Mean Relative Percentage Deviation Research Articles

Effects of screw pressing conditions on fodder radish seed oil yield, throughput, and fatty acid profile

AbstractThis study aims to explore the influence of screw frequency, nozzle diameter, and press head temperature on critical crude fodder radish seed oil (FRSO) yield, throughput, and fatty acid composition. A quadratic equation, developed using response surface methodology, fitted the experimental data for oil yield. It was substantiated by a non‐significant lack‐of‐fit, commendable coefficient‐of‐determination (R2 = 0.782), and a modest mean relative percentage deviation (±7.27%). The analysis of variance pinpointed the statistical significance of press head temperature, nozzle size, and the squared term of press head temperature. The highest FRSO yield (17.61%)—corresponding to an extraction efficiency of 51.3% was found with a screw frequency of 50 Hz, at 80°C, and an 8 mm nozzle. A linear model highlighted that all three pressing factors significantly influenced the FRSO throughput. FRSO consists of C18:1 (30.9%), C22:1 (20.8%), C18:2 (14.9%), and C18:3 (11.9%), aligning with the compositions reported in other studies on fodder radish oils.Practical applicationsEffective control of cold pressing parameters is paramount to maximize oil yield and throughput during the oil extraction process and to ensure the appropriate oil quality. A comprehensive understanding of the intricacies of this process, while carefully considering key parameters, which is essential to ensure efficiency, is achieved through a combination of experimental and statistical methods. This study marks the inaugural attempt to optimize screw pressing for fodder radish seeds while conducting a comparative analysis with hydraulic pressing and the Soxhlet extraction method, focusing on oil yield, throughput, and fatty acid composition within the system by employing a modeling approach for oil extraction. Through the utilization of the response surface methodology coupled with various experimental designs, the processing conditions are successfully optimized. The valuable data gathered can aid equipment design for an efficient, eco‐friendly oil extraction process. Furthermore, the oil extracted under the optimized conditions met the quality standards.

Optimization of radioprotective dose of Juglans nigra leaf extract using response surface methodology

J. nigra leaf contains mixture of various pharmacologically active compounds and it is assumed that they may have the potential radioprotective effect. The purpose of this work was to predict radioprotective doses by correlating changes in organ distribution of radiopharmaceuticals with extract dose levels and rat body weight using response surface methodology (RSM) based on a second-order polynomial equation. The extract was administered daily by oral gavage to rats at dose of 6.9, 10.3, or 13.7 mg kg−1 body weight (bw) day−1 for 10 days. On the eleventh day, 0.1 ml of the one radiopharmaceutical (Na99mTcO4, 99mTc-dimercaptosuccinic acid and 99mTc-tin colloid) was injected into the tail vein. The statistical parameters: the coefficient of determination (0.81–0.95), the coefficient of variation (3.05–11.1), the adequate precision (8.82–19.12) and the mean relative percentage deviation (± 2.3–8.2) were indicated the precision and reliability of RSM. Using RSM, the predicted daily dose of leaf extract ranging from 11.19 to 11.99 mg kg−1 bw may be considered as an optimal daily radiopotective dose for protection of organs from radiation in cases of planned radiation exposures.

Assessment of water absorption characteristics for improved sesame (Sesamum indicum L.) varieties during hydration

AbstractThe water absorption characteristics of sesame varieties (GT‐3, GT‐4, GJT‐5, GT‐6, and TKG‐22) were studied during hydration at temperatures ranging 35–55°C. The Peleg model adequately defined the hydration behavior of sesame seed varieties at the 35°C, 45°C, and 55°C soaking temperatures with the comparable coefficient of determination (R2) and mean relative percentage deviation modulus (P). The Peleg rate constant K1 and the capacity constant K2 reduced significantly with the rise in hydration temperatures, suggesting corresponding increases in the initial hydration rate as well as the equilibrium moisture content in all the varieties tested. The Arrhenius equation was used to calculate the activation energy (Ea) of GT‐3, GT‐4, GJT‐5, GT‐6, and TKG‐22 sesame varieties and was noted to be 38.74, 33.37, 30.68, 37.85, and 33.23 kJ/mol, respectively. The enthalpy (H) was raised significantly with hydration temperature while entropy (ΔS) and released energy (ΔG) were found nonsignificant (p > 0.05).

Mathematical Models of Moisture Sorption Isotherms of Grains Sorghum (Sorghum bicolor (L.) Moench)

1U. of K. J. Agric. Sci. 22(1), 1-12, 2014Mathematical Models of Moisture Sorption Isotherms of GrainsSorghum (Sorghum bicolor (L.) Moench)Eman Abdu Abdalla1 , Mohamed Ayoub Ismail and AbdelmoniemElamin Mohamed2Department of Agricultural Engineering, Faculty of Agriculture,University of Khartoum, SudanAbstract: The objective of the study was to fit or test the experimentaldata of adsorption and desorption isotherms of grains sorghum The studywas carried out at the Department of Agricultural Engineering, Faculty ofAgriculture, University of Khartoum and the Food Processing ResearchCenter, Shambat, Sudan, during January 2007 - March 2008. Fourmathematical models namely modified Henderson, modified Chung-Pfost, modified Oswin and modified Halsey were used to predict sorptionisotherms. The adsorption and desorption isotherms were determinedusing standard static gravimetric method, six levels of water activitiesrang 0.112- 0.865 were maintained by using saturated salt solutions insideair-tight glass desiccators, while incubators were used to maintain three aconstant temperature namely 25oC,35 oC and 45oC. A non-linearregression analysis was used to evaluate the parameters of the fourselected models. The models were compared by using statisticalparameters: mean relative percentage deviation (P%), standard error ofestimates (Es), coefficient of determination (R2 ) and randomness ofresidual plots of difference between measured and predicted values. Forthe mathematical models, the results indicated that the modified Chung-Pfost model satisfactorily predicts the adsorption and desorptionisotherms of grains sorghum

2D mapping of radiation dose and clonogenic survival for accurate assessment of in vitro X-ray GRID irradiation effects

Spatially fractionated radiation therapy (SFRT or GRID) is an approach to deliver high local radiation doses in an ‘on-off’ pattern. To better appraise the radiobiological effects from GRID, a framework to link local radiation dose to clonogenic survival needs to be developed. A549 lung cancer cells were irradiated in T25 cm2 flasks using 220 kV x-rays with an open field or through a tungsten GRID collimator with periodical 5 mm openings and 10 mm blockings. Delivered nominal doses were 2, 5, and 10 Gy. A novel approach for image segmentation was used to locate the centroid of surviving colonies in scanned images of the cell flasks. GafchromicTM film dosimetry (GFD) and FLUKA Monte Carlo (MC) simulations were employed to map the dose at each surviving colony centroid. Fitting the linear-quadratic (LQ) function to clonogenic survival data for open field irradiation, the expected survival level at a given dose level was calculated. The expected survival levels were then mapped together with the observed levels in the GRID-irradiated flasks. GFD and FLUKA MC gave similar dose distributions, with a mean peak-to-valley dose ratio of about 5. LQ-parameters for open field irradiation gave Gy−1 and Gy−2. The mean relative percentage deviation between observed and predicted survival in the (peak; valley) dose regions was (4.6; 3.1) %, (26.6; −1.0) %, and (129.8; −2.3) % for 2, 5 and 10 Gy, respectively. In conclusion, a framework for mapping of surviving colonies following GRID irradiation together with predicted survival levels from homogeneous irradiation was presented. For the given cell line, our findings indicate that GRID irradiation causes reduced survival in the peak regions compared to an open field configuration.

Kinetics of the used cooking oil transesterification in the presence of slaked lime and the triethanolamine:menthol deep eutectic solvent

AbstractThe biodiesel production from the used cooking oils from the frying of different food items (French fries, chicken breasts, or pork steaks) and methanol in the presence of slaked lime as a catalyst and the triethanolamine:menthol (1:2 mol/mol) deep eutectic solvent as a cosolvent was studied. This deep eutectic solvent accelerated the transesterification reaction. The transesterification reaction involves only the chemical reaction controlled region from its beginning and follows the pseudo‐first‐order reaction rate law. A good agreement between the model and the experimental data was confirmed by a low mean relative percent deviation between the predicted and observed values of triacylglycerol conversion degree (<3.5%). The highest apparent reaction rate constant of 0.421 min−1 was achieved with the used cooking oil from frying pork steaks at 60°C. The activation energy increases in the following order of the used cooking oils from frying the food items:French fries (23.1 kJ/mol) chicken breasts (30.7 kJ/mol) pork steaks (41.6 kJ/mol). A methyl esters content higher than 97.5% was achieved within 40 min of the transesterification of the used cooking oils over slaked lime combined with the triethanolamine:menthol deep eutectic solvent.

Kinetics and optimization of biodiesel production from rapeseed oil over calcined waste filter cake from sugar beet processing plant

A low-cost, highly active CaO-based catalyst was prepared from waste filter cake (WFC) from a sugar beet processing factory by calcination in air at 900 °C for 2 h, referred to as the calcined filter cake (CFC). It was used to catalyze the rapeseed oil transesterification with methanol under mild reaction conditions (methanol-to-oil molar ratio of 9:1, catalyst loading of 4–10 %, and reaction temperature of 40–60 °C). Rapeseed oil was characterized regarding the physicochemical properties and fatty acid profile. Low free fatty acid content (about 2.0 mg KOH/g) allowed the direct use of the base CFC catalyst for rapeseed oil transesterification. Rapeseed oil has more unsaturated fatty acids (about 93 %), with oleic acid as the most abundant, than saturated fatty acids (about 7 %). A simplified model combining the changing mechanism of the reaction and the triacylglycerols mass transfer limitation successfully describes the kinetics of transesterification. A good agreement between the model and the experiment was proved by the mean relative percentage deviation for the conversion degree of only ± 7.43 % (based on 42 data). The apparent reaction rate constant follows the Arrhenius equation with the activation energy of 51.9 kJ mol−1. The FAME content higher than 96.5 % can be obtained in wide ranges of the catalyst amount (4–10 %) and the reaction time (about 45–70 min). The following conditions were optimum: the reaction temperature of 59.2 °C, the catalyst loading of 9.1 % (based on the oil weight), and the reaction time of 47 min.

Crude rubber seed oil esterification using a solid catalyst: Optimization by hybrid adaptive neuro-fuzzy inference system and response surface methodology

Esterifying high free fatty acid (FFA) oil with acid is necessary to avoid soap formation during biodiesel production. Thus, this study evaluated the efficacies of response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS) in modeling the esterification process for crude rubber seed oil (CRSO) with a high FFA catalyzed by dehydrated Fe2(SO4)3. A central composite design (CCD) with three factors and five levels was applied to examine the influence of methanol:CRSO molar ratio (25:1–75:1), Fe2(SO4)3 loading (8–16 wt %), and time (3–4 h) on reduction of the high FFA (22.2%) of CRSO. The performance of the particle swarm optimization (PSO), genetic algorithm (GA), and RSM were assessed in optimizing the process variables. Statistics for the ANFIS and RSM models showed that both could reliably describe the esterification process with low mean relative percent deviation (MRPD) of 1.77 and 4.98; and high coefficients of determination (R2) of 0.9838 and 0.9730, respectively. The optimization results are in this order: ANFIS-PSO, ANFIS-GA, RSM-PSO, RSM, and RSM-GA. The ANFIS-PSO hybrid predicted the best optimal condition as Fe2(SO4)3 loading of 16.97 wt%, methanol:CRSO molar ratio of 44.21:1, and time of 3.39 h with the lowest FFA of 0.56%.

Evaluation and Mathematical Analysis of a Four-Dimensional Lotka–Volterra-like Equation Designed to Describe the Batch Nisin Production System

Nisin, an antibacterial compound produced by Lactococcus lactis strains, has been approved by the US Food and Drug Administration to be used as a safe food additive to control the growth of undesirable pathogenic bacteria. Nisin is commonly described as a pH-dependent primary metabolite since its production depends on growth and culture pH evolution. However, the relationships between bacteriocin synthesis (BT), biomass production (X), culture pH, and the consumption of the limiting nutrient (total nitrogen: TN) have not been described until now. Therefore, this study aims to develop a competitive four-dimensional Lotka–Volterra-like Equation (predator-prey system) to describe these complex relationships in three series of batch fermentations with L. lactis CECT 539 in diluted whey (DW)-based media. The developed four-dimensional predator-prey system accurately described each individual culture, providing a good description of the relationships between pH, TN, X, and BT, higher values for R2 and F-ratios, lower values (<10%) for the mean relative percentage deviation modulus, with bias and accuracy factor values approximately equal to one. The mathematical analysis of the developed equation showed the existence of one asymptotically stable equilibrium point, and the phase’s diagram obtained did not show the closed elliptic trajectories observed in biological predator-prey systems.

Sunflower oil methanolysis over modified CaO catalysts

Oil methanolysis over modified CaO catalysts was studied to assess the catalytic performance and to define an appropriate kinetic model. CaO was modified by commercial glycerol and a deep eutectic solvent (DES), choline chloride : glycerol (ChCl : Gly), to obtain catalytically active complexes of CaO and glycerol. The main goal was to investigate the effect of the obtained complexes on the reaction rate and fatty acid methyl ester (FAME) content and to describe the variation of the triacylglycerol (TAG) conversion degree during the reaction time. Fourier transform infrared spectroscopy (FTIR) was applied to confirm the formation of CaO complexes with glycerol or the glycerol-based DES. Different catalyst loadings (0.5, 1, and 5 % of oil weight) and methanol-to-oil molar ratios (6 : 1 and 12 : 1) were applied for investigation of the sunflower oil methanolysis at 60 oC. Two kinetic models were employed yielding the kinetic parameters, which depended on the catalyst loading and the methanol-to-oil molar ratio. Both models showed valid applicability for describing the kinetics of the reactions catalyzed by both complexes (the mean relative percent deviation was lower than 10 %).

Optimized biodiesel production from C. innophyllum bio-oil using Kriging and Ann predicitive models

This work aimed at optimizing the two-stage transesterification efficiency of the production of C. inophyllum biodiesel using artificial neural network and Kriging predictive models. Response surface methodology was used to develop the central rotatable composite design of 27 trial experimental runs with variations in the input process parameters like methanol to oil molar ratio, potassium hydroxide catalyst loading, and reaction time. A multi-layered non-linear regressive artificial neural network model with feed-forward propagation and a numerical surrogate Kriging model was used to predict the C. inophyllum biodiesel yield. The efficacy of the developed model was verified using analysis of variance by com-paring its coefficient of determination and the mean relative percentage deviation values. The optimized C. inophyllum biodiesel as 98.1% is derived with 0.94 v/v of methanol to oil molar ratio, 0.98 wt.% of potassium hydroxide catalyst loading, and 80 minutes reaction time with 70?C constant reaction temperature as predicted by Kriging model. The optimized parameters were also verified experimentally.

Development of an innovative mathematical model to design an active modified atmosphere storage system for mango (cv. Amrapali)

AbstractCurrently, the modified atmosphere storage (MAS) technique is one of the most economical and widely adopted practices used to enhance the shelf life of fresh produce including mango. The MAS system is designed in two ways; one is called passive MAS and other is active MAS. Nowadays the bulk handling and storage of fresh produce at on‐farm level is one of the challenging tasks and therefore, using the basic principle of modified atmosphere packaging (MAP) the study was aimed to develop an active MAS system. In this study, to design an active MAS system for 100 kg of mango, an innovative active mathematical model was developed using enzyme kinetics‐based respiration rate model coupled with Arrhenius equation under active condition (50, 100, and 150 cc of O2 absorber). The designed active system was used for on‐farm handling and storage of mango at 27°C. The basic aim of the model was to determine the exact quantity of oxygen absorber required to bring early dynamic equilibrium condition inside the MAS system with optimum level of gas concentration (5–8% O2 and 5–8% CO2) for mango. The model was solved by Adam's numerical method using Taylor's formulae and iterated in MATLAB software. The mean relative percentage deviation moduli (E) between the experimental and predicted values of O2 and CO2 concentration was found to be 8.97 and 8.42%, respectively, indicating the accuracy of the developed active model.Practical applicationsOn‐farm handling of fresh horticultural crops is the leading problem for orchard growers and causes excess postharvest losses. The current work presents some interesting results on the determination of the exact concentration of oxygen absorber required to design an accurate as well as a perfect active modified atmosphere storage system for 100 kg of mango using the concept of mathematical modeling. The principle aim of this approach was to increase the adaptability of the modified atmosphere packaging concept for preservation and shelf life extension of fresh produce during bulk handling and transportation. The designed system is easy to handle mango during its on‐farm storage and might become a boon for orchard growers.

The empirical formula for calculating the incident air Kerma in intraoral radiographic imaging.

The aim of this paper is to determine the empirical formula for calculating the incident air kerma (Ki), used as a patient dose descriptor in the intraoral radiographic imaging. The data for the formula were collected during the regular annual inspection of intraoral dental X-ray units in 2018, 2019 and early 2020. The measurement data of 50 X-ray units were processed to develop the formula. Exposure factors for imaging molars of the upper jaw of an average patient in a clinical setting were used in the measurement. The formula validity was statistically evaluated using coefficient of correlation, standard error of the fitted function and the mean relative percentage deviation. The measurement values of the radiation doses and calculated values obtained by using the final formula showed good agreement - the mean relative percentage deviation values less than ±15%. Although there are differences in X-ray units, voltages, manufacturers and device architectures (single-phase and high-frequency), the measurement data comply well with computed ones in all cases.

A new model for soil water vapor sorption isotherms considering adsorption and condensation

AbstractA new model, which was based on the Do and Do (2000) model, was developed to describe soil water vapor sorption isotherms (SWSIs) including both adsorption and condensation processes. The model performance was evaluated using measured SWSIs of 33 soil samples with a wide range of clay contents (0.08–0.72 g g−1), clay mineralogy (montmorillonite, kaolinite, and mixed clay samples), and organic C contents (0.001–0.070 g g−1). The new model produced satisfactory fits to measured SWSIs, with the mean relative percentage deviation modulus less than 6.2%. For a given clay mineral type, the adsorption sites and condensation capacity increased with increasing clay content. At a given clay content, the number of adsorption sites was in the order of montmorillonitic samples (ML)>mixed clay samples (MX)>kaolinitic samples (KA), and the condensation capacities of ML and MX were lower than that of KA. For soils with low clay content (<0.12 g g−1) and similar clay mineralogy, the adsorption sites and condensation capacities were positively related to organic C. The model parameter S0 had the potential for deriving cation exchange capacity, specific surface area, and clay content. The C/S0 values could potentially be used as a proxy of the dominant clay mineral type in a sample.

Modeling the biodiesel production using the wheat straw ash as a catalyst

Wheat straw ash (WSA) was investigated as a new catalyst in biodiesel production from sunflower oil. The catalyst was characterized by temperature-programmed decomposition, X- ray powder diffraction, Hg porosimetry, N2 physisorption, and scanning electron microscopy - energy dispersive X-ray spectroscopy methods. The methanolysis reaction was tested in the temperature range of 55?65?C, the catalyst loading range 10?20 % of the oil weight, and the methanol-to-oil molar ratio range 18 : 1?24 : 1. The reaction conditions of the sunflower oil methanolysis over WSA were optimized by using the response surface methodology in combination with the historical experimental design. The optimum process conditions ensuring the highest fatty acid methyl esters (FAME) content of 98.6 % were the reaction temperature of 60.3?C, the catalyst loading of 11.6 % (based on the oil weight), the methanol-to-oil molar ratio of 18.3 :1, and the reaction time of 124 min. The values of the statistical criteria, such as coefficients of determination (R2 = 0.811, R2 = 0.789, R2 = 0.761) and the mean relative percent deviation (MRPD) value of 10.6 % (66 data) implied the acceptability and precision of the developed model. The FAME content after 4 h of reaction under the optimal conditions decreased to 37, 12, and 3 %, after the first, second, and third reuse, respectively.

Uticaj sastava masnih kiselina na brzinu reakcije metanolize biljnih ulja

The base-catalyzed methanolysis of roadside pennycress, olive, melon, grapeseed, hempseed, sunflower, and plum kernel oils was performed in the presence of KOH (1% to the oil weight) at the temperature of 60° C and the methanol/oil molar ratio of 6:1. The aim of this work was to reveal the influence of the fatty acid composition of the oils on the kinetics of these methanolysis reactions. The irreversible pseudo-first-order reaction was used for modeling the kinetics of the methanolysis reactions, and the reaction rate constant was correlated with the content of unsaturated fatty acids in the oil. The value of the reaction rate constant increases linearly with increasing the unsaturated fatty acids content in the oil. The applicability and reliability of the model were confirmed by high values of the coefficient of determination and low values of the mean relative percentage deviation between the calculated and experimental triacylglycerols conversion degree.

Mathematical Modeling and Optimization Studies by Artificial Neural Network, Genetic Algorithm and Response Surface Methodology: A Case of Ferric Sulfate–Catalyzed Esterification of Neem (Azadirachta indica) Seed Oil

High free fatty acids (FFA) content in oils poses challenges such as soap formation and difficulty in the separation of by-products in direct transesterification of oil to biodiesel, which is of environmental concern and also increases the cost of production. Thus, in this study, the ferric sulfate-catalyzed esterification of neem seed oil (NSO) with an FFA of 5.84% was investigated to reduce it to the recommended level of ≤1%. The esterification process for the NSO was modeled using response surface methodology (RSM) and artificial neural network (ANN). The effect of the pertinent process input variablesviz.methanol/NSO molar ratio (10:1–30:1), ferric sulfate dosage (2–6 wt%), and reaction time (30–90 min) and their interactions on the reduction of the FFA of the NSO, were examined using Box Behnken design. The optimal condition for the process for reducing the FFA content of the oil was established using RSM and ANN-genetic algorithm (ANN-GA). The results showed that the models developed described the process accurately with the coefficient of determination (R2) of 0.9656 and 0.9908 and the mean relative percent deviation (MRPD) of 6.5 and 2.9% for RSM and ANN, respectively. The ANN-GA established the optimum reduction of FFA of 0.58% with methanol/NSO molar ratio of 18.51, ferric sulfate dosage of 6 wt%, and reaction time of 62.8 min as against the corresponding values of 0.62% FFA, 23.5, 5.03, and 75 min established by the RSM. Based on the statistics considered in the study, ANN and GA outperformed RSM in modeling and optimization of the NSO esterification process.

Process modeling of solvent extraction of oil from Hura crepitans seeds: adaptive neuro-fuzzy inference system versus response surface methodology

Vegetable oils are a very important feedstock for many industries such as biofuels. There is the need to source for novel and underexploited plant oilseeds to meet the world demand for oils. Thus, the extraction of oil from Hura crepitans (sandbox) seeds was conducted using the solvent extraction method. Modeling of the extraction process was carried out using response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS). The effects of the nature of the solvent (non-polar (n-hexane) and polar (acetone and ethyl acetate)), solid-solvent ratio (0.1–0.3 g/mL), extraction time (2–6 h), and their interactions on the oil yield were investigated using the D-optimal design technique. Performance assessment of the developed models was carried out to check their effectiveness in predicting the H. crepitans seed oil (HCSO) yield using various fit statistics. The coefficient of determination (R2) observed for the RSM and ANFIS models was 0.9720 and 0.9988, respectively, with corresponding mean relative percent deviation (MRPD) of 2.50 and 0.37%. Maximum HCSO yield of 62.95 wt% was achieved by ANFIS coupled with genetic algorithm (GA) using 0.1 g/mL solid-solvent ratio, extraction time of 4.19 h, and acetone, while maximum HCSO yield of 62.50 wt% was observed by RSM with a solid-solvent ratio of 0.1 g/mL, extraction time of 4.04 h, and acetone. Characteristics of the HCSO indicated that it could serve as a good feedstock for the production of oleochemicals such as biodiesel. The results obtained in this study demonstrated that ANFIS is marginally superior to RSM in the modeling of the HCSO extraction process, while GA was slightly better than the numerical tool of RSM in the optimization of the process.

Kinetics Study of Microwave-Assisted Brine Extraction of Lipid from the Microalgae Nannochloropsis sp.

The kinetics of lipid extraction utilizing microwave-assisted extraction (MAE) from Nannochloropsis sp. microalgae were studied using a low cost and green solvent, namely brine (NaCl) solution. The kinetic modelling of the lipid extraction was performed to evaluate the mechanism of the lipid mass transfer using different extraction models, including Fick’s Law, First and Second-order Rate Law and the Patricelli mathematical model. The Patricelli mathematical model described the kinetics of lipid extraction well, with the highest average values of determination coefficient (R2 ≥ 0.952) and the lowest average values of mean relative percentage deviation (MRPD ≤ 8.666%). The lipid analysis indicated a positive influence of the microwave temperature and time on the quantity and quality of extracted lipids. SEM analysis of spent microalgae clearly shows an increase in the distorted cell with increase microwave temperature and time, which could be directly correlated to the mechanism of the MAE-brine technique.

Moisture sorption isotherm and shelf‐life prediction of anticaking agent incorporated spray‐dried soursop (Annona muricata L.) powder

AbstractThe moisture sorption isotherm (MSI) and shelf lives of soursop powders that had been incorporated with two commercial anticaking agents, calcium silicate (CS) and tricalcium phosphate (TCP), and inserted into aluminum laminated polyethylene pouches under room (RT, 25 ± 1°C) and elevated (ET, 38 ± 1°C) temperature, maintained at 93 ± 1% RH, were investigated. The powder possessed a Type III Brunauer's classification isotherm curve. The monolayer moisture content (Mo) was 0.023 ± 0.001 g H2O/g ds. A combination of low mean relative percent deviation modulus, E (2.18–3.75%), small sum of square residual, SSR (1.03 × 10−5–8.51 × 10−6), and high coefficient of determination (R2 > .99) indicating the moisture sorption data was sufficiently good fit using GAB model. Powder without anticaking agent stored at ET has the shortest estimated shelf life (~86 days) while 1.0 g/100 g TCP stored at RT exhibited the longest shelf life (~316 days). This study demonstrated that the incorporation of anticaking agents is effective to maintain the quality of powder by extending the shelf life by lowering moisture adsorption. The acceptability of reconstituted soursop powder based on hedonic test showed the scores for all attributes were higher than six.Practical applicationsUp to date, limited information describes the preservative effect of anticaking agents throughout the storage period. Hence, this work provides an insight to look into detail of how the incorporation of anticaking agents improve or retain the quality of the dried powder especially the moisture sorption isotherm (MSI) behavior. To achieve this, enzymatic pre‐treated spray‐dried powder was incorporated with anticaking agent. MSI was carried out and the behavior was determined by fitting the data into Guggenheim–Anderson–de Boer (GAB) model. Prediction of shelf life was studied by considering the critical moisture content (X c), which is the moisture content of powder that undergoes transition changed. The outcome of this work was expected to be beneficial to food powder industry to comprehend the protective effect of anticaking agents as a functional additive. Production of anticaking agent treated spray‐dried soursop powder was expected to broaden its potential applications as functional ingredient.