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Prediction of Digestible and Metabolizable Energy in Swine Feed Using Machine Learning.

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Paper

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The authors' code

Markdown · 42 lines · 1.4 KB · no license

  1. # pig-feed-prediction-tool
  2. A prediction tool for DE and ME based on the China Feed Database
  3. ## 📦 Download All Files
  5. All related files, including:
  7. - Python script (`predict.py`)
  8. - Trained model files (`models/model_de.pkl`, `models/model_me.pkl`)
  9. - Excel-based prediction tool (`predict.xlsm`)
  11. are available via Baidu Netdisk:
  13. 🔗 **Download link:** [https://pan.baidu.com/s/1qdqU4CuOtdUYuo_UpPuVgQ](https://pan.baidu.com/s/1qdqU4CuOtdUYuo_UpPuVgQ)
  14. 🔐 **Access code:** `5suq`
  16. ---
  18. ## 📝 File Descriptions
  20. | File | Description |
  21. |------|-------------|
  22. | `predict.py` | Python script for running predictions |
  23. | `models/model_de.pkl` | Trained model for DE prediction |
  24. | `models/model_me.pkl` | Trained model for ME prediction |
  25. | `predict.xlsm` | Excel-based prediction interface with embedded VBA macros |
  27. ---
  29. ## 🚀 How to Use
  31. 1. Download all files from the Baidu Netdisk link.
  32. 2. You can choose to:
  33. - Run `predict.py` with your own input data (requires Python 3 and necessary packages)
  34. - Use `predict.xlsm` in Microsoft Excel to input feed composition data and obtain DE/ME predictions
  36. ### ⚠️ Important Notes for Excel Tool Users
  38. - The `predict.xlsm` file contains a macro that uses **Shell** to call Python.
  39. - Please make sure to **replace the Python interpreter path in the macro code** with the full path to your own Python environment.
  40. For example:
  41. ```vba
  42. Shell "C:\Users\yourname\anaconda3\python.exe path\to\predict.py", vbNormalFocus

README.md at commit 56b84a7, no license · at the source

Overview

Authors: Jun-Wen Yu1, Shang-Hua Liu1, Dong-Xin Ye1, De Wu2, Hao Lin1, Yan Lin2
ORCID iDs: De Wu, Hao Lin
  1. School of Life Science and Technology and Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China
  2. Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
Institutions: University of Electronic Science and Technology of China (China); Sichuan Agricultural University (China)
Journal: ACS omega, volume 11, issue 23, pages 34699-34712
Dates: received 30 March 2026; accepted 19 May 2026; published online 1 June 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1021/acsomega.6c03545 · PMID 42326664 · PMCID PMC13280999 · OpenAlex W7163059251
Open access: gold, a free copy (OpenAlex)
Status: empty repository
Categories: other (organism)
Methods: Statistics, Smoothing, state filtering, decompositions, Machine learning, Connectivity
Topic: Animal Nutrition and Physiology (Animal Science and Zoology, Agricultural and Biological Sciences), according to OpenAlex
Funding: Science and Technology Department of Sichuan Province (2021ZDZX0009); Ministry of Finance (SCSZTD-2024-08); Ministry of Agriculture and Rural Affairs of the People's Republic of China (SCSZTD-2024-08); National Key Research and Development Program of China (2021YFD1300202)
Citations: not cited yet (Europe PMC); 51 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above.

Niceyjw/pig-feed-prediction-tool

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 56b84a7c25c753da500ff168ff5aade3bbf4ea76, 29 March 2025
Size: 1 file, 0 scripts
Software Heritage: not archived
Found in: the text, “Development and Application of the Pig Energy Pr”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
1 file
At the source: github.com/Niceyjw/pig-feed-prediction-tool

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 0 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 4 funders, 42 references.

Cite

This paper

Yu, J.-W., Liu, S.-H., Ye, D.-X., Wu, D., Lin, H., & Lin, Y. (2026). Prediction of Digestible and Metabolizable Energy in Swine Feed Using Machine Learning. ACS omega, 11(23), 34699-34712. https://doi.org/10.1021/acsomega.6c03545

BibTeX

@article{yu2026prediction,
author = {Yu, Jun-Wen and Liu, Shang-Hua and Ye, Dong-Xin and Wu, De and Lin, Hao and Lin, Yan},
title = {{Prediction of Digestible and Metabolizable Energy in Swine Feed Using Machine Learning}},
journal = {ACS omega},
year = {2026},
month = jun,
volume = {11},
number = {23},
pages = {34699--34712},
publisher = {American Chemical Society},
issn = {2470-1343},
doi = {10.1021/acsomega.6c03545},
url = {https://doi.org/10.1021/acsomega.6c03545},
pmid = {42326664},
pmcid = {PMC13280999}
}

RIS

TY - JOUR
AU - Yu, Jun-Wen
AU - Liu, Shang-Hua
AU - Ye, Dong-Xin
AU - Wu, De
AU - Lin, Hao
AU - Lin, Yan
TI - Prediction of Digestible and Metabolizable Energy in Swine Feed Using Machine Learning
T2 - ACS omega
J2 - ACS Omega
PY - 2026
DA - 2026/06/01
VL - 11
IS - 23
SP - 34699
EP - 34712
SN - 2470-1343
PB - American Chemical Society
DO - 10.1021/acsomega.6c03545
UR - https://doi.org/10.1021/acsomega.6c03545
LA - en
ER -

CSL-JSON

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"id": "10.1021/acsomega.6c03545",
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"container-title": "ACS omega",
"author": [
{
"family": "Yu",
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"issue": "23",
"page": "34699-34712",
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"PMCID": "PMC13280999",
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