Comparative Study of the Characterisation and Extraction Techniques of Polyphenolic Compounds from Acacia seyal gum

Abstract Acacia seyal gum is an abundant source of natural polyphenolic compounds (NPPCs) and antioxidant activity with numerous benefits and is often used in cancer treatment. The type of extraction technique can significantly impact the yield and isolation of NPPCs from Acacia seyal gum (ASG). The traditional use of maceration extraction reportedly yields fewer NPPCs. Objectives This study investigates five extraction techniques for NPPCs and ASG antioxidant activity, namely: homogenisation, shaking, ultrasonication, magnetic stirring, and maceration. Materials and Methods The evaluation of the antioxidant activity (AoA) of the extracted NPPCs from ASG used five assays, namely: Total Flavonoids Content (TFC), Folin-Ciocalteu index (FCI), 2,2-Diphenyl-1-Picrylhydrazyl radical scavenging activity (DPPH), Ferric Reducing Antioxidant Power (FRAP), and Cupric Reducing Antioxidant Capacity (CUPRAC). Results To minimise the dataset dimensionality requires Principal Component Analysis. The ultrasonic and maceration techniques were the best techniques to extract NPPCs and examine the AoA of ASG, with a high correlation between the NPPCs and AoA. However, the maceration process was slow (12 h) compared to ultrasonication (1 h). Slow extraction can result in a decline of the NPPCs due to polyphenol oxidase-enzyme and impact productivity. Conclusions These findings provide an essential guide for the choice of extraction techniques for the effective extraction of NPPCs from ASG and other plant materials.

Optimization of Ultrasound-Assisted Extraction of Bioactive Compounds from Acacia Seyal Gum Using Response Surface Methodology and Their Chemical Content Identification by Raman, FTIR, and GC-TOFMS

Acacia Seyal gum (ASG), also known as gum Arabic, is an antioxidant-rich soluble fiber. ASG has been reported to have many biological activities, including anticancer, antidiabetic, antiulcer, and immunomodulatory activity. Extraction of bioactive compounds from ASG is commonly performed using conventional extraction methods. However, these techniques have certain limitation in terms of extraction time, energy, and solvent requirements. Ultrasound-assisted extraction (UAE) could be used as an alternative technique to extract bioactive compounds in less time, at low temperature, and with less energy and solvent requirements. In this study, the UAE extraction of ASG was optimized using response surface methodology (RSM). A face-centered central composite design (FCCCD) was used to monitor the effect of different independent factors of ultrasound operation (sonication time, temperature, and solvent ratio) on ASG extraction yield. In addition, screening and characterization of phytochemicals in 60% ethanol ASG extract was carried out using Raman microscopy, Fourier transform infrared spectroscopy (FTIR), and gas chromatography time-of-flight mass spectroscopy (GC-TOFMS) analysis. The results indicated that, under optimal conditions (extraction time 45 min, extraction temperature 40 °C, and solid–liquid ratio of 1:25 g/mL), the yield of ASG was 75.87% ± 0.10. This yield was reasonably close to the predicted yield of 75.39% suggested by the design of experiment. The ANOVA revealed that the model was highly significant due to the low probability value (p < 0.0001). Raman spectrum fingerprint detected polysaccharides, such as galactose and glucose, and protein like lysine and proline, while FTIR spectrum revealed the presence of functional groups peaks value of alkanes, aldehydes, aliphatic amines, and phenol. GC-TOFMS spectroscopic detected the presence of strong d-galactopyranose, carotenoid, and lycopene antioxidant compounds. In conclusion, this study demonstrated that the UAE technique is an efficient method to achieve a high yield of ASG extracts. The selected model is adequate to optimize the extraction of several chemical compounds reported in this study.

Contribution of some Acacia Species on Carbon Sequestration in Blue Nile State, Sudan

Background: The current challenge is to reduce the uncertainties in obtaining accurate and reliable data of carbon stock changes and emission factors essential for reporting national inventories. Improvements in above ground biomass estimation can also help account for changes in carbon stock in forest areas that may potentially participate in the Reducing emissions from deforestation and forest degradation and other initiatives. Current objectives for such estimates need a unified approach which can be measurable, reportable, and verifiable. This might result to a geographically referenced biomass density database for Sudanese forests that would reduce uncertainties in estimating forest aboveground biomass. The main objective: of this study is to assess potential of some selected forest variables for modeling carbon sequestration for Acacia seyal, vr. Seyal, Acacia seyal, vr. fistula, Acacia Senegal. The specific objectives include development of empirical allometric models for forest biomass estimation, estimation of carbon sequestration for these tree species, estimation of carbon sequestration per hectare and comparing the amount with that reported to the region. A total of 10 sample trees for biomass and carbon determination were selected for each of the three species from El Nour Natural Forest Reserve of the Blue Nile State, Sudan. Data of diameter at breast height, total tree height, tree crown diameter, crown height, and upper stem diameters were measured. Then sample trees were felled and sectioned to their components, and weighed. Subsamples were selected from each component for oven drying at 105 ˚C. Finally allometric models were developed and the aboveground dry weight (dwt) and carbon sequestered per hector were calculated. The results: presents biomass equations, biomass expansion factor and wood density that developed for the trees. In case of inventoried wood volume, corrections for biomass expansion factor and wood density value were done, and new values are suggested for use to convert wood volume to biomass estimates. The results also, indicate that diameter at breast height, crown diameter and tree height are good predictors for estimation of tree dwt and carbon stock. Conclusion: The developed allometric equations in this study gave better estimation of dwt than default value. The average carbon stock was found to be 22.57 t/ha.

Role of Acacia seyal on Selected Soil Properties and Sorghum Growth and Yield: A Case Study of Guba Lafto District, North Wollo, Ethiopia

Acacia seyal is one of the multipurpose parkland agroforestry tree species in eastern and southern Africa. It is a common on-farm tree in the Rift Valley of Ethiopia, but information is limited on its effect on soil properties and sorghum growth and yield. The study was conducted to evaluate its effect on selected soil properties and sorghum growth and yield in Guba Lafto district of northern Ethiopia. Six isolated and closely comparable Acacia seyal trees growing on sorghum farms were purposely selected, and plots were marked under the canopy of trees with three radial distances (0–2 m, 2–4 m, and 4–6 m) and one outside of the tree canopy (10 m away from any tree). Soil samples from each distance zone were taken between 0–20 cm and 20–40 cm soil depths for soil property analysis. Four quadrates with 1 m2 at each distance zone in four directions were laid for sorghum growth and yield attribute valuation. The results showed that only total nitrogen (TN) was significantly higher ( P < 0.05 ) at the subsoil layer under the canopy compared to an open area, while other selected soil parameters were not affected by the tree species. Sorghum biomass yield ( P = 0.006 ) and grain yield ( P = 0.025 ) were significantly lower under the canopy of the trees than in the open area. Generally, Acacia seyal had little effect in improving soil properties and showed a negative effect on sorghum yield and growth. Further research on its effect under wide area coverage of parkland system should be performed to bring a radical shift on the intercropping farming system.

Antidepressant effect of methanol root bark extract of Acacia seyal Del. (Fabaceae): Possible involvement of the inflammatory pathway

Purpose: To study the involvement of inflammatory pathways in the antidepressant activity of Acacia seyal in mice.Methods: The median lethal dose (LD50) of the extract Acacia seyal (AS) was determined using OECD guideline 425. The antidepressant activity of AS was assessed against BCG (0.2 mg/kg, ip)-induced depression in mice using Tail suspension test (TST) and open field test (OFT) at 4, 24 and 48 hours post BCG administration.Results: The median lethal dose (LD50) for the extract was > 5000 mg/kg orally. The extract AS at all tested doses (250 – 1000 mg/kg) significantly (p ≤ 0.001) decreased the duration of immobility in TST but increased the number of line crossing in OFT post-BCG.Conclusion: The antidepressant activity of the methanol root bark extract of Acacia seyal in mice may involve an inflammatory mechanism. Thus, the extract of Acacia seyal may be suitable for the management of depression in humans resistant to other conventional antidepressant agents. However, further studies are required to ascertain this Keywords: Depression, Acacia seyal, Tail suspension test, Open field test, Bacillus Calmette-Guerin