ABI End of Initiative Status update / Progress Deep Dive Common Bean Mukankusi Clare • The following slide deck takes your crop breeding team through a series of questions, to focus our dialogue on the team’s 2022-2024 breeding achievements • Please add to each of these slides 1 to max 3 slides that supports/evidences/explains the answers. • “No progress” is a perfectly legitimate answer. We simply want to get a good picture where the crop is at. Better resourced crops are assumed to have made more progress. • We encourage the team to discuss successes and bottlenecks. • We will use the info for the 2022-2024 ABI Report. Introduction • We will share the crop-specific breeding strategy, which is the linkage between Breeding Pipelines, Target Product Profiles and Market Segments and Breeding Pipeline investments, as it is uploaded in the Breeding Portal. • During or after the meeting, please provide us with feedback in case it needs updating. • Three pipelines • Four regions (EA, SA, CAF, LAC) • 40+ countries ReFOCUS – Breeding Strategy Beans CIAT BP00013 Climbing Large sized; Medium sized Beans CIAT BP00012 Medium-large bush Beans CIAT BP00014 Small bush Common Bean Regional Market Segments Bred=eding pipeline Market segment Sub-Region Traits Total Ha targeted by pipeline Medium and large seeded bush beans adapted to the low and mid altitude areas (Andean) East Africa Must Have traits: High SeedFe, Fast cooking, High yield Value added traits: disease resistance to ALS, root rot, BCMV Anth resistance, Drought, Poor soil tolerance, Medium- early maturity, Canning quality, color retention, Bruchid and BSM resistance Burundi: 201,300; Ethiopia: 144,780; Kenya: 1,004,087; Rwanda: 192,281; Tanzania: 996,000; Uganda: 600,000; DRC: 385,611; Total: 3,524,059 Latin America and the Caribbean Colombia: 34,688; Ecuador: 9,602 Total: 46,202 Southern Africa Malawi: 322,448; Zambia: 91,000; Zimbabwe: 33,200; Mozambique: 69,073; RSA: 47,144; Madagascar: 32,000; Angola: 710,698: Total: 1,305,563 West Africa Cameroon: 199,563; Togo: 155,530: Total: 355,093 Climbing beans adapted to the mid and high-altitude areas (Andean and Meso) East Africa Burundi: 359,900; Ethiopia: 3,810; Kenya: 11,675; Rwanda: 302,988; Tanzania: 12,000; Uganda: 320,000; DRC: 19,043; Total: 1,029,416 Small seed bush beans adapted to low and mid altitudes with heat and drought tolerance (Andean) Latin America and the Caribbean Must have traits: Drought tolerance, High Fe and Zn content Value added traits: Bruchid and BSM resistance, heat tolerance, content poor soil tolerance, BCMV, Rust, CBB resistance, Canning quality Ecuador: 2,401; El Salvador: 110,679; Guatemala; 263,659; Haiti: 262,309; Honduras: 167,574; Mexico: 482,958; Nicaragua: 229,465, Venezuela: 61,632; Total: 1,721,881 East Africa Burundi: 18,300; Ethiopia: 224,790; Kenya: 40,864; Rwanda: 58,267; Tanzania: 12,000; Uganda: 30,000; DRC: 47,606; Total: 431,827 Southern Africa Malawi: 6,972; Zambia: 2,000; Zimbabwe: 6,000: Mozambique; 34,536; RSA: 11,860; Madagascar: 32,000; Angola: 133,256; Total: 226,624 West Africa Cameron: 15,351; Ghana: 126,953; Total: 142,304 MS Name Golden green Zebras Pink Cream Brown/Khaki White Countr y UGA TNZ UGA ETH UGA TNZ ETH UGA TNZ ETH UGA TNZ ETH UGA TNZ ETH Portion per ms 0.005 0.015 0.003 0.001 0.001 0.006 0.001 0.005 0.008 0.003 0.003 0.015 0.003 0.008 0.015 0.006 Ha 5,000 19,500 2,500 626 1,000 7,800 626 5,000 9,750 1,831 2,500 19,500 1,831 7,500 19,500 3,419 Large bush beans in AVISA (BMGF) supported countries MS Name Red Red mottled Yellow Sugar Kablanketi/purp le Country UGA TNZ ETH UGA TNZ ETH UGA TNZ ETH UGA TNZ ETH UGA TNZ Portion per ms 0.050 0.100 0.100 0.300 0.300 0.100 0.150 0.230 0.100 0.100 0.200 0.080 0.003 0.053 Ha 50,000 130,000 61,200 300,000 390,000 61,200 150,000 299,000 61,200 100,000 260,000 48,960 2,500 68,250 Tier system for key market segments and breeding effort, CIAT Partner Breeding pipeline Essential Traits Market segment Breeding Approach Tier system CIAT-Uganda Large/med bush CKT, SeedFE, SeedZn, yield Red mottled, Sugar, Red, White BRIO and SSD 1 Climbers White, black, redsSmall bush CIAT-Tanzania Large/med bush Yield, disease resistance Yellow , red mottled GS 1 CIAT-Chitedze Large Medium bush Yield, ALS, CBB, ND/SD Sugar, Red mottled SSD 1 CIAT- Colombia Large Medium bush Yield, ALS, CBB, ANTH, Red mottled, Reds, Sugars Bulk and mass selection 1 Climbers 1 Small bush Drought, Heat, SeedFe and SeedZn Reds, blacks 1 Possible Tier system for key market segments and breeding effort Partner Breeding pipeline Essential Traits Market segment Breeding Approach Tier system RAB-Burundi Large/medium bush Early maturity, yield, Iron & zinc content, disease resistance/tolerance, seed colour and size Red, red mottled, sugar, purple, purple mottled, black, yellow, mwezimoja, cream, white 1, 2, 3, 4 Climbers Small bush ISABU-Burundi Large med bush CKT, SeedFe, SeedZn Sugar, brown/Kaki, reds, red mottled and yellow N/A 4 Climbers KARLO-Kakamega Large/med bush Yield, disease resistance, CKT, SeedFe, SeedZn Red mottled 1, 2, 3, 4 Small bush Reds and blacks KARLO-Katumani Large/Med bush Drought, ALS, CBB, BCMV, CKT, SeedFe and SeedZn Sugar, red mottled, yellow, dark red kidney backcross and bulk 3 and 4 Small bush Drought, ALS, CBB, BCMV Reds and whites IIAM-Mozambique Large/Med bush Heat, drought, yield Red mottled, sugar 3 and 4 Small bush Blacks (niche) ZARI-Zambia Large/med bush ALS, CBB, Bruchid, Yield Sugar, Kablanketi, Red mottled 1, 2, 3, 4 DARS-Malawi Large/medium bush Drought, diseases, yield Red mottled, Sugar, large red 4 • Which of the Crop’s Target Product Profiles (TPPs) received the input or were reviewed and updated using any of the following, between 2022 to 2024, or before: • The input of a gender specialist? PABRA Agric economist (Enid Katungi) and Gender Specialist (Eileen Nchanji) reviewed the regional product profiles for Africa • Deliberately getting men and women perspectives? Yes in PABRA • Past studies that assessed gender disaggregated needs? YES • If not, what hindered the team to do so? ReFOCUS – Gender relevance • For which breeding pipelines is the team able to incorporate the genomic relationship matrix with phenotypic data to estimate genetic breeding value?: Medium , small and climbers for East Africa • For which traits?: Cooking time, Fe, Zn and yield • What benefit have been realized from doing so? • Understood the correlations between the traits and how we can use OCS in MatSel to overcome some of the negative correlations. Made good GG in reducing cooking time and moderate for SeedFe but negative with seed size • We are tracking seed color and seed size to inform crossing decisions for next cycles, We intend to test utility of seed colour markers (e.g. NDSU) in the program • If not, what hinders the team to use genomic information or derive benefits from doing so? Limited use due to resources ACCELERATE – Genomic selection • Over the past three years (2022-2024), has the team been successful in reducing cycle time? Yes • If so, how has this been achieved and what are current cycle times (in months)? 24 months • What are the biggest challenges to recycling from earlier stages (desirably the first stage) of field evaluation? • Phenotyping platforms not throughput as should be. • Inadequate seed amounts at early stage ACCELERATE – Cycle times BRIO R = rapid 2-year cycles of S0,2 family selection accumulating data analysis optimised crossing OCS Year Month J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D Cycle 2A begins Cycle 2B begins Cycle 3A begins GY, SW100 S0 progeny S0,1 and S0,2 seed increase & distribution Partner field trials SNP CKT, Fe, Zn GY, SW100 Founder 2 cycle 1 Crossing F1 x F1 SNP CKT, Fe, Zn GY, SW100 SNP CKT, Fe, Zn GY, SW100 SNP CKT, Fe, Zn 2024 2025 Founder 1 cycle 1 Crossing F1 x F1 2019 2020 2021 2022 2023 CKT, Fe, ZnSNP S0 progeny S0,1 and S0,2 seed increase & distribution GY, SW100 Partner field trials African bean panel (358 genotypes) 1800 high quality SNPs developed by Alliance-CIAT: - “common bean mid-density marker panel” https://excellenceinbreeding.org/toolbox/services/common-bean-mid-density-genotyping-services • Are all the crop’s pipelines dealing with closed breeding populations i.e., using only recycling of elite-by-elite? Not yet • The Mesoamerican bush pipeline is closest, however, some crosses are made using pre-breeding lines. For both the Andean bush and climbing pipelines breeding pipelines a minimum of two breeding cycles would be needed to close the population. • What proportion of breeding pipeline crosses are made with non-elite or other pipelines, and why? 5-10% • Mesoamerican Bush - 85 % were simple crosses (elite x elite) and 15 % were three-way crosses and double modified crosses. - Pyramiding genes or QTLs for biotic (BCMV, ALS, Anthracnose, etc) and/or abiotic stress (principally high mineral content and yield) in the same commercial grain type. • Andean Bush - 80 % of the total crossing block are made for pyramiding genes or QTLs for biotic or/and abiotic stress in the same commercial grain type; 20 % elite x elite • Andean Climber - 60 % of the crossing block was designed to pyramid genes or QTLs for biotic or/and abiotic stress in the same commercial grain type; 40 % elite x elite • For what traits and breeding pipelines is the team using back-crossing, parental lines derived from Trait Discover and Deployment, or other sources? • Heat (Saldaña) and yield under drought stress (Palmira) • Thrips resistance (M. Usitatus) - using different sources how P. acutifolius and interspecific lines. Strategy is using exotic germplasm and embryo rescue, combined with advanced backcrossing. ACCELERATE – Breeding populations • What measures has the team used, over the past 3 years, to improve the underlying quantitative genetics parameters of genetic gain: • Improve Heritability / reduce Error variance: Enhance quality of phenotyping infrastructure, refine experimental design, and acquire new machinery. This approach has contributed to the reduction of error variance, ultimately leading to more reliable estimations of parameters. • Increase Selection intensity • Increase Genetic variance: Using Optimal Contribution selection (OCS) • Increase Genetic correlation with the Target Population of Environments (A bit of climate modeling work, GxE, Early stage on farm testing) • Has the team used simulations to achieve the above? In progress. We have not yet employed simulations, however, we recognize the value of implementing advanced methodologies, such as Bayesian simulations, which could provide more predictive power and robustness in our decision-making processes. This is an area we are actively exploring for future integration. • Have such simulations be useful? No results yet • What challenges has the team experienced to improving quantitative genetics parameters? • primary challenges - uncontrollable environmental and biological factors (unpredictable weather patterns, crop diseases, and human error during data collection) • These external variables can introduce noise into the experiments and affect the precision of genetic parameter estimates. ACCELERATE – Breeding Schemes • What measures has the team used, over the past 3 years (2022-2024), to ensure breeding schemes are aligned with the Target Product Profile and farmers growing conditions? • Breeding schemes developed and are matched to the regional TPP’s • What proportion of essential TPP traits is the team able to capture during • Screening • Early testing • Late testing • On farm verification • … or has the team not assessed this? Proportion not yet assessed, ACCELERATE – Breeding Schemes • What farmer-managed (or farmer representative) trials has the crop breeding team done over the past year? • In collaborations with NARs, late stage farmer managed TRICOT and NARS managed OFT’s • At what Breeding stage: early, late, verification? • AYT/variety candidates and Early generation OnfarmGS TRICOT in Tanzania • Number of sites? 150-300 tricot plots per country, and >30 OFTS **Breeding pipelines? Large and medium seeded for East Africa, Large and medium seeded for southern Africa and small bush beans for EA. • Countries involved? Ethiopia, Uganda, Tanzania, Kenya, Burundi, Malawi, Rwanda, Zimbabwe and Zambia • Has gender disaggregated farmer-feedback been collected? To some extent in the OFTs, Good attention paid to gender farmer feedback in the ONFARM GS trials • What were the insights? Results pending ACCELERATE – On-Farm assessments • Is the team able to implement the recommended check strategy / spatial checks, benchmark checks / to measure realized genetic gains for farmer-relevant conditions? • Yes • If yes, where & how? In the PABRA regional trials and VEF trials mostly • We are able to replicate trials under various conditions. Most of our experiments are designed using a row-column layout to maximize spatial variability. In cases where a row- column design is not feasible, we implement alternative designs such as the alpha-lattice to maintain robust experimental conditions. • If not, why not? ACCELERATE – Assessing genetic gain Regional/Global Check strategy Breeding pipeline Market Segment Improve Traits Aim Connectivity check Benchmark check Medium and large seeded bush beans East Africa Southern Africa West Africa Latin America and the Caribbean Seed Iron content and bioavailability Increase content & bioavailability RWR2245 CAL96, Jesca, RWR2154 Cooking Time Faster cooking CAL96 NABE18, NABE20, UYOLE03, NUA683, SMC21, Yield At least equal or better CAL96 Red mottled: RWR2245, CAL96 Sugar: RWR2154, UYOLE 03 Yellow: KAT B1 Large red: RWR2075 Purple: JESCA Large White: SAB736 Climbing beans East Africa Seed Iron content and bioavailability Increase content & bioavailability MAC44 MAC44 Cooking Time Faster cooking MAC44 MAC44 Yield At least equal or better MAC44 Red mottled: MAC44 Whites: RWV3006 Small red: G2333 Large red: G13614, Decelaya Sugar: NABE12C Purple: RWV1129 Yellow: NAROBEAN5C Small seeded bush beans Latin America and the Caribbean East Africa Southern Africa West Africa Drought tolerance Increase tolerance SER16, DOR390, Tio Canela Red: SEF60, Tio Canela Black: SEN56 White: Seed Iron content and bioavailability Increase content and bioavailability DOR500, MIB465 (black), SMC33 (carioca) Black: SMN97 Red: SMR156 White: SMC16 Yield At least equal or better SER16, Small red: SCR15, SER125 Small black: SCN11 Small white: AWASH1, NABE6 (UBR) Check Strategy for PABRA 2023 regional trail at country-level defining the ruling varieties for each product Country Large Red Mottled Large Sugar Type Med Large Yellow Large Red Kidney Small Red Small White Blacks Purples /Kablanketi Large White Burundi Bush: Kaneza/RWR2245 Climber: Magorori/MAC44 Bush: Rufutamadeni/CODMLB003 Climber: Muhoro Bush: Akajone/IZO2015110 Climber: Rusenyanzego Bush: Kiryugaramye/RWR2091 Climber: Makutsapataro/IZO201543 Bush: M’sole Climber: NUV30 Ethiopia NUA 517 (Keye Bure Metene) Tafach/SAB 632 F10 B. sel new Bilfa 58 (Kello), KATB1 DAB96 (Zo ash) SER119, SER125 SCR15/Keyyo Awash 2, Bifort small seeded–15/ Awash Metin SCN11(Awas h Tikure) SAB736 (Ado Kenya Bush: GLP 2, Nyota/KAD02/DAB 299 Climbers: MAC34, MAC64 Bush: Angaza/KMR 11/NUA671, Embean14 Climbers: MAC12 Bush: KatB1 Bush: GLP 24, KatX56 Bush: GLP 585, Kat B9 (medium red) Bush: GLP 1127 (a), GLP 1004 Rwanda Bush: RWR3194 Climbers: MAC9, MBC23 Bush: RWR2154 Climbers: RWV3317 Bush: Colta Climbers: RWV2264 Climbers: RWV3316 Bush: BOA-1/16 Bush: SER16 Climbers: RWV2350-2B Climbers: RWV3006, CAB2 Tanzania Bush: Calima uyole, Lyamungo 90/ G5621 Climbers: Selian 14/MAC44, Selian 6/ Flodemayo Bush: Uyole 03 Bush: Njano Uyole, Selian13/KATB1 Bush: Selian 97/ LB842, Uyole 96 KATB9 (medium) RCB593 Bush: Jesca, Uyole 18 Bush: Uyole 17 Uganda Bush: NABE19 (Kidney shape), NAROBEAN2/RWR2245 (round) Climber: MAC44/ NAROBEAN4C Bush: RWR2154/NAROBEAN1 Climbers: NABE12C Bush: MOORE80082/NAROB EAN3 Climbers: Nyiramuhondo/NAROB EAN5C Bush: NABE14/RWR2075 Climber: NABE8C/Ngwinurare Bush: SCR 26/NAROBEAN 6 Climber: NABE 10C NABE6/UBR92 NAROBEAN7 /SCN11 Malawi Bush: CAL143, KALIMA Bush: SUG31 Bush: CAL143, PHALOMBE Bush: Teebus RR2, Kabalabala Zambia CAL143, MAC23, NUA45, CIM- ALS-FeZn 08-16-6 , CIM-ALS- FeZn 08-30-2, ZMBP/12/16-4 VTT923/10-3, CIM-SUG-2-LN48- 02, CIM-SUG05-01-02 OPS-KW1, SPS2-4P24 Zorro Zim Cherry, NUA45, Sweet Violet Sweet Violet/VTTT925/9/1/2, Gloria/PC552553, Speckled, Ice/SUG131 Bounty Canpsula, SMC16 • Over the past three years has the team be able to do a GxE analyses across years (> 2 years plus) to rationalize / improve your testing strategy? yes • Yes, we have conducted GxE analyses over the past three years If so, can you please share the results? To be shared by December, 2024 ACCELERATE – Testing strategy • Has the team used Bioflow? • For early testing? Yes, at Palmira we have integrated Bioflow into our early testing workflows. Not yet in Africa • For late testing? Yes, at Palmira Bioflow is also used during the later stages of testing. Analysis for Africa has been initiated • For on-farm verification? Not yet. • For genetic gains assessment? Yes, we have begun using Bioflow for our genetic gain assessments, specifically starting with the 2024 genetic gain report. • If so, could you please share the Multi-Trial Analysis Reports for the crop’s breeding pipelines and market segments? • Yes, we are in the process of compiling the 2024 report, and it will include comprehensive multi-trial analysis data for our breeding pipelines and market segments. Reports will be shared once finalized. • If not used, what hinders the team to use Bioflow? We have only just been introduced to it. Breeders in LAC and Africa will be using it before end of year. ACCELERATE – Data analyses • For which crossing, screening and testing stages is the team using fingerprinting for QA/QC? • For Africa, at F1 • For Palmira, QC markers have not been used routinely in the lab or in the program • If yes, what were insights? Able to remove selfs • If no, what hinders the team to do so? • In somecases the QC do now work well for the breeding materials • additional work is necessary to add more markers for better chromosome coverage, increasing power to distinguish genotypes ACCELERATE – Quality Control • Has the team established and documented the costs of breeding operations? • Africa, in process • Palmira - Yes, the team has established and documented the costs of breeding operations. We have tracked costs across different phases of the pre-breeding pipeline to develop genetic diversity and parental lines for crossing; including early-generation selection, field trials, seed multiplication, and data analysis. Incorporating marker-assisted selection, genotyping costs and development of prototype for process automation. • Different mechanisms are used, such as: - Cost-tracking tools: We use detailed Excel spreadsheets and cost management software to log direct and indirect expenses across the breeding cycle, from seed development to field trials. - Costing platforms (UQ costing tools & Trimble Ag): Software designed to calculate the cost of running a breeding activity, or an entire breeding pipeline operating at maximum capacity - cost and salaries - Collaboration with the business operations & finance team & the PMO (Program Management officer): works closely with the breeding department to ensure all costs are captured and categorized appropriately according to specific project pipelines. - Internal reviews and audits: Internal reviews and audits in the planning and request of field operations services to ensure that the recorded costs reflect actual expenditure and operational efficiency. • If so, for which pipelines? East and Southern Africa; and for all 3 breeding pipelines in Palmira • If so, after the meeting, can we get access to the results? Not ready but will be shared by December, 2024. ACCELERATE – Costing • Based on importance of crops and countries’/partners’ economic strength (low, lower middle, upper middle, high income), has the crop team rationalized network partners as Level 1, Level 2, Spill-over? Yes to some extent • If so, could you please provide the list? • If not, what has hindered you to make progress with this? TRANSFORM – Country and partner priorities Partner Assessments Level 1 Remarks Level 2 Tanzania (1) Apx 1.3 million (2) Partially develop new populations (TARI- Uyole) (3) Defined testing criteria Burundi 1) 940,931 ha under bean production (2) Do not develop new populations (3) partially defined testing criteria Uganda (1) Apx 1,000,000 ha. (2) Generate new populations (3) Defined testing criteria Zambia 1) Apx 100,00 ha (2) Generate new population (3) Well defined testing criteria Ethiopia (1) Apx 612,552.37 ha. (2) Generate new population (3) Well-defined testing criteria Zimbabwe (1) Less than 60,000 ha (2) Generate new populations (3) Well defined testing criteria Kenya (1) Apx 1,169,419ha (2) Partially developing new population (Kakamega) (2) Well defined testing criteria Rwanda (1) Apx 316,072 ha (2) Generate new population (3) Well defined testing criteria Mozambiq ue (1) Apx 800,00ha (2) Generate new population (3) Well defined testing criteria LAC (8 countries) 1) Apx `1.6M ha 2) Only Honduras creates new populations 3) Well defined testing criteria • For which countries has the crop team, during the past three years (2022-2024); i. Jointly defined/reviewed Market Segments and Target Product Profiles with partners? i. Uganda ii. Tanzania iii. Malawi iv. Ethiopia v. Mozambique vi. Kenya vii. Rwanda viii. Burundi ii. Jointly executed advancement meetings with partners? Adhocly; PABRA meeting annual but too large to make advancement decisions iii. Augmented roles of partners: if so, how? To some extent based on Tier system but not yet streamlined for NARS to be accountable iv. Increased resources to NARES: if so, to what extent or how? Not assessed as yet as PABRA initially provide adequate funding to some extent but partners were not adequately monitored TRANSFORM – Greater partner involvement • For which countries are descriptions of national TPPs available? i. Uganda ii. Tanzania iii. Malawi iv. Ethiopia v. Mozambique vi. Kenya vii. Rwanda viii. Burundi • Have they been uploaded into the Breeding Portal? No • If not, can we get access to upload them? Yes TRANSFORM – National TPPs ReORGANIZE What efforts have been made during the past three years to promote in the crop team: • Harmonized CGIAR stage terminology? Yes • Harmonized CGIAR stage gates? Yes • Harmonized CGIAR performance indicators? Not yet • Utilizing RACI’s to clarify responsibilities? To some extent What hindered the team to do so? Common stage gatefor common beans Stage and Gates Outputs Stage 1: Product design Target Product Profile (TPP): Detailing main traits and any potential trait discovery targets Stage Gate: Product Design to Trait Discovery Only required if a trait or traits need to achieve a specified target before crossing Stage Gate: Product Design to Crossing & Selection Stage 2: Trait Discovery Source germplasm and genetic variants: Identified Priority Traits, source germplasm lists, Data and knowledge on genetic variance knowledge, trait correlations and predictions), screening protocols Stage Gate Stage 3: Trait Deployment Semi Elite Donors: Semi-elite trait donors containing novel variation in demanded recurrent parent backgrounds, Data for breeding application including training adjustment for the crossing and screening team Stage Gate Stage 4: Crossing & Screening Experimental Products (Segregating populations; F1-F2): Individuals from populations that have anticipated higher breeding value defined by TPP, Data for training adjustment Stage Gate Stage 5: Early Testing Early Products (Early generation lines (fixed lines F5/F6): Lines with desired realized and predicted breeding value for TPP defined traits, Data for training adjustments Stage Gate Stage 6: Late testing Advanced Products and Candidate Varieties: Advanced generation germplasm (F7 and beyond) with desired breeding value and/or Candidate varieties selected for entry in wider OFT, Data for training adjustments, Estimates of genetic gains, Data on exotic allele advancement Stage Gate Stage 7a: On-Farm testing including PVS (Researcher and farmer managed) Candidate varieties: Candidate varieties selected for entry in Pre-commercial registration trials, estimates of genetic gains in farmers fields, Data on exotic allele advancement, farmer's feedback Stage Gate- to Seed systems Stage 8: Product Registration Registered Variety: Variety release, Demo's, EGS production, licensing DISCOVERY What efforts have been made during the past three years to: No progress (staff changes) Establish Return on Investment (RoI) and Likelihood of Success (LoS) of TD&D pipelines Take decisions to focus TD&D efforts on traits with higher RoI and LoS Use harmonized CGIAR performance indicators? Promote best practice approaches for TD&D? What hindered the team to do so? Other highlights or learnings? • What other 2022-2024 highlights are important to the crop team? • What other 2022-2024 learnings are important to the crop team? After the meeting - Summary Please ensure 1. You upload all 2022-2024 variety releases, made by partners or you, in the Breeding Portal If needed, please provide the update for: 2. The crop’s breeding strategy and/or annual breeding investments If available, please provide : 3. Available multi-year GxE analyses 4. Access to your Multi-Trial Analyses from Bioflow 5. Costing of breeding operations 6. National TPPs 7. Country prioritization: Level1, Level 2, Spill-over Thank You! Discussion & Questions Slide 0: ABI End of Initiative Status update / Progress Deep Dive Slide 1: Introduction Slide 2 Slide 3: Common Bean Regional Market Segments Slide 4 Slide 5: Tier system for key market segments and breeding effort, CIAT Slide 6: Possible Tier system for key market segments and breeding effort Slide 7: ReFOCUS – Gender relevance Slide 8: ACCELERATE – Genomic selection Slide 9: ACCELERATE – Cycle times Slide 10: BRIO R = rapid 2-year cycles of S0,2 family selection accumulating data analysis optimised crossing OCS Slide 11: ACCELERATE – Breeding populations Slide 12: ACCELERATE – Breeding Schemes Slide 13: ACCELERATE – Breeding Schemes Slide 14: ACCELERATE – On-Farm assessments Slide 15: ACCELERATE – Assessing genetic gain Slide 16: Regional/Global Check strategy Slide 17: Check Strategy for PABRA 2023 regional trail at country-level defining the ruling varieties for each product Slide 18: ACCELERATE – Testing strategy Slide 19: ACCELERATE – Data analyses Slide 20: ACCELERATE – Quality Control Slide 21: ACCELERATE – Costing Slide 22: TRANSFORM – Country and partner priorities Slide 23: Partner Assessments Slide 24: TRANSFORM – Greater partner involvement Slide 25: TRANSFORM – National TPPs Slide 26: ReORGANIZE Slide 27: Common stage gatefor common beans Slide 28: DISCOVERY Slide 29: Other highlights or learnings? Slide 30: After the meeting - Summary Slide 31