Influence of voltage and distance on quality attributes of mixed fruit beverage during pulsed light treatment and kinetic modeling

Abstract

The study investigates the influence of pulsed light (PL) processing parameters on quality of mixed fruit beverage followed by kinetic modeling. The attributes tested were aerobic mesophiles (AM), yeast and mold (YM) counts, polyphenol oxidase (PPO) and peroxidase (POD) activity, color change (ΔE*), browning index (ΔBI), antioxidant capacity (AOC), and ascorbic acid (AA) content at varying voltage (1.8–2.4 kV), the number of pulses (2–187), and distance (2.4–9.6 cm). Weibull model described the PL inactivation rate of AM and YM and nth order kinetic model estimated the inactivate rate of PPO, POD, and AA. The maximum inactivation of PPO, POD, and AA content were 41, 51, and 36%, respectively. At the most severe PL condition, ΔE* was 6.4, ΔBI was 5.6 with 14% increment in phenolics. A secondary kinetic model adequately predicted the ratio of rate constant and fluence‐based rate (k/kF) for PPO, YM, and AA correlating voltage (V) and lamp distance (x). PL‐induced pasteurization of the beverage is possible at the fluence rate of 17.42 W/cm2 for 3 min. Practical Applications Exposing the food material to a high intensity pulsed light (PL) is a nonthermal way of food preservation for the shelf‐life extension. The potential of PL treatment (PLT) has been explored for a mixed fruit beverage in terms of its microbial, enzymatic, and nutritional quality. An optimized PLT condition is proposed to obtain a microbially safe fruit beverage along with a minimal loss in bioactive compounds. Subsequently, the kinetic data related to microbial and enzyme inactivation and degradation of vitamins will help in deciding the process parameters like treatment time, lamp voltage, and sample distance from the light source. The secondary kinetic model will eventually help to design a robust PL process condition for similar fruit beverages to obtain a microbiologically safe product with a minimal loss in vitamins.

Pasteurization of fruit juices by pulsed light treatment: A review on the microbial safety, enzymatic stability, and kinetic approach to process design

“…Depending on the type and source of enzyme, the efficacy of PL inactivation greatly varies. Table 2 lists the various enzymes in juices and how the different matrices and treatment conditions can affect the inactivation trend to PLT (Dhar & Chakraborty, 2020; Vollmer et al., 2020).…”

“…Increasing the lamp's supply voltage will simply increase the fluence rate (or fluence per pulse), causing the total fluence to rise as well. It is evident that as the fluence rate or total fluence increases, the magnitude of microbial or enzyme inactivation will also rise to a certain extent (Dhar & Chakraborty, 2020). UV range in the PL's spectrum is mainly responsible for microbial and enzyme inactivation (Levy et al., 2012; Wang et al., 2005).…”

“…The browning values of the thermally treated and PL‐treated pineapple juice were not significantly different. Dhar and Chakraborty (2020) obtained a ΔE * of 6.4 and ΔBI (change in browning index) of 5.6 at a fluence rate of 17.42 W·cm –2 for 3 min in a mixed fruit beverage. Browning is usually observed with a decrease in L * value (lightness) and an increase in a * value (“– a *” green to “+ a *” red color).…”

Microbial Decontamination of Rice Germ Using a Large-Scale Plasma Jet-Pulsed Light-Ultraviolet-C Integrated Treatment System

“…Hence, it is presumed that an increase in the operation time allowed the higher concentration of reactive species to sufficiently react with the natural microorganisms in rice germ, leading to a high microbial inactivation level. Furthermore, as operation time increases, the number of IPL pulses increases, ultimately increasing the total fluence applied to the sample (Dhar and Chakraborty 2020). An increase in the operation time of IPL treatment could have induced more physical damage on cell membranes and walls, leading to more frequent microbial inactivation, compared to when samples are treated for a shorter duration (Cheigh et al 2012;Elmnasser et al 2007;Koch et al 2019).…”

Formulation of a mixed fruit beverage using fuzzy logic optimization of sensory data and designing its batch thermal pasteurization process

“…Blending provides judicious use of minor or underexplored fruits and makes a new range of natural drinks available for the consumers (Bhardwaj & Pandey, 2011). However, it can be hypothesized that masking the bitter and astringent taste of amla and simultaneously utilizing its antioxidant potential can be done by blending with pineapple juice and coconut water (Dhar & Chakraborty, 2020). Pineapple juice will provide the dominant flavor and majority of the soluble solids.…”