MixedFarmCarbonby AgriEnv AI Linked-flow screening model

WHOLE-FARM CROP + DAIRY ACCOUNTING

One farm.
One carbon ledger.

Connect crops, dairy animals, manure, feed, climate, and shared energy in one annual U.S. farm inventory - without counting the same flow twice.

Build the farm inventory Read the science
Crop fieldsFeed, fertilizer, residues
⇄
Linked ledgerManure N · feed · energy
⇄
Dairy herdEnteric + manure
Each physical flow enters the total once.

MIXED-FARM ASSESSMENT

Connect land and animals

Annual farm-gate screening estimate. Farm-grown feed is represented by its fields; only purchased feed is added upstream.

Crop fields

Add each field or crop enterprise. Crop-specific residue parameters update automatically.

Field 1
Field 2
Results update only when you select Calculate.

INTEGRATED WITHOUT DOUBLE COUNTING

A physical-flow ledger connects both enterprises

01

Inventory

Describe crop fields, animal groups, climate, manure handling, and shared farm energy.

02

Link

Route excreted manure N through storage, export, grazing, and application to individual fields.

03

Calculate

Apply IPCC crop-soil, enteric, manure, rice, amendment, and indirect-emission equations.

04

Audit

Export inputs, resolved factors, linked flows, results, assumptions, and source notes.

Detailed science & accuracy PDF

TUTORIAL & SCIENTIFIC BASIS

How MixedFarmCarbon works

Add crop fields and dairy animal groups, retrieve annual climate, route manure nitrogen through storage, grazing, export, and individual fields, enter shared farm energy only once, set supported mitigation scenarios, then select Calculate. The physical-flow ledger prevents double counting of manure N, farm-grown feed, and shared energy.

Purpose

Screen integrated U.S. crop-and-dairy farm emissions, identify linked hotspots, and compare mitigation scenarios.

Inputs

Fields, crop and yield, fertilizer, animals and diet, location and climate, manure flow, feed, energy, refrigerants, and mitigation controls.

Calculations

Crop-soil N₂O, rice CH₄, lime/urea CO₂, enteric CH₄, manure CH₄/N₂O, shared energy, optional feed, and conserved manure-N flows.

Outputs

Whole-farm t CO₂e, source and subsystem hotspots, per-acre/head/milk indicators, physical ledgers, avoided emissions, and licensed audit CSV.

Educational channels

Sustainability Analytics LabDigital Agriculture and AI Lab

Scientific references

DOIs are shown where assigned; standards and databases use official links.

  1. IPCC. 2019 Refinement, Volume 4, Chapters 10 and 11. DOI: not assigned.
  2. IPCC. 2006 Guidelines, Volume 4, Chapters 5, 10 and 11. DOI: not assigned.
  3. U.S. EPA. Inventory of U.S. GHG Emissions and Sinks. DOI: not assigned.
  4. Hristov, A.N. et al. (2015). PNAS 112:10663–10668. DOI: 10.1073/pnas.1504124112.
  5. Niu, M. et al. (2018). Global Change Biology 24:3368–3389. DOI: 10.1111/gcb.14094.
  6. Dijkstra, J. et al. (2018). Journal of Dairy Science 101:9041–9047. DOI: 10.3168/jds.2018-14456.
  7. Kebreab, E. et al. (2023). Journal of Dairy Science. DOI: 10.3168/jds.2022-22211.
  8. Akiyama, H. et al. (2010). Global Change Biology 16:1837–1846. DOI: 10.1111/j.1365-2486.2009.02031.x.
  9. Gilsanz, C. et al. (2016). Agriculture, Ecosystems & Environment 216:1–8. DOI: 10.1016/j.agee.2015.09.030.
  10. Shcherbak, I. et al. (2014). PNAS 111:9199–9204. DOI: 10.1073/pnas.1322434111.
  11. Snyder, C.S. et al. (2009). Agriculture, Ecosystems & Environment 133:247–266. DOI: 10.1016/j.agee.2009.04.021.
  12. Linquist, B. et al. (2012). Field Crops Research 135:10–21. DOI: 10.1016/j.fcr.2012.06.007.
  13. Paustian, K. et al. (2016). Nature 532:49–57. DOI: 10.1038/nature17174.
  14. Thoma, G. et al. (2013). Journal of Dairy Science 96:5405–5425. DOI: 10.3168/jds.2012-6221.
  15. Capper, J.L. et al. (2009). Journal of Animal Science 87:2160–2167. DOI: 10.2527/jas.2009-1781.
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