Abstract
Food safety hazards are any potential agents that can cause adverse health effects to consumers. Due to the health effects that food hazards can cause, food safety becomes a significant concern for consumers. The food safety hazards can be either physical, chemical, or biological and can occur when the food has been contaminated with these agents. Detection of these hazards from different food sources is an essential practice to ensure food quality and safety and to eliminate and control the risk of consuming contaminated foods and to guarantee consumers' health. Hence, being able to analyze and detect these toxins in foods and drinks is a priority to comply with the legislative limits set by food authorities worldwide. The analysis of these toxins has still conducted using conventional methods like chromatography (HPLC, GC, and TLC) and enzymelinked immunosorbent assay (ELISA). These detection methods are time-consuming and require expensive equipment and high expertise in addition to sample pre-treatment (e.g., extraction, purification, and detection and quantification). Hence there is a need for a low-cost, sensitive, rapid, reliable, and portable instrument that is easy to use at the point of source for the detection of food toxicants. In recent years, biosensors have been emerging as a fast, sensitive, reliable, and low-cost technique for the detection of this toxin and have become an alternative screening tool to be applied for prompt detection. To address the adverse effects of food safety hazards, many countries set maximum allowable limits for these hazards. Among these, the European Commission, the US Food and Drug Administration (FDA), the World Health Organization (WHO) are the most known organizations that set maximum levels and regulations. To fulfill the requirements of these regulatory limits, there is an increasing need for the development of simple, fast, sensitive, and cost-effective methods to detect food safety hazards. Therefore, this thesis is focused on the development of biosensors to detect chemical food safety hazards, such as mycotoxins (aflatoxin M1 (AFM1) and ochratoxin A (OTA)), and antibiotic residue (tetracycline (TC)). In this regard, low-cost antibody-assisted biosensors to detect mycotoxin and CO2 fabricated laser-induced graphene (LIG) based molecularly imprinted polymer (MIP) sensor to detect antibiotic residue from different food products were fabricated through printing techniques and tested for their performance in the real sample. These biosensors were functionalized with nanoparticles and specific enzymes to improve the sensitivity, selectivity, and detection limit by improving their electrochemical properties. In addition to these, a simple Executive Summary in English ii and sensitive capacitive sensor was developed to predict the pH of saliva using graphene oxide as a sensing layer. For the detection of AFM1, flexible biosensors were fabricated using dispense-printed electrodes and the surfaces of the working electrode were modified to improve the electrical property. In this section, two methods of modification were utilized. The first one was functionalized with single-walled carbon nanotubes (SWCNTs) while the others were only pre-treated with sodium hydroxide (NaOH) and oxygen plasma (OP). In both cases, the modified electrodes were coated with specific antibodies to improve their specificity and sensitivity and tested in the buffer and milk to test validate application in a real sample. In both cases, the working range of the sensors is 0.01-1 µg/L. The limit of detection (LOD) of the SWCNT-modified sensor was 0.02 µg/L while for those pre-treated with NaOH and OP was 0.024 µg/L, and 0.020 µg/L for NaOH and OP treated electrodes, respectively. This LOD showed an improvement in terms of sensitivity compared to the printed immunosensor for AFM1 in the state of the art. For OTA detection, bendable biosensors on polyethylene terephthalate (PET) and stretchable biosensors on and Poly (dimethyl siloxane) (PDMS) were screen-printed using silver ink and modified the surface of the working electrode with SWCNTs to improve surface and electrical properties. Anti-OTA specific antibodies were immobilized on the modified electrode. When challenged with other interfering mycotoxins, the biosensor was selective to OTA. In terms of mechanical stability, the bendable biosensor was stable to 5000 bending cycles down to 7.5 mm diameter, and the soft biosensor showed functional stability to 300 iterations of stretching up to 33.5%. Both biosensors have a linear range of detection of 0.01 – 1 ng/mL with a LOD of 0.08 and 0.13 ng/mL in grape juice for the bendable and stretchable biosensor, respectively. A 3-electrode system, sensitive and label-free sensor was developed to detect TC residue from milk and meat extract samples using the CO2 laser-induced graphene (LIG) electrodes modified with a molecularly imprinted polymer (MIP) that can be used as an artificial biorecognition element. CO2 LIG fabrication technique is a mask-free, low-cost, and simple method to obtain non-metallic electrodes. LIG was patterned on a polyimide (PI) substrate. Gold nanoparticles (AuNPs) were electrodeposited on the surface of the working electrode to have a highly conductive, and nanostructured, imprinted inner layer. Afterward, o-phenylenediamine (oPD) as a monomer and TC as a template was electropolymerized on the surface of the LIG working Executive Summary in English iii electrode for the formation of a MIP. The sensitivity of the sensor was evaluated by differential pulse voltammetry (DPV) and the LOD obtained was 0.32 nM, 0.85 nM, and 0.8 nM in buffer, milk, and meat extract samples, respectively with a working range of 5 nM to 500 nM and a linear response range between 10 nM to 300 nM. The sensor showed high sensitivity, reproducibility, and stability and can be used as an alternative system to detect TC from animalbased food products. On the other hand, to enable fast and easy dental health observations, a flexible capacitive pH sensor using graphene oxide (GO) as a sensing layer on the LIG electrode produced from a PI film was developed. Cyclic voltammetry (CV) was used as a measurement technique. The area under the CV curve was used to extract the specific capacitance (Cs) and correlated to the corresponding pH level measured. The sensor showed a good correlation between the pH and Cs having R2 of 0.98 and a linear regression equation of Cs = -0.0019 x pH + 0.0169. These proposed biosensors have the desirability of good biosensors such as high sensitivity, short analysis time, cost-effectiveness, simplicity, reliability, reproducible, and selective compared to chromatographic and ELISA methods.