Call apply-like function on each row of dataframe with multiple arguments from each row

I have a dataframe with multiple columns. For each row in the dataframe, I want to call a function on the row, and the input of the function is using multiple columns from that row. For example, let’s say I have this data and this testFunc which accepts two args:

> df <- data.frame(x=c(1,2), y=c(3,4), z=c(5,6))
> df
  x y z
1 1 3 5
2 2 4 6
> testFunc <- function(a, b) a + b

Let’s say I want to apply this testFunc to columns x and z. So, for row 1 I want 1+5, and for row 2 I want 2 + 6. Is there a way to do this without writing a for loop, maybe with the apply function family?

I tried this:

> df[,c('x','z')]
  x z
1 1 5
2 2 6
> lapply(df[,c('x','z')], testFunc)
Error in a + b : 'b' is missing

But got error, any ideas?

EDIT: the actual function I want to call is not a simple sum, but it is power.t.test. I used a+b just for example purposes. The end goal is to be able to do something like this (written in pseudocode):

df = data.frame(
    delta=c(delta_values), 
    power=c(power_values), 
    sig.level=c(sig.level_values)
)

lapply(df, power.t.test(delta_from_each_row_of_df, 
                        power_from_each_row_of_df, 
                        sig.level_from_each_row_of_df
))

where the result is a vector of outputs for power.t.test for each row of df.