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Sesame oil is a kind of vegetable oil, which is loved by people all over the world due to its unique aroma, edible and medicinal value. Driven by interests, counterfeit and shoddy sesame oil products often appear on the market. This study is based on the color change caused by the competitive coordination of Zn2 + at the phase interface between four polyphenol dyes (Alizarin Red S, bromocatechol red, pyrogallol red and catechol violet) and volatile authenticity markers (VAM) in sesame oil. The DD-SIMCA model was constructed based on the RGB values of each sensing point after the reaction of real sesame oil and adulterated sesame oil with four polyphenol dyes. The results of the DD-SIMCA classification model show that the accuracy of sesame oil classification can reach 100%, and the result of the array sensor is much better than that of the single dye. Furthermore, the PLSR quantitative analysis model is used to verify that the RGB value obtained by the sensor is linearly related to the adulteration concentration. Therefore, this study established a visual array sensor for rapid authenticate of sesame oil adulteration based on the flavor compounds. [Display omitted] • Targeted identification of sesame oil adulteration based on its volatile compounds. • A four channel array sensor was developed to detect the authenticity of sesame oil. • This sensor is based on the competitive coordination of dyes and sesame oil to Zn2+. • Based on DD-SIMCA, the authenticity of sesame oil can be authenticated. • This work provides a new method for visual instrument free detection of sesame oil. [ABSTRACT FROM AUTHOR]

[Display omitted] • We developed a colorimetric biosensor to detect glucose and H 2 O 2. • The sensor is based on the peroxidase activities of nanoporphyrin and bromine. • This peroxidase activity is based on electron transfer of porphyrin and Br−. • The detection limits for glucose and H 2 O 2 were 0.15 and 0.5 μmol L−1. • Recovery ratios of spiked human serum and saliva samples were 100 % ± 10 %. Peroxidase is a popular amplifier of biosensor signals, but its application is limited by chemical instability and expensive purification. We developed a sensitive, novel colorimetric biosensor to detect glucose and hydrogen peroxide (H 2 O 2) using Zinc tetrakis (4-pyridinyl) porphyrin (ZnTPyP)-dodecyl trimethyl ammonium bromide (DTAB) nanoparticles (NPs) as peroxidase-like catalysts. ZnTPyP-DTAB NPs can oxidize colorless 3, 3', 5, 5'-tetramethylbenzidine to a blue product (652 nm) in the presence of H 2 O 2 via electron transport between porphyrin and bromine. This peroxidation mechanism was further verified using quantum chemical calculations. The detection limits of the colorimetric ZnTPyP-DTAB NP sensor were 0.15 and 0.5 μmol L−1 for glucose and H 2 O 2 , respectively, and the linear range was 3–70 and 8–50 μmol L−1, respectively. Recovery ratios of the biosensor in spiked human serum and saliva samples were 100 % ± 10 %. This simple method is robust, color stable, and reliable, thus providing an effective colorimetric biosensing platform for biomedical diagnosis. [ABSTRACT FROM AUTHOR]

A rapid and accurate analysis of food quality and safety is essential for human safety and health. Optical sensors based on nanomaterials and nano-effects offer fast detection, simple operation, low cost, high specificity, and sensitivity, and therefore are widely used for food analysis. A variety of nanomaterials, including quantum dots, nano-porphyrin, nano-gold, nano-silver, upconversion nanoparticles, nanozymes, metal oxide nanomaterials and organic fluorescent molecules-based nanomaterials were successfully used as active components for optical sensors to detect harmful food contaminants as well as for quality and authenticity analyses. Most of these nano-sensors rely on either optical instruments or visual colorimetric detection. This paper reviews the detection mechanisms of nanomaterial-based optical sensors as well as the enhancement mechanisms of their specificity and sensitivity. Properties of various optically active nanomaterials, as well as detailed applications of these nano-sensors, are deliberated as well. Despite a variety of optical nanosensors reported in the literature for various applications, including rapid detection of food contaminants, quality and authenticity, their commercialization is still in its infancy stage. [ABSTRACT FROM AUTHOR]

As a traditional and authentic Chinese medicinal material, Chrysanthemum morifolium (CM) has an excellent pharmacological effect. However, it is not easy to trace its origin at present, especially through visualization methods. Herein, Au nanoclusters (AuNCs) were successfully synthesized and combined with Al3 + to form Al@AuNCs complexes through the aggregation-induced fluorescence enhancement (AIE) effect, which was used to construct a visual sensor for the rapid identification of CM. Further studies revealed that 3-hydroxylflavonoid derivatives in CM actively competed with AuNCs for Al3 + through an excited-state intramolecular proton transfer (ESIPT) effect during the recognition process and flavonoids could effectively quench the fluorescence of AuNCs. Consequently, CM of different origins could produce fluorescence of various colors from red to green to produce a rapid visual differentiation effect. Finally, using the PLSDA method in chemometrics, it was proven that the accuracy of CM recognition can be increased from 93.10% and 46.15–100%. [Display omitted] • 3-hydroxy flavonoid derivative binds to Al3+ via ESIPT and produces fluorescence. • The origin of Chrysanthemum morifolium can be rapidly identified by one-step reaction. • Chrysanthemum morifolium in different origins displays fluorescence from red to green. • This sensor is suitable for other samples rich in 3-hydroxyl flavonoid derivatives. [ABSTRACT FROM AUTHOR]

Atractylodis Macrocephalae Rhizoma (AMR) is a bulk herbal foods, which can invigorate spleen and supplement Qi to help health. The accurate identification of the authenticity and origin of AMR is a prerequisite for the safe use and quality control. Herein, a dual-channel colorimetric sensor based on metal ions mediated color transformation of gold nanoparticles (AuNPs) was constructed to identify the authenticity and origin of AMR. The Ag+ / cetyltrimethylammonium chloride modified AuNPs (CTAC-AuNPs) sensing channel and Cr3+ / trisodium citrate modified AuNPs (TCA-AuNPs) sensing channel were rationally designed based on two mechanisms that are the silver deposition and the induced aggregation, respectively. When AMR extracts from different origins or its counterfeits were added to the colorimetric sensor, significantly different terpenoids in extracts can bind to Ag+ or Cr3+ to produce different color transformations. AMR samples from three origins (Zhejiang, Hunan and Anhui) and the counterfeit samples (Gynura japonica (Thunb.) Juel., and Atractylodis Rhizoma) were all accurately classified using the dual-channel colorimetric sensor combined with PLSDA. Our sensor has obvious advantages of simple and instrument-free analysis procedure, which will provide a new idea for the convenient identification of AMR and other herbal foods. [Display omitted] • AuNPs-based dual-channel colorimetric sensor for identifying AMR and its origin. • Two color change systems of AuNPs mediated by Ag+ and Cr3+ were developed in sensor. • The complexation between extracts and metal ions resulted in different color changes. • AMR authenticity and origin can be accurately identified by naked eye or PLSDA. • This method is convenient, accurate and instrument-free, suitable for on-site assay. [ABSTRACT FROM AUTHOR]

In this work, we constructed a machine learning-assisted dual-channel visual sensor array for identifying the origin of Lilium bulbs (BH). Nanogold clusters (AuNCs) and quantum dots (QDs) were selected and combined into sensor arrays. The amino acids existed in lilium bulbs could induce aggregation-induced fluorescence enhancement effect (AIEE) of AuNCs through hydrogen bonding. The hydrogen protons released from the amino acids and phenolic acids could interact with the COO- group of QDs, resulting in aggregation-caused quenching (ACQ) of QDs. Due to the different contents of amino acids and phenolic acids in BH from different origins, the sensor array can produce distinct and different fluorescent colors, such as red, blue, green and purple. In conjunction with pattern recognition by the RF model, the sensor array clearly identifies the origin of BH with 94.4% prediction accuracy. The visual sensor array constructed in this work exhibited the advantages of simplicity, speed, accuracy and portability, showing potential application prospects in identifying the origin of food and traditional Chinese medicine. [Display omitted] • A novel visual sensor array method was constructed for tracing BH origins. • The amino acids in BH could induce AIEE effect of AuNCs through hydrogen bonding. • The protonation and ET effect induced the ACQ of NAC-QDs. • The accuracy of BH origin identification based on dual-channel visual data was 94.4%. [ABSTRACT FROM AUTHOR]

Chrysanthemi Flos (Hangbaiju) is a traditional Chinese medicine and the third most popular beverage after Chinese tea and coffee, but there are geographical confusion and quality control problems in its market distribution. Here, we constructed an Fe3+-mediated fluorescence nanosensing system for the visual identification of Hangbaiju from different origins and the prediction of compounds content, which were verified by HPLC–HRMS. The formation of Fe3+@QDs was the main element of the method under electron transfer (ET) effects, as well as the presence of 1) chelation-quenched fluorescence (CHQF) effects, 2) homogeneous fluorescence resonance energy transfer (Homo-FRET), and 3) the TURN OFF/ON reaction pattern, between caffeic acid and its derivatives (CAs), Fe3+, QDs, flavonoids, and Fe3+@QDs, demonstrated by various characterization methods and density flooding theory (DFT). The visualisation appears green when the sample is high in CAs, red when high in flavonoids, and grey when low in both compounds. The random forest (RF) model based on spectral and visualisation data had an origin identification accuracy of 100 % and 93.33 %, respectively. Eight compounds content prediction based on RF models also showed good results. The best Rp and prediction errors of spectral and visual data were 0.97 and 0.95, 13 % and 12 %, respectively. [Display omitted] • A Fe3+-mediated visual sensor was constructed using quantum dots and chemometrics. • The sensor can predict the content of compounds and identify the origin of Hangbaiju. • Three recognition mechanisms among polyphenol, Fe3+, and sensor were demonstrated. • The accuracy of the origin identification based on visual data was 93.33 %. • The prediction error of the main compound content based on visual data was <17 %. [ABSTRACT FROM AUTHOR]

Citri Reticulatae Pericarpium (CRP) is a medicinal and food homolog commonly used in Chinese medicine. The quality, price, and content of dihydroflavones (DHFs) and polymethoxyflavones (PMFs) in CRP are directly related to their origin. A novel, fast, and simple visual discrimination method for the origin of CRP is presented here. Al3+ and bovine serum albumin/thiosalicylic acid-modified Ag nanoclusters (BSA/TSA-AgNCs) were screened as fluorescent sensors for targeting DHFs and PMFs, respectively. After 60 batches of CRP extracts from different origins reacted with Al3+ or AgNCs sensors, three types of CRP origin could be discriminated accurately by the naked eye or using partial least squares discriminant analysis (PLSDA), according to the significant differences in fluorescence color. It showed a good discrimination effect when applied to filter-paper-based detection. The sensoring mechanism can be the DHFs in CRP form a complex with Al3+, which increases the molecular conjugation and structural rigidity, resulting in a fluorescence enhancement effect. PMFs are more likely to enter the BSA shell of AgNCs owing to hydrophobic interactions and transfer electrons with TSA modified on the surface of AgNCs, resulting in the photoinduced electron transfer (PET) effect and aggregation of TSA-AgNCs, which eventually leads to fluorescence quenching. [Display omitted] • A novel visual fluorescent sensing method for discrimination of CRP origins. • Al3+ and BSA/TSA-AgNCs were selected as sensors for DHFs and PMFs respectively. • CRC, CRD and CRB could be discriminated accurately by either naked eyes or PLSDA. • This method is easy, fast, accurate and instrument-free, suitable for on-site assay. [ABSTRACT FROM AUTHOR]

Heavy metal pollution has gradually become one of the most serious problems in global environmental pollution and can invade the environment, food, and medicine, eventually causing irreversible damage to the human body. Herein, we construct a multichannel visual fluorescence array sensor based on N-doped carbon dots (NCDs) and gold nanocluster (AuNCs). The sensor comprehensively considered the aggregation-induced enhanced fluorescence (AIE) effect of AuNCs, the electron transfer (ET) effect of NCDs, and the fluorescence resonance energy transfer (FRET) effect of AuNCs@NCDs. It was further combined with PLSDA and PLSR to realize rapid and accurate detection of multiple metal ions in tap water, traditional Chinese medicine (TCM), and soil. The LODs of Cd2+, Pb2+, and Hg2+ were 0.15 μmol/L, 0.20 μmol/L and 0.09 μmol/L, respectively. Simultaneously, we proposed an adjustable fluorescence spectral logic device to meet the different determination requirements towards heavy metals. The analysis result of metal ions can be directly achieved by the four output types, NOT (0, 0, 0), Cd2+ (1, 1, 0), Pb2+ (1, 0, 0) and Hg2+ (0, 0, 1). More interestingly, Cd2+ and Pb2+ can be removed by simple centrifugation or sedimentation, which can be observed through the Tyndall effect. Accordingly, we not only constructed the sensing method of multiple metal ions but also proposed a new strategy for future research on the migration of heavy metal ions from complex environments to TCM. • Develop a three-channel array sensing for the detection of Cd2+, Pb2+, and Hg2+. • Successful applied to visual detection of various heavy metals in complex samples. • A logic device was designed to quickly discriminate between different metal ions. • Cd2+ and Pb2+ can produce Tyndall effect with AuNCs and be removed by centrifugation. [ABSTRACT FROM AUTHOR]

• A colorimetric sensor for white spirit based on Ag deposition of AuNRs was proposed. • The colorimetric response was correlated with the inhibition of Ag deposition. • The sensor array consisted of different AuNRs under different reductants. • The discrimination performance was assessed by LC–MS untargeted approach. The rapid and effective discrimination of Chinese white spirits is of great significance for quality control in the white spirit industry. Herein, we proposed a colorimetric sensor for white spirits based on silver deposition on gold nanorods (AuNRs), which were formed by reducing silver ions to Ag nanoshells on the surface of the AuNRs by different reductants containing hydroxyl or amino groups. The degree of inhibition of silver deposition was demonstrated to be strongly associated with the various components of white spirits, such as organic acids, aldehydes, ketones, and esters, which resulted in color differences and a consequent colorimetric response for different types of white spirits. The color differences could be recognized using principal component analysis (PCA), hierarchical cluster analysis (HCA), and linear discriminant analysis (LDA). The colorimetric sensor array was constructed by designing AuNRs with four different morphologies by utilizing different reducing agents to not only successfully distinguish various types of white spirits, including twelve types of strong-aroma-type spirits with similar flavor characteristics and different aroma-type spirits, but also to determine the concentration of the main ingredients affecting the quality of white spirits with a satisfactory linear range. Notably, the discriminating ability of the colorimetric sensor arrays was equal or superior than that of the untargeted metabolomic approach based on liquid chromatography-mass spectrometry. This sensing strategy, with facile preparation, fast response, excellent discrimination and high-throughput signal output, provides a promising application platform for real-time quality monitoring of white spirits and other alcoholic beverages. [ABSTRACT FROM AUTHOR]

• Colorimetric paper sensor array based on three color-emission QDs was established. • Production process and quality of basic liquors of Baijiu can be well monitored. • The sensor required neither special modification nor complex sample preparation. • The sensor only use a simple device and small amount of basic liquor samples. Process analysis of basic liquors of Baijiu is a great challenge in industry due to the complexity fermentation processes and tiny product differentiation of basic liquors. In this work, a new triple channel colorimetric paper sensor array based on quantum dots (QDs) with three color-emission was established for the rapid process monitoring of basic liquors of Baijiu. The fluorescence of QDs can be quenched to varying degrees by the ingredients in basic liquors with different production processes, batches and qualities. Through analyzing color change (RGB value) of QDs under the UV lamp, all the corresponding information that represents basic liquors of Baijiu was extracted and further processed by principal component analysis and partial least squares discriminant analysis. By utilizing this colorimetric paper sensor array, all the production processes, batches and qualities of basic liquors can be monitored quickly and accurately with a recognition rate of 100%. What's more, this paper sensor array required neither special modification nor complex sample preparation and can implement rapid and precise visualization analysis by the naked eye with the aid of a portable UV lamp using only a simple device and small amount of sample, showing its potential applications in the food industry. [ABSTRACT FROM AUTHOR]