# Complete Parameter Reference Guide

This vignette provides a comprehensive reference for all parameters across cowfootR functions, including units, valid options, typical ranges, and data sources. Use this as a technical reference when setting up calculations or troubleshooting data issues.

## Function Overview

cowfootR includes these main calculation functions: - `calc_emissions_enteric()` - Enteric fermentation methane - `calc_emissions_manure()` - Manure management CH4 and N2O
- `calc_emissions_soil()` - Soil N2O emissions - `calc_emissions_energy()` - Energy-related CO2 emissions - `calc_emissions_inputs()` - Purchased input emissions - `calc_total_emissions()` - Aggregation function - `calc_intensity_litre()` - Milk intensity calculations - `calc_intensity_area()` - Area intensity calculations - `calc_batch()` - Batch processing function

## 1. calc_emissions_enteric() Parameters

### Required Parameters

Parameter | Type | Unit | Description | Valid Range | Example
--- | --- | --- | --- | --- | ---
`n_animals` | Numeric | head | Number of animals | > 0 | 100

### Animal Characteristics

Parameter | Type | Unit | Description | Valid Range | Default | Example
--- | --- | --- | --- | --- | --- | ---
`cattle_category` | Character | - | Type of cattle | “dairy_cows”, “heifers”, “calves”, “bulls” | “dairy_cows” | “dairy_cows”
`avg_body_weight` | Numeric | kg | Average live weight | 100-800 | 550 (cows) | 580
`avg_milk_yield` | Numeric | kg/year | Annual milk yield per cow | 1000-15000 | 6000 | 7200

### Production System

Parameter | Type | Unit | Description | Valid Options | Default | Notes
--- | --- | --- | --- | --- | --- | ---
`production_system` | Character | - | System intensity | “intensive”, “extensive”, “mixed” | “mixed” | Affects Tier 1 factors
`dry_matter_intake` | Numeric | kg/day | Daily DM intake per animal | 8-25 (cows) | NULL | Required for accurate Tier 2

### Feed Parameters

Parameter | Type | Unit | Description | Valid Range | Default | Notes
--- | --- | --- | --- | --- | --- | ---
`feed_inputs` | Named list | kg DM/year | Annual feed consumption | > 0 | NULL | Names: grain_dry, grain_wet, ration, byproducts, proteins
`ym_percent` | Numeric | % | Methane conversion factor | 4.0-8.0 | 6.5 | Higher = more CH4 per unit energy

### Methodology Control

Parameter | Type | Unit | Description | Valid Options | Default | Impact
--- | --- | --- | --- | --- | --- | ---
`tier` | Numeric | - | IPCC methodology tier | 1, 2 | 1 | Tier 2 more accurate with detailed data
`emission_factor_ch4` | Numeric | kg CH4/head/year | Custom CH4 factor | 40-150 | NULL | Overrides tier calculations
`gwp_ch4` | Numeric | kg CO2eq/kg CH4 | Global Warming Potential | 25-30 | 27.2 | IPCC AR6 value

## 2. calc_emissions_manure() Parameters

### Required Parameters

Parameter | Type | Unit | Description | Valid Range | Default | Example
--- | --- | --- | --- | --- | --- | ---
`n_cows` | Numeric | head | Total number of animals | > 0 | - | 150

### Manure System

Parameter | Type | Unit | Description | Valid Options | Default | CH4 Impact
--- | --- | --- | --- | --- | --- | ---
`manure_system` | Character | - | Management system type | “pasture”, “solid_storage”, “liquid_storage”, “anaerobic_digester” | “pasture” | High variation
`climate` | Character | - | Climate region | “cold”, “temperate”, “warm” | “temperate” | Affects MCF

### Tier 2 Specific

Parameter | Type | Unit | Description | Valid Range | Default | Required For
--- | --- | --- | --- | --- | --- | ---
`avg_body_weight` | Numeric | kg | Average live weight | 400-700 | 600 | Tier 2 VS calculation
`diet_digestibility` | Numeric | fraction | Diet apparent digestibility | 0.5-0.8 | 0.65 | Tier 2 VS calculation
`retention_days` | Numeric | days | Days manure in system | 10-200 | NULL | System optimization
`system_temperature` | Numeric | °C | Average system temperature | 5-40 | NULL | MCF adjustment

### Nitrogen Management

Parameter | Type | Unit | Description | Valid Range | Default | Impact
--- | --- | --- | --- | --- | --- | ---
`n_excreted` | Numeric | kg N/cow/year | N excretion per cow | 80-150 | 100 | N2O emissions
`ef_n2o_direct` | Numeric | kg N2O-N/kg N | Direct N2O emission factor | 0.005-0.03 | 0.02 | IPCC 2019
`include_indirect` | Logical | - | Include indirect N2O? | TRUE/FALSE | FALSE | +20-30% N2O
`protein_intake_kg` | Numeric | kg/day | Daily protein intake | 1.5-4.0 | NULL | Refines N excretion

## 3. calc_emissions_soil() Parameters

### Nitrogen Inputs

Parameter | Type | Unit | Description | Valid Range | Typical Values | Source
--- | --- | --- | --- | --- | --- | ---
`n_fertilizer_synthetic` | Numeric | kg N/year | Synthetic fertilizer N | 0-5000 | 50-300 kg N/ha | Purchase records
`n_fertilizer_organic` | Numeric | kg N/year | Organic fertilizer N | 0-3000 | 0-100 kg N/ha | Application records
`n_excreta_pasture` | Numeric | kg N/year | N deposited while grazing | 0-20000 | 80-120 kg N/cow/year | Calculated estimate
`n_crop_residues` | Numeric | kg N/year | N in returned crop residues | 0-2000 | 10-50 kg N/ha | Crop management

### Site Conditions

Parameter | Type | Unit | Description | Valid Options | Default | N2O Impact
--- | --- | --- | --- | --- | --- | ---
`soil_type` | Character | - | Soil drainage | “well_drained”, “poorly_drained” | “well_drained” | 50% difference
`climate` | Character | - | Climate classification | “temperate”, “tropical” | “temperate” | 20% difference
`area_ha` | Numeric | hectares | Total farm area | > 0 | NULL | For per-hectare metrics

### Emission Factors

Parameter | Type | Unit | Description | Valid Range | Default | Source
--- | --- | --- | --- | --- | --- | ---
`ef_direct` | Numeric | kg N2O-N/kg N | Direct emission factor | 0.005-0.025 | NULL | IPCC 2019 by soil/climate
`include_indirect` | Logical | - | Include volatilization/leaching | TRUE/FALSE | TRUE | +30-50% total N2O
`gwp_n2o` | Numeric | kg CO2eq/kg N2O | N2O warming potential | 265-300 | 273 | IPCC AR6

## 4. calc_emissions_energy() Parameters

### Fuel Consumption

Parameter | Type | Unit | Description | Typical Range | Default | EF (kg CO2/unit)
--- | --- | --- | --- | --- | --- | ---
`diesel_l` | Numeric | litres/year | Diesel consumption | 2000-15000 | 0 | 2.67
`petrol_l` | Numeric | litres/year | Petrol/gasoline consumption | 500-3000 | 0 | 2.31
`lpg_kg` | Numeric | kg/year | LPG consumption | 100-1000 | 0 | 3.0
`natural_gas_m3` | Numeric | m³/year | Natural gas consumption | 0-5000 | 0 | 2.0
`electricity_kwh` | Numeric | kWh/year | Electricity consumption | 10000-100000 | 0 | Variable by country

### Location and Factors

Parameter | Type | Unit | Description | Valid Options | Default | Notes
--- | --- | --- | --- | --- | --- | ---
`country` | Character | - | Country for grid factors | “UY”, “AR”, “BR”, “NZ”, “US”, “AU”, “DE”, etc. | “UY” | Major impact on electricity EF
`ef_electricity` | Numeric | kg CO2/kWh | Custom electricity factor | 0.05-1.0 | NULL | Overrides country default
`include_upstream` | Logical | - | Include fuel production | TRUE/FALSE | FALSE | +10-15% total

### Grid Emission Factors (Built-in)

Country | Code | EF (kg CO2/kWh) | Source
--- | --- | --- | ---
Uruguay | UY | 0.08 | Clean grid (hydro)
Argentina | AR | 0.35 | Mixed grid
Brazil | BR | 0.12 | Hydro + renewables
New Zealand | NZ | 0.15 | Renewable majority
United States | US | 0.45 | Fossil majority
Australia | AU | 0.75 | Coal dominant

## 5. calc_emissions_inputs() Parameters

### Feed Inputs

Parameter | Type | Unit | Description | Typical Range | Default | EF Range (kg CO2eq/kg)
--- | --- | --- | --- | --- | --- | ---
`conc_kg` | Numeric | kg/year | Concentrate feed | 50000-500000 | 0 | 0.5-1.2
`feed_grain_dry_kg` | Numeric | kg DM/year | Dry grain feeds | 20000-200000 | 0 | 0.3-0.6
`feed_grain_wet_kg` | Numeric | kg DM/year | Wet grain/silage | 10000-100000 | 0 | 0.25-0.45
`feed_ration_kg` | Numeric | kg DM/year | Complete rations | 30000-300000 | 0 | 0.4-0.8
`feed_byproducts_kg` | Numeric | kg DM/year | Feed byproducts | 5000-80000 | 0 | 0.1-0.25
`feed_proteins_kg` | Numeric | kg DM/year | Protein supplements | 5000-50000 | 0 | 1.2-2.8
`feed_corn_kg` | Numeric | kg DM/year | Corn grain specific | 10000-150000 | 0 | 0.35-0.65
`feed_soy_kg` | Numeric | kg DM/year | Soybean meal | 5000-40000 | 0 | 1.5-3.2
`feed_wheat_kg` | Numeric | kg DM/year | Wheat grain | 5000-100000 | 0 | 0.4-0.7

### Other Inputs

Parameter | Type | Unit | Description | Typical Range | Default | EF (kg CO2eq/kg)
--- | --- | --- | --- | --- | --- | ---
`fert_n_kg` | Numeric | kg N/year | Nitrogen fertilizer | 500-5000 | 0 | 5.5-8.5
`plastic_kg` | Numeric | kg/year | Agricultural plastics | 100-1000 | 0 | 1.8-3.8
`transport_km` | Numeric | km | Average transport distance | 50-500 | NULL | 1e-4 kg CO2/kg·km

### Regional Factors

Parameter | Type | Unit | Description | Valid Options | Default | Impact
--- | --- | --- | --- | --- | --- | ---
`region` | Character | - | Regional emission factors | “global”, “EU”, “US”, “Brazil”, “Argentina”, “Australia” | “global” | ±20% variation
`fert_type` | Character | - | Fertilizer type | “urea”, “ammonium_nitrate”, “mixed”, “organic” | “mixed” | ±15% variation
`plastic_type` | Character | - | Plastic type | “LDPE”, “HDPE”, “PP”, “mixed” | “mixed” | ±20% variation

### Advanced Options

Parameter | Type | Unit | Description | Valid Range | Default | Purpose
--- | --- | --- | --- | --- | --- | ---
`include_uncertainty` | Logical | - | Run Monte Carlo analysis | TRUE/FALSE | FALSE | Uncertainty quantification
`ef_conc` | Numeric | kg CO2eq/kg | Override concentrate EF | 0.3-1.5 | NULL | Custom factors
`ef_fert` | Numeric | kg CO2eq/kg N | Override fertilizer EF | 3.0-10.0 | NULL | Local studies
`ef_plastic` | Numeric | kg CO2eq/kg | Override plastic EF | 1.0-5.0 | NULL | Specific materials

## 6. calc_intensity_litre() Parameters

### Required Parameters

Parameter | Type | Unit | Description | Valid Range | Notes
--- | --- | --- | --- | --- | ---
`total_emissions` | Numeric or cf_total | kg CO2eq/year | Total farm emissions | > 0 | From calc_total_emissions()
`milk_litres` | Numeric | litres/year | Annual milk production | > 0 | Farm records

### Milk Composition

Parameter | Type | Unit | Description | Valid Range | Default | Source
--- | --- | --- | --- | --- | --- | ---
`fat` | Numeric | % | Average fat content | 2.5-6.0 | 4.0 | Lab analysis or processor
`protein` | Numeric | % | Average protein content | 2.5-4.5 | 3.3 | Lab analysis or processor
`milk_density` | Numeric | kg/L | Milk density | 1.025-1.035 | 1.03 | Lab measurement

### FPCM Calculation Formula

The Fat and Protein Corrected Milk (FPCM) formula used is:

    FPCM (kg) = milk_kg × (0.1226 × fat% + 0.0776 × protein% + 0.2534)

This standardizes milk to 4.0% fat and 3.3% protein for fair comparison.

## 7. calc_intensity_area() Parameters

### Required Parameters

Parameter | Type | Unit | Description | Valid Range | Notes
--- | --- | --- | --- | --- | ---
`total_emissions` | Numeric or cf_total | kg CO2eq/year | Total farm emissions | > 0 | From calc_total_emissions()
`area_total_ha` | Numeric | hectares | Total farm area | > 0 | Property records

### Area Breakdown

Parameter | Type | Unit | Description | Valid Range | Default | Notes
--- | --- | --- | --- | --- | --- | ---
`area_productive_ha` | Numeric | hectares | Productive/utilized area | ≤ total area | total area | Agricultural use only
`area_breakdown` | Named list | hectares | Detailed land use | > 0 each | NULL | Must sum to total if validate=TRUE

### Valid area_breakdown Names

Valid area_breakdown Names and Descriptions
Name | Description | Typical_Range
--- | --- | ---
pasture_permanent | Permanent grassland | 40-80%
pasture_temporary | Rotational/temporary pasture | 5-20%
crops_feed | Feed crop production | 5-15%
crops_cash | Cash crop production | 0-10%
infrastructure | Buildings, roads, facilities | 2-5%
woodland | Forest/trees | 0-10%
wetlands | Water bodies, wetlands | 0-5%
other | Other non-productive areas | 0-5%

### Validation

Parameter | Type | Unit | Description | Valid Options | Default | Purpose
--- | --- | --- | --- | --- | --- | ---
`validate_area_sum` | Logical | - | Check area breakdown sums | TRUE/FALSE | TRUE | Data quality control

## 8. calc_batch() Parameters

### Data Input

Parameter | Type | Unit | Description | Requirements | Example
--- | --- | --- | --- | --- | ---
`data` | data.frame | - | Farm data with template columns | See template structure | farm_data

### Template Column Requirements

Template Structure (First 15 columns)
Column_Group | Column_Name | Data_Type | Required
--- | --- | --- | ---
Identification | FarmID | character | Yes
Identification | Year | character | No
Production | Milk_litres | numeric | Yes
Production | Fat_percent | numeric | No
Production | Protein_percent | numeric | No
Production | Milk_density | numeric | No
Herd_Composition | Cows_milking | numeric | Yes
Herd_Composition | Cows_dry | numeric | No
Herd_Composition | Heifers_total | numeric | No
Herd_Composition | Calves_total | numeric | No
Herd_Composition | Bulls_total | numeric | No
Animal_Weights | Body_weight_cows_kg | numeric | No
Animal_Weights | Body_weight_heifers_kg | numeric | No
Animal_Weights | Body_weight_calves_kg | numeric | No
Animal_Weights | Body_weight_bulls_kg | numeric | No

### Processing Options

Parameter | Type | Unit | Description | Valid Options | Default | Impact
--- | --- | --- | --- | --- | --- | ---
`tier` | Numeric | - | IPCC methodology tier | 1, 2 | 2 | Accuracy vs data requirements
`boundaries` | boundaries object | - | System boundaries | From set_system_boundaries() | “farm_gate” | Scope of assessment
`benchmark_region` | Character | - | Regional comparison | “uruguay”, “argentina”, etc. | NULL | Performance context
`save_detailed_objects` | Logical | - | Store detailed results | TRUE/FALSE | FALSE | For debugging/analysis

## 9. Parameter Validation and Quality Control

### Automatic Validations

Built-in Validation Rules
Parameter_Type | Validation_Rules | Error_Actions | User_Guidance
--- | --- | --- | ---
Animal Numbers | Must be positive integers | Stop execution with error message | Check data entry and farm records
Production Metrics | Milk yield 1000-15000 kg/cow/year | Warning with guidance on typical ranges | Verify annual vs daily units
Area Data | Area breakdown must sum to total (if validate=TRUE) | Stop or warn based on validate_area_sum setting | Review land use classification
Input Quantities | All quantities ≥ 0 | Stop with error message | Check for data entry errors
Ratios | Stocking rate 0.1-3.0 cows/ha | Warning about unusual values | Confirm farm characteristics

### Data Quality Indicators

Data Quality Assessment Indicators
Indicator | Formula | Excellent_Range | Good_Range | Poor_Range | Unit
--- | --- | --- | --- | --- | ---
Milk yield per cow | Milk_litres / Cows_milking / 1000 | 7000-9000 | 6000-7000 | <5000 or >10000 | kg/cow/year
Stocking rate | Cows_milking / Area_total_ha | 1.2-1.8 | 0.8-1.2 | <0.5 or >2.5 | cows/ha
Feed conversion | Milk_litres / Concentrate_feed_kg | 3.0-5.0 | 2.0-3.0 | <1.5 or >6.0 | L milk/kg conc
Energy intensity | Electricity_kWh / Milk_litres | 0.04-0.06 | 0.06-0.08 | >0.10 | kWh/L milk

## 10. Common Parameter Issues and Solutions

### Missing Data Handling

Handling Missing Parameters
Missing_Parameter | Default_Used | Accuracy_Impact | Recommended_Action
--- | --- | --- | ---
Body weights | Species-specific defaults | Low | Use literature values for breed/region
DM intake | Calculated from body weight | Medium | Estimate from feeding standards
Feed breakdown | Concentrate only | High | Collect detailed feed records
Area breakdown | Total area only | Medium | Survey farm land use patterns
Ym factor | 6.5% | Medium | Use regional studies or 6.0-6.8 range

### Unit Conversion Guide

Unit Conversion Reference
Parameter | Common_Units | cowfootR_Unit | Conversion_Factor | Typical_Values
--- | --- | --- | --- | ---
Milk production | L, kg | L/year | kg = L × density | 1.03 kg/L
Feed amounts | kg fresh, kg DM, tons | kg DM/year | DM = fresh × (1 - moisture%) | 35% DM corn silage
Fertilizer | kg product, kg N | kg N/year | kg N = kg product × N% | 46% N in urea
Body weight | kg, lbs | kg | kg = lbs ÷ 2.205 | 580 kg dairy cow
Area | ha, acres | hectares | ha = acres × 0.405 | 0.405 ha/acre

### Regional Parameter Adjustments

Regional Emission Factor Variations
Region | Soy_EF_Range | Fertilizer_EF | Key_Differences | Use_When
--- | --- | --- | --- | ---
EU | 2.1-3.2 | 5.8-7.9 | High soy transport costs | European farms
US | 1.2-2.2 | 5.3-7.6 | Domestic grain production | US/Canadian farms
Brazil | 0.9-1.6 | 6.0-8.3 | Local soy, high N fertilizer | Brazilian operations
Argentina | 0.8-1.5 | 5.8-8.1 | Local grain/soy production | Argentinian farms
Australia | 1.8-3.0 | 5.4-7.7 | High transport distances | Australian/NZ farms
Global | 1.5-2.8 | 5.5-7.8 | Average of all regions | Unknown/mixed sourcing

## 11. Parameter Sensitivity Rankings

### High Impact Parameters (>15% result change)

High Impact Parameters (Priority for Accurate Data)
Parameter | Function | Impact_Direction | Typical_Variation | Result_Sensitivity | Data_Priority
--- | --- | --- | --- | --- | ---
n_animals | enteric | Linear | ±20% | ±20% | High
milk_litres | intensity | Inverse | ±25% | ±25% | High
conc_kg | inputs | Linear | ±30% | ±25% | High
ym_percent | enteric | Linear | ±15% | ±15% | Medium
avg_body_weight | enteric | Linear | ±10% | ±8% | Medium

### Medium Impact Parameters (5-15% result change)

Medium Impact Parameters
Parameter | Impact_Range | Collection_Difficulty | Recommendation
--- | --- | --- | ---
n_fertilizer_kg | 5-12% | Easy | Get purchase records
diet_digestibility | 8-15% | Medium | Estimate from feed quality
area_total_ha | Area metrics only | Easy | Survey or property records
manure_system | 10-25% manure | Easy | Observe system
region | 5-20% inputs | Easy | Select best match

### Low Impact Parameters (<5% result change)

Low Impact Parameters (Can Use Estimates)
Parameter | Impact_Range | Default_Approach | Notes
--- | --- | --- | ---
plastic_kg | <2% | Estimate broadly | Small contribution unless very large
lpg_kg | <3% | Estimate or ignore | Often minimal in dairy
gwp values | <5% | Use package defaults | IPCC AR6 values recommended
milk_density | <2% | Use 1.03 | Varies little
transport_km | <5% | Estimate 100-200 km | Affects feed emissions only

## 12. Troubleshooting Common Issues

### Error Messages and Solutions

Common Error Messages and Solutions
Error_Type | Common_Cause | Solution | Prevention
--- | --- | --- | ---
Invalid region | Typo in region name | Check spelling: ‘EU’, ‘US’, ‘Brazil’, ‘Argentina’, ‘Australia’ | Use template dropdown lists
Negative values | Data entry error or wrong units | Verify all quantities ≥ 0 and units are correct | Implement data validation in Excel
Area sum mismatch | Land use breakdown doesn’t add up | Review area_breakdown list or set validate_area_sum = FALSE | Use GIS or survey data for areas
Missing required data | Empty cells in required columns | Fill required columns or use defaults | Document data requirements clearly
Unrealistic results | Wrong units or extreme outliers | Check units, outliers, and parameter ranges | Compare results with similar farms

### Performance Optimization

For large batch processing:

Performance Optimization for Large Datasets
Aspect | Recommendation | Performance_Gain | Implementation_Effort
--- | --- | --- | ---
Data Preparation | Pre-validate data, use consistent formats, remove empty rows | 50-70% | Low
Processing Speed | Process in chunks of 50-100 farms, use tier 1 for screening | 30-50% | Medium
Memory Management | Set save_detailed_objects = FALSE for large batches | 60-80% | Low
Error Handling | Implement robust error logging and recovery mechanisms | Prevents crashes | High
Result Storage | Export results incrementally, use database for >1000 farms | Scalable | High

## 13. Advanced Parameter Combinations

### Tier 2 Optimal Parameter Sets

Optimal Parameter Combinations by System Type
System_Type | Key_Parameters | Critical_Measurements | Typical_Accuracy
--- | --- | --- | ---
Intensive Dairy | High DM intake, concentrate feeds, precise body weights | Feed composition, milk yield, system temperature | ±10-15%
Extensive Grazing | Pasture N excretion, extensive manure system, lower Ym | Grazing management, soil conditions, climate data | ±15-25%
Mixed System | Balanced feed inputs, moderate intensities | Feed efficiency ratios, land use breakdown | ±12-20%
Organic System | Organic fertilizers, lower input emissions, pasture focus | Organic input quantities, certification requirements | ±15-30%

### Parameter Interaction Effects

Important Parameter Interactions
Parameter_Pair | Interaction_Type | Effect_Magnitude | Management_Implication
--- | --- | --- | ---
Body weight + DM intake | Multiplicative | Medium | Heavier cows need proportionally more feed
Ym% + Feed quality | Exponential | High | Poor quality diets increase methane conversion
Climate + Soil type | Additive | Medium | Tropical poorly-drained soils have highest N2O
Region + Feed sources | Complex | High | Local feed sourcing reduces transport emissions
Manure system + Retention time | Threshold | Variable | Short retention (<30 days) limits CH4 conversion

## 14. Data Collection Protocols

### Minimum Data Requirements by Objective

Data Requirements by Assessment Objective
Assessment_Goal | Essential_Data | Time_Investment | Accuracy_Target | Tier_Recommendation
--- | --- | --- | --- | ---
Screening Assessment | Animal numbers, milk production, basic inputs | 2-4 hours | ±30% | Tier 1
Management Planning | Detailed feeds, precise areas, management practices | 1-2 days | ±15% | Tier 2
Carbon Trading | Verified production, third-party validated inputs | 3-5 days | ±10% | Tier 2 + validation
Research Study | Complete parameter set, uncertainty quantification | 1-2 weeks | ±5% | Tier 2 + uncertainty

### Data Collection Schedule

Recommended Data Collection Schedule
Data_Category | Collection_Frequency | Storage_Location | Quality_Control
--- | --- | --- | ---
Production Records | Monthly | Farm office | Cross-check with processor
Feed Purchases | Each delivery | Purchase invoices | Verify units and quantities
Energy Consumption | Monthly | Utility bills | Monitor seasonal patterns
Land Management | Seasonal | Management records | Update land use changes
Animal Characteristics | Annual | Herd records | Weigh representative sample

## 15. Quality Assurance Framework

### Validation Hierarchy

Quality Assurance Validation Levels
Level | Validation_Type | Examples | Error_Detection | Implementation
--- | --- | --- | --- | ---
Level 1: Range Checks | Automatic | Values within expected ranges, correct units | 90% | Built-in cowfootR
Level 2: Consistency Checks | Automatic | Milk yield vs feed intake, stocking rate vs area | 70% | Built-in cowfootR
Level 3: Benchmark Comparison | Semi-automatic | Results vs regional averages, peer farm comparison | 50% | User comparison
Level 4: Expert Review | Manual | Technical review by LCA specialist | 95% | External expert

### Red Flag Indicators

Data Quality Red Flag Indicators
Indicator | Warning_Threshold | Likely_Cause | Investigation_Priority
--- | --- | --- | ---
Milk intensity | >2.5 kg CO2eq/kg FPCM | Poor productivity or data errors | High
Feed efficiency | <1.0 L milk/kg concentrate | Overestimated feed use or underestimated milk | High
Energy use | >0.15 kWh/L milk | Energy-intensive processes or errors | Medium
Emission ratios | Enteric <30% of total | Missing emission sources or calculation errors | High
System consistency | Intensive system + low inputs | Inconsistent system classification | Medium

## Conclusion

This parameter reference guide provides comprehensive technical specifications for all cowfootR functions. Use it as a reference when:

- Setting up new farm assessments
- Troubleshooting calculation issues
- Validating data quality
- Understanding parameter sensitivities
- Optimizing data collection efforts

For practical applications, start with the function-specific sections, then refer to validation and troubleshooting sections as needed. The parameter sensitivity rankings help prioritize data collection efforts for maximum accuracy improvement.

Remember that parameter accuracy requirements depend on the intended use of results. Screening assessments can tolerate higher uncertainty than management planning or carbon trading applications.

This reference guide covers cowfootR version 0.1.3 and follows IDF 2022 and IPCC 2019 methodological standards.