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ABSTRACT Milk protein concentrate 85 (MPC85) is a high‐protein dairy ingredient widely used in a variety of foods and prone to performance challenges with certain applications. To address the performance limitations, this study explored pulsed electric field (PEF) processing, a nonthermal method known to alter protein behavior and functional properties. The impact of PEF processing on liquid MPC85 was assessed for solubility, foaming capacity and stability, emulsion stability, gel strength, and water‐holding capacity. Key parameters examined were temperature (25°C–50°C), electric field strength (4–20 kV/cm), and frequency (30–300 Hz). Predicted individual optimized conditions were as follows: For foaming capacity, the minimum (92.35 mL/g; 29.4% lower than the control) was predicted at 25°C, 12.45 kV/cm, and 32.21 Hz and maximum (153.86 mL/g; 17% higher than the control) was predicted at 49.35°C, 19.58 kV/cm, and 119.06 Hz. Maximum emulsion stability (55.12 min; 70.2% higher than the control) was at 50°C, 5.9 kV/cm, and 30 Hz, and the maximum gel strength (4751.33 N; 131% greater than the control) was at 50°C, 4 kV/cm, and 300 Hz. All models showed a good fit to the experimental data. Results demonstrated that foaming stability, water‐holding capacity, and solubility did not show significant improvement under the tested conditions. In conclusion, PEF could be potentially used as a tool to modify the structure of the MPC85 to further promote the application of high‐protein ingredients in the dairy industry. 

Due to its high casein content, micellar casein concentrate (MCC) is a stable protein currently used for various product applications. Our objective was to reduce the viscosity of MCC using a pulsed electric field (PEF) processing which is one of the non-thermal technologies researched in the market. In this study, the effect of processing conditions for PEF treatment, such as temperature (15–45 °C), electric field strength (EFS) (4–20 kV/cm), and frequency on the viscosity (30–300 Hz) of MCC was investigated and optimized using response surface methodology (RSM). The analysis resulted in a quadratic prediction model with R2 = 0.91. The optimized conditions were 35 °C, EFS at 4 kV/cm and frequency at 63 Hz. The optimized consistency coefficient was predicted to be 1440.57 Pa sn which was 46% less than control at 30 °C. Temperature and EFS were found to be the most critical parameters that affect the functionality. Industrial relevance This study provides the optimized process conditions for reducing the viscosity of MCC using PEF, which would benefit the application of MCC in various end-product applications. The results indicate the relevance of using PEF as a treatment through an inline process during the manufacturing of MCC which will in turn allow the dairy industry to fine tune the ingredients and lead to the production of novel ingredients with enhanced functionality. Keywords: Pulsed electric field; Micellar casein concentrate; Viscosity; Response surface methodology; Optimization 

Multi-omics has the promise to provide a detailed molecular picture of biological systems. Although obtaining multi-omics data is relatively easy, methods that analyze such data have been lagging. In this paper, we present an algorithm that uses probabilistic graph representations and external knowledge to perform optimal structure learning and deduce a multifarious interaction network for multi-omics data from a bacterial community. Kefir grain, a microbial community that ferments milk and creates kefir, represents a self-renewing, stable, natural microbial community. Kefir has been shown to have a wide range of health benefits. We obtained a controlled bacterial community using the two most abundant and well-studied species in kefir grains: Lentilactobacillus kefiri and Lactobacillus kefiranofaciens. We applied growth temperatures of 30 °C and 37 °C and obtained transcriptomic, metabolomic, and proteomic data for the same 20 samples (10 samples per temperature). We obtained a multi-omics interaction network, which generated insights that would not have been possible with single-omics analysis. We identified interactions among transcripts, proteins, and metabolites, suggesting active toxin/antitoxin systems. We also observed multifarious interactions that involved the shikimate pathway. These observations helped explain bacterial adaptation to different stress conditions, co-aggregation, and increased activation of L. kefiranofaciens at 37 °C.