Proximate composition of some agricultural wastes in Nigeria and their potential use in activated carbon production

The proximate composition of five agricultural wastes were determined and latter subjected to low temperature conversion process in the presence of nitrogen atmosphere.These agricultural wastes are Cocos nucifera husk, Theobroma cacao pod, Kola nitida pods and Plantago major peels(ripe and unripe peels). All the samples investigated have different intrinsic proximate compositions which affect the yields of their respective chars. Out of the sample investigated, Cocos nucifera husk recorded the lowest bulk density (0.0746g/cm3), ash content(3.95%),cellulose contents(0.52%) and has the lowest char yields.On the other hand ,Theobroma cacao pods recorded the highest cellulose content(41.92%),ash contents(12.67%), crude fiber content(33.60%) and has appreciably high char yields. The lignin contents of samples fell in the range of (6.06%-33.60%).The percentages of chars obtained after conversion at 420\ub0C for each of the precursors were relatively lower to those obtained at 360\ub0C.The percentage yield for all the samples fell within the range of 46 - 64% for 360\ub0C and 43 - 58% for 420\ub0C. Hence,because of their high carbon yields and their inherent compositions ,they can serve as precursors for activated carbon production. @ JASE

Heat-reflux processing of black peppercorn into bioactive antioxidant oleoresins : A three-functioned Taguchi-based grey relational grading

The focus of this research is to identify the best set of factors that influence the heat-reflux recovery of total phenolic content and antioxidant activities under multiple quality characteristics. Parametric Taguchi L9 orthogonal design and grey relational analysis technique were used to investigate the effect of three variables—reflux duration, particle size, and feed-to-solvent ratio on the multiple responses of total phenolic contents, DPPH, and H2O2 activities. According to the grey relational grades response table, the ideal number of criteria for the heat reflux results were 120 min of reflux duration, 0.2 mm of particle size, and a feed-solvent ratio of 1:16. The total phenolic content, DPPH, and H2O2 scavenging activities were measured as 35.23 ± 0.004 mgGAE/g d.w, 107.57 ± 0.04 g/mL, and 87.78 ± 0.32 g/mL, respectively. Moreover, with the Levenberg–Marquardt (LM) neural network architecture, the trained network has a mean square error (MSE) of 3.7646E−07 and an R2 of 0.9500 as the training function outcome, indicating a significant predicted endpoint. The confirmatory experimental results show a 41.9 per cent improvement in relation to the predicted values. The results of this study indicated that, optimising the heat reflux process would be an innovative and beneficial approach for preparing bioactive compounds from functional plants, resulting in cost savings while increasing antioxidant capacity and overall phenolic recovery

Proximate composition of some agricultural wastes in Nigeria and their potential use in activated carbon production

The proximate composition of five agricultural wastes were determined and latter subjected to low temperature conversion process in the presence of nitrogen atmosphere.These agricultural wastes are Cocos nucifera husk,Theobroma cacao pod, Kola nitida pods and Plantago major peels(ripe and unripe peels). All the samples investigated have different intrinsic proximate compositions which affect the yields of their respective chars. Out of the sample investigated, Cocos nucifera husk recorded the lowest bulk density (0.0746g/cm3 ), ash content(3.95%),cellulose contents(0.52%) and has the lowest char yields.On the other hand ,Theobroma cacao pods recorded the highest cellulose content(41.92%),ash contents(12.67%), crude fiber content(33.60%) and has appreciably high char yields. The lignin contents of samples fell in the range of (6.06%-33.60%).The percentages of chars obtained after conversion at 4200 C for each of the precursors were relatively lower to those obtained at 3600 C.The percentage yield for all the samples fell within the range of 46 - 64% for 3600 C and 43 - 58% for 4200 C. Hence,because of their high carbon yields and their inherent compositions ,they can serve as precursors for activated carbon productio

EXPERIMENTAL STUDIES AND ARTIFICIAL NEURAL NETWORKS (ANN) MODELING OF MOISTURE ABSORPTION CHARACTERISTICS OF POLYESTER/MOMODICALFIBRE REINFORCED COMPOSITE

Nowadays, there are interests around the world concerning the applicability of natural fibers in polymer composite development fortechnological advancement. Natural fiber inclusion in synthetic polymer is termed partially degradable polymer composite which is considered environmentally friendly and acceptable. However, a notable deficiency is their poor moisture resistance behaviour that degrades their mechanical properties over time. This work therefore investigated the effect of Momodical fiber fractions on the moisture absorption properties ofPolyester/Momodical fiber reinforced composite. The Momodical fibers were alkali treatedto improve the fiber properties. The Polyester/Momodical fiber composite were developed by incorporating the alkali treated Momodical fibers in the weight fraction of 10, 20, 30 and 40 % in polyester resin. Water immersion test was used to evaluate the water absorption characteristics from which the water diffusion mechanisms of the developed composites were established. For the sake of system behaviour prediction and control, Artificial Neural Networks (ANN) was used for modeling and prediction of the moisture gain ofthe Polyester/Momodical reinforced composites. Scanning Electron Microscope (SEM) was used to elucidate the morphology of raw and alkali treated Momodical fiber. The results showed that the water absorption process was diffusion controlled and diffusion mechanisms cut across less Fickian / Fickian behavior for investigated composites. The composite weight gained and percentage water absorption increased with increased immersion time and fiber loading. The moisture diffusivity ranged from 1.98 E – 12 to5.38 E - 12. The ANN structure 2-5-1-1 developed using 'tansig' 'tansig' 'purelin'transfer function showed a high capability and reliability in modeling and prediction of moisture gain observed in the developed composites. The results suggested an outdoor application in desert cooler pad and built material development where the moisture diffusion tendencies could be beneficial and loss of mechanical strength is trivial

EMPIRICAL MODELING OF THIN LAYER DRYING CHARACTERISTICS OF NAUCLEA LATIFOLIA LEAVES

The thin layer drying characteristics of Nauclea latifolia leaves were studied at four drying temperatures of 35, 45, 55 and 65oC and a constant air velocity of 1.5 m/s in a convective dryer. Experimental kinetic data were fitted to four established drying models available in the literature, namely: the Newton, Henderson and Pabis, Page and Logarithmic models. Model parameters were determined by using non-linear regression analysis while the goodness of fit was assessed by the coefficient of determination (R2 ), root mean square error (RMSE) and the standard error (SE). Fick’s diffusion model and Arrhenius-type equation were used to determine the effective diffusivity and activation energy, respectively. The increase in air temperature significantly reduced the drying time of the Nauclea latifolia leaves. Among the models proposed, the Page model was found satisfactory for describing the air-drying kinetics of Nauclea latifolia leaves. The effective diffusivity increases as temperature increases and ranged between 3.3841 E-08 - 1.1202 E-07 m2 /s while the activation energy of diffusion was estimated to be 40.55 kJ/mol. Keywords: Nauclea latifolia leaves, Convective drying, Modeling, Activation energy, Moisture diffusivity

Mathematical modeling of thin layer drying characteristics of Nauclea latifolia leaves

The thin layer drying characteristics of Nauclea latifolia leaves was studied at four drying temperatures of 35, 45,55 and 65oC and constant air velocity of 1.5 m/s in a convective dryer. Experimental kinetic data was fitted to four established drying models available in the literature namely, the Newton, Henderson and Pabis, Page and Logarithmic models. Model parameters were determined by using non-linear regression analysis while the goodness of fit was assessed by coefficient of determination (R2), root mean square error (RMSE) and standard error (SE). Fick’s diffusion model and Arrhenius-type equation were used to determine the effective diffusivity and activation energy respectively. The increase in air temperature significantly reduced the drying time of the Nauclea latifolia leaves. Among the models proposed, the Page model was selected satisfactory for the description of kinetics of air-drying of Nauclea latifolia leaves. The effective diffusivity increases as temperature increases and ranged between 3.3841 E-08 - 1.1202 E-07 m2/s while the activation energy of diffusion was estimated to be 40.55 kJ/mol

Effect of soluble dietary fibres from Bambara groundnut varieties on the stability of orange oil beverage emulsion

Soluble dietary fibres (SDFs) [30% (w/w)] from four varieties of Bambara groundnut (BGN), viz. black-eye, brown-eye,brown and red were used to stabilize orange oil beverage emulsions at 6% (w/w) orange oil. Emulsion stability was studied using Turbiscan MA 2000 and in terms of oil-droplet size characterization. The volume-surface mean diameter (d3,2) and equivalent volume-mean diameter (d4,3) of the four emulsions ranged between 2.68–4.38 µm and 17.09–18.62 µm,respectively. Emulsions stabilized with black-eye-SDF and brown-SDF possessed the least and highest d3,2 and d4,3,respectively. The d3,2 and d4,3 of all four emulsions were significantly (p< 0.05) different. Emulsions were relatively stable to creaming and destabilized mainly by phenomenon involving oil-droplet aggregation. The backscattering flux of the emulsions ranged from 72.9%(brown-SDF stabilized emulsion) to 85.0% (black-eye-SDF stabilized emulsion). All four BGN SDFs greatly indicated their potential in stabilizing beverage emulsions

Drying characteristics of yam slices (Dioscorea rotundata) in a convective hotair dryer: application of ANFIS in the prediction of drying kinetics

This study applied Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict the moisture ratio (MR) during thedrying process of yam slices (Dioscorea rotundata) in a hot air convective dryer. Also the effective diffusivity,activation energy, and rehydration ratio were calculated. The experiments were carried out at three (3) drying airtemperatures (50, 60, and 70�C), air velocities (0.5, 1, and 1.5 m/s), and slice thickness (3, 6, and 9 mm), and theobtained experimental data were used to check the usefulness of ANFIS in the yam drying process. The resultshowed efficient applicability of ANFIS in predicting the MR at any time of the drying process with a correlationvalue (R2) of 0.98226 and root mean square error value (RMSE) of 0.01702 for the testing stage. The effectivediffusivity increased with an increase in air velocity, air temperature, and thickness and the values (6.382E -09 to1.641E -07 m2/s). The activation energy increased with an increase in air velocity, butfluctuate within the airtemperatures and thickness used (10.59–54.93 KJ/mol). Rehydration ratio was highest at air velocity�air tem-perature�thickness (1.5 m/s�70�C�3 mm), and lowest at air velocity�air temperature�thickness (0.5 m/s�70�C�3 mm). The result showed that the drying kinetics ofDioscorea rotundataexisted in the falling rateperiod. The drying time decreased with increased temperature, air velocity, and decreased slice thickness. Theseestablished results are applicable in process and equipment design, analysis and prediction of hot air convectivedrying of yam (Dioscorea rotundata) slices

Rheological Properties of Sunflower Oil-in-Water Emulsion Containing Vinegar, Stabilized with Gelatinized Bambara Groundnut Flour

The influence of vinegar concentrations on the rheological properties of 40% (w/w)sunflower oil-in-water emulsions stabilized with 7% (w/w) gelatinized bambara groundnut flour (BGNF) was investigated. The rheological properties of interest were steady shear, time dependent and viscoelastic characteristics. Rheological characterizations of the emulsions were carried out using a shear rate controlled rheometer. Both emulsions with and without vinegar were pseudoplastic, thixotropic and viscoelastic fluids. Vinegar however, significantly (p < 0.05) affected rheological properties of BGNF-stabilized emulsion. Vinegar in the emulsion decreased extent of thixotropy, pseudo plasticity and viscoelasticity of BGNF-stabilized emulsions. The results indicated that the rheological properties of BGNF-stabilized emulsion can be controlled and manipulated using vinegar however, the presence of vinegar in BGNF-stabilized emulsion may be deleterious to the emulsion. The result provided the information to understand the influence of vinegar on the rheological properties of BGNF-stabilized emulsions for product and process development