| 1. |
- Barimah, Alberta Osei, et al.
(författare)
-
Sensitive label-free Cu2O/Ag fused chemometrics SERS sensor for rapid detection of total arsenic in tea
- 2021
-
Ingår i: Food Control. - : Elsevier. - 0956-7135 .- 1873-7129. ; 130
-
Tidskriftsartikel (refereegranskat)abstract
- Arsenic (As) is one of the toxic, persistent, and lethal heavy metalloids and requires rapid, less costly, and sensitive detection methods. This study proposed a label-free cuprous oxide/silver (Cu2O/Ag) surface-enhanced Raman scattering (SERS) nanoprobe to detect total As in tea. Different total As spiked tea concentrations were mixed with the Cu2O/Ag SERS nanoprobe for the SERS detection. Quantitative models were established for predicting the total As in tea by comparatively applying chemometric algorithms. Amongst the algorithms, competitive adaptive reweighted sampling partial least squares (CARS-PLS) optimized the most effective spectral variables to predict the total As in tea efficiently. The CARS-PLS gave the highest correlation coefficient value (R-p = 0.9935), very low root means square error (RMSEP = 0.0496 mu g g(-1)) in the prediction set and recorded the highest RPD value of 8.819. The proposed nanoprobe achieved a lower detection limit (0.00561 mu g g(-1)), excellent selectivity, satisfactory reproducibility, and stability. No significant difference was recorded when the performance of the Cu2O/Ag total As SERS sensor was compared with the inductively coupled plasma mass spectrometry (ICP-MS) method. Therefore, this developed Cu2O/Ag coupled chemometrics SERS sensing method could be used to efficiently determine, quantify, and predict total As in tea to promote monitoring of heavy metal contaminants.
|
|
| 2. |
- Guo, Zhiming, et al.
(författare)
-
Detection of Heavy Metals in Food and Agricultural Products by Surface-enhanced Raman Spectroscopy
- 2023
-
Ingår i: Food reviews international (Print). - : Taylor & Francis Group. - 8755-9129 .- 1525-6103. ; 39:3, s. 1440-1461
-
Forskningsöversikt (refereegranskat)abstract
- Heavy metals accumulating in the human body produce physiological toxicity by interfering with the transport of human proteins and enzymes. Heavy metals detection is significant for food safety assurance. This review focuses on recent advances of heavy metals detection of food and agricultural products by surface-enhanced Raman spectroscopy (SERS). The article covers the SERS basic principles and advances in heavy metals detection, including mercury, arsenic, cadmium, lead, chromium among others. Insights in the potential of combining chemometrics and multivariate analysis with SERS and the exploration of novel SERS substrate platforms from both macro and micro scale are discussed. Finally, future application of SERS in heavy metal detection are prospected. SERS is a powerful and promising technique offering the advantages of simple sampling, rapid data collection and non-invasiveness. The findings of this study can allow better understanding of the heavy metals' occurrence and the possibility of its detection using SERS.
|
|
| 3. |
- Guo, Zhiming, et al.
(författare)
-
Determination of lead in food by surface-enhanced Raman spectroscopy with aptamer regulating gold nanoparticles reduction
- 2022
-
Ingår i: Food Control. - : Elsevier. - 0956-7135 .- 1873-7129. ; 132
-
Tidskriftsartikel (refereegranskat)abstract
- Lead ion (Pb2+) is a main heavy metal in food that causes heavy teratogenicity and carcinogenicity. In this study, a rapid and sensitive SERS method for detecting Pb2+ in food was established by aptamer regulating gold nanoparticles reduction. The reduction of HAuCl4 catalyzed by H2O2 is a slow process, and graphene oxide (GO) has excellent catalytic performance for the reaction, which enabled the system to generate gold nanoparticles (AuNPs) with high Raman activity. When the aptamer was introduced into the system, its binding with GO reduced the reaction speed. Upon adding Pb2+ to the system, the aptamer preferentially combined with Pb2+ and GO was released to accelerate the AuNPs production. The concentration of the AuNPs was proportional to the intensity of the added Raman signal molecule 4-MBA and the main Raman peak of Pb2+ appeared at 1595.80 cm(-1). The ability of a novel aptamer (M4-16) and traditional aptamers (T30695, TBA) for Pb2+ determination was compared, and the concentration of the aptamer, HAuCl4 and heating time were optimized to build optimal detection system. After several pretreatment of the original SERS spectroscopy, combined with the comparison of various models, the first-order derivative preprocessing combined with competitive adaptive reweighted sampling model achieved the best performance (R-c = 0.9966, R-p = 0.9972), the detection limit for Pb2+ was 0.1 mu g L-1. The combination of SERS technology and chemometrics is a promising method that could be used to achieve rapid and highly sensitive detection of Pb2+ in food.
|
|
| 4. |
- Guo, Zhiming, et al.
(författare)
-
Determination of perchlorate in tea using SERS with a superhydrophobically treated cysteine modified silver film/polydimethylsiloxane substrate
- 2021
-
Ingår i: Analytical Methods. - : Royal Society of Chemistry. - 1759-9660 .- 1759-9679. ; 13:13, s. 1625-1634
-
Tidskriftsartikel (refereegranskat)abstract
- Perchlorate is a new type of persistent pollutant, which interferes with the synthesis and secretion of thyroxine and affects human health. The EU's limit for perchlorate in tea is 750 mu g kg(-1). The surface-enhanced Raman scattering (SERS) technique has the characteristics of a simple pretreatment method, rapid detection, high sensitivity, high specificity and great stability in the detection of perchlorate. This study proposed a novel superhydrophobic SERS substrate, which can be used to detect perchlorate in tea. Firstly, a chemical deposition method was used to deposit a silver film on the surface of a thin layer of polydimethylsiloxane. After drying, the substrate was immersed in 1H,1H,2H,2H-perfluorodecyltriethoxysilane aqueous solution for 15 hours to make the surface of the substrate superhydrophobic. Then cysteine molecules were deposited on the surface of the silver film/polydimethylsiloxane by incubation. The superhydrophobic surface has a unique enrichment effect on the highly diluted solution, and perchlorate has a strong affinity for the amino group of cysteine. We collected the Raman spectra of 9 gradient concentrations (1-100 mu mol L-1) of perchlorate-spiked tea samples on the hydrophobic substrate, and a linear model of the relationship between the SERS spectral intensity and the concentrations of perchlorate in tea was established. This method reached a good limit of detection of 0.0067 mu mol L-1 (0.82 mu g kg(-1)) in tea, which showed that the developed sensor has high sensitivity and could be used as a fast and simple technique for quantitative detection of perchlorate based on SERS technology.
|
|
| 5. |
- Guo, Zhiming, et al.
(författare)
-
Rapid enrichment detection of patulin and alternariol in apple using surface enhanced Raman spectroscopy with coffee-ring effect
- 2021
-
Ingår i: Lebensmittel-Wissenschaft + Technologie. - : Elsevier. - 0023-6438 .- 1096-1127. ; 152
-
Tidskriftsartikel (refereegranskat)abstract
- Patulin (PAT) and alternariol (AOH) are the main mycotoxin contaminants in fruits and their products, which have great toxic effects on human body due to their teratogenicity and carcinogenicity. This study proposed a surface enhanced Raman spectroscopy (SERS) technology combining chemometrics and coffee-ring effect to build high-throughput label-free detection models for PAT and AOH. A stable coffee ring structure was built by optimizing the drying temperature and droplet volume. Comparing the partial least squares (PLS) models grounded on variables selection method, the best performance was obtained by using synergy interval (Si) and genetic algorithm (GA) for PAT (R-c = 0.9905, R-p = 0.9759) and AOH (R-c = 0.9829, R-p = 0.9808), respectively. The limits of detection (LOD) for PAT and AOH were as low as 1 mu g L-1, and the recovery rates were 92.80%-114.83% with relative standard deviation (RSD) = 4.86 for PAT and 82.06%-108.13% with RSD <= 2.28% for AOH. The SERS technology combined with chemometrics and coffee-ring effect holds promise for high-throughput label-free detection of PAT and AOH in fruits and their products.
|
|
| 6. |
- Schneider, Lea, et al.
(författare)
-
The impact of proxy selection strategies on a millennium-long ensemble of hydroclimatic records in Monsoon Asia
- 2019
-
Ingår i: Quaternary Science Reviews. - : Elsevier BV. - 0277-3791 .- 1873-457X. ; 223
-
Tidskriftsartikel (refereegranskat)abstract
- Large-scale palaeoclimate reconstructions can be very sensitive to the proxy records they are based on, and hence to the criteria used to select proxy records. Data selection rarely follows objective criteria that are applicable to all types of proxies, including both low- and high-resolution records. Thus, there is a need for a uniform and transparent approach to assess the suitability of input proxy data for a reconstruction. Here, we develop classification criteria that are applicable to multiple proxy types and evaluate different selection strategies using a network of 62 millennium-long terrestrial hydroclimate proxy records from Monsoon Asia. Our results reveal that robust evidence for a coherent climate signal and high dating accuracy are important criteria for benchmarking the suitability of each proxy record. We determine these criteria by reviewing the literature for each record (rather than screening against instrumental data). We show that the proposed selection approach can yield a network with a stronger common signal. By evaluating the uncertainty and centennial variability of composite reconstructions, from differently selected subsets of the proxy network, it appears beneficial to use suitable proxies stemming from different archives, as well as having a dense network of proxy sites. We suggest that future large-scale palaeoclimate reconstructions might be improved by evaluating proxy networks according to the universal categories presented here and, if indicated, removing less suitable records. This will strengthen the climate signal in the final reconstruction, allowing more precise inferences about past climate variability and more robust comparisons with climate model simulations.
|
|
| 7. |
- Guo, Zhiming, et al.
(författare)
-
Chemometrics coupled 4-Aminothiophenol labelled Ag-Au alloy SERS off-signal nanosensor for quantitative detection of mercury in black tea
- 2020
-
Ingår i: Spectrochimica Acta Part A - Molecular and Biomolecular Spectroscopy. - : Elsevier BV. - 1386-1425 .- 1873-3557. ; 242
-
Tidskriftsartikel (refereegranskat)abstract
- Black tea like other food crops is prone to mercury ion (Hg2+) contamination right from cultivation to industrial processing. Due to the dangerous health effects posed even in trace contents, sensitive detection and quantification sensors are required. This study employed the surface-enhanced Raman scattering (SERS) enhancement property of 4-aminothiophenol (4-ATP) as a signal turn off approach functionalized on Ag-Au alloyed nanopartide to firstly detect Hg2+ in standard solutions and spiked tea samples. Different chemometric algorithms were applied on the acquired SERS and inductively coupled plasma-mass spectrometry (ICP-MS) chemical reference data to select effective wavelengths and spectral variables in order to develop models to predict the Hg2+. Results indicated that Ag-Au/4-ATP SERS sensor combined with ant colony optimization partial least squares (ACO-PLS) exhibited the best correlation efficient and minimum errors for Hg2+ standard solutions (R-c = 0.984, R-p = 0.974, RMSEC = 0.157 mu g/mL, RMSEP = 0.211 mu g/mL) and spiked tea samples (R-c = 0.979, R-p = 0.963, RMSEC = 0.181 mu g/g and RMSEP = 0210 mu g/g). The limit of detection of the proposed sensor was 4.12 x 10(-7) mu g/mL for Hg2+ standard solutions and 2.83 x 10(-5) mu g/g for Hg2+ spiked tea samples. High stability and reproducibility with relative standard deviation of 1.14% and 0.84% were detected. The potent strong relationship between the SERS sensor and the chemical reference method encourages the application of the developed chemometrics coupled SERS system for future monitoring and evaluation of Hg2+ in tea.
|
|
| 8. |
- Guo, Zhiming, et al.
(författare)
-
Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics
- 2020
-
Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 20:7
-
Tidskriftsartikel (refereegranskat)abstract
- It is crucial for the efficacy of the apple storage to apply methods like electronic nose systems for detection and prediction of spoilage or infection by Penicillium expansum. Based on the acquisition of electronic nose signals, selected sensitive feature sensors of spoilage apple and all sensors were analyzed and compared by the recognition effect. Principal component analysis (PCA), principle component analysis-discriminant analysis (PCA-DA), linear discriminant analysis (LDA), partial least squares discriminate analysis (PLS-DA) and K-nearest neighbor (KNN) were used to establish the classification model of apple with different degrees of corruption. PCA-DA has the best prediction, the accuracy of training set and prediction set was 100% and 97.22%, respectively. synergy interval (SI), genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) are three selection methods used to accurately and quickly extract appropriate feature variables, while constructing a PLS model to predict plaque area. Among them, the PLS model with unique variables was optimized by CARS method, and the best prediction result of the area of the rotten apple was obtained. The best results are as follows: Rc = 0.953, root mean square error of calibration (RMSEC) = 1.28, Rp = 0.972, root mean square error of prediction (RMSEP) = 1.01. The results demonstrated that the electronic nose has a potential application in the classification of rotten apples and the quantitative detection of spoilage area.
|
|
| 9. |
- Guo, Zhiming, et al.
(författare)
-
Identification of the apple spoilage causative fungi and prediction of the spoilage degree using electronic nose
- 2021
-
Ingår i: Journal of food process engineering. - : John Wiley & Sons. - 0145-8876 .- 1745-4530. ; 44:10
-
Tidskriftsartikel (refereegranskat)abstract
- Apple is resistant to storage, but it is susceptible to fungal infection during transportation and storage, resulting in serious losses after harvest. A convenient and nondestructive monitoring method for fungi-inoculated apples was proposed in this research. Four dominant spoilage fungi, including Aspergillus niger, Penicillium expansum, Penicillium chrysogenum, and Alternaria alternata, were inoculated on apple samples. The volatile information of samples with different degrees of spoilage was obtained by gas sensors. The pattern recognition methods were compared to classify the fungi and degrees of spoilage. Back propagation-artificial neural networks (BP-ANN) had the best identification model result with the highest recognition rates of 95.62 and 99.58% for fungi and spoilage degrees, respectively. The variable selection methods were employed, and variables of the gas sensors data for the prediction of apple spoilage area were optimized. The best prediction models of Aspergillus niger, Penicillium expansum, Penicillium chrysogenum, and Alternaria alternata were 0.854, 0.939, 0.909, and 0.918, respectively. The results show that the gas sensors can be used as a nondestructive technique in apple fungi infection evaluation. This proposed fruit spoilage detection technology is expected to provide a reference for the early detection of apple spoilage to promote food quality and safety inspection.Practical ApplicationsThis research used gas sensors to identify the four main spoilage fungi of apples and predicted the spoilage degree of apples using established prediction models. The apple spoilage detection method adopted in this research provides a reference for the early detection of fruit spoilage, which is helpful for apple storage and reduces the economic loss caused by corruption. It is an important measure to help ensure the economic benefits of apple and provide consumers with a large number of high-quality apple products.
|
|
| 10. |
- Guo, Zhiming, et al.
(författare)
-
Intelligent evaluation of taste constituents and polyphenols-to-amino acids ratio in matcha tea powder using near infrared spectroscopy
- 2021
-
Ingår i: Food Chemistry. - : Elsevier. - 0308-8146 .- 1873-7072. ; 353
-
Tidskriftsartikel (refereegranskat)abstract
- Matcha tea is rich in taste and bioactive constituents, quality evaluation of matcha tea is important to ensure flavor and efficacy. Near-infrared spectroscopy (NIR) in combination with variable selection algorithms was proposed as a fast and non-destructive method for the quality evaluation of matcha tea. Total polyphenols (TP), free amino acids (FAA), and polyphenols-to-amino acids ratio (TP/FAA) were assessed as the taste quality indicators. Successive projections algorithm (SPA), genetic algorithm (GA), and simulated annealing (SA) were subsequently developed from the synergy interval partial least squares (SiPLS). The overall results revealed that SiPLS-SPA and SiPLS-SA models combined with NIR exhibited higher predictive capabilities for the effective determination of TP, FAA and TP/FAA with correlation coefficient in the prediction set (Rp) of Rp > 0.97, Rp > 0.98 and Rp > 0.98 respectively. Therefore, this simple and efficient technique could be practically exploited for tea quality control assessment.
|
|
