A smartphone-coalesced nanoprobe for high selective ammonia sensing based on the pH-responsive biomass carbon nanodots and headspace single drop microextraction

Fast real-time monitoring of meat freshness based on fluorescent sensing array and deep learning: From development to deployment

A fluorescent sensor array (FSA) combined with deep learning (DL) techniques was developed for meat freshness real-time monitoring from development to deployment. The array was made up of copper metal nanoclusters (CuNCs) and fluorescent dyes, having a good ability in the quantitative and qualitative detection of ammonia, dimethylamine, and trimethylamine gases with a low limit of detection (as low as 131.56 ppb) in range of 5 ∼ 1000 ppm and visually monitoring the freshness of various meats stored at 4 °C. Moreover, SqueezeNet was applied to automatically identify the fresh level of meat based on FSA images with high accuracy (98.17 %) and further deployed in various production environments such as personal computers, mobile devices, and websites by using open neural network exchange (ONNX) technique. The entire meat freshness recognition process only takes 5 ∼ 7 s. Furthermore, gradient-weighted class activation mapping (Grad-CAM) and uniform manifold approximation and projection (UMAP) explanatory algorithms were used to improve the interpretability and transparency of SqueezeNet. Thus, this study shows a new idea for FSA assisted with DL in meat freshness intelligent monitoring from development to deployment.

A sensitive sensor based on carbon dots for the determination of Fe3+ and ascorbic acid in foods

To develop a feasible, sensitive, and essential sensor is important for the identification of Fe3+ ions and ascorbic acid (AA). Herein, highly fluorescent heteroatom co-doped carbon dots (N,S-CDs) with a quantum yield (QY) of 24.6% were synthesized, using hydrothermal treatment of L-cysteine (Cys) and 1-amino-2-naphthol-4-sulfonic acid (ANSA). The fluorescence emission of the as-prepared N,S-CDs was quenched strongly by Fe3+ ions, and this was further recovered by the reduction effect of AA on Fe3+. Based on this, continuous fluorescence sensing of Fe3+ and AA with an "on-off-on" style was developed. The detection of Fe3+ and AA were in relatively wider linear ranges of 5.00-105 μmol L-1 and 4.97-54.8 μmol L-1, with a detection limit of 0.10 μmol L-1 and 2.4 nmol L-1 (S/N = 3), respectively. Then, the N,S-CDs were successfully used to measure Fe3+ ions and AA in some daily food samples, and this method exhibited some advantages over most other reported techniques in the term of response speed, quantum yield, and detection limit.

Assembly-Induced Emission of Copper Nanoclusters: Revealing the Sensing Mechanism for Detection of Volatile Basic Nitrogen in Seafood Freshness On-Site Monitoring

Total volatile basic nitrogen (TVB-N) is a vital indicator for assessing seafood freshness and edibility. Rapid on-site detection of volatile basic nitrogen (VBN) is of significant importance for food safety monitoring. In this study, highly luminescent self-assembled copper nanoclusters (Cu NCs@p-MBA), synthesized using p-mercaptobenzoic acid (p-MBA) as the ligand, were utilized for the sensitive detection of VBNs. Under acidic conditions, Cu NCs@p-MBA formed compact and well-organized nanosheets through noncovalent interactions, accompanied by intense orange fluorescence emission (651 nm). The benzene carboxylic acid part of Cu NCs@p-MBA provided the driving force for supramolecular assembly and exhibited a strong affinity for amines, particularly low-molecular-weight amines such as ammonia (NH3) and trimethylamine (TMA). The quantitative determination of NH3 and TMA showed the detection limits as low as 0.33 and 0.81 ppm, respectively. Cu NCs@p-MBA also demonstrated good responsiveness to putrescine and histamine. Through density functional theory (DFT) calculations and molecular dynamics (MD) simulations, the precise atomic structure, assembly structure, luminescent properties, and reaction processes of Cu NCs@p-MBA were studied, revealing the sensing mechanism of Cu NCs@p-MBA for highly sensitive detection of VBNs. Based on the self-assembled Cu NCs@p-MBA nanosheets, portable fluorescent labels were developed for semiquantitative, visual, and real-time monitoring of seafood freshness. Therefore, this study exemplified the high sensitivity of self-assembly induced emission (SAIE)-type Cu NCs@p-MBA for VBNs sensing, offering an efficient solution for on-site monitoring of seafood freshness.

Improving anion sensing ability of the indolocarbazole-based fluorescence turn-on sensor by increasing salicylaldehyde response unit

Detection abilities on tested subjects of sensors should be closely connected to the sensing unit numbers. Herein, two anion sensors ICZ-o-1S and ICZ-o-2S were synthesized by using indolo (2,3-a) carbazoles as fluorescent chromophore and salicylaldehyde as recognition site. Though UV-Vis and fluorescent ways, it demonstrated that F^- can induce the sensor solutions becoming colored from colorless to yellow green, and can endow them with bright green turn-on fluorescence, proving their sensitive and selective sensing on F^-. Accordingly, the F ion sensing studies including anti-interference abilities against to other anions on fluorescence response, stoichiometric ratios of sensor-F^- in 1 : 1 and 1 : 2, -OH deprotonation sensing mechanism confirmed by ¹H NMR titration and theoretical calculation were fully covered. Most importantly, fluoride ion detection limits achieved by ICZ-o-1S and ICZ-o-2S were 1.8 × 10^-7 M and 6.0 × 10^-8 M, respectively, the latter with two sensing units exhibited 3 times lower detection limit outcompeted to the former with only one sensing unit, rendering the sensor design strategy of improving detecting ability by increasing sensing unit number was rational. The practical application of F^- detection in water-containing environment calibrated from the standard curve between the fluorescence intensity of sensor-F^- system and the changing F^- concentration was conducted. In addition, the accuracy of the sensor on detecting F^- was evaluated by the spiked recovery experiment, therefore, the fast and convenient F^- concentration detection based on the fluorescence color RGB values of the tested sensor-sample mixture was investigated. Consequently, the results obtained by these two sensors should deliver effective supports on designing high-performance sensors featuring naked-eye and fluorescence turn-on anion sensing by altering the response unit numbers.

Biomass-Derived Carbon Dots and Their Sensing Applications

Carbon dots (CDs) can be widely used in the field of sensing because of its good water solubility, low toxicity, high fluorescence stability and excellent biocompatibility. It has become a popular trend to prepare high-value, inexpensive, renewable and environmentally friendly CDs sensors from biomass resources. This article reviewed the research progress of biomass-derived CDs as chemical, physical and biological sensors in recent years and studied their preparation processes and sensing abilities. Furthermore, the prospects and challenges of biomass-CDs sensors were discussed. This article is expected to provide inspirations for the design, preparation and application of biomass-CDs sensors in the future.

Quantitative Colorimetric Detection of Dissolved Ammonia Using Polydiacetylene Sensors Enabled by Machine Learning Classifiers

Easy-to-use and on-site detection of dissolved ammonia are essential for managing aquatic ecosystems and aquaculture products since low levels of ammonia can cause serious health risks and harm aquatic life. This work demonstrates quantitative naked eye detection of dissolved ammonia based on polydiacetylene (PDA) sensors with machine learning classifiers. PDA vesicles were assembled from diacetylene monomers through a facile green chemical synthesis which exhibited a blue-to-red color transition upon exposure to dissolved ammonia and was detectable by the naked eye. The quantitative color change was studied by UV-vis spectroscopy, and it was found that the absorption peak at 640 nm gradually decreased, and the absorption peak at 540 nm increased with increasing ammonia concentration. The fabricated PDA sensor exhibited a detection limit of ammonia below 10 ppm with a response time of 20 min. Also, the PDA sensor could be stably operated for up to 60 days by storing in a refrigerator. Furthermore, the quantitative on-site monitoring of dissolved ammonia was investigated using colorimetric images with machine learning classifiers. Using a support vector machine for the machine learning model, the classification of ammonia concentration was possible with a high accuracy of 100 and 95.1% using color RGB images captured by a scanner and a smartphone, respectively. These results indicate that using the developed PDA sensor, a simple naked eye detection for dissolved ammonia is possible with higher accuracy and on-site detection enabled by the smartphone and machine learning processes.

A Fluorescence Method Based on N, S-Doped Carbon Dots for Detection of Ammonia in Aquaculture Water and Freshness of Fish

Excessive ammonia can cause the death of fish and the eutrophication of the water environment, so ammonia detection is essential for environmental monitoring. In this study, a highly selective sensing strategy for ammonia detection based on N, S co-doped carbon dots (N, S-CDs) was developed. The as-prepared N, S-CDs exhibited excellent photoluminescence properties and fluorescent stability. N, S-CDs demonstrated fluorescence quenched in the presence of ammonia in the wide linear range of 2–80 mmol/L, and were highly selective towards ammonia over metal ions. Furthermore, a possible fluorescence quenching mechanism is proposed. N, S-CDs were further applied to detection of ammonia in aquaculture water samples and river water samples, showing good practicability with recoveries from 0.93 to 1.27 and relative standard deviations (RSDs) of 0.54% to 17.3%. N, S-CDs were also successfully used to determine the freshness of bighead carps.

Investigation into the predictive performance of colorimetric sensor strips using RGB, CMYK, HSV, and CIELAB coupled with various data preprocessing methods: a case study on an analysis of water quality parameters

The potential use of colorimetric sensors has received significant attention due to its feasibility for use in various applications. After reacting with a sample, the image of the colorimetric sensor can be captured and converted into digital data using several different color models. The analytical data can then be processed with various chemometric methods. This research study investigated the predictive performance of calibration models established using color models commonly used in analytical chemistry including RGB, CMYK, HSV and CIELAB. A total of eight commercially available colorimetric sensors were used to determine the presence of manganese (Mn2+), copper (Cu2+), iron (Fe2+/Fe3+), nitrate (NO3–), phosphate (PO43–), sulfate (SO42–), as well as total hardness and pH values. As external validation tests, real water samples collected in Chiang Mai, Thailand were used. Based on the resulting data obtained using the synthetic test samples, the color that was most similar to the appearing color of the chemical sensor could offer satisfactory results. However, it was not always the case especially when the strips composed of multiple colorimetric sensors or sensor array were used. When tested with external validation, the predictive performance could be improved using appropriate data preprocessing and, in this research study, a normalization method was recommended to guarantee the accuracy of the calibration models.

Dansyl-modified carbon dots with dual-emission for pH sensing, Fe3+ ion detection and fluorescent ink

In this work, a multifunctional ratiometric fluorescence (FL) nanohybrid (CSCDs@DC) was synthesized from chitosan based carbon dots (CSCDs) and dansyl chloride (DC) at room temperature. The CSCDs@DC revealed strong FL intensity, great stability and excellent anti-photobleaching properties. Herein, CSCDs@DC was responsive to pH value in the range of 1.5-4.0 and exhibited color-switchable FL properties between acidic and alkaline environments. In addition, CSCDs@DC showed good selectivity and sensitivity towards Fe³⁺ ions. A good linear relationship for the Fe³⁺ ion detection was obtained in the range from 0 μM to 100 μM, with a detection limit of 1.23 μM. What's more, CSCDs@DC can be used as a fluorescent ink. It expressed superior optical properties after 3 months of storage or continuous exposure to UV light for 24 h. This study suggested that CSCDs@DC had potential in the detection of pH and metal ions, as well as showing promising application in the anti-counterfeiting field.

Smartphone assisted colorimetric and fluorescent triple-channel signal sensor for ascorbic acid assay based on oxidase-like CoOOH nanoflakes

Ascorbic acid (AA) is an important diet-derived antioxidant to human body. Thus, efficient and accurate detection of AA is of considerable significance in food analysis. Herein, smartphone assisted colorimetric and fluorescent triple-channel signal sensor has been developed for AA monitoring based on oxidase-like CoOOH nanoflakes. CoOOH nanoflakes can efficiently catalyze the oxidation of p-phenylenediamine (p-PD) into reddish brown p-PDox. The carbon dots (C-dots) are further introduced, of which the fluorescence can be quenched by p-PDox. However, in the presence of AA, the CoOOH nanoflakes is reduced and thus collapsed. As a result, the oxidation of p-PD is restrained, and thus the fluorescence of C-dots keeps strong. Based on AA induced light color, low absorbance, and strong fluorescence, triple-channel signal sensor has been proposed for AA determination. The AA assay shows a dynamic response range from 0.5 to 10 μM with a detection limit of 0.09 μM. The method assay allows detection of AA in real samples such as fruit juices. Combination with portable smartphone, the developed sensor is potential for AA determination in resource-poor settings.

Fe3+ detection, bioimaging, and patterning based on bright blue-fluorescent N-doped carbon dots

The bright blue fluorescent N-doped carbon dots (N-CDs) was successfully fabricated by one-step hydrothermal treatment of astragalus and was exploited for cellular imaging and patterning.