Browsing by Author "Richard, Upendo"

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    Antimicrobial activities and phytochemical analysis of extracts from Ormocarpum trichocarpum (Taub.) and Euclea divinorum (Hiern) used as traditional medicines inTanzania
    (Tanzania Health Research Users Trust Fund, 2019) Kilonzo, Mhuji; Rubanza, Chrispinus; Richard, Upendo; Sangiwa, Gidion
    Background: Medicinal plants have been of great value to human healthcare in most parts of the world for thousands of years. In Tanzania, over 12,000 species of higher plants have been reported, and about 10% are estimated to be used as medicines to treat different human health conditions. The present study aimed to determine in vitro antimicrobial activities and phytochemical analysis of Ormocarpum trichocarpum and Euclea divinorum which are commonly used as a traditional medicine in Tanzania. Methods: Minimum Inhibitory Concentration (MIC) of plants extracts against tested bacterial and fungal species were determined using 96 wells microdilution method. In this method, 50 μL of nutrient and saboraud’s dextrose broth for bacteria and fungus respectively were loaded in each well followed by 50 μL of extract to make final volume of 100 μL. Subsequently 50 μL were transferred from first rows of each well to the second rows and the process was repeated down the columns to the last wells from which 50 μL were discarded. Thereafter, 50 μL of the selected bacterial and fungal suspension was added to each well thus making final volume of 100μL. The lowest concentration which showed no microbe growth was considered as MIC. The study also evaluated phytochemical compounds present in the ethyl acetate extracts from O. trichocarpum stem bark and E. divinorum root bark extract using Gas Chromatography-Mass Spectrometry (GC-MS) technique. Results: It was revealed that 66% of the tested microbes were susceptible to plant extracts at MIC value of 0.39 mg/mL whereas 83% being susceptible to extracts at MIC value of 0.781 mg/mL. Interestingly, four out of 18 tested plant extracts exhibited high antifungal activity below that of the standard antifungal drug, fluconazole. The GC-MS analysis revealed the presence of various low molecular weight phytochemicals which belongs to six groups of secondary metabolites namely dieterpenes, alphatic hydrocarbons, tetraterpenes, sesquiterpenes, steroid and triterpenes. Conclusion: It was concluded that the presence of various phytochemicals in the tested plant extracts may be associated with pharmacological properties of O. trichocarpum and E. divinorum and therefore justifying ethnomedical usage of such plants.
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    Influence of elevation gradient and plant species composition on soil organic carbon in Mount Rungwe Forest Reserve, Tanzania
    (Elsevier BV, 2023) Mauki, Dickson; Richard, Upendo; Kilonzo, Mhuji
    This study was conducted at Mount Rungwe Forest Reserve, Mbeya, Tanzania, East Africa to investigate the influence of elevation gradients and vegetation composition on soil organic carbon. Elevation gradients were established through three elevation grids, the higher, mid and lower elevation. We hypothesized that soil organic carbon would be richer in high plant diversity than in low plant diversity gradients. Findings from this study observed that, low elevation had high moisture content (47.72 ± 1.49) and % soil organic carbon (4.02 ± 0.56) with low bulk density (1.03 ± 0.001) and soil pH (5.96 ± 0.06). However, only moisture content, bulk density, organic matter and sand content were statistically different across elevation gradients. It was also observed the proportional decreases in diversity as elevation increases with both Shannon and Simpson index of diversity indicating higher species diversity at lower elevations (3.62 and 0.03 respectively). Results from two multiple linear regression models indicated that moisture contents, plant abundance and species diversity explained the most variation in soil organic matter across an elevation gradient with R2 = 0.4063, F (3, 38) = 8.67, p = 0.0002 and R2 = 0.3510, F (2, 39) = 10.55, p < 0.0001 for model 1 (tree abundance) and model 2 (tree diversity) respectively.