1. Introduction
Technological developments have made every area of our lives easier. One of the developments has taken place in the food industry because biosensor-based sensing technologies offer advantages in industrial processes and also in health and chemical ones [
1]. In order to ensure safety and hence to increase food quality, the monitoring of contaminants and impurities such as preservatives in natural and daily foods has become a major interest [
2,
3,
4]. Milk and products made from milk have a special place not only in our daily nutrition but also in our health. Because of the fact that they can carry harmful bacteria and microorganisms, they can spoil the products and make people sick. For this reason, many researchers have attempted to develop biosensors for detecting compositions and some contaminants such as enterotoxins, antibiotics, bacteria, aflatoxins [
5,
6,
7,
8,
9] and monitoring some critical parameters such as the cutting time, pH, temperature, and enzyme concentration [
10,
11,
12,
13,
14,
15,
16] in milk and its products.
In order to produce quality and healthy products and to reduce infection risks, the purity of milk must be monitored at every stage of the process [
17,
18,
19]. This is because researchers have used optical biosensors, especially by using light-matter interactions at both the molecular and bulk levels, for detection or monitoring of the critical parameters in milk and its products [
8,
10,
20]. Optical biosensors utilize light-matter interactions at different levels and they have interesting features and abilities when compared to conventional electronic sensors such as immunity to electromagnetic interference, high sensitivity and selectivity, label-free detection, and ability for remote sensing [
21,
22].
There are some successful examples of fiber optic biosensors in open literature. Hao et al. used a fluorescence-based fiber optic probe to detect melamine in dairy samples such as liquid milk, yoghurt and baby formula milk [
20]. They achieved detection with high sensitivities ranging from 12.62 to 284.18 µg/L. Castillo et al. determined the milk cutting time with a fiber optic sensor by measuring backscattered light. They also monitored milk coagulation with the sensor [
10]. The evanescent field created by the light passing through the fiber with total internal reflections can also be used for sensing purposes [
20]. A plastic optical fiber (POF) biosensor was proposed by Wandermur et al. to detect
Escherichia coli [
8]. In such sensor designs, a bent or tapered sensing area offers better sensitivities [
8,
23,
24,
25]. In addition to fluorescent or absorption-based techniques, Jain and Sarma used the light-scattering technique to modulate UV-vis radiation for the online analysis of milk [
4] and Liu et al., used near-infrared spectroscopy for similar purposes [
5].
In this work, we designed and implemented a fiber optic sensor made of plastic optical fibers to detect some preservatives such as formaldehyde, hydrogen peroxide, and sodium carbonate. In order to ensure better interactions, we coiled the fibers with different turns. As a result, our simple design has been successfully able to detect the preservatives at concentrations of less than 5%.
3. Results and Discussion
Some preservatives such as formaldehyde, hydrogen peroxide, and sodium carbonate, etc., are used to prevent acidity in milk [
36]. In this work, we prepared different solutions by using commercial low-fat (0.1%) milk in which these preservatives were added in different concentrations. The refractive index of the milk increases up to 1.35093 with the preservatives added, while the initial value is 1.34550. It is well known that the refractive indices of the samples are highly dependent on the temperature. So we conducted the experiments between the temperatures of 24 and 26 °C in order to prevent index fluctuations in the samples. The measurements for the different concentrations of the preservatives are given in
Table 3,
Table 4,
Table 5 and
Table 6. The tables show the readouts of P-233 because it has better sensitivities. We did not use P-331 because it has a 3-mm-diameter POF which creates immeasurable losses due to over-bending. This situation points out, in our designs, that bent-dependent power losses will increase as the POF diameters get larger since the mandrel diameter is constant at 3 mm. A detailed discussion of the losses due to bending can be found in Reference [
37]. Note that in all the sensor readouts in the tables, I
0 and I
1 are in arbitrary units; the readouts get higher when the refractive index of the surrounding medium increases. Also note that we used commercially available preservatives to adjust the refractive indices. For example, hydrogen peroxide-39 means that the commercial packaging contains 39 mL pure hydrogen peroxide and 61 mL distilled water. This simple explanation is valid for the other preservatives.
As can be seen from the tables, the sensor probe P-233 can respond to very small changes in the concentration of as much as 1.24%, while the average is 1.43%. The sensitivity in terms of the refractive index difference has very interesting results. The maximum difference in the refractive index is 1.34612 − 1.34550 = 6.2 × 10
−4 (in
Table 6, rows 2 and 1) while the minimum value is 1.34686 − 1.34674 = 1.2 × 10
−4 (in
Table 3, rows 11 and 10). These numerical evaluations show that the sensor probe is able to detect 1.5% changes in concentrations or 5.0 × 10
−4 changes in refractive indices, roughly.
As another performance evaluation, we used a normalized response (
R) as given below:
where
xi refers to any of the I
0−I
1 values in
Table 6 while
xmax and
xmin are the maximum and minimum values of the column, respectively. Then we depicted the response of P-233 for sodium carbonate-25 solutions in terms of
R graphically in
Figure 5. It can clearly be seen that there is an excellent linearity between the concentration and normalized response. In order to test the repeatability of the responses, we made an additional measurement. The errors for the measurements are under 3%. These results were shown with error bars in
Figure 5.
The sensor response of probe P-233 in terms of the refractive index change is shown in
Figure 6. It can be clearly seen from the figure that there is an excellent linear relationship between the refractive indices and the sensor responses.
4. Conclusions
A fiber optic sensor made by bent plastic optical fibers has been presented. The sensor is sensitive to the refractive index changes determined by the concentrations of the medium surrounding the sensing area. The surrounding medium is low-fat milk, the refractive index of which is altered by some preservatives, i.e., formaldehyde, hydrogen peroxide, and sodium carbonate. By adding the preservatives, the resulting refractive indices are changed between 1.34550 and 1.35093 for the minimum (0%) and maximum (14.3%) concentrations of the sodium carbonate-25, respectively. The average change in the concentration is about 1.43%. As a result, we obtained excellent linearity between the concentration and normalized response of the sensor.
It is concluded that the sensor presented in this work can be adopted in liquid food processes to monitor for any target parameter subject to refractive index changes.