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The increase of soluble solids in milk by the addition of powdered products is a normal practice in the elaboration of yogurt in order to enhance viscosity, texture and sensory properties for the consumer. The purpose of this study was to evaluate the effect of adding jumbo squid ( Dosidicus gigas ) powder (protein content, 420 g/kg) on the aforementioned quality properties of yogurt. Six formulations of yogurt were prepared with the addition of 0, 1, 3, 5, 7 or 10 g/100 mL jumbo squid powder, plus one formulation with 3 g/100 mL maltodextrin. During fermentation, yogurts formulated with squid powder gradually achieved greater viscosity while producing both more acidity and at a higher rate than the controls. Apart from lower pH (hence, higher titratable acidity) and higher viscosity, the final enriched yogurts presented lower syneresis than the controls (p < 0.05). Although the highest viscosity (58.90 Pa.s) and the lowest syneresis (1.00%) was achieved by the yogurt with 10 g/100 mL jumbo squid powder, it was the treatment formulated with 3 g/100 mL (pH 4.31, acidity 0.85 g/100 g, viscosity 40.90 Pa.s and syneresis 9.10%) that kept constant sensory properties, as evaluated by the panelists, while improving some physical properties of the control yogurts. [ABSTRACT FROM AUTHOR]

In this work, all publicly-accessible published findings on Alicyclobacillus acidoterrestris heat resistance in fruit beverages as affected by temperature and pH were compiled. Then, study characteristics (protocols, fruit and variety, °Brix, pH, temperature, heating medium, culture medium, inactivation method, strains, etc.) were extracted from the primary studies, and some of them incorporated to a meta-analysis mixed-effects linear model based on the basic Bigelow equation describing the heat resistance parameters of this bacterium. The model estimated mean D * values (time needed for one log reduction at a temperature of 95 °C and a pH of 3.5) of Alicyclobacillus in beverages of different fruits, two different concentration types, with and without bacteriocins, and with and without clarification. The z T (temperature change needed to cause one log reduction in D -values) estimated by the meta-analysis model were compared to those (‘observed’ z T values) reported in the primary studies, and in all cases they were within the confidence intervals of the model. The model was capable of predicting the heat resistance parameters of Alicyclobacillus in fruit beverages beyond the types available in the meta-analytical data. It is expected that the compilation of the thermal resistance of Alicyclobacillus in fruit beverages, carried out in this study, will be of utility to food quality managers in the determination or validation of the lethality of their current heat treatment processes. [ABSTRACT FROM AUTHOR]

Abstract: This communication deals with the use of meta-analysis as a valuable tool for the synthesis of food safety research, and in quantitative risk assessment modelling. A common methodology for the conduction of meta-analysis (i.e., systematic review and data extraction, parameterisation of effect size, estimation of overall effect size, assessment of heterogeneity, and presentation of results) is explained by reviewing two meta-analyses derived from separate sets of primary studies of Salmonella in pork. Integrating different primary studies, the first meta-analysis elucidated for the first time a relationship between the proportion of Salmonella-carrier slaughter pigs entering the slaughter lines and the resulting proportion of contaminated carcasses at the point of evisceration; finding that the individual studies on their own could not reveal. On the other hand, the second application showed that meta-analysis can be used to estimate the overall effect of a critical process stage (chilling) on the incidence of the pathogen under study. The derivation of a relationship between variables and a probabilistic distribution is illustrations of the valuable quantitative information synthesised by the meta-analytical tools, which can be incorporated in risk assessment modelling. Strengths and weaknesses of meta-analysis within the context of food safety are also discussed. [Copyright &y& Elsevier]

The fate of Listeria monocytogenes during ripening of artisanal Minas semi-hard cheese, as influenced by cheese intrinsic properties and by autochthonous (naturally present) or intentionally-added anti-listerial lactic acid bacteria (LAB) was modeled. Selected LAB strains with anti-listerial capacity were added or not to raw or pasteurized milk to prepare 4 cheese treatments. Counts of LAB and L. monocytogenes , pH, temperature and water activity were determined throughout cheese ripening (22 days, 22±1ᵒC). Different approaches were adopted to model the effect of LAB on L. monocytogenes : an independent approach using the Huang primary model to describe LAB growth and the linear decay model to describe pathogen inactivation; the Huang-Cardinal [pH] model using the effect of pH variation in a dynamic tertiary approach; and the Jameson-effect with N max tot model which simultaneously describes L. monocytogenes and LAB fate. L. monocytogenes inactivation occurred in both treatments with added LAB and inactivation was faster in raw milk cheese (−0.0260 h−1) vs. pasteurized milk cheese (−0.0182 h−1), as estimated by the linear decay model. Better goodness-of-fit was achieved for the cheeses without added LAB when the Huang primary model was used. A faster and great pH decline was detected for cheeses with added LAB, and the Huang-Cardinal [pH] model predicted higher pathogen growth rate in cheese produced with raw milk, but greater L. monocytogenes final concentration in pasteurized milk cheese. The Jameson-effect model with N max tot predicted that LAB suppressed pathogen growth in all treatments, except in the treatment with pasteurized milk and no LAB addition. The Huang-Cardinal [pH] model was more accurate in modeling L. monocytogenes kinetics as a function of pH changes than was the Jameson-effect model with N max tot as a function of LAB inhibitory effect based on the goodness-of-fit measures. The Jameson-effect model may however be a better competition model since it can more easily represent L. monocytogenes growth and death. This study presents crucial kinetic data on L. monocytogenes behavior in the presence of competing microbiota in Minas semi-hard cheese under dynamic conditions. • Three different approaches were evaluated to predict L. monocytogenes behavior in semi-hard cheese. • All proposed models were capable of closely describing L. monocytogenes growth/death potential. • Huang-Cardinal [pH] present better fit quality than the Jameson-effect model. • The Huang-Cardinal model was not able to describe inactivation. • Addition of anti-listerial LAB results in a decrease in L. monocytogenes. [ABSTRACT FROM AUTHOR]

Abstract This study compares dynamic tertiary and competition models for L. monocytogenes growth as a function of intrinsic properties of a traditional Brazilian soft cheese and the inhibitory effect of lactic acid bacteria (LAB) during refrigerated storage. Cheeses were prepared from raw or pasteurized milk with or without the addition of selected LAB with known anti-listerial activity. Cheeses were analyzed for LAB and L. monocytogenes counts, pH and water activity (a w) throughout cold storage. Two approaches were used to describe the effect of LAB on L. monocytogenes : a Huang-Cardinal model that considers the effect of pH and a w variation in a dynamic kinetic analysis framework; and microbial competition models, including Lotka-Volterra and Jameson-effect variants, describing the simultaneous growth of L. monocytogenes and LAB. The Jameson-effect with γ and the Lotka-Volterra models produced models with statistically significant coefficients that characterized the inhibitory effect of selected LAB on L. monocytogenes in Minas fresh cheese. The Huang-Cardinal model [pH] outperformed both competition models. Taking a w change into account did not improve the fit quality of the Huang-Cardinal [pH] model. These models for Minas soft cheese should be valuable for future microbial risk assessments for this culturally important traditional cheese. Highlights • LAB with anti-listerial activity reduced the μ opt and Y max of L. monocytogenes. • Dynamic tertiary and competition models presented good fit quality. • Jameson-effect model with γ showed that LAB inhibited L. monocytogenes growth. • Lotka-Volterra model was significant for inhibition of L. monocytogenes. [ABSTRACT FROM AUTHOR]

Artisanal raw milk cheeses are highly appreciated dairy products in Brazil and ensuring their microbiological safety has been a great need. This study reports the isolation and characterization of lactic acid bacteria (LAB) strains with anti-listerial activity, and their effects on Listeria monocytogenes during refrigerated shelf-life of soft Minas cheese and ripening of semi-hard Minas cheese. LAB strains (n = 891) isolated from Minas artisanal cheeses (n = 244) were assessed for anti-listerial activity by deferred antagonism assay at 37 °C and 7 °C. The treatments comprised the production of soft or semi-hard Minas cheeses using raw or pasteurized milk, and including the addition of selected LAB only [ Lactobacillus brevis 2-392, Lactobacillus plantarum 1-399 and 4 Enterococcus faecalis (1-37, 2-49, 2-388 and 1-400)], L. monocytogenes only, selected LAB co-inoculated with L. monocytogenes , or without any added cultures. At 37 °C, 48.1% of LAB isolates showed anti-listerial capacity and 77.5% maintained activity at 7 °C. Selected LAB strains presented a bacteriostatic effect on L. monocytogenes in soft cheese. L. monocytogenes was inactivated during the ripening of semi-hard cheeses by the mix of LAB added. Times to attain a 4 log-reduction of L. monocytogenes were 15 and 21 days for semi-hard cheeses produced with raw and pasteurized milk, respectively. LAB with anti-listerial activity isolated from artisanal Minas cheeses can comprise an additional barrier to L. monocytogenes growth during the refrigerated storage of soft cheese and help shorten the ripening period of semi-hard cheeses aged at ambient temperature. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop robust chemometric models for the routine determination of dietary constituents of quinoa ( Chenopodium quinoa Willd.) using Near-Infrared Transmission (NIT) spectroscopy. Spectra of quinoa grains of 77 cultivars were acquired while dietary constituents were determined by reference methods. Spectra were subjected to multiplicative scatter correction (MSC) or extended multiplicative signal correction (EMSC), and were (or not) treated by Savitzky-Golay (SG) filters. Latent variables were extracted by partial least squares regression (PLSR) or canonical powered partial least squares (CPPLS) algorithms, and the accuracy and predictability of all modelling strategies were compared. Smoothing the spectra improved the accuracy of the models for fat (root mean square error of cross-validation, RMSECV: 0.319–0.327%), ashes (RMSECV: 0.224–0.230%), and particularly for protein (RMSECV: 0.518–0.564%) and carbohydrates (RMSECV: 0.542–0.559%), while enhancing the prediction performance, particularly, for fat (root mean square error of prediction, RMSEP: 0.248–0.335%) and ashes (RMSEP: 0.137–0.191%). Although the highest predictability was achieved for ashes (SG-filtered EMSC/PLSR: bootstrapped 90% confidence interval for RMSEP: [0.376–0.512]) and carbohydrates (SG-filtered MSC/CPPLS: 90% CI RMSEP: [0.651–0.901]), precision was acceptable for protein (SG-filtered MSC/CPPLS: 90% CI RMSEP: [0.650–0.852]), fat (SG-filtered EMSC/CPPLS: 90% CI RMSEP: [0.478–0.654]) and moisture (non-filtered EMSC/PLSR: 90% CI RMSEP: [0.658–0.833]). [ABSTRACT FROM AUTHOR]