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Two milk protein concentrates (MPC, 56 and 85%) were studied as substitutes for 20 and 50% of the protein content in ice cream mix. The basic mix formula had 12% fat, 11% nonfat milk solids, 15% sweetener, and 0.3% stabilizer/emulsifier blend. Protein levels remained constant, and total solids were compensated for in MPC mixes by the addition of polydextrose. Physical properties investigated included apparent viscosity, fat globule size, melting rate, shape retention, and freezing behavior using differential scanning calorimetry. Milk protein concentrate formulations had higher mix viscosity, larger amount of fat destabilization, narrower ice melting curves, and greater shape retention compared with the control. Milk protein concentrates did not offer significant modifications of ice cream physical properties on a constant protein basis when substituted for up to 50% of the protein supplied by nonfat dry milk. Milk protein concentrates may offer ice cream manufacturers an alternative source of milk solids non-fat, especially in mixes reduced in lactose or fat, where higher milk solids nonfat are needed to compensate other losses of total solids.

There is a need for rapid and simple techniques that can be used to predict the quality of cheese. The aim of this research was to develop a simple and rapid screening tool for monitoring Swiss cheese composition by using Fourier transform infrared spectroscopy. Twenty Swiss cheese samples from different manufacturers and degree of maturity were evaluated. Direct measurements of Swiss cheese slices (approximately 0.5 g) were made using a MIRacle 3-reflection diamond attenuated total reflectance (ATR) accessory. Reference methods for moisture (vacuum oven), protein content (Kjeldahl), and fat (Babcock) were used. Calibration models were developed based on a cross-validated (leave-one-out approach) partial least squares regression. The information-rich infrared spectral range for Swiss cheese samples was from 3,000 to 2,800 cm(-1) and 1,800 to 900 cm(-1). The performance statistics for cross-validated models gave estimates for standard error of cross-validation of 0.45, 0.25, and 0.21% for moisture, protein, and fat respectively, and correlation coefficients r > 0.96. Furthermore, the ATR infrared protocol allowed for the classification of cheeses according to manufacturer and aging based on unique spectral information, especially of carbonyl groups, probably due to their distinctive lipid composition. Attenuated total reflectance infrared spectroscopy allowed for the rapid (approximately 3-min analysis time) and accurate analysis of the composition of Swiss cheese. This technique could contribute to the development of simple and rapid protocols for monitoring complex biochemical changes, and predicting the final quality of the cheese.

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