Sous-vide processing of silver carp: Effect of processing temperature and cold storage duration on the microbial quality of the product as well as modeling by artificial neural networks.

Silver carp (Hypophthalmichthys molitrixi) was processed by sous-vide method at different temperatures (60, 65, 70, and 75°C). Then, the microbiological quality of the processed samples was monitored during cold storage (4°C) for 21 days. The target microorganisms were Enterobacteriaceae, Lactic Acid bacteria (LAB), Pseudomonas, Psychrotrophs, and total viable count (TVC). In samples processed at 75°C, the presence of Enterobacteriaceae, Pseudomonas and Psychrotrophs were not detectable up to 15 days of storage and lactic acid bacteria were not detectable even at the end of the storage period. A radial basis function neural network (RBFNN) model was established to predict the changes in the microbial content of silver carp. In this step, the relationship between processing temperature and storage duration on microbial growth was modeled by ANNs (artificial neural networks). The optimal ANN topology for modeling Enterobacteriaceae, Pseudomonas, and Psychrotroph contained 9 neurons in the hidden layer, but it contained 15 and 14 neurons for TVC and LAB, respectively. By experimenting with the temperature of -80°C, it was revealed that the obtained ANN model has a high potential for prediction.

Change in the color of heat-treated, vacuum-packed broccoli stems and florets during storage: effects of process conditions and modeling by an artificial neural network.

BACKGROUND: Vacuum-packed broccoli stems and florets were subjected to heat treatment (60-99 °C) for various time intervals. The activity of peroxidase was measured after processing. Thermally processed samples were then stored at 4 °C for 35 days, and the color of the samples was measured every 7 days. Effects of parameters (heating temperature and duration, storage time) on the color of broccoli were modeled and simulated by an artificial neural network (ANN). RESULTS: Simulations confirmed that stems were predicted to be more prone to changes than florets. More color loss was observed with longer processing or storage combinations. The simulations also confirmed that higher temperatures during heat processing could retard color changes during storage. For stems treated at 80 °C for short durations, color loss was more predominant than both 65 and 99 °C, probably due to the incomplete inactivation of enzymes besides more tissue damage, with increased enzyme access to the substrate. CONCLUSION: The greenness of both stems and florets during storage can be better preserved at higher temperatures (99 °C) and short times. The simulation results revealed that the ANN method could be used as an effective tool for predicting and analyzing the color values of heat-treated broccoli. © 2018 Society of Chemical Industry.

Optimizing spray drying conditions of sour cherry juice based on physicochemical properties, using response surface methodology (RSM).

In this study, the effects of main spray drying conditions such as inlet air temperature (100-140 °C), maltodextrin concentration (MDC: 30-60%), and aspiration rate (AR) (30-50%) on the physicochemical properties of sour cherry powder such as moisture content (MC), hygroscopicity, water solubility index (WSI), and bulk density were investigated. This investigation was carried out by employing response surface methodology and the process conditions were optimized by using this technique. The MC of the powder was negatively related to the linear effect of the MDC and inlet air temperature (IT) and directly related to the AR. Hygroscopicity of the powder was significantly influenced by the MDC. By increasing MDC in the juice, the hygroscopicity of the powder was decreased. MDC and inlet temperature had a positive effect, but the AR had a negative effect on the WSI of powder. MDC and inlet temperature negatively affected the bulk density of powder. By increasing these two variables, the bulk density of powder was decreased. The optimization procedure revealed that the following conditions resulted in a powder with the maximum solubility and minimum hygroscopicity: MDC = 60%, IT = 134 °C, and AR = 30% with a desirability of 0.875.