> tobacco<- read.csv(file.choose(), header=TRUE)
> tobacco.mod=aov(Activity~Treatment+factor(Tobacco), data=tobacco)
> anova(tobacco.mod)
Analysis of Variance Table

Response: Activity
                Df Sum Sq Mean Sq F value    Pr(>F)
Treatment        2  58570 29284.9 112.478 2.804e-12 ***
factor(Tobacco)  2  19684  9841.8  37.801 7.632e-08 ***
Residuals       22   5728   260.4
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> TukeyHSD(tobacco.mod)
  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = Activity ~ Treatment + factor(Tobacco), data = tobacco)

$Treatment
                       diff        lwr      upr     p adj
TMV-Noninfected  101.000000   81.89216 120.1078 0.0000000
TRSV-Noninfected   4.555556  -14.55229  23.6634 0.8221412
TRSV-TMV         -96.444444 -115.55229 -77.3366 0.0000000

$`factor(Tobacco)`
                       diff       lwr       upr     p adj
Strain_B-Strain_A -31.44444 -50.55229 -12.33660 0.0012165
Strain_C-Strain_A  34.66667  15.55882  53.77451 0.0004373
Strain_C-Strain_B  66.11111  47.00327  85.21895 0.0000000