2023] Open
Abstract
Mycotoxin contamination on food and feed can have deleterious effect on human and animal health. Agricultural crops may contain one or more mycotoxin compounds; therefore, a good multiplex detection method is desirable to ensure food safety. In this study, we developed a rapid method using label-free surface-enhanced Raman spectroscopy (SERS) to simultaneously detect three common types of mycotoxins found on corn, namely aflatoxin B1 (AFB1), zearalenone (ZEN), and ochratoxin A (OTA). The intrinsic chemical fingerprint from each mycotoxin was characterized by their unique Raman spectra, enabling clear discrimination between them. The limit of detection (LOD) of AFB1, ZEN, and OTA on corn were 10 ppb (32 nM), 20 ppb (64 nM), and 100 ppb (248 nM), respectively. Multivariate statistical analysis was used to predict concentrations of AFB1, ZEN, and OTA up to 1.5 ppm (4.8 µM) based on the SERS spectra of known concentrations, resulting in a correlation coefficient of 0.74, 0.89, and 0.72, respectively. The sampling time was less than 30 min per sample. The application of label-free SERS and multivariate analysis is a promising method for rapid and simultaneous detection of mycotoxins in corn and may be extended to other types of mycotoxins and crops.
Collapse
Affiliation(s)
- Allison Gabbitas
- Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA; (A.G.); (K.A.)
| | - Gene Ahlborn
- Department of Nutrition, Dietetics and Food Science, Brigham Young University, Provo, UT 84602, USA;
| | - Kaitlyn Allen
- Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA; (A.G.); (K.A.)
| | - Shintaro Pang
- Department of Nutrition, Dietetics and Food Science, Brigham Young University, Provo, UT 84602, USA;
| |
Collapse
|
10
|
Han C, Wang Q, Yao Y, Zhang Q, Huang J, Zhang H, Qu L. Thin layer chromatography coupled with surface enhanced Raman scattering for rapid separation and on-site detection of multi-components. J Chromatogr A 2023; 1706:464217. [PMID: 37517317 DOI: 10.1016/j.chroma.2023.464217] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 08/01/2023]
Abstract
The separation and detection of multi-component mixtures has always been a challenging task. Traditional detection methods often suffer from complex operation, high cost, and low sensitivity. Surface enhanced Raman scattering (SERS) technique is a high sensitivity, powerful and rapid detection tool, which can realize the specific detection of single substance components, but it must solve the problem that multi-component mixtures cannot be accurately determined. Thin layer chromatography (TLC) technology, as a high-throughput separation technology, uses chromatographic plate as the stationary phase, and could select different developing phases for separation experiments. The advantages of TLC technology in short distance and rapid separation are widely used in protein, dye and biomedical fields. However, TLC technology has limitations in detection ability and difficulty in obtaining ideal signal intensity. The combination of TLC technology and SERS technology made the operation procedure simple and the sample size small, which can achieve rapid on-site separation and quantitative detection of mixtures. Due to the rapid development of TLC-SERS technology, it has been widely used in the investigation of various complex systems. This paper reviews the application of TLC-SERS technology in food science, environmental pollution and biomedicine.
Collapse
Affiliation(s)
- Caiqin Han
- Jiangsu Key Laboratory of Advanced Laser Materials and Devices, School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou 221116, China.
| | - Qin Wang
- Jiangsu Key Laboratory of Advanced Laser Materials and Devices, School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou 221116, China
| | - Yue Yao
- Jiangsu Key Laboratory of Advanced Laser Materials and Devices, School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou 221116, China
| | - Qian Zhang
- Jiangsu Key Laboratory of Advanced Laser Materials and Devices, School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou 221116, China
| | - Jiawei Huang
- Jiangsu Key Laboratory of Advanced Laser Materials and Devices, School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou 221116, China
| | - Hengchang Zhang
- Jiangsu Key Laboratory of Advanced Laser Materials and Devices, School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou 221116, China
| | - Lulu Qu
- School of Chemistry and Materials Science, Jiangsu Normal University, Xuzhou 221116, China.
| |
Collapse
|
11
|
Unraveling surface-enhanced Raman spectroscopy results through chemometrics and machine learning: principles, progress, and trends. Anal Bioanal Chem 2023:10.1007/s00216-023-04620-y. [PMID: 36864313 PMCID: PMC9981450 DOI: 10.1007/s00216-023-04620-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 02/02/2023] [Accepted: 02/20/2023] [Indexed: 03/04/2023]
Abstract
Surface-enhanced Raman spectroscopy (SERS) has gained increasing attention because it provides rich chemical information and high sensitivity, being applicable in many scientific fields including medical diagnosis, forensic analysis, food control, and microbiology. Although SERS is often limited by the lack of selectivity in the analysis of samples with complex matrices, the use of multivariate statistics and mathematical tools has been demonstrated to be an efficient strategy to circumvent this issue. Importantly, since the rapid development of artificial intelligence has been promoting the implementation of a wide variety of advanced multivariate methods in SERS, a discussion about the extent of their synergy and possible standardization becomes necessary. This critical review comprises the principles, advantages, and limitations of coupling SERS with chemometrics and machine learning for both qualitative and quantitative analytical applications. Recent advances and trends in combining SERS with uncommonly used but powerful data analysis tools are also discussed. Finally, a section on benchmarking and tips for selecting the suitable chemometric/machine learning method is included. We believe this will help to move SERS from an alternative detection strategy to a general analytical technique for real-life applications.
Collapse
|
12
|
Lu X, Ji S, Ren Z, Jiang S, Yu Q, Guo J, Wang AX, Kong X. Rapid, Convenient, and Ultrasensitive Point-of-Care sensing of histamine from fish: A Portable chromatographic platform based on derivatization reaction. J Chromatogr A 2023; 1696:463953. [PMID: 37037052 DOI: 10.1016/j.chroma.2023.463953] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 03/25/2023] [Accepted: 03/26/2023] [Indexed: 04/03/2023]
Abstract
Food poisoning caused by histamine ingestion is one of the prevalent allergies associated with fish consumption in the world. Reliable detection of histamine from fish by a portable platform was of urgent importance to food safety. A portable technology for on-site monitoring of histamine in tuna was established through combined azo-derivatized thin-layer chromatography (TLC) with surface-enhanced Raman scattering (SERS) spectroscopy. The real tuna meat sample was directly applied onto the portable sensor for the separation of histamine and azo-derivatizing of histamine was reacted on the TLC plate. The colorless histamine was visualized by azo-derivatization after spraying Pauly reagent onto the diatomite TLC plate. The molecule information and concentration of the histamine was measured and calculated by SERS spectra. Diatomite TLC plate was capable of separating histamine with 1.32 × 10-7 M of Au colloid for the SERS enhancement. Accordingly, the limit of detection of histamine from mixture sample could achieve 2.8 × 10-4 ppm. These results indicated that the portable azo-derivatized TLC-SERS sensor not only visualizes the histamine but also improves the intensity of the Raman spectra. The azo-derivatized TLC-SERS sensor could be applied for rapid, convenient, and ultrasensitive point-of-care sensing of histamine in fish.
Collapse
Affiliation(s)
- Xiaoqi Lu
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China
| | - Siyu Ji
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China
| | - Zhengbing Ren
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China
| | - Shangkun Jiang
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China
| | - Qian Yu
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China.
| | - Jiaqi Guo
- Jiangsu Co-Innovation Center for Efficient Processing and Utilization of Forest Resources and Joint International Research Lab of Lignocellulosic Functional Materials, Nanjing Forestry University, Nanjing 210037, PR China
| | - Alan X Wang
- Department of Electrical and Computer Engineering, Baylor University, Waco, TX 76798, USA
| | - Xianming Kong
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun, Liaoning 113001, PR China.
| |
Collapse
|
13
|
Beeram R, Vepa KR, Soma VR. Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques. BIOSENSORS 2023; 13:328. [PMID: 36979540 PMCID: PMC10046859 DOI: 10.3390/bios13030328] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/20/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS's full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.
Collapse
|
14
|
Controllable synthesis of flower-like AuNFs@ZIF-67 core-shell nanocomposites for ultrasensitive SERS detection of histamine in fish. Anal Chim Acta 2023; 1240:340776. [PMID: 36641156 DOI: 10.1016/j.aca.2022.340776] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/29/2022] [Accepted: 12/30/2022] [Indexed: 01/01/2023]
Abstract
Histamine is a significant biomarker to assess the freshness of fish products. In this study, a novel MOF-based SERS sensor for histamine determination was synthesized by wrapping PVP-capped Au nanoflowers with a ZIF-67 shell (Au NFs@ZIF-67). The highly branched Au NFs core exhibited a strong electromagnetic field enhancement effect and provided an ultra-sensitive SERS fingerprint spectrum, while ZIF-67 shell was the contributor to enrich the target and stabilize the substrate. The morphology of the core-shell structures can be easily controlled by the concentrations of the capping agent PVP and MOF precursor Co ion. Consequently, 4-MBA pre-grafted on the optimized SERS substrate can act as the Raman internal standard (IS) to eliminate signal fluctuations through standardizing all spectra against its peak at 1074 cm-1. Moreover, as the specific receptor for histamine molecules, 4-MBA helped reach the low detection sensitivity, where the SERS intensity ratio, I1172/I1074 presented a good linear relationship towards the histamine concentrations (10-3-10-7 M) with the LOD of 0.87 × 10-7 M (R2 = 0.9930). Furthermore, the application in monitoring fish spoilage process demonstrated the feasibility and reliability of the developed sensor. This work provided a facile strategy to construct MOF-based SERS substrate as a potential platform for the shelf-life prediction of fish products.
Collapse
|
15
|
Duan X, Li Z, Wang L, Lin H, Wang K. Engineered nanomaterials-based sensing systems for assessing the freshness of meat and aquatic products: A state-of-the-art review. Compr Rev Food Sci Food Saf 2023; 22:430-450. [PMID: 36451298 DOI: 10.1111/1541-4337.13074] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/02/2022] [Accepted: 10/20/2022] [Indexed: 12/05/2022]
Abstract
Meat and aquatic products are susceptible to spoilage during distribution, transportation, and storage, increasing the urgency of freshness evaluation. Engineered nanomaterials (ENMs) typically with the diameter in the range of 1-100 nm exhibit fascinating physicochemical properties. ENMs-based sensing systems have received extensive attention for food freshness assessment due to the advantages of being fast, simple, and sensitive. This review focuses on summarizing the recent application of ENMs-based sensing systems for food freshness detection. First, chemical indicators related to the freshness of meat and aquatic products are described. Then, how to apply the ENMs including noble metal nanomaterials, metal oxide nanomaterials, carbon nanomaterials, and metal-organic frameworks for the construction of different sensing systems were described. Besides, the recent advance in ENMs-based colorimetric, fluorescent, electrochemical, and surface-enhanced Raman spectroscopy sensing systems for assessing the freshness of meat and aquatic products were outlined. Finally, the challenges and future research perspectives for the application of ENMs-based sensing systems were discussed. The ENMs-based sensing systems have been demonstrated as effective tools for freshness evaluation. The sensing performance of ENMs employed in different sensing systems depends on their composition, size, shape, and stability of nanoparticles. For the real application of ENMs in food industries, the risks and regulatory issues associated with nanomaterials need to be further considered. With the continuous development of nanomaterials and sensing devices, the ENMs-based sensors are expected to be applied in-field for rapid detection of the freshness of meat and aquatic products in the future.
Collapse
Affiliation(s)
- Xiaoyan Duan
- College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Zhuoran Li
- College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Lei Wang
- College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Hong Lin
- College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Kaiqiang Wang
- College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong, China.,Fujian Provincial Key Laboratory of Breeding Lateolabrax Japonicus, Ningde, Fujian, China
| |
Collapse
|
16
|
Yao H, Dong X, Xiong H, Liu J, Zhou J, Ye Y. Functional cotton fabric-based TLC-SERS matrix for rapid and sensitive detection of mixed dyes. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 280:121464. [PMID: 35717930 DOI: 10.1016/j.saa.2022.121464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 05/21/2022] [Accepted: 06/02/2022] [Indexed: 06/15/2023]
Abstract
A facile cotton fabric with a built-in TLC-SERS structure was fabricated to demonstrate an integrated TLC separation and SERS identification of mixed dyes. The soft and flexible SERS fabric was firstly fabricated using a simple method in which gold nanoparticles were in-situ synthesized on cotton fabrics by heating. β-CD was then grafted onto cotton fabric through crosslinking with citric acid in presence of sodium hypophosphite monohydrate via esterification reaction. The adsorption and TLC development performance of β-CD grafted fabrics were comprehensively investigated with two organic dyes, one anionic dye and one nonionic dye. Besides, the recyclable adsorption and separation performance were tested to evaluate its sustainable application prospects. It displayed less adsorption capacity loss and reusable separation performance after several cycles than the pristine cotton fabrics. Finally, two sets of mixed dyes were successfully separated on the TLC fabrics and then identified via on-site SERS according to their different migration distance. The developed TLC-SERS fabric shows the advantage of quick, easy to handle, low-cost, sensitive, and could be exploited in on-site study of synthetic dyes in art objects, textile and packaging products or forensic applications.
Collapse
Affiliation(s)
- Huifang Yao
- Hubei Key Laboratory of the Forensic Science, Hubei University of Police, Wuhan 430035, China
| | - Xiaxiao Dong
- Hubei Collaborative Innovation Center for Advanced Organic Chemical Materials & Ministry-of-Education Key Laboratory for the Synthesis and Application of Organic Functional Molecules & College of Chemistry and Chemical Engineering, Hubei University, Wuhan 430062, China
| | - Hong Xiong
- Hubei Collaborative Innovation Center for Advanced Organic Chemical Materials & Ministry-of-Education Key Laboratory for the Synthesis and Application of Organic Functional Molecules & College of Chemistry and Chemical Engineering, Hubei University, Wuhan 430062, China
| | - Jinwei Liu
- Hubei Collaborative Innovation Center for Advanced Organic Chemical Materials & Ministry-of-Education Key Laboratory for the Synthesis and Application of Organic Functional Molecules & College of Chemistry and Chemical Engineering, Hubei University, Wuhan 430062, China
| | - Ji Zhou
- Hubei Collaborative Innovation Center for Advanced Organic Chemical Materials & Ministry-of-Education Key Laboratory for the Synthesis and Application of Organic Functional Molecules & College of Chemistry and Chemical Engineering, Hubei University, Wuhan 430062, China.
| | - Yong Ye
- Hubei Collaborative Innovation Center for Advanced Organic Chemical Materials & Ministry-of-Education Key Laboratory for the Synthesis and Application of Organic Functional Molecules & College of Chemistry and Chemical Engineering, Hubei University, Wuhan 430062, China.
| |
Collapse
|
17
|
Qu C, Li Y, Du S, Geng Y, Su M, Liu H. Raman spectroscopy for rapid fingerprint analysis of meat quality and security: Principles, progress and prospects. Food Res Int 2022; 161:111805. [DOI: 10.1016/j.foodres.2022.111805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 07/06/2022] [Accepted: 08/18/2022] [Indexed: 11/28/2022]
|
18
|
Zhang M, Yu Q, Guo J, Wu B, Kong X. Review of Thin-Layer Chromatography Tandem with Surface-Enhanced Raman Spectroscopy for Detection of Analytes in Mixture Samples. BIOSENSORS 2022; 12:937. [PMID: 36354446 PMCID: PMC9687685 DOI: 10.3390/bios12110937] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 10/20/2022] [Accepted: 10/25/2022] [Indexed: 06/16/2023]
Abstract
In the real world, analytes usually exist in complex systems, and this makes direct detection by surface-enhanced Raman spectroscopy (SERS) difficult. Thin layer chromatography tandem with SERS (TLC-SERS) has many advantages in analysis such as separation effect, instant speed, simple process, and low cost. Therefore, the TLC-SERS has great potential for detecting analytes in mixtures without sample pretreatment. The review demonstrates TLC-SERS applications in diverse analytical relevant topics such as environmental pollutants, illegal additives, pesticide residues, toxic ingredients, biological molecules, and chemical substances. Important properties such as stationary phase, separation efficiency, and sensitivity are discussed. In addition, future perspectives for improving the efficiency of TLC-SERS in real sample detecting are outlined.
Collapse
Affiliation(s)
- Meizhen Zhang
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun 113001, China
| | - Qian Yu
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun 113001, China
| | - Jiaqi Guo
- Jiangsu Co-Innovation Center for Efficient Processing and Utilization of Forest Resources and Joint International Research Lab of Lignocellulosic Functional Materials, Nanjing Forestry University, Nanjing 210037, China
| | - Bo Wu
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA
| | - Xianming Kong
- School of Petrochemical Engineering, Liaoning Petrochemical University, Fushun 113001, China
| |
Collapse
|
19
|
Microarray-based chemical sensors and biosensors: Fundamentals and food safety applications. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
|
20
|
Fukunaga Y, Okada T. Freeze Surface-Enhanced Raman Scattering Coupled with Thin-Layer Chromatography: Pesticide Detection and Quantification Case. Anal Chem 2022; 94:13507-13515. [PMID: 36136892 DOI: 10.1021/acs.analchem.2c02732] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Thin-layer chromatography (TLC) is widely used in various branches of chemical science to separate components in complex mixtures because of its simplicity. In most cases, analyte spots are visually detected by fluorescence, and the retention factor (Rf) is determined from the distance traveled by the analyte. Further characterizations are often necessary to identify separated chemicals because molecular information other than Rf is not available. Surface-enhanced Raman scattering (SERS) has been coupled with TLC to complement molecular information. In previously reported TLC-SERS, metal nanoparticle suspension was dropped onto analyte spots to obtain SERS spectra. This approach is simple and efficient for SERS measurements on the TLC plate but has limited sensitivity for several reasons, such as the low solubility of analytes in the dropped solution, difficult control of nanoparticle aggregation, and interference from the stationary phase. We recently showed that freezing enhances SERS sensitivity by a factor of ∼103. Freezing simultaneously concentrates analytes and silver nanoparticles (AgNPs) in a freeze concentrated solution, where aggregation of AgNPs is facilitated, allowing sensitive freeze SERS (FSERS) measurements. Here, we discuss FSERS measurements on TLC plates to demonstrate the superiority of this combination, i.e. TLC-FSERS. Freezing enhances SERS sensitivity by freeze concentration and facilitated aggregation of AgNPs and, in addition, eliminates interference from the stationary phase. Under the optimized condition, TLC-FSERS enables the on-site detection of pesticides at the nM level. The use of the SERS signal from adenine added as the internal standard allows us to quantify pesticides. Applications to a commercial green tea beverage are also demonstrated.
Collapse
Affiliation(s)
- Yu Fukunaga
- Department of Chemistry, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8551, Japan
| | - Tetsuo Okada
- Department of Chemistry, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8551, Japan.,National Institute of Technology (KOSEN), Numazu College, 3600 Ooka, Numazu, Shizuoka 410-8501, Japan
| |
Collapse
|
21
|
Liang X, Li L, Han C, Dong Y, Xu F, Lv Z, Zhang Y, Qu Z, Dong W, Sun Y. Rapid Limit Test of Seven Pesticide Residues in Tea Based on the Combination of TLC and Raman Imaging Microscopy. Molecules 2022; 27:5151. [PMID: 36014399 PMCID: PMC9413101 DOI: 10.3390/molecules27165151] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 08/06/2022] [Accepted: 08/08/2022] [Indexed: 11/21/2022] Open
Abstract
Numerous studies have shown that pesticide residues in tea exceeding the maximum residue limits (MRL) can cause harmful effects on the human body. There are many limitations in the existing analytical methods for pesticide residues in tea, so new analytical methods need to be developed. We developed a limit test method that combines thin-layer chromatography with Raman imaging microscopy (TLC-RIM). Seven residual pesticide components in tea (Avermectin, Methomyl, Carbendazim, Imidacloprid, Chlorothalonil, Azoxystrobin, and Acetamiprid) could be preliminarily separated by TLC and then irradiated by a 532 nm laser. Raman spectra of seven pesticides obtained by Raman imaging microscopy could be used to test whether the pesticide residues in tea exceed the MRL. The limits of detection of the seven pesticides were 0.04, 0.10, 0.24, 0.20, 0.12, 0.12, and 1.0 mg/mL, respectively. The simulated positive test showed that the matrix in tea did not interfere with the test of the seven pesticides. When the pesticides were tested within 8 h, the RSD of the peak heights of the seven pesticides were 1.2%~9.6%; the test results of three batches of tea showed that the imidacloprid in one batch of tea exceeded its MRL, and the results were consistent with that by UPLC-MS/MS. The TLC-RIM is fast, sensitive, stable, specific, and reliable.
Collapse
Affiliation(s)
| | - Li Li
- Pharmacy School, Qiqihar Medical University, Qiqihar 161006, China
| | | | | | | | | | | | | | | | | |
Collapse
|
22
|
Surface-enhanced Raman spectroscopy tandem with derivatized thin-layer chromatography for ultra-sensitive on-site detection of histamine from fish. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.108987] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
|
23
|
Ling X, Liu Y, Zhu D, An W, Geng J, Li L, Yu C, Wei JF. Colorimetric visualization of histamine secreted by basophils based on DSP-functionalized gold nanoparticles. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2022; 14:2698-2702. [PMID: 35770648 DOI: 10.1039/d2ay00379a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Histamine released by activated basophils has become an important biomarker and therapeutic target in the development of allergic diseases. To date, several gold nanoparticle (AuNP)-based nanosensors have been reported for histamine detection in foods. However, rapid, highly sensitive and direct detection of histamine in allergic diseases is still lacking due to the complexity of the physical environment. Herein, we developed a novel nanosensor for colorimetric visualization of histamine in activated basophils by simply coupling dithiobis(succinimidylpropionate) (DSP) on the surface of AuNPs (DSP-AuNPs). The DSP moiety serves as a linker and can react with the aliphatic amino group of histamine, and the imidazole ring of histamine can selectively bind with Au by means of p-p conjugation, thus inducing the aggregation of AuNPs. In this study, we experimentally proved that DSP-AuNPs showed good sensitivity and selectivity to histamine among various amino acids, including histidine. Additionally, this nanosensor displayed a rapid response to histamine with a linear range of 0.8-2.5 μM, and the limit of detection (LOD) was 0.014 μM, which is a relatively low LOD in comparison with those of other AuNP-based nanosensors. Finally, DSP-AuNPs are used, for the first time, to successfully detect endogenous histamine changes in activated basophils. Therefore, our work may provide a promising strategy to monitor histamine levels in the basophil activation test.
Collapse
Affiliation(s)
- Xiaojing Ling
- Department of Pharmacy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210009, China.
| | - Yongxin Liu
- Key Laboratory of Flexible Electronics (KLOFE), Institute of Advanced Materials (IAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211800, P. R. China.
| | - Danxuan Zhu
- Women & Children Central Laboratory, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210036, China
| | - Weizhen An
- Key Laboratory of Flexible Electronics (KLOFE), Institute of Advanced Materials (IAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211800, P. R. China.
| | - Jiaying Geng
- Key Laboratory of Flexible Electronics (KLOFE), Institute of Advanced Materials (IAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211800, P. R. China.
| | - Lin Li
- Key Laboratory of Flexible Electronics (KLOFE), Institute of Advanced Materials (IAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211800, P. R. China.
| | - Changmin Yu
- Key Laboratory of Flexible Electronics (KLOFE), Institute of Advanced Materials (IAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211800, P. R. China.
| | - Ji-Fu Wei
- Department of Pharmacy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210009, China.
- Women & Children Central Laboratory, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210036, China
| |
Collapse
|
24
|
Luo SZ, Yang JY, Jia BZ, Wang H, Chen ZJ, Wei XQ, Shen YD, Lei HT, Xu ZL, Luo L. Multicolorimetric and fluorometric dual-modal immunosensor for histamine via enzyme-enabled metallization of gold nanorods and inner filter effect of carbon dots. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.108941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
|
25
|
Establishment of the thin-layer chromatography-surface-enhanced Raman spectroscopy and chemometrics method for simultaneous identification of eleven illegal drugs in anti-rheumatic health food. FOOD BIOSCI 2022. [DOI: 10.1016/j.fbio.2022.101842] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
|
26
|
Li K, Li H, Yin M, Yang D, Xiao F, Kumar Tammina S, Yang Y. Fluorescence-SERS dual-mode for sensing histamine on specific binding histamine-derivative and gold nanoparticles. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 273:121047. [PMID: 35217264 DOI: 10.1016/j.saa.2022.121047] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 02/11/2022] [Accepted: 02/13/2022] [Indexed: 06/14/2023]
Abstract
Histamine (His) is used as an indicator of seafood quality, but it can be toxic at high intakes. A fluorescence (FL)-surface-enhanced Raman scattering (SERS) dual-mode assay system has been developed for His detection. The His detection method was established based on the specific binding capacity of gold nanoparticles (AuNPs) for the FL derivative of His and o-phthalaldehyde (OPA). In this strategy, His reacted with the OPA to form a Schiff base product (O-His) along with a change in FL and SERS activities. The usual nature of AuNPs could display a significant role both enhancement of SERS and quenching of FL signals. The current investigation displayed a good selectivity toward His over all other biogenic amines. Under the optimized analytical conditions, the SERS and FL intensity of the system were linearly proportional to the His concentration in the range of 0.05-4.5 mg/L and 1-20 mg/L with a detection limit of 0.04 mg/L and 0.32 mg/L, respectively. Moreover, the proposed method was successfully applied for His determination in seafood with promising results.
Collapse
Affiliation(s)
- Kexiang Li
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Yunnan Province 650500, China
| | - Hong Li
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Yunnan Province 650500, China; Institute of Agro-products Processing, Yunnan Academy of Agricultural Science, Yunnan Province 650032, China
| | - Mongjia Yin
- Yunnan Lunyang Technology Co., Ltd., Yunnan Province 650032, China
| | - Dezhi Yang
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Yunnan Province 650500, China; Yunnan Lunyang Technology Co., Ltd., Yunnan Province 650032, China.
| | - Feijian Xiao
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Yunnan Province 650500, China
| | - Sai Kumar Tammina
- School of Physics, University of Hyderabad, Hyderabad, Telangana 500046, India
| | - Yaling Yang
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Yunnan Province 650500, China.
| |
Collapse
|
27
|
Rapid Detection of Five Estrogens Added Illegally to Dietary Supplements by Combining TLC with Raman Imaging Microscope. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27092650. [PMID: 35566009 PMCID: PMC9104963 DOI: 10.3390/molecules27092650] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/15/2022] [Accepted: 04/18/2022] [Indexed: 11/17/2022]
Abstract
Estrogens added illegally to dietary supplements are hazardous to human health. Traditional detection and analysis methods have many limitations, and we have developed an assay that combines thin-layer chromatography with Raman imaging microscopy (TLC-RIM). The five estrogens (estrone, estradiol, estriol, ethinyl estradiol, and diethylstilbestrol) were initially separated by TLC, then detected by area scanning Raman imaging with a 532 nm laser under a microscope. Raman spectra were obtained for each estrogen, which were used for detecting estrogen illegally added to botanical dietary supplements. The LOD of each estrogen was 0.4, 1.0, 0.8, 0.2, and 0.2 mg/mL, respectively. The matrix in the real sample did not interfere with the detection of estrogens. The method was fast, sensitive, stable, specific, and reliable.
Collapse
|
28
|
Hou X, Sivashanmugan K, Zhao Y, Zhang B, Wang AX. Multiplex Sensing of Complex Mixtures by Machine Vision Analysis of TLC-SERS Images. SENSORS AND ACTUATORS. B, CHEMICAL 2022; 357:131355. [PMID: 35221529 PMCID: PMC8880841 DOI: 10.1016/j.snb.2021.131355] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Thin layer chromatography in tandem with surface-enhanced Raman scattering (TLC-SERS) has demonstrated tremendous potentials as a new analytical chemistry tool to detect a wide range of substances from real-world samples. However, it still faces significant challenges of multiplex sensing from complex mixtures due to the imperfect separation by TLC and the resulting interference of SERS detection. In this article, we propose a multiplex sensing method of complex mixtures by machine vision analysis of the scanning image of the TLC-SERS results. Briefly, various pure substances in solution and the complex mixture solution are separated by TLC followed by one-dimensional SERS scanning of the entire TLC plate, which generates TLC-SERS images of all target substances along the chromatography path. After that, a machine vision method is employed to extract the template images from the TLC-SERS images of pure substance solutions. Finally, we apply a feature point matching strategy based on the Winner-take-all principle, which matches the template image of each pure substance with the mixture image to confirm the existence and derive the position of each target substance in the TLC plate, respectively. Our experimental results based on the mixture solution of five different substances show that the proposed machine vision analysis is highly selective, sensitive and does not require artificial analysis of the SERS spectra. Therefore, we envision that the proposed machine vision analysis of the TLC-SERS imaging is an objective, accurate, and efficient method for multiplex sensing of trace level of target substances from complex mixtures.
Collapse
Affiliation(s)
- Xingwei Hou
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
- State Key Laboratory of Precision Measurement Technology and Instrument and School of Precision Instruments & Opto-Electronics Engineering, Tianjin University, Tianjin 300072, P.R. China
| | - Kundan Sivashanmugan
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Yong Zhao
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
- School of Electrical Engineering, The Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, P.R. China
| | - Boxin Zhang
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Alan X. Wang
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| |
Collapse
|
29
|
Sha X, Han S, Fang G, Li N, Lin D, Hasi W. A novel suitable TLC-SERS assembly strategy for detection of Rhodamine B and Sudan I in chili oil. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
|
30
|
Wu G, Dou X, Li D, Xu S, Zhang J, Ding Z, Xie J. Recent Progress of Fluorescence Sensors for Histamine in Foods. BIOSENSORS 2022; 12:161. [PMID: 35323431 PMCID: PMC8945960 DOI: 10.3390/bios12030161] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 02/25/2022] [Accepted: 03/02/2022] [Indexed: 05/03/2023]
Abstract
Biological amines are organic nitrogen compounds that can be produced by the decomposition of spoiled food. As an important biological amine, histamine has played an important role in food safety. Many methods have been used to detect histamine in foods. Compared with traditional analysis methods, fluorescence sensors as an adaptable detection tool for histamine in foods have the advantages of low cost, convenience, less operation, high sensitivity, and good visibility. In terms of food safety, fluorescence sensors have shown great utilization potential. In this review, we will introduce the applications and development of fluorescence sensors in food safety based on various types of materials. The performance and effectiveness of the fluorescence sensors are discussed in detail regarding their structure, luminescence mechanism, and recognition mechanism. This review may contribute to the exploration of the application of fluorescence sensors in food-related work.
Collapse
Affiliation(s)
- Gan Wu
- College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; (G.W.); (X.D.); (D.L.)
| | - Xilin Dou
- College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; (G.W.); (X.D.); (D.L.)
| | - Dapeng Li
- College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; (G.W.); (X.D.); (D.L.)
| | - Shihan Xu
- Department of Chemistry, University of Washington, Seattle, WA 98195, USA; (S.X.); (J.Z.)
| | - Jicheng Zhang
- Department of Chemistry, University of Washington, Seattle, WA 98195, USA; (S.X.); (J.Z.)
| | - Zhaoyang Ding
- College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; (G.W.); (X.D.); (D.L.)
| | - Jing Xie
- College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; (G.W.); (X.D.); (D.L.)
| |
Collapse
|
31
|
Liang JF, Peng C, Li P, Ye QX, Wang Y, Yi YT, Yao ZS, Chen GY, Zhang BB, Lin JJ, Luo Q, Chen X. A Review of Detection of Antibiotic Residues in Food by Surface-Enhanced Raman Spectroscopy. Bioinorg Chem Appl 2021; 2021:8180154. [PMID: 34777490 PMCID: PMC8589529 DOI: 10.1155/2021/8180154] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 10/20/2021] [Indexed: 11/17/2022] Open
Abstract
Antibiotics, as veterinary drugs, have made extremely important contributions to disease prevention and treatment in the animal breeding industry. However, the accumulation of antibiotics in animal food due to their overuse during animal feeding is a frequent occurrence, which in turn would cause serious harm to public health when they are consumed by humans. Antibiotic residues in food have become one of the central issues in global food safety. As a safety measure, rapid and effective analytical approaches for detecting these residues must be implemented to prevent contaminated products from reaching the consumers. Traditional analytical methods, such as liquid chromatography, liquid chromatography mass spectrometry, and capillary electrophoresis, involve time-consuming sample preparation and complicated operation and require expensive instrumentation. By comparison, surface-enhanced Raman spectroscopy (SERS) has excellent sensitivity and remarkably enhanced target recognition. Thus, SERS has become a promising alternative analytical method for detecting antibiotic residues, as it can provide an ultrasensitive fingerprint spectrum for the rapid and noninvasive detection of trace analytes. In this study, we comprehensively review the recent progress and advances that have been achieved in the use of SERS in antibiotic residue detection. We introduce and discuss the basic principles of SERS. We then present the prospects and challenges in the use of SERS in the detection of antibiotics in food. Finally, we summarize and discuss the current problems and future trends in the detection of antibiotics in food.
Collapse
Affiliation(s)
- Jun-Fa Liang
- Guangzhou Institute of Food Inspection, Guangzhou, China
| | - Cheng Peng
- Guangzhou Institute of Food Inspection, Guangzhou, China
| | - Peiyu Li
- Department of Forensic Toxicology, School of Forensic Medicine, Southern Medical University, Guangzhou 510515, China
| | - Qiu-Xiong Ye
- Guangzhou Institute of Food Inspection, Guangzhou, China
| | - Yu Wang
- Guangzhou Institute of Food Inspection, Guangzhou, China
| | - Yun-Ting Yi
- Guangzhou Institute of Food Inspection, Guangzhou, China
| | - Zi-Sheng Yao
- Guangzhou Institute of Food Inspection, Guangzhou, China
| | - Gui-Yun Chen
- Guangzhou Institute of Food Inspection, Guangzhou, China
| | - Bin-Bin Zhang
- Guangzhou Institute of Food Inspection, Guangzhou, China
| | - Jia-Jian Lin
- Guangzhou Institute of Food Inspection, Guangzhou, China
| | - Qizhi Luo
- Department of Forensic Toxicology, School of Forensic Medicine, Southern Medical University, Guangzhou 510515, China
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou 510515, China
| | - Xuncai Chen
- Department of Forensic Toxicology, School of Forensic Medicine, Southern Medical University, Guangzhou 510515, China
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou 510515, China
| |
Collapse
|
32
|
Zhang B, Hou X, Zhen C, Wang AX. Sub-Part-Per-Billion Level Sensing of Fentanyl Residues from Wastewater Using Portable Surface-Enhanced Raman Scattering Sensing. BIOSENSORS-BASEL 2021; 11:bios11100370. [PMID: 34677326 PMCID: PMC8534101 DOI: 10.3390/bios11100370] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 09/28/2021] [Accepted: 09/29/2021] [Indexed: 11/16/2022]
Abstract
Detection of illicit drug residues from wastewater provides a new route toward community-level assessment of drug abuse that is critical to public health. However, traditional chemistry analytical tools such as high-performance liquid chromatography in tandem with mass spectrometry (HPLC-MS) cannot meet the large-scale testing requirement in terms of cost, promptness, and convenience of use. In this article, we demonstrated ultra-sensitive and portable surface-enhanced Raman scattering sensing (SERS) of fentanyl, a synthetic opioid, from sewage water and achieved quantitative analysis through principal component analysis and partial least-squares regression. The SERS substrates adopted in this application were synthesized by in situ growth of silver nanoparticles on diatomaceous earth films, which show ultra-high sensitivity down to 10 parts per trillion in artificially contaminated tap water in the lab using a commercial portable Raman spectrometer. Based on training data from artificially contaminated tap water, we predicted the fentanyl concentration in the sewage water from a wastewater treatment plant to be 0.8 parts per billion (ppb). As a comparison, the HPLC-MS confirmed the fentanyl concentration was below 1 ppb but failed to provide a specific value of the concentration since the concentration was too low. In addition, we further proved the validity of our SERS sensing technique by comparing SERS results from multiple sewage water treatment plants, and the results are consistent with the public health data from our local health authority. Such SERS sensing technique with ultra-high sensitivity down to sub-ppb level proved its feasibility for point-of-care detection of illicit drugs from sewage water, which is crucial to assess public health.
Collapse
|
33
|
Pérez Santín E, Rodríguez Solana R, González García M, García Suárez MDM, Blanco Díaz GD, Cima Cabal MD, Moreno Rojas JM, López Sánchez JI. Toxicity prediction based on artificial intelligence: A multidisciplinary overview. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1516] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Efrén Pérez Santín
- Escuela Superior de Ingeniería y Tecnología (ESIT) Universidad Internacional de La Rioja (UNIR) Logroño Spain
| | - Raquel Rodríguez Solana
- Department of Food Science and Health Andalusian Institute of Agricultural and Fisheries Research and Training (IFAPA), Alameda del Obispo Avda Córdoba, Andalucía Spain
| | - Mariano González García
- Escuela Superior de Ingeniería y Tecnología (ESIT) Universidad Internacional de La Rioja (UNIR) Logroño Spain
| | - María Del Mar García Suárez
- Escuela Superior de Ingeniería y Tecnología (ESIT) Universidad Internacional de La Rioja (UNIR) Logroño Spain
| | - Gerardo David Blanco Díaz
- Escuela Superior de Ingeniería y Tecnología (ESIT) Universidad Internacional de La Rioja (UNIR) Logroño Spain
| | - María Dolores Cima Cabal
- Escuela Superior de Ingeniería y Tecnología (ESIT) Universidad Internacional de La Rioja (UNIR) Logroño Spain
| | - José Manuel Moreno Rojas
- Department of Food Science and Health Andalusian Institute of Agricultural and Fisheries Research and Training (IFAPA), Alameda del Obispo Avda Córdoba, Andalucía Spain
| | - José Ignacio López Sánchez
- Escuela Superior de Ingeniería y Tecnología (ESIT) Universidad Internacional de La Rioja (UNIR) Logroño Spain
| |
Collapse
|
34
|
Schackart KE, Yoon JY. Machine Learning Enhances the Performance of Bioreceptor-Free Biosensors. SENSORS (BASEL, SWITZERLAND) 2021; 21:5519. [PMID: 34450960 PMCID: PMC8401027 DOI: 10.3390/s21165519] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 08/09/2021] [Accepted: 08/13/2021] [Indexed: 01/06/2023]
Abstract
Since their inception, biosensors have frequently employed simple regression models to calculate analyte composition based on the biosensor's signal magnitude. Traditionally, bioreceptors provide excellent sensitivity and specificity to the biosensor. Increasingly, however, bioreceptor-free biosensors have been developed for a wide range of applications. Without a bioreceptor, maintaining strong specificity and a low limit of detection have become the major challenge. Machine learning (ML) has been introduced to improve the performance of these biosensors, effectively replacing the bioreceptor with modeling to gain specificity. Here, we present how ML has been used to enhance the performance of these bioreceptor-free biosensors. Particularly, we discuss how ML has been used for imaging, Enose and Etongue, and surface-enhanced Raman spectroscopy (SERS) biosensors. Notably, principal component analysis (PCA) combined with support vector machine (SVM) and various artificial neural network (ANN) algorithms have shown outstanding performance in a variety of tasks. We anticipate that ML will continue to improve the performance of bioreceptor-free biosensors, especially with the prospects of sharing trained models and cloud computing for mobile computation. To facilitate this, the biosensing community would benefit from increased contributions to open-access data repositories for biosensor data.
Collapse
Affiliation(s)
- Kenneth E. Schackart
- Department of Biosystems Engineering, The University of Arizona, Tucson, AZ 85721, USA;
| | - Jeong-Yeol Yoon
- Department of Biosystems Engineering, The University of Arizona, Tucson, AZ 85721, USA;
- Department of Biomedical Engineering, The University of Arizona, Tucson, AZ 85721, USA
| |
Collapse
|
35
|
Influence of Sample Matrix on Determination of Histamine in Fish by Surface Enhanced Raman Spectroscopy Coupled with Chemometric Modelling. Foods 2021; 10:foods10081767. [PMID: 34441544 PMCID: PMC8391157 DOI: 10.3390/foods10081767] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/27/2021] [Accepted: 07/29/2021] [Indexed: 02/03/2023] Open
Abstract
Histamine fish poisoning is a foodborne illness caused by the consumption of fish products with high histamine content. Although intoxication mechanisms and control strategies are well known, it remains by far the most common cause of seafood-related health problems. Since conventional methods for histamine testing are difficult to implement in high-throughput quality control laboratories, simple and rapid methods for histamine testing are needed to ensure the safety of seafood products in global trade. In this work, the previously developed SERS method for the determination of histamine was tested to determine the influence of matrix effect on the performance of the method and to investigate the ability of different chemometric tools to overcome matrix effect issues. Experiments were performed on bluefin tuna (Thunnus thynnus) and bonito (Sarda sarda) samples exposed to varying levels of microbial activity. Spectral analysis confirmed the significant effect of sample matrix, related to different fish species, as well as the extent of microbial activity on the predictive ability of PLSR models with R2 of best model ranging from 0.722–0.945. Models obtained by ANN processing of factors derived by PCA from the raw spectra of the samples showed excellent prediction of histamine, regardless of fish species and extent of microbial activity (R2 of validation > 0.99).
Collapse
|
36
|
Xu J, Ye Y, Ji J, Sun J, Sun X. Advances on the rapid and multiplex detection methods of food allergens. Crit Rev Food Sci Nutr 2021; 62:6887-6907. [PMID: 33830835 DOI: 10.1080/10408398.2021.1907736] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
With the gradually increasing prevalence of food allergy in recent years, food allergy has become a major public health problem worldwide. The clinical symptoms caused by food allergy seriously affect people's quality of life; there are unknown allergen components in novel food and hidden allergens caused by cross contamination in food processing, which pose a serious risk to allergy sufferers. Thus, rapid and multiplex detection methods are required to achieve on-site detection or examination of allergic components, so as to identify the risk of allergy in time. This paper reviews the progress of high-efficiency detection of food allergens, including enhanced traditional detection techniques and emerging detection techniques with the ability high-throughput detection or screening potential food allergen, such as xMAP, biosensors, biochips, etc. focusing on their sensitivity, applicability of each method in food, along with their pretreatment, advantages, limitation in the application of food analysis. This paper also introduces the challenges faced by these high-efficiency detection technologies, as well as the potential of customized allergen screening methods and rapid on-site detection technology as future research directions.
Collapse
Affiliation(s)
- Jiayuan Xu
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Research Center for Functional Food, Synergetic Innovation Center of Food Safety and Quality Control, Jiangnan University, Wuxi, Jiangsu, P.R. China
| | - Yongli Ye
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Research Center for Functional Food, Synergetic Innovation Center of Food Safety and Quality Control, Jiangnan University, Wuxi, Jiangsu, P.R. China
| | - Jian Ji
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Research Center for Functional Food, Synergetic Innovation Center of Food Safety and Quality Control, Jiangnan University, Wuxi, Jiangsu, P.R. China
| | - Jiadi Sun
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Research Center for Functional Food, Synergetic Innovation Center of Food Safety and Quality Control, Jiangnan University, Wuxi, Jiangsu, P.R. China
| | - Xiulan Sun
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Research Center for Functional Food, Synergetic Innovation Center of Food Safety and Quality Control, Jiangnan University, Wuxi, Jiangsu, P.R. China
| |
Collapse
|
37
|
Abstract
Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, especially deep learning, which is famous for image analysis, facial recognition, and speech recognition, has remained relatively elusive to the biosensor community. Herein, how ML can be beneficial to biosensors is systematically discussed. The advantages and drawbacks of most popular ML algorithms are summarized on the basis of sensing data analysis. Specially, deep learning methods such as convolutional neural network (CNN) and recurrent neural network (RNN) are emphasized. Diverse ML-assisted electrochemical biosensors, wearable electronics, SERS and other spectra-based biosensors, fluorescence biosensors and colorimetric biosensors are comprehensively discussed. Furthermore, biosensor networks and multibiosensor data fusion are introduced. This review will nicely bridge ML with biosensors, and greatly expand chemometrics for detection, analysis, and diagnosis.
Collapse
Affiliation(s)
- Feiyun Cui
- Department of Chemical Engineering, Worcester Polytechnic Institute, 100 Institute Road, Worcester, Massachusetts 01609, United States
| | - Yun Yue
- Department of Electrical & Computer Engineering, Worcester Polytechnic Institute, Worcester, Massachusetts 01609, United States
| | - Yi Zhang
- Department of Biomedical Engineering, University of Connecticut, Storrs, Connecticut 06269, United States
| | - Ziming Zhang
- Department of Electrical & Computer Engineering, Worcester Polytechnic Institute, Worcester, Massachusetts 01609, United States
| | - H. Susan Zhou
- Department of Chemical Engineering, Worcester Polytechnic Institute, 100 Institute Road, Worcester, Massachusetts 01609, United States
| |
Collapse
|
38
|
Nanostructured Biosilica of Diatoms: From Water World to Biomedical Applications. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10196811] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Diatoms—unicellular photosynthetic algae—are promising natural sources of nanostructured silica. These microorganisms produce in their membrane approximately a highly ordered porous cell wall called a frustule as protection from environmental stress. Diatom frustules consist of hydrated silica that show peculiar properties including biocompatibility, tailorable surface chemistry, chemical inertness, and thermal stability. Frustules harvested from aquatic ecosystems or diatomaceous fossil sediments represent an excellent cost-effective source of biosilica for a broad range of biomedical applications. The porous ultrastructure of the frustules displays a large surface area available for coating with various biomolecules through different functionalization methods. In this review article, we highlight the main features of diatom biosilica and present some of the most advantageous properties that support the employment of frustules in the field of drug delivery, biosensing, and regenerative medicine. In particular, it is offered an insight into the most common functionalization strategies through which diatom physicochemical properties can be modified and tailored according to the described field of application.
Collapse
|
39
|
Yan S, Liu C, Fang S, Ma J, Qiu J, Xu D, Li L, Yu J, Li D, Liu Q. SERS-based lateral flow assay combined with machine learning for highly sensitive quantitative analysis of Escherichia coli O157:H7. Anal Bioanal Chem 2020; 412:7881-7890. [DOI: 10.1007/s00216-020-02921-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 08/13/2020] [Accepted: 08/27/2020] [Indexed: 10/23/2022]
|
40
|
Huynh KH, Pham XH, Hahm E, An J, Kim HM, Jo A, Seong B, Kim YH, Son BS, Kim J, Rho WY, Jun BH. Facile Histamine Detection by Surface-Enhanced Raman Scattering using SiO 2@Au@Ag Alloy Nanoparticles. Int J Mol Sci 2020; 21:E4048. [PMID: 32516981 PMCID: PMC7311956 DOI: 10.3390/ijms21114048] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/28/2020] [Accepted: 06/03/2020] [Indexed: 12/22/2022] Open
Abstract
Histamine intoxication associated with seafood consumption represents a global health problem. The consumption of high concentrations of histamine can cause illnesses ranging from light symptoms, such as a prickling sensation, to death. In this study, gold-silver alloy-embedded silica (SiO2@Au@Ag) nanoparticles were created to detect histamine using surface-enhanced Raman scattering (SERS). The optimal histamine SERS signal was measured following incubation with 125 μg/mL of SiO2@Au@Ag for 2 h, with a material-to-histamine solution volume ratio of 1:5 and a phosphate-buffered saline-Tween 20 (PBS-T) solvent at pH 7. The SERS intensity of the histamine increased proportionally with the increase in histamine concentration in the range 0.1-0.8 mM, with a limit of detection of 3.698 ppm. Our findings demonstrate the applicability of SERS using nanomaterials for histamine detection. In addition, this study demonstrates that nanoalloys could have a broad application in the future.
Collapse
Affiliation(s)
- Kim-Hung Huynh
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Xuan-Hung Pham
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Eunil Hahm
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Jaehyun An
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Hyung-Mo Kim
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Ahla Jo
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Bomi Seong
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Yoon-Hee Kim
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Byung Sung Son
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Jaehi Kim
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| | - Won-Yeop Rho
- School of International Engineering and Science, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si, Jeollabuk-do 54896, Korea;
| | - Bong-Hyun Jun
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 143-701, Korea; (K.-H.H.); (X.-H.P.); (E.H.); (J.A.); (H.-M.K.); (A.J.); (B.S.); (Y.-H.K.); (B.S.S.); (J.K.)
| |
Collapse
|
41
|
Knežević S, Ognjanović M, Nedić N, Mariano JF, Milanović Z, Petković B, Antić B, Djurić SV, Stanković D. A single drop histamine sensor based on AuNPs/MnO2 modified screen-printed electrode. Microchem J 2020. [DOI: 10.1016/j.microc.2020.104778] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|
42
|
Danchuk AI, Komova NS, Mobarez SN, Doronin SY, Burmistrova NA, Markin AV, Duerkop A. Optical sensors for determination of biogenic amines in food. Anal Bioanal Chem 2020; 412:4023-4036. [PMID: 32382967 PMCID: PMC7320057 DOI: 10.1007/s00216-020-02675-9] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 04/07/2020] [Accepted: 04/21/2020] [Indexed: 12/20/2022]
Abstract
This review presents the state-of-the-art of optical sensors for determination of biogenic amines (BAs) in food by publications covering about the last 10 years. Interest in the development of rapid and preferably on-site methods for quantification of BAs is based on their important role in implementation and regulation of various physiological processes. At the same time, BAs can develop in different kinds of food by fermentation processes or microbial activity or arise due to contamination, which induces toxicological risks and food poisoning and causes serious health issues. Therefore, various optical chemosensor systems have been devised that are easy to assemble and fast responding and low-cost analytical tools. If amenable to on-site analysis, they are an attractive alternative to existing instrumental analytical methods used for BA determination in food. Hence, also portable sensor systems or dipstick sensors are described based on various probes that typically enable signal readouts such as photometry, reflectometry, luminescence, surface-enhanced Raman spectroscopy, or ellipsometry. The quantification of BAs in real food samples and the design of the sensors are highlighted and the analytical figures of merit are compared. Future instrumental trends for BA sensing point to the use of cell phone-based fully automated optical evaluation and devices that could even comprise microfluidic micro total analysis systems.
Collapse
Affiliation(s)
- Alexandra I Danchuk
- Institute of Analytical Chemistry, Chemo and Biosensors, University of Regensburg, 93040, Regensburg, Germany.,Institute of Chemistry, Saratov State University, Saratov, Russian Federation, 410012
| | - Nadezhda S Komova
- Institute of Analytical Chemistry, Chemo and Biosensors, University of Regensburg, 93040, Regensburg, Germany.,Institute of Chemistry, Saratov State University, Saratov, Russian Federation, 410012
| | - Sarah N Mobarez
- Institute of Analytical Chemistry, Chemo and Biosensors, University of Regensburg, 93040, Regensburg, Germany
| | - Sergey Yu Doronin
- Institute of Chemistry, Saratov State University, Saratov, Russian Federation, 410012
| | - Natalia A Burmistrova
- Institute of Chemistry, Saratov State University, Saratov, Russian Federation, 410012
| | - Alexey V Markin
- Institute of Chemistry, Saratov State University, Saratov, Russian Federation, 410012
| | - Axel Duerkop
- Institute of Analytical Chemistry, Chemo and Biosensors, University of Regensburg, 93040, Regensburg, Germany.
| |
Collapse
|
43
|
Dielectric Nanoparticles Coated upon Silver Hollow Nanosphere as an Integrated Design to Reinforce SERS Detection of Trace Ampicillin in Milk Solution. COATINGS 2020. [DOI: 10.3390/coatings10040390] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Surface-enhanced Raman scattering (SERS) technique is competent to trace detection of target species, down to the single molecule level. The detection sensitivity is presumably degraded by the presence of non-specific binding molecules that occupy a SERS-active site (or hot spot) on the substrate surface. In this study, a silver hollow nano-sphere (Ag HNS) with cavity has been particularly designed, followed by depositing dielectric nanoparticles (Di NPs) upon Ag HNS. In the integrated nanostructures, Di NPs/Ag HNS were furthermore confirmed by cutting through the cross sections using the Focused Ion Beam (FIB) technique, which provides the Scanning Electron Microscope (SEM) with Energy-dispersive Spectroscope (EDS) mode for identifying the distribution of Di NPs upon Ag HNS. The results have indicated that Di NPs/Ag HNS exhibits small diameter of cavity, and among Di NPs in this study, Al2O3 with lower dielectric constant provides a much higher SERS enhancement factor (e.g., ~6.2 × 107). In this study, to detect trace amounts (e.g., 0.01 ppm) of Ampicillin in water or milk solution, Al2O3 NPs/Ag HNS was found to be more efficient and less influenced by non-specific binding molecules in milk. A substrate with integrated plasmonic and dielectric components was designed to increase the adsorption of target species and to repulse non-specific binding molecules from SERS-active sites.
Collapse
|
44
|
Sivashanmugan K, Zhao Y, Wang AX. Tetrahydrocannabinol Sensing in Complex Biofluid with Portable Raman Spectrometer Using Diatomaceous SERS Substrates. BIOSENSORS 2019; 9:E125. [PMID: 31615082 PMCID: PMC6955980 DOI: 10.3390/bios9040125] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 10/04/2019] [Accepted: 10/11/2019] [Indexed: 02/07/2023]
Abstract
Using thin-layer chromatography in tandem with surface-enhanced Raman spectroscopy (TLC-SERS) and tetrahydrocannabinol (THC) sensing in complex biological fluids is successfully conducted with a portable Raman spectrometer. Both THC and THC metabolites are detected from the biofluid of marijuana-users as biomarkers for identifying cannabis exposure. In this article, ultra-sensitive SERS substrates based on diatomaceous earth integrated with gold nanoparticles (Au NPs) were employed to detect trace levels of cannabis biomarkers in saliva. Strong characteristic THC and THC metabolite SERS peaks at 1601 and 1681 cm-1 were obtained despite the moderate interference of biological molecules native to saliva. Urine samples were also analyzed, but they required TLC separation of THC from the urine sample to eliminate the strong influence of urea and other organic molecules. TLC separation of THC from the urine was performed by porous microfluidic channel devices using diatomaceous earth as the stationary phase. The experimental results showed clear separation between urea and THC, and strong THC SERS characteristic peaks. Principal component analysis (PCA) was used to analyze the SERS spectra collected from various THC samples. The spectra in the principal component space were well clustered for each sample type and share very similar scores in the main principal component (PC1), which can serve as the benchmark for THC sensing from complex SERS spectra. Therefore, we proved that portable Raman spectrometers can enable an on-site sensing capability using diatomaceous SERS substrates to detect THC in real biological solutions. This portable THC sensing technology will play pivotal roles in forensic analysis, medical diagnosis, and public health.
Collapse
Affiliation(s)
- Kundan Sivashanmugan
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA.
| | - Yong Zhao
- School of Electrical Engineering, The Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Yanshan University, Qinhuangdao 066004, China.
| | - Alan X Wang
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, USA.
| |
Collapse
|