Components for Oxygen:
NeoFox Phase Fluorometer
RedEye® Oxygen Patches (Headspace and In-Solution measurement)
Bifurcated Fiber Optic probe

Components for pH:
Jaz Spectrometer
LS-1 Tungsten Light Source
Bifurcated Fiber Optic Probe
Reflective pH Patches

Experimental Procedure:
•    Oxygen Patches were placed inside the Bio-flask to monitor the oxygen in headspace and in solution.
•    pH patch was placed in solution to monitor pH changes during the fermentation process.
•    Fresh red grapes were mashed and the must was left to sit for 2 days.
•    The liquid was added in the bio-flask. Initial measurements were recorded and yeast cells and nutrients were added to start the fermentation process.
•    This process was observed over a period of 60 hours.

Optical Oxygen Sensors:
•    Prominent method for luminescence sensing in which the lifetime of the indicator compound changes in response to the analyte sensed (phase measurement).
•    A fluorescence method measures the partial pressure of dissolved or gaseous oxygen. The fluorescence is generated at the tip of the optical electrode by a light source.
•    When oxygen in the gas or liquid samples diffuses into the thin film coating, it quenches the fluorescence.
•    The degree of quenching correlates to the level of oxygen pressure.

RedEye Oxygen Sensor Patch:
•    RedEye is a revolutionary oxygen sensing product designed specifically to measure oxygen.
•    RedEye consists of a sensor coating formulation trapped in a sol gel matrix, immobilized and protected from the package contents
•    The RedEye patch has no minimum and maximum diameter  sizes, but typically sizes will vary from a few millimeters to several centimeters
•    RedEye can be easily integrated into any system because of its self-adhesive acrylic  patch having the sensor coating formulation.

O2 Sensing Electronics – NeoFox:
NeoFox is an instrument platform for measurement of fluorescence lifetime and phase for oxygen sensing
•    The frequency domain electronics uses a blue LED excitation and an  avalanche photodiode for detection.
•    A bifurcated optical fiber carries excitation light produced by the blue LED to the thin-film coating of the RedEye Oxygen Sensor
•    Fluorescence generated at the surface of the RedEye Patch is collected by the probe and carried by the optical fiber to the detector.

Lifetime Measurement Technique:
The phase shift between the blue LED excitation and emission signal of fluorescence is used to calculate lifetime.

Advantages of Optical Oxygen Sensors:
•    Uses fiber optic cable for non-intrusive measurements
•    Not contaminated by water or other solutions
•    Immune to EMI
•    Non-electrical, non-conductive
•    Operable in temperature and concentration range of various applications
•    Simple calibration
•    Works with colored samples without any color or light interference

Smart pH Technology:
•    pH buffers used for calibration, references taken by software
•    Absorbance curves seen as pH increases
•    Absorbance peak at 620nm, baseline correction at 512 nm

Temperature Compensation:
Compensation for temperature effects is achieved through the van’t Hoff equation:

•    Isothermal correction corrects pH value based on user-input temperature
•    Dynamic temperature correction available for non-isothermal systems with temperature monitoring

Result Analysis and Conclusion:
•    The graph shows the complete measurement of both oxygen and pH over a period of 60 hours.
•    The next graph shows the measurements over the first two hours. The oxygen sensor in solution quickly dropped from air saturation as soon as the yeast cells and nutrients were added. The pH sensor in solution dropped slightly as the oxygen decreased and CO2 is released. Hence the drop in pH value.
•    The following graph indicates the oxygen sensor in the headspace stays at air saturation approximately the first 2.5 hours. Once the oxygen in solution is completely quenched, the yeast cells and nutrients start consuming oxygen from the headspace.
•    Conclusion: Ocean Optics sensor patches are able to monitor both oxygen and pH non-intrusively which can be used in the fermentation industries.

A 2-meter 35?m bifurcated borosilicate bundle was used inside a T-300 sleeve, and an LS-1 tungsten halogen light source was used. All components were placed inside an environmentally controlled chamber, along with a second beaker of seawater being monitored by a Ross pH electrode. The beakers were sealed with Parafilm®, and the probes kept a tight seal with the film to prevent evaporation. The experimental setup is pictured below:

Galvanic corrosion became apparent with the use of the stainless steel sleeve, most likely due to improper sealing of the mirror’s metal from the steel. This led to accumulation of rust and sediment on the mirror, steadily causing a continued tilt in the absorbance curve. The typical pH algorithm looks at two wavelengths, an analytical wavelength and a baseline correction to account for vertical offset.

Though, a tilt in the absorbance spectra skews these values and yields incorrect measurements. To correct for this, an accompanying algorithm was used to eliminate this tilt effect, bringing the absorbance spectra back to its appropriate position, knowing that 750nm and 509nm (isosbestic point) should be pegged at zero absorbance. The algorithm is shown below, followed by the plot showing the corrected absorbance curve:

Knowing that it is required to monitor three wavelengths in order to account for the tilt, a long-term experiment was run to monitor pH patch stability. Analysis was performed that calculated the continuous pH assuming the original algorithm alone using a 750nm baseline correction, as well as a 509nm (isosbestic point) correction, and also using the tilt correction algorithm that looks at all three wavelengths. The plot of these three trends is shown below:

Clearly the original approach of using a single wavelength for baseline correction is not feasible for long-term measurement; rather, we see that the tilt algorithm is able to account for these absorbance curve distortions and produces a very coherent trend. The probe originally reads sea water as being roughly pH 8.2, and then drifts downwards to just above pH 6, where it equilibrates. This drift is most likely due to galvanic corrosion reactions occurring, which alter the pH of the system.

Ocean Optics also makes a transmissive probe of the same design using chemically inert peek material. This experiment was repeated using this alternate model, the TP-300, again with the Ross pH electrode running in parallel.

The accumulation of sediments and particles on the mirror and/or lens led to the absorbance curve tilt phenomenon previously seen, though this occurs much more slowly than the stainless steel probe. The system equilibrates after roughly 20 hours, and remains at a constant pH for the following 30 hours, showing the potential for strong long-term stability. A comparative plot shows the readings of the optical pH probe and the Ross electrode, with the electrode’s values being recorded manually at five discrete times:

The drift of the Ross pH electrode is slightly over 0.03 pH unit per day, which is roughly 15 times more drift than the specification reported in the user manual. While the Ocean Optics pH probe showed enhanced stability over the Ross electrode, the measurement was cut short due to light source failure. The LS-1 light source bulbs are offered in 900 hour and 10,000 hour lifespans; the longer-use bulb is recommended for long-term measurements. LED(s) may also be used with these sensors as another alternative. This study has been vital in determining a number of aspects and limitations for this optical pH probe system, some notable points include:

- The peek TP-300 probe should be used over the stainless steel version for pH measurement in seawater or high salinity environments; corrosion occurs extremely quickly with the stainless steel and sediment accumulates on the mirror.

- As sediments form on the mirror and/or lens, the absorbance curve may show a tilting distortion; this can be corrected via a dynamic algorithm that looks at three wavelengths to eliminate the effect.

- The light source should be relatively new and stable when performing long-term measurements. As the light source begins to die, there is a non-uniform intensity decay that causes an incorrect pH reading drift, followed by the light source finally dying completely. LED’s may be used as an alternative.

Algorithms Used:

pH Calculation:

Absorbance Spectra “Tilt” Correction:

A reflective pH patch was affixed to the inner wall of a small 7mL tube, and was held in place using a ring stand and clamp. A 600um bifurcated reflective probe was connected to an LS-1 light source with a blue filter, as well as a USB2000 spectrometer with grating #1, 200um slit, and no lens installed. The first feasibility test used clear buffers instead of the muddied buffers, in order to observe the performance. The experimental setup is pictured below, along with the plot of the resulting titration.

Although the curves showed a slight distortion, they followed the expected trend and produced a linear calibration plot. Dirt was obtained and mixed in with the buffer solutions; the experimental setup is shown below.

This yielded a very interesting titration plot, unlike any that had been seen before:

Typically for reflective pH patches, the peak is observed at 620nm and the baseline correction is done at 509nm. In this case, however, we see the peak had shifted closer to 635nm, and the 509nm region was distorted completely. As a result, 750nm was used as the baseline correction wavelength, which produced an incredibly linear calibration plot, as seen below.

This application has been critical in determining the effect of turbidity on the absorbance curves for the reflective pH patches, and has concluded that the correct wavelengths for acquisition and baseline need to be chosen based on the nature of the analyte solution.

Background
The Chemistry Department at the University of Washington is performing a research study where the measurement of oxygen in the headspace of Acetonitrile is critical. Since acetonitirle is an organic solvent and the vapors of acetonitrile are harsh, a sensor which can resist the fumes is applicable for this environment. The Hioxy oxygen sensor design my Ocean Optics was tested for this application.

Equipment
* Phase Fluorometer Electronics (MFPF)
* Bifurcated Fiber Optic Cable
* Hioxy-R Sensor

Feasibility Test Procedure
The MFPF electronics is an instrument platform for measurement of fluorescence lifetime and phase. This frequency domain electronics uses a blue LED excitation and a photodiode for detection. A fluorescence method is used to measure the partial pressure of dissolved or gaseous oxygen. A bifurcated optical fiber carries excitation light produced by the blue LED to the thin-film coating of the Hioxy-R sensor.. Fluorescence generated at the tip of the probe is collected by the probe and carried by the optical fiber to the detector of the MFPF. The phase shift between the blue LED excitation and emission signal of fluorescence is used to calculate the lifetime.  The Lifetime is an essential parameter for the calculation of oxygen.

To test the feasibility of the Hioxy sensor in the Acetonitrile headspace, the Hioxy Sensor is evaluated for its performance before exposure to the acetonitrile vapor.

The Hioxy sensor is exposed to Nitrogen and then to Air as show in Figure 1. The ratio of the lifetime from Nitrogen to Air is noted to be approximately 4.01. Now the sensor is exposed to the vapors of acetonitrile for about 2 hours. After the exposure the sensor is pulled out from the vapors and left in ambient conditions. The ratio of Nitrogen to air is measured again in terms of lifetime. The ratio after this exposure has changed to 4.27. The sensor is again exposed to acetonitrile vapor and the ratio is measured after exposure to be the same at 4.27.

Results
As shown in Figure 1, the Hioxy Sensor looks very stable in the headspace of the Acetonitrile container. The ratio of Nitrogen to Air has changed after the first exposure to Acetonitrile vapor. After the first exposure the ratio stays the same. This means there is a one time effect on the sensor when exposed to acetonitrile vapor.

Conclusion
The Hioxy sensor can be used to measure oxygen in the headspace of Acetonitrile. When a sensor is sold for this application, the sensor needs to be cured with acetonitrile vapor before calibration.

Also note: The sensor needs to be placed in acetonitrile vapor for at least 2 hours before use.

1    INTRODUCTION

1.1    Microorganisms in blood

Microorganisms are one celled organisms such as viruses, fungi and bacteria. Presence of microorganisms is harmful and cause diseases. The presence of microorganisms in blood cultures plays an important role in the diagnosis of different diseases. Different methods have been in existence to detect the presence of microorganisms in blood cultures. Early detection of such organisms is of primary importance to the selection of appropriate therapies and doses to be adopted on patients . Blood culturing systems are bioreactor system which involves the process of selectively growing microorganisms under optimized conditions. Blood culturing systems are closed culture systems where blood along with the growth media is operated under constant temperature along with continuous mixing. The numbers of microorganism increase due to respiration process and establish reactions with blood components changing the forms of hemoglobin. In the absence of microorganisms irrespective of the growth media present, the blood components do undergo changes due to aging of the red blood cells. As the microorganism’s density increases in the blood culture, partial pressure of oxygen is reduced and partial pressure of carbon dioxide is increased as a part of respiration process.

Automated systems are being developed to continuously monitor the different metabolic changes happening in the blood contents along with the changes in the partial pressure of oxygen/carbon dioxide consumed/generated respectively. The instruments primarily constitute the detection system to capture the data points at different intervals to form mathematical models to study the behavior of microorganisms and their growth patterns. The information collected using such systems helps us to understand the time period when the microorganisms have grow and aid in the selection of system parameters optimum to detect the different microorganisms. Some of the changes such as conversion of oxy to deoxyghemoglobin within the red blood cells have been detected using spectroscopy methods which provide growth behavior of organisms . As oxygen is necessary for cell respiration and is consumed during the growth phase of a cell processes for aerobic microorganisms. The cells reproduce and their cell density increases during the growth phase leading to increased oxygen consumption by the cells. The cells consume the dissolved oxygen from the liquid media (blood culture).

This paper presents the application of smart cuvette coated with oxygen sensitive sol gel coating which acts as a detection system to measure the dissolved partial pressure of oxygen in blood culture systems and the trend in oxygen consumption in response to the increasing density of microorganisms

2    SYNTHESIS OF NANO POROUS SOL GEL MATRIX AS A MOLECULAR PROBE FOR DISSOLVED OXYGEN

A ruthenium compound was immobilized in an organically modified silicate (ORMOSIL) using sol gel process. Methyltrimethoxysilane (MTMS) was used as the sol gel precursor. Appropriate amount of water and alcohol is added to the precursor to induce hydrolysis and condensation polymerization. Sub ppb levels of DO were able to be detected using the sol gel coating. Organically modified silicate (ormosil) sol-gel thin films have many advantages over their inorganic sol-gel and polymeric counterparts for sensing applications .

3    MATERIALS AND METHODS

3.1    Cell culture system design (Bioreactor)

An optical system is integrated to monitor the oxygen levels in a bioprocess system in a continuous fashion. The system built is a small scale version of the bioreactor. The integration involves the optical oxygen sensing system with the bioprocess system built to grow cells at constant temperature. Each of the components is described in detail in the following section:

3.2    Smart Oxygen Cuvette

Smart oxygen is a revolutionary oxygen sensing product designed for monitoring the dissolved oxygen in samples for biological and medical applications. Smart oxygen cuvette consists of a sensor coating formulation trapped in a sol gel matrix, immobilized and protected from the package contents. .The cuvette (Glass flourometer cell, Rectangular, Starna Cells Inc, CA) is the cell growth container of the bioprocess system. The Smart Oxygen cuvette has oxygen sensor coating formulation integrated with the cuvette on the inner lining of one of the side as shown in Figure 1

3.3    Qpod

The qpod is a complete sample compartment for fiber optic spectroscopy, including a peltier-controlled cuvette holder with magnetic stirring, and fused silica lens systems with SMA fiber optic connectors. The collimating /imaging/mirror optics enables the collection of rays and focus on the collection fiber. The qpod is equipped with Quantum Northwest TC125 Temperature Controller for temperature control and magnetic stirring to enable the cells in the cuvette to be in continuous stirring mode. As the cells have to be in a continuous stirring mode in a bioreactor, so magnetic stirring feature enables a good control on the stirring aspect integrated into the system .

3.4    NeoFox

The NeoFox Phase Fluorometer is an instrument platform for measurement of fluorescence lifetime and phase. This frequency domain electronics uses a blue LED excitation and a photodiode for detection. A fluorescence method is used to measure the partial pressure of dissolved or gaseous oxygen. A bifurcated optical fiber carries excitation light produced by the blue LED to the thin-film coating of the Smart Cuvette. Fluorescence generated at the surface of the patch is collected by the probe and carried by the optical fiber to the detector of PF. The phase shift between the blue LED excitation and emission signal of fluorescence is used to calculate the lifetime. The Figure 2 below is a representation of the phase measurement.  A new compact phase flourometer, NeoFox developed by Ocean Optics is used in this system design.

Oxygen as a triplet molecule is able to quench efficiently the fluorescence and phosphorescence of certain luminophores. This effect (first described by Kautsky in 1939) is called “dynamic fluorescence quenching.” Collision of an oxygen molecule with a fluorophore in its excited state leads to a non-radiative transfer of energy. The degree of fluorescence quenching relates to the frequency of collisions, and therefore to the concentration, pressure and temperature of the oxygen-containing media. When oxygen in the gas or liquid sample diffuses into the thin-film coating, it quenches the fluorescence. The degree of quenching correlates to the level of oxygen pressure.

4    SENSOR CALIBRATION

In order to make accurate oxygen measurements inside the cuvette, the calibration of the Smart Oxygen Cuvette was performed using the Linear (Stern-Volmer) algorithm. Since this experiments were performed at room temperature (~25C), temperature compensation during the calibration was not required.
Temperature does not affect the fluorescence decay time, fluorescence intensity, collision frequency of the oxygen molecules with the fluorophore, and the diffusion coefficient of oxygen as long as the temperature is maintained between ± 1 °C of the calibrated temperature.

Linear (Stern-Volmer) Algorithm: The Linear (Stern-Volmer) algorithm requires at least two standards of known oxygen concentration. The first standard must have 0% oxygen concentration and the last standard must have a concentration in the high end of the concentration range. The Smart Oxygen Cuvette patch was calibrated at 0% and 20.9% oxygen. The calibration curves were generated from these standards and the linear algorithm was used to calculate oxygen concentration values for unknown samples.

The fluorescence lifetime (?) can be expressed in terms of the Stern-Volmer equation where the fluorescence is related quantitatively to the partial pressure of oxygen:

Where t0 is the lifetime of fluorescence at zero pressure of oxygen, ? is the lifetime of fluorescence at a pressure p of oxygen, and k is the Stern-Volmer constant.

For a given media, and at a constant total pressure and temperature, the partial pressure of oxygen is proportional to oxygen mole fraction. The Stern-Volmer constant (k) is primarily dependent on the chemical composition of the sensor formulation. The Stern-Volmer constant (k) is temperature dependent. All measurements should be made at the same temperature (± 1 °C) from the calibration experiments. If temperature compensation is needed, then the relationship between the Stern-Volmer values and temperature is defined as:

The lifetime of fluorescence at zero pressure of oxygen depends on details of the optical setup: the power of the LED, the optical fibers, loss of light at the probe due to fiber coupling, and backscattering from the sample. It is important to measure the lifetime of fluorescence at zero pressure of oxygen (I0) for each experimental setup .

5    OPTICAL SENSING SYSTEM INTEGRATION WITH CELL CULTURE SYSTEM

The Smart Oxygen cuvette is placed in a qpod and the side of the cuvette which has the oxygen sensor coated material is interfaced with the bifurcated reflectance probe. The bifurcated reflectance probe is connected to the NeoFox system. The LED source on the NeoFox provides the excitation light and is coupled to one of the legs of the bifurcated optical probe. The reflected florescence light is coupled back into the other leg of the bifurcated probe and terminated at the detector surface on NeoFox. The NeoFox interfaces with the NeoFox Viewer Software (Ocean Optics Inc.) which measures the oxygen levels. The complete system used to measure oxygen levels is shown in Figure 3

5.1    Experimental Setup

The oxygen sensing experiment was carried out in a Smart Oxygen Cuvette. To build a two point calibration, the nitrogen gas is diffused into the cuvette for 0% oxygen and then air is diffused into the cuvette for 20.9% oxygen. The two points are captured and a calibration curve is built to quantify the oxygen levels in the range of 0 – 21% from the life time measurements. We start our experiment by placing Whole goat blood and water (1:1.5) in the cuvette, magnetic stirrer is placed in the cuvette and the stirring speed is set to a maximum using the qpod temperature and magnetic controller interface. The temperature is set at room temperature. The NeoFox viewer software starts logging the data from the instant diluted blood is placed in the cuvette. The oxygen concentration in blood starts at a low concentration of oxygen and increases until almost air saturation. Once the oxygen level increases and is stable, yeast cells are added to the blood in the cuvette. The oxygen quenching is observed over a period of time. After each run all of the dissolved oxygen sensor data is logged. The cuvette is washed and dried and placed back into the qpod for the next run. The experiment is conducted 3 times.

To replicate the bioprocess conditions, nutrients were added to the blood to study the rate of dissolved oxygen in the cell culture media. The experiments were repeated with the yeast cells of 200mgrams. The sensor data was logged for a period of 30 minutes and after each run, the cuvette was rinsed and dried with vacuum for the next run. The experiment was repeated three times.
Another set of experiments was run to study the time it takes to quench the dissolved oxygen in a closed cuvette. Different amounts of yeast were added to the diluted blood and the time it takes to quench the dissolved oxygen is recorded.

Figure 3 shows the bioreactor setup with oxygen sensor patch interfaced with bifurcated fiber optic probe. The legs of the fiber optic probe are connected to the LED excitation source and detector on the NeoFox. The USB interface on the NeoFox transfers the data to the NeoFox Viewer Software for the data logging process

6    RESULTS AND DISCUSSION

The Smart Oxygen cuvette is a small-scale system used to study the effects on the oxygen partial pressure of the blood sample in the presence of microorganisms in the blood. During the experiment while the blood is diluted with water and added to the cuvette very low concentration of dissolved oxygen is present. Due to stirring the blood in a closed system cuvette the oxygen level in the dissolved blood eventually rises up to air saturation. Once the dissolved oxygen level is stabilized at air saturation, the yeast cells are added to observe the consumption of the oxygen

The yeast cells when dissolved in blood started consuming the oxygen through the liquid cell membrane interface by the diffusion process. The system is calibrated and the dissolved oxygen levels are monitored when the yeast cells are added and the measurements have been carried out for a time period of approximately 30 minutes. The experimental results (n = 3) in Figure 4 show the performance of Smart Oxygen Cuvette in measuring the oxygen levels continuously as the bioprocess happens in the cell culture system. As the cells are consuming the oxygen in the liquid media through diffusion, the oxygen depleted in the liquid media is what the Smart Oxygen Cuvette is really sensing. The same experiment can be extended to a single cell, in a micro fluidic well culture system. The one side of the cuvette has the oxygen sensing coating which measures the oxygen level depleted in the liquid media surrounding the cell. Using the diffusion parameters of the cell, one can calculate the oxygen consumed by each cell. It is observed that adding 200 milligrams of yeast to about 2.5mL of diluted blood can quench the oxygen to approximately 1 % within 20 minutes. The three runs show very similar results as shown in Figure 4.

Figure 4 shows the dissolved oxygen levels in a bioreactor system measured using a Smart Oxygen Cuvette

The small scale culture applications have the advantage of the studying the effect of multiple nutrients/environmental conditions on the oxygen levels consumed and also on the process throughput. With an objective to study the performance of the performance of Smart Cuvette in sensing oxygen levels in the cell culture, we have performed another set of experiment varying the amount of yeast dissolved in blood. The oxygen is consumed by the cells faster if the amount of cells is more. Figure 5 shows the performance of Smart Oxygen Cuvette in measuring the dissolved oxygen levels in cell culture environment with different yeast amount added to diluted blood.

Figure 5 shows the oxygen consumed by cells when different amounts of yeast is added to diluted blood as measured by Smart Oxygen Cuvette

7    CONCLUSION

A Smart Oxygen cuvette is reported to provide superior measurements of dissolved oxygen in important biological experiments such as in blood culture/bioreactor systems. The integration of Smart oxygen cuvette when combined with advanced phase fluorometry can be used to develop portable systems to measure presence of bacteria in different blood cultures. The fluorescent technology based on oxygen quenching has already proven it success in the mycobacterial growth indicator(TB test)  and is used to accurately identify mycobacteria .Development of a cost effective system integrated with multiplexing capabilities would open a new approach to study the presence of microorganisms in blood culture  system. As healthcare costs are rising and especially with the increasing incidence of TB cases, the proposed system can be used in the preventive healthcare to diagnose the presence of bacteria at an early stage from blood sample. Systems of this nature would accelerate the intervention procedures and facilitate the reduction of healthcare costs.

[ii] Debra E. Huffman, et al, “J.New method for the detection of micro-organisms in blood: application of quantitative interpretation model to aerobic blood cultures”, Biomed. Opt. 14, 034043 (2009), DOI:10.1117/1.3156837

Method:
pH Sensing

Hardware Used:
USB2000 Spectrometer: Grating #1, 200um slit, no lens installed
LS-1 Light Source
Bifurcated Reflective Probe, 600um
SpectraSuite Software

Measurement Mode:
Absorbance

Notes:

There was an interest in non-intrusively monitoring pH in tubes containing wet soil samples. This was significant for a number of reasons; this was the first time the reflective patches were to be tested in something other than a cuvette, on a curved surface rather, and this was also the first time an analyte solution was observed that contained sediment or turbidity.

A reflective pH patch was affixed to the inner wall of a small 7mL tube, and was held in place using a ring stand and clamp. A 600um bifurcated reflective probe was connected to an LS-1 light source with a blue filter, as well as a USB2000 spectrometer with grating #1, 200um slit, and no lens installed. The first feasibility test used clear buffers instead of the muddied buffers, in order to observe the performance. The experimental setup is pictured below, along with the plot of the resulting titration.

Although the curves showed a slight distortion, they followed the expected trend and produced a linear calibration plot. Dirt was obtained and mixed in with the buffer solutions; the experimental setup is shown below.

This yielded a very interesting titration plot, unlike any that had been seen before:

Typically for reflective pH patches, the peak is observed at 620nm and the baseline correction is done at 509nm. In this case, however, we see the peak had shifted closer to 635nm, and the 509nm region was distorted completely. As a result, 750nm was used as the baseline correction wavelength, which produced an incredibly linear calibration plot, as seen below.

This application has been critical in determining the effect of turbidity on the absorbance curves for the reflective pH patches, and has concluded that the correct wavelengths for acquisition and baseline need to be chosen based on the nature of the analyte solution.

Algorithm Used: