cowfootR

# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("juanmarcosmoreno-arch/cowfootR")

library(cowfootR)

# 1. Define system boundaries
boundaries <- set_system_boundaries("farm_gate")

# 2. Calculate emissions by source
enteric <- calc_emissions_enteric(
  n_animals = 100, 
  cattle_category = "dairy_cows",
  boundaries = boundaries
)

manure <- calc_emissions_manure(
  n_cows = 100, 
  boundaries = boundaries
)

soil <- calc_emissions_soil(
  n_fertilizer_synthetic = 1500, 
  n_excreta_pasture = 5000, 
  area_ha = 120,
  boundaries = boundaries
)

energy <- calc_emissions_energy(
  diesel_l = 2000, 
  electricity_kwh = 5000, 
  boundaries = boundaries
)

inputs <- calc_emissions_inputs(
  conc_kg = 1000, 
  fert_n_kg = 500, 
  boundaries = boundaries
)

# 3. Calculate total emissions
total_emissions <- calc_total_emissions(enteric, manure, soil, energy, inputs)
print(paste("Total emissions:", round(total_emissions$total_co2eq, 1), "kg CO2eq"))

# 4. Calculate intensity metrics
milk_intensity <- calc_intensity_litre(
  total_emissions = total_emissions,
  milk_litres = 750000,
  fat = 4.0,
  protein = 3.3
)
print(paste("Milk intensity:", round(milk_intensity$intensity_co2eq_per_kg_fpcm, 2), 
            "kg CO2eq/kg FPCM"))

area_intensity <- calc_intensity_area(
  total_emissions = total_emissions,
  area_total_ha = 120
)
print(paste("Area intensity:", round(area_intensity$intensity_per_total_ha, 1), 
            "kg CO2eq/ha"))

# 1. Download and fill template
cf_download_template("my_farms_template.xlsx")
# Open the file, fill with your farm data, and save

# 2. Read data and process multiple farms
farm_data <- readxl::read_excel("my_farms_data.xlsx")
results <- calc_batch(
  data = farm_data,
  tier = 2,
  benchmark_region = "uruguay"  # optional
)

# 3. View processing summary
print(results$summary)

# 4. Export comprehensive results to Excel
export_hdc_report(results, "carbon_footprint_results.xlsx")

# Example farm data
farm_data <- data.frame(
  FarmID = c("Farm_A", "Farm_B", "Farm_C"),
  Year = c("2023", "2023", "2023"),
  Milk_litres = c(500000, 750000, 300000),
  Fat_percent = c(4.0, 3.8, 4.2),
  Protein_percent = c(3.3, 3.2, 3.4),
  Cows_milking = c(100, 150, 60),
  Area_total_ha = c(200, 300, 120),
  N_fertilizer_kg = c(2000, 3000, 1200),
  Diesel_litres = c(4000, 6000, 2400),
  Electricity_kWh = c(10000, 15000, 6000)
)

# Process all farms
results <- calc_batch(farm_data, tier = 2)

# Check results for each farm
for (i in seq_along(results$farm_results)) {
  farm <- results$farm_results[[i]]
  if (farm$success) {
    cat("Farm", farm$farm_id, ":", round(farm$emissions_total, 1), "kg CO2eq\n")
  } else {
    cat("Farm", farm$farm_id, ": ERROR -", farm$error, "\n")
  }
}

# Farm gate (direct on-farm emissions only)
boundaries_fg <- set_system_boundaries("farm_gate")

# Cradle to farm gate (includes upstream production)
boundaries_cfg <- set_system_boundaries("cradle_to_farm_gate")

# Use in calculations
results <- calc_batch(farm_data, boundaries = boundaries_cfg)

# Process with error handling
results <- calc_batch(farm_data)

# Check for processing errors
if (results$summary$n_farms_with_errors > 0) {
  error_farms <- results$farm_results[
    sapply(results$farm_results, function(x) !x$success)
  ]
  
  for (farm in error_farms) {
    cat("Farm", farm$farm_id, "failed:", farm$error, "\n")
  }
}