Effect of ultrasonic homogenization on the Vis/NIR bulk optical properties of milk

Observation of a temperature dependent anomaly in the UV translucency of milk useful for UV-C preservation techniques

Milk fat globules and casein micelles are the dispersed particles of milk that are responsible for its typical white turbid appearance and usually make it difficult to treat with modern ultraviolet light (UV) preservation techniques. The translucency of milk depends largely on the refractive indices of the dispersed particles, which are directly affected by temperature changes, as incorporated triglycerides can crystallize, melt or transition into other polymorphs. These structural changes have a significant effect on the scattering properties and thus on the UV light propagation in milk, especially by milk fat globules. In this study, a temporary minimum in the optical density of milk was observed within UV wavelength at 14 °C when heating the milk from 6 to 40 °C. This anomaly is consistent with structural changes detected by a distinct endothermic peak at 14 °C using differential scanning calorimetry. Apparently, the optical density anomaly between 10 and 20 °C disappears when the polymorphic transition already has proceeded through previous isothermal equilibration. Thus, melting of equilibrated triglycerides may not affect the RI of milk fat globules at ca. 14 °C as much as melt-mediated polymorphic transitioning. An increased efficiency of UV-C preservation (254 nm) at the translucency optimum was demonstrated by temperature-dependent microbial inactivation experiments.

Agarose Gel Characterization for the Fabrication of Brain Tissue Phantoms for Infrared Multispectral Vision Systems

Synthetic phantoms that recreate the characteristics of biological tissues are valuable tools for systematically studying and comprehending physiologies, pathologies, and biological processes related to tissues. The reproduction of mechanical and optical properties allows for the development and evaluation of novel systems and applications in areas such as imaging, optics, ultrasound, or dosimetry, among others. This paper proposes a methodology for manufacturing agarose-based phantoms that mimics the optical properties of healthy brain tissue within the wavelength infrared range of 800 to 820 nm. The fabrication of such phantoms enables the possibility of testing and experimentation in controlled and safe environments toward the design of new near-infrared multispectral imaging systems in neurosurgery. The results of an experimental optical characterization study indicate the validity and reliability of the proposed method for fabricating brain tissue phantoms in a cost-effective and straightforward fashion.

Applications of optical property measurement for quality evaluation of agri-food products: a review

Spectroscopic techniques coupled with chemometric approaches have been widely used for quality evaluation of agricultural and food (agri-food) products due to the nondestructive, simple, fast, and easy characters. However, these techniques face the issues or challenges of relatively weak robustness, generalizability, and applicability in modeling and prediction because they measure the aggregate amount of light interaction with tissues, resulting in the combined effect of absorption and scattering of photons. Optical property measurement could separate absorption from scattering, providing new insights into more reliable prediction performance in quality evaluation, which is attracting increasing attention. In this review, a brief overview of the currently popular measurement techniques, in terms of light transfer principles and data analysis algorithms, is first presented. Then, the emphases are put on the recent advances of these techniques for measuring optical properties of agri-food products since 2000. Corresponding applications on qualitative and quantitative analyses of quality evaluation, as well as light transfer simulations within tissues, were reviewed. Furthermore, the leading groups working on optical property measurement worldwide are highlighted, which is the first summary to the best of our knowledge. Finally, challenges for optical property measurement are discussed, and some viewpoints on future research directions are also given.

Measuring the Optical Properties of Highly Diffuse Materials

Measuring the optical properties of highly diffuse materials is a challenge as it could be related to the white colour or an oversaturation of pixels in the acquisition system. We used a spatially resolved method and adapted a nonlinear trust-region algorithm to the fit Farrell diffusion theory model. We established an inversion method to estimate two optical properties of a material through a single reflectance measurement: the absorption and the reduced scattering coefficient. We demonstrate the validity of our method by comparing results obtained on milk samples, with a good fitting and a retrieval of linear correlations with the fat content, given by R2 scores over 0.94 with low p-values. The values of absorption coefficients retrieved vary between 1 × 10-3 and 8 × 10-3 mm-1, whilst the values of the scattering coefficients obtained from our method are between 3 and 8 mm-1 depending on the percentage of fat in the milk sample, and under the assumption of the anisotropy factor g>0.8. We also measured and analyzed the results on white paint and paper, although the paper results were difficult to relate to indicators. Thus, the method designed works for highly diffuse isotropic materials.

Discrimination of Milk Freshness Based on Synchronous Two-Dimensional Visible/Near-Infrared Correlation Spectroscopy Coupled with Chemometrics

Milk is one of the preferred beverages in modern healthy diets, and its freshness is of great significance for product sales and applications. By combining the two-dimensional (2D) correlation spectroscopy technique and chemometrics, a new method based on visible/near-infrared (Vis/NIR) spectroscopy was proposed to discriminate the freshness of milk. To clarify the relationship be-tween the freshness of milk and the spectra, the changes in the physicochemical indicators of milk during storage were analyzed as well as the Vis/NIR spectra and the 2D-Vis/NIR correlation spectra. The threshold-value method, linear discriminant analysis (LDA) method, and support vector machine (SVM) method were used to construct the discriminant models of milk freshness, and the parameters of the SVM-based models were optimized by the grid search method and particle swarm optimization algorithm. The results showed that with the prolongation of storage time, the absorbance of the Vis/NIR spectra of milk gradually increased, and the intensity of autocorrelation peaks and cross peaks in synchronous 2D-Vis/NIR spectra also increased significantly. Compared with the SVM-based models using Vis/NIR spectra, the SVM-based model using 2D-Vis/NIR spectra had a >15% higher prediction accuracy. Under the same conditions, the prediction performances of the SVM-based models were better than those of the threshold-value-based or LDA-based models. In addition, the accuracy rate of the SVM-based model using the synchronous 2D-Vis/NIR autocorrelation spectra was >97%. This work indicates that the 2D-Vis/NIR correlation spectra coupled with chemometrics is a great pattern to rapidly discriminate the freshness of milk, which provides technical support for improving the evaluation system of milk quality and maintaining the safety of milk product quality.

The Ability of Near Infrared (NIR) Spectroscopy to Predict Functional Properties in Foods: Challenges and Opportunities

Near infrared (NIR) spectroscopy is considered one of the main routine analytical methods used by the food industry. This technique is utilised to determine proximate chemical compositions (e.g., protein, dry matter, fat and fibre) of a wide range of food ingredients and products. Novel algorithms and new instrumentation are allowing the development of new applications of NIR spectroscopy in the field of food science and technology. Specifically, several studies have reported the use of NIR spectroscopy to evaluate or measure functional properties in both food ingredients and products in addition to their chemical composition. This mini-review highlights and discussed the applications, challenges and opportunities that NIR spectroscopy offers to target the quantification and measurement of food functionality in dairy and cereals.

Evaluation of MEMS NIR Spectrometers for On-Farm Analysis of Raw Milk Composition

Today, measurement of raw milk quality and composition relies on Fourier transform infrared spectroscopy to monitor and improve dairy production and cow health. However, these laboratory analyzers are bulky, expensive and can only be used by experts. Moreover, the sample logistics and data transfer delay the information on product quality, and the measures taken to optimize the care and feeding of the cattle render them less suitable for real-time monitoring. An on-farm spectrometer with compact size and affordable cost could bring a solution for this discrepancy. This paper evaluates the performance of microelectromechanical system (MEMS)-based near-infrared (NIR) spectrometers as on-farm milk analyzers. These spectrometers use Fabry–Pérot interferometers for wavelength tuning, giving them the advantage of very compact size and affordable price. This study discusses the ability of MEMS spectrometers to reach the accuracy limits set by the International Committee for Animal Recording (ICAR) for at-line analyzers of the milk content regarding fat, protein and lactose. According to the achieved results, the transmission measurements with the NIRONE 2.5 spectrometer perform best, with an acceptable root mean squared error of prediction (RMSEP = 0.21% w/w) for the measurement of milk fat and excellent performance (RMSEP ≤ 0.11% w/w) for protein and lactose. In addition, the transmission measurements using the NIRONE 2.0 module give similar results for fat and lactose (RMSEP of 0.21 and 0.10% w/w respectively), while the prediction of protein is slightly deteriorated (RMSEP = 0.15% w/w). These results show that the MEMS spectrometers can reach sufficient prediction accuracy compared to ICAR standard values for at-line and in-line fat, protein and lactose prediction.

Milk as a Complex Multiphase Polydisperse System: Approaches for the Quantitative and Qualitative Analysis

Milk is a product that requires quality control at all stages of production: from the dairy farm, processing at the dairy plant to finished products. Milk is a complex multiphase polydisperse system, whose components not only determine the quality and price of raw milk, but also reflect the physiological state of the herd. Today’s production volumes and rates require simple, fast, cost-effective, and accurate analytical methods, and most manufacturers want to move away from methods that use reagents that increase analysis time and move to rapid analysis methods. The review presents methods for the rapid determination of the main components of milk, examines their advantages and disadvantages. Optical spectroscopy is a fast, non-destructive, precise, and reliable tool for determination of the main constituents and common adulterants in milk. While mid-infrared spectroscopy is a well-established off-line laboratory technique for the routine quality control of milk, near-infrared technologies provide relatively low-cost and robust solutions suitable for on-site and in-line applications on milking farms and dairy production facilities. Other techniques, discussed in this review, including Raman spectroscopy, atomic spectroscopy, molecular fluorescence spectroscopy, are also used for milk analysis but much less extensively. Acoustic methods are also suitable for non-destructive on-line analysis of milk. Acoustic characterization can provide information on fat content, particle size distribution of fat and proteins, changes in the biophysical properties of milk over time, the content of specific proteins and pollutants. The basic principles of ultrasonic techniques, including transmission, pulse-echo, interferometer, and microbalance approaches, are briefly described and milk parameters measured with their help, including frequency ranges and measurement accuracy, are given.

Dependency of the optical scattering properties of human milk on casein content and common sample preparation methods

SIGNIFICANCE

Quantifying human milk composition is important for daily nutritional management in neonatal intensive cares worldwide. Photonic solutions based on visible light can potentially aid in this analysis, as energy content of human milk depends largely on fat content, and the optical scattering properties of human milk predominantly depend on the size and concentration of fat globules. However, it is expected that human milk scattering changes upon homogenization, routinely done before analysis, which may affect fat globule size.

AIM

The first aim of this study was to investigate how the most common homogenization methods (gently inverting by hand, vortexing, and sonication) affect the optical properties of human milk. The second aim was to estimate the scattering contribution of casein micelles, the second most dominant scatterers in human milk.

APPROACH

We combined diffuse reflectance spectroscopy with spectroscopic optical coherence tomography to measure the scattering coefficient μs, reduced scattering coefficient μs', and anisotropy g between 450 and 600 nm.

RESULTS

Sonication induced the strongest changes in μs, μs', and g compared to the gently inverted samples (203%, 202%, and 7%, respectively, at 550 nm), but also vortexing changed μs' with 20%. Although casein micelles only showed a modest contribution to μs and g at 550 nm (7% and 1%, respectively), their contribution to μs' was 29%.

CONCLUSIONS

The scattering properties of human milk strongly depend on the homogenization method that is employed, and gentle inversion should be the preferred method. The contribution of casein micelles was relatively small for μs and g but considerably larger for μs'.

Potential of Near-Infrared Spectroscopy to Evaluate the Cleaning Performance of Dishwashing Processes

Automatic dishwashing is a process which takes enormous amounts of resources (energy, water, chemicals). However, most of the dishwashing programs are designed and tested to clean the worst scenario for a certain kind of load items (glass, porcelain, etc.) and do not or only partly adapt to the actual load and soiling conditions. Thus, resources are wasted which could be avoided if a better adaptation to the actual status of the dishwashing process would be possible. It is, therefore, the aim of this study to investigate the possibility of using near-infrared technology to evaluate the status of the dishwashing process by analyzing the content of soil components already dissolved in the dishwashing water. Compared to other methods, the main advantage of near-infrared measurements is the possibility to differentiate between soils or soil components (carbohydrates, fats and protein) at very low concentrations. Near-infrared spectroscopy implemented in an automatic dishwasher could observe and evaluate an automatic dishwashing processes by using online measurements of the detachment of soils from soiled dishes. Thirty-seven model emulsions containing detergent, tap water, different soils and soil concentrations were created and measured by using near-infrared spectroscopy to demonstrate its suitability for the evaluation of dishwashing processes. The spectra were the basis of developing near-infrared calibration models for each soil component using the partial least squares regression method with internal cross-validation. The coefficients of determination in internal cross-validation (R²) are 0.88 for carbohydrates, 0.92 for fats and 0.99 for proteins. Thereafter, the calibration models developed were externally validated with samples of known concentrations of these soil components. The known concentrations were determined during external validation. The results of calibration and evaluation show that it is generally possible to measure very low concentrations of soil components in dishwashing liquor. The applicability to a real dishwashing process and the usage of other soils has yet to be tested.

Recent advances in ultrasound application as a novel technique in analysis, processing and quality control of fruits, juices and dairy products industries: A review

Recently, ultrasound has been widely used in the researches in the food science and technology. Among the food materials, fruits, juices and dairy products are strongly sensitive to ultrasound-based techniques. In this review paper, applications of ultrasound in terms of high and low-power modes in processing, instrumentation and control of the industrial operations are studied in the fruit, juice and dairy sectors of the food science and technology by emphasizing the principles of these techniques and their physicochemical effects on the products. Also, a comprehensive analysis of these methods and important factors influencing their performance are presented, along with the advantages and the drawbacks of each ultrasound-assisted techniques. The solutions for better productivity of this technique would be presented and future trend of this technology would be outlined. By studying the latest researches and advances in the field of ultrasound applications, it has been confirmed that this technique can be helpful in accelerating processes, reducing energy requirements, increasing productivity, and producing better quality food materials in the fields of fruits, juices and dairy products. Notwithstanding, in order to solve the challenges ahead, and for potential applications of ultrasound technology, further researches need to be expanded in the areas mentioned. Also, with the advancement of technology, more advanced equipment, ultrasound transducers and instrumentations would be introduced that needs to be applied in this regard, to solve the current challenges.

Optical properties of human milk

With human milk being the most important source of infant nutrition, the protection and support of breastfeeding are essential from a global health perspective. Nevertheless, relatively few objective methods are available to investigate human milk composition and lactation physiology when a mother experiences breastfeeding problems. We argue that optics and photonics offer promising opportunities for this purpose. Any research activity within this new application field starts with a thorough understanding on how light interacts with human milk. Therefore, the aim of this study was to investigate the full set of optical properties for human milk and the biological variability therein. Using a novel approach that combines spatially resolved diffuse reflectance spectroscopy (SR-DRS) and spectroscopic optical coherence tomography (sOCT) between 450 and 650 nm, we quantified the absorption coefficient µ_a , scattering coefficient µ_s , reduced scattering coefficient µ_s', anisotropy g and backscattering coefficient µ_b,NA of mature human milk from 14 participants released at different stages during a breastfeed (foremilk, bulk milk and hindmilk). Significant correlations were found between µ_a , µ_s , µ_s' and µ_b,NA and the biochemically determined fat concentration per sample (R_s = 0.38, R_s = 0.77, R_s = 0.80, R_s = 0.44 respectively). We explained the observed variations in the optical properties of human milk using Mie theory and the biological variability in both the concentration and size distribution of milk fat globules. In conclusion, we have provided a full set of optical properties for human milk, which can hopefully serve as a starting point for future biophotonic studies on human milk and the milk containing lactating breast.

Ultrasonic nano-emulsification - A review

The emulsions with nano-sized dispersed phase is called nanoemulsions having a wide variety of applications ranging from food, dairy, pharmaceutics to paint and oil industries. As one of the high energy consumer methods, ultrasonic emulsification (UE) are being utilized in many processes providing unique benefits and advantages. In the present review, ultrasonic nano-emulsification is critically reviewed and assessed by focusing on the main parameters such pre-emulsion processes, multi-frequency or multi-step irradiations and also surfactant-free parameters. Furthermore, categorizing aposematic data of experimental researches such as frequency, irradiation power and time, oil phase and surfactant concentration and also droplet size and stability duration are analyzed and conceded in tables being beneficial to indicate uncovered fields. It is believed that the UE with optimized parameters and stimulated conditions is a developing method with various advantages.

Optical Radiomic Signatures Derived from Optical Coherence Tomography Images Improve Identification of Melanoma

The current gold standard for clinical diagnosis of melanoma is excisional biopsy and histopathologic analysis. Approximately 15-30 benign lesions are biopsied to diagnose each melanoma. In addition, biopsies are invasive and result in pain, anxiety, scarring, and disfigurement of patients, which can add additional burden to the health care system. Among several imaging techniques developed to enhance melanoma diagnosis, optical coherence tomography (OCT), with its high-resolution and intermediate penetration depth, can potentially provide required diagnostic information noninvasively. Here, we present an image analysis algorithm, "optical properties extraction (OPE)," which improves the specificity and sensitivity of OCT by identifying unique optical radiomic signatures pertinent to melanoma detection. We evaluated the performance of the algorithm using several tissue-mimicking phantoms and then tested the OPE algorithm on 69 human subjects. Our data show that benign nevi and melanoma can be differentiated with 97% sensitivity and 98% specificity. These findings suggest that the adoption of OPE algorithm in the clinic can lead to improvements in melanoma diagnosis and patient experience. SIGNIFICANCE: This study describes a noninvasive, safe, simple-to-implement, and accurate method for the detection and differentiation of malignant melanoma versus benign nevi.

Investigation of optical properties of dissected and homogenized biological tissue

Knowledge of tissue optical properties, in particular the absorption μa and the reduced scattering coefficient μs', is required for diagnostic and therapeutic applications in which the light distribution during treatment has to be known. As it is generally very difficult to obtain this information with sufficient accuracy in vivo, optical properties are often approximately determined on ex vivo tissue samples. In this case, the obtained optical properties may strongly depend on the sample preparation. The extent of the expectable preparation-dependent differences was systematically investigated in comparative measurements on dissected and homogenized porcine tissue samples (liver, lung, brain, and muscle). These measurements were performed at wavelengths 520, 635, 660, and 785 nm, using a dual-step reflectance device and at a spectral range of 515 to 800 nm with an integrating sphere setup. In a third experiment, the density of tissue samples (dissected and homogenized) was investigated, as the characteristic of the packaging of internal tissue structures strongly influences the absorption and scattering. The standard errors of the obtained absorption and reduced scattering coefficients were found to be reduced in case of homogenized tissue. Homogenizing the tissues also allows a much easier and faster sample preparation, as macroscopic internal tissue structures are destroyed in the homogenized tissue so that a planar tissue sample with well-defined thickness can easily and accurately be prepared by filling the tissue paste into a cuvette. Consequently, a better reproducibility result was obtained when using homogenized samples. According to the density measurements accomplished for dissected and homogenized tissue samples, all types of tissues, except lung, showed a decrease in the density due to the homogenization process. The presented results are in good agreement for μs' regardless of the preparation procedure, whereas μa differs, probably influenced by blood content and dehydration. Because of faster and easier preparation and easier sample positioning, homogenization prior to measurement seems to be suitable for investigating the optical properties ex vivo. Additionally, by means of using the homogenization process, the sample size and thickness do not need to be particularly large, as is the case for most biopsies from the OR.

Estimation of particle size distributions from bulk scattering spectra: sensitivity to distribution type and spectral noise

A shape dependent method for particle size distribution (PSD) estimation based on bulk scattering properties was elaborated. This method estimates the parameters of a particle size distribution with predefined shape from the bulk scattering spectra. The estimation routine was validated on simulated data of polystyrene in water suspensions. To investigate the effect of measurement errors on PSD estimates, a sensitivity analysis was performed. The influence of spectral resolution and range was rather limited. Good PSD estimations were obtained on noise-free spectra, spectra with limited random noise and for estimations on μs or μs' in case of a multiplicative baseline. However, the PSD estimation deteriorated if an incorrect value for the refractive index of the particle relative to the medium was used as input parameter. Deviations caused by an incorrect distribution type were smaller for more narrow PSDs than for broader ones. Overall, this study showed the potential to estimate PSDs from bulk scattering spectra and indicated the factors affecting the accuracy.

Broadband Optical Properties of Milk

Dairy products play an important role in our daily nutrition. As a turbid scattering medium with different kinds of particles and droplets, each alteration of these components changes the scattering properties of milk. The goal of this work is the determination of the amount of main scattering components, the fat droplets and the casein micelles, by understanding the light propagation in homogenized milk and in raw milk. To provide the absolute impact of these milk components, the geometrical and optical properties such as the size distribution and the refractive index (RI) of the components have to be examined. We determined the reduced scattering coefficient [Formula: see text] and the absorption coefficient [Formula: see text] from integrating sphere measurements. By use of a collimated transmission setup, the scattering coefficient [Formula: see text] was measured. Size measurements were performed to validate the influence of the fat droplet size on the results of the scattering properties; also, the RI of both components was determined by the said coefficients. These results were used to determine the absolute impact of the milk components on the scattering behavior. By fitting Mie theory calculations on scattering spectra [Formula: see text] and [Formula: see text] from different raw milk samples, it was possible to get reliable values for the concentrations of fat and casein and for the size of the fat droplets. By destroying the casein micelles, it was possible to separate the influence of the different scattering components on scattering behavior.

Near-infrared bulk optical properties of goat wound tissue and human serum: consequences for an implantable optical glucose sensor

Near-infrared (NIR) spectroscopy offers a promising technological platform for continuous glucose monitoring in the human body. Moreover, these measurements could be performed in vivo with an implantable single-chip based optical sensor. However, a thin tissue layer may grow in the optical path of the sensor. As most biological tissues are highly scattering, they only allow a small fraction of the collimated light to pass, significantly reducing the light throughput. To quantify the effect of a thin tissue layer in the optical path, the bulk optical properties of serum and tissue samples grown on implanted dummy sensors were characterized using double integrating sphere and unscattered transmittance measurements. The estimated bulk optical properties were then used to calculate the light attenuation through a thin tissue layer. The combination band of glucose was found to be the better option, relative to the first overtone band, as the absorptivity of glucose molecules is higher, while the reduction in unscattered transmittance due to tissue growth is less. Additionally, as the wound tissue was found to be highly scattering, the unscattered transmittance of the tissue layer is expected to be very low. Therefore, a sensor configuration which measures the diffuse transmittance and/or reflectance instead was recommended. (a) Dummy sensor; (b) explanted dummy sensor in tissue lump; (c) removal of dummy sensor from tissue lump; and (d) 900 µm slices of tissue lump.

Computational optimization of the configuration of a spatially resolved spectroscopy sensor for milk analysis

A global optimizer has been developed, capable of computing the optimal configuration in a probe for spatially resolved reflectance spectroscopy (SRS). The main objective is to minimize the number of detection fibers, while maintaining an accurate estimation of both absorption and scattering profiles. Multiple fibers are necessary to robustify the estimation of optical properties against noise, which is typically present in the measured signals and influences the accuracy of the inverse estimation. The optimizer is based on a robust metamodel-based inverse estimation of the absorption coefficient and a reduced scattering coefficient from the acquired SRS signals. A genetic algorithm is used to evaluate the effect of the fiber placement on the performance of the inverse estimator to find the bulk optical properties of raw milk. The algorithm to find the optimal fiber placement was repeatedly executed for cases with a different number of detection fibers, ranging from 3 to 30. Afterwards, the optimal designs for each considered number of fibers were compared based on their performance in separating the absorption and scattering properties, and the significance of the differences was tested. A sensor configuration with 13 detection fibers was found to be the combination with the lowest number of fibers which provided an estimation performance which was not significantly worse than the one obtained with the best design (30 detection fibers). This design resulted in the root mean squared error of prediction (RMSEP) of 1.411 cm(-1) (R(2) = 0.965) for the estimation of the bulk absorption coefficient values, and 0.382 cm(-1) (R(2) = 0.996) for the reduced scattering coefficient values.

Classification and Processing Optimization of Barley Milk Production Using NIR Spectroscopy, Particle Size, and Total Dissolved Solids Analysis

Barley is a grain whose consumption has a significant nutritional benefit for human health as a very good source of dietary fibre, minerals, vitamins, and phenolic and phytic acids. Nowadays, it is more and more often used in the production of plant milk, which is used to replace cow milk in the diet by an increasing number of consumers. The aim of the study was to classify barley milk and determine the optimal processing conditions in barley milk production based on NIR spectra, particle size, and total dissolved solids analysis. Standard recipe for barley milk was used without added additives. Barley grain was ground and mixed in a blender for 15, 30, 45, and 60 seconds. The samples were filtered and particle size of the grains was determined by laser diffraction particle sizing. The plant milk was also analysed using near infrared spectroscopy (NIRS), in the range from 904 to 1699 nm. Furthermore, conductivity of each sample was determined and microphotographs were taken in order to identify the structure of fat globules and particles in the barley milk. NIR spectra, particle size distribution, and conductivity results all point to 45 seconds as the optimal blending time, since further blending results in the saturation of the samples.