process_tdl_cycle_polynomial: Process TDL cycles using a polynomial correction method

In PhotoGEA: Photosynthetic Gas Exchange Analysis

Process TDL cycles using a polynomial correction method

Description

Uses the 12C and 13C signal from the calibration lines of a tunable diode laser (TDL) to determine correction factors and apply them to the sample lines. Applicable for a system with two or more reference tanks whose 12C and 13C concentrations are known beforehand.

Usage

  process_tdl_cycle_polynomial(
    tdl_cycle,
    poly_order,
    reference_tanks,
    reference_tank_time_points = NA,
    valve_column_name = 'valve_number',
    raw_12c_colname = 'Conc12C_Avg',
    raw_13c_colname = 'Conc13C_Avg'
  )

Arguments

tdl_cycle	An exdf object representing one cycle of TDL data.
poly_order	The order of the polynomial to fit, where 1 indicates a linear fit, 2 indicates a quadratic fit, etc. This argument will be passed to stats::poly during the fitting procedure.
reference_tanks	A list where each element is a list with three named elements: valve, conc_12C, and conc_13C. valve should indicate the valve number for the reference tank, and the other two elements should indicate the known concentrations of 12C and 13C in the tank.
reference_tank_time_points	Either NA or a list where each element is a list with three named elements: valve, start, and end. valve should indicate the valve number for a reference tank, and the other two elements should indicate the first and last time points where the measurements from this valve should be averaged. The order of valves must be the same as in the reference_tanks input argument.
valve_column_name	The name of the column in tdl_cycle that contains the valve number.
raw_12c_colname	The name of the column in tdl_cycle that contains the 12C signal.
raw_13c_colname	The name of the column in tdl_cycle that contains the 13C signal.

Details

This function applies a simple correction to the measured values of 12C and 13C. This correction is based on the fact that each reference tank has both a true concentration (which is known beforehand) and a measured concentration (from the TDL) of each isotope. Using this information, it is possible to perform a polynomial fit of true vs. measured concentrations; in other words, it is possible to identify a polynomial function that determines true concentrations from measured ones. This function can then be applied to tanks whose concentration is not known beforehand; in this case, it provides an estimate of the true concentration, otherwise referred to as a calibrated value.

When making dynamic TDL measurements, concentrations from some of the reference valves may be logged at multiple time points. In this case, it is typical to take an average value from a subset of them. process_tdl_cycle_polynomial can handle this situation when its reference_tank_time_points input argument is not NA.

This function assumes that tdl_cycle represents a single TDL measurement cycle. To process multiple cycles at once, this function is often used along with by.exdf and consolidate.

Value

A list with two elements:

• tdl_data: An exdf object containing the original content of tdl_cycle and several new columns: 'calibrated_12c', 'calibrated_13c', 'total_CO2', and 'delta_C13'.

• calibration_parameters: An exdf object describing the fitted polynomial coefficients.

Examples

# Example 1: An example of a `reference_tank_time_points` list for a situation
# where there are just two reference valves (1 and 3)
reference_tank_time_points <- list(
  list(valve = 1, start = 101, end = 300), # Take an average of time points 101 - 300 for valve 1
  list(valve = 3, start = 201, end = 300)  # Take an average of time points 201 - 300 for valve 3
)

# Example2 : reading a TDL file that is included with the PhotoGEA package,
# identifying its measurement cycles, and then processing them.
tdl_file <- read_gasex_file(
  PhotoGEA_example_file_path('tdl_sampling_1.dat'),
  'TIMESTAMP'
)

# This is a large file; for this example, we will truncate to just the first
# 200 rows so it runs faster
tdl_file <- tdl_file[seq_len(200), , TRUE]

# Identify TDL cycles
tdl_file <- identify_tdl_cycles(
  tdl_file,
  valve_column_name = 'valve_number',
  cycle_start_valve = 20,
  expected_cycle_length_minutes = 2.7,
  expected_cycle_num_valves = 9,
  timestamp_colname = 'TIMESTAMP'
)

# Process TDL cycles; note that the reference tank concentrations used in this
# example are not accurate, so the results are not meaningful
processed_tdl <- consolidate(by(
  tdl_file,
  tdl_file[, 'cycle_num'],
  process_tdl_cycle_polynomial,
  poly_order = 1,
  reference_tanks = list(
    list(valve = 23, conc_12C = 70.37507124, conc_13C = 0.754892652),
    list(valve = 26, conc_12C = 491.1854149, conc_13C = 5.269599965)
  )
))

# The output is a list of two exdf objects
names(processed_tdl)

# The calibration parameters include the coefficients of the polynomial fit for
# each cycle
colnames(processed_tdl$calibration_parameters)

# The processed TDL data includes new columns for the calibrated CO2
# concentrations
colnames(processed_tdl$tdl_data)

PhotoGEA documentation built on April 11, 2025, 5:48 p.m.