## 1 Introduction  
Fiber optic sensors (FOSs) have emerged as a revolutionary technology in various industrial applications due to their numerous advantages. The development of fiber optic technology began in the 1970s with advancements towards low-loss optical fibers for telecommunications. This led researchers to explore the potential of fiber optics as a novel waveguide for fast data communication [1, 2]. The integration of fiber optic communications and optoelectronics industries catalyzed the creation of fiber optic sensors, capable of detecting changes in phase, intensity, wavelength, and external disturbances [3, 4]. These sensors offer high sensitivity and precision in detecting environmental changes, allowing real-time monitoring of critical variables. Their ability to operate in hostile environments, compact size, and flexibility enable easy integration into existing systems. Additionally, their capacity to transmit signals over long distances without significant loss ensures efficient and accurate communication. These characteristics, along with low maintenance and high durability, make fiber optic sensors an advanced and reliable solution for improving process control and safety in diverse industries [2, 3]. Fiber optic sensors have been developed in various geometries, structures, and platforms, including fiber Bragg gratings(FBGs) [5], long-period gratings (LPGs) [6], specialty fibers [7], tapered fibers [8], multimodal interference (MMI) phenomenon [9; 10; 11] and in-fiber surface plasmon resonance [12], among others. These varied configurations highlight the versatility and adaptability of FOS technology to meet different sensing requirements. As already mentioned, fiber optic sensors have been used in multiple areas; in the food industry, fiber optic sensors are particularly valuable for their ability to perform real-time analysis [13]. This capability allows continuous and precise monitoring during production processes, significantly enhancing the quality control and safety of food products. By providing rapid and reliable detection of contaminants and adulterants, these sensors help ensure that foods meet regulatory standards and consumer expectations, reducing the risk of foodborne illnesses and improving trust in the supply chain [14; 15]. An excellent example of a food product that could greatly benefit from advanced tracking techniques is honey. Widely consumed for its nutritional value and as a natural sweetener, honey is particularly vulnerable to adulteration [16]. The main mechanisms used to alter honey include dilution with water, the addition of cheap sugars or syrups, mixing with lower quality honey or honey of unknown origin, or adding chemicals such as antibiotics or pesticides to prevent fermentation and prolong shelf life [16; 17]. Adulterating honey with water increases its humidity content, potentially enabling the growth of yeasts and other microorganisms, thereby reducing its shelf life and quality. Additionally, honey adulterated with water has a higher risk of microbiological contamination, leading to health issues such as gastrointestinal infections [18; 19]. Similarly, adulteration with glucose and other sugars not only degrades the nutritional quality of honey but also alters its chemical and biochemical properties, affecting its taste and potentially harming consumer health [20]. Ensuring the quality and authenticity of honey is essential for consumers to enjoy its nutritional benefits. Various techniques have been developed to measure and analyze the physicochemical parameters of honey, including water content and glucose. Reported techniques include the use of refracometers [21], electrical conductivity [22], spectroscopy [23], stable carbon isotope ratio analysis [24; 25], chromatography [26; 27], Fourier transform (FT) Raman spectroscopy, and microscopic detection [28]. However, most of these techniques demand a significant amount of manual work and were not applied for practical honey quality assessment.