Persistent Identifier
|
doi:10.7910/DVN/JIU3OK |
Publication Date
|
2025-02-03 |
Title
| Evidence for Resilient Livestock (ERL): Livestock Feed Nutritional Meta-dataset from Africa |
Author
| Steward, Peter RichardInternational Center for Tropical Agriculture - CIATORCIDhttps://orcid.org/0000-0003-3985-4911
Joshi, NamitaInternational Center for Tropical Agriculture - CIATORCIDhttps://orcid.org/0009-0006-1473-7718
Rosenstock, Todd StuartBioversity InternationalORCIDhttps://orcid.org/0000-0002-1958-9500 |
Point of Contact
|
Use email button above to contact.
Alliance Data Management (Bioversity International and the International Center for Tropical Agriculture) |
Description
| Purpose, Nature, and Scope: This data collection focuses on extracting and organizing data on animal feed nutritional composition and digestibility as part of the Evidence for Resilient Agriculture (ERA) initiative. The dataset serves as a foundational resource for understanding livestock feed practices and their implications for productivity, sustainability, and environmental impact. While no specific research questions have been addressed yet, the dataset provides a critical input for ongoing and future research. Special Characteristics:
The dataset includes:
- Nutritional composition data (e.g., protein, fiber, and energy content) for various feed types.
- Digestibility data (e.g., dry matter and energy digestibility) relevant to livestock systems.
- Contextual metadata, such as livestock species, feed types, and geographic locations.
The data is curated within the ERA data model, using a controlled vocabulary for consistency and interoperability. Applications: This dataset can be shared with collaborators who have developed emissions calculators requiring detailed information about the nutritional composition and digestibility of livestock diets. These tools use such data to estimate emissions and develop mitigation strategies by analyzing or modifying animal diets. More information here: https://eragriculture.github.io/ERL/ERL_feed_data.html Methodology: The dataset was created using the ERA data model, leveraging a structured Excel-based extraction template (Skinny Cow template) to systematically extract and compile data from published studies. The focus was on capturing nutritional composition, digestibility metrics, and associated metadata (e.g., livestock types, feed practices, and geographic details). For more details on how the dataset was created, see the ERL Feed Data documentation and the Guide to Livestock Data Analysis in the ERA Dataset. (2025-01) |
Subject
| Earth and Environmental Sciences; Agricultural Sciences |
Keyword
| feed composition (AGROVOC) http://aims.fao.org/aos/agrovoc/c_10770
digestibility (AGROVOC) http://aims.fao.org/aos/agrovoc/c_2266
livestock (AGROVOC) http://aims.fao.org/aos/agrovoc/c_4397
feeds (AGROVOC) http://aims.fao.org/aos/agrovoc/c_2843
Africa (Research Region)
Climate Action (Research Lever) |
Topic Classification
| livestock (AGROVOC) http://aims.fao.org/aos/agrovoc/c_4397
meta-analysis (AGROVOC) http://aims.fao.org/aos/agrovoc/c_3a821ebd
Africa (AGROVOC) http://aims.fao.org/aos/agrovoc/c_165 |
Language
| English |
Producer
| Bioversity International and the International Center for Tropical Agriculture https://alliancebioversityciat.org/ |
Distributor
| Bioversity International and the International Center for Tropical Agriculture https://alliancebioversityciat.org/ |
Distribution Date
| 2024-12-15 |
Depositor
| Alliance Data Management |
Deposit Date
| 2025-01-22 |
Time Period
| Start Date: 1970; End Date: 2018 |
Data Type
| Quantitative Data; Trial Data; Nutritional Data |
Related Dataset
| Rosenstock, Todd Stuart; Steward, Peter Richard; Joshi, Namita, 2024, "Agriculture Ontology for Meta-analysis (AOM): Livestock Prototype", (https://doi.org/10.7910/DVN/75E7HV); Rosenstock, Todd Stuart; Steward, Peter Richard; Joshi, Namita; Mumo, Elijah Mustoki; Ombewa, Babra Vivian Adhiambo; Kacha, Gabrielle Nour, 2024, "Evidence for Resilient Agriculture (ERA): Livestock Data", (https://doi.org/10.7910/DVN/XY9WAX) |
Other Reference
| https://www.nature.com/articles/s41597-024-03805-z; https://eragriculture.github.io/ERL/ERL_feed_data.html |