The main difference between calc_rate.bg
and calc_rate
, is that this
function allows a rate to be determined from the same region of multiple
oxygen data columns, whereas calc_rate
allows multiple rates to be
determined from different regions of a single dataset.
Units
There are no units involved in calc_rate.bg
. This is a deliberate decision.
The units of oxygen concentration and time will be specified later in
convert_rate()
when rates are converted to specific output units. It is
important however, the background time~oxygen data is in the same time and
oxygen units as the data used to determine the rate which will be adjusted.
Subsetting data regions
calc_rate.bg
does not have internal subsetting of data regions. If you need
to subset the data to specific regions you don't want to use, see
subset_data()
, which allows for easy passing (or piping) of subsets to
calc_rate.bg
.
Background respiration vs background input of oxygen
Most users will be using this function to account for background oxygen
consumption rates from microbial activity that need to be quantified and
their effects removed from experimental specimen rates. However, there are
some experiments where oxygen input rates may be of interest, for example
in open tank or open arena respirometry where the input of oxygen from the
water surface has been calculated or quantified. There are also cases in
closed respirometry where there may be an input of oxygen via leaks or oxygen
production from photosynthesis which need to be quantified. calc_rate.bg
is
readily capable of quantifying production rates as well as consumption, and
these can also be used for adjustments in adjust_rate()
.
Plot
A plot is produced (provided plot = TRUE
) showing all examined columns of
oxygen against time (bottom blue axis) and row index (top red axis), with the
rate and linear model coefficients. Single rates can be plotted by changing
the pos
input either in the main function call, or by plotting the output,
e.g. plot(object, pos = 2)
. Console output messages can be suppressed using
quiet = TRUE
. If equations obscure the plot they can be suppressed using
legend = FALSE
.
S3 Generic Functions
Saved output objects can be used in the generic S3 functions print()
,
summary()
, and mean()
.
print()
: prints all background rates, plus the mean background rate.
summary()
: prints summary table of all results and metadata, or those
specified by the pos
input. e.g. summary(x, pos = 1:5)
. The summary can
be exported as a separate dataframe by passing export = TRUE
.
mean()
: calculates the mean of all rates, or those specified by the pos
input. e.g. mean(x, pos = 1:5)
The mean can be exported as a separate value
by passing export = TRUE
.
More
For additional help, documentation, vignettes, and more visit the respR
website at https://januarharianto.github.io/respR/