Published August 12, 2026 | Version 1.0.0

Reproducibility Package: Quantifying the Economic Cost of Reducing Dietary Fiber to Mitigate Greenhouse Gas Emissions in U.S. Dairy Cattle

  • 1. ADA University, School of Agricultural and Food Sciences, Department of Animal Science, Baku, Azerbaijan
  • 2. University of Wisconsin-Madison, Department of Animal and Dairy Sciences, Madison, WI, USA

Description

Complete reproducibility package for a study quantifying the joint enteric-methane and farm-profitability consequences of dietary fiber (neutral detergent fiber, NDF) composition in U.S. lactating dairy cow diets, using constrained nonlinear optimization. Includes:

  • Python source code reproducing the full constrained-optimization pipeline: diet formulation, the enteric methane equation of Niu et al. (2018), external validation against published benchmarks, price-sensitivity analysis, an alfalfa-inclusion cost analysis, and a seven-ingredient (byproduct-feed) robustness check;
  • The ingredient composition/price library and external validation benchmarks used as model inputs;
  • All six result tables and two figures reported in the accompanying manuscript;
  • Full documentation (codebook, data description, reproducibility checklist, and a step-by-step replication guide).

The study formulates realistic, rumen-health-constrained lactating cow diets de novo across the commercial range of dietary NDF and solves for the income-over-feed-cost (IOFC)-maximizing diet at each fiber level, jointly reporting the resulting enteric greenhouse gas (GHG) emission intensity and farm economics. It finds that GHG emission intensity rises approximately linearly with dietary NDF, but that farm profitability does not decline in step -- the economic cost is concentrated once the least expensive low-fiber forage option is exhausted, and is highly sensitive to which feeds (including common byproducts such as distillers dried grains with solubles and soybean hulls) are available to the formulator.

This package is organized around the study itself rather than any single journal submission, so that it remains valid regardless of the eventual publication venue or manuscript title.

Notes

Underlying ingredient-price and external-validation benchmark data originate from publicly available third-party sources documented in full in docs/DATA_DESCRIPTION.md. Code and derived/processed data in this repository are released under the MIT License.

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