Comparison of Box-Behnken, Face Central Composite and Full Factorial Designs in Optimization of Hempseed Oil Extraction by n-Hexane: a Case Study

Statistical multivariate methods like Box-Behnken, face central composite and full factorial designs (BBD, FCCD and FFD, respectively) in combination with the response surface methodology (RSM) were compared when applied in modeling and optimization of the hempseed oil (HSO) extraction by n-hexane. The effects of solvent-to-seed ratio, operation temperature and extraction time on HSO yield were investigated at the solvent-to-seed ratio of 3:1, 6.5:1 or 10:1 mL/g, the extraction temperature of 20, 45 or 70 °C and the extraction time of 5, 10 or 15 min. All three methods were efficient in the statistical modeling and optimization of the influential process variables and led to almost the same optimal process conditions and predicted HSO yield. Having better statistical performances and being economically advantageous over the FFD with repetition, the BBD or FCCD combined with the RSM is recommended for the optimization of liquid-solid extraction processes

Modeling the kinetics of essential oil hydrodistillation from plant materials

The present work deals with modeling the kinetics of essential oils extraction from plant materials by water and steam distillation. The experimental data were obtained by studying the hydrodistillation kinetics of essential oil from juniper berries. The literature data on the kinetics of essential oils hydrodistillation from different plant materials were also included into the modeling. A physical model based on simultaneous washing and diffusion of essential oil from plant materials were developed to describe the kinetics of essential oils hydrodistillation, and two other simpler models were derived from this physical model assuming either instantaneous washing followed by diffusion or diffusion with no washing (i.e. the first-order kinetics). The main goal was to compare these models and suggest the optimum ones for water and steam distillation and for different plant materials. All three models described well the experimental kinetic data on water distillation irrespective of the type of distillation equipment and its scale, the type of plant materials and the operational conditions. The most applicable one is the model involving simultaneous washing and diffusion of the essential oil. However, this model was generally inapplicable for steam distillation of essential oils, except for juniper berries. For this hydrodistillation technique, the pseudo first-order model was shown to be the best one. In a few cases, a variation of the essential oil yield with time was observed to be sigmoidal and was modeled by the Boltzmann sigmoid function

Optimization of expression, purification and HRMS characterization of recombinant N-protein fragment from SARS-CoV-2

Nucleocapsid (N) protein is the most abundant SARS-CoV-2 virus derived protein and strong immunogen which can be used as a component of the immunological tests for the diagnosis of SARS-CoV-2 infection. Recombinant fragment of N-protein (58–419 aa) was expressed in E. coli in a soluble form using developed optimized protocol of expression (16-18h, 37 °C, 0.4 mM IPTG). After lysis of cells, N-protein from soluble fraction of lysate was purified using optimized protocol for purification by immobilized metal affinity chromatography on Ni-Sepharose in two repeated steps under different elution conditions. Obtained fraction of N-protein after the second chromatography was desalted and concentrated using phosphate buffer solution and ultrafiltration. The purity of isolated N-protein was deterrmined by SDS PAGE, while high resolution mass spectrometry was used for its characterization. Isolated N-protein was over 90% purity and identified as the most intense and abundant protein fragment, with PEAKS PTM score of 508 and sequence coverage of over 70%, including 173 unique peptides

Sandwich ELISA for the Quantification of Nucleocapsid Protein of SARS-CoV-2 Based on Polyclonal Antibodies from Two Different Species

In this study, a cost-effective sandwich ELISA test, based on polyclonal antibodies, for routine quantification SARS-CoV-2 nucleocapsid (N) protein was developed. The recombinant N protein was produced and used for the production of mice and rabbit antisera. Polyclonal N protein-specific antibodies served as capture and detection antibodies. The prototype ELISA has LOD 0.93 ng/mL and LOQ 5.3 ng/mL, with a linear range of 1.52–48.83 ng/mL. N protein heat pretreatment (56 °C, 1 h) decreased, while pretreatment with 1% Triton X-100 increased analytical ELISA sensitivity. The diagnostic specificity of ELISA was 100% (95% CI, 91.19–100.00%) and sensitivity was 52.94% (95% CI, 35.13–70.22%) compared to rtRT-PCR (Ct < 40). Profoundly higher sensitivity was obtained using patient samples mostly containing Wuhan-similar variants (Wuhan, alpha, and delta), 62.50% (95% CI, 40.59 to 81.20%), in comparison to samples mostly containing Wuhan-distant variants (Omicron) 30.00% (6.67–65.25%). The developed product has relatively high diagnostic sensitivity in relation to its analytical sensitivity due to the usage of polyclonal antibodies from two species, providing a wide repertoire of antibodies against multiple N protein epitopes. Moreover, the fast, simple, and inexpensive production of polyclonal antibodies, as the most expensive assay components, would result in affordable antigen tests

Decision algorithms in fire detection systems

Analogue (and addressable) fire detection systems enables a new quality in improving sensitivity to real fires and reducing susceptibility to nuisance alarm sources. Different decision algorithms types were developed with intention to improve sensitivity and reduce false alarm occurrence. At the beginning, it was free alarm level adjustment based on preset level. Majority of multi-criteria decision work was based on multi-sensor (multi-signature) decision algorithms - using different type of sensors on the same location or, rather, using different aspects (level and rise) of one sensor measured value. Our idea is to improve sensitivity and reduce false alarm occurrence by forming groups of sensors that work in similar conditions (same world side in the building, same or similar technology or working time). Original multi-criteria decision algorithms based on level, rise and difference of level and rise from group average are discussed in this paper

Using geothermal water for greenhouse heating

On construction with dimensions 15 x 5 x 2 m, conditions of temperature transmission and vegetables growth are examined. We have been cultivating pepper, cucumber, small cucumber, tomato, and lattice. Over ground heating has been used, consisting of one bent pipe with radius of 10 mm, in the shape of hairpin along the both sides of the construction. Underground heating consists of six pipes with radius of 20 mm on the depth of 350-400 mm. There have been measured the temperature inside construction, the temperature outside construction, the waterflow, and water temperature flowing into and out of the construction. The approximate heating flow factor K is determined by both the equation: heating balance equation and basic equation for temperature transmition. Vegetable growth has been watching during the period of time from March to November 2005

Modeling the kinetics of essential oil hydrodistillation from juniper berries (Juniperus communis L.) using non-linear regression

This paper presents kinetics modeling of essential oil hydrodistillation from juniper berries (Juniperus communis L.) by using a non-linear regression methodology. The proposed model has the polynomial-logarithmic form. The initial equation of the proposed non-linear model is q = q∞•(a•(logt)2 + b•logt + c) and by substituting a1=q∞•a, b1 = q∞•b and c1 = q∞•c, the final equation is obtained as q = a1•(logt)2 + b1•logt + c1. In this equation q is the quantity of the obtained oil at time t, while a1, b1 and c1 are parameters to be determined for each sample. From the final equation it can be seen that the key parameter q∞, which presents the maximal oil quantity obtained after infinite time, is already included in parameters a1, b1 and c1. In this way, experimental determination of this parameter is avoided. Using the proposed model with parameters obtained by regression, the values of oil hydrodistillation in time are calculated for each sample and compared to the experimental values. In addition, two kinetic models previously proposed in literature were applied to the same experimental results. The developed model provided better agreements with the experimental values than the two, generally accepted kinetic models of this process. The average values of error measures (RSS, RSE, AIC and MRPD) obtained for our model (0.005; 0.017; –84.33; 1.65) were generally lower than the corresponding values of the other two models (0.025; 0.041; –53.20; 3.89) and (0.0035; 0.015; –86.83; 1.59). Also, parameter estimation for the proposed model was significantly simpler (maximum 2 iterations per sample) using the non-linear regression than that for the existing models (maximum 9 iterations per sample). [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR-35026

Statističko modelovanje i optimizacija proizvodnje biodizela u prisustvu ultrazvuka primenom različitih eksperimentalnih planova

The present study compares the performances of the regression models developed by the response surface methodology combined with the full factorial, Box-Behnken or face central composite designs applied for the ultrasound-assisted KOH-catalyzed methanolysis of sunflower oil. While all models led to similar optimal reaction conditions, the models based on the simpler designs had the smaller corrected Akaike information criterion values, the insignificant lack of fit and the more favorable statistical criteria than the model based on the full factorial design. Including fewer experiments, the Box-Behnken design can be recommended for the optimization of ultrasound-assisted biodiesel production processes.U radu se porede performanse regresionih modela razvijenih na osnovu kombinovanja metodologije površine odziva sa punim faktorijelnim, Boks-Benken-ovim ili centralnim kompozitnim planom kada se primene na ultrazvukom podržanu bazno-katalizovanu metanolizu suncokretovog ulja. Iako su svi modeli dali slične optimalne uslove reakcije, modeli zasnovani na jednostavnijim planovima imali su manje vrednosti Akaike-ovog informacionog kriterijuma, neznačajnu vrednost odstupanja od modela i povoljnije statističke kriterijume u odnosu na model zasnovan na punom faktorijelnim planu. Boks-Benken-ov plan, koji zahteva manji broj eksperimenata, može da se preporuči za optimizaciju proizvodnje biodizela u ultrazvučnom reaktoru

Influence of common juniper berries pretreatment on the essential oil yield, chemical composition and extraction kinetics of classical and microwave assisted hydrodistillation

The present paper dealt with the influence of the common juniper berries pretreatment on the yield, chemical composition and extraction kinetics of juniper essential oil (JEO) obtained by classical (HD) and microwave assisted hydrodistillation (MAHD). The highest JEO yield was obtained by HD from one-minute dry-ground juniper berries (2.23 +/- 0.00 g/100 g). No statistically significant influence of swelling and distillation technique on JEO yield was observed. Therefore, the optimal pretreatment process involved no swelling and one-minute grinding. However, no significant difference in the chemical composition of the JEOs obtained by the two techniques was observed. A new phenomenological kinetic model was developed on the basis of the mechanism of JEO extraction by both HD MAHD, which assumed three simultaneously-occurring stages: washing, unhindered diffusion and hindered diffusion. The main advantage of developed model was its ability to describe the variations of JEO yield and distillation rates with time. Furthermore, it had the smallest mean relative percentage deviation compared to the well-known kinetics models and the parameters that all were statistically significant, so it was recommended for modeling the kinetics of JEO extraction by HD and especially MAHD