Disposable Colorimetric Paper-Based Probe for the Detection of Amine-Containing Gases in Aquatic Sediments

A smartphone-adaptable fluorescent probe for visual monitoring of fish freshness and its application in fluorescent dyes

Due to increasing food safety issues, developing intelligent, on-site, and visual methods for detecting fish freshness has attracted significant attention. Here, we have prepared a benzo[h]chromene derivative BCN that can visually detect 12 biogenic amines (BAs) with high sensitivity. The mechanism for recognizing cadaverine (Cad) is that the probe reacts with Cad to produce a Schiff base derivative, which alters the charge distribution within the molecule, resulting in significant colorimetric and fluorescence changes. The sensing label BCN/FPS was prepared by loading the probe BCN on filter paper, and a visual detection platform was constructed by combining it with a smartphone. By monitoring the correspondence between label color and TVB-N content, a working curve of (R + B)/(R + B + G) with TVB-N content was obtained, enabling visual evaluation of salmon freshness using only a mobile phone. In addition, based on the good solubility and processability of BCN, its application in fluorescent dyes including impregnating dyes, printing inks, coatings, and flexible films has been explored, which opens up new directions for the application of BCN. Therefore, BCN has the potential for real-time monitoring of meat freshness and preparation of fluorescent materials.

Paper-based sensors: affordable, versatile, and emerging analyte detection platforms

Paper-based sensors, often referred to as paper-based analytical devices (PADs), stand as a transformative technology in the field of analytical chemistry. They offer an affordable, versatile, and accessible solution for diverse analyte detection. These sensors harness the unique properties of paper substrates to provide a cost-effective and adaptable platform for rapid analyte detection, spanning chemical species, biomolecules, and pathogens. This review highlights the key attributes that make paper-based sensors an attractive choice for analyte detection. PADs demonstrate their versatility by accommodating a wide range of analytes, from ions and gases to proteins, nucleic acids, and more, with customizable designs for specific applications. Their user-friendly operation and minimal infrastructure requirements suit point-of-care diagnostics, environmental monitoring, food safety, and more. This review also explores various fabrication methods such as inkjet printing, wax printing, screen printing, dip coating, and photolithography. Incorporating nanomaterials and biorecognition elements promises even more sophisticated and sensitive applications.

Polymer Imbibition Through Paper Strips

Liquid wicking and imbibition through porous strips are fundamental to paper microfluidics. In this study, we outline these processes via capillary rise dynamics (CRD) experiments by employing deionized water as a reference fluid and comparing its dynamics with those of aqueous polymer solutions. Replacing the working fluid with polymer solutions led to the occurrence of an intermediate viscous-dominated regime, followed by the gravity-dominated regime at a long-time scale. This transition from viscous-dominated to gravity-dominated was found to be a function of the porous substrate pore diameter. The delay in CRD from the viscous-dominated to gravity-dominated regime is explained by the presence of the prewetting front (PWF). To address it, PWF dynamics has also been quantified, along with the characterization of its morphological differences.

Detection of gases and organic vapors by cellulose-based sensors

The growing interest in the development of cost-effective, straightforward, and rapid analytical systems has found cellulose-based materials, including cellulose derivatives, cellulose-based gels, nanocellulosic materials, and the corresponding (nano)cellulose-based composites, to be valuable platforms for sensor development. The present work presents recent advances in the development of cellulose-based sensors for the determination of volatile analytes and derivatives of analytical relevance. In particular, strategies described in the literature for the fabrication and modification of cellulose-based substrates with responsive materials are summarized. In addition, selected contributions reported in the field of paper-based volatile sensors are discussed, with a particular emphasis on quick response (QR) code paper-based platforms, intelligent films for food freshness monitoring, and sensor arrays for volatile discrimination purposes. Furthermore, analytical strategies devised for the determination of ionic species by in situ generation of volatile derivatives in both paper-based analytical devices (PADs) and microfluidic PADs will also be described.

Machine Learning-Based Analytical Systems: Food Forensics

Despite a large amount of money being spent on both food analyses and control measures, various food-borne illnesses associated with pathogens, toxins, pesticides, adulterants, colorants, and other contaminants pose a serious threat to human health, and thus food safety draws considerable attention in the modern pace of the world. The presence of various biogenic amines in processed food have been frequently considered as the primary quality parameter in order to check food freshness and spoilage of protein-rich food. Various conventional detection methods for detecting hazardous analytes including microscopy, nucleic acid, and immunoassay-based techniques have been employed; however, recently, array-based sensing strategies are becoming popular for the development of a highly accurate and precise analytical method. Array-based sensing is majorly facilitated by the advancements in multivariate analytical techniques as well as machine learning-based approaches. These techniques allow one to solve the typical problem associated with the interpretation of the complex response patterns generated in array-based strategies. Consequently, the machine learning-based neural networks enable the fast, robust, and accurate detection of analytes using sensor arrays. Thus, for commercial applications, most of the focus has shifted toward the development of analytical methods based on electrical and chemical sensor arrays. Therefore, herein, we briefly highlight and review the recently reported array-based sensor systems supported by machine learning and multivariate analytics to monitor food safety and quality in the field of food forensics.

Facile Synthesis of Fe-Doped Hydroxyapatite Nanoparticles from Waste Coal Ash: Fabrication of a Portable Sensor for the Sensitive and Selective Colorimetric Detection of Hydrogen Sulfide

In this work, a new strategy has been reported for the portable detection of H₂S based on Fe-doped hydroxyapatite nanoparticles (Fe-HA) using a colorimetric paper test strip integrated with a smartphone platform. Fe-HA NPs were fabricated successfully via recycling waste coal ash. The obtained probe response toward H₂S was through a distinct visual color change. The sensing mechanism is based on the displacement reaction, in which PO₄ ^3- is replaced by S^2-. The prepared test strip shows high selectivity, and the other compounds containing thiol and sulfur anion have a negligible effect on the detection of H₂S. The designed scheme is applied for H₂S detection in the concentration range of 0.5-130 ppm with a limit of detection of 70 ppb. Furthermore, such a disposable sensor was used as a practical system for monitoring H₂S in actual water samples, suggesting the promising potential of this platform for suitable analysis of H₂S in an aqueous environment.

A pyrylium salt-based fluorescent probe for the highly sensitive detection of methylamine vapour

The MTPY exhibits an obvious fluorescence response from yellow to cyan when reacted with CH3NH2 with a low detection limit (2.6 ppt, 8.4 × 10−8 M). The sensing mechanism was traced by mass spectrometry.

Direct minimally invasive enzymatic determination of tyramine in cheese using digital imaging

An enzymatic method for the direct (without pretreatment) minimally invasive tyramine determination in cheese is proposed. Colorimetric test strips containing tyramine oxidase (TAO), peroxidase and 3,3',5,5'-tetramethylbenzidine (Q-TAO), allow tyramine determination through the RGB chromatic coordinates of the observed blue colour (LOD = 2.6·10^-6 M, LOQ = 8.7·10^-6 M, RSD% (n = 5; 1.8·10^-4 M) = 3.2%). The strips are inserted in the sample for 2 min and then the RGB coordinates are measured using a smartphone. Previously, these Q-TAO strips have been also optimized for tyramine determination in cheese extract. To do that, a spectrophotometric method in solution for tyramine determination in cheese extracts has been developed, which included an in-depth study of the indicating reaction; this study has allowed to gain new information about the spectroscopic properties of different TMB species and, which it is more important, to detect cross-reactions between TAO and TMB species. A mathematical model has also been developed which relate the RGB signals obtained with the tyramine concentrations, the instrumental characteristics of the smartphone and the spectroscopic properties of the absorbing product of the enzymatic reaction.

Liquid Wicking in a Paper Strip: An Experimental and Numerical Study

In this decade, paper-based microfluidics has gained more interest in the research due to the vast applications in medical diagnosis, environmental monitoring, food safety analysis, etc. In this work, we presented a set of experiments to understand the physics of the capillary flow phenomenon through paper strips. Here, using the wicking phenomenon of the liquid in porous media, experimentally, we find out the capillary height of the liquid in filter paper at different time intervals. It was found that the Lucas-Washburn (L-W) model, as well as the evaporation model, fails to predict the capillary rise accurately. However, the detailed numerical solution shows a better similarity with the experimental results. We have also shown the different regimes of the wicking phenomenon using scaling analysis of the modified L-W model. The capillary rise method was applied to detect the added water content in milk. We used milk as a liquid food and found the added water content from the change in the capillary height at different concentrations of milk. Finally, results obtained from the paper-based device were verified with the commercially available lactometer data.