Effects of instant controlled pressure drop treatment combined with refractance window drying on infusion quality of made green tea

BACKGROUND

The study aimed to determine the effects of instant controlled decompression of steam pressure, termed as ICPD (instant controlled pressure drop) on fresh tea leaves, when combined with refractance window drying (RWD) of rolled green teas during green tea manufacturing. The ICPD steam treatment pressure (TP; 0.1-0.3 MPa), treatment time (TT; 10-20 s) and refractance window drying temperature (RWDT; 70-90 °C) were used as the processing parameters for manufacturing of green tea.

RESULT

Response surface methodology was employed to enumerate the effects of ICPD process conditions and temperature of RWD on total phenolic content (TPC), total flavonoid content (TFC) and DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity of the green tea infusion. An optimum condition for green tea processing was found at TP 0.2 MPa, TT 20 s with RWDT at 70 °C. In comparison to made green tea manufactured without ICPD treatment, the ICPD treated green tea showed enhanced TPC, TFC and DPPH radical scavenging activity along with better colour and sensory attributes. The microstructural study of ICPD treated green tea samples showed more deformed cell surface integrity, larger stomatal pore size and cracks at the leaf surface in comparison with non-treated green tea sample.

CONCLUSION

Present study reveals that an ICPD treatment at 0.2 MPa for 20 s can be used as an alternative to the traditional enzyme inactivation step of hot water treatment, for green tea leaves to improve the infusion quality in terms of increased levels of TPC and TFC and DPPH radical scavenging activity. © 2024 Society of Chemical Industry.

Adaptive neuro-fuzzy interface system and neural network modeling for the drying kinetics of instant controlled pressure drop treated parboiled rice

Hot air drying kinetics of paddy grains during instant controlled pressure drop (ICPD) assisted parboiling process and its impact on the quality and micro-structural properties of milled rice were investigated. Among five mathematical models, Midilli model showed best fitted outcomes for prediction of adequate drying behavior. For the mapping of moisture ratio (MR) as a function of treatment pressure (TP), decompressed state duration (DD) and drying time (DT), artificial neural network (ANN) and adaptive neuro-fuzzy interface system (ANFIS) were applied. ANFIS model (5-5-5) with Gaussian membership function demonstrated best performance when contrasted with 3-5-1 ANN architecture. Effective diffusivity of the drying process varied from 2.8 × 10^-09 to 7.0 × 10^-09 m²/s with the increase of TP and DD. In comparison of quality parameters with the variation of TP and DD, positive impacts on head rice yield (HRY), redness (a*) and yellowness (b*) values and negative consequences on cooking time (CT) and brightness (L*) value were observed. The outcomes additionally uncovered that parboiled rice obtained at 0.6 MPa TP, indicated best quality in terms of improved process performance, HRY, CT, color and micro-structural properties.

Reaction order and neural network approaches for the simulation of COVID-19 spreading kinetic in India

COVID-19 has created a pandemic situation in the whole world. Controlling of COVID-19 spreading rate in the social environment is a challenge for all individuals. In the present study, simulation of the lockdown effect on the COVID-19 spreading rate in India and mapping of its recovery percentage (until May 2020) were investigated. Investigation of the lockdown impact dependent on first order reaction kinetics demonstrated higher effect of lockdown 1 on controlling the COVID-19 spreading rate when contrasted with lockdown 2 and 3. Although decreasing trend was followed for the reaction rate constant of different lockdown stages, the distinction between the lockdown 2 and 3 was minimal. Mathematical and feed forward neural network (FFNN) approaches were applied for the simulation of COVID-19 spreading rate. In case of mathematical approach, exponential model indicated adequate performance for the prediction of the spreading rate behavior. For the FFNN based modeling, 1-5-1 was selected as the best architecture so as to predict adequate spreading rate for all the cases. The architecture also showed effective performance in order to forecast number of cases for next 14 days. The recovery percentage was modeled as a function of number of days with the assistance of polynomial fitting. Therefore, the investigation recommends proper social distancing and efficient management of corona virus in order to achieve higher decreasing trend of reaction rate constant and required recovery percentage for the stabilization of India.

Drying characteristics of ready-to-eat komal chawal rice: processing and modeling

A traditional ready-to-eat rice from Assam, India, known as komal chawal is produced by steaming of steeped chokuwa paddy, which is a low-amylose variety, and by drying the steamed paddy under shade as a measure of controlling the drying rate for sustenance of a quick rehydration quality. As an improvement over this traditional method in terms of production time, komal chawal is produced by parboiling the chokuwa brown rice with model predicted soaking and steaming conditions. Thin-layer drying behavior of the steamed brown rice was studied at drying temperatures of 40-60 °C, at an air velocity of 1 m/s. Among different thin-layer drying models, Page equation fitted best to the drying data, with the coefficient of determination (R2) and root mean square error as the measures for selection of the best fitted model. While the moisture diffusivity values were in the range of 2.08 × 10-10-3.34 × 10-10 m2/s, the effects of drying air temperature on the drying rate was modeled with an activation energy of 20.44 kJ/mol for an the Arrhenius kind of temperature dependence of diffusivity. Based on the effects of drying temperature on rehydration, textural, and pasting properties of the product a lower drying temperature is recommended.

Quality of ready-to-eat komal chawal produced by brown rice parboiling method

Komal chawal, meaning soft rice, produced by brown rice parboiling of a low amylose rice variety chokuwa, was studied for its physical, physico-chemical, morphological and structural characteristics. The product was produced by soaking the brown rice at 60 °C for 90 min, followed by steaming and air drying to 12.0% (wb). The two steaming conditions used were: (1) open-steaming at atmospheric pressure for 20 min and (2) pressure-steaming at 1 atm (gauge) for 10 min. The three different drying temperatures used were 40, 50 and 60 °C. When soaked in water at 60 °C for 20 min the product attained a hardness value of cooked rice. The extent of changes in the kernel and flour properties as compared to the raw form were affected by the severity of the steaming condition and drying air temperature. The pressure steamed samples exhibited virtually persistent growth in paste viscosity in the profiles obtained from the rapid viscosity analyzer. X-ray diffraction analysis of flours revealed a loss of A-type pattern and formation of feeble peaks of A + V-type mixed patterns in steam-treated samples. Scanning electron photomicrographs showed the loss of the polygonal shape by starch granules during processing. The values of rehydration ratio, equilibrium moisture content for rehydration, sediment volume, extent of color change as denoted by total color difference, and the percent head rice yield were higher in pressure steamed komal chawal samples.