Quality changes during thermal processing of two mixed formulas of fruits and vegetables pulps

Abstract

The present work aimed to evaluate, through thermal degradation kinetics (80 °C to 98 °C in time intervals of 0.5 to 25 min), the effects of different thermal treatments on the biochemical, physicochemical, sensory and microbiological parameters of two mixed fruit and vegetable pulps, a yellow and a red one. The evaluated fruit and vegetable pulps resulted from the mixture of different fruits and vegetables proportions (pineapple, beetroot, strawberry and lemon juice) added to a 50% (p/p) pear-based pulp to maximize their bioactivity, physicochemical stability and sensorial acceptance. Evaluated quality parameters included the determination of peroxidase activity (POD), pH, soluble solids content (SSC), total phenolic content (TPC), CIELab colour, sensory evaluation (colour, taste and aroma) and total mesophilic aerobic counts (TAPC). Regarding heat treatments optimization for both pulps with lower pH, it was concluded that higher temperature treatments (90 to 98 °C) applied over a shorter time (less than 5 min) were more effective to inactivate POD, to reduce the initial microbial load (>2 log10 cycles) and to maximize sensorial attributes. In both mix pulps, total phenolic content (TPC) was not significantly influenced by the different applied time-temperature binomials. From the degradation kinetic models and as an example, it was possible to conclude that POD followed a 1st order kinetic, where the temperature effect was well fitted to the Arrhenius equation. The results allowed to obtain optimized time-temperature binomials for each pulp to simultaneously achieve POD enzyme inactivation, microbial reduction, and maximization of quality parameters relatively to fresh pulps, 90 °C/5 min and 98 °C/2.5 min, for the yellow pulp and red pulp, respectively.

Effect of Heat Treatment on Smoothie Quality by Response Surface Methodology

“…Color analysis was evaluated using a tristimulus colorimeter (Minolta chroma Meter, CR-300, Osaka, Japan), measuring the CIEL*a*b* parameters as described in [8]. From the CIELab coordinates, hue (ºh) and total color difference (∆E = ((∆L) 2 + (∆a) 2 + (∆b) 2 ) 0.5 were calculated as described in [9,10], respectively. Sixteen measurements were determined per treatment condition.…”

Chemical kinetics and thermodynamics of PPO activity, colour changes and microbial degradation during blanching of the sugarcane billets

“…Kinetic models have also identified a correlation between nutrient contents, enzyme activities, and heat treatment temperatures. [15][16][17][18] The understanding on progress of reactions is dependent on knowledge of thermodynamics and kinetics. Thermodynamics explains the driving force for any reaction and is helpful in understanding direction of reaction, along with changes involved in energy and entropy.…”

“…20 Arrhenius and Errying equations have been widely used to evaluate effect of temperature on chemical and biological reaction rates in fruit juices, which led to reduction in quality losses. 16,21 The Lineweaver-Burk equation has been utilized to obtain the K m and V max values of PPO inhibition kinetics of bean sprouts, mushroom, blackberry and tea. [22][23][24][25] The information of chemical kinetics and thermodynamics for the various reactions involved in change in PPO activity, colour and microbial degradation during blanching the sugarcane has not been the subject of investigation so far.…”

Current Trends in Intelligent Control Neural Networks for Thermal Processing (Foods): Systematic Literature Review

“…The processing time at a specific retort temperature must be carefully calculated to reach a safe level of microbial activity inactivation, ensuring public safety and health. For these objectives, the accuracy in the calculation method is essential for the development of food science and its professional technical practitioners [11], [12], [13].…”

“…Neural Network is a parallel information processing system consisting of a number of neurons (nodes or units), which are arranged in layers and connected by links. Neural Network mimics the highly interconnected structure of the human brain and nerves [13], [20]. According to [21], Neural Network is a computational method that builds multiple processing units based on interconnected connections.…”