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Introduction

Thorough and reproducible quality control programs are paramount to a successful dairy processing operation. Such programs ensure that dairy products are safe to consume, meet brand standards for taste and texture, and deliver consistent experiences for consumers, all while maximizing margins and reducing waste. Failure to monitor quality parameters throughout the value chain can have a negative impact on finished product quality, and ultimately brand reputation.

A core component of most quality control programs is the use of analytical testing methods to verify key product and raw material composition, or proximate values, such as fat, protein, lactose, total solids, solids-not-fat. There are many options available for monitoring product composition from an analytical perspective, including primary methods such as chromatography, the Gerber butyrometric method, the Mojonnier gravimetric method or the Röse-Gottlieb method. However, most modern dairy processors opt to utilize more user-friendly and efficient secondary techniques, such as Fourier transform infrared spectroscopy, or FTIR. Regardless of the analytical technique chosen, the complex nature of milk samples adds challenges to the analysis, which, if left unaddressed, could compromise data quality. In this white paper, we will discuss the role that FTIR plays in optimizing dairy production, as well as the importance of mitigating matrix effects through sample preparation techniques.

 
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Fourier-transform Infrared (FTIR) Molecular Vibrational Spectroscopy

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Figure 1 LactoScope FT-A FTIR Instrument for Dairy Testing

FTIR is a broadly used analysis technique in many industries for a multitude of applications. It is used for qualitative, quantitative, and quality measurements with applications ranging from materials identification in industrial applications, to testing for the percentage of an active ingredient in a pharmaceutical sample, to food quality testing. Infrared spectroscopy is a technique based on measuring the interaction of infrared light with matter. Infrared light of specific wavelengths gets absorbed by specific chemical bonds present in the sample. The remaining light is collected by a detector through either reflection or transmission. The resulting spectrum can be used to determine the composition of the sample, as well as how much of the respective component is present using chemometrics. The energy range of the infrared light extends from 700nm – 1mm (14,289cm-1 to 10cm-1), and interacts only with samples containing vibrational modes of its chemical bonds capable of absorbing these wavelengths/energies. The technique itself is non-destructive and rapid, with measurement times of less than one minute – excluding any sample preparation required.

FTIR Applications in Dairy Testing

In the dairy industry, FTIR technologies are widely utilized as a means of qualitatively and quantitatively analyzing and verifying raw material and finished product quality. FTIR is frequently used in the following dairy quality control activities:

  • Raw Material Screening: Utilized to monitor the composition of raw materials, such as raw liquid milk, for uniformity and compliance. Dairy processors typically monitor fat content in incoming raw milk supplies to ensure fair payment to suppliers, and to plan for production of processed dairy products which rely on fat from raw milk.
  • Adulteration Detection: FTIR technologies can enable the detection of adulteration and abnormalities in raw milk, in both targeted searches for components such as urea, melamine, ammonium, and glucose, or untargeted adulteration screenings. Identification of adulterants in raw milk ensures that producers don’t contaminate pure raw milk samples with contaminated supply.
  • Finished Product Quality Control: Testing to confirm optimal and consistent levels of components such as fat, protein, lactose, solids, fatty acids, and pH ensures finished products meet brand guidelines and formulations are optimized for margin maximization.

Matrix Complexities in Raw Milk Testing

Animal-sourced raw milk is an inherently complex matrix, owing to a number of critical factors. This complexity, without mitigation, can present challenges when analyzing samples with FTIR instruments.

Diversity of Components

Milk contains a large variety of components in various concentrations as noted in Table 1, with water, fat, protein and carbohydrates (lactose) as the primary constituents1. Several of these components, including water, fat and protein content, can vary substantially depending upon the species and breed of the animal, their diet, age, and the stage of lactation. The highest concentrations of fat in the raw milk of cows are typically found in colostrum, or the first milk produced following birth. A decline during the first 2 months of lactation is then appreciated, followed by a slow increase as lactation progresses2.

ParameterCowSheepGoatBuffaloCamel
Total Solids (%)11.8 – 13.018.1 - 20.011.9 - 16.315.7 – 17.211.9 – 15.0
Proteins (%)3.0 – 3.94.5 - 7.03.0 – 5.22.7 – 4.72.4 – 4.2
Casein/Whey Ratio4.73.13.54.62.7 – 3.2
Fat (%)3.3 – 5.45.0 – 9.03.0 – 7.25.3 – 9.02.0 – 6.0
Lactose (%)4.4 – 5.64.1 - 5.93.2 – 5.03.2 – 4.93.5 – 5.1
Ash (%)0.7 – 0.80.8 – 1.00.8 – 1.00.8 – 0.9    0.69 -.09

Table 1 – Average composition of raw milk samples across various species1.

Fat Structure

Fat globules are the largest structures in milk varying in size from 0.1 to 15μm and averaging 2.5µm in diameter. Although these molecules are the largest structures in milk, they can vary greatly in size and do not tend to be uniform throughout a sample. This inhomogeneity causes non-uniform sample thickness, which means concentration, and hence the absorption measurement, of fat molecules can be inconsistent throughout the sample.

When infrared light encounters fat globules, it can scatter unpredictably, rather than passing straight through the sample. This scattering effect distorts the intensity of the transmitted light and can reduce the accuracy of absorbance measurements.

Further, fat globules are coated in a phospholipid and protein membrane to create a stabilized emulsion in the water phase, or a suspension of droplets of one liquid in another3. The surface of fat globules is not perfectly smooth, which can cause additional scattering. The irregular surface of the globules can cause multiple reflections and scattering events within the sample, affecting the infrared light’s path and leading to less predictable and less repeatable spectra.

Protein Composition

Milk contains a variety of proteins, each with different structures and functions. The proteins in milk include hydrophobic caseins (such as αs1-casein, αs2-casein, κ-casein and β-casein) which form large clusters called micelles, water-soluble serum proteins, or whey, (including α-lactalbumin and β-lactoglobulin), and membrane proteins. These proteins form colloidal particles approximately 0.2µm in diameter. Protein micelles contain thousands of individual protein molecules, each with their own structure, which can affect their infrared absorption characteristics4.

Further, when heated or exposed to pH levels outside of their tolerance limits (typically 4.6 or lower) protein structures can be altered, or denatured, as bonds within the protein molecules are broken. As FTIR spectroscopy relies on detecting specific vibrational or rotational modes related to these structures, denaturation can shift, diminish, or alter these absorption features, complicating the interpretation of the FTIR spectra.

The above factors – diversity of components, fat structure and protein composition – can complicate the analysis of milk samples utilizing analytical techniques like FTIR. Proper sample preparation, utilizing homogenization techniques prior to analysis, can mitigate many of these matrix effects, and enable an accurate, representative, and reproducible analysis.

The Importance of Sample Homogenization

Nearly all commercially available finished milk is homogenized during processing to prevent components from separating prior to consumption. The importance of creating a homogenous mixture also holds true for analysis by techniques such as FTIR, as the analysis of a non-uniform sample can strongly impact the quality of results obtained from the analysis. Without homogenization, the fat globules in milk can be unevenly distributed, which can lead to inaccuracies in FTIR analysis, typically causing a result which is biased high.

The Process of Homogenization

Homogenization of raw milk samples is a mechanical process which breaks down fat globules to create a more uniform composition. The homogenization process can be conducted in a number of ways, including processing with a high-pressure, ultrasonic, or rotor-stator homogenizer. High-pressure homogenization is the most common form of homogenization prior to analysis using commercial analyzers. These homogenizers force the sample through a small crevice to forcefully break up large fat globules into small droplets, typically measuring less than 1µm.

Homogenizers can be single stage, in which the sample is pushed through the homogenizer once, or dual stage in which the sample is homogenized twice in succession. Dual stage homogenizers further break down the protein membranes surrounding fat globules, as some homogenized fat globules can lump together again following the initial homogenization process. Homogenizers can be stand-alone devices, or they can be integrated into an FTIR instrument, such as the Perten LactoScope FT-A, to reduce operator effort and analysis time, while also mitigating the potential for user error by automating the process.

Effects of Homogenization

Homogenization breaks down large fat globules which can range in size from their 2-5µm diameter in raw milk to a more uniform size of less than 1 µm throughout the sample. Without homogenization, large fat globules can lead to inaccuracies in FTIR analysis, typically resulting in fat predictions with are higher if the infrared light is directed through a large, non-uniform, globule during analysis. 

In addition to reducing the size of the fat particles, homogenization also disperses the particles more uniformly throughout the sample, as shown in Figure 2, further improving the reliability the analysis. This is crucial for FTIR, which measures the interaction of infrared light with specific molecular bonds. As such, variability in the sample can lead to inconsistent or inaccurate results. Further, the uneven distribution of fat or other components in a sample can lead to scattered or attenuated signals during FTIR analysis, which can degrade the quality of the spectral data. By reducing the size of fat globules, homogenization minimizes light scattering, leading to clearer and more accurate FTIR spectra. This allows for better detection and quantification of proteins, carbohydrates, and other components.

a-Microscopic-images-1250magnification-of-fat-globules-in-raw-milk-b-microscopic.png

Figure 2 - Microscopic images of fat globules in a) raw unhomogenized milk, b) raw milk homogenized for 120 seconds, and c) raw milk homogenized for 1200 seconds. The black scale bar in the bottom‐right corner represents 10 μm5. Shown for illustrative purposes only.5

Finally, homogenization prior to analysis can enhance the signal quality of an FTIR analysis by reducing the amount of noise present in the analysis, and minimizing the impact of the aforementioned matrix effects. Smaller and more evenly distributed fat globules are less likely to interfere with the infrared light, leading to sharper and more distinct absorption bands for the components of interest.

Conclusion

Analytical techniques, such as FTIR have enabled dairy producers to monitor the quality and consistency of their products throughout the value chain – from raw material receipt through finished product creation. When utilizing FTIR, it is critical for users to understand the complexities of the milk matrix, including the diversity of its components, the structure and potential interference of fat, and the composition of proteins. Many of these complexities can be mitigated through the use of sample preparation procedures, such as homogenization, to ensure sample analyses are both accurate and reproducible.

References

  1. National Research Council (US) Committee on Technological Options to Improve the Nutritional Attributes of Animal Products. Designing Foods: Animal Product Options in the Marketplace. Washington (DC): National Academies Press (US); 1988. Factors Affecting the Composition of Milk from Dairy Cows.
  2. National Research Council (US) Committee on Technological Options to Improve the Nutritional Attributes of Animal Products. Designing Foods: Animal Product Options in the Marketplace. Washington (DC): National Academies Press (US); 1988. Factors Affecting the Composition of Milk from Dairy Cows.
  3. Leser, Martin & Michel, Martin. (2008). Colloids in Milk Products. CHIMIA International Journal for Chemistry. 62. 783-788. 10.2533/chimia.2008.783.
  4. Bylund, G. et al., (2015). Dairy Processing Handbook (3rd ed.). Tetra Pak.
  5. Soltani Firouz, Mahmoud & Sardari, Hamed & Soofiabadi, Mahsa & Hosseinpour, Soleiman. (2022). Ultrasound assisted processing of milk: Advances and challenges. Journal of Food Process Engineering. 46. 10.1111/jfpe.14173.