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The role of reliable data collection systems for improved livestock genetics in Burundi: Experience from ILRI ADGG program
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The role of reliable data collection systems for improved livestock genetics in Burundi: Experience from ILRI ADGG program
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Presented by Julie Ojango and Chinyere Ekine-Dzivenu at the Workshop on sustainable development of Burundi's dairy sector--Partners of the regional integrated agricultural development in the great lakes (PRDAIGL) project workshop, Burundi, 2–3 November 2022
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The role of reliable data collection systems for improved livestock genetics in Burundi: Experience from ILRI ADGG program
- Better lives through livestock The role of reliable data collection systems for improved livestock genetics in Burundi: Experience from ILRI ADGG program Workshop on sustainable development of Burundi's dairy sector--Partners of the regional integrated agricultural development in the great lakes (PRDAIGL) project workshop, Burundi, 2–3 November 2022 Julie Ojango, Chinyere Ekine-Dzivenu. Livestock Genetics International Livestock Research Institute (ILRI)
- 2 The bottom line
- 3 Challenges facing dairy producers in Africa • Farmers do not have access to productive and adapted livestock seedstock that best suit their production systems • Access to various services and inputs is inadequate, hence gains in productivity in one generation cannot be sustained in the next one • Farmers have very limited access to information to enable them extract optimum benefits for their dairy enterprises • No systematic and sustainable breeding or selection taking place Huge differences in productivity in the different farming systems
- 4 Consequences of low production levels Methane emission per kilogram of milk is about 4 times higher in the top herds than in herds that produce an average of 2000 kg of milk
- 5 Addressing the challenges facing small holder livestock (dairy) systems through innovative application of ICT and genomic technology What is the African Genetic Gain Program about ?
- 6 ADGG’s Innovative Approach and Objectives • Establish/Revamp National livestock Performance Recording Centers (DPRCs) or Platforms for herd and cow data management • Develop & scale ICT platforms to capture herd, cow level & other related data & link it to DPRCs & other databases • Develop a pipeline for genomic evaluations to identify genetically superior bulls & cows for propagation using Artificial Insemination and natural mating • Establish a digital farmer extension and feedback system using genomic and performance data for improved herd management • Establish private-public partnerships to sustainably resource recording, genetic evaluation and digital extension at county & regional levels
- 7 ADGG’s innovative approach o Digital platforms for on-farm performance tracking o Decision-support and Farmer-to-Farmer performance benchmarking o Smart use of records & genomics tools for selection and AI service delivery Accelerate on-farm genetic gains • Milk Yield • Milk composition • Weight • Reproductive Performance • Heat tolerance • Survival rates • Lactation persistency • Mastitis incidences • Disease tolerance • Methane emission • Adaptability Indices o Target appropriate genotypes to the agro-ecology o Use young bulls with a focus on production & adaptation o Local feed/fodder resource use efficiency Genotypes adapted to local agro-ecology Economically and Environmentally relevant Traits Adapted, and Genetically superior "seed” animals for local production systems Accelerate on-farm genetic gains
- 8 ADGG digital data platform (webpage)
- •Farming systems characteristics •Characteristics of dairy animals on farms •Monitor animal performance •Monitor use of technologies (eg Artificial Insemination, vaccination) •Service providers Data capture Country Data platforms Data Extraction API Management System Administration Data Validation DATA PLATFORM Data Feedback systems •Customized data summaries •Genomic evaluation •Customized indexes for animal selection Analytics •Managing reproduction •Managing calves at different stages •Using livestock data for decisions •Managing animal health E-Learning tools • i-Cow • Interherd + Other data bases The ADGG Platform The ADGG landing page: https://portal.adgg.ilri.org/ An agile, robust, flexible & scalable system
- 10 Breeds reared in different regions Useful data summaries for informed decision making by different stakeholders : Example from Tanzania
- 11 Cont’d - Useful data summaries for decision making by different stakeholders
- Visualization tools for partners e.g. -for NAICs
- 13 Feedback to farmers
- 14 • ILRI director general, Jimmy Smith (left) and Minister for Livestock and Fisheries Luhaga Mpina (2nd to left) present the award for best bull at a special bull and cow show at the Nane Nane exhibition center in Dodoma, Tanzania, June 2019. Photo ILR Milestones & Achievements • Ethiopia First dairy animal parade held on Tuesday March 30, 2020, Fikiru Regessa, State Minister of Agriculture (extreme left), Selam Meseret ADGG Ethiopia National Coordinator (middle), and Asrat Tera, Director General of National Animal Genetics Institute (NAGII) Ethiopia.
- Artificial Insemination Breeding Products Manage Reproduction Manage Calves Improved Heifers Bulls for breeding Productive Dairy Cows More Milk Health & Hygiene Optimal feeding Monitor performance and costs Products from a dairy enterprise Natural mating
- Index for selecting seed animals developed using results from genomic evaluation to improve milk production without increasing body weight • In 2018, about 5600 animals sampled • GeneSeek Genomic Profiler (GGP) Bovine 50K used for genotyping • 40581 SNPs imputed to high density • In 2022 an additional 3000 animals sampled for genotyping per country
- Objective: Evaluate changes in genetic parameters for milk yield and estimate breeding values for milk production under heat stress conditions. Data –phenotype, genotype, weather Genomic analysis of milk yield and heat tolerance in small holder dairy system of sub-Saharan Africa C.C. Ekine-Dzivenu, R. Mrode1, R.D. Oloo, D. Komwihangilo, E. Lyatuu, G. Msuta, J.M. Ojango, A.M. Okeyo -1 0 1 2 3 4 69 70 71 72 73 74 76 77 78 79 80 81 82 Milk EBV THI 65769 55133 59078 63039 51938 59188 59155 Results Antagonistic relationships between milk yield and thermal tolerance. Milk production reduced by 4.16% to 14.42% across THI groups (heat stress levels). Reaction norm shows genetic variations exist between sires, indicating the possibility to select animals that perform optimally in different environments. Chinyere Ekine-Dzivenu cekine@cgiar.org
- Better lives through livestock Take home message Current & emerging ICT and genomic tools plus reproductive technologies present new opportunities for Burundi to hasten genetic gains, hence there is no excuse any more inaction.
- THANK YOU
- 20 Acknowlegment of Partners Dairy Farmers & Farmer organizations National/regional Institutions/govts.
Editor's Notes
- Good afternoon and welcome back from lunch. I will give you more in-depth view of the ADGG data platform building on what Julie presented yesterday.
- I would like to start by reminding you of this slide from yesterday that what you cannot measure, you cannot improve.
- These are some of the problems facing small holder farmers in Africa ….lack of appropriate animals suited to our production system, in adequate access to input and services and extension information and also lack of systematic breeding and selection going on By applying a few changes in the management of their cattle, the small holder farmer can almost double his production
- With the low production of our animals we have higher green house gas emission intensity which is leading to the change in the climate that we are seeing in our environment…..you can tell that the rains don’t come when it should come and the dry seasons are longer so if we have more productive animals,
- Yesterday, we heard from Julie that in the developed parts of the world where dairy cows are producing a lot of milk, data was key. They had established system for collecting data from farmers and used that to develop the cattle population. The problem we have in Africa is that we do not have such well established systems but we have ow discovered that we can work around that. Almost everyone has a mobile phone, farmers have mobile phones and we can use this to capture information we need to improve our dairy cattle populations coupled with DNA information form the cow’s hair. But how do you measure in such fragmented system as ours in sub-Saharan Africa Maximise productivity er unit land community best seeds production systems….cimmyt seeds to grow under inspection from them. Theny bought back the seed, gave it back to Perenial fodder……grow what we know will work well…… Persistence,,,,how long deos it last in the cutting or grazing regime
- So when ADGG comes into a country Establish a platform for data recording Establish ICT platform for capturing the data Develop pipeline for genomic evaluation for identifying the genetically superior animals Establish digital farmer feedback and extension system for informed decision making Establish public private partnerships to keep the system running beyond the program
- So ADGG collects data on economically important traits—MY, milk composition, weight, methane emission, heat tolerance, in the production environment of the farmer where the trait will be expressed and couples this information with the DNA information of the farmer to find the star animals that is adapted and genetically superior for breeding
- When you open the data platform, this is what you see. The highlighted countries have data on the system. Data on the platform is secure and only people who are authorized to get access to the data can view it.
- This platform is structured to capture data, analyze it and give feed back to farmers and other actors in the dairy value chain. This platforms in can interface with others in other parts of the world and can be expanded to support different livestock species
- Different actors can get very useful information for decision making from the platform. For example, for countries the livestock department can see what milk production looks like in the country and the breeds that are in use where
- You can filter the data by regions in the country or ward and can see number of farmers and animals registered, category of farmers, gender distribution, breed……etc The ministry for example can use these summaries for informed decision making
- This is a dashboard that was developed for one of our partners. So this is for NAIC, can see how semen is distributed in the country and the breed that is nost and least used for example, They can also monitor activities of inseminators to see how well they are performing……what is the rate of pregnancy for each inseminator…….and much more
- For farmers, they get feedback on how they are preforming relative to others in their region. Individuals preforming well within district can become champions for influencing other farmers on best practices for improved production. They also get information on the composition of the animals to help manage them appropriate to extract optimum benefit. What we see I the field is that an animal is called a HF but when we look at the DNA profile, it is a crossbred having many more breeds like in this picture. Also, farmers can receive alerts on their mobile devices in the event of an outbreak in their area like here, it says …..
- We have developed and constantly refining our selection index f
- Another thing that happens when you have data constantly coming into the platform is that you can begin to ask questions and get answers so here we were interested to know whether heatsess was affecting animals in tz in therms of producu=tion and we see that whe the weather becomes hot they mlk procutioon drops. So then we ask another question, can we breed animals that can witstand this stress and still keep producing without being disturbed and we see tha
- Developing this platform and providing all this information is a collective effort of many partners, many institutions and the dairy Farmers. Thank you to everybody who has contributed and enabled us to have data from all types of dairy farmers in Africa all in one portal.
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