Flexible graphene electronics are rapidly gaining interest, but their widespread implementation has been impeded by challenges with ink preparation, ink printing, and post-print annealing processes. Laser-induced graphene (LIG) promises a facile alternative by creating flexible graphene electronics on polyimide substrates through a one-step laser writing fabrication method. Herein we demonstrate the use of LIG, created through a low-cost UV laser, for electrochemical ion selective sensing of plant-available nitrogen (i.e., both ammonium and nitrate ions: NH4+ and NO3-) in soil samples. The laser used to create the LIG was operated at distinct pulse rates (10, 20, 30, 40, and 50 ms) in order to maximize the LIG electrochemical reactivity. Results illustrated that a laser pulse rate of 20 ms led to a high percentage of sp2 carbon (77%) and optimal peak oxidation current of 120 uA during ferricyanide cyclic voltammetry. Therefore, LIG electrodes created with a 20 ms pulse rate were consequently functionalized with distinct ionophores specific to NH4+(nonactin) or NO3-(tridodecylmethylammonium nitrate) within polyvinyl chloride (PVC)-based membranes to create distinct solid contact ion selective electrodes (SC-ISEs) for NH4+ and NO3-ion sensing respectively. The LIG SC-ISEs displayed near Nernstian sensitivities of 51.7 ± 7.8 mV/decade (NH4+) and -54.8 ± 2.5 mV/ decade (NO3-), detection limits of 28.2 ± 25.0 uM (NH4+) and 20.6 ± 14.8 uM (NO3-), low long-term drift of 0.93 mV/hr (NH4+) sensors and -5.3 μV/hr (NO3-) sensors and linear sensing ranges within 10-5-10-1 M for both sensors. Moreover, soil slurry sensing was performed and recovery percentages of 96% and 95% were obtained for added NH4+and NO3-, respectively. These results, combined with a facile fabrication that does not require metallic nanoparticle decoration, make these LIG electrochemical sensors appealing for a wide range of in field or point-of-service applications for soil health management. ABSTRACTFlexible graphene electronics are rapidly gaining interest, but their widespread implementation has been impeded by challenges with ink preparation, ink printing, and postprint annealing processes. Laser-induced graphene (LIG) promises a facile alternative by creating flexible graphene electronics on polyimide substrates through a one-step laser writing fabrication method. Herein we demonstrate the use of LIG, created through a low-cost UV laser, for electrochemical ion selective sensing of plant-available nitrogen (i.e., both ammonium and nitrate ions: NH 4 + and NO 3 -metallic nanoparticle decoration, make these LIG electrochemical sensors appealing for a wide range of in-field or point-of-service applications for soil health management.

We demonstrate a sensing mechanism for rapid detection of Listeria monocytogenes in food samples using the actuation of chitosan-aptamer nanobrush borders. The bio-inspired soft material and sensing strategy mimic natural symbiotic systems, where low levels of bacteria are selectively captured from complex matrices. To engineer this biomimetic system, we first develop reduced graphene oxide/nanoplatinum (rGO-nPt) electrodes, and characterize the fundamental electrochemical behavior in the presence and absence of chitosan nanobrushes during actuation (pH-stimulated osmotic swelling). We then characterize the electrochemical behavior of the nanobrush when receptors (antibodies or DNA aptamers) are conjugated to the surface. Finally, we test various techniques to determine the most efficient capture strategy based on nanobrush actuation, and then apply the biosensors in a food product. Maximum cell capture occurs when aptamers conjugated to the nanobrush bind cells in the extended conformation (pH < 6), followed by impedance measurement in the collapsed nanobrush conformation (pH > 6). The aptamer-nanobrush hybrid material was more efficient than the antibody-nanobrush material, which was likely due to the relatively high adsorption capacity for aptamers. The biomimetic material was used to develop a rapid test (17 min) for selectively detecting L. monocytogenes at concentrations ranging from 9 to 107 CFU mL-1 with no pre-concentration, and in the presence of other Gram-positive cells (Listeria innocua and Staphylococcus aureus). Use of this bio-inspired material is among the most efficient for L. monocytogenes sensing to date, and does not require sample pretreatment, making nanobrush borders a promising new material for rapid pathogen detection in food.

The presence of unsafe levels of microorganisms in food constitutes a growing economic and public health problem that necessitates new technology for their rapid detection along the food continuum from production to consumption. While traditional techniques are reliable, there is a need for more sensitive, selective, rapid, and costeffective approaches for food safety evaluation. Methods such as microbiological counts are sufficiently accurate and inexpensive, and are capable of determining presence and viability for most pathogens. However, these techniques are time consuming, involve destructive sampling, and require trained personnel and biosafety-certified facilities for analysis. Molecular techniques such as the polymerase chain reaction have greatly improved analytical capability over the last decade, achieving shorter analysis time with quantitative data and strain specificity, and in some cases the ability to discriminate cell viability. The emerging field of nanosensors/biosensors has demonstrated a variety of devices that hold promise to bridge the gap between traditional plate counting and molecular techniques. Many nanosensors/biosensors are rapid, portable, accurate devices that can be used as an additional screening tool for identifying unsafe levels of microorganisms in food products with no need for pre-enrichment. In this review, we provide a brief overview of available biorecognitiontransduction techniques for detecting bacteria in food. We then discuss the advantages and disadvantages of each technique, and describe some recent biosensor or nanosensor technologies that are under development. We conclude by summarizing the opportunities and challenges in the field of pathogen monitoring in food systems and we focus the discussion on the strengths/weaknesses of the most popular biorecognition agents and transducer nanomaterials for biosensing.

Irrigation water is a primary source of fresh produce contamination by bacteria during the preharvest, particularly in hydroponic systems where the control of pests and pathogens is a major challenge. In this work, we demonstrate the development of a Listeria biosensor using platinum interdigitated microelectrodes (Pt-IME). The sensor is incorporated into a particle/sediment trap for the real-time analysis of irrigation water in a hydroponic lettuce system. We demonstrate the application of this system using a smartphone-based potentiostat for rapid on-site analysis of water quality. A detailed characterization of the electrochemical behavior was conducted in the presence/absence of DNA and Listeria spp., which was followed by calibration in various solutions with and without flow. In flow conditions (100 mL samples), the aptasensor had a sensitivity of 3.37 ± 0.21 kΩ log-CFU−1 mL, and the LOD was 48 ± 12 CFU mL−1 with a linear range of 102 to 104 CFU mL−1. In stagnant solution with no flow, the aptasensor performance was significantly improved in buffer, vegetable broth, and hydroponic media. Sensor hysteresis ranged from 2 to 16% after rinsing in a strong basic solution (direct reuse) and was insignificant after removing the aptamer via washing in Piranha solution (reuse after adsorption with fresh aptamer). This is the first demonstration of an aptasensor used to monitor microbial water quality for hydroponic lettuce in real time using a smartphone-based acquisition system for volumes that conform with the regulatory standards. The aptasensor demonstrated a recovery of 90% and may be reused a limited number of times with minor washing steps.

In this review, we discuss the role of sensor analytics point solutions (SNAPS), a reduced complexity machine-assisted decision support tool. We summarize the approaches used for mobile phone-based chemical/biological sensors, including general hardware and software requirements for signal transduction and acquisition. We introduce SNAPS, part of a platform approach to converge sensor data and analytics. The platform is designed to consist of a portfolio of modular tools which may lend itself to dynamic composability by enabling context-specific selection of relevant units, resulting in case-based working modules. SNAPS is an element of this platform where data analytics, statistical characterization and algorithms may be delivered to the data either via embedded systems in devices, or sourced, in near real-time, from mist, fog or cloud computing resources. Convergence of the physical systems with the cyber components paves the path for SNAPS to progress to higher levels of artificial reasoning tools (ART) and emerge as data-informed decision support, as a service for general societal needs. Proof of concept examples of SNAPS are demonstrated both for quantitative data and qualitative data, each operated using a mobile device (smartphone or tablet) for data acquisition and analytics. We discuss the challenges and opportunities for SNAPS, centered around the value to users/stakeholders and the key performance indicators users may find helpful, for these types of machine-assisted tools.

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Figure 5: Bode plots for A) PNIPAAm-ConA and B) PNIPAAm-Anti-GroEL antibody modified electrodes exposed to various concentrations of E. coli O157:H7 (CFU mL -1 ) in vegetable broth. Insets show the exploded view over the frequency range of 1-3.5 Hz. Nyquist plots for C) PNIPAAm-ConA modified electrodes and D) PNIPAAm-Anti-GroEL antibody modified electrodes exposed to various concentration of E. coli O157:H7 (CFU mL -1 ) in vegetable broth. Calibration curves at 1 Hz for E) PNIPAAm-ConA and F) PNIPAAm-Anti-GroEL antibody modified electrodes exposed to E. coli O157:H7 in vegetable broth over their respective linear ranges.Foodborne pathogens are a major concern for the health and safety of the public. Escherichia coli spp. are some of the most common foodborne bacteria. Conventional methods for detecting E. coli are time-consuming and require highly trained personnel and laboratories. Therefore, More rapid, sensitive, and reliable methods are needed for pathogen detection in food products to ensure public health.To develop a sensing mechanism for rapid, label-free detection of E. coli spp. in food samples using temperatureresponsiveness of poly(N-isopropylacrylmide) (PNIPAAm) brushes. This bio-inspired soft material and sensing mechanism resembles natural bacteria-host symbiotic systems where low concentrations of bacteria in complex matrices are selectively captured.

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