A statistical analysis project examining the antibacterial efficacy of citronella essential oil (Cymbopogon nardus) against Escherichia coli and Staphylococcus aureus. This study uses SPSS one-way ANOVA and post-hoc testing to evaluate experimental data.
This analysis investigates the potential of citronella essential oil as a natural antimicrobial agent against antibiotic-resistant bacteria. The research was motivated by the global crisis of antimicrobial resistance, where pathogens such as E. coli and S. aureus have developed resistance to conventional antibiotics.
According to the WHO (2020), antimicrobial resistance causes over 700,000 deaths annually, with projections reaching 10 million deaths per year by 2050 if no action is taken. This underscores the urgent need to explore alternative antimicrobial agents derived from natural sources.
Citronella is a tall aromatic grass with documented traditional medicinal uses. Its essential oil contains bioactive compounds such as citronellal, geraniol, and limonene, which have shown promise as antimicrobial agents. Despite traditional knowledge supporting its antibacterial properties, systematic analysis of its efficacy against common pathogenic bacteria remains limited.
- Common cause of urinary tract infections and foodborne illnesses
- Rising antibiotic resistance is a major clinical concern
- Outer membrane acts as a barrier to many antimicrobial compounds
- Common cause of skin infections and pneumonia
- Methicillin-resistant strains (MRSA) pose major healthcare challenges
- Forms biofilms that contribute to persistent infections
The experimental study aimed to:
- Determine the antibacterial activities of citronella essential oil against E. coli and S. aureus
- Assess whether oil concentration affects antibacterial potency (zones of inhibition)
- Compare susceptibility between the two bacterial species
- Evaluate the minimum inhibitory concentration (MIC) at different dilution levels
| Concentration | Test 1 | Test 2 | Mean |
|---|---|---|---|
| Positive Control | 19 mm | 18 mm | 18.5 mm |
| 50% | 15 mm | 15 mm | 15.0 mm |
| 25% | 10 mm | 9 mm | 9.5 mm |
| 12.5% | 9 mm | 8 mm | 8.5 mm |
| Negative Control | – | – | No inhibition |
| Concentration | Test 1 | Test 2 | Mean |
|---|---|---|---|
| Positive Control | 18 mm | 17 mm | 17.5 mm |
| 50% | 13 mm | 12 mm | 12.5 mm |
| 25% | 9 mm | 8 mm | 8.5 mm |
| 12.5% | 8 mm | 7 mm | 7.5 mm |
| Negative Control | – | – | No inhibition |
One-way ANOVA was chosen because:
- It compares means across multiple groups (positive control, 50%, 25%, 12.5%)
- It tests overall significance efficiently, avoiding inflated Type I error from multiple t-tests
- It directly addresses whether concentration affects antibacterial activity
- It allows post-hoc testing (Tukey HSD) to identify specific group differences
- Null Hypothesis (H₀): No significant difference in mean zone of inhibition across concentrations
- Alternative Hypothesis (Hₐ): Significant difference exists in mean zone of inhibition across concentrations
- Citronella oil’s antibacterial potency increases with concentration.
- Each step increase (12.5% → 25% → 50%) produced statistically significant differences.
- S. aureus was consistently more susceptible than E. coli:
- S. aureus (50%): 15.0 mm
- E. coli (50%): 12.5 mm
- This aligns with biological theory: Gram-positive bacteria are more permeable to hydrophobic compounds.
- 50% concentration was most effective.
- 12.5% showed measurable activity but was not significantly different from 25%.
- Practical MIC lies between 12.5% and 25%.
- ANOVA analysis yielded p = 0.000, providing strong evidence that the observed effects are real and reproducible.
This SPSS analysis demonstrates that citronella essential oil exhibits a statistically significant, concentration-dependent antibacterial effect against both E. coli and S. aureus, with greater efficacy against the Gram-positive species. The findings support the hypothesis that citronella oil has therapeutic potential as a natural antimicrobial agent.
- Statistical Analysis Conducted By: Sagambor
- Statistical Software Used: SPSS