Skip to contents

Dairy Cattle Environmental Impact

Easy_Example.Rmd

Getting Started with a Basic Assessment

This guide will walk you through a Basic Assessment for Mature Dairy Cattle in Spain (2015). We will use a single regional identifier to link your census data to nutritional requirements and environmental impact.

Note on File Locations: All files are located in the user_data/ folder.

📂 Folder Structure

  • User Files (Update these): livestock_census.csv, diet_profiles.csv, diet_ingredients.csv, livestock_definitions.csv, livestock_weights.csv, manure_management.csv.
  • In case of usage of the automatic cycle: reproduction_parameters.csv
  • Reference Files (Expert use only): feed_characteristics.csv, forage_yields.csv, mapping.csv, fao_crop_yields.csv, ipcc_coefficients.csv, ipcc_mm.csv.

Step 1: The Census

Open livestock_census.csv. This is where you define who is on the farm. For this basic example, we focus on a national level.

animal_tag region subregion class_flex population
mature_dairy_cattle spain 848686

Step 2: Designing the Diet

The diet must be fulfilled manually based on nutritional reports (e.g., Informe Zootécnico 2015).

A. Check Ingredients

Open feed_characteristics.csv to see the list of available feed items. If you wish, you can add as many new ingredients as you want, always fulfilling all columns.

B. Define the Profile (diet.csv)

diet_tag region forage concentrate milk milk_replacer
diet_dairy_mature spain 60 40 0 0

C. Ingredient Breakdown (diet_ingredients.csv)

Put the same diet_tag and region as many times as ingredients the diet has. * Important: The % for ingredients must sum 100% within their category (e.g., if you have 50% Barley and 50% Corn, they sum to 100% of the “Concentrate” portion).

Step 3: Animal Categories and Coefficients

Open livestock_definitions.csv. This file links your animal to the IPCC equations. Use the exact descriptions from ipcc_coefficients.csv.

animal_tag region diet_tag c_pregnancy milk_yield fat_content
mature_dairy_cattle spain diet_dairy_mature cattle and buffalo 8894.38 3.73

Step 4: Body Weights

Open weights.csv. Ensure the keys match the census exactly.

animal_tag region adult_weight weight_gain average_weight
mature_dairy_cattle spain 675 0 675

Step 5: Manure Management (manure_management.csv)

  1. Check ipcc_mm.csv for valid management_system and system_climate names (You can also check the section X of this documentation).
  2. If you have more than one system for the exactly same animal, duplicate the row and split the allocation.
animal_tag region subregion class_flex system_base management_months system_climate system_subclimate climate_zone system_variant climate_moisture animal_type animal_subtype allocation
mature_dairy_cattle spain liquid_slurry 3 cool temperate wet with_natural_crust_cover wet cattle dairy 0.343
mature_dairy_cattle spain solid_storage temperate dry cattle dairy 0.069

Step 7: Running the Analysis

Once your CSVs are updated, run the following in R:

library(herdr)

results <- generate_impact_assessment(
  automatic_cycle = FALSE)