About
This website hosts the public documentation for the methods used to create the values and metrics reported to Fieldprint Platform users. The website is searchable and organized primarily by each sustainability indicator. Below is a summary of updates in the latest version of the Platform.
Please contact science@fieldtomarket.org to submit feedback on the documentation or report errors.
Sustainability Indicators
The Fieldprint Platform aims to be a transparent, credible, and accessible tool for all agricultural stakeholders in evaluating the environmental impact associated with the production of twenty row crop commodities at the field level. The outcomes from individual fields can be aggregated to represent a farm or a supply shed (a group of farmer suppliers in a defined geography or market). Considering all 2024 planted acres1 of crops in Field to Market’s program, the Fieldprint Platform can be used to estimate the environmental impact of approximately 267 million acres (108 million hectares) of United States cropland, representing nearly 70% of all U.S. planted cropland2.
1 harvested acres for alfalfa
2 382 million acres
Field to Market’s program centers on eight sustainability indicators that estimate environmental impacts on individual farm fields. These indicators are built into our Fieldprint Platform® and have been carefully developed over the past decade with input from farmers, researchers, companies, and other partners. The Metrics Committee oversees these tools, with four elected members representing each of our five membership groups. The committee reviews each indicator every three to five years to make sure it stays current and useful. Input and guidance is also gathered from workshops, consultants, and science councils.
Changes in Methods 5.0
Updates in the Fieldprint Platform 5.0 Methods are summarized below by indicator or topic. Major revisions were conducted for the methods of the Energy Use, GHG Emissions, and Soil Carbon indicators.
Biodiversity
The structural score for the cultivated land module of the Habitat Potential Index in version 5.0 no longer accounts for land use change from surface waters (such as wetlands, lakes, ponds, rivers, or streams) to cultivated land. This is related to the limitations of the Direct Land Use Change method in the GHG Emissions section.
Energy Use and associated GHG Emissions
Methods for estimating Energy Use and associated GHG emissions were updated as follows:
| Item | Primary Sources |
|---|---|
| Irrigation operations | Hoffman, Howell, and Solomon (1990); Eisenhauer et al. (2021) |
| Field operations | Kucera and Coreil (2023) |
| Manure transportation | ANL (2024); Bormann et al. (2024); Wilson et al. (2022) |
| Crop transportation | BTS (2024); internal analysis |
| Crop drying | Arinze et al. (1996); Blankenship and Chew (1979); Ford (2024); Panigrahi et al. (2023); Parker, Muller, and Buckmaster (1992); Savoie and Joannis (2006) |
GHG Emissions
For methods related to all other field-level GHG emissions, the following list indicates whether a method is an addition or a revision for the FP v5, the source, and tier classification:
| Method | Primary Sources | Tier | Change |
|---|---|---|---|
| CH4 emissions from flooded rice cultivation | Ogle et al. (2024) | Tier 2 | 🔁Revision |
| Non-CO2 emissions from biomass burning | Ogle et al. (2024) | Tier 1 | 🔁Revision |
| Soil N2O | Ogle et al. (2024) | Tier 1 | 🔁Revision |
| CH4 flux from non-flooded soils | Ogle et al. (2024) | Tier 1 | ➕Addition |
| CO2 from carbonate lime applications to soils | Ogle et al. (2024) | Tier 2 | ➕Addition |
| CO2 from urea fertilizer applications | Ogle et al. (2024) | Tier 1 | ➕Addition |
| Direct land use change | IPCC (2019); ECEuropean Commission (2010) | Tier 2 | ➕Addition |
| Soil carbon stock changes | SWAT+ model (Bieger et al. 2017; Zhang et al. 2013) | Tier 3 | ➕Addition |
Soil Carbon
The Soil Conditioning Index (Carlson et al. 2016) has been replaced with a process-based model. The SWAT+ model service quantifies soil carbon stock to a specified depth in the soil profile, the default set to 30 cm. The model simulates soil carbon stock, fluxes among carbon and nitrogen pools, and CO2 emissions by soil horizon, as well as carbon and nitrogen loss through runoff, lateral flow, and percolation through the soil profile.
The SWAT+ soil organic carbon module was based on the SWAT-C model (Zhang et al. 2013). SWAT-C incorporated terrestrial soil organic matter dynamics from the CENTURY and EPIC models and aquatic carbon cycling processes from QUAL2K and CE-QUAL-W2 (Du et al. 2019) into SWAT2012.
With the implementation of SWAT+, annual sequestered soil organic carbon stock changes can be expressed either as elemental carbon or carbon dioxide equivalents as follows:
\[ \Delta SOC = \Delta SOC_{microbial} + \Delta SOC_{slow} + \Delta SOC_{passive} \] Where:
- \(\Delta SOC\) = Soil organic carbon (SOC) stock changes from consecutive years.
- \(\Delta SOC_{microbial}\) = SOC stock changes from the mass of microorganisms within the soil.
- \(\Delta SOC_{slow}\) = SOC stock changes from partially decomposed organic matter that breaks down over several years.
- \(\Delta SOC_{passive}\) = SOC stock changes from passive humus that decomposes over centuries.
Indicators without method revisions from version 4.2
Land Use
Irrigation Water Use
Soil Conservation3
Water Quality
3 As with previous versions, users are invited to report any modeled soil erosion values that seem unusually high
Other Notes
Yield Inputs
- Rice yield should be entered on a standard moisture basis4.
- Alfalfa harvest moisture should be entered as moisture at baling, not at cutting.
- Seed cotton yield can be estimated from lint yield entered by user.
4 standard moisture = 14%
Manure Inputs
- Users can now enter an exact manure application rate (\(gal\ ac^{-1}\) or \(ton\ ac^{-1}\)).
- Default manure content values (% solids, Total N, Total P2O5) are sourced from a custom backend table derived from manureDB (Bormann et al. 2024).
- Support and collaboration could enable users to override the defaults with their own manure content values.