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Run Production Module Pipeline

Source: R/run_production_module.R
run_production_module.Rd

Calculates cohort-level production outputs over the assessment period by combining cohort-level herd structure inputs with herd-level production parameters. The function returns milk, fibre, and meat outputs for each cohort.

Usage

run_production_module(
  cohort_level_data,
  herd_level_data,
  simulation_duration = 365,
  show_indicator = TRUE
)

Arguments

cohort_level_data

data.table. Cohort-level input table (one row per herd-cohort) with the following data requirement:

herd_id

Character. Unique identifier for the herd, repeated for each cohort belonging to the same herd.

cohort_short

Character. Sex- and age-specific cohort code describing the production stage of the animals. Supported values include:

  • FA: adult females (from age at first parturition)

  • FS: sub-adult females (from weaning to age at first parturition)

  • FJ: juvenile females (from birth to weaning)

  • MA: adult males (from age at first breeding)

  • MS: sub-adult males (from weaning to age at first breeding)

  • MJ: juvenile males (from birth to weaning)

cohort_stock_size

Numeric. Average population size in each of the 6 sex–age cohorts (# heads). (cohorts=FJ, FS, FA, MJ, MS, MA).

offtake_heads_assessment

Numeric. Total number of animals removed via offtake over the assessment period, aggregated to 6 sex–age cohorts (heads/assessment period) (cohorts = FJ, FS, FA, MJ, MS, MA).

live_weight_cohort_at_slaughter

Numeric. Live weight at slaughter for animals removed from the cohort (kg).

herd_level_data

data.table. Herd-level input table (one row per herd_id) with the following data requirement:

herd_id

Character. Unique identifier for the herd, repeated for each cohort belonging to the same herd.

species_short

Character. Code identifying the livestock species. Supported values include:

  • PGS: pigs

  • CML: camels

  • CTL: cattle

  • BFL: buffalo

  • SHP: sheep

  • GTS: goats

milk_yield_day

Numeric. Average milk yield per milk-producing animal during the assessment duration (kg/head/day). This value is calculated as the total quantity of milk produced for human consumption by milk-producing animals during the assessment period, divided by the number of milk-producing animals, and the length of the assessment period (days). Required only for species = CML, CTL, BFL, SHP, and GTS.

lactating_females_fraction

Numeric. Proportion of adult females that are lactating during the assessment period (fraction). Required only for species: CML, CTL, BFL, SHP, and GTS.

milk_protein_fraction

Numeric. Milk protein fraction (kg protein/kg milk). Required only for species = CML, CTL, BFL, SHP, and GTS.

milk_fat_fraction

Numeric. Milk fat fraction (kg fat/kg milk). Required only for species = CML, CTL, BFL, SHP, and GTS.

milk_lactose_fraction

Numeric. Milk lactose fraction (kg lactose/kg milk). Required only for species = CML, CTL, BFL, SHP, and GTS.

milk_protein_fraction_standard

Numeric. Standard protein content of milk, used to calculate Fat-protein-corrected milk (FPCM), (kg protein/kg milk). Suggested value = 0.033.

milk_fat_fraction_standard

Numeric. Standard fat content of milk, used to calculate Fat-protein-corrected milk (FPCM), (kg fat/kg milk). Suggested value = 0.04.

milk_lactose_fraction_standard

Numeric. Standard lactose content of milk, used to calculate Fat-protein-corrected milk (FPCM), (kg lactose/kg milk). Suggested value = 0.048.

fibre_yield_year

Numeric. Annual production yield of fibre, such as wool, cashmere, mohair (kg/head/year). Required only for species = CML, SHP, and GTS.

carcass_dressing_fraction

Numeric. Ratio of a slaughtered animal's carcass weight to its live weight (fraction).

bone_free_meat_fraction

Numeric. Ratio of bone-free-meat to carcass weight (fraction).

meat_protein_fraction

Numeric. Protein content of bone-free-meat (kg protein/kg bone-free-meat).

simulation_duration

Numeric. Length of the assessment period (days).

show_indicator

Logical. Whether to display progress indicators during simulation. Defaults to TRUE.

Value

A data.table with the original cohort-level input columns plus the following new variables:

milk_production_mass_cohort

Numeric. Total milk production produced over the assessment period (kg/cohort/assessment period).

milk_production_protein_cohort

Numeric. Total milk protein production produced over the assessment period (kg protein/cohort/assessment period).

milk_production_fpcm_cohort

Numeric. Total fat-protein-corrected milk (FPCM) produced over the assessment period (kg/cohort/assessment period).

fibre_production_cohort

Numeric. Total fibre produced over the assessment period by cohort (kg /cohort/assessment period).

meat_production_live_weight_cohort

Numeric . Total meat produced as live weight over the assessment period by cohort (kg/cohort/assessment period).

meat_production_carcass_weight_cohort

Numeric. Total meat as carcass weight (excluding organs, and other by-products after dressing) produced over the assessment period by cohort (kg/cohort/assessment period).

meat_production_bone_free_meat_cohort

Numeric. Total bone-free-meat (excluding bones, organs, and other by-products after dressing and bone removal) produced over the assessment period by cohort (kg/cohort/assessment period).

meat_production_protein_cohort

Numeric. Total meat protein (excluding bones, organs, and other by-products after dressing and bone removal) produced over the assessment period by cohort (kg protein/cohort/assessment period).

Details

This function represents the intermediate module of the Global Livestock Environmental Assessment Model (GLEAM) computational pipeline run_gleam() to estimate meat, milk and fibre production outputs from livestock and performs the following calculation sequence:

  1. Milk outputs are computed using calc_milk_production

  2. Fibre outputs are computed using calc_fibre_production

  3. Meat outputs are computed using calc_meat_production

For species/cohorts where milk or fibre production is not applicable, outputs are returned as zero.

See also

run_gleam, calc_milk_production, calc_fibre_production, calc_meat_production

Examples

# \donttest{
# Load production inputs (cohort and herd-level)
production_chrt_dt <- data.table::fread(system.file(
  "extdata/run_modules_examples/production_input_chrt_data.csv",
  package = "gleam"
))
production_hrd_dt <- data.table::fread(system.file(
  "extdata/run_modules_examples/production_input_hrd_data.csv",
  package = "gleam"
))

# Run production calculations
results <- run_production_module(
  cohort_level_data = production_chrt_dt,
  herd_level_data = production_hrd_dt,
  simulation_duration = 365
)
#> 🕒 Calculating production (milk, fibre, meat), please wait…
#> ✔ Production cohort calculations completed.
# }