Tiziana M.P. Cattaneo

Detection of Vegetable Proteins from Soy, Pea and Wheat Isolates in Milk Powder by near Infrared Spectroscopy:

This work aimed to prove the feasibility of using near infrared (NIR) spectroscopy to detect vegetable proteins (soy, pea and wheat isolates) in milk powder. One hundred and fifty-five samples of genuine and adulterated milk powder (NIZO, Ede, The Netherlands) were analysed by NIR spectroscopy using an InfraAlyzer 500 (Bran+Luebbe). NIR spectra were collected at room temperature, and data were processed by Sesame Software (Bran+Luebbe) to select the most significant wavelengths. Calibrations were made on all samples in the range 0–5% of added vegetable proteins. Separate prediction and validation sets were prepared using samples not included in the calibration set. The best results were obtained by applying multiple linear regression (MLR) to the first derivative of absorbance values at five wavelengths. NIR spectroscopy proved a very effective tool for detecting the presence of vegetable proteins in milk powder on the basis of standard error of calibration (SEC), standard error of prediction (SEP) and standard error of validation (SEV) values found in this study. The calibration carve was characterised by a regression coefficient (R2) equal to 0.993 with a SEC of 0.20, a SEP of 0.23 and a SEV of 0.21.

A preliminary study using Fourier transform near infrared spectroscopy to monitor the shelf-life of packed industrial ricotta cheese

Ricotta cheese is a dairy product characterised by a short shelf life. The aim of this study was to monitor changes occurring during storage of packed industrial ricotta cheese using a simple and fast method. Several samples of manufactured ricotta cheese were monitored during storage at three different temperatures (3, 10 and 20°C). Spectral data were collected over the range 12000 to 4400 cm−1 using a Fourier transform near infrared (FT-NIR) spectrometer fitted with an optic fibre working in diffuse reflectance. Some chemical and rheological parameters were also measured. Principal component analysis (PCA) was applied as an exploratory chemometric technique to each one of the three sets of data (FT-NIR, chemical and rheological data) and a calibration model between the NIR data set and chemical and rheological indices was developed by means of partial least squares regression. The PCA results showed in all cases the influence of the storage temperature on the shelf life trend and were able to identify a critical day of shelf life for each storage temperature.

Review: The use of near infrared spectroscopy for determination of adulteration and contamination in milk and milk powder: updating knowledge

This review aims to update information on the use of near infrared (NIR) spectroscopy in identifying and quantifying the presence of adulterants and contaminants in milk and milk powder. Milk and milk products are recognised excellent sources of nutrition globally and are of great economic importance. In recent years, there have been a number of documented incidences of both deliberate adulteration and accidental contamination of foodstuffs. There is a clear need to detect these by a fast, accurate and non-destructive methodology. This has stimulated researchers to explore the possibility of applying NIR technology for their detection. NIR spectroscopy is a logical technique for use as it offers a rapid, low-cost and convenient analysis of key constituents. Fast responses are particularly important to industry, where an answer is needed within minutes. Most important, apart from its powerful prediction capability, the non-destructive nature of this technique is very useful for fast analysis in on-line and at-line inspections and authentication of food. NIR has the potential for detecting milk and milk powder adulteration by both economically motivated adulterants such as melamine as well as contaminants that may have been introduced unintentionally such as microorganisms. In comparison with mid-infrared and Raman, NIR spectroscopy allows the detection of contaminants and their quantification faster and with the same, or better, performances. Furthermore, NIR instrumentation is, in general, less sensitive to environmental conditions and is highly flexible. In particular, for the detection of a very low level of contamination, further investigations are warranted to identify the basis of the calibrations and test their performance when put into routine use. Consumers must have confidence in the analyses which ensure safe and genuine dairy products.

Contribution of light scattering to near infrared absorption in milk.

The presence of milk fat globule emulsion produces scattering phenomena on near infrared (NIR) radiation through the raw milk. Numerically, 80% of milk fat globules have a diameter of less than 3μm interfering with the radiation having a wavelength from 1 μm to 2.5 μm with a radiation dispersion in all directions. Consequently, the NIR transmitted radiation does not behave in accordance with Lambert–Beers law: the NIR spectra of milk samples with high fat content have high offset values and lower specific absorptions than those of samples with lower fat levels. Usually, this problem is reduced by acting at the level of sample preparation (homogenisation), of optical geometry (transflectance mode coupled with the use of an integrating sphere to collect the widespread radiation) and using chemometric regression models able to optimise non-linear spectral responses. Transmittance measurements have already been exploited for the determination of macro-composition in the agro-food and in the dairy fields. In this work, a set of 150 individual milk samples, collected over three days from a single farm with 49 milking cows, was analysed with Fourier transform-NIR apparatus in order to study the effects of scattering on partial least squares predictors for casein. The spectra of non-homogenised raw whole milk and the respective skimmed samples were collected in transmission mode. Using the true scattering curves obtained by subtraction from the raw milk spectra of skimmed milk spectra the extended multiplicative scatter correction (EMSC) estimate of scattering effects was optimised. EMSC uses polynomial filters in modelling the aspecific absorptions due to the scattering effects. The correct scatter elimination can help in the individuation and interpretation of the true predictors in calibration procedures.

Capillary electrophoresis of sialylated oligosaccharides in milk from different species

Oligosaccharides are relevant components of human milk, which have been quite well studied for their pre-biotic effect and their capacity in stimulating the immune system. Since oligosaccharides from milk of non-human mammals received so far less attention, the aim of this work was the application of capillary electrophoresis (CE) for the analysis of sialylated oligosaccharides in cow, goat and equine (mare and donkey) milk to possibly identify potential sources of oligosaccharides to use as health promoting ingredients in functional foods. Human milk was used as reference milk. A recent CE technique was applied to resolve and quantify 3-sialyllactose (3-SL), 6-sialyllactose (6-SL) and disialyl-lacto-N-tetraose (DSLNT). Analysis of non-human milk samples confirmed differences among species and individuals: DSLNT, which was the most abundant compound in human milk (455-805μg/mL) was missing in most of the samples. In most cases, 3-SL showed to be the most concentrated of the quantified analytes, with values ranging from 12 to 77μg/mL.

Estimation of Fat Globule Size Distribution in Milk Using an Inverse Light Scattering Model in the near Infrared Region

The determination of particle characteristics from light scattering patterns is a challenging inversion problem and, not least, a demanding instrumentation problem. Despite the importance of the knowledge of size distribution in several technological dairy processes, often laser diffractometers and other instrumentation for particle size analysis are not available in dairy laboratories and, therefore, such information is not easily available, except for research purposes. Near infrared (NIR) instrumentation, instead, is largely available in dairy labs. Laser granulometers are based on the principle that particles scatter light from one or two laser beams with an angular pattern directly related to their size. Consequently, a suspension of particles forms an angular pattern of scattered light that is characteristic of its size distribution. In a similar manner, a NIR spectrometer in transmission mode can be considered as a tool for studying the behaviour of forward scattering at different wavelengths. In this work, a model based on an approximation of Mie scattering was developed for the calculation of scattering due to fat globules in the NIR transmission spectrum of milk. The inversion of the model was applied to raw milk spectra in the spectral regions from 1000 nm to 1360 nm and from 1580 nm to 1800 nm, free from strong absorption bands, in order to estimate the fat particle size distribution. More than 700 samples, collected monthly for two years from 50 Friesian–Holstein, 7 Jersey and 5 Brown cows, were analysed. Four hundred of these samples were also analysed using a laser granulometer. The correlation (r2) between NIR and laser granulometric data was equal to 0.95 for the mean volume surface diameter (d3,2) with a root mean square error (RMSE) of 0.11 microns. A sub-class of Weibull distribution with only one freedom parameter proved to be sufficient in order to describe milk fat globule distribution and fit spectral data. The method developed in this work can be useful both for genetic selection and technological purposes and easily extended to the analysis of other dietary fat emulsions.

Relationship between Sensory Scores and near Infrared Absorptions in Characterising Bitto, an Italian Protected Denomination of Origin Cheese

Historically, specific types of cheese are made in certain geographic areas. Often they have unique flavour characteristics. Studies have suggested the role of local pastures in determining cheese aroma. Bitto is a protected denomination of origin cheese produced in summer in Valtellina (Lombardy, Italy). The aim of this paper was to study the relationship between sensory scores assigned to Bitto cheese by a highly trained panel of experts and near infrared (NIR) data in verifying the NIR ability in predicting sensory characteristics. Bitto moulds (39), with assigned sensory scores, were analysed in the whole NIR range by an Fourier transform-NIR spectrometer. Grated cheese spectra (156) were recorded in reflectance mode. Spectra were grouped in two independent sets (calibration/prediction set = 30 samples; test set = nine samples). PLS1 and PLSD were applied. PLS1 results allowed a satisfactory prediction of total sensory score (RMSEP 2.53; bias 1.2; slope 0.814) and an acceptable prediction of “Taste and Flavour” score (RMSEP 0.60; bias 0.51; slope 0.565) for the nine samples in the test set. An acceptable preliminary classification of samples into three “quality classes” was also obtained applying PLSD. Factor loadings plots allowed the identification of some NIR absorption bands related to the development of cheese taste and flavour.

Near infrared monitoring of mineralisation of liquid dairy manure in agricultural soils

Liquid dairy manure is a major organic input to cultivated soils. Therefore, a method for monitoring the mineralisation of slurries should be a useful tool for managing soil fertilisation. In order to examine whether the biodegradation of cattle sludge can be monitored by near infrared (NIR) spectroscopy, soil samples from a laboratory incubation experiment were analysed using this rapid and inexpensive method. Five different cattle slurries were added to three soils with increasing clay content in such an amount as to give 130 ppm of total nitrogen. The resulting 18 experimental treatments (three control soils and 15 soil-slurry combinations) were incubated for 180 days under optimal temperature and soil water content. Each treatment was sampled at 0, 2, 8, 12, 16, 21, 29, 41, 72, 121 and 180 days: the respired CO2 was captured in alkali traps and mineral N was extracted using 1 M KCl. Three replicates of each sampling were analysed individually. The resulting 648 samples, air dried and ground at 0.5 mm, were analysed by NIR spectroscopy using an Antaris (Thermo Nicolet) Fourier transform-NIR spectrometer. Although the slurries and soil mineralised carbon represent only a very small part of the total soil organic carbon, the mineralisation of carbon can be clearly monitored by NIR spectroscopy in both amended and unamended soils. Whereas NO3–N evolution was difficult to predict using NIR data, the results for NH4–N were more encouraging. Using measurements of CO2–C respired, a two-pool mineralisation model was developed and the simulated concentration of carbon pools in the soils were used for the development of NIR equations. The results obtained in this work have demonstrated that NIR is a useful tool for monitoring the carbon mineralisation process when cattle sludge is incorporated into agricultural soils.

New applications of near infrared spectroscopy on dairy products

Dairy products provide an important source of nutrition globally and are one of the food sectors with the highest economic value.1 Within the food production and processing industry, the requirements of quality control have received much focus recently. In parallel, modern near infrared (NIR) technology offers fast and cost-effective analyses that can afford quality control in both the laboratory and factory environments. Applications of NIR spectroscopy within the dairy industry go back to the late 1970s. As for other food and feed applications, the traditional methods for determining the quality of dairy products are time-consuming and expensive.2 To overcome these disadvantages, the potential of NIR spectroscopy for monitoring the quality of milk has been evaluated by several research groups. Most studies have indicated that NIR can be used to predict the chemical composition of milk and dairy products and to monitor the cutting-point during cheese manufacturing. Other studies have demonstrated the potential of NIR to also predict sensory characteristics (for example, hardness and tenderness) of dairy products. Considerable work has been done since that time, justifying more than one review.3–5 NIR spectroscopy was historically used for measurement of low moisture products. The first applications in the dairy industry were for the analysis of milk powders. Over the intervening years, developments both in hardware and in software have permitted extension of analyses to more complex heterogeneous products such as cheese and yoghurt.2 Liquid milk is the starting point of any dairy product and is one of the best controlled food products in the world. In this context, this special issue was assembled to collect information about the new developments and uses of NIR spectroscopy as a useful tool along the full dairy chain, updating research on the analysis of liquid milk and the products derived from it, while also exploring some new applications and including practical experiences and outcomes from an industrial perspective.

NIR and other luminometric methods to monitor the primary clotting phase of milk

The rapid routine method currently used to monitor the ability of milk to coagulate does not provide information on the primary clotting phase. The purpose of this work was to assess if the principal critical events related to the primary clotting phase could be detected by NIR and by other methods based on the interaction of light and material (fluorescence spectroscopy, tristimulus colorimetry) that provide a quick response. Six different coagulation tests were carried out. Reconstituted skim milk powder was used as standard substrate and the same liquid calf rennet solution was added. Milk NIR spectra were collected at 35°C using an InfrAlyzer 500 (Bran+Luebbe). Spectra were taken every 70 seconds, from rennet addition up to about 10 minutes after clotting time. Data were processed by IDAS-PC software to find the most discriminant wavelengths in highlighting spectral differences. For fluorescence tests, the primary clotting phase was monitored collecting samples at different times and stopping the enzymatic reaction at 0°C in an ice-bath. Spectrofluorimetric titrations were carried out by using ANS as hydrophobic probe and a Luminescence Spectrometer LS-B. Protein Surface Hydrophobycity (PSH) values were calculated. The ANS relative distribution was also monitored after ultracentrifugation at 0°C. In this case ANS was added to milk before rennet addition. Colorimetric assays were carried out by using a tristimulus colorimetry and data collected at the same time as NIR spectra. Differences in luminosity values were calculated. The clotting time was calculated using both a Formagraph Instrument and by visual observation of coagulation. NIR data show two critical events during the primary clotting phase, confirmed by the other techniques used. The first appears a few minutes before clotting. The second, in accordance with the visual observation of coagulation, detects the clotting point, before Formagraph in corrispondence of micellar aggregation. Interesting results are obtained by plotting selected NIR 2nd derivative absorbance values against time; this establishes a trend of coagulation, which is also detectedby the other techniques. The interrelationship among the different techniques is discussed and spectral data are interpreted in terms of water bonds and/or different amounts of free water due to the formation of new products and/or protein structure rearrangements.