Improving high throughput manufacture of laser-inscribed graphene electrodes via hierarchical clustering.

Laser-inscribed graphene (LIG), initially developed for graphene supercapacitors, has found widespread use in sensor research and development, particularly as a platform for low-cost electrochemical sensing. However, batch-to-batch variation in LIG fabrication introduces uncertainty that cannot be adequately tracked during manufacturing process, limiting scalability. Therefore, there is an urgent need for robust quality control (QC) methodologies to identify and select similar and functional LIG electrodes for sensor fabrication. For the first time, we have developed a statistical workflow and an open-source hierarchical clustering tool for QC analysis in LIG electrode fabrication. The QC process was challenged with multi-operator cyclic voltammetry (CV) data for bare and metalized LIG. As a proof of concept, we employed the developed QC process for laboratory-scale manufacturing of LIG-based biosensors. The study demonstrates that our QC process can rapidly identify similar LIG electrodes from large batches (n ≥ 36) of electrodes, leading to a reduction in biosensor measurement variation by approximately 13% compared to the control group without QC. The statistical workflow and open-source code presented here provide a versatile toolkit for clustering analysis, opening a pathway toward scalable manufacturing of LIG electrodes in sensing. In addition, we establish a data repository for further study of LIG variation.

The WRKY46-MYC2 module plays a critical role in E-2-hexenal-induced anti-herbivore responses by promoting flavonoid accumulation.

Volatile organic compounds (VOCs) play key roles in plant-plant communication, especially in response to pest attack. E-2-hexenal is an important component of VOCs, but it is unclear whether it can induce endogenous plant resistance to insects. Here, we show that E-2-hexenal activates early signaling events in Arabidopsis (Arabidopsis thaliana) mesophyll cells, including an H2O2 burst at the plasma membrane, the directed flow of calcium ions, and an increase in cytosolic calcium concentration. Treatment of wild-type Arabidopsis plants with E-2-hexenal increases their resistance when challenged with the diamondback moth Plutella xylostella L., and this phenomenon is largely lost in the wrky46 mutant. Mechanistically, E-2-hexenal induces the expression of WRKY46 and MYC2, and the physical interaction of their encoded proteins was verified by yeast two-hybrid, firefly luciferase complementation imaging, and in vitro pull-down assays. The WRKY46-MYC2 complex directly binds to the promoter of RBOHD to promote its expression, as demonstrated by luciferase reporter, yeast one-hybrid, chromatin immunoprecipitation, and electrophoretic mobility shift assays. This module also positively regulates the expression of E-2-hexenal-induced naringenin biosynthesis genes (TT4 and CHIL) and the accumulation of total flavonoids, thereby modulating plant tolerance to insects. Together, our results highlight an important role for the WRKY46-MYC2 module in the E-2-hexenal-induced defense response of Arabidopsis, providing new insights into the mechanisms by which VOCs trigger plant defense responses.

Polarized distribution of extracellular nucleotides promotes gravity-directed polarization of development in spores of Ceratopteris richardii.

Gravity directs the polarization of Ceratopteris fern spores. This process begins with the uptake of calcium through channels at the bottom of the spore, a step necessary for the gravity response. Data showing that extracellular ATP (eATP) regulates calcium channels led to the hypothesis that extracellular nucleotides could play a role in the gravity-directed polarization of Ceratopteris spores. In animal and plant cells ATP can be released from mechanosensitive channels. This report tests the hypothesis that the polarized release of ATP from spores could be activated by gravity, preferentially along the bottom of the spore, leading to an asymmetrical accumulation of eATP. In order to carry out this test, an ATP biosensor was used to measure the [eATP] at the bottom and top of germinating spores during gravity-directed polarization. The [eATP] along the bottom of the spore averaged 7-fold higher than the concentration at the top. All treatments that disrupted eATP signaling resulted in a statistically significant decrease in the gravity response. In order to investigate the source of ATP release, spores were treated with Brefeldin A (BFA) and gadolinium trichloride (GdCl3). These treatments resulted in a significant decrease in gravity-directed polarization. An ATP biosensor was also used to measure ATP release after treatment with both BFA and GdCl3. Both of these treatments caused a significant decrease in [ATP] measured around spores. These results support the hypothesis that ATP could be released from mechanosensitive channels and secretory vesicles during the gravity-directed polarization of Ceratopteris spores.

Machine Learning for Improved Detection of Pathogenic E. coli in Hydroponic Irrigation Water Using Impedimetric Aptasensors: A Comparative Study.

Reuse of alternative water sources for irrigation (e.g., untreated surface water) is a sustainable approach that has the potential to reduce water gaps, while increasing food production. However, when growing fresh produce, this practice increases the risk of bacterial contamination. Thus, rapid and accurate identification of pathogenic organisms such as Shiga-toxin producing Escherichia coli (STEC) is crucial for resource management when using alternative water(s). Although many biosensors exist for monitoring pathogens in food systems, there is an urgent need for data analysis methodologies that can be applied to accurately predict bacteria concentrations in complex matrices such as untreated surface water. In this work, we applied an impedimetric electrochemical aptasensor based on gold interdigitated electrodes for measuring E. coliO157:H7 in surface water for hydroponic lettuce irrigation. We developed a statistical machine-learning (SML) framework for assessing different existing SML methods to predict the E. coliO157:H7 concentration. In this study, three classes of statistical models were evaluated for optimizing prediction accuracy. The SML framework developed here facilitates selection of the most appropriate analytical approach for a given application. In the case of E. coliO157:H7 prediction in untreated surface water, selection of the optimum SML technique led to a reduction of test set RMSE by at least 20% when compared with the classic analytical technique. The statistical framework and code (open source) include a portfolio of SML models, an approach which can be used by other researchers using electrochemical biosensors to measure pathogens in hydroponic irrigation water for rapid decision support.

SPOT: Scanning plant IoT facility for high-throughput plant phenotyping.

Many plant phenotyping platforms have been kept out of the reach of smaller labs and institutions due to high cost and proprietary software. The Scanning Plant IoT (SPOT) Facility, located at the University of Florida, is a mobile, laboratory-based platform that facilitates open-source collection of high-quality, interoperable plant phenotypic data. It consists of three main sensors: a hyperspectral sensor, a thermal camera, and a LiDAR camera. Real-time data from the sensors can be collected in its 10 ft. × 10 ft. scanning region. The mobility of the device allows its use in large growth chambers, environmentally controlled rooms, or greenhouses. Sensors are oriented nadir and positioned via computer numerical control of stepper motors. In a preliminary experiment, data gathered from SPOT was used to autonomously and nondestructively differentiate between cultivars.

A capacitive laser-induced graphene based aptasensor for SARS-CoV-2 detection in human saliva.

SARS-CoV-2 virus induced CoVID-19 pandemic has accelerated the development of diagnostic tools. Devices integrated with electrochemical biosensors may be an interesting alternative to respond to the high demand for testing, particularly in contexts where access to standard detection technologies is lacking. Aptamers as recognition elements are useful due to their stability, specificity, and sensitivity to binding target molecules. We have developed a non-invasive electrochemical aptamer-based biosensor targeting SARS-CoV-2 in human saliva. The aptamer is expected to detect the Spike protein of SARS-CoV-2 wildtype and its variants. Laser-induced graphene (LIG) electrodes coated with platinum nanoparticles were biofunctionalized with a biotin-tagged aptamer. Electrochemical Impedance Spectroscopy (EIS) for BA.1 sensing was conducted in sodium chloride/sodium bicarbonate solution supplemented with pooled saliva. To estimate sensing performance, the aptasensor was tested with contrived samples of UV-attenuated virions from 10 to 10,000 copies/ml. Selectivity was assessed by exposing the aptasensor to non-targeted viruses (hCoV-OC43, Influenza A, and RSV-A). EIS data outputs were further used to select a suitable response variable and cutoff frequency. Capacitance increases in response to the gradual loading of the attenuated BA.1. The aptasensor was sensitive and specific for BA.1 at a lower viral load (10-100 copies/ml) and was capable of discriminating between negative and positive contrived samples (with strain specificity against other viruses: OC43, Influenza A, and RSV-A). The aptasensor detected SARS-CoV-2 with an estimated LOD of 1790 copies/ml in contrived samples. In human clinical samples, the aptasensor presents an accuracy of 72%, with 75% of positive percent of agreement and 67% of negative percent of agreement. Our results show that the aptasensor is a promising candidate to detect SARS-CoV-2 during early stages of infection when virion concentrations are low, which may be useful for preventing the asymptomatic spread of CoVID-19.

Carbon dots using a household cleaning liquid as a dopant for iron detection in hydroponic systems.

Iron (Fe) is a required micronutrient in plants for the production of chlorophyll and transport of oxygen. A commonly used surrogate for measuring nutrient levels is the measurement of electrical conductivity or total dissolved solids, but this technique is not selective towards any particular dissolved ion. In this study, using a conventional microwave, fluorescent carbon dots (CDs) are produced from glucose and a household cleaning product and applied towards monitoring dissolved ferric iron levels in hydroponic systems through fluorescent quenching. The produced particles have an average size of 3.19 ± 0.76 nm with a relatively high degree of oxygen surface groups. When using an excitation of 405 nm, a broad emission peak is centered at approximately 500 nm. A limit-of-detection of 0.196 ± 0.067 ppm (3.51 ± 1.21 µM) with minimal interference from common heavy metal quenchers and ions found in hydroponic systems was determined. Butterhead lettuce was grown while discretely monitoring iron levels via the CDs for three separate weeks of growth. The CDs displayed a non-significant difference (p > 0.05) in performance when compared to a standard method. These results along with a simple and relatively low-cost production method make the CDs in this study a promising tool for monitoring iron levels in hydroponic systems.

A Connected World: System-Level Support Through Biosensors.

The goal of protecting the health of future generations is a blueprint for future biosensor design. Systems-level decision support requires that biosensors provide meaningful service to society. In this review, we summarize recent developments in cyber physical systems and biosensors connected with decision support. We identify key processes and practices that may guide the establishment of connections between user needs and biosensor engineering using an informatics approach. We call for data science and decision science to be formally connected with sensor science for understanding system complexity and realizing the ambition of biosensors-as-a-service. This review calls for a focus on quality of service early in the design process as a means to improve the meaningful value of a given biosensor. We close by noting that technology development, including biosensors and decision support systems, is a cautionary tale. The economics of scale govern the success, or failure, of any biosensor system.

Perspective: Phosphorus monitoring must be rooted in sustainability frameworks spanning material scale to human scale.

Phosphorus (P) is a finite resource, and its environmental fate and transport is complex. With fertilizer prices expected to remain high for years and disruption to supply chains, there is a pressing need to recover and reuse P (primarily as fertilizer). Whether recovery is to occur from urban systems (e.g., human urine), agricultural soil (e.g., legacy P), or from contaminated surface waters, quantification of P in various forms is vital. Monitoring systems with embedded near real time decision support, so called cyber physical systems, are likely to play a major role in the management of P throughout agro-ecosystems. Data on P flow(s) connects the environmental, economic, and social pillars of the triple bottom line (TBL) sustainabilty framework. Emerging monitoring systems must account for complex interactions in the sample, and interface with a dynamic decision support system that considers adaptive dynamics to societal needs. It is known from decades of study that P is ubiquitous, yet without quantitative tools for studying the dynamic nature of P in the environment, the details may remain elusive. If new monitoring systems (including CPS and mobile sensors) are informed by sustainability frameworks, data-informed decision making may foster resource recovery and environmental stewardship from technology users to policymakers.

Rapid and label-free Listeria monocytogenes detection based on stimuli-responsive alginate-platinum thiomer nanobrushes.

In this work, we demonstrate the development of a rapid and label-free electrochemical biosensor to detect Listeria monocytogenes using a novel stimulus-response thiomer nanobrush material. Nanobrushes were developed via one-step simultaneous co-deposition of nanoplatinum (Pt) and alginate thiomers (ALG-thiomer). ALG-thiomer/Pt nanobrush platform significantly increased the average electroactive surface area of electrodes by 7 folds and maintained the actuation properties (pH-stimulated osmotic swelling) of the alginate. Dielectric behavior during brush actuation was characterized with positively, neutral, and negatively charged redox probes above and below the isoelectric point of alginate, indicating ALG-thiomer surface charge plays an important role in signal acquisition. The ALG-thiomer platform was biofunctionalized with an aptamer selective for the internalin A protein on Listeria for biosensing applications. Aptamer loading was optimized and various cell capture strategies were investigated (brush extended versus collapsed). Maximum cell capture occurs when the ALG-thiomer/aptamer is in the extended conformation (pH > 3.5), followed by impedance measurement in the collapsed conformation (pH < 3.5). Low concentrations of bacteria (5 CFU mL-1) were sensed from a complex food matrix (chicken broth) and selectivity testing against other Gram-positive bacteria (Staphylococcus aureus) indicate the aptamer affinity is maintained, even at these pH values. The new hybrid soft material is among the most efficient and fastest (17 min) for L. monocytogenes biosensing to date, and does not require sample pretreatment, constituting a promising new material platform for sensing small molecules or cells.

An Experimental Framework for Developing Point-of-Need Biosensors: Connecting Bio-Layer Interferometry and Electrochemical Impedance Spectroscopy.

Biolayer interferometry (BLI) is a well-established laboratory technique for studying biomolecular interactions important for applications such as drug development. Currently, there are interesting opportunities for expanding the use of BLI in other fields, including the development of rapid diagnostic tools. To date, there are no detailed frameworks for implementing BLI in target-recognition studies that are pivotal for developing point-of-need biosensors. Here, we attempt to bridge these domains by providing a framework that connects output(s) of molecular interaction studies with key performance indicators used in the development of point-of-need biosensors. First, we briefly review the governing theory for protein-ligand interactions, and we then summarize the approach for real-time kinetic quantification using various techniques. The 2020 PRISMA guideline was used for all governing theory reviews and meta-analyses. Using the information from the meta-analysis, we introduce an experimental framework for connecting outcomes from BLI experiments (KD, kon, koff) with electrochemical (capacitive) biosensor design. As a first step in the development of a larger framework, we specifically focus on mapping BLI outcomes to five biosensor key performance indicators (sensitivity, selectivity, response time, hysteresis, operating range). The applicability of our framework was demonstrated in a study of case based on published literature related to SARS-CoV-2 spike protein to show the development of a capacitive biosensor based on truncated angiotensin-converting enzyme 2 (ACE2) as the receptor. The case study focuses on non-specific binding and selectivity as research goals. The proposed framework proved to be an important first step toward modeling/simulation efforts that map molecular interactions to sensor design.

Development of a Biosensor Based on Angiotensin-Converting Enzyme II for Severe Acute Respiratory Syndrome Coronavirus 2 Detection in Human Saliva.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the novel coronavirus responsible for COVID-19. Infection in humans requires angiotensin-converting enzyme II (hACE2) as the point of entry for SARS-CoV-2. PCR testing is generally definitive but expensive, although it is highly sensitive and accurate. Biosensor-based monitoring could be a low-cost, accurate, and non-invasive approach to improve testing capacity. We develop a capacitive hACE2 biosensor for intact SARS-CoV-2 detection in saliva. Laser-induced graphene (LIG) electrodes were modified with platinum nanoparticles. The quality control of LIG electrodes was performed using cyclic voltammetry. Truncated hACE2 was used as a biorecognition element and attached to the electrode surface by streptavidin-biotin coupling. Biolayer interferometry was used for qualitative interaction screening of hACE2 with UV-attenuated virions. Electrochemical impedance spectroscopy (EIS) was used for signal transduction. Truncated hACE2 binds wild-type SARS-CoV-2 and its variants with greater avidity than human coronavirus (common cold virus). The limit of detection (LoD) is estimated to be 2,960 copies/ml. The detection process usually takes less than 30 min. The strength of these features makes the hACE2 biosensor a potentially low-cost approach for screening SARS-CoV-2 in non-clinical settings with high demand for rapid testing (for example, schools and airports).

CML8 and GAD4 function in (Z)-3-hexenol-mediated defense by regulating γ-aminobutyric acid accumulation in Arabidopsis.

(Z)-3-hexenol, a small gaseous molecule, is produced in plants under biotic stress and induces defense responses in neighboring plants. However, little is known about how (Z)-3-hexenol induces plant defense-related signaling. In this study, we uncovered how (Z)-3-hexenol treatment enhances plant resistance to insect attacks by increasing γ-aminobutyric acid (GABA) contents in Arabidopsis leaves. First, (Z)-3-hexenol increases the intracellular content of calcium as secondary messenger in Arabidopsis leaf mesophyll cells. Both intracellular and extracellular calcium stores regulate changes in calcium content. Then, CML8 and GAD4 transmit calcium signaling to affect (Z)-3-hexenol induced GABA content and plant resistance. Herein, CML8 interaction with GAD4 was examined via yeast two-hybrid assays, firefly luciferase complementation imaging, and GST pull-down assays. These results indicate that (Z)-3-hexenol treatment increased the GABA contents in Arabidopsis leaves based on CML8 and GAD4, thus increasing plant resistance to the insect Plutella xylostella. This study revealed the mechanism of activating plant insect defense induced by (Z)-3-hexenol, which guides the study of volatiles as biological pest control.

Bioanalytical approaches for the detection, characterization, and risk assessment of micro/nanoplastics in agriculture and food systems.

This review discusses the most recent literature (mostly since 2019) on the presence and impact of microplastics (MPs, particle size of 1 µm to 5 mm) and nanoplastics (NPs, particle size of 1 to 1000 nm) throughout the agricultural and food supply chain, focusing on the methods and technologies for the detection and characterization of these materials at key entry points. Methods for the detection of M/NPs include electron and atomic force microscopy, vibrational spectroscopy (FTIR and Raman), hyperspectral (bright field and dark field) and fluorescence imaging, and pyrolysis-gas chromatography coupled to mass spectrometry. Microfluidic biosensors and risk assessment assays of MP/NP for in vitro, in vivo, and in silico models have also been used. Advantages and limitations of each method or approach in specific application scenarios are discussed to highlight the scientific and technological obstacles to be overcome in future research. Although progress in recent years has increased our understanding of the mechanisms and the extent to which MP/NP affects health and the environment, many challenges remain largely due to the lack of standardized and reliable detection and characterization methods. Most of the methods available today are low-throughput, which limits their practical application to food and agricultural samples. Development of rapid and high-throughput field-deployable methods for onsite screening of MP/NPs is therefore a high priority. Based on the current literature, we conclude that detecting the presence and understanding the impact of MP/NP throughout the agricultural and food supply chain require the development of novel deployable analytical methods and sensors, the combination of high-precision lab analysis with rapid onsite screening, and a data hub(s) that hosts and curates data for future analysis.

Context-Aware Diagnostic Specificity (CADS).

Rapid detection of proteins is critical in a vast array of diagnostic or monitoring applications [...].

Hydrophobic laser-induced graphene potentiometric ion-selective electrodes for nitrate sensing.

Current solid-contact ion-selective electrodes (ISEs) suffer from signal-to-noise drift and short lifespans partly due to water uptake and the development of an aqueous layer between the transducer and ion-selective membrane. To address these challenges, we report on a nitrate ISE based on hydrophobic laser-induced graphene (LIG) coated with a poly(vinyl) chloride-based nitrate selective membrane. The hydrophobic LIG was created using a polyimide substrate and a double lasing process under ambient conditions (air at 23.0 ± 1.0 °C) that resulted in a static water contact angle of 135.5 ± 0.7° (mean ± standard deviation) in wettability testing. The LIG-ISE displayed a Nernstian response of - 58.17 ± 4.21 mV dec-1 and a limit-of-detection (LOD) of 6.01 ± 1.44 µM. Constant current chronopotentiometry and a water layer test were used to evaluate the potential (emf) signal stability with similar performance to previously published work with graphene-based ISEs. Using a portable potentiostat, the sensor displayed comparable (p > 0.05) results to a US Environmental Protection Agency (EPA)-accepted analytical method when analyzing water samples collected from two lakes in Ames, IA. The sensors were stored in surface water samples for 5 weeks and displayed nonsignificant difference in performance (LOD and sensitivity). These results, combined with a rapid and low-cost fabrication technique, make the development of hydrophobic LIG-ISEs appealing for a wide range of long-term in situ surface water quality applications.

One-Step Fabrication of Stimuli-Responsive Chitosan-Platinum Brushes for Listeria monocytogenes Detection.

Bacterial contamination in food-processing facilities is a critical issue that leads to outbreaks compromising the integrity of the food supply and public health. We developed a label-free and rapid electrochemical biosensor for Listeria monocytogenes detection using a new one-step simultaneous sonoelectrodeposition of platinum and chitosan (CHI/Pt) to create a biomimetic nanostructure that actuates under pH changes. The XPS analysis shows the effective co-deposition of chitosan and platinum on the electrode surface. This deposition was optimized to enhance the electroactive surface area by 11 times compared with a bare platinum-iridium electrode (p < 0.05). Electrochemical behavior during chitosan actuation (pH-stimulated osmotic swelling) was characterized with three different redox probes (positive, neutral, and negative charge) above and below the isoelectric point of chitosan. These results showed that using a negatively charged redox probe led to the highest electroactive surface area, corroborating previous studies of stimulus-response polymers on metal electrodes. Following this material characterization, CHI/Pt brushes were functionalized with aptamers selective for L. monocytogenes capture. These aptasensors were functional at concentrations up to 106 CFU/mL with no preconcentration nor extraneous reagent addition. Selectivity was assessed in the presence of other Gram-positive bacteria (Staphylococcus aureus) and with a food product (chicken broth). Actuation led to improved L. monocytogenes detection with a low limit of detection (33 CFU/10 mL in chicken broth). The aptasensor developed herein offers a simple fabrication procedure with only one-step deposition followed by functionalization and rapid L. monocytogenes detection, with 15 min bacteria capture and 2 min sensing.

Fate of enteric viruses during leafy greens (romaine lettuce) production using treated municipal wastewater and AP205 bacteriophage as a surrogate.

Water reuse programs are being explored to close the gap between supply and demand for irrigation in agriculture. However, these sources could contain hazardous microbial contaminants, and pose risks to public health. This study aimed to grow and irrigate romaine lettuce with inoculated wastewater effluent to track AP205 bacteriophage prevalence through cultivation and post-harvest storage. AP205 is a bacteriophage and was used as a surrogate for enteric viruses. Low and high dosages (mean ± standard deviation) of AP205 at 4.8 ± 0.4 log PFU/mL and 6.6 ± 0.2 log PFU/mL; respectively, were prepared to examine viral load influence on contamination levels. Foliage, leachate, and soil contamination levels were directly related to AP205 concentrations in the effluent. AP205 concentrations increased throughout cultivation for foliage and leachate, suggesting bacteriophage accumulation. During post-harvest storage (14 day at 4 °C), there was a significant decrease in AP205 concentration on the foliage. Results show that wastewater effluents usage for leafy greens cultivation can pose risks to humans and additional steps are required to safely apply wastewater effluents to soils and crops.

Prevalence of Escherichia coli and Antibiotic-Resistant Bacteria During Fresh Produce Production (Romaine Lettuce) Using Municipal Wastewater Effluents.

High demand for food and water encourages the exploration of new water reuse programs, including treated municipal wastewater usage. However, these sources could contain high contaminant levels posing risks to public health. The objective of this study was to grow and irrigate a leafy green (romaine lettuce) with treated wastewater from a municipal wastewater treatment plant to track Escherichia coli and antibiotic-resistant microorganisms through cultivation and post-harvest storage to assess their fate and prevalence. Contamination levels found in the foliage, leachate, and soil were directly (p < 0.05) related to E. coli concentrations in the irrigation water. Wastewater concentrations from 177 to 423 CFU ml-1 resulted in 15-25% retention in the foliage. Leachate and soil presented means of 231 and 116% retention, respectively. E. coli accumulation on the foliage was observed (p < 0.05) and increased by over 400% during 14-day storage (4°C). From randomly selected E. coli colonies, in all four biomass types, 81 and 34% showed resistance to ampicillin and cephalothin, respectively. Reclaimed wastewater usage for leafy greens cultivation could pose potential health risks, especially considering the bacteria found have a high probability of being antibiotic resistance. Successful reuse of wastewater in agriculture will depend on appropriate mitigation and management strategies to guarantee an inexpensive, efficient, and safe water supply.

FEAST of biosensors: Food, environmental and agricultural sensing technologies (FEAST) in North America.

We review the challenges and opportunities for biosensor research in North America aimed to accelerate translational research. We call for platform approaches based on: i) tools that can support interoperability between food, environment and agriculture, ii) open-source tools for analytics, iii) algorithms used for data and information arbitrage, and iv) use-inspired sensor design. We summarize select mobile devices and phone-based biosensors that couple analytical systems with biosensors for improving decision support. Over 100 biosensors developed by labs in North America were analyzed, including lab-based and portable devices. The results of this literature review show that nearly one quarter of the manuscripts focused on fundamental platform development or material characterization. Among the biosensors analyzed for food (post-harvest) or environmental applications, most devices were based on optical transduction (whether a lab assay or portable device). Most biosensors for agricultural applications were based on electrochemical transduction and few utilized a mobile platform. Presently, the FEAST of biosensors has produced a wealth of opportunity but faces a famine of actionable information without a platform for analytics.