High-Pressure Processing for Cold Brew Coffee: Safety and Quality Assessment under Refrigerated and Ambient Storage.

Cold brew coffee (CBC) has gained in popularity due to its distinct sensory experience. However, CBC can pose a risk for bacterial pathogens if not stored properly. High-Pressure Processing (HPP) is a nonthermal technology that can improve the safety of CBC while maintaining its quality. In this study, CBC made from ground roasted coffee grains was processed at 600 MPa for 3 min and stored at 4 or 23 °C for 90 days. The microbiological quality indicators remained stable throughout the study period. Physicochemical and quality parameters, such as pH, total dissolved solids, titratable acidity, color, total phenolic compounds and antioxidant activity, were not significantly affected by HPP. Both unprocessed and HPP CBC samples showed changes in pH, titratable acidity and color stability after 60 days at 23 °C. Unprocessed CBC samples spiked with Escherichia coli O157:H7, Listeria monocytogenes and Salmonella enterica showed decreased counts, but the pathogens were still detectable after 60 days at 4 °C and after 90 days at 23 °C. HPP achieved a >6-log10 reduction in the species tested, with non-detectable levels for at least 90 days at both storage temperatures. These findings suggest that HPP can effectively control vegetative pathogens and spoilage microorganisms in CBC while preserving its quality attributes.

Assessing the pressure resistance of Escherichia coli O157:H7, Listeria monocytogenes and Salmonella enterica to high pressure processing (HPP) in citric acid model solutions for process validation.

Despite the commercial success of high pressure processing (HPP) in the juice industry, some regulatory agencies still require process validation. However, there is a lack of consensus on various aspects regarding validation protocols, including the selection of representative strains to be used in challenge tests. This study characterized the variable response of Escherichia coli O157:H7 (34 strains), Listeria monocytogenes (44 strains) and Salmonella enterica (45 strains) to HPP, and identified potential candidates to use in process validation. Stationary phase cells were submitted to 500 MPa for 1 min at 10 °C in model solutions consisting of tryptic soy broth + 0.6% yeast extract (TSBYE) adjusted to pH 4.5 and 6.0 with citric acid. At pH 6.0, pressure resistance widely varied between species and within strains of the same species. E. coli O157:H7 and L. monocytogenes were the most pressure resistant and showed high variability at strain level, as the total count range given by minimum and maximum counts spread between 2.0 and 6.5 log10 CFU/ml. S. enterica was the least resistant pathogen with more than 82% of the isolates displaying non-detectable counts after HPP. Recovery through storage at 12 °C was also variable for all pathogens, but eventually most strains recovered with median counts on day 14 between 8.3 and 8.9 log10 CFU/ml. For pH 4.5 solutions, 26 E. coli O157:H7 strains displayed survivors after HPP but did not adapt, registering non-detectable counts in the next sampling dates. None of the L. monocytogenes and S. enterica strains survived HPP or incubation at pH 4.5 (<2.0 log10 CFU/ml), suggesting that citric acid at 4.16 g/l is a safe barrier for pathogen control under moderate HPP conditions. Principal component and cluster analyses served to propose strain cocktails for each species based on their pressure resistant and adaptation phenotypes. Additionally, S. enterica was identified as less pressure resistant and less prone to recover following HPP than E. coli O157:H7 and L. monocytogenes, so its relevance in process validation for juices should be questioned. Future work will validate the proposed strain cocktails on real food systems.

Hygroscopic properties and glass transition of dehydrated mango, apple and banana.

An undesirable crispiness loss occurs when some dry fruits reach a critical moisture content (Xc ) and their glass transition temperature (Tg ) matches the storage temperature. Models for sorption isotherms and onset Tg values for dry mango, apple, and banana were used to estimate Xc values at 25 and 32 °C. All models yielded R2 > 0.97 but information theory criteria strongly supported GAB in all but one case (40 °C, mango). The Gordon-Taylor Tg model (GT) yielded high R2 values for apple and banana but resulted in R2 = 0.834 for mango. As moisture approached zero, mango Tg estimates displayed a downward concavity contrasting with a rapidly increasing trend for apple and banana. The Khalloufi-Maslouhi-Ratti (KMR) model for Tg as a function of aw showed a linear behavior. Although the KMR model fitted data with R2 > 0.996, it requires more parameters and when aw approached 0, estimated Tg values increased at a slower rate than for the GT model. In the case of banana and mango, both models predicted approximately the same Xc at 25 °C but not at 32 °C. Finally, all Xc values estimated based on Tg were lower than the monolayer values obtained with the GAB (apple and banana) and BET (mango) models. These results indicate that the glass transition induced by moisture uptake dominates the quality degradation of these dry fruits.

Inactivation model and risk-analysis design for apple juice processing by high-pressure CO2.

Sigmoidal microbial survival curves are observed in high-pressure carbon dioxide (HPCD) pasteurization treatments. The objectives of this study were to use the Gompertz primary model to describe the inactivation in apple juice of the pathogen Escherichia coli CGMCC1.90 and to apply probabilistic engineering to select HPCD treatments meeting at least 5 log10 reductions (SV ≥ 5) at 95% confidence. This required secondary models for the temperature (T, °C) and pressure (P, MPa) dependence of the Gompertz model parameters. The expressions [Formula: see text] and [Formula: see text] selected using goodness-of-fit measures and assessments based on Akaike and Bayesian information criteria were consistent with proposed mechanistic models for HPCD bactericidal effects. Monte Carlo simulations accounting for the variability and uncertainty of the parameter b and c estimates were used to predict SV values for a given time, temperature and CO2 pressure combination and desired confidence boundary. A similar approach used to estimate process times meeting SV ≥ 5 at 95% confidence for a given temperature and CO2 pressure combination, showed that HPCD processes met this requirement only for relatively long processing times, i.e., 35-124 min in the experimental range of 32-42 °C and 10-30 MPa. Therefore, further HPCD research is required to reduce processing time.

A Gompertz Model Approach to Microbial Inactivation Kinetics by High-Pressure Processing (HPP): Model Selection and Experimental Validation.

A recently proposed Gompertz model (GMPZ) approach describing microbial inactivation kinetics by high-pressure processing (HPP) incorporated the initial microbial load (N0 ) and lower microbial quantification limit (Nlim ), and simplified the dynamic effects of come-up time (CUT). The inactivation of Listeria innocua in milk by HPP treatments at 300, 400, 500, and 600 MPa and pressure holding times (thold ) ≤10 min was determined experimentally to validate this model approach. Models based on exponential, logistic-exponential, and inverse functions were evaluated to describe the effect of pressure on the lag time (λ) and maximum inactivation rate (µmax ), whereas the asymptote difference (A) was fixed as A = log10 (N0 /Nlim ). Model performance was statistically evaluated and further validated with additional data obtained at 450 and 550 MPa. All GMPZ models adequately fitted L. innocua data according to the coefficient of determination (R2  ≥ 0.95) but those including a logistic-exponential function for µmax (P) were superior (R2  ≥ 0.97). These GMPZ versions predicted that approximately 597 MPa is the theoretical pressure level (Pλ ) at which microbial inactivation begins during CUT, mathematically defined as λ (P = Pλ ) = tCUT , and matching the value observed on the microbial survival curve at 600 MPa. As pressure increased, predictions tended to slightly underestimate the HPP lethality in the tail section of the survival curve. This may be overseen in practice since the observed microbial counts were below the predicted log10 N values. Overall, the modeling approach is promising, justifying further validation work for other microorganisms and food systems.