FAQ: What is the Lowest Concentration that can be Detected by the PicoRaman M3 Spectrometer?
FAQ series: This series of publications explores some of the most often-asked questions regarding Timegated® spectrometers and measurements. This is an updated version of the FAQ episode that was originally published in 2025.
The short answer to this question is that there is no universal lower limit to what concentration the instrument can detect. This parameter, often referred to as the limit of detection (LoD) or detection limit (DL), will depend entirely on the samples in question and the measurement settings. Let's explore the topic in more detail.
Understanding the Limit of Detection (LoD)
We can think of the LoD as the point where the analyte signal exceeds noise. In this context, noise encompasses all spectral signals that do not result from our analytes. This includes, for example, instrumental noise, fluorescence, and overlapping Raman signals from other components present in the sample. In other words, the LoD depends not only on the analyte of interest but also on the sample's chemical composition as a whole. For example, during a bioreactor run, glucose may have a higher LoD in the later stages of the process when the cell density is higher and thus the sample is more fluorescent.
Raman spectroscopy is an optical technology, and the results, including LoD, often depend on the measured material’s optical properties. One important factor is photon absorbance in a specific wavelength range. For example, a red, brown, or black sample may have a high absorbance in a 532nm range, meaning that the sample matrix alone may absorb a significant amount of 532nm excitation laser photons which may then result in fewer observed Raman photons. High absorbance may also result in a higher probability of the material being altered or burned by the laser which may then necessitate reduction in laser power.
How Measurement Settings Impact LoD
Measurement settings can also affect the LoD. For example, the sample might be sensitive to the excitation laser, and the reduction of laser power may result in lowered Raman signal intensities. The measurement length is also an important factor: longer measurements usually result in lower noise levels and thus lower LoD. This is why it is important to define and state the measurement parameters for a certain LoD value. The sample matrix and application requirements may place limits to available measurement time and other measurement settings.
Timegated® Raman Technology may provide an advantage compared with conventional Raman by reducing noise and signal “swamping” caused by fluorescence or thermal interference. Time-gating may also enable the use of shorter wavelength excitation by reducing fluorescence interference which usually leads to higher Raman intensities.
Practical Steps for Defining the LoD
In practice, to define the LoD for a specific analyte and sample matrix, you need a set of samples with varying concentrations of the analyte. The concentration range must be low and include concentration values that approach the LoD. The denser the concentration range in the vicinity of the LoD, the more accurate the estimation will be. The set should also include blank samples: samples where the analyte of interest is completely absent. The Raman spectra corresponding to these samples, once pre-processed using baseline correction and normalization can then be used to calculate the LoD.
When defining LoDs for a specific application, both the analyte and blank samples should represent the sample material that is encountered in the actual application. Using simplified or non-representative materials may lead to overly optimistic LoD estimates. Finding a representative blank sample with zero analyte concentration may sometimes be challenging. Creating representative sample materials for a dynamic process with changing material compositions may also pose challenges.
Methods for Calculating the LoD
Because Raman spectroscopy results in multivariate data, there are several ways to approach calculating the LoD, and the result will sometimes differ greatly depending on the chosen method. The idea is to find the concentration at which the Raman spectrum resembles that of a blank sample, plus a given margin. The magnitude of the margin determines the probability of false positives and negatives at the LoD.
IUPAC defines LoD as the minimum single result which, with a stated probability, can be distinguished from a suitable blank value.
One approach is to simply compare the spectra at different concentrations visually: what is the lowest concentration at which the analyte peaks are visible? This is of course an inexact approach with room for subjectivity, and a method based on quantitative analysis is often preferred. This means having some function or model to relate the spectral data to the concentration of the analyte. The LoD is then calculated by determining what concentration the function will assign to a standard blank sample with the standard amount of noise (again, plus a given margin). This is then interpreted as the LoD, as the model cannot reliably detect the presence of the analyte below this point.
The function in question will depend on how you utilize the spectral data. One option is to choose a single relevant variable from the spectrum, for example, the analyte’s highest peak, to analyze. Then a simple univariate linear function is sufficient. However, using a single point on the spectrum does not capture the entirety of the analyte signal, and LoD values calculated this way may be overestimated. Using the whole Raman spectrum, or at least some relevant region of it, captures more of the analyte signal, but necessitates the use of multivariate models like PLS. The model regression vector is then used in the LoD calculations. Alternatively, the multivariate information can be condensed into a single variable, for example by taking the area under the relevant analyte peaks. Then a simple linear model would again suffice.
LoD and LoQ
It is important to note that, no matter the complexity of the function used, the LoD estimate will be affected by model uncertainty as well as instrument and sample-related noise. For a more conservative estimate, this can be addressed by adding the model uncertainty to the LoD. Furthermore, the LoD merely gives the lowest reliably detectable concentration, which is not necessarily a concentration at which reliable quantitative analysis can be done. For this there exists a distinct but related parameter, the limit of quantitation (LoQ) or quantitation limit (QL), which is often as a rule of thumb 3 or 3.3 times the LoD.
IUPAC also reminds of the LoD/LoQ differentiation by including the following in the LoD definition: The LoD limit defines the point at which the analysis becomes possible and this may be different from the lower limit of the determinable analytical range.
Example: Determining LoD for Glucose in Bioprocessing Media Using the PicoRaman M3 Spectrometer
Again, no universal LoD can be given for the PicoRaman M3 spectrometer, but we can give an example in the case of glucose. Glucose was added to cell culture media at concentrations of 0, 1, 2, 3, 4, 5, and 6 g/L, and based on visual inspection of the spectra, we were able to see that the LoD was less than 1 g/L. We then made a statistical estimate for the exact value of the LoD. A PLS model was built with the samples’ Raman spectra, and using the regression vector of the model, the LoD was calculated to be approximately 0.03 g/L. When allowing for the model uncertainty, the LoD for glucose in this bioprocessing media would be no greater than 0.42 g/L. However, it needs to be considered that no samples with glucose concentration at these values were included in the dataset.
The observant reader may notice after reading the above paragraph that it does not state specifics like the utilized media type or the time used for each measurement. The key takeaway is that each LoD depends on calculation/determination method, and it is specific to a specified sample type and measurement parameters. No single LoD value can be stated for a given analyte that would hold true for all sample types and measurement configurations.
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