References

  • References

    Introduction References 
    The World Bank. 2021. Moving Towards Sustainability: The Livestock Sector and the World Bank. https://www.worldbank.org/en/topic/agriculture/brief/moving-towards-sustainability-the-livestock-sector-and-the-world-bank

    Example Task References

    Task 1: Comparing feed demand with supply 

    Task 2: Undertaking Tier 2 livestock calculations for a GHG inventory 

    Task 3: Estimating the cost-effectiveness of a livestock GHG mitigation project

    • Duffy, C., Apdini, T., Styles, D., Gibbons, J., Peguero, F., Arndt, C., ... & Chadwick, D. (2021). Marginal abatement cost curves for Latin American dairy production: a Costa Rica case study. Journal of Cleaner Production, 311, 127556. https://doi.org/10.1016/j.jclepro.2021.127556.
    • Gerber, Pierre and Germer, Leah Arabella. (2024). Enhancing Climate-Smart Outcomes from Livestock Systems : A How-To Guide Following the Project Cycle (English). Washington, D.C.: World Bank Group. http://documents.worldbank.org/curated/en/099040924202522226
    • MacLeod, M., Vera Eory, Guillaume Gruère and Jussi Lankoski (2015), “Cost-Effectiveness of Greenhouse Gas Mitigation Measures for Agriculture: A Literature Review” OECD Food, Agriculture and Fisheries Papers, No. 89, OECD Publishing, Paris. http://dx.doi.org/10.1787/5jrvvkq900vj-en
    • Ng’ang’a, S., G. Smith, C. Mwungu, S. Alemayehu, E. Girvetz and E. Hyman (2020) Cost-Benefit Analysis of Improved Livestock Management Practices in the Oromia Lowlands of Ethiopia. United States Agency for International Development (USAID) and Crown Agents USA with Abt Associates and the International Center for Tropical Agriculture (CIAT) Washington, DC available at https://pdf.usaid.gov/pdf_docs/PA00X1KT.pdf. 

    Data sources references

    Section B – General Principles

    Approach 1: Sample survey 

    Approach 3: Direct measurement

    • FAO (2018a) Guidelines on methods for estimating livestock production and productivity. Rome: FAO. https://openknowledge.fao.org/handle/20.500.14283/ca6400en
    • FAO and Global Research Alliance on Agricultural Greenhouse Gases. 2020. Livestock Activity Data Guidance (L-ADG): Methods and guidance on compilation of activity data for Tier 2 livestock GHG inventories. https://doi.org/10.4060/ca7510en. 
    • Goopy, J.P., A.A. Onyango, U. Dickhoefer, K. Butterbach-Bahl (2018) A new approach for improving emission factors for enteric methane emissions of cattle in smallholder systems of East Africa – Results for Nyando, Western Kenya, Agricultural Systems, Volume 161, Pages 72-80, https://doi.org/10.1016/j.agsy.2017.12.004. 
    • Ndung’u PW, Bebe BO, Ondiek JO, Butterbach-Bahl K, Merbold L, Goopy JP. (2019) Improved region-specific emission factors for enteric methane emissions from cattle in smallholder mixed crop: livestock systems of Nandi County, Kenya. Animal Production Science 59, 1136–1146. https://doi.org/10.1071/AN17809

    Approach 4: Earth observation

    • Fraval, S., Mutua, J. Y., Amole, T., Tolera, A., Feyisa, T., Thornton, P. K., Notenbaert, A. M. O., Adesogan, A., Balehegn, M., Ayantunde, A. A., Zampaligre, N., & Duncan, A. J. (2024). Feed balances for ruminant livestock: Gridded estimates for data constrained regions. Animal, 101199. https://doi.org/10.1016/j.animal.2024.101199
    • Mutua, J. (2026). Livestock Feed Assessment and Forecasting with Earth Observation. Jameel Observatory stocktaking webinar on enhancing forecasting and earth observation data and applications for drylands of the Horn of Africa, Edinburgh, United Kingdom. 
    • Rahimi, J., Haas, E., Grote, R., Kraus, D., Smerald, A., Laux, P., Goopy, J., & Butterbach-Bahl, K. (2021). Beyond livestock carrying capacity in the Sahelian and Sudanian zones of West Africa. Scientific Reports, 11(1), Article 1. https://doi.org/10.1038/s41598-021-01706-4

  • Appendix A. Enumerator training

    Feed basket data aims to capture what animals actually consume, not what farmers believe is recommended or desirable. This distinction must be clearly internalized during enumerator training and reinforced throughout fieldwork. 

    Pre-Enumeration Responsibilities

    In addition to attending training and preparing enumeration schedules, enumerators must:

    • Become familiar with local feed types, names, and seasonal availability;
    • Clearly understand the different animal categories (e.g., lactating cows, dry cows, heifers, calves, small ruminants); 
    • Review local measurement units (bundles, sacks, bowls, carts) and associated conversion factors; and 
    • Participate in practical exercises involving real feeds or feed photographs.

    These approaches are consistent with the training philosophy of International Livestock Research Institute's (ILRI) Feed Assessment Tool (FEAST), which emphasizes feed identification and contextual understanding before data collection.

    Core Principles of Quality Feed Basket Data Collection

    Enumerator training should emphasize the following principles:

    • Completeness: All feeds offered must be recorded, including small supplements (salt, minerals, by-products) 
    • Specificity: Feeds must be identified precisely (e.g., maize stover vs. sorghum stover) 
    • Quantification: Amounts must be estimated as accurately as possible using local-to-standard unit conversions 
    • Temporal clarity: The reference period (typical day, dry vs. wet season) must be consistent 
    • Animal specificity: Feed baskets must be linked to clearly defined animal groups 

    These principles align closely with guidance in ILRI’s FEAST methodology.

    Interview Techniques for Feed Basket Surveys

    Enumerators must ask questions exactly as worded, in the correct order, and without unauthorized interpretation. If the questions need to be translated to a local language, it is recommended to prepare a fully translated questionnaire in advance, rather than translating the question during the interview. Otherwise, mistakes in translation may be made and/or questions may be asked differently across farmers.

    Enumerators should avoid yes or no questions and should never suggest feeds or quantities. For feed basket surveys, it is important to use structured probing, for example, “What else do you give when pasture is scarce?” “Do calves receive the same feed as adult animals?” “What changes in the dry season?” . This will ensure data points are not missed.

    Enumerators should record how farmers feed their animals and should not suggest or decide on feeding practices. If animals from different categories are fed together, enumerators should carefully allocate the reported feeds to the appropriate animal category during data recording, ensuring that feeds are not mixed across categories.

    Estimating Feed Quantities: A Critical Skill

    Quantity estimation is the most error-prone element of feed basket surveys. Enumerator training must therefore include:

    • Practice converting local units to kilograms;
    • Clear distinction between per-animal and per-herd feeding;
    • Clarification of sharing among animals; and
    • Recording of grazing time (hours/day), not just stall-fed feeds

    ILRI’s FEAST Instructor Guide provides tested approaches for handling these challenges and is widely cited as best practice for livestock feed assessment.

    Seasonality and Variability

    Feed availability and feeding practices vary substantially across seasons. Enumerators must be trained to:

    • Collect feed basket data separately for wet and dry seasons;
    • Record feed substitutions and shortages; and
    • Avoid averaging across seasons unless explicitly instructed

    Seasonal feed calendars, as recommended in ILRI training materials, are strongly encouraged during interviews.

    Quality Control During and After Enumeration

    Quality control should include:

    • Same day checking of questionnaires;
    • Verification that all feeds, quantities, and animal categories are completed;
    • Cross-checks for internal consistency (e.g., feed quantity vs. number of animals; feed quantity vs. milk yield);
    • Immediate clarification with respondents when inconsistencies arise ; and
    • Supervisors should conduct spot checks and random re-interviews, in line with the recommendations for quality assurance laid out in ILRI’s FEAST tool. 

    Ethical Conduct and Professionalism

    Enumerators should strive to be honest, accurate, adaptable, and culturally aware. 

    Enumerators must:

    • Obtain informed consent;
    • Respect local norms and time constraints; and
    • Avoid raising expectations of direct benefits

    Resources: 

  • Appendix B. Using Open Data Kit for Collecting Feed Data

    Open Data Kit (ODK) is a free, open-source set of tools designed for mobile data collection in environments with limited internet connectivity. It allows users to create digital forms, collect data on Android devices, and aggregate that data on a central server for analysis. 

    ODK is advantageous over error-prone paper-based data collection due to its offline digital workflow, which captures not just text and numbers, but also GPS coordinates and photos. The app uses skip logic (e.g., if "Concentrates" is selected, a follow-up question about the specific concentrate or protein content appears). Using ODK for data collection also gives the chance to integrate data quality checks into the data collection forms by setting a range of plausible data for any sensitive variables and giving hints to the data collector whenever entered data seems implausible.

    Using ODK for dairy cow feed data

    It is important to note that using ODK is a collection tool that also requires experienced data collectors who have at least a basic understanding of dairy/animal nutrition. They should be able to roughly judge the quality of feeds and the relationship between their intake and animal productivity. It is advisable to weigh the feed items on-site rather than relying on information provided by farmers. 

    1. Questionnaire development

    Before data collection, the questionnaire is first developed in Excel and then uploaded to the desired ODK tool. Kobo toolbox is a common ODK tool used. 

    A good questionnaire should include: 

    • Feed types: (e.g., Napier grass, maize bran, minerals, hay, or silage) 
    • Feed quantities: Amount fed per cow (kg) or total amount fed if animals are fed together, feeding frequencies,
    • Feed quality: (e.g., maize silage with whole plant including grain vs maize stover silage; stage of fodder harvest; storage conditions and duration, colour, texture, etc.) 
    • Water Access: Frequency of watering 
    • Inputs: For feed production 
    • Cow ID: For example, ear tags
    • Photos: For example, to show the fodder quality or the cow’s body condition score 
    • Herd count: For the entire herd 
    1. Field data collection

    Even in remote areas without a signal, data collectors can: 

    • Open the ODKapp on an Android tablet or smartphone 
    • Fill out the feed data
    • Save data locally on the device 
    1. Data syncing and aggregation

    Once the data collector accesses Wi-Fi or mobile data, they can "Send Finalized Forms" to a central server. The data then becomes visible to the project manager or anyone given access via a password.

    1. Analysis and feedback

    Project managers can export the data to Excel, and it can be analysed using any data analysis tool like R, Stata, or SPSS.