Nano effect fluorescence visual sensor based on Au-AgNCs: A novel strategy to identify the origin and growth year of Lilium bulbs.

In this study, we developed a cost-effective fluorescence visual sensor strategy based on gold and silver nanocluster (Au-AgNCs) for the rapid identification of the origins and growth years of Lilium bulbs (LB). Au-AgNCs combined with catechins in LB produce aggregation-induced emission (AIE). The catechin content in LB of different origins and growth years varied, resulting in different fluorescence color responses of the sensor system. Furthermore, the RGB values of the fluorescent color were extracted, and the discriminant effect of visual visualisation was verified using the data-driven soft independent modelling of class analogy (DD-SIMCA) and partial least squares discriminant analysis (PLSDA) models. The results showed that the accuracy of DD-SIMCA for identifying LB origins and PLSDA for growth year identification was 100%. These results indicated that the established strategy could accurately identify the quality of LB, which has great potential for application in the rapid and visual identification of other foods.

Digital image colorimetry in combination with chemometrics for the detection of carbaryl based on the peroxidase-like activity of nanoporphyrins and the etching process of gold nanoparticles.

Carbaryl is a typical carbamate pesticide that plays an essential role in agricultural production, but its residues cause serious harm to the environment and human health. Here, we developed a polychromatic colorimetric sensor based on ZnTPyP-DTAB peroxidase activity and gold nano-bipyramids (Au NBPs) etching to detect carbaryl. ZnTPyP-DTAB catalyzes the decomposition of H2O2 to hydroxyl radicals, and Au NBPs are etched. The coordination of zinc and nitrogen in nanometer porphyrins was affected by the steric effects of carbaryl, which resulted in decreased activity of ZnTPyP-DTAB peroxidase. The detection limit of carbaryl was 0.26 mg/kg. The recoveries of carbaryl in reaal sample ranged from 91 % to 107% (RSD ≤ 0.7%). The sensor platform displayed a series of high-resolution multicolor variations of rainbow colors within the above concentration range. The rich color variation facilitates the acquisition of digital images. RGB value transformation combined with partial least squares regression model can accurately and quantitatively detect carbaryl in vegetables, fruits and Chinese medicinal materials.

Accurate identification of the geographical origins of lily using near-infrared spectroscopy combined with carbon dot-tetramethoxyporphyrin nanocomposite and chemometrics.

Near-infrared spectroscopy technique is a prevailing tool for quality control of foods and traditional Chinese medicines. However, it usually faced the problems of severe peak overlap, low classification accuracy and poor specificity. In this work, the potential of carbon dot-tetramethoxyporphyrin nanocomposite-based nano-effect near-infrared spectroscopy sensor combined with chemometric method was investigated for the accurate identification lily from different geographical origins. Partial least squares-discriminant analysis (PLS-DA) was used for differentiating geographical origins of lily based on the collected traditional and nano-effect near-infrared spectroscopy. Compared with traditional near-infrared spectroscopy, the nano-effect near-infrared spectroscopy obtains superior classification performance with 100% accuracy on the training and test set. The results showed that the proposed method based on near-infrared spectroscopy combined with nanocomposites and chemometrics could be considered as a promising tool for rapid discrimination of the authenticity of food and traditional Chinese medicine in the future.

Maillard reaction products and guaiacol as production process and raw material markers for the authentication of sesame oil.

BACKGROUND: Sesame oil has an excellent flavor and is widely appreciated. It has a higher price than other vegetable oils because of the high price of its raw materials, and different processing techniques also result in products of different quality levels, which can command different prices. In the market, there is a persistent problem of adulteration of sesame oil, driven by economic interests. The screening of volatile markers used to distinguish the authenticity of sesame oil raw materials and production processes is therefore very important. RESULTS: In this work, six markers related to the production processes and raw materials of sesame oil were screened by gas chromatography-tandem mass spectrometry (GC-MS/MS) combined with chemometric analysis. They were 3-methyl-2-butanone, 2-ethyl-5-methyl-pyrazine, guaiacol, 2,6-dimethyl-pyrazine, 5-methyl furfural, and ethyl-pyrazine. The concentration of these markers in sesame oil is between 10 and1000 times that found in other vegetable oils. However, only 3-methyl-2-butanone and 2-ethyl-5-methyl-pyrazine differed significantly as the result of the use of different production processes. Except for guaiacol, which was mainly derived from raw materials, the other five compounds mentioned above all result from the Maillard reaction during thermal processing. The six compounds mentioned above are sufficient to distinguish fraud involving sesame oil raw materials and production processes, and can identify accurately adulteration levels of 30% concentration. CONCLUSION: In this study, the classification markers can identify the adulteration of sesame oil accurately. These six compounds are therefore important for the authenticity of sesame oil and provide a theoretical basis for the rapid and accurate identification of the authenticity of sesame oil. © 2021 Society of Chemical Industry.

Fluorescent sensor based on quantum dots and nano-porphyrin for highly sensitive and specific determination of ethyl carbamate in fermented food.

BACKGROUND: Ethyl carbamate (EC) is a potentially toxic carcinogen produced during fermentation and storage of fermented foods, and many countries have set thresholds for its content in food. Therefore, sensitive, rapid and accurate detection of EC is meaningful to ensure the quality of fermented food. RESULTS: This study introduces a CdTe quantum dots/nano-5,10,15,20-tetrakis (4-methoxyphenyl)-porphyrin (nano TPP-OCH3 ) fluorescence sensor system detection of EC. The specificity of this sensing mainly relies on a photo-induced electron transfer and electrostatic force interaction between EC and nano TPP-OCH3 . This sensor presented a linear range of 10 to 1000 µg L-1 (R2  = 0.9903) with a low detection limit of 7.14 µg L-1 . Meanwhile, the recovery (91.19-101.09%) and precision [relative standard deviation (RSD) = 0.64-3.05%] of the sensor for the analysis of fermented food (yellow rice wine, soy sauce, Chinese spirits, Pu-erh tea) samples were good and could meet the requirements of practical detection. Moreover, the detection results of fermented food (yellow rice wine, soy sauce, Chinese spirits, Pu-erh tea) samples by this sensor are basically consistent with those of high-performance liquid chromatography with fluorescence detector (HPLC-FLD). CONCLUSION: This method was expected to provide a potential platform for sensitive and accurate detection of EC in food safety monitoring, which would provide knowledge of the flavor and quality related to fermented food. © 2021 Society of Chemical Industry.

A novel thioctic acid-carbon dots fluorescence sensor for the detection of Hg2+ and thiophanate methyl via S-Hg affinity.

Mercury ions and thiophanate methyl (TM), are common contaminants present in the environment and food products. These contaminants cause neurovirulence and carcinogenicity effect on the human body. Herein, thioctic acid-carbon dots (SCDs) was synthesized and applied in a fluorescent "turn-off-on" probe to detect Hg2+ and TM. The presence of other common metal ions and pesticides did not affect the response of the developed sensor. Further investigation revealed that the fluorescent "turn-off-on" model were static, wherein the "turn-off" was induced by an electron transfer effect, while the "turn-on" was caused by the formation of TM-Hg complexes. Under optimal conditions, the fluorescence sensor method exhibited limits of detection as low as 33.3 nmol/L and 7.6 nmol/L for Hg2+ and TM, respectively. The developed sensor was designed to detect Hg2+ and TM in real tap water, grape juice and Citri Reticulatae Pericarpium (CRP) water samples.

Determination of l-theanine in tea water using fluorescence-visualized paper-based sensors based on CdTe quantum dots/corn carbon dots and nano-porphyrin with chemometrics.

BACKGROUND: The quality of tea is influenced by numerous factors, especially l-theanine, which is one of the important markers used to evaluate the sweetness and freshness of tea. Sensitive, rapid, and accurate detection of l-theanine is therefore useful to identify the grade and quality of tea. RESULTS: A high-sensitivity, paper-based fluorescent sensor combined with chemometrics was established to detect l-theanine in tea water based on CdTe quantum dots / corn carbon dots and nano tetra pyridel-porphine zinc (ZnTPyP). To verify the reliability of this method, fluorescence spectra and fluorescence-visualized paper-based sensors were compared. The fluorescence spectrum method demonstrated a linear range of 1 to 10 000 nmol L-1 and a limit of detection (LOD) of 0.19 nmol L-1 . In the fluorescence-visualized paper-based sensors there was a linear range of 10-1000 nmol L-1 , and the LOD was 10 nmol L-1 . Partial least squares discriminant analysis (PLSDA) and partial least squares regression analysis (PLSR) were used successfully to determine l-theanine accurately in tea water with this approach. The accuracy of the PLSDA model was 100% both in the training set and the predicting set, and the correlation coefficient between the actual concentration and the predicted concentration was greater than 0.9997 in the PLSR model. CONCLUSION: This fluorescence-visualized paper-based sensor, combined with chemometrics, could be applied efficiently to the practical analysis of tea water samples, which provides a new idea to ensure the flavor and quality of tea. © 2020 Society of Chemical Industry.

A novel fluorescence sensing strategy based on nanoparticles combined with spectral splicing and chemometrics for the recognition of Citrus reticulata 'Chachi' and its storage year.

BACKGROUND: The fluorescence sensing method has been increasingly applied in food quality control because it is fast and sensitive. However, its application in quality evaluation is challenging. Using Citri Reticulatae Pericarpium (CRP; dried mandarin orange peel) as an example, we developed a simple and low-cost fluorescence sensing strategy based on nanoparticles combined with spectral splicing and chemometrics for quality evaluation. This method can recognize Citrus reticulata 'Chachi' (CRC) from other CRP cultivars and further identify the storage year. RESULTS: Nanogold particles and cadmium telluride quantum dots were selected as nanosensors and mixed with aqueous extracts of CRP separately to produce fluorescence quenching spectra. Then, a simple spectral splicing procedure was applied to obtain spliced spectra comprising different combinations of the self-fluorescence and fluorescence quenching spectra of CRP samples. With the aid of partial least-squares discriminant analysis, the new strategy achieved recognition rates of 100% in distinguishing CRC samples from other CRP samples, as well as recognition rates of 100% for the training set and 98.04% for the prediction set in the discrimination of the storage year of CRC. The recognition mechanism is dominated by interactions between the nanoparticles and the fluorescent components in the CRP samples, but other components also have concurrent effects. CONCLUSIONS: This novel fluorescence sensing strategy not only provides a new tool for the quality evaluation of CRC but also has good prospects for the authentication and traceability of other foods and herbs. Crucially, the developed method is convenient, simple and effective. © 2020 Society of Chemical Industry.